Preprints
https://doi.org/10.5194/amt-2023-152
https://doi.org/10.5194/amt-2023-152
25 Jul 2023
 | 25 Jul 2023
Status: a revised version of this preprint was accepted for the journal AMT and is expected to appear here in due course.

Comparisons and quality control of wind observations in a mountainous city using wind profile radar and the Aeolus satellite

Hua Lu, Min Xie, Wei Zhao, Bojun Liu, Tijian Wang, and Bingliang Zhuang

Abstract. Observations of vertical wind in Chongqing, a typical mountainous city in China, are important, but sparse and have low resolution. To obtain more wind profile data, this study matched the Aeolus track with ground-based wind observation sites in Chongqing in 2021. Based on the obtained results, verification and quality control studies were conducted on the wind observations of a wind profile radar (WPR) with radiosonde (RS) data, and a comparison of the Aeolus Mie-cloudy and Rayleigh-clear wind products with WPR data was then performed. The conclusions can be summarized as follows: (1) A clear correlation between the wind observations of WPR and RS was found, with a correlation coefficient (R) of 69.92 %. Their root-mean-square deviation increased with height but decreased by 3–4 km. (2) After quality control of Gaussian filtering (GF) and empirical orthogonal function construction (EOFc, G = 87.23 %) of the WPR data, the R between the WPR and RS reached 76.00 % and 95.44 %, respectively. The vertical distribution showed that GF could better retain the characteristics of WPR wind observations, but with limited improvement in decreasing deviations, whereas EOFc performed better in decreasing deviations, but considerably modified the original characteristics of the wind field, especially regarding intensive vertical wind shear in strong convective weather processes. (3) In terms of the differences between the Aeolus and WPR data, 56.0 % and 67.8 % deviations were observed between ±5 m/s for Rayleigh-clear and Mie-cloudy winds vs. WPR winds, respectively. Vertically, the mean differences of both Rayleigh-clean and Mie-cloudy winds versus WPR winds appeared below 1.5 km, which is attributed to the prevailing quiet and small winds within the boundary layer in Chongqing, such that the movement of molecules and aerosols is mostly affected by irregular turbulence. Additionally, large mean differences of 4–8 km for Mie-cloudy versus WPR winds may be related to the high content of cloud liquid water in the middle troposphere, influenced by the topography of the Tibetan Plateau. (4) The differences in both Rayleigh-clear and Mie-cloudy versus WPR winds had changed. Deviations of 58.9 % and 59.6 % were concentrated between ±5m/s for Rayleigh-clear versus WPR winds with GF and EOFc quality control, respectively. In contrast, 69.1 % and 70.2 % of deviations appeared between ±5 m/s for Rayleigh-clear versus WPR and EOFc WPR winds, respectively. These results shed light on the comprehensive applications of multi-source wind profile data in mountainous cities or areas with sparse ground-based wind observations.

Hua Lu et al.

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on amt-2023-152', Anonymous Referee #1, 15 Aug 2023
    • AC1: 'Reply on RC1', Min Xie, 04 Sep 2023
  • RC2: 'Comment on amt-2023-152', Anonymous Referee #2, 19 Aug 2023
    • AC2: 'Reply on RC2', Min Xie, 04 Sep 2023

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on amt-2023-152', Anonymous Referee #1, 15 Aug 2023
    • AC1: 'Reply on RC1', Min Xie, 04 Sep 2023
  • RC2: 'Comment on amt-2023-152', Anonymous Referee #2, 19 Aug 2023
    • AC2: 'Reply on RC2', Min Xie, 04 Sep 2023

Hua Lu et al.

Hua Lu et al.

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Short summary
Observations of vertical wind in regions with complex terrain are essential, but always sparse and have poor representation. Data verification and quality control study are conducted on the wind profile radar and Aeolus wind products in this study, trying to compensate for the limitations of wind field observations. The results shed light on the comprehensive applications of multi-source wind profile data in complicated terrain regions with sparse ground-based wind observations.