Assimilation and Evaluation of the COSMIC–2 and Sounding Data in Tropospheric Atmospheric Refractivity Forecasting across the Yellow Sea through an Ocean–Atmosphere–Wave Coupled Model

Author:

Wu Sheng1,Song Jiayu1,Zou Jing2,Tian Xiangjun3,Qiu Zhijin2ORCID,Wang Bo2,Hu Tong2,Li Zhiqian2ORCID,Zhang Zhiyang4

Affiliation:

1. Yantai Research Institute, Harbin Engineering University, Yantai 264000, China

2. Institute of Oceanographic Instrumentation, Qilu University of Technology (Shandong Academy of Sciences), Qingdao 266001, China

3. Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China

4. Jiangsu Key Laboratory of Function Control Technology for Advanced Materials, Jiangsu Ocean University, Lianyungang 222000, China

Abstract

In this study, a forecasting model was developed based on the COAWST and atmospheric 3D EnVar module to investigate the effects of assimilation of the sounding and COSMIC–2 data on the forecasting of the revised atmospheric refraction. Three groups of 72 h forecasting tests, with assimilation of different data obtained for a period of one month, were constructed over the Yellow Sea. The results revealed that the bias of the revised atmospheric refraction was the lowest if both the sounding and COSMIC–2 data were assimilated. As a result of the assimilation of the hybrid data, the mean bias reduced by 6.09–6.28% within an altitude of 10 km, and the greatest reduction occurred below the altitude of 3000 m. In contrast, the test that assimilated only the sounding data led to an increase in bias at several levels. This increased bias was corrected after the introduction of the COSMIC–2 data, with the mean correction of 1.6 M within the middle and lower troposphere. During the typhoon period, the improvements in the assimilation were more significant than usual. The improved forecasts of the revised atmospheric refraction were mainly due to the moisture changes within the middle and lower troposphere, while the changes in the upper troposphere were influenced by multiple factors.

Funder

the Natural Science Foundation of Shandong province, China

Jiangsu Ocean University

Publisher

MDPI AG

Subject

Atmospheric Science,Environmental Science (miscellaneous)

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