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

University Of Maryland, College Park, College Park MD

Investigators

Abstract

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