%0 Journal Article
%T Four-dimensional variational data assimilation for a limited area model
%A Nils Gustafsson
%A Xiang-Yu Huang
%A Xiaohua Yang
%A Kristian Mogensen
%J Tellus A
%D 2012
%I Co-Action Publishing
%R 10.3402/tellusa.v64i0.14985
%X 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
%K data assimilation
%K analysis
%K numerical weather prediction
%U http://www.tellusa.net/index.php/tellusa/article/view/14985/pdf_1