Open AccessNew Method of Spatial Extrapolation of Meteorological Fields on the Mesoscale Level Using a Kalman Filter Algorithm for a Four-Dimensional Dynamic–Stochastic Model
Author(s) -
V. S. Komarov,
A. V. Lavrinenko,
A. V. Kreminskii,
N. Ya. Lomakina,
Yu. B. Popov,
A. I. Popova
Publication year - 2007
Publication title -
journal of atmospheric and oceanic technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.774
H-Index - 124
eISSN - 1520-0426
pISSN - 0739-0572
DOI - 10.1175/jtech1967.1
Subject(s) - extrapolation , mesoscale meteorology , kalman filter , meteorology , ensemble kalman filter , extended kalman filter , computer science , wind speed , filter (signal processing) , algorithm , remote sensing , mathematics , geology , statistics , geography , artificial intelligence , computer vision
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.