Analyzing the Structure and Evolution of Southern Hemisphere Synoptic Variability Using a New Reanalysis Observations Database

中纬度地区的天气和气候以天气尺度风暴为主，即气旋和反气旋。它们与斜压波有关，斜压波构成了这些风暴的对流层延伸，它们负责热、动量和水分交换，这些交换构成了大气环流的重要组成部分。从历史上看，斜压波的三维结构只有在高空测深可用时才能得到认识。最近，利用数据同化技术（40年的重新分析）从气象服务业务数据库获得的全球数据集试图描述总环流的四维方面。由于现场数据的覆盖范围远小于北半球，因此在这些重新分析中，南半球斜压波统计数据的表示在不同气象部门的产品之间存在很大差异。PI将使用刚刚可用的原始观测数据库研究这些统计数据。PI将调查南半球风暴路径的真实振幅，以及天气尺度扰动的结构和演变。这项工作的意义将超出了解南半球各个观测地点的时间和垂直相关特征的直接目标。最重要的特征将是经常用于研究大尺度大气变率的再分析的校准，以及结果对未来数据同化产品的可能影响。

Weather and climate in the mid-latitudes are dominated by synoptic scale storms, i.e. cyclones and anticyclones. Associated with baroclinic waves that constitute the tropospheric extension of these storms, they are responsible for heat, momentum and moisture exchanges that make up important parts of the general circulation. Historically, the three-dimensional structure of baroclinic waves was only appreciated when upper air soundings became available. More recently, global datasets derived from the operational databases of weather services using data assimilation techniques (40 years of re-analyses) have attempted to describe the four-dimensional aspects of the general circulation. As the coverage of in-situ data is far less than in the Northern Hemisphere, the representation of the statistics of baroclinic waves in the Southern Hemisphere in those re-analyses differ considerably between products from different weather services. The PI will study these statistics using the original observations database that has just become available. The PI will investigate the true amplitude of the Southern Hemisphere storm track, and the structure and evolution of synoptic scale perturbations. The work will have implications beyond the immediate goal of understanding temporally and vertically correlated features at individual Southern Hemisphere observing sites. The most important features will be the calibration of re-analyses that are often used to study large-scale atmospheric variability, and possible implications of the results for future data assimilation products.