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A steady-state Kalman filter for assimilating data from a single polar orbiting satelliteA steady-state scheme for data assimilation in the context of a single, short period (relative to a day), sun-synchronous, polar-orbiting satellite is examined. If the satellite takes observations continuously, the gains, which are the weights for blending observations and predictions together, are steady in time. For a linear system forced by random noise, the optimal steady-state gains (Wiener gains) are equivalent to those of a Kalman filter. Computing the Kalman gains increases the computational cost of the model by a large factor, but computing the Wiener gains does not. The latter are computed by iteration using prior estimates of the gains to assimilate simulated observations of one run of the model, termed 'truth' into another run termed 'prediction'. At each stage, the prediction errors form the basis for the next estimate of the gains. Steady state is achieved after three or four iterations. Further simplification is achieved by making the gains depend on longitudinal distance from the observation point, not on absolute longitude. For a single-layer primitive equation model, the scheme works well even if only the mass field is observed but not the velocity field. Although the scheme was developed for Mars Observer, it should be applicable to data retrieved from Earth atmosphere satellites, for example, UARS.
Document ID
19950048025
Acquisition Source
Legacy CDMS
Document Type
Reprint (Version printed in journal)
Authors
Banfield, Don
(California Institute of Technology, Pasadena, CA United States)
Ingersoll, Andrew P.
(California Institute of Technology, Pasadena, CA United States)
Keppenne, Christian L.
(Jet Propulsion Laboratory, California Inst. of Tech., Pasadena, CA United States)
Date Acquired
August 16, 2013
Publication Date
March 15, 1995
Publication Information
Publication: Journal of the Atmospheric Sciences
Volume: 52
Issue: 6
ISSN: 0022-4928
Subject Category
Meteorology And Climatology
Accession Number
95A79624
Distribution Limits
Public
Copyright
Other

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