Spatial interpolation of meteorological fields using a multilevel parametric dynamic stochastic low-order model
| Autor: | A.V. Lavrinenko, A. I. Popova, E. A. Moldovanova, D.F. Mymrina, Yu B Popov, K.Y. Popova |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Atmospheric Science
010504 meteorology & atmospheric sciences 010103 numerical & computational mathematics Kalman filter 01 natural sciences Wind speed Multivariate interpolation Troposphere Geophysics Altitude Data assimilation Space and Planetary Science Feature (computer vision) 0101 mathematics Algorithm Physics::Atmospheric and Oceanic Physics 0105 earth and related environmental sciences Mathematics Parametric statistics |
| Zdroj: | Journal of Atmospheric and Solar-Terrestrial Physics. 181:38-43 |
| ISSN: | 1364-6826 |
| Popis: | The paper focuses on a new method of spatial interpolation of air temperature and wind velocity fields in the troposphere. The method is based on Kalman filtering and a multilevel parametric dynamic stochastic low-order model. The key feature of the proposed model is that it has parameters, which are responsible for the altitude levels. Generally, models use so-called “shallow water” (shallow water approximation), and altitude correlation is not taken into account, or they may rely only on mandatory isobaric levels data, thus ignoring the data obtained for significant levels. Standard levels are located at considerable distances in altitude from each other and the altitude correlation there is not usually significant. By using parameters that are responsible for the altitude levels, this model allows us to estimate the effect that information coming from neighbouring altitude levels may have on the final estimate. The paper presents the results of a statistical estimation of the proposed spatial interpolation algorithm. A comparison of the results statistical estimation spatial interpolation of the proposed algorithm with a four-dimensional dynamic-stochastic model is given. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Full Text from ScienceDirect