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Collaborative Research: ITR/AP: Towards The Development Of Operational Adjoint Method Based Ensemble Prediction Techniques For El Nino Southern Oscillation

合作研究：ITR/AP：致力于开发基于运算伴随方法的厄尔尼诺南方涛动集合预测技术

基本信息

批准号：
0628690
负责人：
Andrew Moore
金额：
$ 8.37万
依托单位：
University of California-Santa Cruz
依托单位国家：
美国
项目类别：
Continuing Grant
财政年份：
2006
资助国家：
美国
起止时间：
2006-01-03 至 2007-08-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=0628690&HistoricalAwards=false
关键词：
Collaborative Research ITR AP Towards

项目摘要

This research project will explore the utility of adjoint-based methods of ensemble prediction for El Nino Southern Oscillation (ENSO), with the view to support the development of a new operational ensemble prediction scheme for ENSO. The PIs will use a hierarchy of coupled ENSO models that represent different levels of approximation of coupled ocean-atmosphere General Circulation Models (GCM). In addition to exploring singular vector and stochastic optimal based ensemble prediction techniques, they will compare these techniques with the method of bred modes that is currently used for ensemble weather prediction at the National Centers for Environmental Prediction. The ensemble prediction experiments will be analyzed using conventional statistical techniques and using a new theoretical framework based on information theory. The research builds on existing methods and ideas that have been applied successfully to Numerical Weather Prediction on timescales of 5-10 days using complex state-of-the-art atmospheric GCMs. The techniques have been applied successfully to ENSO prediction using simple coupled models, however, the application of existing ideas to complex ENSO prediction presents some significant new challenges that need to be addressed. The work is important because it has the potential to improve ENSO forecasts, which has important societal benefits.

这一研究项目将探讨厄尔尼诺/南方涛动（ENSO）集合预报的伴随方法的效用，以期支持制订一个新的厄尔尼诺/南方涛动集合预报业务计划。PI将使用一系列耦合厄尔尼诺/南方涛动模式，这些模式代表耦合海洋-大气环流模式的不同近似水平。除了探索基于奇异向量和随机最优的集合预测技术外，他们还将这些技术与目前在国家环境预测中心用于集合天气预测的繁殖模式方法进行比较。集合预报实验将使用传统的统计技术和使用基于信息论的新的理论框架进行分析。这项研究建立在现有的方法和思想，已成功地应用于数值天气预报的时间尺度为5-10天，使用复杂的国家的最先进的大气GCM。该技术已成功地应用于ENSO预测使用简单的耦合模式，然而，现有的想法复杂的ENSO预测的应用程序提出了一些重大的新的挑战，需要加以解决。这项工作很重要，因为它有可能改善厄尔尼诺/南方涛动预测，这具有重要的社会效益。