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

Daniel Smith, Ian Renfrew, Stephen Dorling, Jeremy D. Price, Ian A. Boutle

Research output: Contribution to journalArticlepeer-review

24 Citations (Scopus)
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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, 333 m and 100 m, in simulating 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, 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‐hour change in fog onset time. Overall the sub‐km models demonstrate promise but they have a high sensitivity to surface properties.
Original languageEnglish
Pages (from-to)746-763
Number of pages18
JournalQuarterly Journal of the Royal Meteorological Society
Issue number735
Early online date7 Nov 2020
Publication statusPublished - Jan 2021


  • NWP
  • boundary-layer
  • radiation fog
  • soil thermal conductivity

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