Sub-kilometre Scale Numerical Weather Prediction of Radiation Fog

Abstract:

Fog has a large socio-economic impact particularly on ground transport, aviation and human health. 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), which took place in the UK, has provided a new, comprehensive and detailed observational dataset creating a unique opportunity to assess the NWP of fog events. The performance of the Met Office Unified Model (MetUM) with three horizontal grid-lengths; 1.5 km, 333 m and 100 m, is evaluated for four LANFEX case studies. In general, the sub-km scale versions of the MetUM are in better agreement with the observations, however there are a number of systematic model deficiencies. The MetUM produces valleys that are too warm and hills that are too cold at night, leading to valleys that do not have enough fog and hills that have too much. A holistic set of physical parametrization sensitivity experiments were performed and a large sensitivity to soil temperature was revealed - in all cases, the model erroneously transfers heat too readily to the surface, negating fog formation. Sensitivity tests show that the specification of soil thermal conductivity can lead to up to a 5-hour change in fog formation. Overall the sub-km models demonstrate promise, but they have a high sensitivity to surface properties.