Microwave radiance data assimilation(DA)enhances initial conditions for numerical weather prediction(NWP)and shows great potential for improving forecasts in tropical regions like East Africa,where observational data ...Microwave radiance data assimilation(DA)enhances initial conditions for numerical weather prediction(NWP)and shows great potential for improving forecasts in tropical regions like East Africa,where observational data scarcity and complex tropical dynamics present significant challenges.Effectiveness of radiance assimilation is a function of variations in channel sensitivity to local atmospheric conditions and region-specific bias characteristics.However,microwave radiance assimilation in Limited-Area Models(LAMs)over East Africa remains largely unexplored.This study investigates the impact of assimilating microwave radiance channels with weighting functions peaking in the troposphere and lower stratosphere on rainfall forecasts over East Africa from a five-satellite constellation:the Microwave Temperature Sounder-2(MWTS-2)onboard Fengyun-3D(FY-3D),the Advanced Technology Microwave Sounder(ATMS)onboard JPSS,and the Advanced Microwave Sounding Unit-A(AMSU-A)onboard NOAA-15/18/19 satellites.The 6-h cycling DA experiments over a convectively active 15-day period show that assimilation of ATMS and AMSU-A radiances enhances representation of initial conditions,thereby reducing analysis and forecast errors.Assimilation of MWTS-2 radiances improves the analysis and forecasts further,especially for the tropospheric thermodynamic fields.The joint multi-microwave assimilation fills critical observation gaps over East Africa,allowing realistic simulations of diurnal precipitation trends,and capturing rainfall intensities exceeding 50 mm in 24 h,especially for T+12-h to T+24-h lead times.These findings are validated by a high-intensity rainfall case over Mandera,where spatio-temporal consistency is observed in instability and convection triggering.Forecast evaluation metrics have confirmed enhanced rainfall forecast skill for deep and rapidly developing convective systems.The study provides valuable insights into the gains of assimilating microwave radiance data over tropical regions,particularly in East Africa.展开更多
Accurate information on atmospheric temperature of tropical cyclones （TCs） is important for monitoring and pre- diction of their developments and evolution. For hurricanes, temperature anomaly in the upper troposphe...Accurate information on atmospheric temperature of tropical cyclones （TCs） is important for monitoring and pre- diction of their developments and evolution. For hurricanes, temperature anomaly in the upper troposphere can be de-rived from Advanced Microwave Sounding Unit （AMSU） and Advanced Technology Microwave Sounder （ATMS） through either regression-based or variational retrieval algorithms. This study investigates the dependency of TC warm core structure on emission and scattering processes in the forward operator used for radiance computations in temperature retrievals. In particular, the precipitation scattering at ATMS high-frequency channels can significantly change the retrieval outcomes. The simulation results in this study reveal that the brightness temperatures at 183 GHz could be depressed by 30-50 K under cloud ice water path of 1.5 mm, and thus, the temperature structure in hur-ricane atmosphere could be distorted if the ice cloud scattering was inaccurately characterized in the retrieval system. It is found that for Hurricanes Irma, Maria, and Harvey that occurred in 2017, their warm core anomalies retrieved from ATMS temperature sounding channels 4 15 were more reasonable and realistic, compared with the retrievals from all other channel combinations and earlier hurricane simulation results.展开更多
基金Supported by the National Natural Science Foundation of China(U2442218 and U2442601)。
文摘Microwave radiance data assimilation(DA)enhances initial conditions for numerical weather prediction(NWP)and shows great potential for improving forecasts in tropical regions like East Africa,where observational data scarcity and complex tropical dynamics present significant challenges.Effectiveness of radiance assimilation is a function of variations in channel sensitivity to local atmospheric conditions and region-specific bias characteristics.However,microwave radiance assimilation in Limited-Area Models(LAMs)over East Africa remains largely unexplored.This study investigates the impact of assimilating microwave radiance channels with weighting functions peaking in the troposphere and lower stratosphere on rainfall forecasts over East Africa from a five-satellite constellation:the Microwave Temperature Sounder-2(MWTS-2)onboard Fengyun-3D(FY-3D),the Advanced Technology Microwave Sounder(ATMS)onboard JPSS,and the Advanced Microwave Sounding Unit-A(AMSU-A)onboard NOAA-15/18/19 satellites.The 6-h cycling DA experiments over a convectively active 15-day period show that assimilation of ATMS and AMSU-A radiances enhances representation of initial conditions,thereby reducing analysis and forecast errors.Assimilation of MWTS-2 radiances improves the analysis and forecasts further,especially for the tropospheric thermodynamic fields.The joint multi-microwave assimilation fills critical observation gaps over East Africa,allowing realistic simulations of diurnal precipitation trends,and capturing rainfall intensities exceeding 50 mm in 24 h,especially for T+12-h to T+24-h lead times.These findings are validated by a high-intensity rainfall case over Mandera,where spatio-temporal consistency is observed in instability and convection triggering.Forecast evaluation metrics have confirmed enhanced rainfall forecast skill for deep and rapidly developing convective systems.The study provides valuable insights into the gains of assimilating microwave radiance data over tropical regions,particularly in East Africa.
基金Supported by the National Natural Science Foundation of China(91337218 and 41475103)China Meteorological Administration Special Public Welfare Research Fund(GYHY201406008)
文摘Accurate information on atmospheric temperature of tropical cyclones （TCs） is important for monitoring and pre- diction of their developments and evolution. For hurricanes, temperature anomaly in the upper troposphere can be de-rived from Advanced Microwave Sounding Unit （AMSU） and Advanced Technology Microwave Sounder （ATMS） through either regression-based or variational retrieval algorithms. This study investigates the dependency of TC warm core structure on emission and scattering processes in the forward operator used for radiance computations in temperature retrievals. In particular, the precipitation scattering at ATMS high-frequency channels can significantly change the retrieval outcomes. The simulation results in this study reveal that the brightness temperatures at 183 GHz could be depressed by 30-50 K under cloud ice water path of 1.5 mm, and thus, the temperature structure in hur-ricane atmosphere could be distorted if the ice cloud scattering was inaccurately characterized in the retrieval system. It is found that for Hurricanes Irma, Maria, and Harvey that occurred in 2017, their warm core anomalies retrieved from ATMS temperature sounding channels 4 15 were more reasonable and realistic, compared with the retrievals from all other channel combinations and earlier hurricane simulation results.
