Gaoyuan qixiang (Dec 2023)

The Impact of Assimilating Himawari-8 Radiance Data on the Prediction of a Severe Storm over Sichuan-Chongqing Region

  • Hao LIANG,
  • Dongmei XU,
  • Aiqing SHU,
  • Xuewei ZHANG,
  • Lixin SONG

DOI
https://doi.org/10.7522/j.issn.1000-0534.2022.00112
Journal volume & issue
Vol. 42, no. 6
pp. 1478 – 1491

Abstract

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Himawari-8 is a new generation of stationary orbit imager, AHI (Advanced Himawari Imager) onboard is able to is able to provide observations with high spatial and temporal resolution to detect weather systems continuously over Sichuan - Chongqing Region.In this study, a numerical simulation is conducted for a severe regional storm event over Sichuan-Chongqing region on April 19, 2019 based on the weather Research and Forecasting (WRF) model.Furtherly, several radiance data assimilation experiments were performed for the storm with the WRF data assimilation (WRFDA) system from Himawari-8 AHI water vapor channels.Infrared radiance quality control and cloud detection procedures are conducted firstly.Cycling data assimilation schemes are further designed to investigate the impact of assimilating AHI radiance on the analyses and prediction of the weather system.The results show that the simulated brightness temperature of AHI water channels based on the radiative transfer model of CRTM in the analysis is more consistent with the observed brightness temperature than the those simulated from the background.It is also found that that assimilation of Himawari-8 AHI water vapor channels contributes to better describing the model initial conditions including the wind field, the water vapor field, and the radar reflectivity on multiple levels.Compared to the control experiment without any data assimilation, the forecast skill is enhanced in terms of predicting the main patterns of the precipitation after assimilating the AHI water vapor radiance data.To be specific, the assimilation experiment could capture the position of the main rainband and the center of heavy precipitation better.Through the AHI water vapor data assimilation, the heavy precipitation centers that are missed in the control experiment are successfully predicted.In addition, AHI radiance data assimilation experiment effectively improves the overestimated heavy precipitation from the control experiment in eastern Sichuan and southeastern Gansu for both the range and intensity.This study aims to provide the useful reference for the pretreatment and assimilation of geostationary infrared radiance data in the rainstorm system in numerical models over Sichuan-Chongqing Region.

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