Conference Proceedings
Ensemble Perturbations for Chemical Data Assimilation
Jeremy D Silver, Jorgen Brandt, Jesper H Christensen, Michael Kahnert, Lennart Robertson, DG Steyn (ed.), PJH Builtjes (ed.), RMA Timmermans (ed.)
AIR POLLUTION MODELING AND ITS APPLICATION XXII | SPRINGER | Published : 2014
Abstract
The ensemble Kalman filter is a commonly used framework for chemical data assimilation. Random perturbations are required for the ensemble initial conditions and to account for model error. For a chemical transport model, such perturbations should represent appropriate scales of variation and correlations in the horizontal, vertical and chemical dimensions. We present a sampling scheme to generate normally distributed perturbations with covariances based on a climatological background covariance matrix, estimated with a spectral decomposition, assuming horizontally homogeneous and isotropic error correlations. We tested the sampling scheme with an ensemble Kalman filter coupled to the Danish..
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