CMG: Characterization of Inter-Tropical Convergence Zone (ITCZ) Dynamics and Breakdown Using Statistical Learning Methods and Satellite Data
CMG:使用统计学习方法和卫星数据描述热带辐合带 (ITCZ) 动态和分解特征
基本信息
- 批准号:0530926
- 负责人:
- 金额:$ 61.82万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2005
- 资助国家:美国
- 起止时间:2005-09-15 至 2010-08-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
The project is aimed at developing statistical learning techniques that can be applied to satellite data in order to characterize the time-dependent structure and dynamics of an atmospheric feature known as the Inter-Tropical Convergence Zone (ITCZ), an important part of the large-scale atmospheric circulation. The information gathered by applying the statistical learning techniques will be used to improve the scientific understanding of ITCZ dynamics and breakdown. One goal of the project is to develop statistical methods that identify dynamical features in satellite data for the tropics. These data include visible and infra-red imagery, scatterometer winds (QuikSCAT data), rainfall estimates from the Tropical Rainfall Monitoring Mission satellite, and liquid cloud water content from microwave measurements, together with derived quantities such as relative vorticity fields. Of particular interest are the shape, location and intensity of relative vorticity pools within the ITCZ, thought to be related to ITCZ breakdown. These parameters will first be estimated from instantaneous two-dimensional data fields, primarily the combination of the QuickSCAT data and visible and infra-red data from the GEOS satellite. The project will then go on to identify these parameters in time sequences of imagery using several statistical techniques. Parameter estimation within the ITCZ will be extended to include the estimation of non-ITCZ disturbances which may affect ITCZ dynamics, such as "westward-propagating disturbances". The algorithms developed will be tested by applying them to unseen data and comparing the results to human-produced annotation of the images. Initial development will use fields generated by numerical model simulations of ITCZ dynamics, including simulations of breakdown by internal vorticity-mode instabilities as well as ITCZ breakdowns induced by interaction with westward-propagating disturbances. The sequences of maps of ITCZ structure will be made available via the web as a data product.Once developed, the statistical techniques just described will be used to produce sequences of ITCZ state that will then be used to determine the different modes of breakdown exhibited by the ITCZ and their relative frequency. There will also be an examination of the relative frequency of shallow and deep ITCZs, and the influence of tropical disturbances on meridional mixing, as well as a search for evidence of whether Madden-Julien oscillations influence ITCZ dynamics, including breakdown. In the later stages of the project, the statistical learning techniques will be applied to high-resolution atmospheric model output. The statistics on ITCZ states derived from the general circulation model will be compared with those derived from the satellite data to examine quantitatively whether there is any systematic bias in the behavior of the ITCZ in the atmospheric circulation model. The researchers will also attempt to derive state sequences of the ITCZ from GOES data alone, comparing the results with those obtained from the combination of GOES satellite data and scatterometer wind data. If this is successful, the evolution of ITCZ dynamics will be studied over the period 1979-2005, using the raw GOES data as input to the analysis. This will permit a search for correlations between variations in ITCZ dynamics and decadal climate variability.This project includes education and training opportunities for a post-doctoral investigator and a graduate student. The techniques developed may be applicable to other types of satellite and non-satellite imagery. Dissemination of results will be by the standard methods of presentations at scientific meetings and in peer-reviewed journal articles; however data products developed by the project will be made publicly available via a web-site.
该项目旨在开发可应用于卫星数据的统计学习技术,以描述称为热带间辐合带的大气特征的随时间变化的结构和动力学特征,这是大尺度大气环流的重要组成部分。通过应用统计学习技术收集的信息将被用来增进对ITCZ动态和细分的科学理解。该项目的目标之一是开发统计方法,以确定热带卫星数据中的动力特征。这些数据包括可见光和红外线图像、散射计风速(QuikSCAT数据)、热带降雨监测团卫星的降雨量估计数、来自微波测量的液态云水含量,以及诸如相对涡量场等导出的量。尤其令人感兴趣的是ITCZ内相对涡度池的形状、位置和强度,被认为与ITCZ破裂有关。这些参数将首先从瞬时二维数据场估计,主要是QuickScat数据和来自地球观测系统卫星的可见光和红外线数据的组合。然后,该项目将继续使用几种统计技术在图像的时间序列中确定这些参数。ITCZ内的参数估计将扩展到包括对可能影响ITCZ动态的非ITCZ扰动的估计,例如“西传扰动”。开发的算法将通过将它们应用于看不见的数据并将结果与人类对图像的注释进行比较来进行测试。最初的发展将使用ITCZ动力学的数值模式模拟产生的场,包括模拟由内部涡度模式不稳定引起的击穿以及由与向西传播的扰动相互作用引起的ITCZ击穿。ITCZ结构图的序列将作为数据产品通过网络提供。一旦开发完成,上述统计技术将被用于产生ITCZ状态的序列,然后用于确定ITCZ表现出的不同击穿模式及其相对频率。还将审查浅层和深层ITCZ的相对频率,热带扰动对经向混合的影响,以及寻找Madden-Julien振荡是否影响ITCZ动态,包括破裂的证据。在该项目的后期阶段,统计学习技术将应用于高分辨率大气模式输出。从大气环流模式得到的ITCZ状态的统计数据将与从卫星数据得到的统计数据进行比较,以定量地检查大气环流模式中ITCZ的行为是否存在任何系统偏差。研究人员还将尝试仅从GOES数据得出ITCZ的状态序列,并将结果与GOES卫星数据和散射计风场数据相结合获得的结果进行比较。如果这是成功的,将使用GOES原始数据作为分析的输入,研究1979-2005年期间ITCZ动态的演变。这将允许寻找ITCZ动态变化与十年气候变化之间的相关性。该项目包括一名博士后研究员和一名研究生的教育和培训机会。所开发的技术可能适用于其他类型的卫星和非卫星图像。将通过在科学会议和同行评议的期刊文章中介绍的标准方法传播成果;不过,该项目开发的数据产品将通过网站向公众提供。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Gudrun Magnusdottir其他文献
Gudrun Magnusdottir的其他文献
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