Four-dimensional variational data assimilation for a limited area model

Nils Gustafsson; Xiang-Yu Huang; Xiaohua Yang; Kristian Mogensen; Magnus Lindskog; Ole Vignes; Tomas Wilhelmsson; Sigurdur Thorsteinsson

doi:10.3402/tellusa.v64i0.14985

Four-dimensional variational data assimilation for a limited area model

Volume 64 (2012): Issue 1

By: Nils Gustafsson, Xiang-Yu Huang, Xiaohua Yang, Kristian Mogensen, Magnus Lindskog, Ole Vignes, Tomas Wilhelmsson and Sigurdur Thorsteinsson

Open Access

|Dec 2012

Abstract

A 4-dimensional variational data assimilation (4D-Var) scheme for the HIgh Resolution Limited Area Model (HIRLAM) forecasting system is described in this article. The innovative approaches to the multi-incremental formulation, the weak digital filter constraint and the semi-Lagrangian time integration are highlighted with some details. The implicit dynamical structure functions are discussed using single observation experiments, and the sensitivity to various parameters of the 4D-Var formulation is illustrated. To assess the meteorological impact of HIRLAM 4D-Var, data assimilation experiments for five periods of 1 month each were performed, using HIRLAM 3D-Var as a reference. It is shown that the HIRLAM 4D-Var consistently out-performs the HIRLAM 3D-Var, in particular for cases with strong mesoscale storm developments. The computational performance of the HIRLAM 4D-Var is also discussed.

The review process was handled by Subject Editor Abdel Hannachi

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Articles in this issue

DOI: https://doi.org/10.3402/tellusa.v64i0.14985 | Journal eISSN: 3035-9554

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Language: English

Page range: 14985 - 14985

Submitted on: May 31, 2011

Accepted on: Dec 7, 2011

Published on: Dec 1, 2012

Published by: Stockholm University Press

In partnership with: Paradigm Publishing Services

Keywords:

data assimilation,

analysis,

numerical weather prediction

© 2012 Nils Gustafsson, Xiang-Yu Huang, Xiaohua Yang, Kristian Mogensen, Magnus Lindskog, Ole Vignes, Tomas Wilhelmsson, Sigurdur Thorsteinsson, published by Stockholm University Press
This work is licensed under the Creative Commons Attribution 4.0 License.

Volume 64 (2012): Issue 1