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

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).