@article{LUO2025, 
author = {Tengling LUO and Shuo MA and Weimin ZHANG and Yanlai ZHAO and Yi YU and Jinhui YANG and Shaoying LI},
title = {Assimilation of MetOp-C AMSU-A Data Using the ARMS as an Observation Operator in the YH4DVAR System},
year = {2025},
journal = {Journal of Meteorological Research},
volume = {39},
number = {2},
pages = {252-271},
keywords = {Advanced Radiative Transfer Modeling System (ARMS), Radiative Transfer for the Television and Infrared Observation Satellite Operational Vertical Sounder (RTTOV), data assimilation, Advanced Microwave Sounding Unit-A (AMSU-A)},
url = {https://www.sciopen.com/article/10.1007/s13351-025-4206-2},
doi = {10.1007/s13351-025-4206-2},
abstract = {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 AMSU-A 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 Verti-cal 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 approximately 1%. ARMS has now been operationally adopted as an alternative observational operator wi-thin YH4DVAR, demonstrating exceptional numerical stability, computational efficiency, and promising potential for future satellite data assimilation applications.}
}