| The Computational Complexity of Atmospheric Data Assimilation (1998) | |||||||||||||||||
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| The computational complexity involved in Four Dimensional Data Assimilation (4DDA) for climate research is discussed. The general problem is that of assimilating observations that are inhomogeneously placed in space and time into a dynamical model. NASA's Data Assimilation Office (DAO) is developing and using a suite of algorithms whose main goal is to provide accurate, consistent, gridded datasets, or "analyses", in support of Earth System Science Research. Two large-scale problems are discussed: the first, Goddard Earth Observing System Data Assimilation System (GEOS DAS), uses a grid-point based atmospheric general circulation model (GCM) and an observation-space based analysis system, the Physical-space Statistical Analysis System (PSAS). Observations over a six hourly, "synoptic", period are aggregated and an analysis is performed using accurately assigned error statistics. Current runs, in excess of real time are rated at below 1 gigaflop/s for the Core system, while future incre... | |||||||||||||||||
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