Assimilation of Additional Radiosonde Observation Helps Improve the Prediction of Typhoon-Related Rainfall in the Pearl River Delta

Abstract

Typhoons frequently hit the Pearl River Delta (PRD), threatening the region’s dense population and assets. Typhoon precipitation forecasting in this region is challenging, in part because of the complex hydrometeorological effects over the coast and the scarcity of upstream marine meteorological observations. Typhoon Mun was formed in the South China Sea on 2 July 2019, and it brought heavy rainfall to the PRD when its center moved to the Beibu Gulf. During Typhoon Mun, an additional sounding was conducted offshore in the PRD every 12 h to assess the incremental impact on the skill of precipitation forecasting. A precipitation prediction based on the Weather Research and Forecasting (WRF) Model underestimated the 12-h accumulated precipitation over the PRD by 87%, with the Final Analysis (FNL) data from the National Centers for Environmental Prediction in the United States as initial fields. To address this issue, we implemented a solution by reconstructing the initial field through the assimilation of the additional radiosonde observations using the WRF three-dimensional variational (3D-Var) method. The prediction with the new initial fields reduced the rainfall underestimation by 24%. A difference analysis indicates that the planetary boundary layer scheme used in FNL underestimates the low-level temperature and humidity, especially after the rainfall peak. In contrast, assimilation gives a more realistic lower-tropospheric structure, significantly enhancing the moisture flux convergence around 925 hPa and divergence around 700 hPa around the PRD. Sensitivity experiments show that assimilating atmospheric thermal (i.e., temperature and humidity) profiles is more helpful than dynamic (wind) profiles in improving the rainfall prediction of the typhoon.