Comparison of ERA5-Land and CMPAS reanalysis data for the regional assessment of precipitation in Chongqing, China

Precipitation data play a crucial role in meteorological research, and there are many different sources of precipitation data available. A comprehensive understanding of dataset reliability is essential for conducting research on weather and climate patterns studies. This study utilizes the multi-source hourly precipitation product from the China Meteorological Administration (CMA), derived from CMPAS, and the atmospheric reanalysis fifth-generation product (ERA5-Land) from the European Centre for Medium-Range Weather Forecasts (ECMWF).Through comparative analysis and evaluation of these two reanalysis precipitation products at different resolutions, the following conclusions are drawn: (1) The variation trends of ERA5-Land and CMPAS data are essentially consistent with the observed data. However, CMPAS exhibits smaller deviations, lower root mean square errors, and higher correlation coefficients. (2) In terms of accuracy at various precipitation levels, CMPAS outperforms ERA5-Land, which tends to overestimate low-level precipitation. (3) Across different terrain types, the quality of CMPAS is generally superior to ERA5-Land, particularly in the high-altitude regions of northeastern and southeastern Chongqing where ERA5-Land shows the greatest precipitation deviation and higher error values in mountainous areas compared to hills and plains. (4) Both CMPAS and GPM can effectively reproduce the spatial characteristics of precipitation. However, ERA5-Land and GPM tend to overestimate precipitation to some extent, while GPCP underestimates it, CMPAS is the closest to the observed values.

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Publication Details

Journal
Meteorology and Atmospheric Physics
Published
2025-02-07
DOI
https://doi.org/10.1007/s00703-025-01062-2
Citations
1
Primary Topic
Climate variability and models
Type
article
Field-Weighted Citation Impact
1.11

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article

Comparison of ERA5-Land and CMPAS reanalysis data for the regional assessment of precipitation in Chongqing, China

Yi Jiang, Linxiao Wei, Qingmeng Li, Fang Liu et al.
1 citations
Meteorology and Atmospheric Physics
Climate variability and models
1.11
article

Comparison of ERA5-Land and CMPAS reanalysis data for the regional assessment of precipitation in Chongqing, China

Yi Jiang, Linxiao Wei, Qingmeng Li, Fang Liu, Jun Zhu
article en
1 citations

Abstract

Precipitation data play a crucial role in meteorological research, and there are many different sources of precipitation data available. A comprehensive understanding of dataset reliability is essential for conducting research on weather and climate patterns studies. This study utilizes the multi-source hourly precipitation product from the China Meteorological Administration (CMA), derived from CMPAS, and the atmospheric reanalysis fifth-generation product (ERA5-Land) from the European Centre for Medium-Range Weather Forecasts (ECMWF).Through comparative analysis and evaluation of these two reanalysis precipitation products at different resolutions, the following conclusions are drawn: (1) The variation trends of ERA5-Land and CMPAS data are essentially consistent with the observed data. However, CMPAS exhibits smaller deviations, lower root mean square errors, and higher correlation coefficients. (2) In terms of accuracy at various precipitation levels, CMPAS outperforms ERA5-Land, which tends to overestimate low-level precipitation. (3) Across different terrain types, the quality of CMPAS is generally superior to ERA5-Land, particularly in the high-altitude regions of northeastern and southeastern Chongqing where ERA5-Land shows the greatest precipitation deviation and higher error values in mountainous areas compared to hills and plains. (4) Both CMPAS and GPM can effectively reproduce the spatial characteristics of precipitation. However, ERA5-Land and GPM tend to overestimate precipitation to some extent, while GPCP underestimates it, CMPAS is the closest to the observed values.

Meteorology and Atmospheric PhysicsVol. 137(2)
Hainan Meteorology Administration (CN), Chongqing Emergency Medical Center (CN), Qinghai Meteorological Bureau (CN), Hainan Meteorological Service (CN)
Key Technology Research and Development Program of Shandong
Climate action
Openalex Percentile: Top 27%
Climate variability and models
1.11
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