Preprints
https://doi.org/10.5194/acp-2021-298
https://doi.org/10.5194/acp-2021-298

  21 Apr 2021

21 Apr 2021

Review status: this preprint is currently under review for the journal ACP.

Study on the seasonal variation of Aeolus detection performance over China using ERA5 and radiosonde data

Siying Chen1, Rongzheng Cao1, Yixuan Xie1, Yinchao Zhang1, Wangshu Tan1, He Chen1, Pan Guo1, and Peitao Zhao2 Siying Chen et al.
  • 1School of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, China
  • 2Meterological Observation Center of CMA, Beijing 100081, China

Abstract. Aeolus wind products have been available to ordinary users on May 12, 2020. In this paper, the Aeolus wind observations, L-band radiosonde (L-band RS) data and the European Centre for Medium-Range Weather Forecasts (ECMWF) fifth generation atmospheric reanalyses (ERA5) are used to analyse the seasonality of Aeolus detection performance over China. Based on the Rayleigh-clear data and Mie-cloudy data, the data quality of the Aeolus effective detection data is verified, and the results show that the Aeolus data is in good agreement with the L-band RS data and the ERA5 data. The relative errors of Aeolus data in the four regions (Chifeng, Baoshan, Shapingba and Qingyuan) in China were calculated according to different months (July to December 2019, May to October 2020). The relative error of the Rayleigh-clear data in summer is significantly higher than that in winter, as the mean relative error parameter in July is 174 % higher than that in December. Besides, the distribution about the wind direction and the high-altitude clouds in different months (July and December) are analysed. The results show that the distribution of angle, between the horizontal wind direction of the atmosphere and the horizontal line of sight (HLOS), has a greater proportion in the high error interval (70°–110°) in summer, and this proportion is 8.14 % higher in July than in December. In addition, the cloud top height in summer is about 3–5 km higher than in winter, which may reduce the signal-to-noise ratio (SNR) of Aeolus. The results show that the detection performance of Aeolus is affected by seasonal factors, which may be caused by seasonal changes in wind direction and cloud distribution.

Siying Chen et al.

Status: open (until 16 Jun 2021)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse

Siying Chen et al.

Siying Chen et al.

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Short summary
In this study, the seasonal variation of Aeolus detection performance over China is analyzed by using L-band RS detection data and ERA5 reanalysis data. The results show that the detection performance of Aeolus is affected by seasonal factors, which may be caused by seasonal changes in wind direction and cloud distribution.
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