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Assessment of Representativeness and Accuracy for Multisource Meteorological Data During Rainstorms in Beijing

Year: 2026
Type: article
Abstract: Evaluating the representativeness and accuracy of multisource meteorological data is imperative due to their overwhelmingly indispensable role in extreme weather forecasting and data assimilation. The reliability of ground‐based remote sensing is evaluated using in situ measurements in this study, and the validated remote sensing data are subsequently employed to assess reanalysis across the troposphere. It is found that comparisons against in situ measurements demonstrate the reliability of microwave radiometer measurements and that microwave radiometry provides an effective complementary method for tropospheric profiling when evaluated against radiosonde observations. The microwave radiometer shows higher accuracy and representativeness compared to reanalysis within the boundary layer. Biases of two reanalysis data sets, CMA‐RA v1.5 (CRA) versus ERA5, reveal CRA's great potential for rainstorm researches. Weather‐dependent analysis shows the deterioration of representativeness from increasing atmospheric heterogeneity manifested by increasing humidity, whereas the representativeness of temperature remains high above the qualified threshold (>0.7).
DOI: 10.1029/2025jd045843
Authors: Yulong Tan, Jinyuan Xin, Xiang Qin, Yang Yang, Zifa Wang, Hang Su, Yongjing Ma, Yifan Tao, Ruixia Liu, Yiming Wei, Yuerong Li, Shaoting Zhang, Kecheng Peng, Xinbing Ren, Dandan Zhao
Institutions: Chinese Academy of Sciences, Northwest Institute of Eco-Environment and Resources, Institute of Atmospheric Physics, University of Chinese Academy of Sciences, State Key Laboratory of Severe Weather, Civil Aviation Flight University of China
Language: English
Open Access status: bronze
OpenAlex ID: W7225467297
FWCI:
Cites: 30
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Related to: 10