Assimilation of FY-3D MWTS-Ⅱ Radiance with 3D Precipitation Detection and the Impacts on Typhoon Forecasts

Precipitation detection is an essential step in radiance assimilation because the uncertainties in precipitation would affect the radiative transfer calculation and observation errors.The traditional precipitation detection method for microwave only detects clouds and precipitation horizontally,without considering the three-dimensional distribution of clouds.Extending precipitation detection from 2D to 3D is expected to bring more useful information to the data assimilation without using the all-sky approach.In this study,the 3D precipitation detection method is adopted to assimilate Microwave Temperature Sounder-2(MWTS-Ⅱ)onboard the Fengyun-3D,which can dynamically detect the channels above precipitating clouds by considering the near-real-time cloud parameters.Cycling data assimilation and forecasting experiments for Typhoons Lekima(2019)and Mitag(2019)are carried out.Compared with the control experiment,the quantity of assimilated data with the 3D precipitation detection increases by approximately 23%.The quality of the additional MWTS-Ⅱradiance data is close to the clear-sky data.The case studies show that the average root-mean-square errors(RMSE)of prognostic variables are reduced by 1.7%in the upper troposphere,leading to an average reduction of4.53%in typhoon track forecasts.The detailed diagnoses of Typhoon Lekima(2019)further show that the additional MWTS-Ⅱradiances brought by the 3D precipitation detection facilitate portraying a more reasonable circulation situation,thus providing more precise structures.This paper preliminarily proves that 3D precipitation detection has potential added value for increasing satellite data utilization and improving typhoon forecasts.

A Precipitation Detection Method for MWTS-Ⅱ Radiance Assimilation in Typhoon Simulation

FY-3C Microwave Temperature SounderⅡ(MWTS-Ⅱ)lacks observations at 23.8 GHz,31 GHz and 89 GHz,making it difficult to remove the data contaminated by precipitation in assimilation.In this paper,a fast forward operator based on the Community Radiative Transfer Model(CRTM)was used to analyze the relationship between the observation minus background simulation(O-B)and the cloud fractions in different MWTS-Ⅱchannels.In addition,based on the community Gridpoint Statistical Interpolation(GSI)system,the radiation brightness temperature of the MWTS-Ⅱwas assimilated in the regional Numerical Weather Prediction(NWP)model.In the process of assimilation,Visible and Infrared Radiometer(VIRR)cloud detection products were matched to MWTS-Ⅱpixels for precipitation detection.For typhoon No.18 in 2014,impact tests of MWTS-Ⅱdata assimilation was carried out.The results show that,though the bias observation minus analysis(O-A)of assimilated data can be reduced by quality control only with|O-B|<3 K;however,the O-A becomes much smaller while the precipitation detection is performed with Fvirr<0.9(VIRR cloud fraction threshold of 0.9).Besides,the change of the environmental field around the typhoon is more conducive to make the simulated track closer to the observation.The 72-hour typhoon track simulation error also shows that,after the precipitation detection,the error of simulated typhoon track is significantly reduced,which reflects the validity of a precipitation detection method based on a double criterion of|O-B|<3 K and Fvirr<0.9.