OSSEs on the FY-4M Geostationary Microwave Satellite Based on CMA-GFS and CMA-MESO | IEEE Journals & Magazine | IEEE Xplore

OSSEs on the FY-4M Geostationary Microwave Satellite Based on CMA-GFS and CMA-MESO


Abstract:

Geostationary orbit (GEO) microwave sounding technology, which can continuously monitor Earth and intensively observe weather conditions such as strong convection, has un...Show More

Abstract:

Geostationary orbit (GEO) microwave sounding technology, which can continuously monitor Earth and intensively observe weather conditions such as strong convection, has unique advantages. An observing system simulation experiment (OSSE) is an important means to evaluate new meteorological instruments and explore assimilation techniques for new observations. In this article, an OSSE based on the China Fengyun-4M (FY-4M) GEO microwave satellite is introduced in detail. The nature run (NR) of the OSSE is generated by the Mesoscale Weather Numerical Forecast System of the China Meteorological Administration (CMA-MESO), while the Global Forecast System of the CMA (CMA-GFS) is used to achieve the 4-D variational (4D-Var) assimilation and prediction experiment. The atmospheric parameters from the NR are used as inputs to the radiative transfer (RT) for the TIROS operational vertical sounder (RTTOV) model to simulate the FY-4M GEO microwave brightness temperature. The OSSE results show that assimilating GEO microwave data has a positive effect on typhoon forecasting. Specifically, the shorter the observation time interval is, the smaller the observation noise and the better the assimilation effect. There are differences in the role of different frequency band channels in improving forecasts; the best observation effect can only be achieved by setting the observation error appropriately, and the data preprocessing strategy is crucial for improving the assimilation quality. The GEO microwave OSSE further reveals the influence of future FY-4M geostationary microwave observations on typhoon forecasts and the issues that need to be addressed when assimilating these new data.
Article Sequence Number: 5302819
Date of Publication: 29 October 2024

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I. Introduction

Passive microwave remote sensing can obtain atmospheric parameters inside clouds and precipitation, playing a crucial role in weather forecasting [1]. The existing microwave atmospheric sounders are, however, equipped with a limited number of polar-orbiting meteorological satellites, restricting the ability to collect high-frequency temporal observations for specific regions [2]. Although geostationary satellites have the unique advantage of continuously monitoring the Earth in meteorological applications, achieving high spatial resolution geostationary microwave observations still faces technical challenges.

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