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FOUR-DIMENSIONAL VARIATIONAL DATA ASSIMILATION IN NUMERICAL WEATHER PREDICTION

Huynh Thi Hong Ngu 1
La Thi Cang 1
Volume & Issue: Vol. 11 No. 12 (2008) | Page No.: 98-103 | DOI: 10.32508/stdj.v11i12.2720
Published: 2008-12-31

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This article is published with open access by Viet Nam National University, Ho Chi Minh City, Viet Nam. This article is distributed under the terms of the Creative Commons Attribution License (CC-BY 4.0) which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.

Abstract

Data assimilation is a very complicated cycle in numerical weather prediction and influences the quality of forecast. In this technique, the observered meteorological data are combined with the results of previous short-range forecast of the model to make an initial condition for a new prediction. This paper presents: four-dimensional variational assimilation (4D-Var), the most advanced technique for the data assimilation; the application of data assimilation in numerical weather prediction in Vietnam at present and the development of this technique in future.

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