Technical Note: Spectral representation of spatial correlations in variational assimilation with grid point models and application to the Belgian Assimilation System for Chemical Observations (BASCOE)

Abstract

The formulation of the background error covariances represented in the spectral space is discussed in the context of univariate assimilation relying on a grid point model, leaving out all the aspects of balances between the different control variables needed in meteorological assimilation. The spectral transform operations are discussed in the case of a spherical harmonics basis and we stress that there is no need for an inverse spectral transform and of a Gaussian grid. The analysis increments are thus produced directly on the model grid. The practice of producing analysis increments on a horizontal Gaussian grid and then interpolating to an equally spaced grid is also shown to produce a degradation of the analysis. The method discussed in this paper allows the implementation of separable and non-separable spatial correlations. The separable formulation has been implemented in the Belgian Assimilation System for Chemical ObsErvations (BASCOE) and its impact on the assimilation of O₃ observed by the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) is shown. To promote the use of this method by other non-meteorological variational systems and in particular chemistry, the Fortran code developed is made available to the community.