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This study evaluates the impact of lightning data assimilation (DA) on short-term forecasts of an extremely heavy rainfall event that occurred in Zhengzhou, Henan Province on July 20, 2021. Based on the Weather Research and Forecast (WRF) three-dimensional variational (3DVAR) data assimilation system (WRFDA), two cycling DA experiments were designed: one test (CONV) assimilated ground and sounding observation data (i. e., wind speed, wind direction, temperature, and air pressure), and the other test (LGDA) assimilated both conventional observations and pseudo-relative humidity observations derived from lightning data. The results of assimilated test were compared with those of the test without data assimilation (NoDA). Neither the analysis fields of CONV nor NoDA were able to simulate the echo structure of a strong convective system. Since LGDA increased the adjustment of the humidity field, its analysis field had a large increase in hydrometeor at the location where lightning strikes and the distribution of relative humidity and reflectivity was closest to the China Global Atmosphere Reanalysis data and radar reflectivity observations. The predictive precipitation shows that the spatial coverage of the rainstorm belt (6-h accumulated precipitation≥50 mm), as well as the location and amount of heavy precipitation center (6-h accumulated precipitation≥200 mm), have been well predicted by LGDA, demonstrating the positive impact of lightning DA on this extremely heavy rainfall event, especially the precipitation forecast for the first three hours. [ABSTRACT FROM AUTHOR]

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