Abstract

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.

Highlights

  • Global wind field data are indispensable meteorological parameters for weather forecasting (Ishii et al, 2017)

  • The current observation dataset used for ECMWF Reanalysis v5 (ERA5) assimilation does not contain the observation results of Aeolus; there was no mutual influence between the Level 2B (L2B) data of Aeolus and the reanalysis data of ERA5

  • The Aeolus detection data were in good agreement with the ERA5 and L-band RS data, and the quality of the data used in the present study was reliable

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Summary

Introduction

Global wind field data are indispensable meteorological parameters for weather forecasting (Ishii et al, 2017). The Aeolus is equipped with a 355 nm direct-detection wind lidar, which uses a single-view detection method to obtain the horizontal line-of-sight (HLOS) component of the three-dimensional wind field from space. It adopts a dual-channel design and uses different frequency discriminators to receive the Mie and Rayleigh channel signals (Stoffelen et al, 2005; Reitebuch, 2012). Global Aeolus data verification studies using the numerical weather prediction (NWP) model have been undertaken (Rennie and Isaksen, 2019; Martin et al, 2021). Two conjectures regarding Aeolus’s different wind product capabilities were introduced and verified

Aeolus L2B wind products
L-band radiosonde wind data
ERA5 data
Data matching
Calculation of the relative error
Data quality
Seasonal variations in relative errors
Seasonal variations in atmospheric wind direction
Seasonal variations in upper cloud cover
Conclusion

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