CMG: Characterization of Inter-Tropical Convergence Zone (ITCZ) Dynamics and Breakdown Using Statistical Learning Methods and Satellite Data

该项目旨在开发可应用于卫星数据的统计学习技术，以确定称为热带辐合带的大气特征的随时间变化的结构和动态特征，热带辐合带是大规模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用于提高对ITCZ动态和故障的科学理解。 该项目的目标之一是开发统计方法，以确定热带地区卫星数据中的动态特征。 这些数据包括可见光和红外线图像、散射计风（QuikSCAT数据）、热带降雨监测使命卫星的降雨量估计值、微波测量的液态云含水量，以及相对涡度场等衍生量。 特别感兴趣的是ITCZ内的相对涡度池的形状，位置和强度，被认为是与ITCZ崩溃。 这些参数将首先根据瞬时二维数据场进行估算，主要是QuickSCAT数据与地球观测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可能影响ITCZ动态的非ITCZ扰动的估计，例如“向西传播的扰动”。 开发的算法将通过将其应用于看不见的数据并将结果与人工制作的图像注释进行比较来进行测试。 初步开发将使用ITCZ动力学数值模型模拟产生的场，包括模拟内部涡模不稳定性引起的破裂以及与向西传播的扰动相互作用引起的ITCZ破裂。 ITCZ结构图序列将作为数据产品通过网络提供，一旦开发完成，将使用刚才所述的统计技术来产生ITCZ状态序列，然后将使用这些序列来确定ITCZ所表现出的不同击穿模式及其相对频率。 还将检查浅和深ITCZ的相对频率，热带扰动对纬向混合的影响，以及寻找Madden-Julien振荡是否影响ITCZ动态的证据，包括崩溃。 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型输出。 从大气环流模式中得到的ITCZ状态的统计数据将与从卫星数据中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。 研究人员还将尝试单独从GOES数据中获得ITCZ的状态序列，将结果与GOES卫星数据和散射计风数据相结合获得的结果进行比较。 如果这项工作取得成功，将利用地球观测环境系统的原始数据作为分析的投入，研究1979-2005年期间热带过渡区动态的演变。 这将有助于研究热带对流带动态变化与十年气候变率之间的相互关系，该项目包括为一名博士后研究员和一名研究生提供教育和培训机会。 所开发的技术可适用于其他类型的卫星和非卫星图像。 结果的传播将通过科学会议和同行评审期刊文章中的标准演示方法进行;然而，该项目开发的数据产品将通过网站公开提供。

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.