EGU General Assembly 2024  

Major efforts have been made in recent decades to decipher the climate of the past and its drivers with the help of proxy archives. Reconstructions of past climate variations are of immediate societal relevance because they serve as a baseline for anthropogenic climate change, and help us understand how past societies coped (or failed to cope) with extreme climate events. Good paleoclimatology, however, relies on ever more precise and accurate dates. While many proxy archives provide continuous year-by-year sequences going back many thousands of years, ambiguities in their interpretation introduce time uncertainty which increases over time. As a consequence, natural climate variability is underestimated when time-uncertain climate reconstructions are combined.

Through the use of "Miyake events" — novel time markers that are accurate to the year, globally distributed and detectable in different climate archives — it has recently become possible to better date and synchronize some of these climate archives, notably the polar ice-core records. The revised dating of ice cores from both Greenland and Antarctica combined with technological advances based on real-time continuous flow analysis techniques has shed new light on a prominent impact of volcanic eruptions on past climate and human societies. In this talk, I will highlight how we can date ancient eruptions, (sometimes to the season), geochemically identify their provenance and quantify their climate impact potential through emissions of sulfuric gases using large networks of ice cores. Case studies include prominent eruptions from Vesuvius or Santorini as well as eruptions largely unknown to the general public, for example from Alaska. I will discuss linkages to precisely dated proxies (e.g. tree-rings) and documentary records to demonstrate the accuracy of the new ice-core chronologies and to delineate climatic and societal responses to external shocks caused by major volcanic eruptions. In my concluding remarks, I will show how such lessons from the past can help to improve our understanding of past natural climate variability and to quantify global risks arising from volcanic activity in the future.

How to cite: Sigl, M.: A slice through time — securing timelines of past climate, global volcanism and human societies, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8168, https://doi.org/10.5194/egusphere-egu24-8168, 2024.

The Mid-Pleistocene Transition (MPT) is commonly characterized as a change in both temperature and ice volume from smaller amplitude, 41-kyr variability to higher amplitude, ~100-kyr variability in the absence of any significant change in orbital forcing. Here we reassess these characteristics based on our new reconstructions of changes in global mean surface temperature (DGMST) and global mean sea level over the last 2.5 Myr. Our reconstruction of DGMST includes an initial phase of long-term cooling through the early Pleistocene followed by a second phase of accelerated cooling during the MPT (1.5-0.9 Ma) that was accompanied by a transition from dominant 41-kyr low-amplitude periodicity to dominant ~100-kyr high-amplitude periodicity. Changes in rates of long-term cooling and variability are consistent with changes in the carbon cycle driven initially by geologic processes followed by additional changes during the MPT in the Southern Ocean carbon cycle. The spectrum of our sea-level reconstruction is dominated by 41-kyr variance until ~1.2 Ma with subsequent emergence of a ~100-kyr signal that, unlike global temperature, has nearly the same concentration of variance as the 41-kyr signal during this time. Moreover, our sea-level reconstruction is significantly different than all other reconstructions in showing fluctuations of large ice sheets throughout the Pleistocene as compared to a change from fluctuations in smaller to larger ice sheets during the MPT. We attribute their longer period variations after the MPT to modulation of obliquity forcing by the newly established low-frequency CO₂ variability. Specifically, prior to reaching their maximum size at the end of each ~100-kyr interval, ice-sheet response to periods of lower CO₂ was modulated by higher obliquity, and vice versa, with the times of maximum ice-sheet growth only occurring when low CO₂ combined with the next obliquity low. Ice sheets then began to melt in response to the next increase in obliquity, with the subsequent sequence of events and feedbacks leading to a termination. High-resolution ice-core CO₂ records that extend beyond 0.8 Ma are needed to test this hypothesis. Otherwise, large ice sheets shared a common size threshold throughout the Pleistocene equivalent to sea level below -80 m that, when exceeded, resulted in a termination that was paced by the next increase in obliquity.

How to cite: Clark, P. U., Shakun, J., Rosenthal, Y., Pollard, D., Köhler, P., Hostetler, S., Bartlein, P., Liu, Z., Zhu, C., Schrag, D., and Pisias, N.: A Revisionist View of the Mid-Pleistocene Transition, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3722, https://doi.org/10.5194/egusphere-egu24-3722, 2024.

Recent research has highlighted that radiative feedbacks — and thus climate sensitivity — are not constant in time but depend sensitively on sea surface temperature patterns. I will discuss three implications of this realization.

First, I will show how coupled climate models fail to reproduce observed surface warming patterns and global mean top of the atmosphere (TOA) radiation trends. I use large initial condition ensembles to compare observations to account for internal variability and model mean-state biases. For certain periods, not a single ensemble member can reproduce observed values of surface temperature trends and TOA radiation trends. Models which more greatly underestimate the observed local sensitivity of surface and TOA, and models with a weak variability in the Equatorial Pacific surface temperatures tend to have a higher equilibrium climate sensitivity. Despite these astonishing observation-model discrepancies their global-mean temperatures are simulated well which points to a common model problem in surface heat fluxes and ocean heat uptake.

Second, I will discuss the relevance of the pattern effect for climate change projections. Given that problems coupled models have in reproducing observed warming patterns, we should doubt their pattern evolution in projections. I will introduce “surface warming pattern storylines” starting from the observations and bridging to simulated future patterns in standard scenarios. I show that (CMIP) coupled climate models used ubiquitously for climate change projections underestimate the uncertainty of possible global-mean temperature evolutions due to their surface warming patterns throughout the 21st century.

Third, I will introduce how a feed-forward convolutional neural network (CNN) can be trained to learn the pattern effect and predict global-mean TOA radiation from surface warming patterns. I use explainable artificial intelligence methods to visualize and quantify that the CNN draws its predictive skill for physically meaningful reasons. Remarkably and different from traditional approaches, I can predict radiation under strong climate change from training the CNN on internal variability alone. This out-of-sample application works only when feedbacks are allowed to be non-linear or equivalent, changing in time, which is another, independent manifestation of the relevance of the pattern effect.

How to cite: Rugenstein, M.: The pattern effect: How radiative feedbacks depend on surface warming patterns and influence near-term projections , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12777, https://doi.org/10.5194/egusphere-egu24-12777, 2024.

Weather Compound Events (WCE), broadly defined as “the combination of multiple drivers and/or hazards that contributes to societal or environmental risk” [1], contribute to important societal impacts and widespread economical damages. However, the underlying mechanisms and complete storylines of these events are complex and not well understood yet.

In this study, we build an 25-year database of co-occurrent hot and dry compound events (HDCE) including heatwaves, droughts, dust storms and wildfires affecting Europe and the Mediterranean Basin from 2003 to 2020. based on Earth Observation exclusively. Individual natural hazards were systematically identified by a spatial and temporal matching algorithm applied on consistent ESA CCI Earth Observation datasets. The resulting individual natural hazard masks were then overlayed over Europe and permitted to identify regions simultaneously affected by two or more natural hazards on a daily basis. The climatology revealed HDCE hotspots among others in Northern Italy, Balkans and Caucasus regions.

Characteristics of HDCE such as their duration, intensity and spatial extension are stored in the database. HDCE could also be associated with a severity index to aid comparison across events.

Long-term statistics of the generated HDCE have shown a high interannual variability with HDCE being more frequent during the 5 last years rather than two decades ago.

The large-scale preconditions preceding and occurring during HDCE are investigated as well in this study and revealed systematic patterns in the atmospheric dynamics.

[1] Zscheischler, J., Martius, O., Westra, S., Bevacqua, E., Raymond, C., Horton, R.M., van den Hurk, B., AghaKouchak, A., Jézéquel, A., Mahecha, M.D. and Maraun, D., 2020. A typology of compound weather and climate events. Nature reviews earth & environment, 1(7), pp.333-347.

How to cite: Fluck, E.: A 25-year assessment of Hot and Dry Weather Compound Events in Europe using Earth Observation , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-109, https://doi.org/10.5194/egusphere-egu24-109, 2024.

In April 2023, the Western Mediterranean region was hit by an exceptional and unprecedented heatwave that broke several temperature records. In Cordoba (Spain), the previous April maximum temperature record was exceeded by almost 5ºC. In this study, we investigated the interaction between soil moisture and the extreme temperatures reached during this event, using the latest available observational data and several statistical techniques capable of quantifying this relationship. Our results revealed that soil moisture deficit preconditions, concurring with a strong subtropical ridge as a synoptic driver, had a key contribution to the amplification of this record-breaking heatwave. Specifically, we estimated that the most extreme temperature records would have been 4.53 times less likely and 2.19°C lower if the soils had been wet. These findings indicated that soil moisture content may be a crucial variable for seasonal forecasting of early HW in this region and other Mediterranean climate regimes that already suffering an increment in the frequency of compound drought–heatwave events. 

How to cite: Lemus-Canovas, M., Insua-Costa, D., Trigo, R. M., and Miralles, D. G.: Revealing the role of long-term drought in the record-shattering April 2023 heatwave in the Western Mediterranean, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-134, https://doi.org/10.5194/egusphere-egu24-134, 2024.

Attribution of compound events informs preparedness for emerging hazards. However, the task remains challenging because of complex space-time interactions amongst extremes, climate models’ deficiency in reproducing dynamics of various scales, and uncertainties in dynamic aspects of climate change. 
During June-July 2020, a historic flood hit the Yangtze River Valley and to its south the hottest summer since 1961 was observed, leading to disproportionate socioeconomic and environmental impacts to southern China. For attributing the recording-breaking spatially compounding event, we conduct a storyline attribution analysis by designing a series of simulation experiments via a weather forecast model, with large-scale dynamics equally constrained and thermodynamics of the climate system modified. We report that given the large-scale dynamic setup, anthropogenic influence has exacerbated the 2020 extreme Mei-yu rainfall by ~6.5% and warmed the southern co-occurring seasonal heat by ~1℃. The framework further details human influence on key elements to the two extremes individually and their coupling in space. If the same compound event unfolds in the 2090s, it is plausible to expect the monsoonal rainfall extremes ~14% wetter and the accompanying South China heat ~2.1°C warmer than observed.
This method opens an avenue for attribution of low-likelihood, dynamically-driven, spatially and temporally compounding events.

How to cite: Chen, Y.: Storyline attribution and projection of the 2020 spatially compounding flood-heat event in southern China, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-185, https://doi.org/10.5194/egusphere-egu24-185, 2024.

Extreme droughts and pluvials are recurrent natural hazards that often lead to disastrous socio-economic impacts. These hydroclimatic extremes are generally characterized by large-scale spatial-temporal patterns spanning thousands of kilometres with time-evolving features of expansion or shrinkage. The spatial-temporal dynamics of these hydroclimatic extremes can pose compound impacts across multiple locations. Understanding the propagation behaviour, including movement and propagation, is crucial for disaster response and mitigation. The spatial propagation dynamics of droughts/pluvials are inherently complex as they are often associated with and modulated by natural climate variability, such as El Niño-Southern Oscillation (ENSO), North Atlantic Oscillation (NAO), and atmospheric dynamics like Rossby waves. However, the specific influences of these drivers on the spatial propagation pathways of droughts and pluvials remain elusive. Here, we conduct a multi-layer complex network-based analysis to explore the interactions between drought/pluvial propagation pathways and potential modulating mechanisms with a focus on the conterminous United States. We first identify extreme drought and pluvial occurrences using self-calibrated Palmer Drought Severity Index (scPDSI) and Standardized Precipitation Index (SPI) during 1948–2016. We then apply event coincidence analysis (ECA) for all location pairs to construct fully-connected drought and pluvial complex networks, based on which we identify the spatial-temporal propagation pathways through community analysis. Subsequently, partial event coincidence analysis is carried out to elucidate the direct links from potential climate modulators (e.g., ENSO, NAO, and Rossby waves) to extreme event propagation. Our results provide insights into how climate variability and large-scale circulation patterns affect the spatial propagation of droughts and pluvials, offering valuable information for pre-emptive actions to mitigate remotely synchronized extreme events.

How to cite: Wang, H.-M. and He, X.: Lagged Synchronizations of Hydroclimatic Extremes and Their Propagation Dynamics Revealed by Complex Event Coincidence Networks, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-842, https://doi.org/10.5194/egusphere-egu24-842, 2024.

Natural hazards rarely occur in isolation. Frequently, one hazard triggers another, such as an earthquake triggering a tsunami. Likewise, the likelihood of a hazardous event can be amplified by the occurrence of a previous event, such as a drought amplifying the likelihood of a wildfire to occur. However, two extremes can also co-occur as a compound event, leading to even higher combined impacts.

While the field of compound events is advancing rapidly, studies often focus solely on climatic extremes occurring at the same time, excluding non-climate-related hazards or previous triggering and amplifying conditions. Therefore, this research aims to better understand the dependencies between different (pre-conditioning) hazard magnitudes, geographic features, and historic natural hazard footprints accounting for both climatic and geological hazards.

With the use of statistical tools, such as vine copulas, we model the relationships within two different hazard groups. The first group consists of drought, heatwave, and fuel indicators to calculate the risk of wildfires. The second group includes earthquakes, precipitation, and slope data to calculate the risk of landslides. While the first group is considered a compound event, the second group can be classified as a multi-hazard, with different triggering or amplifying relationships. For both groups, we attempt to use the same method to model stochastic events that include a potential hazard footprint for wildfires and landslides on a local to European scale. This model allows users to evaluate potential hazard combinations and footprints in their regions, enabling better preparedness for potential multi-hazard events.

How to cite: Claassen, J., Ward, P., Jäger, W., Koks, E., and de Ruiter, M.: A European Perspective on Joint Probabilities of Multi-Hazards, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-955, https://doi.org/10.5194/egusphere-egu24-955, 2024.

The emergency of global‐scale hydroclimatic extremes (i.e., meteorological droughts, extreme precipitations, heat waves and cold surges) and associated compound events has recently drawn much attention. A global‐scale unified and comprehensive event set with accurate information on spatiotemporal evolutions is necessary for better mechanism understanding and reliable predictions in sequential studies. Accordingly, this manuscript describes the first‐generation global event‐based database of hydroclimatic extremes produced with the newly proposed 3D (longitude–latitude–time) DBSCAN‐based workflow of event detection. The short name of this database is Glo3DHydroClimEventSet(v1.0) , which is obtained from the FigsharePlus webpage ( https://doi.org/10.25452/figshare.plus.23564517 ). The 1951–2022 ERA5‐based multiscale and multi‐threshold daily running datasets of precipitation and near‐surface air temperature are calculated and employed as the input data. A comprehensive event set of hydroclimate extremes is the output of the 3D DBSCAN‐based workflow. From perspectives of spatiotemporal evolutions, this event‐based database is also measured and attached with metric information. For case‐based validation, some recently reported hydroclimatic extremes (e.g., the 2020 summertime flood‐inducing Yangtze River extreme precipitation event) are employed and accurately detected in the Glo3DHydroClimEventSet(v1.0) database. Meanwhile, global‐scale spatiotemporal distributions are preliminarily analysed. For example, global‐scale event counts of extreme heatwaves displayed an increasing tendency since 2005, with a rapid increase after 2010. To sum up, this Glo3DHydroClimEventSet(v1.0) database may facilitate new scientific achievements concerning event‐based hydroclimatic extremes, especially in communities of atmosphere, hydrology, natural hazards and associated socioeconomics. The DOI-based linkage is  https://doi.org/10.1002/joc.8289 .

How to cite: Liu, Z. and Zhou, W.: Glo3DHydroClimEventSet(v1.0) : A global‐scale event set of hydroclimatic extremes detected with the 3D DBSCAN ‐based workflow (1951–2022), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2346, https://doi.org/10.5194/egusphere-egu24-2346, 2024.

This study investigates the coupled variability of temperature and precipitation in eastern China during summer using empirical orthogonal function (EOF) analysis to better understand and mitigate simultaneous occurrences of extreme events,such as compound droughts and heat waves. Two dominant modes are identified: the first exhibits a strong warming and drying trend in the region north of the Yangtze River, with the opposite occurring in the south; the second illustrates decadal oscillations in temperature and precipitation, alternating between cool-wet conditions and warm-dry conditions in southern China. The underlying mechanisms for these leading modes are revealed through correlation, composite analysis,and model simulations. The first mode is associated with a negative Pacific-Japan teleconnection in the lower atmosphere and a stationary Rossby wave train across Eurasia in the upper troposphere, which are influenced by global warming and sea surface temperature anomalies in the western North Atlantic. The second mode is linked to alternating active periods of the North Atlantic Oscillation (NAO) and Pacific Decadal Oscillation (PDO). The NAO exerts a significant influence on the summer climate in eastern China during its active phases, while the PDO shows an opposite effect when the NAO is less active. These findings provide valuable implications for long-term planning and adaptation strategies to better cope with compound extreme events in eastern China.

How to cite: Zhang, Y. and Zhou, W.: Long-term coupled variability of temperature and precipitationin eastern China and the underlying mechanisms, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2743, https://doi.org/10.5194/egusphere-egu24-2743, 2024.

Compound wind and precipitation extremes (CWPEs) can severely impact natural and socioeconomic systems. However, our understanding of CWPE future changes, drivers, and uncertainties under a warmer climate is limited. Here, analyzing the event both on oceans and landmasses via state-of-the-art climate model simulations, we reveal a poleward shift of CWPE occurrences by the late 21st century, with notable increases at latitudes exceeding 50° in both hemispheres and decreases in the subtropics around 25°. CWPE intensification occurs across approximately 90% of global landmasses, especially under a high-emission scenario. Most changes in CWPE frequency and intensity (about 70% and 80%, respectively) stem from changes in precipitation extremes. We further identify large uncertainties in CWPE changes, which can be understood at the regional level by considering climate model differences in trends of CWPE drivers. These results provide insights into understanding CWPE changes under a warmer climate, aiding robust regional adaptation strategy development.

How to cite: Li, D., Zscheischler, J., Chen, Y., Yin, B., Feng, J., Freund, M., Qi, J., Zhu, Y., and Bevacqua, E.: Intensification and Poleward Shift of Compound Wind and Precipitation Extremes in a Warmer Climate, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2962, https://doi.org/10.5194/egusphere-egu24-2962, 2024.

High impact events are often compound events with relevance for a wide range of societal sectors: Infrastructure and Urban Resilience, Agricultural Adaptation and Food Security, Public Health and Healthcare Preparedness, Insurance and Financial Risk Management, Energy Systems, Natural Systems, Globally interconnected Networks: Food Networks, Supply chains, transport systems.

 Consequently, compound events and associated physical risks have been prominently acknowledged in recent high-level reports such as the sixth assessment report of the IPCC, fifth US National Climate Assessment, numerous UNDRR briefing notes and the Risk report of the world economic forum among others.

Driven by the need to enhance our physical and statistical understanding of high impact climate events, compound event research has made substantial progress and has emerged as a new inter/trans/multi-disciplinary field of study over the past decade, bridging climate, environmental science as well as statistics and data science. To be fully usable for solving real world problems substantial challenges remain, these include lack of high-resolution data, model biases in tail risks, and impact relevant event definition. This talk will provide an overview of current challenges in accurately projecting and predicting risks from compound events for various societal sectors and points towards potential solutions to address these.

How to cite: Kornhuber, K.: Usable Compound Event Research, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3151, https://doi.org/10.5194/egusphere-egu24-3151, 2024.

Compound dry and hot extremes are proved to be the most damaging climatic stressor to wheat thereby with grave implications for food security, thus it is critical to systematically reveal their changes under unabated global warming. This study provides a comprehensive analysis of the changes in compound dry and hot days (CDHD) occurring within dynamic wheat growing seasons of 2015-2100 over dynamic wheat planting regions worldwide under SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5, including CDHD’s frequency and severity. This study sought to fill the gap in knowledge by identifying the CDHD occurring within dynamic wheat growing seasons, clarifying the correlations between droughts and heats as well as their impacts on CDHD, and revealing the driven mechanism of global warming for the increase of CDHD.

Our results demonstrate a notable increase in CDHD’s frequency and severity worldwide under all SSPs, such increase is sharper over southern Asia in winter wheat growing season, and southern Canada, northern America, Ukraine, Turkey and northern Kazakhstan in spring wheat growing season. As the top 10 wheat producer, India and America will suffer much more detrimental CDHD in their wheat growing season. Adopting a low forcing pathway will mitigate CDHD risks in up to 93.3% of wheat areas. Positive dependence between droughts and heats in wheat growing season is found over more than 74.2% of wheat areas, which will effectively promote the frequency and severity of CDHD. Global warming will dominate the increase of CDHD directly by increasing hot days and indirectly by enhancing potential evapotranspiration thereby aggravating droughts. This study helps to optimize adaptation strategies for mitigating CDHD risks on wheat production, and provides new insights and analysis paradigm for investigating future variations in compound extremes occurring within dynamic crops growing seasons.

How to cite: He, Y., Zhao, Y., Duan, Y., Hu, X., and Shi, P.: Global Warming Determines Future Increase in Compound Dry and Hot Days within Wheat Growing Seasons Worldwide, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3395, https://doi.org/10.5194/egusphere-egu24-3395, 2024.

Droughts and floods, as individual hazards, pose significant challenges, but their consecutive occurrence can trigger catastrophic cascades of disasters. Therefore, it is crucial to understand these extreme events, known as drought-pluvial (DPAT) and pluvial-drought abrupt transitions (PDAT), to mitigate their risks and potential impacts effectively. Our study utilizes historical records spanning from 1940 to 2022 to identify DPAT and PDAT events, investigating their frequencies, durations, intensities, and underlying causes. Additionally, we analyzed the frequency, duration, and intensity of these events under projected future scenarios. Globally, there has been an increasing trend in the frequency of DPAT and PDAT events, with significant upticks observed in Eastern North America, South Asia, East Asia, the Middle East, Africa, and Australia. In the 2010s, these disasters impacted over 100 million people, predominantly in less economically developed countries. Our findings enhance the current understanding of DPAT and PDAT, thereby contributing to the development of more effective mitigation and adaptation strategies against their impacts.

How to cite: Yang, Y., Lu, X., and Xiao, X.: Abrupt transitions between drought and pluvial events becoming more widespread and intense, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3689, https://doi.org/10.5194/egusphere-egu24-3689, 2024.

Attribution of high-impact weather events to anthropogenic climate change is important for disentangling long-term trends from natural variability and estimating potential future impacts. Up to this point, most attribution studies have focused on univariate drivers, despite the fact that many impacts are related to multiple compounding weather and climate drivers. For instance, co-occurring climate extremes in neighbouring regions can lead to very large combined impacts. Yet, attribution of spatially compounding events with different hazards poses a great challenge. Here, we present a comprehensive framework for compound event attribution to disentangle the effects of natural variability and anthropogenic climate change on the event. Taking the 2020 spatially compounding heavy precipitation and heatwave event in China as a showcase, we find that the respective dynamic and thermodynamic contributions to the intensity of this event are 51% (35–67%) and 39% (18–59%), and anthropogenic climate change has increased the occurrence probability of similar events at least 10-fold. We estimate that compared to the current climate, such events will become 10 times and 14 times more likely until the middle and end of the 21^st century, respectively, under a high-emissions scenario. This increase in likelihood can be substantially reduced (to seven times more likely) under a low-emissions scenario. Our study demonstrates the effect of anthropogenic climate change on high-impact compound extreme events and highlights the urgent need to reduce greenhouse gas emissions.

How to cite: Qian, C., Ye, Y., Bevacqua, E., and Zscheischler, J.: Human influences on spatially compounding flooding and heatwave events in China and future increasing risks, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4229, https://doi.org/10.5194/egusphere-egu24-4229, 2024.

This study focuses on a new compounding concern, the sudden turn from drought to flood (STDF), that is becoming increasingly prominent. Droughts usually end due to increased precipitation, but if excessive rainfall occurs, it can lead to secondary impacts on already barren land, increasing the likelihood of landslides and making farmland flooding significantly costlier than it would have been if only flooding had occurred. Therefore, we must pay more attention to compound disasters that increase the vulnerability of populations and ecosystems. Most studies on rapid drought-to-flood transitions have analyzed individual cases, whereas few have studied the STDF characteristics in China or even globally or the long-term changes in the STDF trend. In this study, we selected an STDF screening method that is accurate on a daily scale.

In this study we calculated the SPEI on a 1-month scale, sliding a 30-day window in order to obtain the SPEI values for each day. Second, we used a relative threshold rather than an absolute threshold to define a flood in consideration of regional precipitation differences. A definition of STDF as follows:

,where t_o is the drought start time, t_d is the drought end time, and t_p is the time when flooding starts. Here, a drought is said to have occurred when the SPEI ≤-0.5 for more than 40 consecutive days. Our reference method considers drought duration to be more than 20 days, which is based on the persistence of the drought. And the main reason for our choice of 40 days is mainly to exclude the effect of flash droughts, although that type of event proved not to have a significant impact on our results in the subsequent discussion. PREt represents the t-d precipitation (for example, t=3, PRE3 is the 3d cumulative precipitation), when PREt is greater than the 99.5th (for PRE3)/99.3th (for PRE5)/98.7th (for PRE10) percentile precipitation for each reference period (1961-2020) as the flood threshold. (Based on the natural disasters released by the Emergency Management Department and the China’s Yearbook of Meteorological Disasters , 234 floods events were obtained for the period of 2010-2020, and so a threshold of 99.5th, 99.3th, and 98.7th percentile (corresponding to 3d/5d/10d continuous precipitation) was determined for their ranking in the rainfall series from 1961 to 2020.)

The results show that STDFs have been increasing more frequently in China at a rate of average 2.8 events per decade. The most significant increases occurred in May and June, resulting in an advance of one month for the STDF peak. The STDF hotspots are concentrated in north and northeast China and YRD. Nearly 35% of droughts in northern and northeast China have been immediately followed by a flood rather than a gradual drought mitigation or a drought alone. STDFs have become more prevalent in northern China as a result of increased flood frequency and precipitation volatility, while in southern China, the increase in STDF frequency is primarily due to an increase in drought frequency.

How to cite: Wang, H., Wang, S., Shu, X., He, Y., and Huang, J.: Increasing occurrence of sudden turns from drought to flood over China, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4582, https://doi.org/10.5194/egusphere-egu24-4582, 2024.

In the context of global climate change, extreme climate events are becoming increasingly frequent.  Extreme climate events constitute major risks to global food security. The simultaneous occurrence of multiple extreme climate events may have a much greater impact than individual extreme events in isolation. Here we quantitatively analyzed the impact of individual and combined extreme climate indices, including cold days (CD), warm degree days (WDD), precipitation, and compound hot – windy - dry (HWD), on the yields of three major crops (winter wheat, soybeans, and maize) globally by establishing a linear mixed-effects model. CD, HWD, and WDD are identified as the most significant driving factors causing yield losses in winter wheat, soybeans, and maize, respectively. During the planting to the jointing stage, per 10 days of CD account for a 3.2% reduction in winter wheat yield. During the jointing to heading stage, per 10 h of HWD and per 10 °C day-1 WDD result in a 7.5% reduction in soybean yield and a 2.7% reduction in maize yield, respectively. We quantified "yield shocks" and found that the regions experiencing yield shocks exhibit a similar spatial distribution to extreme climate indices. These extreme climate indices are likely to be the driving factors behind yield shocks for the three crops. Our findings indicate that multiple individual extreme climate factors, as well as compound heat-drought-wind (HDW) indices that have been overlooked in traditional risk assessments, impact the yield of the three major crops globally.

How to cite: kun, X. and Xin, Q. C. X.: Investigate the Effects of Compound Extreme Climate Events on Global  crop Yield from 1982 to 2016, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4843, https://doi.org/10.5194/egusphere-egu24-4843, 2024.

When different flooding drivers co-occur, they can cause compound floods. Despite the potential impact of compound flooding, few studies have projected how the joint probability of flooding drivers may change. Furthermore, existing projections are based on only 5 to 6 climate model simulations because flooding drivers such as storm surges and river run-off need to be simulated offline using computationally expensive hydrodynamic and hydrological models. Here, we use a large ensemble of simulations from the Coupled Model Intercomparison Project 6 to project changes in the joint probability of extreme storm surges and precipitation in Europe under a medium and high emissions scenario. To compute storm surges for so many simulations, we apply a statistical storm surge model trained with tide gauge observations and atmospheric forcing from the ERA5 reanalysis. We find that the joint probability of extreme storm surges and precipitation will increase in the northwest and decrease in most of the southwest of Europe. On average, the absolute magnitude of these changes is 36% to 49% by 2080, depending on the scenario. We show that due to internal climate variability and inter-model differences, projections based on small climate model ensembles can differ qualitatively depending on the specific simulations included. Therefore, our results provide a more robust and less uncertain representation of changes in the potential for compound flooding in Europe than previous projections.

How to cite: Hermans, T., Busecke, J., Wahl, T., Malagón-Santos, V., Tadesse, M., Jane, R., and van de Wal, R.: Projecting Changes in the Drivers of Compound Flooding in Europe Using CMIP6 Models, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5030, https://doi.org/10.5194/egusphere-egu24-5030, 2024.

Recent wildfire seasons broke records in terms of severity and damage in different regions of the world, e.g. in California in 2021 and in Southern Europe in 2022. The  probability of such severe and large wildfires is enhanced by compounding meteorological conditions of hot, dry and windy weather, which lead to dry fuels supporting the spread of fires. Drivers of low-frequency but high-impact fire events operate on different spatio-temporal scales and are difficult to identify with classical regression methods. Here, we use causal inference methods to describe the relationships between different variables driving fires and quantify their effect on the occurrence of fire events. We examine hydro-meteorological and land-surface drivers of wildfires in different European climate regions by leveraging ESAs’ FireCCI burnt area product together with CERRA reanalysis data from 2002 to 2022. Our results show region-specific patterns of the different variables prior to the wildfire events, which allow us to identify different wildfire pre-condition types. Highlighting the spatial variability of different wildfire drivers in various climate regions of Europe provides valuable insights for the development of targeted fire prevention measures and management. 

How to cite: Miller, J., Macakova, M., Touma, D., and Brunner, M.: Compounding preconditions leading to wildfires differ across European climate regions, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5210, https://doi.org/10.5194/egusphere-egu24-5210, 2024.

Hot extremes impose severe effects on human health and the ecosystem, especially when high-temperature extremes sequentially occur in both daytime and nighttime within 1 day, known as Compound Hot Extremes (CHEs). Although a number of studies have focused on independent hot extremes, not enough work is devoted to compound ones, not to mention the coupling strength in covariations between the two variables (daytime and nighttime temperature: Tmax and Tmin) over a given region. The instantaneous coupling strength can be derived by Dynamical System (DS) approach from covariations between Tmax and Tmin over a given region, and used to classify CHEs into coupled and decoupled types. Results show that coupled CHEs tend to be more intense with prolonged duration and extensive spatial extent compared with decoupled CHEs. Also, the mechanisms behind these two types of CHEs are largely different. Coupled CHEs are accompanied by a significant intensification and westward extension of the western North Pacific subtropical high (WNPSH), and the extremely high-temperature is mainly caused by receiving more solar radiation under the corresponding anticyclone. It is found that barotropic structure, weak jet stream and developing La Niña are conducive to the enhancement and persistence of WNPSH, in favor of the occurrence of long-lasting CHEs. Decoupled CHEs are associated with strong sea-land breeze (SLB), whose diurnal cycle could weaken the persistent large-scale circulation and suppress covariations between Tmax and Tmin. This kind of decoupled hot extremes are attributed to the combined effect of receiving more solar radiation during the day and trapping more long-wave radiation at night, where moisture and cloud cover play an important role.

How to cite: Guo, Y. and Fu, Z.: Regional coupled and decoupled day-night compound hot extremes over the mid-lower reaches of the Yangtze River: characteristics and mechanisms, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5420, https://doi.org/10.5194/egusphere-egu24-5420, 2024.

The increasing frequency and severity of climate extremes pose a multifaceted threat to health, economic stability, and both natural and human-made environments. Potential overlap and accumulation of extremes as compound extremes poses further challenges. Ongoing climate change intensifies these challenges, underscoring the importance of a better understanding of the causes and drivers for compound events. Earth system model projections suggest that more frequent climatic compound extremes affect terrestrial biosphere fluxes, potentially reducing the land’s CO₂ storage potential. However, whether models are able to represent such interactions like the priming of the biosphere towards extremes accurately remains to be shown.

Here, we focus on the role of concurrent precipitation and temperature as drivers of biosphere flux extremes and investigate their change in frequency and intensity based on their occurrence in historical simulations, reanalyses, and future projections. We use thresholds to define concurrent extremes and Monte Carlo randomization to constrain uncertainties. Further, we examine the association of climatic compound events with anomalies in biosphere carbon fluxes to ascertain their mutual relation, aiming to establish how these climatic compound events contribute to preconditioning extremes in the biosphere. Given this assessment of the occurrence change of climatic compound events and their connection to extremes in biosphere carbon fluxes, we infer how climatic compound events may precondition the biosphere for extremes. Lagged overlaps show significant seasonality and spatial heterogeneity in preconditioning. Comparing reanalyses and historical simulations in a model of the terrestrial carbon cycle and a comprehensive Earth System Model, we examine how well primed biosphere extremes agree in different data sources. Leveraging these findings, we evaluate if model projections show signs of stronger climatic priming of the biosphere in the next century.

How to cite: Riebandt, B., Adam, M., Ziegler, E., and Rehfeld, K.: Preconditioned biosphere flux extremes in terrestrial carbon cycle models and reanalyses in the recent past, present, and future, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5617, https://doi.org/10.5194/egusphere-egu24-5617, 2024.

Compound extreme weather events (CE), characterized by the concurrent influence of multiple weather and climate drivers, have the potential to exacerbate the concentration of air pollution on the atmosphere. Attributing specific extreme weather events directly to climate change is challenging; however, it is widely acknowledged that climate change will intensify different extreme events by changing their frequency, intensity, spatial extent, duration, and timing. Several types of weather extremes, such as stagnation conditions and heatwaves (HW), can lead to hazardous air quality situations by allowing some pollutants, such as ozone (O3), to accumulate and persist in the near-surface environment. O3 is in general more pronounced in the summer due to the photochemical nature of the source. Given its highly heterogeneous distribution across both space and time, combined with a relatively short life-time, it becomes imperative to gain insights into the patterns governing the global spatial data distribution related to this complex phenomenon. This study aims to evaluate the amplifying effects of CE (concurrence of stagnation and heatwaves) on O₃ peak levels globally during the summer season.

The study utilizes the simulations of historical 1980-2009) and future (2050-2079) climate under the Shared Socio-economic Pathways (SSP) SSP2-4.5 and SSP5-8.5. Using a model from the Coupled Model Intercomparison Project Phase 6 (CMIP6), the investigation explores the global temporo-spatial trends and disparities in compound-event occurrences across countries.

We find that O₃ concentrations during the summer are higher in the center of North America and the center of the Asian continent compare with the other parts in the world (surpassing the 85 pbb during summer). A significant disparity in ozone concentrations was observed between the SSP2-4.5 and SSP5-8.5 scenarios. The SSP5-8.5 scenario demonstrates notably higher concentrations of peak O₃ compared to the historical period, with increase of up to 20 ppb in certain regions, such as the Asian continent. Furthermore, it is noteworthy that O₃ concentrations are expected to decrease in the future in the central part of North America in both scenarios up to 15 ppb during the summer season.

Focusing on CE throughout the summer season and under all scenarios studied, elevated O₃ concentrations are observed worldwide during CE compared to non-event conditions, particularly during heatwaves, with an increase of 40, 35 and 40 ppb during summer in the historical, SSP2-4.5 and SSP5-8.5 scenarios in comparison with non-event conditions. These heatwave events generally dominate the formation of O₃ peak concentrations during CE.

Comparatively, during stagnation events, the highest peak O₃ concentrations undergo a substantial increase in the mid-to-late century scenario, notably in the Asian continent, with a projected increase of nearly 12% in O₃ for the SSP2-4.5 scenario and a 25% increase for the SSP5-8.5 scenario. Conversely, during combined heatwave and stagnation events in the SSP2-4.5 scenario, a decrease in average concentrations is expected in the future across all continents.

These results underscore the imperative need to further mitigate air pollutant emissions during weather extremes to minimize the adverse impacts of these events on air quality and human health.

How to cite: Jimenez-Guerrero, P., Cvijanovic, I., Rodó, X., and Tarín-Carrasco, P.: Compound events increase the ground-level tropospheric ozone concentrations worldwide., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5986, https://doi.org/10.5194/egusphere-egu24-5986, 2024.

Austral Chile, characterized by its intricate topography of small islands, channels, and fiords, relies heavily on navigation for local economic activities, security, and societal functions. Wind-related hazards pose a significant safety threat to navigation, with the complex topography exerting a profound influence on local wind patterns. This study undertakes a comprehensive examination of large-scale winds in the region as an initial step toward understanding the intricate dynamics of local wind systems. This study is part of a larger research project that aims to produce a very high-resolution wind forecasting system, based on the downscaling of WRF simulations by using Deep learning techniques (SiVAR-Austral, funded by ANID ID22I10206).

Utilizing 50 years of ERA 5 reanalysis daily wind fields, we employ a self-organizing map (SOM) approach, with four distinct SOMs corresponding to each season, to unveil seasonal wind patterns. Furthermore, a cluster algorithm is applied to establish relationships between these patterns, elucidating the various stages of synoptic conditions associated with different wind patterns. Through an in-depth analysis, we explore the frequencies of these patterns across different decades, providing insights into their temporal evolution.

Our findings reveal the complex interplay between the region's topography and wind patterns, offering a better understanding of the seasonal variations in large-scale winds. The identification of distinct synoptic conditions associated with specific wind patterns enhances our ability to predict and mitigate navigation-related safety threats. Additionally, the temporal evolution of these patterns across decades contributes valuable information for long-term planning and risk assessment. This research lays the foundation for a more robust comprehension of wind dynamics in Austral Chile, with potential applications in enhancing navigation safety protocols and supporting sustainable coastal development.

How to cite: Cordova, A. M., Andrade, P., Pozo, D., Bozkurt, D., and Arevalo, J.: Temporal Analysis of Large-Scale Winds in Austral Chile, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6635, https://doi.org/10.5194/egusphere-egu24-6635, 2024.

Simultaneous occurrences of multiple heatwaves or cold spells in remote geographical regions have drawn considerable attention in the literature, due to their potentially far-reaching impacts. These include widespread crop failures, increased mortality, wildfires, power supply disruptions and more. We introduce a flexible toolbox to identify and study such concurrent temperature extremes, with adjustable parameters that different users can tailor to their specific needs and impacts of interest. We then use the toolbox to present a climatological analysis of concurrent heatwaves and cold spells in the global midlatitudes. Specific geographical areas, such as Western Russia, Central Europe, Southwestern Eurasia and Western North America, emerge as hotspots for concurrent temperature extremes. Concurrent heatwaves are becoming more frequent, longer-lasting and more extended in the Northern Hemisphere, while the opposite holds for concurrent cold spells. Concurrent heatwaves in the Southern Hemisphere are comparatively rare. However, their sharp increase in recent decades means that they are becoming an emerging hazard in the Southern midlatitudes. Notably, trends in concurrent temperature extremes are significantly stronger than the corresponding trends in all temperature extremes. This suggests that concurrent heatwaves will be an increasingly important climatic hazard in both absolute and relative terms in a future, warmer, climate.

How to cite: Segalini, A., Messori, G., and Ramos, A. M.: Climatology and Trends in Concurrent Temperature Extremes in the Global Extratropics, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7651, https://doi.org/10.5194/egusphere-egu24-7651, 2024.

The Indian coastline, flanked by the Bay of Bengal and the Arabian Sea, is prone to the impact of intense low-pressure systems, specifically tropical cyclones and monsoon depressions and lows, which are accompanied by extreme rainfall and storm surges. The vulnerability of the Indian coastline to compound flooding, characterized by concurrent occurrence of extreme rainfall with extreme storm surge (SS-RF) or extreme rainfall with extreme sea level (SL-RF), poses a significant challenge in the face of changing climatic conditions. Analysing the past changes in the characteristics of compound flood events is essential to understanding the changing flood risks associated with concurrent extremes along the Indian coastline. This study utilises hourly sea level data from 8 tide gauge stations operated by Survey of India and daily rainfall data at those stations prepared from 0.25° gridded rainfall product of the India Meteorological Department (IMD). The skew surge time series corresponding to the stations are prepared by harmonic analysis of sea level data, and daily maxima of the time series which represent storm surge are analyzed. The concurrent extremes are identified as events where extremes of rainfall, sea level, and skew surge exceeded their respective 95th percentile thresholds concurrently. Our findings reveal distinct seasonal patterns, with higher occurrences of extreme sea level-rainfall (SL-RF) and extreme storm surge-rainfall (SS-RF) events during the summer monsoon (June to September) and post-monsoon (October to December) seasons along the east coast. Conversely, along the west coast, there are negligible SL-RF events throughout the year and the SS-RF events are clustered in the summer monsoon season only. The variability in frequency and intensity of concurrent extremes is higher in the post-monsoon than in the summer monsoon season along the east coast. The interannual variability of compound extremes on the east coast is primarily influenced by the El Niño Southern Oscillation (ENSO). During El Niño conditions, a decreasing trend in the frequency and intensity of concurrent extremes is observed, while La Niña conditions contribute to an increasing trend. ENSO impact also extends to the frequency and intensity of tropical cyclones during the post-monsoon season, also contributing to the interannual variability of concurrent extremes. The findings underscore the complex dynamics of the compound flood risk along the Indian coastline and provide valuable insights for assessing and managing flood risk under changing climate.

Figure 1: The number of compound extremes witnessed at typical locations along the east-coast of India during (a) the summer monsoon (JJAS) and (b) post-monsoon (OND) seasons. The El Nino and La Nina composite of the frequency of compound extremes are plotted for JJAS in (c), (d) and for OND in (e), (f).

How to cite: Dutta, D., Srinivas, V. V., and Bala, G.: Characteristics of compound flooding along the Indian coastline: Seasonal and interannual variability, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8078, https://doi.org/10.5194/egusphere-egu24-8078, 2024.

Many studies have shown that compounding extreme events are likely to exacerbate socio-economic risks compared to single extremes. Despite this important fact, studies focussing on the connectivity of extreme events and their associated impacts frequently have some shortcomings. First, extreme events such as droughts and heat waves are often predefined through thresholds, restricting the class of meteorological events leading to the observed impacts. The choice of threshold for defining these extreme events is also often of meteorological and/or statistical nature and thus potentially unsuitable for the holistic identification of the associated impacts. Furthermore, impacts can arise from combinations of non-extreme events that might fall short of the threshold-based identification, thereby limiting the ability to account for key dynamics that determine the risk associated with compound events. Our study aims to overcome those shortcomings by linking climate events with their observed impacts in agriculture. We analyse wet and warm late winters followed by dry and hot springs, and the associated agricultural damages in Europe with the aim of reconstructing these compound events based on the observed impact. A first analysis is conducted for winter wheat impacts in France, the largest European winter wheat producer. We identify agro-climatic zones based on multivariate time series clustering and employ a regularized generalized canonical correlation analysis to identify the large-scale drivers of crop variability for these regions. The patterns that emerge from the analysis are characterized by wet and warm conditions in January and February linked to a positive North Atlantic Oscillation (NAO) state, followed by warm and dry conditions in April induced by a tripole with a blocking high over Central Europe. Using imbalanced random forests, we construct objective bounds and define thresholds to identify which temperatures are warm enough or which water balances are low enough to be associated with significant effect on crop yield reduction. Our results indicate that imbalanced random forests can predict these types of events reasonably well at the local scale, and that the derived thresholds are mostly lower than the commonly used thresholds for detecting similar extreme events. The latter illustrates that the combination of non-extreme climate events can indeed be detrimental to agricultural production in Europe, which is also crucial as the analysed types of events are predicted to occur more often in the future as a result of climate change. 

How to cite: Luther, N., Essenfelder, A. H., Ceglar, A., Toreti, A., Vlachopoulos, O., and Xoplaki, E.: Reconstructing compound events from crop variability in Europe, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8594, https://doi.org/10.5194/egusphere-egu24-8594, 2024.

Landslides are impactful and complex natural hazards, causing important damages in vulnerable areas. They can be related to several pre-existing conditions and triggering factors. The former are variables that do not directly cause the event but that increase its likelihood in the presence of a triggering variable. Example of the former are the slope or the aspect, of the latter precipitation, earthquakes, snowmelt, or human disturbances. Among the triggering factors the most important is rainfall. Usually deep-seated movement, characterized by a slip surface deeper than 1.5 m, are related to repeated moderate precipitation episodes while shallow landslides, characterized by a slip surface less deep than 1.5 m, to single and more intense episodes. Landslide detection is usually performed with the use of precipitation thresholds, either process-based or empirical ones. Here we introduce a new methodology to detect landslides based on temporal clustering of precipitation. Temporal clustering is a particular typology of compound event falling inside the category of temporal compounding events and it is defined as the occurrence of multiple events of the same type in close succession. The new method is compared with the use of empirical rainfall threhsolds considering as case study two landslide inventories in the Lisbon region, Portugal. The method shows a better sensitivity with respect to empirical rainfall thresholds and a performance in terms of precision variable dependending on the site. In general, the detection of deep landslides is better than of shallow landslide. The method requires only precipitation data and the selection of a precipitation quantile to identify events and it could help to improve the detection of rainfall-triggered landslides.

How to cite: Banfi, F., Bevacqua, E., Rivoire, P., Oliveira, S. C., Pinto, J. G., Ramos, A. M., and De Michele, C.: Temporal clustering of rainfall for landslides detection, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9036, https://doi.org/10.5194/egusphere-egu24-9036, 2024.

Climate change is expected to increase the frequency and intensity of compound hot-dry events, which can have significant impacts on human life, economic systems, and agriculture. The extent of this impact depends on the socioeconomic pathway we adopt in the future. While sustainable development aspires to reconcile economic growth, environmental protection, and social equity, thereby ensuring a more sustainable future for all, fossil-fueled development may drive economic growth at the expense of exacerbating climate change, pollution, and resource depletion. This study employs a CMIP6 multi-model ensemble to scrutinize the global-scale potential for mitigating climate change impacts on compound hot-dry events under sustainable development versus fossil-fueled development. These events are quantified by analyzing the joint distribution probability between temperature and soil moisture extremes through bivariate copula functions. The results show that although the likelihood of compound hot-dry events is expected to increase under both scenarios, the increase under fossil-fueled development is anticipated to be twice larger than that under sustainable development. The results show that although the likelihood of compound hot-dry events is expected to increase under both scenarios, the increase under fossil-fueled development is anticipated to be twice as large as that under sustainable development. The mitigated impact through sustainable development is not regionally uniform, with the largest mitigation, up to one-third, expected in the Mediterranean region.

How to cite: Hosseinzadehtalaei, P., Termonia, P., and Tabari, H.: Avoided impacts of climate change on compound hot-dry events under sustainable development versus fossil-fueled development, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9167, https://doi.org/10.5194/egusphere-egu24-9167, 2024.

Brazil’s Pantanal wetland is one of the most threatened Brazilian ecosystems from direct anthropogenic pressures and climate change. In this study, the overarching research question is to explore whether compound drought-heat events (CDHEs) have become more recurrent, intense, and widespread over Brazil’s Pantanal wetland in recent decades. For this, two different approaches were proposed and tested using validated long-term time series of monthly precipitation, temperature, and the satellite-based Vegetation Health Index (VHI) to characterize the spatiotemporal pattern of CDHEs over Pantanal. The Standardized Precipitation Index (SPI), Standardized Temperature Index (STI), and Standardized Precipitation Evapotranspiration Index (SPEI) from 1981 to 2021 were calculated. The results showed that using both approaches, the frequency of events is higher in the moderate category, which is expected since the criteria are less restrictive. In addition, the highest frequency of CDHE events occurs at the end of the dry season. The results also indicated that CDHE events have been more recurrent and widespread since 2000 in Pantanal. Besides, considering all methods for identifying the CDHEs, the probability density function indicates a shift pattern to warmer and drier conditions in the last 40 years. The Mann-Kendall tests also confirmed the assumption that there is a significantly increasing trend in the compound drought-heat events in the Pantanal. Developing methodologies for monitoring compound climate events is crucial for assessing climate risks in a warming climate. Besides, it is expected that the results contribute to convincing the urgent need for environmental protection strategies and disaster risk reduction plans for the Pantanal.

How to cite: Martins do Amaral Cunha, A. P.: Monitoring compound drought-heat events over Brazil’s Pantanal wetland, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9271, https://doi.org/10.5194/egusphere-egu24-9271, 2024.

Hot and dry extreme events in Europe have become more frequent and pose serious threats to human health, agriculture, infrastructure, and ecology. Single and compound hot and dry extremes in Europe have been attributed to synoptic atmospheric circulation variations and land-atmosphere interactions. However, the exact causal pathways and their strength, as well as their historical trends, have not been quantified. An accurate understanding of the mechanisms behind these land-atmosphere extremes is crucial to improving S2S forecasts and implementing appropriate adaptation measures. Here, we use the Peter and Clark momentary conditional independence (PCMCI) based Causal Effect Networks (CENs) to detect and quantify dynamic and thermodynamic causal precursors of extremely high 2m temperature (T2m) and extremely low soil water deficit and surplus (WSD) in central Europe (CEU).

Our analysis reveals that the single hot events are driven mainly by anomalous atmospheric patterns and soil water deficiency, while single dry events are mainly driven by the soil moisture memory, and anomalous atmospheric patterns, and only marginally by temperature changes. The atmospheric circulation patterns preceding both single hot and dry events show a high-pressure system over central Europe, with a low-pressure system over the Atlantic Ocean, and partly explain the occurrence of the compound events. This atmospheric pattern is also linked to an anomalous zonal cold-warm-cold SST pattern over the Atlantic Ocean and a warmer eastern Pacific Ocean.

The identified causal links vary with temperature and humidity conditions, that is, the impact of soil moisture memory on the WSD variation is sensitive to T2m and WSD, while the influence of soil moisture condition on T2m changes is strengthened by reduced WSD. Moreover, during compound hot and dry extremes, the effect of reduced soil moisture on temperature is significantly higher than during single events, reaching twice the magnitude under moderate conditions. When historical trends are analyzed, we show that the impact of dry soil on temperature is amplified by 42% (46%) for single (compound) extremes during 1979-2020, while the influence of atmospheric drivers on soil moisture is intensified by 28% (43%).

This work emphasizes (i) the intensification of the strength of the thermodynamic causal pathways for warmer and dryer CEU over time and (ii) the stress on the varying forcing strength of the drivers, which can lead to non-linear variations of weather stressors under climate changes and thus add extra challenges to extreme adaptations.

How to cite: Di Capua, G., Tian, Y., Giaquinto, D., Claassen, J., Ali, J., Li, H., and De Michele, C.: Changes in the causal effect networks of single and compound extreme hot and dry events in Central Europe, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10748, https://doi.org/10.5194/egusphere-egu24-10748, 2024.

Compound events (CE) are the combination of climate phenomena which, taken individually, are not necessarily extreme but whose (concurrent or sequential) composition can cause very strong impacts and damages. Hence, the understanding of their potential past and future changes and evolutions are of great importance and, thus, more and more research is being carried out on this issue ([1], [2]). However, these questions are still rarely addressed over France, especially at high spatial resolution, even though they are necessary for the development of adaptation strategies. The present study focuses on historical multivariate compound events (several events occurring at the same time and same location), like hot and dry events or extreme wind and precipitation events, and aims to detect past changes in probability of such events over France. ERA5 reanalyses [3] are then used on the 1950-2022 period.

The first question that arises is: Where and when did these signals emerge in France? Are patterns forming? This issue is addressed through the analysis of “times” and “periods” of emergence, corresponding to moments when the change in probability of a specific CE is out of its natural variability [4].  The second question that comes up is: “What drives the emergence? What are the contributions of the changes in the marginal distributions and in the dependence structure to the change of compound events probability?” The study tries to answer this question thanks to the copula theory, allowing to decompose these different contributions. Copula functions are used to model bivariate joint probabilities, and are increasingly applied to hydroclimatic variables ([5], [6]).

Depending on the intensity and the type of the compound, the results indicate that (1) maps of time of emergence show clear spatial patterns and (2) that the changes in marginal distributions play a much more significant role than the changes in dependence during the emergence. This work opens perspectives for future projects, such as investigating physical phenomena driving these patterns and more deeply understanding changes in dependence between the different climate variables. Then analyzing climate model ability to reproduce the results would enable the application of the methodology to attribution framework and a better assessment of the risks associated with past and future climate change. 

References
[1] Singh, Harsimrenjit, Mohammad Reza Najafi, and Alex J. Cannon. "Characterizing non-stationary compound extreme events in a changing climate based on large-ensemble climate simulations." Climate Dynamics 56 (2021): 1389-1405.
[2] Ridder, N. N., et al. "Increased occurrence of high impact compound events under climate change." Npj Climate and Atmospheric Science 5.1 (2022): 3.
[3] Hersbach, Hans, et al. "The ERA5 global reanalysis." Quarterly Journal of the Royal Meteorological Society 146.730 (2020): 1999-2049.
[4] François, Bastien, and Mathieu Vrac. "Time of emergence of compound events: contribution of univariate and dependence properties." Natural Hazards and Earth System Sciences 23.1 (2023): 21-44.
[5] Zscheischler, Jakob, and Sonia I. Seneviratne. "Dependence of drivers affects risks associated with compound events." Science advances 3.6 (2017): e1700263.
[6] Tootoonchi, Faranak, et al. "Copulas for hydroclimatic analysis: A practice‐oriented overview." Wiley Interdisciplinary Reviews: Water 9.2 (2022): e1579.

How to cite: Schmutz, J., Vrac, M., and François, B.: Time and period of emergence of compound events in France, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11331, https://doi.org/10.5194/egusphere-egu24-11331, 2024.

The variability in the occurrence of concurrent extremes like droughts and heatwaves is often attributed to climate change and anthropogenic factors, neglecting its connection with large-scale global teleconnections. The current study investigates the temporal and spatial connections between concurrent droughts and heatwaves (CDHW) in India to large scale global teleconnections like El Nino Southern Oscillation, North Atlantic Oscillation, Pacific Decadal Oscillation, and Indian Ocean Dipole. Utilizing composite and wavelet coherence analyses, we conduct a univariate assessment of droughts and heatwaves, quantified with the standardized precipitation index and standardized heat index, respectively, in association with large-scale global teleconnections (referred as climate drivers). Further, a novel attribution table framework proposed to quantify the conditional probability of CDHW given the onset of climate drivers. We found that the probability of CDHW preceeding the onset of climate drivers is much higher compared to the probability of CDHW occuring without the onset of climate drivers. The insights from this study suggest the potential use of global teleconnections for issuing season-ahead forecasts of CDHW.

How to cite: Das Bhowmik, R., Tabbussum, R., and Mujumdar, P.: Understanding the association between global teleconnections and concurrent drought and heatwaves events over India, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11345, https://doi.org/10.5194/egusphere-egu24-11345, 2024.

Coastal areas are becoming increasingly vulnerable due to climate change. These regions are exposed to various sources of flooding, such as high sea levels, river discharge and heavy rainfall. Our study focuses on understanding compound flooding from storm surges and river discharge in Croatia. This is the first study on compound floods in this country. For this purpose, we analysed the time series of water levels and discharges from hydrological stations located along ten major coastal rivers. Since there are only a limited number of tide gauges in Croatia, we combined measured data with numerical reanalyses. The sea level data for the entire Adriatic Sea were obtained from the Copernicus Marine Service (Mediterranean Sea Physics Reanalysis) and were then corrected using machine learning and measured data.

Previous studies have shown that neglecting seasonal variations in river discharge and storm surges could lead to a significant underestimation of the expected annual damage from compound floods. Different seasons bring distinct weather and river discharge patterns that influence the probability and severity of compound floods. To address this, our study investigated seasonal correlation and co-occurrence by analysing the monthly maximum values. By examining each season in detail, we uncovered the variations in the compound flood potential index.

This analysis provides a more comprehensive understanding of compound floods in Croatia, which is crucial for risk assessment and risk management. Finally, we mapped the correlation coefficients, the number of co-occurrences and the compound flood potential index along the Croatian coast and organised the results in a GIS database. These maps will improve our ability to systematically select the most vulnerable areas where the risk of compound flooding should be analysed at the local level.

How to cite: Krvavica, N., Bilić, M. M., and Ružić, I.: Compound Flood Potential from Co-occurrence of River Discharge and Storm Surge in Croatia, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11560, https://doi.org/10.5194/egusphere-egu24-11560, 2024.

Changes in wind speed and temperature significantly co-alter soil erosion climatic erosivity. However, knowledge on compound climatic elements of soil erosion to climate change is limited. Here, we quantify long-term climatic erosivity based on the wind erosion climatic erovisity and freeze-thaw climatic index, and analyze the contributions of single and compound factors using the slope change ratio of accumulative quantity methods. Our results show frequency of compound events is gradually decreasing as a result of climate change. Compound climatic erosivity exhibits large spatial variability and decreases with the wind erosion climatic erosivity and freeze-thaw climatic index. Moreover, a negative temporal trend of compound climatic erosivity is found in 61.28% of the study area from 1981 to 2020, which is largely attributed to declining wind speed. One unanticipated finding was that the frequency of compound erosion has shown a decreasing trend at some sites, but the intensity has shown an increasing trend. A possible explanation for this might be the extreme wind speeds and temperatures. Our findings highlight compounding effects of climatic conditions have a more severe impact on soil erosion.

How to cite: Yang, W.: Compound variation in freeze-thaw index and wind climatic erosivity in the agro-pastoral ecotone in northern China , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12712, https://doi.org/10.5194/egusphere-egu24-12712, 2024.

Climate change impacts are accelerating and intensifying, as observed over the past years, especially in the past year 2023.The current CMIP6 global climate simulations (GCMs) show higher climate sensitivity resulting in stronger warming and related impacts than previous simulations. Mountain regions are especially vulnerable as the warming climate relates to thawing of permafrost destabilising slopes and the emerging risk of heat and altered precipitation pattern that cause (extreme) flooding. Furthermore, the occurrence of compound events has gained increased attention as those pose substantial threat to the prevailing settlements and infrastructure.

Nevertheless, the available GCM simulations are spatially too coarse to investigate the mentioned extreme events in complex terrain. Therefore, statistical and dynamical downscaling is performed within the ICARIA project (Russo et al., 2023) to better analyse future climate impacts for the mountain regions of Salzburg. For the dynamical downscaling two regional climate models (RCMs), the WRF and COSMO-CLM (CCLM) are used to simulate the future climate conditions for the SSP126, SSP585 at spatial resolution of 2-5 km² until 2100.

The verification of the two RCMs with respect to CHELSA (Karger et al., 2017) display that the 5km² WRF model simulations overestimate the precipitation intensities, especially in mountainous regions, the same goes for CCLM. With respect to temperature, WRF and CCLM display an underestimation of temperature in higher altitudes (above 600m) and a good representation below.

Additionally, statistical downscaling has also been performed within ICARIA following the FICLIMA method. For this procedure, a set of 59 weather observations were used together with 10 CMIP6 GCMs. ERA5-Land and statistics such as MAE, Bias or Kolmogorov-Smirnov test were used for verification purposes of the methodology for each spot and model. Those that passed filters of quality and performance in the representation of past climate produced local downscaled climate projections at daily resolution for each location for the Tier 1 SSPs (1.26, 2.45, 3.70 and 5.85). Both the statistical and dynamical downscaling methods' outputs will serve to compare results and better assess the inherent uncertainties of climate projections.

Since the focus is on extreme events, the prevailing simulations are analysed with respect to the global warming levels (1.5°C, 2°C, 3°C and 4°C) and their related local impacts. To investigate extreme events related to precipitation and wind, as well as their compound occurrence, suitable indicators are investigated, such as precipitation intensity estimates through future IDF curves and wind gust events with return periods of 1, 2, 5, 10, 20, 50, 100, 500 years. Further, consecutive events, that have a compound impact on the system, are considered through investigating the region and hazard specific time period before and after the occurrence of the extreme event.

Russo, B., de la Cruz Coronas, À., Leone, M., Evans, B., Brito, R. S., Havlik, D., ... & Sfetsos, A. (2023). Improving Climate Resilience of Critical Assets: The ICARIA Project. Sustainability, 15(19), 14090

Karger, D. N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R. W., ... & Kessler, M. (2017). Climatologies at high resolution for the earth’s land surface areas. Scientific data, 4(1), 1-20.

How to cite: Bügelmayer-Blaschek, M., Hasel, K., Züger, J., Monjo, R., and Paradinas, C.: Local climate change impacts - new insights for mountain regions of Salzburg based on high resolution climate simulations, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12824, https://doi.org/10.5194/egusphere-egu24-12824, 2024.

We investigate the most extreme but physically plausible heat-loaded European summers in current and near future climate conditions using ensemble boosting. With this approach, we identify the most extreme summers in an initial-condition large ensemble with the model CESM2 and boost them, creating a large ensemble of re-initialized simulations with slightly perturbed atmospheric initial conditions. This allows us to efficiently generate storylines for summers that are even more extreme than the original simulations, either due to a higher number of days or grid cells exceeding extreme heat thresholds, or original heatwave clusters exceeding such thresholds by larger margins.

We compare these storylines of summer heat clusters to the most extreme European summers in the observational record, and determine the necessary and exacerbating mechanisms behind these clusters of extreme heat. We quantify how factors such as the intensity and persistence of atmospheric patterns as well as sea surface temperatures and terrestrial water budgets contribute to the most extreme simulated summers. Furthermore, we disentangle the effects of extreme early heat in May-June acting as a preconditioning factor in driving more extreme conditions during the rest of the summer, due to it causing more heat-prone conditions such as warmer oceanic basins and dryer soils, versus the effects of large-scale preconditioning factors that may lead to more persistent and intense heat through the summer, regardless of if it starts early in the season or not.

Ensemble boosting is a computationally efficient approach that allows us to sample extreme rare events, now over time scales of several months, while preserving physical consistency both in time, space and across variables. This is an ideal setup for disentangling contributions from different driving factors, and the generated boosting storylines can be used in impact studies that require physical consistency, a prolonged simulation time, and successive or compounding hazard exposure.

How to cite: Suarez-Gutierrez, L., Beyerle, U., Mittermeier, M., Vautard, R., and Fischer, E. M.: Summers full of extreme heat: using ensemble boosting storylines to quantify the drivers of heatwave clusters, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12906, https://doi.org/10.5194/egusphere-egu24-12906, 2024.

Global coffee production is at risk from synchronous crop failures, characterised by widespread reductions in yield occurring in multiple regions at the same time. For other crops, we know that these synchronous failures can be forced by spatially compounding climate anomalies, which in turn may be driven by large-scale climate modes like the El Niño Southern Oscillation (ENSO).

This talk will discuss the extent to which climate hazards occur and co-occur across the world’s major coffee-growing regions. These climate hazards include temperature and rainfall anomalies and are selected to cover two coffee species and different periods of the crop growing cycle. The talk will show that regional and global risk posed from spatially compounding hazards has increased over recent decades. There is a clear shift in the profile of this risk. Temperature-based hazards are now much more likely to exceed thresholds for optimal growing conditions, rather than being overly cold as observed during the 1980s.

Through multiple lines of evidence we find relationships between spatially compounding hazards and six tropical climate modes such as ENSO and the Madden Julian Oscillation. Individual regions exhibit differing relationships with these modes. ENSO is found to have the strongest links with multiple regions during the same crop cycle, posing implications for ENSO-driven global impacts to supply.

How to cite: Richardson, D.: The risk to global coffee supply from synchronous climate hazards, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13620, https://doi.org/10.5194/egusphere-egu24-13620, 2024.

The intricate physical complexity of compound coastal flooding—resulting from the combination of river floods and storm surges—is known for often leading to more severe consequences than independent-driver floods. Damages from this type of flooding are expected to increase due to the impact of climate change on precipitation patterns and coastal storms, coupled with the increasing trends in population growth and economic activities along coastal regions. In the United States, the Federal Emergency Management Agency’s (FEMA) National Flood Insurance Program (NFIP) is the largest provider of flood insurance policies, and currently, more than two million NFIP flood claim transactions (1978 to present) are available to the public for analysis. However, there is a lack of studies that analyze how compound events reflect on insurance claims.

In this study, we focus on over 60,000 counties across the entire coastline of the United States to provide an exhaustive analysis of the distribution of economic losses in areas subject to river flooding, coastal flooding, and regions susceptible to compound events.

To identify the relative importance of the driving mechanisms (inland vs. coastal flows) for a particular location, we apply a published index [D-Index, readers are referred to the article, https://doi.org/10.1016/j.jhydrol.2023.130278 for details] that is capable of physically attributing the cause of flood depth to either river or coastal drivers, or a combination of both rainfall and storm surge.

We focus the analysis on the number of damages reported in the claims, comparing and contrasting claims in counties physically labeled as coastal, river, or compound. By calculating the quantile weight distance (QWD) of the damages from claims in the ‘compound’ counties and claims in the ‘independent-driver’ counties, we further investigate how rainfall and tide characteristics of storm events relate to the NFIP flood claims in the case of compound events. We further quantify differences in QWD by comparing and contrasting FEMA’s high-risk flood zones (identifying the 1-percent annual chance floodplain), where insurance is required for homes financed through federally backed or federally-regulated lenders, and FEMA’s low and moderate-risk flood zones, where flood insurance is not required.

In conclusion, this study furnishes invaluable insights into the intricate challenges of assessing compound coastal flooding impacts on insurance claims. The proposed methodology, integrating a flood type-specific mapping system and considering spatial variabilities of inundation characteristics, establishes a robust foundation for a comprehensive and improved flood risk assessment in coastal CONUS.

These findings empower coastal communities to proactively manage concealed risks and fortify their resilience against the compounding impacts of environmental forcings. This research offers a proactive and informed strategy to mitigate the potentially disastrous consequences of compound coastal flooding in a changing climate and socio-economic landscape.

How to cite: Mitu, M. F., Sofia, G., Shen, X., and Anagnostou, E. N.: Translating Flood Insurance Claims in the Coastal CONUS within the Spectrum of Compound Flood Risk, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14082, https://doi.org/10.5194/egusphere-egu24-14082, 2024.

How to cite: Rogers, C. and Warren, R.: Fast and Accurate Calculation of Wet-bulb Temperature for Humid-Heat Extremes, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14205, https://doi.org/10.5194/egusphere-egu24-14205, 2024.

The compound occurrence of heatwaves and droughts (COHWD) may result in disastrous impacts and losses across various socioeconomic sectors. Therefore, it is important to understand and predict these phenomena to support decision makers and stakeholders in implementing preparedness and adaptation measures. However, questions concerning the underlying physics that drive and potentially exacerbate these extremes in the future still remain open. 

This study focuses on identifying COHWD and their characteristics during the lasts 62 summers through the analysis of atmospheric variables from the ERA5, GPCC and CRU datasets in the northern hemisphere (NH). Three regions, as categorized in the latest IPCC report, are analyzed: Western & Central Europe (WCE), the Mediterranean (MED) and Eastern Asia (EAS). These regions are selected because they account for the main breadbaskets in the NH.

Results show that WCE and MED have witnessed an increase in the area affected by COHWD over . In contrast, EAS does not exhibit a clear trend over the past six decades.  Moreover, by analyzing the variability of large atmospheric circulation patterns and climate oscillations, such as the North Atlantic Oscillation and the El Niño/Southern Oscillation, the dynamical drivers of COHWDs are identified. This research aims at providing new insights into the dynamical mechanisms driving COHWDs, to improve the identification, understanding, prediction and management of such events in the future. 

How to cite: Castillo, N., Gaetani, M., and Martina, M.: Compound occurrence of heat waves and drought in the Northern Hemisphere, atmospheric circulation patterns and impacts., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14358, https://doi.org/10.5194/egusphere-egu24-14358, 2024.

For improving climate projections, there is a need to understand the physical processes governing the variability of dynamically driven variables, like near-surface temperature. Studies have shown that some features like surface drying and anticyclonic upper level conditions are associated with enhanced surface warming. However, the different ways in which surface, radiative and atmospheric variables compound to cause a heatwave, and the relative magnitudes of these variables and their relationship with heatwave intensity has not been well understood. Further, the large scale dynamics governing such conditions, and the effects of slowly varying climate features like ENSO and AO, are unresolved.

Using the ERA5 reanalysis dataset, we are studying the drivers of variability of daily mean 2 meter temperature (T2m) anomaly over the northwest Indian heatwave hotspot region, in the entire premonsoon season (March to June). Our approach is to develop an interaction framework which identifies governing surface and weather regimes active during different months, and quantify how large-scale climate patterns modulate their frequency of occurrence. We are leveraging the decision tree classification framework to identify the dominant weather patterns explaining different quartiles of T2m anomaly, owing to its non-linear modeling capability. 

During March and April, the T2m anomalies are accompanied by a vertically coherent temperature anomaly field, and typically last only for a day or two. The decision tree classification algorithm suggests that anomalous surface warming during this period is preceded by increased shortwave radiation corresponding to subsidence across the tropospheric extent. The decay of such an anomaly is marked by decreased downward shortwave radiation fluxes and increased downward longwave radiation fluxes, indicating the role of ventilation and cloud formation. The direction of sensible flux anomaly also changes between the two phases, directed from the atmosphere to the surface in the warming phase, and from the surface of the atmosphere in the decay phase. During May and June, the warming anomalies last for more than three days, and the sensible heat flux anomalies are directed toward the surface. Although shortwave anomalies peak along with T2m anomalies, there is also an increased convergence of dry static energy in the lower troposphere, between 600–900 hPa, in the region. Geopotential anomalies on the 350 K isentropic surface are anti-correlated with potential vorticity anomaly, establishing the role of Rossby wave packets as the dynamical drivers of temperature variability in this region. 

Thus, we show how an interpretable machine learning algorithm like the decision tree could potentially identify proximal drivers and compounding factors of heatwaves, provide a way to rank them by their importance, and eventually lead to a multiscale framework by incorporating longer term signals such as ENSO. 

How to cite: Shah, H. and Monteiro, J.: Pathways to temperature variability in South Asia, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14371, https://doi.org/10.5194/egusphere-egu24-14371, 2024.

Compound droughts and heatwaves (CDHWs) exert substantial socio-economic and ecological impacts, with their impacts reach epidemic proportions when CDHWs manifest simultaneously across multiple locations. Recent studies have begun to understand CDHWs, but their spatial compounding effects are not yet explored. This study utilizes weekly precipitation and temperature data to investigate the spatial synchronization of CDHWs and its changes. We define drought and heatwave weeks using the Standardized Precipitation Index (SPI 3-weekly) and the 90th percentile threshold of weekly temperatures. Our analysis reveals an unprecedented increase in the global land area and the number of regions experiencing concurrent CDHWs, particularly notable post-2000. The frequency of globally synchronized CDHWs (more than 5 regions affected simultaneously) has surged from 3 weeks (1982-1992) to 18 weeks (2012-2022), which is primarily attributed to a simultaneous global rise in temperatures driven by climate change. Analyzing CDHWs from observed data and counterfactual scenarios, where temperature data is detrended, we noted significantly higher likelihood of synchronization in observations due to intensified heatwaves in a warmer world. Notably, certain region pairs exhibit a higher likelihood of CDHW synchronization regardless being geographically distant. Spearman correlation and Granger causality analyses highlight major climatic modes, including El-Nino Southern Oscillation, Atlantic Multidecadal Oscillation, Western Tropical Indian Ocean, and Mode-2 of global Sea Surface Temperature, influencing changes in the areal extent of CDHWs globally as well as regionally. These insights are useful to predict the CDHWs and to quantify their socio-ecological impacts.

How to cite: ul Hassan, W., Saharwardi, M. S., Prasad Dasari, H., Gandham, H., Hoteit, I., and Abualnaja, Y.: Accelerating Heatwaves Intensify Spatial Synchronization of Compound Drought and Heatwave Events, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14461, https://doi.org/10.5194/egusphere-egu24-14461, 2024.

Coastal regions face escalating threats under climate change, necessitating a comprehensive understanding of compound flooding dynamics. This study aims to investigate the interplay between precipitation, wind waves, and meteorologically-driven storm surge, assessing their joint behavior leading to compound coastal flood risks in the Pacific Northwest. We examined two approaches to capture all possible drivers leading to compound events, which may not necessarily result from the extreme conditions of individual marginal variables. First, we used a conditional approach and assessed the block maxima (BM) of each variable in conjunction with the corresponding values of the other variables. Second, a peak-over-threshold (POT) investigation was conducted to generate datasets where all variables exceed their 95th percentiles. To calculate the joint return period of coastal flooding drivers, we used the most appropriate marginal distributions commonly used in coastal engineering, including the Generalized Pareto Distribution (GPD) for the POT-based approach and the Generalized Extreme Value (GEV) distribution for the BM. Subsequently, we computed the joint probability distribution by fitting the best-suited copula to the datasets to capture the interdependencies between the drivers. Moreover, as meteorological drivers may change under global warming, we extended our analysis to consider future projections of surge, waves, and precipitation. This enabled us to examine changes in the aforementioned dependencies and return periods. Sub-daily time series of surge and wave heights were obtained from the Canadian Coastal Climate Risk Information System (CCCRIS) (https://cccris.ca/), which provides high-resolution (~250 m along coastlines) simulations driven by ERA5 reanalysis and future projections until 2100 under the RCP8.5 emission scenario driven by four different combinations of global and regional models, namely, CanESM2.CanRCM4, CanESM2.CRCM5-QUAM, MPI-ESM-MR.CRCM5-QUAM, and GFDL-ESM2M.WRF. For each grid point, the corresponding precipitation data is obtained from the nearest grid point of the respective climate models. We assessed the degree to which each driver contributed to the overall change in the joint return period of concurring extremes in coastal flooding. We also conducted an analysis to quantify the respective contributions of each driver’s projection and their dependence structure to the uncertainty in changes of return periods. This study leveraged high-resolution data that encapsulated the regional dynamic responses, which is pivotal for precisely evaluating climatic hazards and developing efficient adaptation schemes, thereby ensuring a more informed decision-making process for coastal management and engineering applications.

How to cite: Fereshtehpour, M., Najafi, M. R., and Casas-Prat, M.: Compound Coastal Flooding Drivers in the Pacific Northwest: Understanding Precipitation-Surge-Wave Interactions and Projected Changes, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14796, https://doi.org/10.5194/egusphere-egu24-14796, 2024.

Many coastal low-lying areas prone to coastal floods are protected by defense constructions. This often entails the establishing of artificial drainage systems to keep the hinterlands from flooding during heavy rain events. The coincidence of storm tide and heavy precipitation events may considerably limit the technical drainage capacity and lead to flooding. This situation can be exacerbated in the future due to changing conditions of both single drivers as well and their combinations. To assess the risks of inland flooding, a model based approach, combining the results from regional climate models with hydrological model for hinterlands and hydrodynamic model for coastal areas is established and applied. As a focus area, the water board Emden (Germany) and the gauge Knock are selected, which is a low-lying artificially drained area between the Ems river and the North Sea. For historical events, the main drivers leading to diminished drainage capacity and system overload were moderate storm series combined with the large-scale heavy precipitations. Whereas extreme storm tides or heavy precipitations alone posed no significant challenge for the system. The combinations of future emission scenarios (RCP2.6 and RCP8.5) and regionalized climate models (MPI-ESM and HadGEM2) together with local sea level rise projections are used to estimate the system overload and flood risk under the climate change conditions. For control period, the main cause of moderate system overload appears to be heavy precipitations rather than storm tides. For future projections, the importance and intensity of compound events will increase, reflecting changes in mean sea level and thus storm tides as well as intensification of heavy rain events.

How to cite: Gaslikova, L., Bormann, H., Kebschull, J., Weisse, R., and Meyer, E.: Climate change impact on inland flood risks due to compound storm tide and precipitation events for managed low-lying coastal areas., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15681, https://doi.org/10.5194/egusphere-egu24-15681, 2024.

The intricate coastline of the Adriatic Sea presents challenges for sailing, especially through narrow island channels in severe weather conditions. To plan construction work, an assessment was requested to determine the most favorable period for conducting maritime activities in two channels in the first half of the year, the Hvar Channel and the Korčula Channel. Motivated by that request, climatological analysis using available measurements of several meteorological parameters was conducted.

Favorable conditions for sailing usually include weak or moderate wind intensity, often generated by island or coastal circulation. To determine the unfavorable conditions for maritime transport several meteorological parameters are examined with emphasis on wind, wave height, and thunderstorms, as these might contribute to the most hazardous sailing conditions in this region. The eastern coast of the Adriatic Sea is exposed to the strong winds blowing during the colder part of the year: the bora (northeast wind) and the jugo (southeast wind). Due to the orientation of the Adriatic Sea and analyzed sea channels, the jugo usually generates larger waves than the bora thus endangering maritime transport. However, navigating in strong bora conditions poses different risks due to its typically turbulent nature and strong intensity.

With these considerations in mind, unfavorable navigation conditions are defined using three criteria: (i) wind strength reaching or exceeding Force 5 (Beaufort scale) and at least a moderate wave height, (ii) wind strength reaching or exceeding Force 8 regardless of the sea state, and (iii) the presence of thunderstorm conditions involving hail, thunder, and showers.

In the analysis, it is concluded that the number of days with unfavorable conditions decreases from January to June, as expected. The most unfavorable conditions are most likely to occur in January, while June proves to be the most suitable month for conducting work with an average of 5.7 days with unfavorable conditions. Throughout all considered months, there should be at least 10 days with favorable conditions. Moreover, in June of any year, the number of days with unfavorable conditions did not exceed 7.

How to cite: Kožul, E., Odak Plenković, I., and Muić, I.: Determining the frequency of unfavorable conditions for sailing in Adriatic Sea channels , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15746, https://doi.org/10.5194/egusphere-egu24-15746, 2024.

Various countries around the world have been experiencing coastal disasters caused by coastal flooding, and Korean Peninsula is no exception. Most coastal flooding occurs during extreme sea level conditions which is comprised astronomical tides, nontidal residuals, wind wave, and mean sea level. To respond to coastal flooding disasters, it is important to understand the characteristics of extreme sea levels. Therefore, this study analyzed the spatiotemporal patterns of extreme sea levels along the Korean Peninsula and evaluated the effects of the astronomical tides and nontidal residuals represented by storm surges on extreme sea levels among the components constituting extreme sea levels. At this time, when analyzing the impact of the storm surge, it was evaluated whether the storm surge was caused by tropical cyclones or extra-tropical cyclones, and what storm condition were more dangerous in the Korean Peninsula. This study collected observed tidal data from 1979 to 2021 at 48 tide stations which are installed along the coast of the KP and performed a hormonic analysis to distinguish them into astronomical and storm surge components. In this case, storm surges occurring in summer and winter were considered to be caused by tropical cyclones and continental cyclones, respectively. In addition, to more accurately analyze the regional characteristics, the Korea’s coast was divided in the three zones: the East Sea, the West Sea, and the South Sea. As a result of the study, it was found that the extreme sea levels along the Korean Peninsula showed regional differences, and in the case of the south coast, storm surges generated by tropical cyclones were the main drive of extreme sea levels.

How to cite: Yang, J.-A.: Spatio-temporal analysis of extreme sea level in the Korean Peninsula, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16044, https://doi.org/10.5194/egusphere-egu24-16044, 2024.

The joint occurrence of droughts and heat waves is expected to change with advancing climate change. While drought and heat themselves can already have major impacts on ecosystems and society, their compound occurrence can lead to amplified effects. Previous studies have analyzed changes in the occurrences frequency of compound drought-heat events and found increasing trends in some regions. In this study, we revisit these occurrence trends and additionally analyze the mechanisms that couple drought and heat as well as their changes in space and time. Considering drought as deficit of soil moisture and heat as an extreme temperature, evapotranspiration (ET) is the main physical process connecting both extremes. Therefore, we focus particularly on ET anomalies, because higher-than-normal ET during drought-heat events indicates that heat is inducing drought (heat → drought) as high temperatures lead to high vapor pressure deficit which increases ET that in turn depletes soil moisture. Vice versa, lower-than-normal ET suggests drought is triggering hot temperatures (drought → heat) as low soil moisture limits ET such that more of the incoming radiation is partitioned to sensible heat flux and hence warming the air. To better understand the underlying controls of these ET anomalies, we analyze their drivers by considering anomalies of precipitation, radiation, vapor pressure deficit and Leaf Area Index, which are in turn linked to anomalies in atmospheric circulation. Finally, we compare the relevance of these drivers, and of the drought → heat vs. heat → drought mechanisms in space, and link them with aridity and land cover type. In our analysis, we employ weekly data from the ERA5 reanalysis alongside gridded products derived with machine learning methods which were trained with in-situ observations. We define drought and heat with a percentile based approach filtering the lowest (< 5th percentile) absolute soil moisture values and highest (> 95th percentile) absolute temperatures at each grid cell. Understanding the mechanisms behind compound drought-heat extremes can help improve related forecasts, and to validate and constrain model projections of trends in these events. 

How to cite: Kroll, J., Stephan, R., Rieder, H., Hesselbjerg Christensen, J., and Orth, R.: Drivers of compound drought-heat extremes across recent decades, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17562, https://doi.org/10.5194/egusphere-egu24-17562, 2024.

This study investigates the evolution of extreme precipitation over the Greater Antilles and its relationship with large-scale sea surface temperature (SST) during the period 1985-2015. The data used are derived from two satellite datasets, CHIRPS (Climate Hazards Group InfraRed Precipitation, Funk et al. (2015)) and NOAA (OI V2 Sea Surface Temperature, Huang et al. (2021)), at resolution of 5km and 25km respectively.  Changes in the characteristics of six indices of precipitation extremes (Precipitation total; number of rainy days;  contribution of heavy rainfall, R95p, maximum duration of consecutive rainy and dry days) defined by the WMO ETCCDI (World Meteorological Organization Expert Team on Climate Change Detection and Indices, Peterson et al. (2001)) are described and the influence of four large-scale SST indices (Northern Oscillation Index, NAO; Southern Oscillation Index, SOI; Tropical South Atlantic, TSA; Caribbean Sea Surface Temperature, SST-CAR) is investigated using Spearman's correlation coefficient. The results show that at regional scale, a positive phase of the TSA index contributes to an increase of the rainfall intensity while a positive phase of NAO is significantly associated with a decrease of total precipitation, of daily rainfall intensity, and of heavy rainfall. At country level, in southeastern Cuba and Puerto Rico, the increase in heavy precipitation and rainfall intensity is linked to a positive phase of the SOI, TSA and SST-CAR, while in Jamaica and northern Haiti, they are associated with positive phase of TSA and SST-CAR. Increases in the number of rainy days and the maximum duration of consecutive rainy days over the southern Haiti and the Dominican Republic are significantly associated with positive phase of the Southern Oscillation (SOI) and warming of SST over the east of the Caribbean Sea. The results of this study show that, in the Caribbean, particularly in the Greater Antilles, large-scale SST have had a strong influence on extreme precipitation over the past 30 years.

Keywords: Caribbean region; Greater Antilles; Extreme precipitation; Climate variability; Sea surface temperature

How to cite: Destouches, C., Diedhiou, A., Anquetin, S., Hingray, B., Pierre, A., Joseph, A., and Boisson, D.: Changes in extreme precipitation patterns over the Greater Antilles and teleconnection with large-scale sea surface temperature, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18239, https://doi.org/10.5194/egusphere-egu24-18239, 2024.

We investigate the representation of compound hot-dry events in decadal predictions and their relationship with their univariate hot and dry components. We use a CMIP6 multi-model ensemble (MME) of 125 members from the Decadal Climate Prediction Project (DCPP) hindcast simulations and compare it with different observational references. Our analysis focuses on the first five lead years of the simulations, with the different ensemble members initialised every year from 1960 to 2014. We analyse the skill of predicting hot, dry and hot-dry events in the multi-model ensemble. Specifically, we select the days above the 90th percentile of the daily maximum temperature for hot events. For dry events, we use two indicators, the Standardised Precipitation Index (SPI) and the Standardised Precipitation Evapotranspiration Index (SPEI), with accumulation periods of 3, 6 and 12 months, and we consider a dry event a month that shows an SPI or an SPEI value ≤1. Finally, we identify days that present both hot and dry conditions according to these criteria as compound hot-dry days.

Preliminary results for the observations show a strong correlation between precipitation and the occurrence of compound events, especially for long accumulation periods, suggesting the importance of dryness as a driver for compound hot-dry events. In the DCPP hindcasts, the hot events show some robust predictive skill, mainly as a consequence of the increasing trend in temperature. On the other hand, dry events show sparse skill, concentrated in dry areas of the world and especially for extended accumulation periods. Further analysis of the skill of compound events and their relationship to their univariate counterparts in DCPP hindcasts will shed light on the representation of such events in decadal forecasts. However, these initial results underline the importance of precipitation in both the occurrence of present hot-dry compound events and the prediction of such events in the future.

How to cite: Aranyossy, A., Donat, M., Deluca, P., Delgado-Torres, C., and Solaraju-Murali, B.: Interconnections and decadal predictability of global hot, dry and compound hot-dry events, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18528, https://doi.org/10.5194/egusphere-egu24-18528, 2024.

With the intensity and frequency of climate driven disasters increasing as result of climate change, there is ever more need to plan for such events and develop means to mitigate against them (UNDRR, 2015). Traditionally, the assessment of risks and impacts to regions posed by climate extreme events have been carried out in a “one at a time” approach, where the effects of each hazard, are assessed individually (Russo et al., 2023). However, it is recognised that  a transition to a more multi-hazard and multisectoral approach  is needed to be more efficient and effective in mitigating the risks/impacts posed to society, infrastructures, or the environment (Sendai Framework, 2015), (Russo et al. 2023). Whilst risk/impact assessment modelling can be complex, the derivation of risk/impacts is complicated further within a multi-hazard assessment due to the interdependent relationships between hazard, exposure and vulnerability, and that these vary over time in response to a preceding hazard (Gill et al. 2021).

The European Funded ICARIA project seeks to create an asset level modelling framework for understanding the potential risks/impacts posed by multi-hazard climate driven hazards, whilst also providing insight into cost-effective means of mitigating against them through the application of suitable adaptation measures. Two of the key challenges when transitioning from a single to a multi-hazard modelling approach are that (1) hazards are not directly comparable due differences in their processes and metrics, and (2) the effects of one hazard can influence the behaviour/characteristics of another hazard (Forzieri et al., 2016). To simulate the potential risks/impacts that could result from the modelled range of compound and consecutive hazards, a two-stage approach is being adopted that consists of (1) a deterministic physical modelling approach for quantifying the risks/impacts that can arise through simulation of various compound and consecutive hazard scenarios, along with (2) a stochastic Bayesian Network (BN) method for defining the probability distribution of such events. The BN will consider historical data for defining the probability distribution of modelled, multi-hazard scenarios for both current and future scenarios whilst data from the physical modelling will be used for defining the distribution of parameters relating to exposure, vulnerability, and impacts for the business as usual (no adaptation) and future adaptation scenarios.

Acknowledgement

The ICARIA project (Improving Climate Resilience of Critical Assets) is funded by the European Commission through the Horizon Europe Programme, grant number 101093806. https://cordis.europa.eu/project/id/101093806.

References

Forzieri, G., Feyen, L., Russo, S., Vousdoukas, M., Alfieri, L., Outten, S., Migliavacca, M., Bianchi, A., Rojas, R., & Cid, A. (2016). Multi-hazard assessment in Europe under climate change. Climatic Change, 137(1), 105–119. https://doi.org/10.1007/s10584-016-1661-x

Gill, J. C., Hussain, E., & Malamud, B. D. (2021). Workshop Report: Multi-Hazard Risk Scenarios for Tomorrow’s Cities.

Russo, B., de la Cruz Coronas, À., Leone, M., Evans, B., Brito, R. S., Havlik, D., Bügelmayer-Blaschek, M., Pacheco, D., & Sfetsos, A. (2023). Improving Climate Resilience of Critical Assets: The ICARIA Project. Sustainability, 15(19). https://doi.org/10.3390/su151914090

“United Nations - Headquarters United Nations Office for Disaster Risk Reduction.” (2015). Sendai Framework for Disaster Risk Reduction 2015-2030.

How to cite: Evans, B., Chen, A., De La Cruz Coronas, A., Russo, B., Turchi, A., Leone, M., and Büegelmayer, M.: Bayesian Network Approach for Assessing Probability of Multi-Hazard Climate Driven Events, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18959, https://doi.org/10.5194/egusphere-egu24-18959, 2024.

Globally, climate change is a vital issue which exacerbates many severe consequences and causes the increasing frequency and severity of extreme weather events. Extreme climatic events, such as flash flooding, heatwaves, and droughts, pose severe impacts on societies and ecosystems, due to their large spatial coverage and high intensity. These extreme climatic events often occur simultaneously or sequentially as so-called compound events (CEs), causing high economic and societal losses as compared to the losses due to individual climatic extreme events. In the last two decades, Pakistan was ranked among the top ten countries which are most vulnerable to climate change and disasters, such as intense flooding, extreme heat, and droughts, among others. This paper presents case studies of extreme and compounding events in the last two decades with severe devastating impacts on people, infrastructure, and ecosystems. Specifically, two worst-case studies have been focused such as a flood in 2010 followed by a drought and a flood in 2022 followed by the heatwave. The post-disaster analysis shows that major part of the country was severely affected by these two CEs as a result of damaging the standing crops, destroying land, and causing displacement of millions of people along with losses and damages in fatalities and monetary terms. Therefore, this study is very vital for decision-making authorities to perceive the expected risk for human life, environment, and infrastructure in the future. So that pre and post-disaster mitigation policies and strategies could be formulated at local and national levels. The paper concludes with a discussion of the implications for CE adaptation in Pakistan. Key recommendations are provided to mitigate the impacts of future CEs.

How to cite: imran, A.: Extreme and compounding events in Pakistan, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20174, https://doi.org/10.5194/egusphere-egu24-20174, 2024.

Probabilistic network models (PNMs) have established themselves as a data-driven modeling and machine learning prediction technique utilized across various disciplines, including climate analysis. Learning algorithms efficiently extract the underlying spatial dependency structure in a graph and a consistent probabilistic model from data (e.g. gridded reanalysis or climate model outputs for particular variables). The graph and probabilistic model together constitute a truly probabilistic backbone of the system underlying the data. The complex dependency structure between the variables in the dataset is encoded using both pairwise and conditional dependencies and can be explored and characterized using network and probabilistic metrics. When applied to climate data, PNMs have been demonstrated to faithfully uncover the various long‐range teleconnections relevant in temperature datasets, in particular those emerging in El Niño periods (Graafland, 2020).

The combination of multiple climate drivers and/or hazards that contribute to societal or environmental risk are the so-called compound weather and climate events. These compound events can be the result of a combination of factors over different dimensions: temporal, spatial, multi-variable, etc. (Zscheischler et al. 2020). In particular, spatially compound events take place when hazards in multiple connected locations cause an aggregated impact. In this work we apply PNMs to extract and characterize most essential spatial dependencies of compound events resulting from concurrent temperature and precipitation hazards, either in the same location or spatially connected, which can be relevant for agriculture. Furthermore, PNMs are used to propagate evidence of different levels of observed and projected global warming to assess the possible evolution of compound events in a changing climate.

References

Graafland, C.E., Gutiérrez, J.M., López, J.M. et al. The probabilistic backbone of data-driven complex networks: an example in climate. Sci Rep 10, 11484 (2020). DOI: 10.1038/s41598-020-67970-y

Zscheischler, J., Martius, O., Westra, S. et al.  (2020). A typology of compound weather and climate events. Nat Rev Earth Environ 1, 333–347, doi: 10.1038/s43017-020-0060-z.

Acknowledgement

This work is part of Project COMPOUND (TED2021-131334A-I00) funded by MCIN/AEI/10.13039/501100011033 and by the European Union NextGenerationEU/PRTR. 

How to cite: Graafland, C. E., Casanueva, A., Manzanas, R., and Gutierrez, J. M.: On the use of probabilistic network models to assess spatially compound events in a warmer world, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20589, https://doi.org/10.5194/egusphere-egu24-20589, 2024.

Climate change is intensifying the occurrence of various extreme weather events across different geographic regions. While most research tends to concentrate on individual extremes, such as heatwaves, droughts, or floods, there’s been minimal exploration into how multiple, diverse extremes interact and compound impact social vulnerability. This study analyzes the overlapping spatial and temporal impact of temperature, precipitation, and hydroclimatic extremes across the US in the context of climate change.

Using data and predictions from global and regional climate models for present (including historical) and future emissions scenarios, we compute several indices of different extremes related to heatwaves, floods, and droughts. The aim is to categorize regions, or states or counties, based on their exposure to simultaneous extremes, incorporating social vulnerability and socioeconomic factors. The combination of exposure to multiple hazards and social vulnerability reveals regions in the US that face the highest risks from climate change.

Understanding the likelihood of compound climatic extremes occurring in areas with vulnerable populations can significantly aid in planning for adaptation and reducing the risk of disasters. By employing machine learning techniques to predict both multidimensional extremes and social vulnerability, policymakers can tailor evidence-based strategies to enhance community resilience. The methodology and findings provide a framework for evaluating multidimensional climate risks, applicable not just in the US but also in other countries and regions worldwide.

How to cite: Bhattarai, S., Sharma, S., and Talchabhadel, R.: Assessing Multidimensional Climate Extremes and Associated Vulnerabilities Across the United States , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20600, https://doi.org/10.5194/egusphere-egu24-20600, 2024.

Long-term climate trends superimposed on climate variability changes are recognized to manipulate the living environments, and ultimately ecological resources for hominins, which in turn affect hominin activities. Archaeological evidence from loess sediments from Shangchen on the southeastern Chinese Loess Plateau indicates a suspension of hominin occupation around the time of the early mid-Pleistocene climate transition (MPT), prompting a re-assessment of climate-vegetation-hominin interactions. Our research generated magnetic susceptibility, total organic carbon cotent and its carbon isotope compositions, black carbon content and brGDGTs-derived mean annual temperatue and precipitation records in loess deposits with in situ lithic records covering the period of hominin occupation (~2.1–0.6 Ma). The results reveal four distinct climate-vegetation periods (2.1–1.8 Ma, 1.8–1.26 Ma, 1.26–0.9 Ma and 0.9–0.6 Ma). During the early MPT (1.26–0.9 Ma), unprecendently high variability in climate-environment and a long-term aridification with C₄ vegetation expansion trend may have driven early humans to move to more hospitable locations in the region. Comparison with the record at Nihewan indicates that large-scale climate oscillations induced disparate hominin responses due to distinctive local environmental conditions.

How to cite: Wang, Z., Zhou, B., Xu, X., Pang, Y., Bird, M., Wang, B., Meadows, M., and Taylor, D.: Hominin response to oscillations in climate and local environments during the Mid-Pleistocene Climate Transition in northern China, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2668, https://doi.org/10.5194/egusphere-egu24-2668, 2024.

Community assembly principles driving microbial biogeography have been studied in many environments, but rarely in the Arctic deep biosphere. The sea-level rise during the Holocene (11–0 ky BP) and its resulting sedimentation and biogeochemical processes can control microbial life in the Arctic sediments. We investigated subsurface sediments from the Arctic Ocean using metabarcoding-based sequencing to characterize bacterial 16S rRNA gene composition, respectively. We found enriched cyanobacterial sequences in methanogenic sediments, suggesting past cyanobacterial blooms in the Arctic Mid-Holocene (7–8 ky BP). Bacterial assemblage profiles with a sedimentary history of Holocene sea-level rise in the Arctic Ocean enabled a better understanding of the ecological processes governing community assembly across Holocene sedimentary habitats. The Arctic subsurface sediments deposited during the Holocene harbour distinguishable bacterial communities reflecting geochemical and paleoclimate separations. These local bacterial communities were phylogenetically influenced by interactions between biotic (symbiosis–competition or immigration–emigration) and abiotic (habitat specificity) factors governing community assembly under paleoclimate conditions. We conclude that bacterial profiles integrated with geological records seem useful for tracking microbial habitat preference, which reflects climate-triggered changes from the paleodepositional environment (the so-called ‘ancient DNAs’).

How to cite: Dukki, H. and Seung-Il, N.: Ancient DNAs: Influence of Sedimentary Deposition on Bacterial Communities in Arctic Holocene Sediments, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2955, https://doi.org/10.5194/egusphere-egu24-2955, 2024.

The Qinghai-Tibet Plateau (QTP) is an important ecological barrier in China and even East Asia, and its main vegetation cover type is grassland. With the global climate change, the phenological period of grassland on the QTP is constantly changing, which affects the climate and ecosystem through carbon cycle, hydrothermal cycle, etc. The influencing factors of phenology and its future change trend have become the key issues. In this paper, the spring phenological model of the QTP grassland was constructed by using the start of growing season (SOS) extracted from MODIS NDVI, air temperature and soil moisture data from 2000 to 2020. Combined with CMIP6 climate data, the future phenological changes of the QTP grassland under the SSP245 scenario were predicted. The results showed that: (1) The cumulative temperature and cumulative soil water threshold model was effective in simulating spring phenology of grassland on the QTP, and the root-mean-square error was only about 8 days. (2) The climatic thresholds at SOS of different vegetation types are closely related to their spatial distribution locations. Vegetation growth in the eastern and southern parts of the QTP requires higher hydrothermal conditions. (3) The QTP showed an overall warming and wetting trend in the future, with greater changes in the first half of the 21st century than those in the second half of the 21st century. (4) The advance of SOS in the northwest grassland was significantly higher than that in the southeast grassland. By the end of the 21st century, most grasslands on the QTP began to grow before mid-June.

How to cite: Wang, L., Zhao, X., Yin, H., and Zhu, G.: Modeling and future prediction of spring phenology in grassland on the Qinghai-Tibetan Plateau, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4247, https://doi.org/10.5194/egusphere-egu24-4247, 2024.

Human history is full of examples documenting that cultural innovations played a key role in reducing the impact of environmental stress on early populations. Over the past 1 million years this type of adaptation (e.g., clothing, shelter, hunting techniques, social behaviour) likely also increased human population size. Humans are cumulative cultural learners, who can integrate knowledge and culture from one generation to the next. The larger the number of interacting people, the faster the rate of innovation.  Here we introduce a stochastic consumer-resource modeling framework, that simulates the dynamics of cultural transmission, learning, and innovation, population size, and resource depletion in a changing environment. Culture is introduced as a booster to carrying capacity. A zero-dimensional version of the model simulates nonlinear phase-synchronization between culture, population and external climate forcings. We will also present the first results of the model in 2 dimensions with full global resolution and 3 interacting hominin species to assess which role differences in cultural innovation played in the extinction of Neanderthals and Denisovans.

How to cite: Timmermann, A., Wasay, A., Raia, P., and Ruan, J.: Climate, culture and population size, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4791, https://doi.org/10.5194/egusphere-egu24-4791, 2024.

Stalagmites are well-known as paleoclimatic archives, but recent work [e.g., 1,2] has also demonstrated their paleobiological potential as archives of ancient animal and plant DNA. Because of this property, stalagmites have the potential to provide information on how past climatic fluctuations have impacted land fauna, specifically cave fauna of which bats are key ecosystem services providers. The aim of this work is to use stalagmites to gain precisely such knowledge. With this endeavour, we acquired geochemical data (Sr/Ca, δ¹⁸O, δ¹³C) along the growth axis of three early Holocene stalagmites from Ireland, which we used for climatic and environmental reconstruction. In addition, we acquired ancient DNA data in stalagmite laminae, including those where climatic and environmental shifts were observed. Results of these analyses are presented here and include new U-Th-dated stable isotopic curves and ancient DNA data chronologically anchored to stalagmite-derived climatic records. We also discuss our analytical workflow and the pros and cons we faced while combining geological and biological data on stalagmites such as data acquisition resolution, stalagmite chemistry, and DNA data quality.

[1] Stahlschmidt et al. (2019) Scientific Reports, 9, 6628. [2] Marchesini et al. (2023) Quaternary Research, 112, 180-188

How to cite: Ansberque, C., Linderholm, A., Mark, C., Kylander, M., and McDermott, F.: Snapshots of Ireland’s Holocene climate and fauna from stalagmites, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5928, https://doi.org/10.5194/egusphere-egu24-5928, 2024.

Understanding the intricacies of climate behavior is paramount for regions like Houceima-Tanger-Tétouan, where agroclimatic phenomena directly influence socio-economic stability. This study rigorously evaluates the performance of climate models against the ERA5-Land reanalysis data, focusing on two pivotal agroclimatic indices: dry spell and heat wave frequencies. Such indices are integral for regional drought risk management, agricultural planning, and environmental policy formulation.

Our approach integrates a dual comparison framework—comparing model outputs against each other (inter-model) and against multiple runs of the same model (intra-model). We also validate the ERA5-Land data against 16 years of in-situ measurements to confirm its aptitude as a benchmark dataset, particularly examining its representation of temperature and precipitation.

Findings indicate a strong temperature data correlation with in-situ measurements, affirming the ERA5-Land's reliability for temperature-related indices. However, precipitation data showed considerable variability, necessitating cautious application and potential model adjustments. Among the models, the MOHC-HadGEM2-ES demonstrated notable accuracy in dry spell predictions for selected domains, while the MPI-M-MPI-ESM-MR model stood out for its heat wave frequency projections, especially in the EUR-44 domain.

Our results pave the way for selecting the most appropriate models for regional climate projections. They also highlight the necessity of model calibration, especially for precipitation indices, to ensure the precision of climate-related predictions. The study contributes to the field by providing a clear pathway for the utilization of tailored climate models in developing robust adaptive strategies to climate variability in the Houceima-Tanger-Tétouan region.

How to cite: Qacami, M., Bourgault, M.-A., Chikhaoui, M., Badard, T., Trudel, M., and Najat, B.: Assessing Model Relevance: Agroclimatic Indices Across Different CORDEX Domains for Enhanced Climate Projections in the Houceima-Tanger-Tétouan Region, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6756, https://doi.org/10.5194/egusphere-egu24-6756, 2024.

There is a chance of 1 in 2,700 that asteroid Bennu will hit Earth in 2182 CE. The collision of such medium-sized asteroids (~0.3-1 km in diameter) with our planet can inject massive amounts of dust into the atmosphere, with unknown consequences for terrestrial and marine ecosystems. Here, we use the coupled high-top Community Earth System Model Version 2 (CESM2) with interactive chemistry to investigate how medium-sized asteroid strikes would impact climate, vegetation, and marine productivity. Our idealized simulations show that globally dispersed dust layers of up to 400 Tg in mass block shortwave radiation to the surface for nearly two years, resulting in rapid global cooling and delayed weakening of the hydrological cycle for up to four years after the impact. The combined effects of reduced sunlight, cold temperature, and decreased precipitation significantly inhibit photosynthesis in the terrestrial ecosystem for almost nineteen months. Marine phytoplankton production decreases moderately within five months due to reduced sunlight. Subsequently, however, and depending on the iron amount of the asteroid, large diatom blooms occur over the eastern equatorial Pacific and Southern Ocean due to iron fertilization from strong upwelling and dust deposition, respectively.

How to cite: Dai, L. and Timmermann, A.: Climatic and ecological responses to medium-sized asteroid collision, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6896, https://doi.org/10.5194/egusphere-egu24-6896, 2024.

With growing concern about climate change and the increasing importance of Internet of Things (IoT) devices, the interaction between these two topics has been a focus of increased research. The purpose of this research paper, "Enhancing Climate Change Resilience in IoT Devices: Qualitative Analysis of Problems, Innovations, and Best Practises of IoT Devices," is to conduct a comprehensive qualitative analysis of the relation between IoT technology and climate resilience. This paper details the findings, providing contribution to the departments by offering solutions and recommendations that organisations can consider for improving the resilience of IoT devices in a severe weather condition. The paper includes an in-depth analysis of the present condition of IoT device usage, showing the broad and diverse areas of their application in many sectors, such as smart infrastructure, industrial manufacturing, agriculture, healthcare and more. This analysis highlights that many companies in both, the public and private sectors, are using sensors, actuators, cameras, routers and other devices. It then conducts a qualitative analysis of the particular problems that these devices deal with when subjected to challenging climatic conditions, with a focus on the impact of the environment on their performance. The paper illustrates IoT devices that have shown great climate resilience through real-world examples and in-depth qualitative evaluations of effective situations, delivering useful quality lessons for both developers and consumers. Furthermore, the study conducts a qualitative analysis of the elements that manufacturers and developers should consider while developing climate resistant IoT devices.

The evaluation of the importance of quality aspects, such as standards and certifications, in assuring the reliability of IoT devices in various climatic situations is a key aspect of this qualitative study. The paper conducts deep research of these parameters and their influence on device performance, it also emphasises the significance of subjective components of maintenance and protection practises, providing organisations with practical qualitative to overcome severe weather conditions and secure their IoT devices. By looking more closely at these factors, the study aims to find the deeper fundamental factors that affect how resilient and durable devices are. Bringing up the importance of qualitative aspects of maintenance and protection practises shows how important it is to think about not only technological aspects but also subjective features that make IoT devices more durable and make sure they work well even in extreme weather conditions. Over this research, comprehensive interviews with IT professionals from a variety of companies were used to gather data for this study. Open-ended questions were used to get rich and detailed insights. Along with the descriptive information, reports from the sector, case studies, and best practises were also analysed analytically. This created a complete narrative framework for learning about the problems and chances that come with those devices that are resilient to climate change. Besides that, includes qualitative analysis of predicted quality improvements and IoT device applications, taking into consideration changing climatic challenges and technology developments. Remote tracking and predictive maintenance are critical for maintaining the reliability and resilience of IoT devices.  

How to cite: Zhunissova, D., Topping, P. D., and Evans, P. J.: Enhancing Climate Resilience in IoT Devices: Challenges, innovations, and best practices. , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9488, https://doi.org/10.5194/egusphere-egu24-9488, 2024.

Dune ecosystems are among the most vulnerable regions to climate change worldwide. However, studies on how crossing critical aridity thresholds influence the microbiome of these ecosystems remains scarce. These microbes play a pivotal role in shaping terrestrial ecosystem traits and functions.

In this study, we collected 1.4-meter sediment cores at 5 cm intervals from deserts in Xinjiang, China, in two study sites before and after crossing a previously described aridity threshold. We conducted a comprehensive analysis of community diversity and spatial structure, in light of the changes in environmental heterogeneity and autocorrelation, further exploring the community’s differential sensitivity to fluctuations and evidence of state transitions under various states.

The results demonstrate that microbial communities in sand dunes before and after crossing aridity thresholds exhibit distinct vertical ecological niche differentiation patterns under spatial effects. This includes variations in their beta diversity, rarity mode, assembly process, topological properties, and the stability of their networks. This offers new insights into the possible evidence of microbial community state transitions and potential mechanisms in deserts crossing aridity thresholds.

How to cite: Wu, S., Delgado-Baquerizo, M., and Ruan, A.: Microbial evidences of abrupt shifts in dunes ecosystems after passing an aridity threshold, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10113, https://doi.org/10.5194/egusphere-egu24-10113, 2024.

Climate variations during the last glacial period had major impacts on plant and animal populations including humans. Yet, relationships between human population levels and climate through time and across space remain elusive. Here, we used the archaeological radiocarbon dates spanning 50 to 10 ka BP in China to indicate fluctuations in human population sizes, and investigated their correlations with climate variables from paleoclimate proxies and climate model outputs using a Bayesian radiocarbon‐dated event count (REC) statistical model. We find that temperature has a significant positive effect on population in China during 50 – 10 ka, while the sensitivity of population size to temperature exhibits a declining trend over time, suggesting a potential gradual adaptation to cold climates. We further used a global ecosystem model that explicitly simulates human population dynamics, the ORCHIDEE-FOEGE model, to reconstruct human densities during the LGM, and investigated the roles of climate and atmospheric CO2 levels in shaping the distribution of human populations in China.

How to cite: Zhu, D., Lin, Z., and Zhou, J.: Spatiotemporal relationships between human population and climate during the last glacial period in China, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10236, https://doi.org/10.5194/egusphere-egu24-10236, 2024.

Strontium isotope ratios (⁸⁷Sr/⁸⁶Sr) of incrementally grown tissues have been used to study movement and migration of animals. Despite advances in characterizing ⁸⁷Sr/⁸⁶Sr turnover [1], the 2-D geometry of turnover in the tooth enamel is still poorly understood. The relocation of a zoo elephant (Loxodonta africana) named Misha provided an exceptional case study for understanding this pattern [1]. We documented the ⁸⁷Sr/⁸⁶Sr turnover in Misha’s molar using high-resolution in situ measurements with laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS).

We prepared a longitudinally-cut thick section from Misha’s molar plate for LA-ICP-MS analysis. Within the tooth enamel, we measured 10 LA-ICP-MS transects parallel to the enamel dentine junction (EDJ), to map the 2-D pattern of ⁸⁷Sr/⁸⁶Sr turnover. Within the dentine, we measured a transect adjacent to the EDJ to document the unattenuated ⁸⁷Sr/⁸⁶Sr turnover sequence. We also analyzed conventionally drilled enamel samples from the same molar plate using the solution method for ⁸⁷Sr/⁸⁶Sr to document any turnover signal attenuation.

Molar dentine data are consistent with the published Sr turnover pattern in Misha’s tusk dentine. The inner half of the molar enamel preserves the turnover features in high fidelity, with a 2-D turnover geometry closely following that of enamel apposition. By contrast, the middle to outer surface of the enamel shows progressively more elevated ⁸⁷Sr/⁸⁶Sr values than those of the dentine. Data from drilled enamel samples show an attenuated turnover pattern due to averaging during drilling, as well as more elevated ⁸⁷Sr/⁸⁶Sr. We attribute these elevated Sr ratios to post-relocation Sr overprinting primarily on the outer enamel surface during enamel maturation.

Our results suggest that in situ LA-ICP-MS analysis of the inner half of enamel best recovers the time scale and magnitude of the ⁸⁷Sr/⁸⁶Sr turnover in an elephant molar. By contrast, the attenuated and overprinted turnover sequence from conventionally drilled enamel samples may lead to biased interpretations of the timing and geospatial scale of the animal’s movement history. To properly interpret conventionally drilled enamel sequences, future work would benefit from a modeling framework that can account for attenuation, overprint, and turnover of Sr, to quantitatively reconstruct movement or life history of extant and extinct animals. 

References:

[1] Yang, D., Bowen, G. J., Uno, K. T., Podkovyroff, K., Carpenter, N. A., Fernandez, D. P., & Cerling, T. E. (2023). BITS: A Bayesian Isotope Turnover and Sampling model for strontium isotopes in proboscideans and its potential utility in movement ecology. Methods in Ecology and Evolution, 14, 2800–2813. https://doi.org/10.1111/2041-210X.14218

How to cite: Yang, D., Podkovyroff, K., Uno, K., Bowen, G., Fernandez, D., and Cerling, T.: Strontium isotope turnover event mapped onto an elephant molar: implications for movement reconstructions, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12518, https://doi.org/10.5194/egusphere-egu24-12518, 2024.

Increasing conservation efforts are required to avert biodiversity decline caused by climate and land use changes.

In a recent study (Hari et al. in prep), we combined climate change scenarios (RCP2.6 and RCP6.0) and land use change projections to assess their impact on future species distribution for a large number of mammals, birds and amphibians. Future projections of land use change were derived from the Land Use Harmonization dataset v2 (LUH2), which does not make any explicit assumptions about the area under protection in these scenarios.

Here, we extend the scope of our future biodiversity projections by adding new land use scenarios explicitly accounting for different “Nature Futures” in the sense of different levels of biodiversity conservation (i.e., current protected areas or 30x30 target). In the first conservation scenario, we fix the protected areas based on the World Database on Protected Areas (WDPA), thereby assuming that protected areas will remain the same in the future as it is today. In a second category of scenarios, we create land use scenarios compatible with the Global Biodiversity Framework’s “30x30” target based on the spatially optimized dataset by Jung et al. (2021) combined with LUH2.

We then quantify how incorporating different levels of protected areas for conservation change the future species richness based on our land use filtering approach. We also analyze how these two scenarios of land management for conservation interfere with different levels of global warming and what are the implications for the climate resilience of different biodiversity conservation choices.

How to cite: Hari, C., Fischer, M., and Davin, É.: The impact of protected areas on biodiversity conservation under different climate and land use change projections, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12629, https://doi.org/10.5194/egusphere-egu24-12629, 2024.

We identify past human habitat preferences over time to investigate the role of vegetation and ecosystem diversity on hominin adaptation and migration. Using a transient 3-million-year earth system-biome model simulation and an extensive hominin fossil and archaeological database we distinguish in what habitat previous Hominin lived. Our analysis shows that early African hominins predominantly lived in open environments such as grassland and dry shrubland. Hominins adapted to a broader range of biomes by migrating into Eurasia. By linking the location and age of hominin sites with corresponding simulated regional biomes, we also find a preference for spatially diverse environments. Suggesting our ancestors actively sought out mosaic landscapes.

How to cite: Zeller, E., Timmermann, A., Yun, K.-S., Raia, P., Stein, K., and Ruan, J.: Human adaptation to diverse biomes over the past 3 million years, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13260, https://doi.org/10.5194/egusphere-egu24-13260, 2024.

Life-history diversity has been shown to contribute to the resilience of species but can be challenging to quantify, particularly where intra-population genetic structure is lacking. Such is the case for salmon within many fisheries of the North American Pacific Northwest, where the resolution of genetic markers is variable and limited. For Sockeye salmon (Oncorhynchus nerka) within the U.S.-Canada transboundary Taku Watershed, for example, single-nucleotide polymorphisms have successfully distinguished populations associated with specific inland lakes but allocates many individuals to an undifferentiated “River Type” stock. The extent and dynamics of geographic structure within this stock, and thus its potential contribution to the fishery’s resilience, remain unresolved.

In such cases, intrinsic non-genetic markers that record key aspects of life history, such as the isotope ratios of body tissues, can provide valuable information on population structure and diversity. We combined a recently published stream network model for strontium stable isotopes (⁸⁷Sr/⁸⁶Sr) with otolith (ear stone) microchemistry data to infer the geographic natal origins of 45 adult fish captured during the 2019 run. Our analysis was implemented in a Bayesian framework and leveraged radio tag data as a source of prior information. We distinguish 4 previously undifferentiated sub-populations within the River Type stock, characterized by groups of fish with distinct natal ⁸⁷Sr/⁸⁶Sr values and, by inference, natal habitat locations. Although data from additional years will be needed to assess the persistence of these patterns, the result implies potential for previously unrecognized geographic structure within the River Type stock as a contributor to resilience within the population. The lack of genetic differentiation among the subpopulations may suggest that plasticity of habitat use is prevalent and contributes to adaptation. Alternatively, individuals may exhibit strong site fidelity, but differentiation of these sub-populations may be relatively recent or obscured by gene flow. Distinction between these hypotheses should be resolvable by applying the Sr-isotope method to fish recovered across multiple years.

How to cite: Bowen, G., Brennan, K., Brennan, S., and Cline, T.: Decoding Cryptic Population Structures using Stable Isotope Markers, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14207, https://doi.org/10.5194/egusphere-egu24-14207, 2024.

The relationship between initial Homo sapiens dispersal from Africa to East Asia and the orbitally paced evolution of the Asian summer monsoon (ASM)—currently the largest monsoon system—remains underexplored due to lack of coordinated synthesis of both Asianpaleoanthropological and paleoclimatic data. Here, we investigate orbital-scale ASM dynamics during the last 280 thousand years (kyr) and their likely influences on early H. sapiens dispersal to East Asia, through a unique integration of i) new centennial-resolution ASM records from the Chinese Loess Plateau, ii) model-basedEast Asian hydroclimatic reconstructions, iii) paleoanthropological data compilations, and iv) global H. sapiens habitat suitability simulations. Our combined proxy- and model-based reconstructions suggest that ASM precipitation responded to a combination of Northern Hemisphere ice volume, greenhouse gas, and regional summer insolation forcing, with cooccurring primary orbital cycles of ~100-kyr,41-kyr, and ~20-kyr. Between ~125 and 70 kyr ago, summer monsoon rains and temperatures increased in vast areas across Asia. This episode coincides with the earliest H. sapiens fossil occurrence at multiple localities in East Asia. Following the transcontinental increase in simulated habitat suitability, we suggest that ASM strengthening together with Southeast African climate deterioration may have promoted the initial H. sapiens dispersal from their African homeland to remote East Asia during the last interglacial.

How to cite: Ruan, J., Ao, H., Martinón-Torrese, M., Krapp, M., Liebrandh, D., Dekkers, M. J., Caley, T., Jonell, T. N., Zhu, Z., Huang, C., Li, X., Zhang, Z., Sun, Q., Yang, P., Jiang, J., Li, X., Song, Y., Qiang, X., Zhang, P., and An, Z.: Concurrent Asian monsoon strengthening and early modern human dispersal to East Asia during the last interglacial, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14448, https://doi.org/10.5194/egusphere-egu24-14448, 2024.

Plant species and communities’ distribution are remarkably affected by the climate change, particularly in arctic and alpine biomes. In alpine ecosystems, species and communities are shifting upwards due to the temperature increase, seeking for the optimum growth conditions. As a prominent effect, a progressive increase of vegetation cover is leading an alpine greening, with important consequences for the overall plant diversity. Nonetheless, little is known about how this trend may produce different effects along elevation gradients. Innovative upscaling approaches able to link field monitoring evidence to remote sensing data represent a promising tool to get new insights into the ecological mechanisms involved in these changes, and to produce reliable projections over time. This study aimed at parsing the long-term trends of remote sensing-derived vegetation indices in five GLORIA (Global Observation Research Initiative in Alpine Environments) network target regions, located across the Italian Alps and Apennines. Normalized Difference Vegetation Index (NDVI) was calculated for each growing season (June-September) in the period 1985-2022, using Landsat 5 and 8 multispectral satellite images of each mountain summit. Linear mixed-effects models were used to analyze the relationships between NDVI, time and climate variables, in different elevation belts. NDVI linearly increased over the last 37 years, but with significant higher increase rates and values at the treeline, lower alpine and alpine zones, compared to the upper alpine, subnival and nival belts. Moreover, NDVI was significantly affected by temperature at lower altitudes, with a significant interaction with rain precipitations, while climate variables were not determinant at high elevations. These results provided further evidence of the ongoing alpine greening and showed that vegetation at the treeline is responding faster than the other communities to a warmer and drier climate. Therefore, future scenarios depicting the fate of alpine plant community communities should not neglect for the interplay of temperature and precipitation regimes. Our finding opens future perspectives on the interpretation of GLORIA field evidence, in a continental upscaling perspective.

How to cite: Vuerich, M., Boscutti, F., Mosanghini, D., and Trotta, G. and the GLORIA Italian Network team: Using long-term remote sensing series to upscale the vegetation shifts along elevation in the GLORIA network Italian peaks, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18466, https://doi.org/10.5194/egusphere-egu24-18466, 2024.

The increasing relevance of climate change as a threat of species extinction is a pressing concern, as highlighted by the recent IUCN Red List accessment for amphibians (Luedtke et al., 2023). Despite the reported threats of climate change, measuring its influence across species remains complex and lacking the appropiate tools (Cazalis et al., 2022). Changes in "climate niche", referring to the environmental conditions necessary for a species to thrive, have long been discussed and used to predict species distributions and extinctions. Here, we utilize the recently available Red List classifications to test this paradigm within state-of-the-art predictive models of comparative extinction risk. Using historical weather data from the ERA-5 reanalysis, we explore the predictive significance of a wide range of potential definitions of climate niche exceedance. Extinction risk models have consistently identified geographic range size and human population density as important correlates to extinction risk. Also controling for factors such as habitat fragmentation, land use, human preassures, biogeographical realms and biological traits, we use a random forest model to predict the transitions between Red List categories for over 5.000 amphibian species and evaluate results against the official accessments. This approach tests the evidence base of the climate niche paradigm and evaluates its effectiveness as a tool for incorporating climate change into extinction risk models.


Luedtke, J.A., Chanson, J., Neam, K. et al. Ongoing declines for the world’s amphibians in the face of emerging threats. Nature 622, 308–314 (2023). https://doi.org/10.1038/s41586-023-06578-4

Cazalis, V., Di Marco, M., Butchart, S. H. et al., Bridging the research-implementation gap in iucn red list assessments, Trends in Ecology & Evolution (2022).
https://doi.org/10.1016/j.tree.2021.12.002

How to cite: Sarnighausen, C., Kotz, M., Wenz, L., and Vardag, S.: Testing the climate-niche paradigm for species extinction risk, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18850, https://doi.org/10.5194/egusphere-egu24-18850, 2024.

Assessments of the effects of climate change on terrestrial biodiversity typically rely on species distribution models [1] which neither exploit data on historical abundance changes nor consider the potentially important role of climate extremes. Here, we combine global data on the abundance of vertebrate species populations [2] with metrics of exposure to local climate conditions to demonstrate that historical warming and increased exposure to heat, heavy precipitation extremes and drought have had significant impacts on abundance, even after controlling for changing human pressures. Fixed-effects models reveal plausibly causal impacts which vary by species class and habitat system, as well as by latitude and the extent of human pressure. Results indicate that warming and intensified heat extremes have negative impacts at low latitudes for freshwater fish and terrestrial birds. By contrast, warming can bring benefits to freshwater birds and terrestrial mammals. Heavy precipitation extremes and drought appear to have had mainly negative impacts on abundance across species’ and habitats. We then combine these empirical results with estimates of the changes in climate conditions and extremes which are attributable to anthropogenic influence, using an established impact-attribution framework [3]. This approach reveals that anthropogenic climate change has caused considerable alterations to the abundance of terrestrial life, for example by reducing the abundance of terrestrial birds and freshwater fish by up to 40% at low latitudes.

[1] Thomas, Chris D., et al. "Extinction risk from climate change." Nature 427.6970 (2004): 145-148.

[2] Loh, Jonathan, et al. "The Living Planet Index: using species population time series to track trends in biodiversity." Philosophical Transactions of the Royal Society B: Biological Sciences 360.1454 (2005): 289-295.

[3] Mengel, Matthias, et al. "ATTRICI v1. 1–counterfactual climate for impact attribution." Geoscientific Model Development 14.8 (2021): 5269-5284.

How to cite: Kotz, M., Amano, T., Watson, J., and Wenz, L.: Anthropogenic intensification of climate extremes has altered vertebrate species abundance, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19008, https://doi.org/10.5194/egusphere-egu24-19008, 2024.

Exploration of the paleobiology of extinct taxa through ancient DNA and proteomics has been largely limited to Plio-Pleistocene fossils due to molecular breakdown over time, a problem exacerbated in tropical settings. Here, we report small proteomes from the interior enamel of fossils deposited at paleontological sites dating between 29–1.5 Ma in the Turkana Basin, Kenya, which has produced the richest record of Cenozoic mammal evolution in eastern Africa. We recovered enamel protein fragments in all sampled fossils, including a ~ 29 Ma Arsinoitherium specimen belonging to an extinct mammalian order, Embrithopoda. Identified proteins include the classical structural enamel proteins amelogenin, enamelin, and ameloblastin, but also less abundant enamel proteins including collagens and proteases. Protein fragment counts decline in progressively older fossils, but we observe significant variability in Early Miocene preservation across sites, with ~17 Ma deinothere and elephantimorph proboscidean fossils from Buluk preserving substantially more proteins than rhinocerotid and anthracotheriid fossils from ~18 Ma Locherangan and hippopotamids from younger localities at Napudet (< 11 Ma). Most specimens yield known clade-specific diagenetiforms that support morphology-based taxonomic identifications. Matches to clade-specific proteins suggest the future potential of paleoproteomics to contribute to the systematic placement of extinct taxa, but should be approached with caution due to sometimes sparse fragment identification and the possibility of sequence diagenesis. We identify likely modifications that support the ancient age of these proteins, and the oldest examples of advanced glycation end-products and carbamylation yet known. The discovery of protein sequences within dense enamel tissues in one of the persistently warmest regions on Earth promises the discovery of far older proteomes that will aid in the study of the biology and evolutionary relationships of extinct taxa.

How to cite: Green, D., Uno, K., Miller, E., Feibel, C., Aoron, E., Beck, C., Grossman, A., Kirera, F., Kirinya, M., Leakey, L., Liutkus-Pierce, C., Manthi, F., Ndiema, E., Nyete, C., Rowan, J., Russo, G., Sanders, W., Smiley, T., Princehouse, P., Vitek, N., and Cleland, T.: 29 million years of diverse mammalian enamel proteomes from Turkana in the East African Rift System, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-21192, https://doi.org/10.5194/egusphere-egu24-21192, 2024.

Issues related to whether climate change have caused great calamites in human society are of fundamental importance to current climate change research. The causes and ecological consequences of climate change can, of course, be measured at different levels according to different scales because the natural sciences have long understood the verification of causality and importance of scale. Research regarding human responses to climate change in the humanities and social sciences has been less explicit, less precise, and more variable. The growing need for interdisciplinary work in the issues across the natural/social science boundary (gap), however, demands some common understandings about the causality and scaling issues on climate impact. We seek to facilitate the dialogue between natural and social scientists by reviewing some of the fundamental aspects of the philosophical concepts of causality and scale that can be employed in the climate change/human response study, especially as they relate to large scales of the human responses to ever-changing global climate in history. Here we present the common philosophical concepts of causality and scale in natural sciences and social sciences, examine how researchers in the field employ the philosophical concepts to verify the relationship between human societies and climate change using various samples with multiple scales and explore how to connect and break the links between climate change, human calamites and resilience at different levels of hierarchies. 

How to cite: Zhang, D. D.: Scale and Causal inference: from philosophical concepts to empirical verification in relationship between climate change and social responses., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-21871, https://doi.org/10.5194/egusphere-egu24-21871, 2024.

Seasonal variations in climatic variables, and the resulting changes in vegetation, are strong factors governing ecosystem dynamics in modern and ancient times. Stable isotope ratios recorded in tooth enamel document isotopic variations in the environment at the time of enamel formation and thus reveal the intensity and duration of seasonal dietary and climatic variations. However, the long and multi-phased process of enamel mineralization causes a dampening of the original input signal. An inverse model previously developed for ever-growing canines of Hippopotamus amphibius proposes to recover the original input signal and assumes constant enamel growth rate, appositional angle, and maturation length. The present study aims to test these assumptions. To do so, we integrated data from histological thin sections, microtomodensitometric analyses, and stable isotope analyses on teeth of extant H. amphibius specimens (3 upper canines, 1 lower canine, 1 third molar) to quantify the geometric and temporal patterns of enamel mineralization. To estimate enamel extension rates (EER, in µm/increment), we counted the number of increments representing the position of appositional front for each segment of 5 mm along the enamel-dentine junction in thin sections made along the growth axis of each tooth. We used microtomodensitometry to determine the pattern of enamel maturation using grey values profiles of X-ray radiographies as a proxy for enamel mineralization degree. Serial sampling along one upper canine of an individual from Chad, coming from an environment with one rainy season per year, allowed us to document the intra-tooth d¹³C and d¹⁸O variations over 6 years and thus provided an independent temporal control on histological variations. The histological study showed that the enamel apposition phase is strongly irregular over time within the canines, with no clear temporal trend. EERs vary strongly among teeth and within each tooth (50-200 µm/increment, 100-350 µm/increment, and 80-200 µm/increment for the 3 upper canines; 150-550 µm/increment for the lower canine; 70-130 µm/increment for the third molar). The median EER value from the upper canine of the juvenile individual (ca. 180 µm/increment) is significantly higher than median EER values from the upper canines of two adult individuals (ca. 110 µm/increment). Similar variations are also observed in apposition angles (3°-8°, 2.5°-4.5°, 3°-7° for the 3 upper canines; 2°-8° for the lower canine; 6°-18° for the third molar). The enamel mineralization parameters vary with age and tooth type (canine vs. molar). Based on strongly correlated seasonal variations in d¹³C and d¹⁸O, we also confirm cyclic dietary variations with higher proportions of C₄ plants consumed during the dry seasons. Using the range of enamel mineralization parameters observed within one single hippo canine, we conducted sensitivity tests on the inverse modeling method, producing different modeled input signals that suggest a wider range of uncertainty. In conclusion, the documented intra-canine variability of EER, as well as other histological parameters (apposition angle, maturation length), reveals challenges when applying the current inverse model to wild populations. Future work would benefit from a systematic histological investigation into the sources of variation of enamel growth and mineralization patterns. 

How to cite: Souron, A., Couvrat, M., Pubert, É., Santos, F., Yang, D., Frémondeau, D., Nékoulnang, C., and Otero, O.: Variable enamel growth rates in hippopotamid canines: Implications for seasonality reconstructions using inverse modeling of intra-tooth isotope data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-22198, https://doi.org/10.5194/egusphere-egu24-22198, 2024.

With the evolution in climate, heat waves are occurring more commonly which leads to imply indoor temperatures. Several temperature thresholds have been suggested in diverse environments for the indication of indoor overheating. In this study, threshold values for perceived heat stress are evaluated and differentiated between susceptible households and non-susceptible households for the residents of Faisalabad in Pakistan. Data from 52 low to middle-income households were analyzed with the help of regression analysis, t-tests, and analysis of variances to discover characteristics associated with perceived heat stress during the nighttime period in the selected houses. We considered socio-demographic characteristics, health-related queries, heat-related health problems, and house/building material variables from the selected households. The results suggest that the health status during heat stress, age factor, climate zone, and high indoor temperature were the key attributes for the perceived heat stress. The threshold limit advised by the WHO for indoor is 24°C and most of the dwellers in case study live in 36-38°C. People appeared to be at risk for perceived heat stress without knowing to be at risk, particularly when numerous people live in one room (threshold limit 34.8^◦C), suffering from disease (35.6 ^◦C) and below 60 (39.8 ^oC); therefore they do not take it seriously, to take adaption measures.

How to cite: Ibrahim, M., Ehsan, S., and Abbas, F.: Estimate Temperature Threshold for Low to Middle-Income Dwellers of Faisalabad City during Hot Summer Days, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-384, https://doi.org/10.5194/egusphere-egu24-384, 2024.

Air pollution, the largest global environmental health threat, associated with millions of premature death each year, is getting worse with climate change. To protect their health from air pollution, governments encourage people to stay indoors and avoid high pollution episodes. Moving indoors to reduce exposure to outdoor air is a form of avoidance adaptation. The frequency of this adaptive action can affect the amount of time people spend inside buildings. In Europe and North America, people already spend 90% of their time indoors. Air pollution from outdoors can infiltrate the building envelope, exposing people to pollution of outdoor origin at all times, and reducing the value of avoidance adaptation. To better understand the effect of this infiltration on human health, we examine the impact of building standards on the value of avoidance adaptation. This involves considering the costs of improving building envelopes and ventilation, and associated benefits due to avoided premature death from air pollution exposure. We conduct a historical study in the United States from 1980 to 2010 to examine the spatial and temporal patterns of costs and benefits associated with improving building standards to enhance adaptation to air pollution. This includes investigating past missed opportunities in reducing mortality and laying the foundation for future studies on existing long-term opportunities, all within the context of a changing climate. To achieve this, we establish baseline levels of exposure to the most harmful air pollutant, fine particulate matter, under this historical building stock across the United States. Subsequently, we assess the benefits and costs realized under each building standard improvement scenario (Improved Building Envelope and Improved Ventilation). This study will identify the demographics that can benefit the most from these improvements, quantifying, for example, the potential net gains of improving housing quality for low-income communities. It will address open questions on the value of adaptation in protecting human health under increasing risks from a changing climate.

How to cite: Salehi, A. R., Sparks, M., and Saari, R.: Hidden Health Opportunities: The Role of Building Standards in Adapting to Air Pollution in a Changing Climate, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-783, https://doi.org/10.5194/egusphere-egu24-783, 2024.

Community-acquired pneumonia (CAP) is one of the most frequent causes of death among infectious diseases worldwide. Analyzing a dataset of 5,223 CAP patients in a German multicenter cohort study, our research uniquely explores the twofold combined impact of meteorological conditions, air quality conditions, and pre-existing chronic obstructive pulmonary disease (COPD) on CAP admissions. Both the twofold compound effect of absolute values of meteorological and air quality conditions and, even more, their day-to-day changes significantly influence CAP admissions. Our study emphasizes the important role of air quality conditions over meteorological conditions in contributing to increased CAP admissions, with these weather conditions exerting their influence with a lag time of approximately three to four days. Individuals with pre-existing COPD face the highest risk of CAP admission in the general cohort. The implications of our findings extend to supporting at-risk individuals through protective measures and providing healthcare providers with valuable insights for resource planning during pneumonia-inducing weather conditions.

How to cite: Brenner, T., Link, A.-C., Reudenbach, C., Bendix, J., Weckler, B., Pott, H., Rupp, J., Witzenrath, M., Rohde, G., Pletz, M., Bertrams, W., and Schmeck, B.: Combined Impacts of Weather Conditions and COPD on the Risk for Community-Acquired Pneumonia, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1878, https://doi.org/10.5194/egusphere-egu24-1878, 2024.

Background: Increased attention has been paid to humid-heat extremes as they are projected to increase in both frequency and intensity. However, it remains unclear how compound extremes of heat and humidity affects morbidity when the climate is projected to continue warming in the future, in particular for a megacity with a large population.

Methods: We chose the Wet-Bulb Globe Temperature (WBGT) index as the metric to characterize the humid-heat exposure. The historical associations between daily outpatient visits and daily mean WBGT was established using a Distributed Lag Non-linear Model (DLNM) during the warm season (June to September) from 2013 to 2015 in Shanghai, a prominent megacity of China. Future morbidity burden related to the combined effect of high temperature and humidity were projected under four greenhouse gases (GHGs) emission scenarios (SSP126, SSP245, SSP370 and SSP585).

Results: The humid-heat weather was significantly associated with a higher risk of outpatient visits in Shanghai than the high-temperature conditions. Relative to the baseline period (2010–2019), the morbidity burden due to humid-heat weather was projected to increase 4.4% (95% confidence interval (CI): 1.1% –10.1%) even under the strict emission control scenario (SSP126) by 2100. Under the high-GHGs emission scenario (SSP585), this burden was projected to be 25.4% (95% CI: 15.8% –38.4%), which is 10.1% (95% CI: 6.5% –15.8%) more than that due to high-temperature weather. Our results also indicate that humid-hot nights could cause large morbidity risks under high-GHGs emission scenarios particularly in heat-sensible diseases such as the respiratory and cardiovascular disease by the end of this century.

Conclusions: Humid heat exposures significantly increased the all-cause morbidity risk in the megacity Shanghai, especially in humid-hot nights. Our findings suggest that the combined effect of elevated temperature and humidity is projected to have more substantial impact on health compared to high temperature alone in a warming climate.

How to cite: Liang, C., Yuan, J., Tang, X., Kan, H., Cai, W., and Chen, J.: The influence of humid heat on morbidity of megacity Shanghai in China, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2325, https://doi.org/10.5194/egusphere-egu24-2325, 2024.

Climate change is expected to substantially alter biodiversity, leading to alterations in phenology, genetic composition, and species distribution while also affecting species interactions and ecosystem. Invasive alien species (IAS) have threatened the integrity of ecosystems throughout the world. They affect the species diversity of native ecosystems and threaten their biological integrity. Due to increasing movement of people and goods around the world, and with new trade routes opening and enhanced transportation, the number of species being introduced into new areas is rising. IAS reduce agricultural yields, irrigated croplands, grazing areas, and water availability, and contribute to the spread of mosquito-borne diseases. Mosquitoes are widely spread Mosquitoes are widely spread and transmit malaria and several arthropod-borne viruses. A particular example of IAS is Parthenium hysterophorus (Asteraceae). It is one of the world's most serious invasive plants that is able to thrive and spread aggressively outside its original geographical areas. Native to the subtropics and tropics of North and South America, Parthenium has negative effects on human, livestock, agriculture and the environment. The aim of this study is to determine the abundance and diversity of mosquito vectors at sites with different degrees of invasive plant infestations in the Rift valley area in Kenya. Currently, the spread of invasive plant species is a major problem in Kenya, where indigenous flora is replaced. The study sites are located in Baringo county. A total of 50000 mosquitoes were captured using a combination of different trapping techniques from six sites, three of them with IAS (Parthenium) and three without. We identified 48 species. A subset of 1000 mosquitoes was analyzed for evidence of recent plant feeding using cold anthrone test. An overall low fructose positivity rate (10.9%) was found. Barcode technique was applied to identify plant food source using specific primers for a locus from the chloroplast genome, ribulose diphosphate carboxylase. The DNA from all trees or shrubs within a 100m radius from the trap was collected to build a barcode reference library. Plant DNA with 55.3% (n = 553) success rate was identified. Sequences were successfully generated from samples, indicating Parthenium plants as the predominant plant fed by mosquito vectors. This survey is an inventory of the mosquito population composition and of the abundance and richness of arboviruses. It provides an insight into how changes in community ecology interact with the main types of land-use change and influence the dynamics of relevant arboviruses in Kenya. Thus, it provides a beneficial knowledge for targeted control.

Keywords

Climate change, land-use changes, agricultural expansion, infectious diseases, mosquito ecology, invasive plants, Parthenium hysterophorus

How to cite: Osman, T., Fevre, E., and Borgemeister, C.: Land-use management of invasive species could help prevent spread of mosquitoes borne diseases: Evidence from Kenya  , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3257, https://doi.org/10.5194/egusphere-egu24-3257, 2024.

Development of innovative tools for real-time monitoring and forecast of environmental health impacts is central to effective public health interventions and resource allocation strategies. Though a need for such generic tools has been previously echoed by public health planners and regional authorities responsible for issuing anticipatory alerts, a comprehensive, robust and scalable real-time operational framework for predicting temperature-related excess deaths at local scale has not been developed yet. Filling this gap, we propose a flexible conceptual framework for coupling publicly available operational weather forecasts with temperature-mortality risk functions specific to small census-based zones, the latter derived using state-of-the-art environmental epidemiological models. Utilising high-resolution temperature data forecast by a leading European meteorological centre, we demonstrate a real-time application to forecast the excess mortality during the July 2022 heatwave over England and Wales. The output by way of expected temperature-related excess deaths at small geographic areas on different lead times, can be automated to generate maps at various spatio-temporal scales, thus facilitating preventive action and allocation of public-health resources in advance. While the real-case example discussed here demonstrates an application for predicting (expected) heat-related excess deaths, the framework can also be adapted to other weather-related health risks and to different geographical areas, provided data on both meteorological exposure and the underlying health outcomes are available to calibrate the associated risk functions. The proposed framework addresses an urgent need for predicting the short-term environmental health burden on public health systems globally, especially in low- and middle-income regions, where rapid response to mitigate adverse exposures and impacts to extreme temperatures are often constrained by available resources.

How to cite: Mistry, M. N. and Gasparrini, A.: Real-time forecast of temperature-related excess mortality at small-area level: A conceptual framework, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3476, https://doi.org/10.5194/egusphere-egu24-3476, 2024.

Background and aims: Climate change is expected to increase the frequency and severity of monsoon floods in south-east Asia and will severely impact food and nutrition security. The Food and Agricultural Approaches to Reducing Malnutrition (FAARM) cluster-randomized controlled trial in rural Bangladesh, aimed to improve nutrition outcomes through a Nutrition-Sensitive Agriculture (NSA) intervention. We evaluated the role of the intervention in moderating the impact of seasonal flood exposures on women’s dietary diversity (WDD) and food group consumption.

Description and recommendations: Using Bayesian interaction models, we paired a time series measure of seasonal flooding with high-frequency dietary data collected bi-monthly from 2,701 women throughout the trial (2015-2019). We found that for a 1% increase in flooding in Mar/Apr, subsequent WDD decreased by 18% of a food group in the control-arm, with no detrimental effect observed in the treatment-arm. Of the food groups, vitamin-A-rich foods (VA) was most influenced by seasonal flooding. The odds of consuming VA are normally 41% higher in the May/June months. However, for every 1% increase in flooding in Mar/Apr, the odds of consuming VA in May/June only increases by 13% for the control-arm, and by 27% for the treatment group.

Significance: Flooding has a variable impact on WDD and food consumption, and the NSA intervention appeared to offset the detrimental effects of flooding on WDD in the most volatile season. This study highlights the sensitivity of diets to changing monsoon patterns and provides an approach to evaluating the impacts of interventions on these intricate pathways.

How to cite: Offner, C., Sparling, T. M., Dooley, C., Waid, J., Gabrysch, S., and Kadiyala, S.: How seasonal flooding affects diets in Bangladesh during a nutrition-sensitive agriculture intervention., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3881, https://doi.org/10.5194/egusphere-egu24-3881, 2024.

Anthropogenic emissions are responsible for deteriorated air quality and accelerated climate change in developing countries like India. The current trajectory of emissions is expected to further degrade air quality, potentially leading to increased warming levels by the end of the century, posing severe consequences for public health. In this study, we analyzed two scenarios using the GAINS-model framework - the business-as-usual (BAU), relying on existing air pollution control policies and measures, and the sustainable development scenario (SDS), integrating advanced air pollution control policies and measures, aiming to contain the global temperature increase below 2°C by 2100. We estimated the health burden attributable to ambient air pollution in BAU and SDS scenarios, segregated into regional and sectoral emissions in India for the years 2030 and 2050. Under the BAU scenario, premature mortality and disability-adjusted life-years (DALYs) are projected to increase from 0.72 million (95% CI: 0.53-0.89) and 24.8 million (15.4-30.5) in 2015 by 9.7% and 2.4% in 2030, respectively. In 2050, mortality and DALYs are projected to further increase to 0.88 million (0.75-1.01) and 26.2 million (22.8-29.6). At the sub-national level, states with a low Socio-demographic Index (SDI) are expected to possess majority (49-53%) of the health burden. However, if India follows the SDS scenario, 0.16 million (0.14-0.18) lives and 3.7 million (3.2-4.3) DALYs can be avoided in 2030. The corresponding benefits in 2050 will be 0.34 million (0.29-0.39) lives and 8.4 million (7.1-9.7) DALYs, respectively, relative to the BAU scenario. Our results reveal that states with a high SDI would experience the most significant benefits (15% and 26% for mortality & 26% and 44% for DALYs in 2030 and 2050), as compared to middle and low SDI states. The findings underscore the importance of immediate adoption of cost-effective and advanced technologies driven by sustainable development policies is imperative to mitigate air pollution and climate change simultaneously. A stronger mandate to revise the environmental standards and health policies is necessary to maximize health benefits in India. 

How to cite: Sarkar, D., Dey, S., Purohit, P., and Chowdhury, S.: Health Benefits of Meeting 2-degree Warming Scenario in India, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5480, https://doi.org/10.5194/egusphere-egu24-5480, 2024.

The concurrent rise in global temperatures and air pollution levels has raised concerns regarding their joint effects on human health. Heatwaves, exacerbated by climate change, have become more frequent and intense, posing significant health risks to vulnerable populations. Concurrently, air pollution, stemming from anthropogenic activities and environmental factors, contributes to respiratory and cardiovascular ailments, amplifying the health burden.

It becomes important to utilize multifaceted data from climate models, demographic and socioeconomic projections like the Shared Socioeconomic Pathways (SSPs), geographical information and other pertinent datasets in exploring the complex relationship between climate change, exposure to air pollution, extreme heat and related health outcomes. Using various data sets including climate, demographic, and socioeconomic information at different scales (cohort, city, and small area levels), the recently concluded EU Horizon 2020 EXHAUSTION project quantified the synergetic effects of exposure to extreme heat and air pollution on mortality risks for respiratory and cardiovascular diseases. The project also investigated the influence of various vulnerability factors (e.g. socioeconomic conditions, access to green space) on the health risks. The heat-health burden was projected under future scenarios until 2100, taking into account shifting demographic patterns and baseline health status in various scenarios.

We advocate for the extension of methodologies employed in EXHAUSTION to encompass low- and middle-income countries in South Asia and sub-Saharan Africa, where extreme occurrences of heat and air pollution prevail. The assessment of climate change impacts on human health in these regions is notably challenging due to the scarcity of data across various domains, encompassing health, climate, and socio-demographic information. We advocate for enhanced accessibility and availability of this data to deepen our understanding of the effects of climate change-induced extreme heat and air pollution on mortality and morbidity in LMICs. This improved access will better equip health officials to strategize interventions and bolster adaptation responses. Furthermore, there is a need for more detailed emission and socio-demographic projections in LMICs, underpinned by data and reflective of current trends.

How to cite: Aunan, K.: Connecting climate change and health to protect the most vulnerable, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6687, https://doi.org/10.5194/egusphere-egu24-6687, 2024.

Prague is the capital and the largest city of the Czech Republic and its historic centre near the Vltava river is a popular tourist destination. Especially the area along the right bank of the Vltava river, called Náplavka, is one of the most popular locations to visit during the summer months due to many social and cultural events that take place here. However, given the north-south orientation of the Vltava river and the lack of greenery and shade in this area, the question arises as to what extent thermal conditions are comfortable during hot summer days at Náplavka. Many previous studies have shown that the presence of greenery and shade is essential for reducing the heat stress in the streets.

In this study we assessed the effect of shading on biometeorological conditions at eight different measuring sites located along a loop between Charles Square and the Náplavka riverbank. Meteorological parameters (including air temperature, relative humidity, wind speed, Heat Index, Wet-Bulb Globe Temperature) were measured and recorded using the Kestrel 5400 portable tool, every two hours between 8:00 a.m. and 6:00 p.m. CEST on 9 days during summer in 2019 and on 5 days in 2022. In addition, fisheye photographs were taken at each location to quantify the effect of shading. From these data, we calculated advanced thermal comfort indices (Physiologically Equivalent Temperature, Universal Thermal Climate Index) and Sky View Factor (SVF) in the RayMan Pro program. We compared measured data from all sites under different weather conditions between 2019 and 2022, and assessed the evolution of heat stress during the day as a function of shading at each site.

Our results showed that while in the morning Náplavka’s biometeorological conditions were most comfortable among all measurement sites, they became most stressful in the afternoon. The analysis of the fisheye images showed that the lack of greenery and shading at Náplavka contributed significantly to the high heat stress levels. Our results suggest that the relocation of day-long events from Náplavka to other locations (e.g. a park at Charles Square) should be considered and/or adequate sun protection should be provided on hot summer days.

How to cite: Chlapcová, L., Urban, A., and Kyselý, J.: The role of shading on biometeorological conditions in the historic centre of Prague, Czech Republic., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6696, https://doi.org/10.5194/egusphere-egu24-6696, 2024.

Heat stroke is a serious heat-related health outcome that can eventually lead to death. Due to the poor accessibility of heat stroke data, the large-scale relationship between heat stroke and meteorological factors is still unclear. We collected daily heat stroke search index and meteorological data for the period 2013–2020 in 333 Chinese cities to quantify the threshold of people may suffer from heat stroke by Random Forest model. When the daily mean temperature exceeded 23.5°C, heat stroke cases may occur in China. Then, we calculated the total heatwave duration exceeding the threshold quantified aforementioned and population exposure to heatwave in China using four scenario combinations, namely SSP1SSP1-2.6, SSP2SSP2-4.5, SSP3SSP3-7.0, SSP5SSP5-8.5, for 1986-2005, 2041-2060 and 2081-2100 periods.

How to cite: Han, Q.: Heat stroke risk in China quantified by web-based data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7407, https://doi.org/10.5194/egusphere-egu24-7407, 2024.

In temperate climates, influenza follows a seasonal pattern with peak incidence in winter and contributes significantly to excess winter mortality. The relationship between weather variability, influenza and human health is complex and the underlying mechanisms remain unclear. This study investigated the links between meteorological variables, influenza epidemics, and mortality in the Czech Republic over the 1982/83 to 2019/20 epidemics seasons. Results showed that severe influenza outbreaks with largest mortality impacts, primarily driven by A/H3N2 viruses, were preceded by falling temperatures, increasing relative humidity and cloud cover, and low air temperatures, high cloud cover and high relative humidity prevailed for their duration. In contrast, A/H1N1-related epidemics with lower mortality impacts occurred usually during periods of average or above-average temperatures, accompanied by elevated relative humidity and cloud cover. Influenza epidemics peaking later in winter or in early spring were associated with high excess mortality, usually lasted longer and were accompanied by prolonged periods of low temperatures. The results highlight the importance of ambient temperature and other weather variables in the transmission of influenza virus and course and severity of the epidemics. Prolonged periods of low temperatures in winter, together with the prevalence of influenza A/H3N2 in the population, were identified as an important contributing factors to the significant excess mortality in the temperate climate of central Europe.

How to cite: Hanzlíková, H., Urban, A., Plavcová, E., Kynčl, J., and Kyselý, J.: Weather, influenza epidemics and mortality patterns in central Europe, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7794, https://doi.org/10.5194/egusphere-egu24-7794, 2024.

Air quality and surface temperature exert significant influences on human health. However, the impact of air pollution and non-optimal temperature is not uniformly experienced across the population. In this study, we employ the "Gini" coefficient, a commonly used concept in economics. While traditionally applied to represent wealth inequality, we adapt this coefficient to gauge spatial inequality in population exposure to air pollutants and temperature, irrespective of the economic income of the population. As pollution and temperature are dynamic and subject to change in the future due to varying climate change and socioeconomic scenarios, our analysis extends to potential scenarios projected by the Coupled Model Intercomparison Project (CMIP6). We show changes of the Gini coefficient both at global, regional and country scale for the present century (2000-2100) covered by the model simulations. Our findings indicate that at global level, air quality inequality has peaked around the present time, with a trend towards decreasing inequality in most projections, reaching a minimum by the end of the century. Conversely, temperature exposure inequality will fluctuate based on the scenario, primarily showing an increasing inequality trend over time in alignment with anticipated climate change impacts. Importantly, the Gini coefficient estimation provides a complementary view to air quality and climate change assessment, indicating exposure disparities among the population in a specific region. Our study shows the unequal distribution of air quality and temperature exposure among populations, emphasizing the need for targeted interventions and policies to address these disparities, especially considering the projected changes in climate and socioeconomic factors.

How to cite: Pozzer, A., Chowdhury, S., Ma, L., and Steffens, B.: Inequality in the exposure to air pollution and temperature through the century, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8031, https://doi.org/10.5194/egusphere-egu24-8031, 2024.

Urbanization and global warming have led to the emergence of urban heat islands, profoundly impacting the liveability and long-term well-being of people living in cities. This study investigates the impact of urban green space composition and configuration on stress and sleep quality in Leuven, Belgium, during the summers of 2021 and 2022.

Utilizing three validated stress questionnaires (PSS, PSQI, and HSSI), we assessed mental health, sleep quality and heat stress during 4 heat and 4 control events for 785 respondents. Concurrently, we recorded risk and vulnerability factors related to physical sensitivity, socio-economic sensitivity and personal living space for each respondent. Urban land cover data at 50m and 250m buffer scales were analysed using composition and configuration metrics. Structural equation models were employed to investigate the impact of urban green space on stress and sleep quality during both heat and non-heat control events. Models were adjusted for risk and vulnerability factors, and effectively dealt with spatial autocorrelation inherent in our data.

During control events, mental health, sleep quality and heat stress were predominantly associated with risk and vulnerability factors. High physical sensitivity, elevated socio-economic sensitivity and suboptimal personal living spaces were associated with higher physiological stress, poor sleep quality, and higher heat stress. Conversely, during heat events, stress indicators were predominantly associated with the surrounding green space, while associations with risk and vulnerability factors were limited. Augmenting high green relative cover may mitigate heat stress, while increasing low green cover may alleviate both heat stress and enhance sleep quality. Stratified analyses for socio-economic status and distinct urban-rural regions revealed notable differences among subgroups.

In conclusion, this study emphasizes the importance of incorporating both low and high green spaces to mitigate heat stress and improve sleep quality and therefore, human health, during heat events.

How to cite: Beele, E., Aerts, R., Reyniers, M., and Somers, B.: Residential green space and summer heat stress: a repeated cross-sectional study, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9746, https://doi.org/10.5194/egusphere-egu24-9746, 2024.

Native to tropical and subtropical regions of Southeast Asia, Aedes albopictus, commonly known as the tiger mosquito, has been spreading worldwide with the aid of human activity. The geographical distribution and temporal dynamics of this mosquito are of special interest, given its role as a vector for arboviruses such as dengue (DENV) and chikungunya (CHIKV). Climate change, and its consequent increase in ­­both mean surface temperatures and the frequency and intensity of heat waves, has the potential to affect the behavior and seasonal activity of this mosquito, thereby posing a significant risk to human health. Understanding the impact of mean temperature changes and extremes on potential vector-borne disease risk is paramount to forecasting future trends as well as developing meaningful intervention strategies.

In this work, we study the dynamics of Ae. albopictus over three decades, spanning 1990-2019, with a particular emphasis on the Italian Peninsula, which has remained a significant hotspot in Europe, since its introduction in the 1990s. We employed and adapted VECTRI, a climate-sensitive dynamical model that was originally designed for malaria. The model has been modified to parameterize Ae. albopictus and successfully calibrated to reproduce the seasonality of the vector using ovitrap data from various locations in Italy. Driving the model using high resolution EOBS gridded observation data, we perform various experiments to isolate the impact of temperature trends and late-spring to summer temperature extremes. Our results show a temperature-driven linear increase in the length of the mosquito season, with larger increases over the southern regions. Overall, temperature extremes tend to increase the bulk egg population across the country, although different spatial trends are highlighted: warm events tend to reduce vector populations in the Po valley and southern regions of Italy,already subject to the highest temperatures, while they tend to increase vector abundance over fringe highland areas. Our results indicate that 10-day temperature forecasts could be utilized to predict mosquito activity and consequently guide vector control intervention strategies such as insecticide spraying in the higher altitude regions identified in this study.

How to cite: Garrido Zornoza, M., Caminade, C., and Tompkins, A.: Reacting to climate change and temperature extremes: A case study on the tiger mosquito in Italy­, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10908, https://doi.org/10.5194/egusphere-egu24-10908, 2024.

Copernicus is the Earth observation component of the European Union’s Space programme, looking at our planet and its environment to benefit all European citizens.

The Copernicus services transform a wealth of satellite and ground-based measurements into value-added information by processing and analysing the products.

All the information is provided with an open and free data policy to help public national and European authorities, policy makers, international organisations, and service providers to improve European citizens' quality of life.

There are six operational Copernicus Services covering the whole Earth System including ocean, land, atmosphere, and more horizontal domains such as climate change, emergency and security.

To facilitate the use of these information by the different user communities, some Thematic Hubs have been created and are under development. One of the first hubs is the Copernicus Health Hub (CHH) and it is focusing on the health community.

The CHH collects and provides all the Copernicus environmental information that are pertinent to Health, following the WHO definition: Physical, Mental and Well-being. The Health Hub is also supporting the users in better exploiting and uptake Copernicus data and products (via documentation, access to catalogues, inspirational use case stories, …). In addition, the CHH should collect new requirements for the evolution of the Copernicus programme.

In this presentation, the CHH will be introduced in more details, the different types of environmental information will be presented accompanied by some use cases to inspire further developments and new applications for the health community.

How to cite: Letertre, J., Borger, C., Ananasso, C., and Peuch, V.-H.: Copernicus Health Hub: Health community accessing environmental information from the Copernicus Programme, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11803, https://doi.org/10.5194/egusphere-egu24-11803, 2024.

Today’s cities face many challenges, including those related to climate change, energy efficiency, and human well-being. These issues are closely linked to the thermal dynamics of the built environment. Sub-optimal solutions and increased vulnerability often result from a lack of deep understanding of the spatial and temporal variations of thermal interactions in the urban context, particularly in data-limited regions. The primary objective of this thesis is to develop a methodology for creating "as-built" digital thermal models through 3D reconstruction of urban scene objects such as buildings, trees, and pavements. The coupling of 3D geometry and TIR (Thermal Infra-Red) acquisitions at different periods enhances the semantic richness of the model and facilitates the study of building-tree thermal interactions. This, in turn, enables the calculation and the monitoring of the evolution of thermal comfort indices at a micro-scale (<2km). To this end, the TRIO team has developed LASER/F (Latent And Sensible Radiation Fluxes), a microclimate simulation software that can replicate the effect of buildings and trees on the urban microclimate. The buildings and trees of interest are modeled with a high level of detail (LOD3) to improve the accuracy of the simulations. The simulated thermal model will be evaluated using "real" thermal and eco-physiological data collected in the field. The validated model will be used to simulate various scenarios for improving thermal comfort, making it a valuable decision-making tool for urban planning. The study will be conducted at two sites, one in Strasbourg (France) and the other in Rabat (Morocco). This study aims to analyze, compare, and improve LASER/F simulations at two sites, in two different countries and climates. The goal is to assess the impact of existing vegetation configurations and propose scenarios for improving thermal comfort. This may include changes to tree species or positions and the modification of urban geometry. Measurement campaigns have been carried out at the Strasbourg site during the summer of 2023. Fixed environmental measurements such as wind speed, relative humidity, global radiation, and sap flow were carried out. 3D geometry acquisitions were performed using laser scanners. TIR data was also acquired thanks to thermal cameras at fixed positions and thermobuttons located on facades. Moreover, a mobile system composed of RGB (Red Green Blue) cameras and a TIR camera has been specifically designed. Similar campaigns are planned for the Rabat site in 2024.

How to cite: Delasse, C., Hajji, R., Landes, T., Macher, H., Kastendeuch, P., and Najjar, G.: Digital thermal 3D model for thermal comfort analysis at district scale., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12490, https://doi.org/10.5194/egusphere-egu24-12490, 2024.

Oceanic-atmospheric interactions play a crucial role in the modulation of monsoon rainfall. This is the first study that directly investigates the impact of tropical sea surface temperature (SST) variability on the frequency of sentinel reporting of travel-related dengue from the Geosentinel global emerging infectious disease surveillance network, by using the latest climate reanalysis ERA-5 produced by the European Center for Medium-Range Weather Forecasts, for the period 2007 to 2019. More specifically, we explore lag structures and the associated spatial correlation patterns between travel-related dengue cases, SSTs, and total precipitation over the tropics. We found that the Indo-Pacific and Atlantic Ocean SSTs have a remote influence on dengue risk in global regions that exhibit distinct monsoon characteristics. The coupling between SST variations and rainfall is an important driver of travel-related dengue cases and could act as an early warning signal for outbreak preparedness and travel medicine preventive advice. Finally, our findings highlight the need to better understand the large-scale and local circulation response to changes in the pattern of tropical ocean warming, to be able to better predict extreme events such as droughts and floods and devise adaptation measures against dengue outbreaks.

How to cite: Dafka, S., Libman, M., Hamer, D. H., Rocklöv, J., and Huits, R.: The association between tropical sea surface temperature variability and sentinel reporting of travel-related dengue , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12795, https://doi.org/10.5194/egusphere-egu24-12795, 2024.

The city of Belgrade has experienced a rise in temperatures during summers, marked by an increased frequency and intensity of heat waves. A concerning element is the escalation of overnight temperatures, which fail to cool down adequately. This phenomenon is particularly prevalent in urban areas due to the urban heat island effect. This study aims to provide evidence of the summer discomfort experienced in Belgrade during tropical nights over the past two decades and its impact on health. To achieve this, it is compiled a dataset containing daily weather information recorded at 9 pm (CET) spanning the years 2000 to 2020.

How to cite: Pecelj, M.: Summer Discomfort During Tropical Nights in Belgrade (Serbia), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13063, https://doi.org/10.5194/egusphere-egu24-13063, 2024.

Since the pioneering work in the early 2000s, there has been interest in the climate science community in using the compounding effects of heat and humidity (in the form of wet-bulb temperatures or other meteorological indices such as heat index) to understand health risks due to thermal stress on humans. For instance it has been suggested that the combination of high heat and humidity was responsible for the high mortality observed during the 2015 heatwaves in South Asia. However, assessing health impacts of temperature and humidity is challenging in South Asia since the health data required for epidemiological work is rarely available or reliable for robust analyses.

Using quality-controlled surface observations, we show that the humidity (or equivalently, wet-bulb temperatures) was in fact lower during most high impact heatwaves in South Asia -- the daily maximum was very close to its monthly mean value whereas the daily minimum dropped to much lower values. We show that this is due to a deeper boundary layer which dilutes the near-surface water vapour concentrations. Therefore, our analysis suggests that one-dimensional indices such as wet-bulb temperature may not be accurate in predicting health risks across the wide variety of meteorological conditions that South Asia experiences.

Using recent experimental results that demonstrate that hazardous conditions can occur at lower humidity values, we show that thresholds derived from these experiments produce a more realistic spatial and temporal distribution of hazardous conditions in South Asia as compared to wet-bulb temperatures alone. Furthermore, we show that hazardous exposure during the day extends to times not usually considered hazardous in public health messaging. Our results suggest that physiological thresholds provide a complementary way to assess health risk due to heat along with epidemiological regression studies.

How to cite: Monteiro, J., Justine, J., Shah, H., and Rao, N.: The exceedance of physiologically relevant thresholds in South Asia, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13800, https://doi.org/10.5194/egusphere-egu24-13800, 2024.

Health facilities in Pacific Island Countries are under threat due to ongoing climate change, namely from extreme weather events such as tropical cyclones. However, obtaining accurate projections of risks are inhibited due to the size and complex geometries of these islands which are not accurately or sometimes even entirely represented in the current resolution of global climate models.  Using higher resolution models and the Synthetic Tropical cyclOne geneRation Model (STORM) to generate 10,000 synthentic tropical cyclones, this study takes a greater in-depth analysis of extreme weather events and tropical cyclones at hospitals in Fiji, Vanuatu, Solomon Islands and Tonga.

Preliminary results show an approximately 150% increase in the frequency of extreme cyclones of category 4 or 5 at hospitals across the Pacific, with Vanuatu and Tonga projected to experience a 200% increase in extreme storms. Projected increases in extreme rainfall days (number of days where rainfall exceeds 95^th percentile) ranges between 14-161% and extreme heat days are expected to increase between 43-303 days per year by the end of the century. Mitigating against the impacts of climate change on medical care in these islands is hugely important, and so future aims of this work are to use statistical downscaling and AI-driven model acceleration, as part of our project EMPIRIC² (EMulation of Pacific Island Risk to Infrastructure from Climate), to provide robust, time-variant facility risks statistics directly to policymakers who are working to improve health infrastructure resilience across the South Pacific.

How to cite: McCrystall, M., Horvat, C., McLeod, L., Stewart, M., Stone, L., Taylor, S., Forbes, C., Natuzzi, E., and Kafoa, B.: Quantifying future risk of South Pacific Hospitals from climate change, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13976, https://doi.org/10.5194/egusphere-egu24-13976, 2024.

Ground-level ozone is a major air pollutant harmful for human health and there are concerns that ground-level ozone will increase over Europe under climate change despite efforts for a rigorous air pollution control. In addition, high levels of ground-level ozone often occur in combination with high air temperatures, for instance under persistent anticyclonic conditions in summer. Due to climate change heat events such as hot days and heat waves are also increasing. Thus, ground-level ozone health risks could combine with increased health risks from heat exposure.

Changes in the atmospheric chemistry from increased biogenic volatile organic compound emissions, faster chemistry kinetics, and faster peroxyacetyl nitrate decomposition as well as enhanced stratosphere-troposphere exchange, changes of the large-scale atmospheric circulation and synoptic patterns, increased stagnancy, and changes of atmospheric humidity may lead to increases of ground-level ozone in the scope of climate change. For Europe regional differences exist. For instance, over central Europe there is a strong relationship with meteorological conditions, while over southern and northern Europe the influence of ozone persistence and hence precursor emissions is comparably strong on ozone exceedances.

The present contribution comprises relationships of ground-level ozone and temperature with the atmospheric circulation, changes of health-relevant ground-level ozone and temperature events under future climate change as well as the connection of ground-level ozone and temperature with human health outcomes.  

How to cite: Hertig, E. and Kaspar-Ott, I.: Health-relevant compound ground-level ozone and temperature events in Europe, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15152, https://doi.org/10.5194/egusphere-egu24-15152, 2024.

The construction of simulation models for personal exposure analysis requires the integration of field-based data representing spatially distributed values (e.g. air pollution, noise, temperatures), agent-based data (e.g. daily activities, residential and work locations) and socio-economic data (e.g. age, social economic status, mode of commute) to fully cover the space-time activity patterns of cohort participants. In addition, evaluating the associated uncertainty is necessary as potentially not all required input variables are known.

We developed a modelling framework implemented in Python providing modules for 1) the specification of agents' activity diaries including the durations of activities and their spatial contexts, i.e. the location of a person during that activity, commute trips between residential and work location are thereby routed using OpenStreetMap data; 2) incorporating multiple environmental factors potentially on different temporal and spatial scales; 3) personal exposure assessment by calculating, for each time step and environmental factor, average exposure values within the spatial contexts. The modules can be combined in a Python script for exposure assessment of all agents in a cohort, including Monte Carlo simulations.

We show results from a modelling study conducted for the province of Utrecht, the Netherlands. The study area covers about 500000 residential address locations covering urban and rural areas. We used cadastral and census data to define characteristic diurnal activity profiles describing different characteristics such as social economic status and commute type (e.g. car, bicycle, on foot). We calculated individual exposures to NO₂, PM_2.5 and noise in Monte Carlo mode and demonstrate the spatial variability of exposures per activity profile and the associated uncertainty. The personal exposures for commuter profiles show more contrast across addresses compared to the homemaker profiles.

Our activity-based mobility simulation provides a representative description of space-time activities of individuals. The calculated personal exposures can be used for further epidemiological analysis to investigate the relationship between air pollution exposure and chronic diseases such as diabetes or cardiovascular disease.

How to cite: Schmitz, O., de Hoogh, K., Probst-Hensch, N., Jeong, A., Flückiger, B., Vienneau, D., Hoek, G., Kyriakou, K., Vermeulen, R. C. H., and Karssenberg, D.: A computational framework for personal multi-exposure assessment using space-time activity and socio-economic data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15296, https://doi.org/10.5194/egusphere-egu24-15296, 2024.

Climate change is exacerbating global disease risks, which will change household medical expenditures. Employing machine learning techniques and fine-scale bank transaction data, this study explores the changing household medical expenditures in 290 Chinese cities under four SSP scenarios (SSP1-2.6、SSP2-4.5、SSP3-7.0、SSP5-8.5) and further evaluates the adaptive impacts from socio-economic and physiological adaptations. The results show that the increasing temperature is projected to decrease future medical expenses in China by 5.24% (SSP1-2.6) to 5.60% (SSP5-8.5) in 2060. Cities exhibit differentiated sensitivity to increasing temperatures. Richer cities have enhanced resilience to high temperatures, and cold regions demonstrate less vulnerability to extreme cold weather. Physiological adaptation to climate change can significantly reduce medical expenditures by 27.6% by 2060. Meanwhile, socio-economic adaptation is expected to amplify national total medical expenses by 22.5% in 2060 under the SSP5-8.5 scenario. Our study incorporates adaptation into the prediction of future medical expenditures in China, aiming to assist cities in devising tailored climate adaptation strategies to alleviate the household economic strain induced by climate change. 

How to cite: Zhu, D., Liu, M., Li, R., Shan, Y., Zhang, H., Bi, J., and Hubacek, K.: Increasing climate change changes household medical expenditures, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16105, https://doi.org/10.5194/egusphere-egu24-16105, 2024.

How to cite: Srnec, L., Magjarević, V., and Sokol Jurković, R.: Health protection from heat waves in Croatia - today and in the future, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16469, https://doi.org/10.5194/egusphere-egu24-16469, 2024.

Although the World Health Organization has declared that the COVID-19 pandemic no longer qualifies as a global public health emergency, it still needs to review the response of society to the COVID-19 pandemic. Previous studies indicated that socio-economic status (SES) was linearly associated with the COVID-19 pandemic. However, this relationship may be more complex due to regional differences. Meanwhile, it needs to analyze the nonlinear impact of multiple factors on the infection rate. In the study, we analyzed the differences in infections among low, lower-middle, upper-middle and high SES group (LSG, LMSG, UMSG, and HSG, respectively), and considered the social and meteorological factors, revealing the effect and mechanisms of SES on infections. The results showed that the relationship between SES and infection rate was inverted U-shaped, especially in the first three phases. The contribution of meteorological factors to the infection rate first increased and then decreased. In the first phase, mask usage was the most important factor affecting the change in infection rate, with the contribution of 23.17%. In the second phase, temperature was the most important factor affecting the change in infection rate. In the third and fourth phases, vaccination was the most important factor. Furthermore, the nonlinear impact of multiple factors related to SES on the infections explains the complex relationship between SES and infections. The study argues for greater attention to countries with medium SES and the need for future targeted measures to cope with infectious diseases.

How to cite: Sun, Y. and Shi, P.: Multiple factors drive the infection rate in the progress of the COVID-19 pandemic, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18312, https://doi.org/10.5194/egusphere-egu24-18312, 2024.

As our climate is changing due to global warming, severe weather is expected to increase in frequency and it's intensity. Out of many examples of severe weather, we are focusing on cold and heat waves which greatly affect people causing increased mortality and morbidity. Also, some of the most important climate modifiers in Croatia are the Adriatic, the Mediterranean, the Dinarides orography, and the Pannonian plain. Because of this, the strongest winds in the Adriatic coast of Croatia are jugo and bora which can sometimes reach gale strength. They are associated with different weather conditions and can also have an impact on morbidity. For example, people describe a favorable impact on health and mood during most cases of moderate bora and unfavorable during moderate jugo episodes.

 In this work, we are exploring the potential of the Universal Thermal Climate Index (UTCI) and Potential Equivalent Temperature (PET) as severe weather-related health risk indicators in Croatia. The UTCI and PET are bioclimate indices that use human heat balance models to represent the thermal stress and comfort that is induced in the human body by meteorological conditions. For a couple of continental, maritime, and mountain stations in Croatia UTCI and PET are calculated from measurements. The exception is the mean radiant temperature which is estimated from the Rayman model based again on the measurements of global radiation, air temperature, and relative humidity. The distribution of all-cause death counts at different UTCI and PET values is investigated to determine a more appropriate measure of health risk.

The UTCI and PET are calculated for the domain over Croatia for the selected cases of a heat wave, a cold wave, and strong wind episodes. The meteorological data used for the calculation of UTCI and PET are hourly NWP model ALADIN-HR output values of air temperature, relative humidity, wind speed, and mean radiant temperature. The UTCI and PET are compared and show good agreement. Results for the cases of strong wind show UTCI sensitivity to the wind but depend on the air temperature primarily.

How to cite: Muić, I., Odak Plenković, I., Srnec, L., and Horvath, K.: Assessing health risks in Croatia for cases of severe weather via UTCI and PET, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19453, https://doi.org/10.5194/egusphere-egu24-19453, 2024.

This study investigates changes in fine particulate matter (PM_2.5) concentration and air-quality index (AQI) in Asia using nine different Coupled Model Inter-Comparison Project 6 (CMIP6) climate model ensembles from historical and future scenarios under shared socioeconomic pathways (SSPs). The results indicated that the estimated present-day PM_2.5 concentrations were comparable to satellite-derived data. Overall, the PM_2.5 concentrations of the analyzed regions exceeded the WHO air-quality guidelines, particularly in East Asia and South Asia. In future SSP scenarios that consider the implementation of significant air-quality controls (SSP1-2.6, SSP5-8.5) and medium air-quality controls (SSP2-4.5), the annual PM_2.5 levels were predicted to substantially reduce (by 46% to around 66% of the present-day levels) in East Asia, resulting in a significant improvement in the AQI values in the mid-future. Conversely, weak air pollution controls considered in the SSP3-7.0 scenario resulted in poor AQI values in China and India. Moreover, a predicted increase in the percentage of aged populations (>65 years) in these regions, coupled with high AQI values, may increase the risk of premature deaths in the future. This study also examined the regional impact of PM_2.5 mitigations on downward shortwave energy and surface air temperature. Our results revealed that, although significant air pollution controls can reduce long-term exposure to PM_2.5, it may also contribute to the warming of near- and mid-future climates.

How to cite: Sung, H. M., Shim, S., Kim, J., Lee, J.-H., Sun, M.-A., Chung, C.-Y., and Byun, Y.-H.: Regional Features of Long-Term Exposure to PM2.5 Air Quality over Asia under SSP Scenarios Based on CMIP6 Models, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20406, https://doi.org/10.5194/egusphere-egu24-20406, 2024.

How to cite: de Luca, C., Cavalieri, B., Baldassarre, B., Ommer, J., and Kalas, M.: Health integration in climate-related policies: evidence and gaps in the EU policy context  , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20465, https://doi.org/10.5194/egusphere-egu24-20465, 2024.

Multiple factors influence the risk of heat stroke and that, collectively, define the vulnerability of the population. This vulnerability can be physiologically differentiated by older adults and children, by gender, or due to the level of exposure to sporting activities or labor, among others. During the last two decades, hot extreme events are drastically increasing related to climate change and other climate phenomena such as El Niño event. The World Health Organization estimates that more than 70,000 heat-related deaths occurred in Europe during the last two weeks of August 2003 and almost 62,000 deaths during summer 2022. In Mexico, the record of heat-related deaths was set during the summer of 2023 when the Health Secretariat reported 373 deaths due to extreme heat events. The five ranking states were Nuevo León (27% of the cases), Sonora (20%), Baja California (14%), Tamaulipas and Veracruz (8% respectively), and 80% of them are located between the 25 to 31°Latitude North. To understand which the most influential factors for heat-related deaths are, this study analyzes the interaction between land surface temperature, spatial population dynamics, and the exposure-response relationship to urban form and the concentration of air pollution in the Monterrey Metropolitan Area. The paper will present the operational structure of a smart information system based on RS and GIS for planning a better and safer city life in San Nicolás de los Garza, the municipality that ranked first on heat-related deaths. In summary, results indicate the next highlights: (1) extreme heat waves are increasing every year in the metropolitan area, (2) urban heat islands are spatially and temporally located, therefore, (3) risk reduction and civil protection actions must include a holistic approach including warning early systems, social, labor and health care actions, (4) preventive policies must be implemented such as sustainable urban planning for population climate justice, (5) and adopting nature-based solutions. 

How to cite: Yépez-Rincón, F. D., Avendaño, A., Fernández Delgadillo, S., Ferriño Fierro, A. L., Guerra Cobián, V. H., Huerta García, R. E., González Méndez, B., Ramírez Serrato, N. L., Ábrego Góngora, C. J., Pérez Ruiz, R., and Aguilar Cruz, R.: Smart information system based on RS and GIS as an adaptation strategy for reducing mortality from heat waves , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20786, https://doi.org/10.5194/egusphere-egu24-20786, 2024.

Countries in sub-Saharan Africa (SSA) have some of the highest levels of child malnutrition, with more than one-third of children under five in the region characterized as chronically undernourished. High reliance on subsistence farming, poor adoption of irrigation technologies, and variable climate conditions make populations in SSA highly vulnerable to malnutrition during droughts. We use anthropometric data for 520,734 children under the age of five from 34 countries in SSA collected between 1990 and 2022 in combination with high-resolution agricultural and climate data to estimate the association between agricultural droughts and child undernutrition in the region. We use global gridded data on the geographical distribution of crop areas for 15 major crops. Data on crop planting and harvesting dates are also collected for each crop. The Standardized Precipitation Evapotranspiration Index (SPEI), a multi-scalar drought index, is used to measure the intensity and spatial distribution of droughts during key periods of agricultural production (planting, growth, and harvesting) and of different duration (seasonal and long-lasting droughts). Our analysis shows that droughts during the crop-growing seasons are associated with an increased risk of child undernutrition in SSA. The findings presented in this study call for urgent action to improve drought monitoring and response in SSA where the risks to child health posed by global warming are considerable. Under climate change, the severity and frequency of extreme weather and climate events, including droughts, are projected to increase, which will place millions of children at risk of hunger unless timely action plans are taken to improve food security in the region.

How to cite: Dimitrova, A., Gershunov, A., and Benmarhnia, T.: How agricultural droughts are contributing to child undernutrition in sub-Saharan Africa, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20931, https://doi.org/10.5194/egusphere-egu24-20931, 2024.

The critical challenge in a hydrological system is to predict whether the system approaches a critical threshold. The urban centres are grappled by the extreme events especially floods with the shifts from one stable state to another in an urban socio-environmental system. Here, we identified the critical transitions of hydrological processes, including precipitation and runoff, by analyzing their shifting nature. Structural break-regression models, incorporating shifts in both mean and trend, are applied to the series.  The point of change indicates the transition within the system.  These models are then evaluated using two widely employed penalized likelihood criteria for multiple changepoints. These criteria strike a balance between the quality of model fit (measured by likelihood) and the consideration of parsimony. Two models are tested i.e., bisegmentation and penalised maximum likelihood with the white noise detection. The latter was found to be better fit to both precipitation and runoff for the three cities (Guwahati, Mumbai, and Dehradun) in India.

How to cite: Jain, J., Khare, D., and Munoz-Arriola, F.: Identifying the Transitions in the Stable Socio-Environmental System Due to Extreme Events , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-947, https://doi.org/10.5194/egusphere-egu24-947, 2024.

Utilizing the sophisticated Multi-Regional Input-Output Analysis (MRIO) approach, this investigation meticulously examines the nitrogen (N), phosphorus (P), and potassium (K) fertilizer footprints associated with predominant crops throughout various Chinese provinces. Crucial provinces, namely Heilongjiang, Jiangsu, Shandong, and Henan, manifest a pronounced geographical aggregation in fertilizer footprints. Intriguingly, Heilongjiang, Shandong, and Henan collectively represent 49.2% and 42.7% of the cumulative national footprint.

From a provisioning perspective, the assimilation of N, P, and K fertilizers predominantly gravitates towards Heilongjiang, Shandong, Henan, Jiangsu, and Anhui, cumulatively contributing 32.74%, 35.73%, and 36.48% to the nation's aggregate input. Distinctly, regions such as the Yangtze River Delta, Pearl River Delta, and the Beijing-Tianjin-Hebei conurbation emerge as paramount crop consumption hubs, with aggregate consumptions scaling to 4505.12 Gg, 1741.71 Gg, and 2026.57 Gg, respectively. Notably, the exogenous crop provisions in metropolises like Shanghai and Beijing play a pivotal role in shaping their N, P, and K footprints, quantified at 6.78%, 5.56%, and 5.79%, and 1.26%, 1.37%, and 1.71%, respectively.

Furthermore, three salient regions—the Northeastern Plains, the Huang-Huai-Hai Plains, and the Middle to Lower tracts of the Yangtze River—collectively encompass 57.4%, 66.1%, and 66.26% of the national N, P, and K footprints. Compellingly, the dynamics of crop footprint migration in provinces such as Henan, Heilongjiang, and Shandong appear to be predominantly modulated by wheat and corn.

In summation, this scholarly endeavor elucidates the intricate spatial delineation of the fertilizer footprint, its translocation mechanisms, and its intricate interplay with socio-economic and demographic paradigms, thereby laying a robust theoretical groundwork for augmenting fertilizer efficacy and championing the cause of sustainable agricultural practices.

How to cite: Wu, Y., Liu, J., and Geng, Y.: Analysis of the Fertilizer Footprint of Principal Crops in China: A Spatial Allocation Perspective, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2179, https://doi.org/10.5194/egusphere-egu24-2179, 2024.

Human society is grappling with the need to supply reliable and affordable freshwater for growing populations without destroying ecosystems. Environmental flows (EF) have been considered, and implemented, as a promising approach to sustainable water systems since its inception. However, the persistent antagonism between EF and other water demands is questionable, as the loss of hydro-ecological functions due to excessive water withdrawal (WW) could be balanced by the compensatory benefits of EF (i.e., EF improves resilience). Here, we introduce a mathematical push-pull framework to demonstrate how can EF be applied to lead to shifts in water availability explicitly in terms of magnitude and frequency. Our case study in the Yangtze River Basin reveals that EF implementation improves water availability over long time scales. We determine a boundary between EF and WW that leads to an escape from or stabilization within a stable equilibrium attraction. We use this boundary to define reasonable EF tailored to repeated, discrete WWs. Our results support the implementation of EF and its accompanying measures as part of the post-2030 eco-restoration framework.

How to cite: Zhao, Y., Zhang, X., Tao, S., Xiong, F., Deng, Z., Bing, J., Yan, S., Liu, J., and Xia, J.: Shifts in water availability due to environmental flows, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2326, https://doi.org/10.5194/egusphere-egu24-2326, 2024.

Degradation of ecosystems can occur when certain ecological thresholds are passed below which ecosystem responses remain within ‘safe ecological limits’. Ecosystems such as drylands are sensitive to both aridification and grazing, but the combined effects of such factors on the emergence of ecological thresholds beyond which ecosystem degradation occurs has yet to be quantitatively evaluated. This limits our understanding on ‘safe operating spaces’ for grazing, the main land use in drylands worldwide. Here we assessed how 20 structural and functional ecosystem attributes respond to joint changes in aridity and grazing pressure across China´s drylands. Gradual increases in aridity resulted in abrupt decreases in productivity, soil fertility and plant richness. Rising grazing pressures lowered such aridity thresholds for most ecosystem variables, thus showing how ecological thresholds can be amplified by the joint effects of these two factors. We found that 44.4% of China’s drylands are unsuitable for grazing due to climate change-induced aridification, a percentage that may increase to 50.8% by 2100. Of current dryland grazing areas, 8.9% exceeded their maximum allowable grazing pressure. Our findings provide important insights into the relationship between aridity and optimal grazing pressure and identify safe operating spaces for grazing across China’s drylands.

How to cite: Li, C., Fu, B., Wang, S., Stringer, L., Zhou, W., and Ren, Z.: The safe operating spaces for grazing in China’s drylands, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2580, https://doi.org/10.5194/egusphere-egu24-2580, 2024.

The analysis of global catastrophic events often occurs in isolation, simplifying their study. In reality, risks cascade and interact. Therefore, it is essential to consider the interconnected nature of global risks. This investigation explores the interplay between nuclear winter and planetary boundaries. It may seem reasonable to assume that respecting planetary boundaries, which define a safe operating space for the planet, is preferable before a nuclear war. However, that does not always seem to be the case. For instance, increased nitrogen emissions today could serve as a nutrient buffer during nuclear winter. Contrastingly, mitigating climate change, means an even larger temperature drop in nuclear winter in comparison with pre-industrial times. This exploratory study also highlights planetary boundaries that could enhance human survival if we adhere to their limits, both presently and after a nuclear war. The best example being biosphere integrity, as conserving it has no direct downsides and would make the Earth system more resilient to resist the shock of a nuclear winter.

How to cite: Jehn, F. U.: Anthropocene Under Dark Skies: The Compounding Effects of Nuclear Winter and Overstepped Planetary Boundaries, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2773, https://doi.org/10.5194/egusphere-egu24-2773, 2024.

The Atlantic Meridional Overturning Circulation (AMOC) is a crucial part of the climate system that carries warm and saline water towards the northern Atlantic and is an important component in the global meridional heat transport. However, the AMOC is a so-called “tipping element”: there is observational evidence that it is in a bistable regime and may thus collapse under anthropogenic greenhouse gas emissions. Bi-stability has also been found in a hierarchy of models, from a simple two-box model up to a CMIP5 global climate model (CESM1). Considering a possible upcoming tipping, it is critical to assess how likely the AMOC is to undergo a collapse under different greenhouse gas forcing scenarios.  This issue is tightly related to the notion of resilience, which refers to the ability of a system to sustain a certain forcing while remaining in its original state or to return to its original state after being displaced.

Studying the resilience of the AMOC requires to observe its collapse, which is very difficult due to its rarity, especially in very complex models. That is why we use a rare-event algorithm called Transition-Adaptive Multilevel Splitting (TAMS). Given a certain definition of the current-day and collapsed AMOC, TAMS pushes trajectories in the direction of a collapse at a much lower cost than Monte-Carlo simulations. This method outputs typical collapse trajectories starting from a present-day AMOC, under a certain chosen hosing flux. This process is repeated for a wide range of freshwater forcings. From those trajectories, we extract observables (e.g. the AMOC strength), which are scalar functions that are interpreted as resilience observables. By monitoring these observables, we can rank different climate change scenarios depending on the risks they impose on the AMOC. Moreover, we relate these observables to existing mathematical definitions of resilience. Finally, we determine which observables are best suited to describe the resilience of the  AMOC, with a focus on those that can be measured in the field.

How to cite: Jacques-Dumas, V., Kühn, C., and Dijkstra, H. A.: Resilience of the AMOC, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4134, https://doi.org/10.5194/egusphere-egu24-4134, 2024.

Assessments of climate change effects on humans and ecosystems have previously included only limited information on the consequences of climate tipping points. While some national evaluations have touched on tipping point implications, assessment has been largely qualitative, with minimal quantitative analysis. Understanding and quantification of impacts of tipping points is recognised as a significant knowledge gap, and improving the research base in this area is essential for climate risks to be fully evaluated.

This presentation examines the current knowledge of Earth system tipping point impacts on people, exploring the evidence on impacts from individual tipping points, and assessing specific sectors and their vulnerability to these tipping points. Localised effects arise when climate tipping points, such as permafrost thaw and forest dieback, are crossed. These effects stem from land surface changes and alterations in regional climates and weather extremes. Global impacts manifest through large-scale shifts in atmospheric and oceanic circulations, altering global warming rates and sea level rise. Oceanic dynamics, like collapse of the Atlantic Meridional Overturning Circulation, can reshape regional climates and cause widespread shifts in temperature and precipitation patterns. Similarly, cryospheric tipping points, such as marine ice cliff collapse, have the potential to accelerate sea level rise, affecting flooding hazards like coastal inundation. Biosphere tipping points, such as Amazon dieback, intensify greenhouse gas concentrations, hastening global warming and its associated extreme weather events, regional climate shifts and sea level rise.

All these have the potential to impact the security of water, food and energy, human health, ecosystem services, communities and economies. The body of evidence varies across tipping points and sectors, but the implications for profound impacts across all areas of human society are clear.

How to cite: Betts, R., Dyke, J., Fuller, E., Jackson, L., Laybourn-Langton, L., Steinert, N., and Xu, Y.: Assessing impacts of Earth system tipping points on human societies , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6874, https://doi.org/10.5194/egusphere-egu24-6874, 2024.

Under current emission trajectories, at least temporarily overshooting the Paris global warming limit of 1.5 °C above pre-industrial levels is a distinct possibility. Permanently exceeding this limit would substantially increase the risks of triggering several climate tipping elements with associated high-end impacts on human societies and the Earth system. It is essential to assess this risk under emission pathways that temporarily overshoot 1.5 °C. Here, we investigate the tipping risks associated with a number of policy-relevant future emission scenarios, using a stylised Earth system model that comprises four interconnected core tipping elements. Assessing tipping risks in the year 2300, we find a non-linear increase for overshoots that exceed 1.8 °C peak temperature or persist above 1.5 °C beyond the end of the 21st century. Scenarios following current policies or pledges lead to high tipping risk of 30% (median) and more, with uncertainty from climate sensitivity and carbon-cycle feedbacks translating to large uncertainties in tipping risk (45% and more) for these scenarios. Further, we show that on multi-century timescales achieving and maintaining at least net-zero greenhouse gas emissions is paramount to minimise tipping risks. Our results underscore that stringent emission reductions in the current decade in line with the Paris Agreement 1.5 °C limit are critical for planetary stability.

How to cite: Högner, A. (., Möller, T., Schleussner, C.-F., Bien, S., Kitzmann, N. H., Lamboll, R. D., Rogelj, J., Donges, J. F., Rockström, J., and Wunderling, N.: Achieving net zero greenhouse gas emissions critical to limit climate tipping risks, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7633, https://doi.org/10.5194/egusphere-egu24-7633, 2024.

How to cite: Breier, J.: The InSEEDS Model - coupling LPJmL and copan:CORE towards an integrated human-earth system model of regenerative land-system change, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7670, https://doi.org/10.5194/egusphere-egu24-7670, 2024.

Climate tipping elements are large-scale subsystems of the Earth that may transgress critical thresholds (tipping points) under ongoing global warming, with substantial impacts on biosphere and human societies. While recent scientific efforts have improved our knowledge on individual tipping elements, the interactions between them are less well understood. Also, the potential of individual tipping events to induce cascading tipping elsewhere, or stabilize other tipping elements is largely unknown. As a contribution to the Global Tipping Points Report (GTPR) 2023 for COP28, we mapped out the current state of the literature on interactions between climate tipping elements. We find that tipping elements in the climate system are closely interacting, meaning a substantial change in one will have consequences for subsequently connected tipping systems. A majority of interactions between climate tipping systems are destabilising. While confirmation or rejection through future research is necessary, it seems possible that interactions between climate tipping systems destabilise the Earth system in addition to climate change effects on individual tipping systems. Further, we are quickly approaching global warming thresholds where tipping system interactions become relevant, because multiple individual thresholds are being crossed. Concretely, tipping cascades can neither be ruled out on centennial to millennial timescales at global warming levels between 1.5–2.0°C, nor on shorter timescales if global warming would surpass 2.0°C. To address crucial knowledge gaps in tipping system interactions, we propose four strategies forward combining observation-based approaches, Earth system modelling expertise, computational advances, and expert knowledge.

How to cite: Wunderling, N. and von der Heydt, A. and the GTPR-tipping-interactions-team: Reviewing climate tipping point interactions and cascades under global warming, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7905, https://doi.org/10.5194/egusphere-egu24-7905, 2024.

We present here a tool for the detection of abrupt transitions in CMIP6 model outputs, that is aimed to update and extend the catalog of tipping points presented in Drijfhout et al. 2015, based on the evaluation of CMIP5 intercomparison.

The tool consists of three fundamental steps: 

• Data manipulation: model outputs are sampled according to the user’s preferences, aggregated along the integration period and interpolated to a common grid for the whole multi-model ensemble. A 10-years moving average is also applied;
• Criteria for abrupt transitions: Criteria for the detection of abrupt transitions are computed and combined. These are: exceedance of the preindustrial 99-percentile standard deviation, exceedance of the preindustrial 99-percentile jump over 10 years period, exceedance of the preindustriak 99-percentile yearly anomaly for each year in the last 30 years of the simulation, p-value of a Kolmogorov-Smirnov hypothesis test for normality of the distribution;
• Masking and clustering: grid points for which the time series of anomalies with respect to preindustrial conditions that satisfy at least 3 out of 4 of the criteria illustrated above are selected. Successively, grid points are clustered in order to exclude sparse points and highlight significant regions affected by widespread abrupt transitions;

We present a preliminary analysis demonstrating the usage of this tool on a set of ocean-sea-ice-related quantities for a number of models participating in CMIP6 project under disparate SSP scenarios. 

How to cite: Lembo, V., Corti, S., Angevaare, J., and Drijfhout, S.: A tool for objective detection of abrupt transitions in CMIP6 models, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10861, https://doi.org/10.5194/egusphere-egu24-10861, 2024.

Understanding the emergent dynamics – in particular critical transitions – in complex social-ecological systems is key to foster positive social transformations in the Anthropocene era. Regime shifts in some ecosystems may be preceded by statistical early warning signals, but systems where such signals can be tested systematically are elusive. The r/place game hosted by Reddit is a social experiment that provides data for thousands of subsystems that can undergo critical transitions. It is therefore an excellent testbed for comparing the performance of various warning indicators. In r/place, millions of users collaborated to build many discernible drawings on a canvas of pixels. A drawing undergoes a transition when it is rapidly replaced by another. We build an early warning signal indicator that uses machine learning to combine the predictive power of a number of time-dependent and system-specific variables, and we show that its performance far exceeds that of standard indicators. For example, when training the algorithm and testing its performance on separate parts of the 2022 r/place, we detect half of the transitions coming in less than 20 minutes with only a 0.6% false positive rate. The performance only slightly decreases when training on 2022 data and testing on the 2023 experiment, showing that the predictive power holds across significantly different setups. We use SHAP values to elucidate the drivers of any given warning and highlight generic properties of warnings in online social systems. Some properties, such as a decreasing return time, are at odds with standard statistical indicators. Where sufficient data is available, our tool and resulting insights can contribute to warn of – and possibly trigger or avoid – macroscopic social and ecological change.

How to cite: Falmagne, G. and Stephenson, A. B.: Interpretable Early Warning Signals in Large Human Groups, using Machine Learning in an Online Game-experiment, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12076, https://doi.org/10.5194/egusphere-egu24-12076, 2024.

Natural terrestrial ecosystems in different parts of the world have been losing resilience in the past decades. Such losses of resilience can be the precursors for regime shifts on local or regional scales that can have large impacts on ecosystem structure and function as well as nature’s contributions to people. Drivers of resilience loss include mainly changes in the mean and variability of temperature and precipitation, and anthropogenic land modifications of adjacent or remote ecosystems.

Global assessments of ecosystem resilience often exclude areas with direct anthropogenic land use changes and focus instead on remnant natural ecosystems. However, for regional stakeholders it is important to understand how land-use and zoning decisions may affect the resilience of remaining ecosystems and the risk of critical transitions.

In this study, we conduct a high-resolution global assessment of terrestrial ecosystem resilience losses, using time series of multiple remotely-sensed ecosystem indicators, and employing a range of early warning signals. We also evaluate the importance of different climatic and anthropogenic drivers at a local scale of administrative units in causing the detected changes in resilience. This allows us to get a comprehensive and robust understanding of different dimensions of change in global ecosystem resilience and their locally relevant drivers of change.

How to cite: Knecht, N., Fetzer, I., and Rocha, J.: Global terrestrial ecosystem resilience: a high-resolution multivariate analysis of patterns and drivers, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12856, https://doi.org/10.5194/egusphere-egu24-12856, 2024.

The Brazilian Amazon is a powerful Ecosystem Service (ES) provider. Simultaneously, many Amazonian local communities still preserve an intrinsic economic and cultural relationship in this Social-Ecological System. Paradoxically, the region concentrates a significant portion of the nation's poorest people, demonstrating the risks and susceptibility to socio-ecological vulnerability that region. Thus, the Amazon Forest dieback hypothesis predicts that the increased CO₂ (eCO₂), rising temperatures and droughts may push the forest toward a tipping point, which would bring a new composition of ES and would reflect on regional economic - cultural ways of living, as well as, social wellbeing and health. Hence, the research employed a cascade model using the Functional Diversity (FD) approach. The aim was to assess the impact of climate changes on CO₂ storage related to Ecosystem Services and their implications for the adaptation capacity of both rural and urban populations in the Brazilian Amazon. The initial analysis, using the CAETE model, evaluated vegetation FD responses in a scenario of 50% precipitation reduction. This revealed a shift in plant composition towards drought-related strategies, leading to a 37-49% reduction in total carbon storage in the basin, resulting in increased carbon release into the atmosphere. This result translates direct impacts to global and local climate regulation and indirect to shifting of water flux and to native provisioning services. The second evaluating was on social dimension ambit, through drafting of Social Ecological Vulnerability Index (SEVI) with secondary data of the municipalities of Manaus, Itacoatiara e Silves in the state of Amazonas and Ilha de Cotijuba in the Belém city in the state of Pará. The SEVI points out that the common factor of the vulnerability among the municipalities was the indicators of the socio-climate exposure for susceptibility to disasters, to rising temperature and FD changes. The SEVI result summed to FD modelling demonstrate that the social well-being of communities is threated due to the impacts on the native ES, even though they are placed in the one of most biodiverse forest from the globe. In addition, the susceptibility to diseases related to climate change increases in the regions greater urbanized (score 2.5, in the range from 0 low to 4 high vulnerability) with in turn can undermine the public health system in the urban centres in expanding in the Amazonia. Thus, the SEVI reveals that the impacts, stemming from the shifting FD of the modelled plant community, do not merely pose a distant threat to social well-being, health, and income; instead, they exacerbate socio-ecological vulnerability. In view that, people recognize and link hazards in infrastructure (ES for erosion control), mobility, and food supply (ES for water flow, fish, and wild food). Therefore, all the results support the challenges for the development of public policies of climate adaptation involving social health, future maintenance of provisioning native ES, above all in the municipalities with inadequate socioeconomic indicators

How to cite: Almeida Canova, M., Rius, B., Darela Filho, J., and Montenegro Lapola, D.: Climate Change and Social- Ecological Vulnerability Index in the Brazilian Amazon: A study with a cascade model approach, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13183, https://doi.org/10.5194/egusphere-egu24-13183, 2024.

In the recent update of the Planetary Boundaries framework, Richardson et al. propose to use human appropriation of net primary productivity (HANPP) as a new indicator for the functional biosphere integrity boundary. They provide a planetary scale analysis and suggest to further complement this by an ecological metric.

To aid with the spatially explicit analysis of both HANPP and an ecological metric in an automated and easy way, we developed the "biospheremetrics" R package. The package combines 2 complementary metrics:

The BioCol metric operationalizes the HANPP framework in order to represent a meaningful Planetary Boundary indicator, and is accompanied by the EcoRisk metric, which quantifies biogeochemical and vegetation structural changes as a proxy for the risk of ecosystem destabilization. Both metrics are computable in a dynamic global vegetation modelling framework.

We spatially explicitly analyse both metrics over the past 500 years with simulations of the dynamic global vegetation model LPJmL and find that presently (period 2007-2016), large regions show modification and extraction of >25% of the preindustrial potential net primary production, leading to drastic alterations in key ecosystem properties and suggesting a high risk for ecosystem destabilization. In consequence of these dynamics, EcoRisk shows particularly high values in regions with intense land use and deforestation, but also in regions prone to impacts of climate change such as the arctic and boreal zone.

We additionally show how both metrics could be combined to inform the Planetary Boundary of functional biosphere integrity, compare our results with other spatially explicit global biosphere integrity metrics and discuss the setting of (provisional) thresholds.

How to cite: Stenzel, F., Breier, J., Braun, J., Erb, K., Gerten, D., Matej, S., Haberl, H., Ostberg, S., Roux, N., Schaphoff, S., and Lucht, W.: Using biosphere metrics to assess the Planetary boundary for functional biosphere integrity, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13292, https://doi.org/10.5194/egusphere-egu24-13292, 2024.

In an attempt to define a safe operating space for humanity, the Planetary Boundary (PB) framework proposes precautionary limits to human interference with nine critical Earth system processes. However, quantitative assessments of these limits and past, present or potential future statuses and transgressions of PBs are (i) inflicted by differences in definitions, data and models used and (ii) require process-based models of the Earth system in the absence of globally available observational datasets on the PB control variables. To advance such process-based and consistent PB quantifications for terrestrial PBs (land system change, biosphere integrity, freshwater change, biogeochemical flows), we developed an R based software package, “boundaries”, for calculation and visualization of PBs based on outputs from the global terrestrial biosphere model LPJmL. The coupled, spatiotemporally explicit and dynamic simulation of the biogeochemical processes underlying the control variables in LPJmL allows for calculation of the temporal evolution of PB statuses, i.e. if, where and how strongly boundaries are transgressed, at different scales (for both planetary and corresponding subglobal boundaries from regional to grid cell scale).

Next to a short technical overview on boundaries and its structure, the poster shows calculated current spatially-explicit statuses of the four PBs considered as well as their simulated evolution during past decades, based on one consistent modelling framework and applying the latest PB definitions. In addition to contributing to a better understanding of temporal trajectories, spatial patterns and drivers of PB transgressions, boundaries can be applied to evaluate future scenarios in terms of their PB impacts and potentials to return to a safe space within PBs. As one potential critical PB trade-off, the poster focuses on different land-based carbon dioxide removal (CDR) strategies for reducing pressures on the climate change PB. The scenarios’ results show the importance of dietary changes towards less livestock products to release pasture areas for CDR. If forests can be restored on spared land, pressures on multiple PBs could be synergistically alleviated.

How to cite: Braun, J., Gerten, D., Breier, J., Stenzel, F., Werner, C., and Lucht, W.: Assessing historical and potential future Planetary Boundary transgressions in a consistent modelling framework, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14873, https://doi.org/10.5194/egusphere-egu24-14873, 2024.

While Planetary Boundary science has advanced tremendously over the past decades, we still lack a deep understanding of the intricate, yet pivotal connections between many biological and physical functions of the Earth system. This is of grave concern, since the stability of the planet and interactions between its components are the foundation of human civilization. Moreover, as it stands, science only has the resources to measure and analyze the planet’s vital signs every 6-8 years (Rockström et al. 2009, Steffen et al. 2015, Richardson et al., 2003), and our imperfect measurement framework has some worrying blind spots.
To address these challenges, the Potsdam Institute for Climate Impact Research and its partners are launching a major scientific effort to close the knowledge gaps, both in terms of our ability to model how the Earth system evolves under the pressure of human activity, as well as our ability to measure the state of the Earth system with high temporal resolution. This will culminate in an annual Planetary Boundary (PB) Health Check, conceived and reviewed by a diverse international scientific and stakeholder community. Employing cutting-edge Earth-system and tipping-point modelling, ambitious whole-Earth monitoring, and exploring artificial-intelligence-based big-data analytics, the Health Check shall offer a comprehensive, timely, and unparalleled assessment of the planet's health. With yearly updates of PB transgressions at its core, the Health Check will further develop the boundary measures themselves and provide important context, e.g. via case studies and policy implications.  It will reveal current risks due to ongoing transgression of PBs and develop transformation pathways to guide global development back to Earth’s safe operating space. Besides peer-reviewed publications, these results will be communicated to the public using state-of-the-art visualizations and communication partnerships.

In this presentation we will give details about this new science initiative, the partners we work with, out short and long-term goals and give an overview of involvement opportunities in this rapidly growing project.

References

Rockström, J., Steffen, W., Noone, K. et al. A safe operating space for humanity. Nature 461, 472–475 (2009). https://doi.org/10.1038/461472a
Steffen, W. et al. ,Planetary boundaries: Guiding human development on a changing planet.Science347,1259855(2015).DOI:10.1126/science.1259855 
Richardson, K. et al., Earth beyond six of nine planetary boundaries.Sci. Adv.9,eadh2458(2023).DOI:10.1126/sciadv.adh2458

How to cite: Caesar, L., Kitzmann, N., and Rockström, J.: Advancing Planetary Boundary Science, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15269, https://doi.org/10.5194/egusphere-egu24-15269, 2024.

The use of early warning signals to detect the movement of natural systems towards tipping points is well established. Here, we explore whether the same indicators can provide early opportunity signals (EOS) of a tipping point in a social dataset – views of online electric vehicle (EV) adverts from a UK car selling website (2018–2023). The daily share of EV adverts views (versus non-EV adverts) is small but increasing overall and responds to specific external events, including abrupt petrol/diesel price increases, by spiking upwards before returning to a quasi-equilibrium state. An increasing return time observed over time indicates a loss of resilience of the incumbent state dominated by ICEV advert views. View share also exhibits increases in lag-1 autocorrelation and variance consistent with hypothesised movement towards a tipping point to an EV-dominated market. Segregating the viewing data by price range and year, we find a change in viewing habits from 2023. Trends in EOS from EV advert views in low-mid price ranges provide evidence that these sectors of the market may have passed a tipping point, consistent with other evidence that second-hand EVs recently reached price parity with equivalent ICEV models. We provide a case study of how EOS can be used to predict the movement towards tipping in social systems using novel data.

How to cite: Boulton, C., Buxton, J., and Lenton, T.: Early opportunity signals of a tipping point in the UK’s second-hand electric vehicle market, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15331, https://doi.org/10.5194/egusphere-egu24-15331, 2024.

Earth system stability commonly denotes the continuation of the Holocene's relatively stable climatic and ecological conditions essential for human civilisation, whereas Earth resilience describes the Earth system’s ability to recover from significant disturbances, such as the transgression of any of the nine planetary boundaries. Given the nature of the Earth system as a non-autonomous, stochastic, non-linear system, it is not clear what exactly constitutes stable states, semi-stable states or mere transients. An alternative approach is to regard the glacial-interglacial cycle as a stable attractor and thus ask, how stable or resilient is this cycle to perturbations? The answer could provide insights relevant for contextualising the embedded transitions of critical tipping points happening on much shorter time scales.

In this study, we explore the stability and resilience of the glacial-interglacial cycle using a conceptual climate model developed by Talento and Ganopolski (2021), based on atmospheric CO2 concentration, global mean temperature, and global ice volume. The model is driven by astronomical forcing and replicates the ice age cycles of the last 800,000 years with a correlation of 0.86. Following the classical idea of Hasselmann, we have extended this model with additive noise to represent unresolved processes. An analysis of an ensemble of trajectories reveals periods of significant divergence and convergence, indicating that the model’s sensitivity to noise varies in response to astronomical forcing. We have further applied a transfer operator approach in an attempt to identify stable and decaying states of the model and to study their evolution with changes in astronomical forcing. Findings shed light on the complexity and sensitivity of the Earth system's dynamics.

References:
Talento, S., & Ganopolski, A. (2021). Reduced-complexity model for the impact of anthropogenic CO2 emissions on future glacial cycles. Earth System Dynamics, 12(4), 1275-1293.

How to cite: Harteg, J. S., Wunderling, N., Klose, A. K., and Donges, J. F.: Assessing the stability of glacial-interglacial cycles: a stochastic model analysis of Earth system resilience, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15457, https://doi.org/10.5194/egusphere-egu24-15457, 2024.

Ecosystem resilience represents the capacity of an ecosystem to withstand and recover from external perturbations, an increasingly important property for ecosystem function in an era of escalating climate extremes and anthropogenic pressures. Whilst recent studies have related forest resilience to natural factors such as climate and biomass, the link between forest diversity and resilience is not yet understood.

This study quantifies the sensitivity of ecosystem resilience on forest diversity in Europe over the period 2003-2021. Two commonly used resilience indicators are considered based on MODIS kNDVI (kernel Normalized Difference Vegetation Index) data acquired at high spatial and temporal resolution: the 1-lag temporal autocorrelation, relating to the ecosystem memory, and the standard deviation, relating to the ecosystem stability. Forest diversity is expressed in terms of horizontal and vertical structural heterogeneity metrics derived from GEDI (LiDAR) (Light Detection and Ranging) acquisitions. A Random Forest (RF) model is leveraged to isolate the interplay between forest resilience and diversity metrics by disentangling possible confounding environmental variables such as climate. The RF model is then applied to retrieve local sensitivities in terms of Individual Conditional Expectations.

The work first finds that European forests with a higher level of vertical and horizontal structural diversity are systematically associated with higher resilience levels. The relationship is coherent across bio-geographical regions in Europe. Importantly, the emerging relation between forest resilience and forest diversity is consistent under increasing temperature patterns. This suggests that forest management targeted to higher levels of forest heterogeneity has the potential to offset the decline in forest resilience associated with the projected climate warming scenarios and the consequent increasing disturbance regimes.

How to cite: Pickering, M., Elia, A., Girardello, M., Oton, G., Capobianco, S., Piccardo, M., Ceccherini, G., Forzieri, G., Migliavacca, M., and Cescatti, A.: Assessing the relationship between forest structural diversity and resilience in a warming climate, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16017, https://doi.org/10.5194/egusphere-egu24-16017, 2024.

The climate of the Pleistocene is characterized by alternating cold (glacial) and warm (interglacial) periods. This cyclicity is mainly caused by the so-called Milankovitch cycles as a result of periodic changes in Earth’s orbital parameters. Many models have already successfully captured the non-linearities of the climate-cryosphere system responsible for the 100 kyrs cycles and the Mid-Pleistocene transition. However, these models widely differ in the number of explicit physical processes included and in the degree of complexity to solve them (from purely conceptual to Earth-system models). 

In this talk I will present a simple a-dimensional model that sequentially includes ice-sheet dynamics, ice aging and climate-cryosphere feedbacks. This model is able to capture the timing and shape of glacial cycles of the last 2 million years and can also be used to predict future glacial inceptions and thus the duration of the Anthropocene. Following different assumptions of human greenhouse gas emissions, I will show the expected timing of future glacial inceptions as well as the periodicities of the late Anthropocene glacial cycles.

How to cite: Alvarez-Solas, J.: Simulating glacial cycles from the Pleistocene to the end of the Anthropocene, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16345, https://doi.org/10.5194/egusphere-egu24-16345, 2024.

In the face of Anthropogenic change, ecosystems globally have shown evidence of resilience loss in the past several decades. By governing key processes in terrestrial ecosystems, the hydrological cycle is critical for Earth system stability. A resilient system is able to retain its function and structure in the face of external perturbations. Changes to driving hydrological variables, i.e., precipitation, evaporation, and soil moisture, are thought to be important drivers of terrestrial ecosystem resilience, and vice-versa through land-atmosphere feedbacks. Resilience has been estimated through time series analysis, where an increase in metrics of system recovery time can signal a loss of system resilience. To date, such methods of resilience analysis have not yet been applied to hydrological variables. As a result, there is limited quantification of the role of the water cycle in Earth system resilience.

Here, using remotely sensed time series data, we employ both early warning signals of resilience loss and indicators of rate-based tipping to asses resilience loss in key hydrological variables at the global scale. In doing so, we present a spatially distributed assessment of global water resilience, highlight regions vulnerable to resilience loss, and provide insights into how water resilience affects terrestrial ecosystem resilience. Changes to hydrological variables can have wide-reaching impacts on ecological (e.g., affecting biodiversity, ecosystem structure and function), and social systems (e.g., affecting crop yields in breadbasket regions). Here, we present a new dimension to the characterisation of regions vulnerable to resilience loss.

How to cite: Lotcheris, R., Wang-Erlandsson, L., and Rocha, J.: Remote sensing-based detection of resilience loss in the terrestrial water cycle, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17019, https://doi.org/10.5194/egusphere-egu24-17019, 2024.

To date, statues and trajectories of planetary boundaries have mostly been investigated separately, without fully quantifying if and to what extent transgression of one or more boundaries affects the status of respective others. To address this research gap, we have configured the state-of-the-art LPJmL Dynamic Global Vegetation Model so as to represent the terrestrial planetary boundaries (for land-system change, biosphere integrity, freshwater change, and biogeochemical/nitrogen flows) in an internally consistent, process-based framework. As the model simulates these boundaries’ underlying processes and control variables in a spatially explicit and dynamic manner, and as it also accounts for effects of climate change (a fifth planetary boundary considered through external forcing), it enables systematic studies of interactive effects among any of the five boundaries considered.

In a scenario study focused on here, we employed the model to systematically quantify the effects of different transgression levels of the climate change boundary (using gridded climate output from ten CMIP6 models for distinct atmospheric CO2 levels from 350 ppm to 1000 ppm) upon the land-system change boundary (areal extent of temperate, boreal and tropical forest biomes). Changes are analysed both by the end of this century and, to account for long-term legacy effects, by the end of the millennium, respectively. The simulations indicate that staying within the 350 ppm climate change boundary would stabilize the land-system change boundary, not inducing notable expansions or contractions of forest biome extent (on top of the historical shifts that have been brought about by anthropogenic deforestation). However, transgressing the climate change boundary beyond its zone of increasing risk (>450 ppm) is simulated to lead to increasingly substantial forest biome shifts, the higher the ppm level rises and the more time passes. Specifically, this involves a poleward tree-line shift, boreal forest dieback, expansion of temperate forest into today’s boreal zone, and a slight tropical forest expansion.

We furthermore find that these one-way interactions imply changes of the status of other planetary boundaries as well, as shifts in their control variables (e.g. large soil moisture and runoff anomalies) are simulated for the very areas where the forest biome shifts occur. Moreover, the vegetation changes are likely to provide feedback to the climate change boundary itself.

In additional simulations (making use of a planetary boundary simulation package linked to the LPJmL model), we investigate the historical evolution of the terrestrial planetary boundaries’ statuses during the past century. This examination suggests that the timing and spatial location of transgressions differs strongly among boundaries, with multiple boundaries crossed in the late 20th century, and transgression of the climate change boundary gaining increasing impact. Possible cascading and compound effects of these simultaneous transgressions, and particularly their likely aggravation in the future, require comprehensive analyses in further studies.

How to cite: Gerten, D., Tobian, A., Braun, J., Breier, J., and Stenzel, F.: Transgression of the climate change planetary boundary critically affects the status of other boundaries, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17216, https://doi.org/10.5194/egusphere-egu24-17216, 2024.

The capacity for tipping points in the climate system was elucidated decades ago by numerical climate models, which showed that nonlinearities could arise from physical interactions between the ocean, sea ice, and atmospheric components, leading to rapid shifts between qualitatively different states. However, there has been comparatively little work on physical interactions with the human component of the Earth system through numerical modeling due, in part, to the rarity of inclusion of the human system directly in Earth system models. Earth System economics provides a new approach for doing so, by proposing a particular set of physical variables that can be used as a basis for simulating such changes. These variables include spatially resolved population demography, time allocation to activities, a spatially resolved technosphere, and spatial networks that capture transportation fluxes. New global compilations of time use and technosphere data are helping to enable this approach, by quantifying the dependencies of material fluxes on time use and context. This opens the possibility of simulating long-term dynamics through motivated changes to time allocation, with outcomes dependent on the evolution of the technosphere and other coupled features of the Earth system. Examples will be discussed regarding how this approach can provide holistic, physically-grounded ways to identify possible nonlinearities and tipping points, by explicitly resolving aspects of human activities and technosphere changes, constrained by the conservation of mass, energy, and time.

How to cite: Galbraith, E.: Estimating possible nonlinearities in the Human-Earth system with Earth system economics, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17717, https://doi.org/10.5194/egusphere-egu24-17717, 2024.

The anticipated rise in the frequency of severe droughts triggered by events such as El Niño and abnormal warming of the Atlantic Ocean is expected to have profound impacts on the Amazon forest. However, whether the Amazon forest can effectively cope with changes in precipitation patterns and maintain its resilience remains to be determined. The impacts can vary across different regions of the Amazon due to the inherent heterogeneity in annual precipitation rate and periodicity in dry and wet periods. Furthermore, it is essential to highlight that resilience assessment frequently revolves around the ecosystem's ability to maintain or restore its carbon stock after a disturbance. Nonetheless, numerous other ecosystem processes and properties, such as evapotranspiration and functional diversity, might signal a shift in resilience before a consistent alteration in carbon stock becomes apparent. To address these concerns, our study will apply the trait-based vegetation model CAETÊ (CArbon and Ecosystem functional Trait Evaluation model). To comprehend the effects of an elevated frequency of decreased precipitation in the Amazon forest, we will apply a 20% precipitation reduction across three different frequencies: 7 years, 3 years, and 1 year. The model will be run across five distinct Amazon regions: northwest, center, south, northeast, and southeast. The assessment of resilience will encompass both resistance and recovery measures and will be evaluated using standard metrics such as carbon stock, while the analysis will extend to include other crucial indicators such as evapotranspiration, net primary productivity, and functional diversity. We anti