ITR/AP+IM (GEO) Reanalysis of the Climate of the Global Ocean

ITR/AP IM (GEO) 全球海洋气候再分析

• 批准号: 0113148
• 负责人: James Carton
• 金额: $ 49.86万
• 依托单位: University of Maryland, College Park
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2001
• 资助国家: 美国
• 起止时间: 2001-09-01 至 2005-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0113148&HistoricalAwards=false
• 关键词: ITR; AP+IM; GEO; Reanalysis; Climate

0113148 Carton This project will provide improved estimates of the historical changes in the climate of the oceans by using direct and indirect observations to constrain numerical models of the global ocean circulation, temperature, and salinity through application of sequential estimation techniques. Application of sequential estimation to the problem of ocean reanalysis faces a number of problems. Full implementation is impractical on current computers. Further problems result from the presence of long spatial and temporal correlation scales in the observation minus forecast model differences. In addition, the subsurface data sets are limited and non-stationary. This project will exploit modern developments in computer science and meteorology to address these challenges. The specific focus is on variability of the global ocean during the 60-year period 1940-2000. A suite of preliminary reanalyses of the monthly temperature, salinity, and velocity fields of the ocean has been conducted using data assimilation, which have helped to identify a number of problems that must be surmounted. At the same time, there have been substantial improvements in the database of historical observations. This project will support an interdisciplinary collaboration between an oceanographer and meteorologist at University of Maryland (Jim Carton and Eugenia Kalnay) and an applied mathematician at NASA/GSFC (Dick Dee) to continue to explore new computational methods and algorithms developed for the problem of atmospheric data assimilation to explore seasonal to decadal variability of the oceans. The scientific objectives also address parts of the first of the scientific objectives of the CLImate Variability and predictability (CLIVAR) program: to describe and understand the physical processes responsible for climate variability and predictability on seasonal, interannual, decadal and centennial time scales, through the collection and analysis of observations and the development and application of models of the coupled climate system, in cooperation with other relevant climate research and observing programs (CLIVAR, 1998). Funding is provided through the Information Technology Research Initiative and the CLIVAR program.0113148

0113148 Carton 该项目将通过直接和间接观测，通过应用顺序估计技术来约束全球海洋环流、温度和盐度的数值模型，从而提供对海洋气候历史变化的改进估计。将序贯估计应用于海洋再分析问题面临着许多问题。在当前的计算机上完全实现是不切实际的。进一步的问题是由于观测减去预测模型差异时存在较长的空间和时间相关尺度。此外，地下数据集有限且不稳定。该项目将利用计算机科学和气象学的现代发展来应对这些挑战。具体重点是 1940 年至 2000 年 60 年间全球海洋的变化。使用数据同化对海洋的每月温度、盐度和速度场进行了一系列初步重新分析，这有助于确定一些必须克服的问题。与此同时，历史观测数据库也有了实质性的改进。该项目将支持马里兰大学的海洋学家和气象学家（Jim Carton 和 Eugenia Kalnay）与 NASA/GSFC 的应用数学家（Dick Dee）之间的跨学科合作，继续探索针对大气问题开发的新计算方法和算法数据同化以探索海洋的季节到十年的变化。科学目标还涉及气候变率和可预测性 (CLIVAR) 计划第一个科学目标的部分内容：通过与其他相关气候研究和观测计划合作，收集和分析观测数据以及开发和应用耦合气候系统模型（CLIVAR，1998）。资金通过信息技术研究计划和 CLIVAR 计划提供。0113148