Abstract. Aeolus wind products became available to the public on 12 May 2020. In this study, Aeolus wind observations, L-band radiosonde (RS) data, and the European Centre for Medium-Range Weather Forecasts fifth-generation atmospheric reanalysis (ERA5) data were used to analyze the seasonality of Aeolus wind product performance over China. Based on the Rayleigh-clear and Mie-cloudy data, the data quality of the Aeolus effective detection data was verified, and the results showed that the Aeolus data were in good agreement with the L-band RS and ERA5 data. The Aeolus data relative errors in the four regions (Chifeng, Baoshan, Shapingba, and Qingyuan) in China were calculated based on different months (July to December 2019 and May to October 2020). The relative error in the Rayleigh-clear data in summer was significantly higher than that in winter, with the mean relative error parameter in July 174 % higher than that in December. The mean random error increased by 0.97 m s−1 in July compared with December, which also supported this conclusion. In addition, the distribution of the wind direction and high-altitude clouds in different months (July and December) was analyzed. The results showed that the distribution of the angle between the horizontal wind direction of the atmosphere and the horizontal line of sight had a greater proportion in the high error interval (70–110∘) in summer, and this proportion was 8.14 % higher in July than in December. The cloud top height in summer was approximately 3–5 km higher than that in winter, which might decrease the signal-to-noise ratio of Aeolus. Therefore, the wind product performance of Aeolus was affected by seasonal factors, which might be caused by seasonal changes in wind direction and cloud distribution.
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.
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