Synergistic Effects of Infrared and Microwave Radiance in All-sky Data Assimilation for a Heavy Precipitation Case over the Korean Peninsula

Abstract

This study investigates how the integration strategy of infrared (IR) and microwave (MW) brightness temperatures (TBs) influences precipitation forecasting within an all-sky radiance data assimilation (DA) framework using a three-dimensional variational method. To improve heavy rainfall forecasts over Korea, we propose an asynchronous assimilation approach in which, when both IR and MW observations are available, only MW TBs are assimilated, and IR TBs are intentionally excluded to reduce redundancy and potential inconsistencies in cloud representation. The case study, focusing on a heavy precipitation event over the Korean Peninsula, employs IR TBs from the Himawari Imager (AHI) on Himawari-8 and MW TB from the Global Precipitation Measurement (GPM) Microwave Imager (GMI) and the Advanced Microwave Scanning Radiometer 2 (AMSR2) aboard the Global Change Observing Mission (GCOM-W). For comparison, two conventional synchronous strategies are conducted as baselines: one integrating clear-sky IR with all-sky MW, and the other integrating all-sky IR with all-sky MW. Results show that the asynchronous approach achieves the best balance between upper-level solid and lower-level liquid hydrometeors, leading to the most accurate precipitation forecasts. In contrast, with synchronous approaches, the all-sky IR with MW strategy enhances upper-level clouds but reduces low-level moisture, potentially resulting in localized heavy rainfall. Meanwhile, the clear-sky IR with MW approach underestimates upper-level cloud structures, which contributes to underestimation of stratiform rainfall. These findings highlight the importance of optimally designed IR–MW integration strategies for this specific heavy precipitation event and provide insights for future improvements in satellite-based precipitation assimilation systems. © 2008-2012 IEEE.