葵花8号辐射率资料同化在一次川渝暴雨预报中的应用研究

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

新一代静止气象卫星葵花8号(Himawari-8)上搭载的静止轨道成像仪AHI(Advanced Himawari Imager)凭借其高时空分辨率可以对重庆地区暴雨进行连续观测。本文选取2019年4月19日的一次区域性暴雨天气过程为试验个例,采用WRF(Weather Research and Forecasting)中尺度模式进行数值模拟。基于WRFDA(Weather Research and Forecasting model Data Assimilation)同化系统对葵花8号静止气象卫星的AHI辐射率资料进行相应的质量控制和云检测,进而开展循环同化试验,考察卫星资料同化对这次强对流天气过程预报结果的改进。结果表明在同化AHI红外辐射率资料之后,辐射传输模式模拟的亮温和观测亮温更为接近。此外,AHI水汽通道辐射率资料同化有效提高了对各层高度上的风场、水汽场、雷达回波等要素特征的分析效果,并且使模式的初始条件更逼近真实的大气状态。研究发现同化AHI水汽通道辐射率资料后模拟的降水整体分布与实际情况更为接近,主要雨带位置以及强降水中心的精确程度显著高于背景场的预报效果。经过卫星同化的试验可以预报出控制试验漏报的强降水中心,并且有效地削弱了四川东部和甘肃东南部的虚假强降水范围以及强降水中心。本研究可以为川渝地区暴雨天气数值预报系统中的静止红外辐射率资料的预处理和同化应用提供有益的参考。

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.