The Advanced Radiative Transfer Modeling System(ARMS),a computationally efficient satellite observation operator,has been successfully integrated into the YinHe four-dimensional variational data assimilation(YH4DVAR)s...The Advanced Radiative Transfer Modeling System(ARMS),a computationally efficient satellite observation operator,has been successfully integrated into the YinHe four-dimensional variational data assimilation(YH4DVAR)system.This study investigates the impacts of assimilating Advanced Microwave Sounding Unit-A(AMSU-A)observations from the Meteorological Operational Satellite-C(MetOp-C)on the performance of YH4DVAR.Through a month-long global statistical analysis and a case study of Typhoon Hinnamnor,we evaluate the benefits of AMSUA data assimilation under clear sky conditions.Key findings are as follows.(1)ARMS achieves simulation accuracy comparable to RTTOV(Radiative Transfer for the Television and InfraRed Observation Satellite Operational Vertical sounder)version 11.2,demonstrating only a 0.5%discrepancy in data retention after quality control.(2)Implementation of ARMS as an operator in YH4DVAR enhances forecast accuracy for the 850-hPa temperature and 500-hPa geopotential height in the tropical region.(3)Compared to RTTOV,ARMS has improved the intensity forecast of Typhoon Hinnamnor and reduced mean wind speed errors by approximately 2%and central pressure errors by approximately1%.ARMS has now been operationally adopted as an alternative observational operator within YH4DVAR,demonstrating exceptional numerical stability,computational efficiency,and promising potential for future satellite data assimilation applications.展开更多
基金Supported by the National Key Research and Development Program of China(2021YFC3101500)National Natural Science Foundation of China(42075149,42375155,and 62372460)Natural Science Foundation of Hunan Province of China(2023JJ40667)。
文摘The Advanced Radiative Transfer Modeling System(ARMS),a computationally efficient satellite observation operator,has been successfully integrated into the YinHe four-dimensional variational data assimilation(YH4DVAR)system.This study investigates the impacts of assimilating Advanced Microwave Sounding Unit-A(AMSU-A)observations from the Meteorological Operational Satellite-C(MetOp-C)on the performance of YH4DVAR.Through a month-long global statistical analysis and a case study of Typhoon Hinnamnor,we evaluate the benefits of AMSUA data assimilation under clear sky conditions.Key findings are as follows.(1)ARMS achieves simulation accuracy comparable to RTTOV(Radiative Transfer for the Television and InfraRed Observation Satellite Operational Vertical sounder)version 11.2,demonstrating only a 0.5%discrepancy in data retention after quality control.(2)Implementation of ARMS as an operator in YH4DVAR enhances forecast accuracy for the 850-hPa temperature and 500-hPa geopotential height in the tropical region.(3)Compared to RTTOV,ARMS has improved the intensity forecast of Typhoon Hinnamnor and reduced mean wind speed errors by approximately 2%and central pressure errors by approximately1%.ARMS has now been operationally adopted as an alternative observational operator within YH4DVAR,demonstrating exceptional numerical stability,computational efficiency,and promising potential for future satellite data assimilation applications.
