Topographical influence on kilometer-scale hourly precipitation prediction during the 2021 Zhengzhou flood

Topographical forcing plays a fundamental role in extreme precipitation events. This study investigates the influence of topographical factors on the 3-km hourly precipitation forecast from the China Meteorological Administration’s Mesoscale Weather Numerical Forecast System (CMA-MESO) during the 2021 Zhengzhou flood by employing spatio-temporal geographically weighted regression (GTWR). The results show that CMA-MESO overestimates the topographical impact on the spatial distribution of precipitation while underestimating its influence on the temporal variation of precipitation during the extreme event. The model’s underestimation of heavy precipitation in Zhengzhou can be largely attributed to the dominant influence of the near-surface temperature (ST)-precipitation relationship, which exhibits greater temporal stability in the model than in the observation. This study expands the application of GTWR to quantify the temporally varying topographical influence on extreme precipitation event, filling a gap in the understanding of non-stationary topographical forcing. Furthermore, it provides insights for improving the planet boundary layer (PBL) and orographic parameterization schemes in kilometer-scale predictions.

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Publication Details

Journal
Natural Hazards
Published
2025-12-26
DOI
https://doi.org/10.1007/s11069-025-07790-3
Primary Topic
Meteorological Phenomena and Simulations
Type
article
Field-Weighted Citation Impact
0.00

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article

Topographical influence on kilometer-scale hourly precipitation prediction during the 2021 Zhengzhou flood

Linyun Yang, Haoming Chen
Natural Hazards
Meteorological Phenomena and Simulations
article

Topographical influence on kilometer-scale hourly precipitation prediction during the 2021 Zhengzhou flood

Linyun Yang, Haoming Chen
article en

Abstract

Topographical forcing plays a fundamental role in extreme precipitation events. This study investigates the influence of topographical factors on the 3-km hourly precipitation forecast from the China Meteorological Administration’s Mesoscale Weather Numerical Forecast System (CMA-MESO) during the 2021 Zhengzhou flood by employing spatio-temporal geographically weighted regression (GTWR). The results show that CMA-MESO overestimates the topographical impact on the spatial distribution of precipitation while underestimating its influence on the temporal variation of precipitation during the extreme event. The model’s underestimation of heavy precipitation in Zhengzhou can be largely attributed to the dominant influence of the near-surface temperature (ST)-precipitation relationship, which exhibits greater temporal stability in the model than in the observation. This study expands the application of GTWR to quantify the temporally varying topographical influence on extreme precipitation event, filling a gap in the understanding of non-stationary topographical forcing. Furthermore, it provides insights for improving the planet boundary layer (PBL) and orographic parameterization schemes in kilometer-scale predictions.

Natural HazardsVol. 122(1)
Chinese Academy of Meteorological Sciences (CN)
National Aeronautics and Space Administration, National Natural Science Foundation of China
Climate action
Openalex Percentile: Top 32%
Meteorological Phenomena and Simulations
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