Articles | Volume 19, issue 14
https://doi.org/10.5194/gmd-19-6857-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-19-6857-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
MErSiM v1.0: resolving biases in global silicate weathering model with a data-driven surface erosion module
Jiaxi Zhao
Laboratory for Climate and Ocean-Atmosphere Studies, Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing 100871, China
Laboratory for Climate and Ocean-Atmosphere Studies, Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing 100871, China
Institute of Carbon Neutrality, Peking University, Beijing, China
Institute of Ocean Research, Peking University, Beijing, China
Yongyun Hu
Laboratory for Climate and Ocean-Atmosphere Studies, Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing 100871, China
Institute of Ocean Research, Peking University, Beijing, China
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EGUsphere, https://doi.org/10.5194/egusphere-2026-3925, https://doi.org/10.5194/egusphere-2026-3925, 2026
This preprint is open for discussion and under review for Climate of the Past (CP).
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EGUsphere, https://doi.org/10.5194/egusphere-2026-1385, https://doi.org/10.5194/egusphere-2026-1385, 2026
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This study investigates the dramatic global cooling during the Late Ordovician, 440 million years ago. Our simulations reveal a powerful feedback loop: as the ice sheet grew, it generated strong, cold winds flowing down its slopes. These winds further cooled the continents, causing the ice sheet to expand even more. The super ice sheet led to a substantial global temperature drop of about 1.5 °C. Interestingly, while continents froze, the oceans warmed.
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The Cryosphere, 19, 6381–6402, https://doi.org/10.5194/tc-19-6381-2025, https://doi.org/10.5194/tc-19-6381-2025, 2025
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Clim. Past, 21, 1263–1279, https://doi.org/10.5194/cp-21-1263-2025, https://doi.org/10.5194/cp-21-1263-2025, 2025
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For 1 century, the hemispheric summer insolation is proposed as a key pacemaker of astronomical climate change. However, an increasing number of geologic records reveal that the low-latitude hydrological cycle shows asynchronous precessional evolutions that are very often out of phase with the summer insolation. Here, we propose that the astronomically driven low-latitude hydrological cycle is not paced by summer insolation but by shifting perihelion.
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Clim. Past, 20, 1195–1211, https://doi.org/10.5194/cp-20-1195-2024, https://doi.org/10.5194/cp-20-1195-2024, 2024
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We analyse simulations with idealised aerosol scenarios to examine the importance of aerosol forcing on mPWP precipitation and how aerosol uncertainty could explain the data–model mismatch. We find further warming, a narrower and stronger ITCZ, and monsoon domain rainfall change after removal of industrial emissions. Aerosols have more impacts on tropical precipitation than the mPWP boundary conditions. This highlights the importance of prescribed aerosol scenarios in simulating mPWP climate.
Haoyue Zuo, Yonggang Liu, Gaojun Li, Zhifang Xu, Liang Zhao, Zhengtang Guo, and Yongyun Hu
Geosci. Model Dev., 17, 3949–3974, https://doi.org/10.5194/gmd-17-3949-2024, https://doi.org/10.5194/gmd-17-3949-2024, 2024
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Compared to the silicate weathering fluxes measured at large river basins, the current models tend to systematically overestimate the fluxes over the tropical region, which leads to an overestimation of the global total weathering flux. The most possible cause of such bias is found to be the overestimation of tropical surface erosion, which indicates that the tropical vegetation likely slows down physical erosion significantly. We propose a way of taking this effect into account in models.
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Short summary
By using artificial intelligence and geological measurements, we built a machine learning model that accurately shows how landscapes erode. With this module included we developed a new silicate weatherig model, named MErSiM v1.0, which corrected a major overestimation of weathering flux in models simulating Earth’s long-term carbon cycle. This revealed that Earth's natural ability to remove atmospheric carbon dioxide is profoundly weaker under intense warming than previously understood.
By using artificial intelligence and geological measurements, we built a machine learning model...