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Assimilation of FY-3D MWTS-Ⅱ Radiance with 3D Precipitation Detection and the Impacts on Typhoon Forecasts
作者姓名:Luyao QIN  Yaodeng CHEN  Gang MA  Fuzhong WENG  Deming MENG  Peng ZHANG
作者单位:1. Key Laboratory of Meteorological Disaster of Ministry of Education (KLME)/Joint International Research Laboratory of Climate and Environment Change (ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science & Technology;2. Earth System Modeling and Prediction Centre, China Meteorological Administration;3. Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites (LRCVES/CMA), National Satellite Meteorological Center, China Meteorological Administration (NSMC/CMA)
基金项目:jointly sponsored by the National Key Research and Development Program of China (Grant Nos. 2018YFC1506701 and 2017YFC1502102);;the National Natural Science Foundation of China (Grant No. 41675102);
摘    要: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 a...


Assimilation of FY-3D MWTS-II Radiance with 3D Precipitation Detection and the Impacts on Typhoon Forecasts
Luyao QIN,Yaodeng CHEN,Gang MA,Fuzhong WENG,Deming MENG,Peng ZHANG.Assimilation of FY-3D MWTS-II Radiance with 3D Precipitation Detection and the Impacts on Typhoon Forecasts[J].Advances in Atmospheric Sciences,2023,40(5):900-919.
Authors:Luyao QIN  Yaodeng CHEN  Gang MA  Fuzhong WENG  Deming MENG  Peng ZHANG
Abstract: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-II radiance 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 of 4.53% in typhoon track forecasts. The detailed diagnoses of Typhoon Lekima (2019) further show that the additional MWTS-II radiances 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.
Keywords:numerical weather prediction  radiance assimilation  microwave temperature sounding  FY-3D MWTS-II  precipitation detection
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