Adaptive mesh method in the Met Office variational data assimilation system

A frequent problem in forecasting fog or icy roads in a numerical weather prediction (NWP) system is attributed to the misinterpretation of the boundary‐layer structure in the assimilation procedure. Case‐studies showed that the misinterpretation of temperature inversions and stratocumulus layers in the assimilation is due to inappropriate background‐error covariances. This paper looks at the application of static adaptive mesh methods in the Met Office variational assimilation system to modify the background‐error correlations in the boundary layer when temperature inversions or stratocumulus layers are present in the background state. Results show improvements in the analysis root mean square errors with respect to radiosonde observations and surface observations and improvements in forecast errors in 2 m temperature in the presence of low clouds. This enhancement in 2 m temperature forecast is attributed to reduced background vertical correlations and increased temperature background‐error variances in the assimilation due to the movement of the grid near the surface.