Abstract
Abstract. Aeolus is the first satellite mission to directly observe wind profile information on a global scale. After implementing a set of bias corrections, the Aeolus data products went public on 12 May 2020. However, Aeolus wind products over China have thus far not been evaluated extensively by ground-based remote sensing measurements. In this study, the Mie-cloudy and Rayleigh-clear wind products from Aeolus measurements are validated against wind observations from the radar wind profiler (RWP) network in China. Based on the position of each RWP site relative to the closest Aeolus ground tracks, three matchup categories are proposed, and comparisons between Aeolus wind products and RWP wind observations are performed for each category separately. The performance of Mie-cloudy wind products does not change much between the three matchup categories. On the other hand, for Rayleigh-clear and RWP wind products, categories 1 and 2 are found to have much smaller differences compared with category 3. This could be due to the RWP site being sufficiently approximate to the Aeolus ground track for categories 1 and 2. In the vertical, the Aeolus wind products are similar to the RWP wind observations, except for the Rayleigh-clear winds in the height range of 0–1 km. The mean absolute normalized differences between the Mie-cloudy (Rayleigh-clear) and the RWP wind components are 3.06 (5.45), 2.79 (4.81), and 3.32 (5.72) m/s at all orbit times and ascending and descending Aeolus orbit times, respectively. This indicates that the wind products for ascending orbits are slightly superior to those for descending orbits, and the observation time has a minor effect on the comparison. From the perspective of spatial differences, the Aeolus Mie-cloudy winds are consistent with RWP winds in most of east China, except in coastal areas where the Aeolus Rayleigh-clear winds are more reliable. Overall, the correlation coefficient R between the Mie-cloudy (Rayleigh-clear) wind and RWP wind component observation is 0.94 (0.81), suggesting that Aeolus wind products are in good agreement with wind observations from the RWP network in China. The findings give us sufficient confidence in assimilating the newly released Aeolus wind products in operational weather forecasting in China.
Highlights
R values between Mie-cloudy and radar wind profiler (RWP) winds are 0.94, 0.9, and 0.9 for all data, ascending orbits, and descending orbits, respectively. These results indicate that the Aeolus Mie-cloudy wind products are broadly consistent with RWP wind observations over China
Differences between Aeolus horizontal lineof-sight (HLOS) and RWP winds may be due to Aeolus and RWP errors and due to how RWP represents the Aeolus winds in terms of spatial and temporal aggregation
We note that atmospheric heterogeneity may differ for ascending (18:00 local solar time (LST)) and descending (06:00 LST) Aeolus orbits due to the daily atmospheric cycle over land
Summary
Observations of atmospheric wind profiles are essential to the prediction of extreme rainfall events (Nash and Oakley, 2001; Huuskonen et al, 2014; King et al, 2017), the forecasting of tropical cyclones and hurricanes (Pu et al, 2010; Stettner et al, 2019), a better understanding of persistent haze pollution episodes (Liu et al, 2018; Yang et al, 2019; Zhang et al, 2014, 2020; Huang et al, 2020), and complicated aerosol– cloud–precipitation interactions (Li et al, 2011; Lebo and Morrison, 2014; Guo et al, 2018, 2019; Huang et al, 2019; Shi et al, 2020). Continuous global wind profile observations are of great significance for advancing our knowledge of atmospheric dynamics as well as for improving the accuracy of numerical weather prediction (Stoffelen et al, 2005) To this end, various instruments have been developed to measure wind speed and direction, including radiosondes, radar wind profilers (RWPs), and geostationary satellites (Stoffelen et al, 2019; Bentamy et al, 1999; Draper and Long, 2002; Guo et al, 2016; Liu et al, 2019).
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