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气象:2023,49(8):901-914
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基于高垂直分辨率探空数据对五种典型下垫面湍流分布特征分析
龚玺,陈起英,倪长健,龙海川
(成都信息工程大学,成都 610225; 湖南省株洲市气象局,株洲 412003; 气象防灾减灾湖南省重点实验室,长沙 410118; 中国气象局地球系统数值预报中心,北京 100081; 灾害天气国家重点实验室,北京 100081)
Turbulence Distribution Characteristics of Five Typical Underlying Surfaces Based on High Vertical Resolution Radiosonde Data
GONG Xi,CHEN Qiying,NI Changjian,LONG Haichuan
(Chengdu University of Information Technology, Chengdu 610225; Zhuzhou Meteorological Office of Hunan Province, Zhuzhou 412003; Key Laboratory of Preventing and Reducing Meteorological Disaster of Hunan Province, Changsha 410118; Center for Earth System Modeling and Prediction of CMA, Beijing 100081; State Key Laboratory on Severe Weather, Beijing 100081)
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投稿时间:2022-03-01    修订日期:2022-10-16
中文摘要: 由于湍流的时空尺度小、变化率大,缺乏大规模的现场观测,导致对全国范围内的大气湍流特征研究甚少。自2011年起,我国开始存储秒级高垂直分辨率探空数据,为深入研究中国各地的湍流特征提供了可能。在用探空资料诊断分析湍流特征时,首先分析了中国地区仪器噪音对分析结果的影响,证实噪音会使对流层平均的湍流耗散率偏小,证明了去除噪音的必要性。在此基础上,采用Thorpe分析法详细分析了湍流的强度(湍流耗散率)与下垫面类型的关系。结果显示,在对流层,全年平均草地的湍流最强,然后依次是旱地作物、水田作物、灌木、荒地。在平流层下层依然受到下垫面的影响,全年平均草地的湍流依旧最强,旱地作物次之。湍流在不同下垫面均表现出明显的季节性,且夏季对流层上层的强度和频率最高。研究结果将有助于理解不同下垫面对流层的湍流特征,为航空器飞行安全保障、大气污染扩散模式、天气预报模式的湍流参数化方案改进提供参考。
Abstract:Due to the small spatiotemporal scale and large change rate of turbulence, and the lack of large-scale field observation, there are fewer researches on the characteristics of atmospheric turbulence in China. Since 2011, China has begun to store second-level high-resolution sounding data, which makes it possible to deeply study the characteristics of turbulence in various parts of China. When using radiosonde data to diagnose the characteristics of turbulence, it is necessary to consider the impact of instrument noise on the analysis results. This paper analyzes the impact of instrument noise on the analysis results in China, which proves that noise can reduce the average turbulent dissipation rate in the troposphere, indicating the necessity of removing noise. On this basis, the Thorpe analysis method is used in analyzing the relationship between the intensity of turbulence (turbulence dissipation rate) and the type of underlying surface in detail. The results reveal that the turbulence in the troposphere and the annual average grassland turbulence are the strongest, followed by those of dryland crops, paddy crops, shrubs and wasteland. In the lower stratosphere, it is still affected by the underlying surface, and the annual average turbulence of grassland is still the strongest, and the next is the turbulence of dry land crops. The turbulence shows obvious seasonality on different underlying surfaces, and the turbulence intensity and frequency in the upper troposphere are the highest in summer. The results of this paper would help to understand the turbulence characteristics of different underlying surfaces, and provide guidance for the improvement of turbulence parameterization schemes of aircraft flight safety guarantee, air pollution model and so on.
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基金项目:国家重点研发计划(2019YFC0214602、2017YFC1501902)和国家自然科学基金项目(41375107)共同资助
引用文本:
龚玺,陈起英,倪长健,龙海川,2023.基于高垂直分辨率探空数据对五种典型下垫面湍流分布特征分析[J].气象,49(8):901-914.
GONG Xi,CHEN Qiying,NI Changjian,LONG Haichuan,2023.Turbulence Distribution Characteristics of Five Typical Underlying Surfaces Based on High Vertical Resolution Radiosonde Data[J].Meteor Mon,49(8):901-914.