Articles | Volume 7, issue 2
https://doi.org/10.5194/wcd-7-743-2026
© 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/wcd-7-743-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
11 May 2026
Research article |
| 11 May 2026
| 11 May 2026
Impacts of orography and urbanization on extreme precipitation event in Beijing during 2023
Haobo Cui
State Key Laboratory of Earth Surface Processes and Disaster Risk Reduction, Faculty of Geographical Science, Beijing Normal University, Beijing, 100875 China
Hongyong Yu
State Key Laboratory of Earth Surface Processes and Disaster Risk Reduction, Faculty of Geographical Science, Beijing Normal University, Beijing, 100875 China
Xingshuo Zuo
State Key Laboratory of Earth Surface Processes and Disaster Risk Reduction, Faculty of Geographical Science, Beijing Normal University, Beijing, 100875 China
State Key Laboratory of Earth Surface Processes and Disaster Risk Reduction, Faculty of Geographical Science, Beijing Normal University, Beijing, 100875 China
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Shouye Xue and Guocan Wu
Hydrol. Earth Syst. Sci., 29, 5575–5591, https://doi.org/10.5194/hess-29-5575-2025, https://doi.org/10.5194/hess-29-5575-2025, 2025
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Soil moisture is influenced by both precipitation and evapotranspiration, with spatial heterogeneities and seasonal variations across different ecological zones. In this study, the joint distributions of precipitation and soil moisture were analyzed at monthly and annual scales. The negative dependences between soil moisture and precipitation were found, due to soil property changes induced by land–surface interactions. The results can enhance our understandings in drought and hydrometeorology.
Hongfei Hao, Kaicun Wang, Guocan Wu, Jianbao Liu, and Jing Li
Earth Syst. Sci. Data, 16, 4051–4076, https://doi.org/10.5194/essd-16-4051-2024, https://doi.org/10.5194/essd-16-4051-2024, 2024
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In this study, daily PM2.5 concentrations are estimated from 1959 to 2022 using a machine learning method at more than 5000 terrestrial sites in the Northern Hemisphere based on hourly atmospheric visibility data, which are extracted from the Meteorological Terminal Aviation Routine Weather Report (METAR).
Hongfei Hao, Kaicun Wang, Chuanfeng Zhao, Guocan Wu, and Jing Li
Earth Syst. Sci. Data, 16, 3233–3260, https://doi.org/10.5194/essd-16-3233-2024, https://doi.org/10.5194/essd-16-3233-2024, 2024
Short summary
Short summary
In this study, we employed a machine learning technique to derive daily aerosol optical depth from hourly visibility observations collected at more than 5000 airports worldwide from 1959 to 2021 combined with reanalysis meteorological parameters.
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Short summary
Numerical simulation is important in enhancing our understanding of hydrological processes. This study evaluated the effects of orography and land use on an extreme precipitation event, from several comparative schemes in a forecast model. It showed that, the orography and urban surfaces reshaped the spatiotemporal distribution of the extreme precipitation. As extreme precipitation events could be frequent in the future, it can enhance our understanding of extreme precipitation process.
Numerical simulation is important in enhancing our understanding of hydrological processes. This...
