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Original Paper

Assimilation of MetOp-C AMSU-A Data Using the ARMS as an Observation Operator in the YH4DVAR System

College of Meteorology and Oceanography, National University of Defense Technology, Changsha 410073
College of Computer Science and Technology, National University of Defense Technology, Changsha 410073
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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.

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Journal of Meteorological Research
Pages 252-271

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Cite this article:
LUO T, MA S, ZHANG W, et al. Assimilation of MetOp-C AMSU-A Data Using the ARMS as an Observation Operator in the YH4DVAR System. Journal of Meteorological Research, 2025, 39(2): 252-271. https://doi.org/10.1007/s13351-025-4206-2

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Received: 25 October 2024
Published: 11 February 2025
© The Chinese Meteorological Society and Springer-Verlag Berlin Heidelberg 2024