Preliminary Study on Direct Assimilation of Cloud-affected Satellite Microwave Brightness Temperatures  

作　　者：Sibo ZHANG Li GUAN 

机构地区：[1]Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters,Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration,Nanjing University of Information Science and Technology,Nanjing 210044,China

出　　处：《Advances in Atmospheric Sciences》2017年第2期199-208,共10页大气科学进展（英文版）

基　　金：supported by the National Natural Science Foundation of China(Grant Nos.41575029 and 41375106);the Six Talent Peaks project of Jiangsu Province(Grant No.2014JY021)

摘　　要：Direct assimilation of cloud-affected microwave brightness temperatures from AMSU-A into the GSI three-dimensional variational （3D-Var） assimilation system is preliminarily studied in this paper. A combination of cloud microphysics param- eters retrieved by the 1D-Var algorithm （including vertical profiles of cloud liquid water content, ice water content, and rain water content） and atmospheric state parameters from objective analysis fields of an NWP model are used as background fields. Three cloud microphysics parameters （cloud liquid water content, ice water content, and rain water content） are ap- plied to the control variable. Typhoon Halong （2014） is selected as an example. The results show that direct assimilation of cloud-affected AMSU-A observations can effectively adjust the structure of large-scale temperature, humidity and wind anal- ysis fields due to the assimilation of more AMSU-A observations in typhoon cloudy areas, especially typhoon spiral cloud belts. These adjustments, with temperatures increasing and humidities decreasing in the movement direction of the typhoon, bring the forecasted typhoon moving direction closer to its real path. The assimilation of cloud-affected satellite microwave brightness temperatures can provide better analysis fields that are more similar to the actual situation. Furthermore, typhoon prediction accuracy is improved using these assimilation analysis fields as the initial forecast fields in NWP models.Direct assimilation of cloud-affected microwave brightness temperatures from AMSU-A into the GSI three-dimensional variational （3D-Var） assimilation system is preliminarily studied in this paper. A combination of cloud microphysics param- eters retrieved by the 1D-Var algorithm （including vertical profiles of cloud liquid water content, ice water content, and rain water content） and atmospheric state parameters from objective analysis fields of an NWP model are used as background fields. Three cloud microphysics parameters （cloud liquid water content, ice water content, and rain water content） are ap- plied to the control variable. Typhoon Halong （2014） is selected as an example. The results show that direct assimilation of cloud-affected AMSU-A observations can effectively adjust the structure of large-scale temperature, humidity and wind anal- ysis fields due to the assimilation of more AMSU-A observations in typhoon cloudy areas, especially typhoon spiral cloud belts. These adjustments, with temperatures increasing and humidities decreasing in the movement direction of the typhoon, bring the forecasted typhoon moving direction closer to its real path. The assimilation of cloud-affected satellite microwave brightness temperatures can provide better analysis fields that are more similar to the actual situation. Furthermore, typhoon prediction accuracy is improved using these assimilation analysis fields as the initial forecast fields in NWP models.

关 键 词：atmospheric sounding microwave remote sensing data assimilation cloudy radiances GSI 

分 类 号：P407.7[天文地球—大气科学及气象学]