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New Method of Spatial Extrapolation of Meteorological Fields on the Mesoscale Level Using a Kalman Filter Algorithm for a Four-Dimensional Dynamic–Stochastic Model

New Method of Spatial Extrapolation of Meteorological Fields on the Mesoscale Level Using a... A new method and an algorithm of spatial extrapolation of mesometeorological fields to a territory uncovered with observations are suggested. The algorithm uses a linear Kalman filter for a four-dimensional dynamic–stochastic model of space–time variations of the atmospheric parameters. The results of statistical estimation of the quality of the algorithm used for spatial extrapolation of mesoscale temperature and wind velocity fields are discussed. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Atmospheric and Oceanic Technology American Meteorological Society

New Method of Spatial Extrapolation of Meteorological Fields on the Mesoscale Level Using a Kalman Filter Algorithm for a Four-Dimensional Dynamic–Stochastic Model

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Publisher
American Meteorological Society
Copyright
Copyright © 2007 American Meteorological Society
ISSN
1520-0426
DOI
10.1175/JTECH1967.1
Publisher site
See Article on Publisher Site

Abstract

A new method and an algorithm of spatial extrapolation of mesometeorological fields to a territory uncovered with observations are suggested. The algorithm uses a linear Kalman filter for a four-dimensional dynamic–stochastic model of space–time variations of the atmospheric parameters. The results of statistical estimation of the quality of the algorithm used for spatial extrapolation of mesoscale temperature and wind velocity fields are discussed.

Journal

Journal of Atmospheric and Oceanic TechnologyAmerican Meteorological Society

Published: Feb 1, 2007

References