Improving All-sky Simulations of Typhoon Cloud/Rain Band Structures of NOAA-20 CrIS Window Channel Observations

Abstract

The Cross-track Infrared Sounder (CrIS) observations (O) contributed greatly to numerical weather prediction. Further contribution depends on the success of all-sky data assimilation, which requires a method to produce realistic cloud/rain band structures from background fields (i. e., 6-h forecasts), and to remove large biases of all-sky simulation of brightness temperature in the presence of clouds. In this study, CrIS all-sky simulations of brightness temperatures at an arbitrarily selected window channel within Typhoon Hinnamnor (2022) are investigated. The 3-km Weather Research and Forecasting model with three microphysics schemes were used to produce 6-h background forecasts (B). The O−B statistic deviate greatly from Gaussian distribution with large biases in either water clouds, or thin ice clouds, or thick ice clouds within Typhoon Hinnamnor. By developing a linear regression function of three all-sky simulations of brightness temperature from 6-h forecasts with three microphysics schemes, the O−B statistics approximate a Gaussian normal distribution in water clouds, thin ice clouds and thick ice clouds. Taking the regression function that is established by a training dataset to combine 6-h background forecasts at later times, the cloud/rain band structures compared much more favorably with CrIS observations than those from an individual microphysics, and the O−B biases are significantly reduced. The work in this study to quantify and remove biases in background fields of brightness temperature and generating realistic typhoon cloud/rain band structures in background fields will allow a better description of center position, intensity and size to improve typhoon forecasts.