Correlation Structures between Satellite All-Sky Infrared Brightness Temperatures and the Atmospheric State at Storm Scales  

作　　者：Yunji ZHANG Eugene E.CLOTHIAUX David J.STENSRUD 

机构地区：[1]Center for Advanced Data Assimilation and Predictability Techniques,and Department of Meteorology and Atmospheric Science,The Pennsylvania State University,University Park,Pennsylvania 16802,USA

出　　处：《Advances in Atmospheric Sciences》2022年第5期714-732,共19页大气科学进展（英文版）

基　　金：supported by the NASA under awards NNX15AQ51G and 80NSSC19K0728;the ONR under award N000141812517;the NOAA Office of Weather and Air Quality under award NA18OAR4590369.

摘　　要：This study explores the structures of the correlations between infrared(IR)brightness temperatures(BTs)from the three water vapor channels of the Advanced Baseline Imager(ABI)onboard the GOES-16 satellite and the atmospheric state.Ensemble-based data assimilation techniques such as the ensemble Kalman filter(EnKF)rely on correlations to propagate innovations of BTs to increments of model state variables.Because the three water vapor channels are sensitive to moisture in different layers of the troposphere,the heights of the strongest correlations between these channels and moisture in clear-sky regions are closely related to the peaks of their respective weighting functions.In cloudy regions,the strongest correlations appear at the cloud tops of deep clouds,and ice hydrometeors generally have stronger correlations with BT than liquid hydrometeors.The magnitudes of the correlations decrease from the peak value in a column with both vertical and horizontal distance.Just how the correlations decrease depend on both the cloud scenes and the cloud structures,as well as the model variables.Horizontal correlations between BTs and moisture,as well as hydrometeors,in fully cloudy regions decrease to almost 0 at about 30 km.The horizontal correlations with atmospheric state variables in clear-sky regions are broader,maintaining non-zero values out to~100 km.The results in this study provide information on the proper choice of cut-off radii in horizontal and vertical localization schemes for the assimilation of BTs.They also provide insights on the most efficient and effective use of the different water vapor channels.

关 键 词：severe storm remote sensing data assimilation numerical modeling 

分 类 号：P407[天文地球—大气科学及气象学]