Abstract
The European Space Agency (ESA) Earth Explorer Atmospheric Dynamics Mission Aeolus is the first satellite mission providing wind profile information on a global scale, and its wind products have been released on 12 May 2020. Here we verify and intercompare the wind observations from ESA’s satellite mission Aeolus and the European Centre for Medium-Range Weather Forecasts (ECMWF) fifth generation atmospheric reanalyses (ERA5) with radiosonde (RS) observations over China, to allow a fitting application of Aeolus winds. Aeolus provides wind observations in aerosol-free (referred to as Rayleigh-clear winds) and cloudy atmospheres (Mie-cloudy winds). In terms of Aeolus and RS winds, the correlation coefficient (R) and mean difference of Rayleigh-clear (Mie-cloudy) vs RS winds are 0.94 (0.97) and −0.24 ± 7.01 (0.18 ± 4.42) m/s, respectively. The vertical profiles of wind speed differences between Aeolus and RS winds are similar to each other during ascending and descending orbits. The comparison of ECMWF winds relative to Aeolus winds provides the R and mean difference of Rayleigh-clear (Mie-cloudy) winds, which are 0.95 (0.97) and −0.16 ± 6.78 (−0.21 ± 3.91) m/s, respectively. The Rayleigh-clear and Mie-cloudy winds are very consistent with the ECMWF winds, likely due to the assimilation of Aeolus wind observations into the ECMWF analysis. Moreover, we find that among the results of comparing Aeolus with RS and ECMWF winds, a small difference between Rayleigh-clear winds relative to RS winds is appeared in the height range of 2–3 km during descending orbits. This result may be due to the high vertical velocity during the descending orbits. The mean differences between Rayleigh-clear (Mie-cloudy) winds and RS winds during the ascending and descending orbit phase are −0.07 ± 0.69 (−0.72 ± 1.48) and 0.3 ± 1.25 (0.1 ± 1.32) m/s. These small deviations indicate that the performance of Aeolus wind products may be unaffected by the orbit phase or HLOS wind conditions. In addition, the R and mean difference between ERA5 and RS zonal wind components are 0.97 and −0.46 ± 3.12 m/s, respectively. Overall, the Aeolus winds over China are similar to the RS and ECMWF winds. The findings give us sufficient confidence and information to apply Aeolus wind products in numerical weather prediction in China and in climate change research.
Highlights
Atmospheric three-dimensional wind fields play a key role for the prediction of extreme events (Pu et al, 2010; Guo et al, 2018; Stettner et al, 2019), a better understanding of air pollution dispersion (Liu et al, 2018; Yang et al, 2019; Shi et al, 2020; Su et al, 2020; Zhang et al, 2020) and complex aerosol15 cloud-precipitation interactions (Koren et al, 2005; Fan et al, 2009; Li et al, 2011; Guo et al, 2017; Liu et al, 2020a)
The mean differences between Rayleigh-clear (Mie-cloudy) winds and RS winds during the ascending and descending orbit phase are 0.07±0.69 ( 0.72±1.48) 5 and 0.3±1.25 (0.1±1.32) m/s. These small deviations indicate that the performance of Aeolus wind products may be unaffected by the orbit phase or horizontal line-of-sight (HLOS) wind conditions
Following the study of Lux et al (2020), the operational European Centre for Medium-Range Weather Forecasts (ECMWF) wind data from the Aeolus Level 2C (L2C) wind product are obtained to compared with Aeolus winds
Summary
Atmospheric three-dimensional wind fields play a key role for the prediction of extreme events (Pu et al, 2010; Guo et al, 2018; Stettner et al, 2019), a better understanding of air pollution dispersion (Liu et al, 2018; Yang et al, 2019; Shi et al, 2020; Su et al, 2020; Zhang et al, 2020) and complex aerosol cloud-precipitation interactions (Koren et al, 2005; Fan et al, 2009; Li et al, 2011; Guo et al, 2017; Liu et al, 2020a). The flight altitude and repeat cycle of the Aeolus satellite are about 320 km and 7days, respectively (Witschas et al, 2020) It provides measurements of the wind vector component along the instrument's line-of-sight from the ground up to 30 km altitude (Rennie et al, 2020). It is worthwhile to further verify the performance of Aeolus wind products in China using the China’s RS observation network This network comprises 120 RS sites homogeneously distributed across mainland China and provides atmospheric soundings of winds (Guo et al, 2016; 2019). The use of these data, together with ERA-5 reanalysis data, provides a unique opportunity to deepen our 15 understanding of the performance of Aeolus wind products over all mainland China.
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