利用风廓线雷达和 Aeolus 卫星对一个山区城市的风观测结果进行比较和质量控制

IF 3.2 3区 地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES Atmospheric Measurement Techniques Pub Date : 2024-01-12 DOI:10.5194/amt-17-167-2024
Hua Lu, Min Xie, Wei Zhao, Bojun Liu, Tijian Wang, Bingliang Zhuang
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引用次数: 0

摘要

摘要重庆是中国典型的山区城市,对其垂直风廓线的观测非常重要,但观测数据稀少且分辨率较低。为了获得更多的风廓线数据,本研究将 Aeolus 轨迹与 2021 年重庆的地面风观测点进行了匹配。根据所获得的结果,对风廓线雷达(WPR)与无线电探空仪(RS)的风观测数据进行了验证和质量控制研究,并将 Aeolus Mie-阴天和 Rayleigh-晴天风产品(Aeolus 风在多云和富含气溶胶大气条件下通过 Mie 通道收集的数据测量的风,以及在晴朗空气条件下通过 Rayleigh 收集的数据测量的风)与 WPR 数据进行了比较。结论可归纳如下:(1) 发现 WPR 和 RS 的风观测数据之间存在明显的相关性,相关系数 (R) 为 0.71。它们的均方根偏差随高度增加而增大,但在 3 至 4 千米的高度上有所减小。(2) 使用高斯滤波(GF)和经验正交函数构造(EOFc;G=87.23%)对 WPR 数据进行质量控制后,WPR 和 RS 之间的 R 分别达到 0.83 和 0.95。从垂直分布来看,GF 更好地保留了 WPR 风观测资料的特征,但对偏差减小的改善有限;而 EOFc 在偏差减小方面表现较好,但大大改变了风场的原有特征,特别是强对流天气过程中的强垂直风切变。(3) 就 Aeolus 和 WPR 数据之间的差异而言,观察到雷利晴朗风和米易多云风(利用米易通道收集的数据在多云和富含气溶胶的大气条件下测量的 Aeolus 风,以及利用雷利收集的数据在晴朗空气条件下测量的风)与 WPR 风之间的偏差分别为 56.0 % 和 67.8 %,均在±5 m s-1 以内。在垂直方向上,1.5 千米以下的瑞利晴风和米氏阴风与 WPR 风的平均值相差较大,这是因为重庆边界层内普遍存在静风和小风,在这种情况下,分子和气溶胶的运动主要受到不规则湍流的影响。此外,在 4 至 8 千米高度范围内,Mie-cloudy 风与 WPR 风的平均值差异较大,这可能与重庆对流层中层云液态水含量较高有关。(4) 瑞利晴风和米易多云风与 WPR 风的差异均发生了变化。在 GF 和 EOFc 质量控制下,瑞利晴风与 WPR 风的偏差分别集中在±5 m s-1 以内,分别为 58.9% 和 59.6%。相比之下,瑞利清风与 WPR 风和 EOFc WPR 风的偏差分别为 69.1 % 和 70.2 %,均在±5 m s-1 以内。这些结果为多源风廓线数据在山区城市或地面风观测稀少地区的综合应用提供了启示。
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Comparisons and quality control of wind observations in a mountainous city using wind profile radar and the Aeolus satellite
Abstract. Observations of the vertical wind profile in Chongqing, a typical mountainous city in China, are important, but they are 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 (Aeolus winds measured in cloudy and aerosol-rich atmospheric conditions from Mie-channel-collected data and winds measured in clear-air conditions from Rayleigh-collected data) 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 0.71. Their root mean square deviation increased with height but decreased at heights between 3 and 4 km. (2) After quality control using Gaussian filtering (GF) and empirical orthogonal function construction (EOFc; G=87.23 %) of the WPR data, the R between the WPR and RS reached 0.83 and 0.95, 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 within ±5 m s−1 for Rayleigh-clear and Mie-cloudy winds (Aeolus winds measured in cloudy and aerosol-rich atmospheric conditions from Mie-channel-collected data and winds measured in clear-air conditions from Rayleigh-collected data) vs WPR winds, respectively. Vertically, large 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; in this case the movement of molecules and aerosols is mostly affected by irregular turbulence. Additionally, large mean differences at a height range between 4 and 8 km for Mie-cloudy versus WPR winds may be related to the high content of cloud liquid water in the middle troposphere of Chongqing. (4) The differences in both Rayleigh-clear and Mie-cloudy versus WPR winds had changed. Deviations of 58.9 % and 59.6 % were concentrated within ±5 m s−1 for Rayleigh-clear versus WPR winds with GF and EOFc quality control, respectively. In contrast, 69.1 % and 70.2 % of deviations appeared within ±5 m s−1 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.
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来源期刊
Atmospheric Measurement Techniques
Atmospheric Measurement Techniques METEOROLOGY & ATMOSPHERIC SCIENCES-
CiteScore
7.10
自引率
18.40%
发文量
331
审稿时长
3 months
期刊介绍: Atmospheric Measurement Techniques (AMT) is an international scientific journal dedicated to the publication and discussion of advances in remote sensing, in-situ and laboratory measurement techniques for the constituents and properties of the Earth’s atmosphere. The main subject areas comprise the development, intercomparison and validation of measurement instruments and techniques of data processing and information retrieval for gases, aerosols, and clouds. The manuscript types considered for peer-reviewed publication are research articles, review articles, and commentaries.
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