EGUsphere – The preprint repository hosted by the European Geosciences Union

EGUsphere, the not-for-profit open scientific repository of the European Geosciences Union (EGU), brings together preprints in the domain of Earth, Space, and Planetary sciences in a diverse, inclusive, and systematic collection of contributions, including:

EGUsphere is transparent and interactive, giving authors of presentations and preprints the opportunity to receive attributed comments from the public aimed at stimulating discussion, cooperation, and to revise their materials in open review.

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Recently-posted preprints

15 Sep 2025
Estimation of CO2 fluxes in the cities of Zurich and Paris using the ICON-ART CTDAS inverse modelling framework
Nikolai Ponomarev, Michael Steiner, Erik Koene, Pascal Rubli, Stuart Grange, Lionel Constantin, Michel Ramonet, Leslie David, Lukas Emmenegger, and Dominik Brunner
EGUsphere, https://doi.org/10.5194/egusphere-2025-3668,https://doi.org/10.5194/egusphere-2025-3668, 2025
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15 Sep 2025
Inferring the role of IPO phase dependencies and extratropical internal variability on the tropics
Mark Collier, Dylan Harries, and Terence O'Kane
EGUsphere, https://doi.org/10.5194/egusphere-2025-3948,https://doi.org/10.5194/egusphere-2025-3948, 2025
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15 Sep 2025
A Physics-Constrained Deep-Learning Framework based on Long-Term Remote-Sensing Data for Retrieving Vertical Distribution of PM2.5 Chemical Components
Hongyi Li, Ting Yang, Yele Sun, and Zifa Wang
EGUsphere, https://doi.org/10.5194/egusphere-2025-4237,https://doi.org/10.5194/egusphere-2025-4237, 2025
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15 Sep 2025
Exceptional high AOD over Svalbard in Summer 2019: A multi-instrumental approach
Sara Herrero-Anta, Sabine Eckhardt, Nikolaos Evangeliou, Stefania Gilardoni, Sandra Graßl, Dominic Heslin-Rees, Stelios Kazadzis, Natalia Kouremeti, Radovan Krejci, David Mateos, Mauro Mazzola, Christoph Ritter, Roberto Román, Kerstin Stebel, and Tymon Zielinski
EGUsphere, https://doi.org/10.5194/egusphere-2025-3423,https://doi.org/10.5194/egusphere-2025-3423, 2025
Discussion: open, 0 comments
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15 Sep 2025
An explainable semi-supervised deep learning framework for mineral prospectivity mapping: DEEP-SEAM v1.0
Zijing Luo, Ehsan Farahbakhsh, Stephen Hore, and R. Dietmar Müller
EGUsphere, https://doi.org/10.5194/egusphere-2025-3283,https://doi.org/10.5194/egusphere-2025-3283, 2025
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