Enhancing Forecasts of Tropical Cyclone Extratropical Transition By Statistical Pattern Recognition

通过统计模式识别加强热带气旋温带转变的预报

• 批准号: 0730079
• 负责人: Elizabeth Ritchie
• 金额: $ 48.19万
• 依托单位: University of Arizona
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-10-01 至 2011-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0730079&HistoricalAwards=false
• 关键词: Enhancing; Forecasts; Tropical; Cyclone; Extratropical

The project builds on previous work which developed a statistical pattern recognition technique called Projection Pursuit (PP) that can be used to predict the extratropical transition (ET) of tropical cyclones based on large-scale characteristics of the surrounding atmosphere that can be gleaned from global analyses, model forecasts, and satellite observations. Normally tropical storms weaken as they leave the warm waters of the subtropics and turn poleward. ET leads to a reintensification of the storm causing it to remain dangerous. The investigators plan to generalize and refine the PP technique, taking it from proof-of-concept to an experimental forecasting tool applicable for real-time forecasting. While the project has a substantial applied aspect, the investigators also aim to understand the underlying physical mechanisms that separate the two categories of storms (ET versus dissipating) embodied by a combination of the storm characteristics and those of the larger synoptic environment, as well as differentiate between various rates of intensification. The ultimate goal is an automated system that can identify likely candidates for ET from model and remote sensing information. The methodology will have application for hurricane and typhoon forecasting and would be applicable in the T-PARC field campaign. Two graduate students and one undergraduate will be supported.

该项目建立在以前的工作基础上，开发了一种称为投影寻踪（PP）的统计模式识别技术，可用于预测热带气旋的热带气旋外转换（ET），基于可从全球分析，模式预报和卫星观测中收集的周围大气的大尺度特征。 通常热带风暴在离开亚热带温暖的沃茨并转向极地时会减弱。 ET导致风暴再次加剧，使其保持危险。 研究人员计划推广和完善PP技术，将其从概念验证变为适用于实时预测的实验预测工具。 虽然该项目具有实质性的应用方面，但研究人员还旨在了解将两类风暴（ET与消散）分开的潜在物理机制，这些风暴由风暴特征和较大天气环境的组合体现，以及区分不同的强化率。 最终的目标是一个自动化的系统，可以识别可能的候选人ET模型和遥感信息。 该方法将适用于飓风和台风预报，并将适用于T-PARC实地活动。将资助两名研究生和一名本科生。