Collaborative Research: Enabling Petascale Ensemble-based Data Assimilation for the Numerical Analysis and Prediction of High-Impact Weather

合作研究：实现基于千万亿级集合的数据同化，以进行高影响天气的数值分析和预测

• 批准号: 0904941
• 负责人: Sergiu Sanielevici
• 金额: $ 7.58万
• 依托单位: Carnegie-Mellon University
• 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: 2009-09-01 至 2013-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0904941&HistoricalAwards=false
• 关键词: Collaborative; Research; Enabling; Petascale; Ensemble

This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5). This proposal addresses the most challenging problems of very-high-resolution Numerical Weather Prediction, obtaining the optimal state estimations for initializing ensembles of predictions by assimilating the highest volume of weather observations available, and addressing problem sizes and scales that are only attainable on petascale computing platforms. The project is focused on the very hard problem of thunderstorm initiation, propagation and evolution. The effect of this investment in more accurate and timely forecast of thunderstorms can have a potentially transformative impact on hazard analysis and management.

该奖项根据 2009 年美国复苏和再投资法案（公法 111-5）提供资金。该提案解决了极高分辨率数值天气预报中最具挑战性的问题，通过同化最大量的可用天气观测来获得初始化预测集合的最佳状态估计，并解决只有在千万亿级计算平台上才能实现的问题规模和规模。该项目的重点是雷暴的产生、传播和演化这一非常棘手的问题。这项投资对更准确、更及时的雷暴预报的影响可能会对灾害分析和管理产生潜在的变革性影响。