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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Get engaged in EGUsphere, screen newly-submitted preprints before they are posted on the platform, and gain review experiences. We are looking forward to receiving your application. Apply now!

Recently-posted preprints

24 Aug 2026
A traceable grid-based framework for earthquake parametric insurance pricing: methodology and case studies in Indonesia
Hartati, Adhitya Ronnie Effendie, Nanang Susyanto, and Wiwit Suryanto
EGUsphere, https://doi.org/10.5194/egusphere-2026-2681,https://doi.org/10.5194/egusphere-2026-2681, 2026
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24 Aug 2026
Vertical responses of urban heat islands to heatwaves and their local climate zones dependence: a case study of Guangzhou, China
Fu Luo, Yuanjian Yang, Ting Sun, Zuofang Zheng, Xueyan Bi, Guoyu Ren, and Simone Lolli
EGUsphere, https://doi.org/10.5194/egusphere-2026-3392,https://doi.org/10.5194/egusphere-2026-3392, 2026
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24 Aug 2026
Measurement Methods and Applications of Atmospheric Refractivity Based on Raman Lidar
Yushang Wu, Xiaofeng Zhao, Zeming Zhou, Pinglv Yang, Deyang Li, Menglong Zhou, Kaijun Tu, Bo Wang, and Zhijin Qiu
EGUsphere, https://doi.org/10.5194/egusphere-2026-3895,https://doi.org/10.5194/egusphere-2026-3895, 2026
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24 Aug 2026
Enhancing Parameter Calibration in Land Surface Models Using a Multi-Task Surrogate Model within a Differentiable Parameter Learning Framework
Wenpeng Xie, Hongmei Li, and Kei Yoshimura
EGUsphere, https://doi.org/10.5194/egusphere-2026-4009,https://doi.org/10.5194/egusphere-2026-4009, 2026
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24 Aug 2026
Deep Reinforcement Learning – Driven Optimization of Ice Cloud Bulk Scattering Properties in RTTOV-SCATT Using Arctic Weather Satellite Observations
Ke Chen, Yuyang Yao, and Fujia Meng
EGUsphere, https://doi.org/10.5194/egusphere-2026-4021,https://doi.org/10.5194/egusphere-2026-4021, 2026
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