Sub-km scale numerical weather prediction model simulations of radiation fog

The numerical weather prediction (NWP) of fog remains a challenge, with accurate forecasts relying on the representation of many interacting physical processes. The recent Local And Non-local Fog EXperiment (LANFEX) has generated a detailed observational dataset, creating a unique opportunity to assess the NWP of fog events. We evaluate the performance of operational and research configurations of the Met Office Unified Model (MetUM) with three horizontal grid lengths, 1.5 km and 333 and 100 m, in simulating four LANFEX case studies. In general, the subkilometre (sub-km) scale versions of MetUM are in better agreement with the observations; however, there are a number of systematic model deficiencies. MetUM produces valleys that are too warm and hills that are too cold, leading to valleys that do not have enough fog and hills that have too much. A large sensitivity to soil temperature was identified from a set of parametrisation sensitivity experiments. In all the case studies, the model erroneously transfers heat too readily through the soil to the surface, preventing fog formation. Sensitivity tests show that the specification of the soil thermal conductivity parametrisation can lead to up to a 5-hr change in fog onset time. Overall, the sub-km models demonstrate promise, but they have a high sensitivity to surface properties.

Automated summary

Numerical weather prediction (NWP) of fog remains a challenge, with the Met Office Unified Model (MetUM) showing significant systematic model deficiencies in simulating fog events. The sub-km scale versions of MetUM are in better agreement with observations, but demonstrate high sensitivity to surface properties. Sensitivity tests reveal that the specification of soil thermal conductivity parametrisation can lead to up to a 5-hr change in fog onset time.