Heterogeneous convective-scale background error covariances with the inclusion of hydrometeor variables

They however still lack advanced data assimilation schemes able to efficiently use observations to initialize hydrometeor fields. This challenging task may benefit from a better understanding of the statistical structure of background errors in precipitating areas for both traditional and hydrometeor variables, which is the goal of this study.

A special binning has been devised to compute separate background error covariances matrices for precipitating and non-precipitating areas. This binning is based on bi-dimensional geographical masks defined by the vertical averaged rain content of the background error perturbations. The sample for computing the covariances is taken from an ensemble of short range forecasts run at 3-km resolution for the prediction of two specific cases of convective storms over the US.