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Incorporating Parallel Computing into the Goddard Earth Observing System Data Assimilation System (GEOS DAS)Atmospheric data assimilation is a method of combining actual observations with model forecasts to produce a more accurate description of the earth system than the observations or forecast alone can provide. The output of data assimilation, sometimes called the analysis, are regular, gridded datasets of observed and unobserved variables. Analysis plays a key role in numerical weather prediction and is becoming increasingly important for climate research. These applications, and the need for timely validation of scientific enhancements to the data assimilation system pose computational demands that are best met by distributed parallel software. The mission of the NASA Data Assimilation Office (DAO) is to provide datasets for climate research and to support NASA satellite and aircraft missions. The system used to create these datasets is the Goddard Earth Observing System Data Assimilation System (GEOS DAS). The core components of the the GEOS DAS are: the GEOS General Circulation Model (GCM), the Physical-space Statistical Analysis System (PSAS), the Observer, the on-line Quality Control (QC) system, the Coupler (which feeds analysis increments back to the GCM), and an I/O package for processing the large amounts of data the system produces (which will be described in another presentation in this session). The discussion will center on the following issues: the computational complexity for the whole GEOS DAS, assessment of the performance of the individual elements of GEOS DAS, and parallelization strategy for some of the components of the system.
Document ID
19980205536
Acquisition Source
Goddard Space Flight Center
Document Type
Abstract
Authors
Larson, Jay W.
(NASA Goddard Space Flight Center Greenbelt, MD United States)
Date Acquired
August 18, 2013
Publication Date
June 1, 1998
Publication Information
Publication: Second International Workshop on Software Engineering and Code Design in Parallel Meteorological and Oceanographic Applications
Subject Category
Earth Resources And Remote Sensing
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.

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