Doppler Radar Observations and Ensemble-Based Data Assimilation for Cloud-Resolving Hurricane Prediction

用于云解析飓风预测的多普勒雷达观测和基于集合的数据同化

• 批准号: 0840651
• 负责人: Fuqing Zhang
• 金额: $ 55.01万
• 依托单位: Pennsylvania State Univ University Park
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-06-01 至 2013-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0840651&HistoricalAwards=false
• 关键词: Doppler; Radar; Observations; Ensemble; Based

This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5).Despite significant progress in short-range hurricane track forecasts, over the past decade there has been virtually no improvement in predicting hurricane intensity and amount of precipitation, and very limited skill exists in the numerical prediction of tropical cyclone formation, rapid intensification or decay. It remains unclear whether the lack of numerical forecast skill derives from imperfect initial conditions, inadequate data assimilation techniques, imperfect forecast models, or from intrinsic predictability limits due to chaotic dynamics. This research will use ensemble-based data assimilation (EnDA) to explore the initialization and prediction of tropical cyclones as well as the fundamental limits to the predictability of hurricane structure and intensity. The research will utilize special data sets collected on three 2005 hurricanes (Katrina, Ophelia and Rita) during the Rainband and Intensity Experiment (RAINEX). The RAINEX was a joint NSF/NOAA field project that employed multiple aircraft with Doppler radars and dropsonde capabilities to investigate the hurricane intensity changes that are associated with eyewall-rainband interactions. Other cases to be examined include Emily (2005), Wilma (2005), and Humberto (2007). All of these selected cases have extensive and unique Doppler radar observations that were collected over the lifecycles of the hurricanes. Major objectives of the research include: (1) assess the impacts on predictability of assimilating ground-based and airborne radar observations in addition to regular and experimental in-situ and remotely sensed observations; (2) explore the role of the large-scale environment and internal dynamics, including moist convection, on the predictability of hurricane structure and intensity change; and (3) evaluate the impact and effectiveness of different observing platforms and targeting strategies on hurricane prediction through observing system numerical experiments with both simulated and actual observations. Intellectual merit: The combination of the EnDA technique with field observations constitutes a potentially significant advance in data assimilation and understanding of dynamics, intensity, structure, prediction, and fundamental limits of predictability of tropical cyclones. The work will also may provide guidance for future observing network design and observing strategy. Broader impacts: The research will provide educational benefits through the extensive participation of a doctoral graduate student and a postdoctoral scientist. Research findings will be used in advanced educational courses and undergraduate research projects. Knowledge gained about the predictability of hurricanes potentially will benefit the operational communities and the general public. The EnDA techniques and computer codes will be made freely available online with ample documentation to benefit the larger academic community.

该奖项是根据2009年美国复苏和再投资法案（公法111-5）资助的。尽管在短期飓风路径预报方面取得了重大进展，但在过去十年中，对飓风强度和降水量的预测几乎没有任何改善，对热带气旋形成、快速增强或衰减的数值预测也非常有限。目前尚不清楚缺乏数值预报技能是由于初始条件不完善、数据同化技术不完善、预报模型不完善还是混沌动力学固有的可预测性限制。本研究将利用基于集合的数据同化（EnDA）来探讨热带气旋的初始化和预测，以及飓风结构和强度可预测性的基本限制。这项研究将利用在“雨带和强度实验”（RAINEX）期间收集的2005年三次飓风（卡特里娜、奥菲莉亚和丽塔）的特殊数据集。RAINEX是美国国家科学基金会和美国国家海洋和大气管理局联合开展的一项野外项目，该项目使用多架飞机，配备多普勒雷达和投下探空仪，研究飓风强度变化与眼壁-雨带相互作用的关系。其他需要研究的案例包括Emily（2005）、Wilma（2005）和Humberto（2007）。所有这些选定的案例都有广泛而独特的多普勒雷达观测，这些观测是在飓风的生命周期中收集的。研究的主要目标包括：(1)评估除常规和实验原位和遥感观测外，同化地面和机载雷达观测对可预测性的影响；(2)探讨大尺度环境和内部动力（包括湿对流）对飓风结构和强度变化可预测性的影响；(3)通过模拟观测和实际观测的观测系统数值试验，评价不同观测平台和目标策略对飓风预报的影响和有效性。知识价值：EnDA技术与实地观测相结合，在数据同化和理解热带气旋的动力学、强度、结构、预测和可预测性的基本限制方面构成了潜在的重大进步。该工作还可为今后观测网络的设计和观测策略提供指导。更广泛的影响：该研究将通过博士研究生和博士后科学家的广泛参与提供教育效益。研究成果将用于高等教育课程和本科生研究项目。获得的关于飓风可预测性的知识可能会使业务社区和公众受益。EnDA技术和计算机代码将在网上免费提供，并提供充足的文档，以使更大的学术界受益。