Demistify: a large-eddy simulation (LES) and single-column model (SCM) intercomparison of radiation fog Journal Article uri icon



  • Abstract. An intercomparison between 10 single-column (SCM) and 5 large-eddy; simulation (LES) models is presented for a radiation fog case study; inspired by the Local and; Non-local Fog Experiment (LANFEX) field campaign. Seven of the SCMs represent; single-column equivalents of operational numerical weather; prediction (NWP) models, whilst three are research-grade SCMs designed; for fog simulation, and the LESs are designed to reproduce in the; best manner currently possible the underlying physical processes; governing fog formation. The LES model results are of variable; quality and do not provide a consistent baseline against which to; compare the NWP models, particularly under high aerosol or cloud; droplet number concentration (CDNC) conditions. The main SCM bias; appears to be toward the overdevelopment of fog, i.e. fog which is too; thick, although the inter-model variability is large. In reality; there is a subtle balance between water lost to the surface and; water condensed into fog, and the ability of a model to accurately; simulate this process strongly determines the quality of its; forecast. Some NWP SCMs do not represent fundamental components of; this process (e.g. cloud droplet sedimentation) and therefore are; naturally hampered in their ability to deliver accurate; simulations. Finally, we show that modelled fog development is as; sensitive to the shape of the cloud droplet size distribution, a; rarely studied or modified part of the microphysical; parameterisation, as it is to the underlying aerosol or CDNC.;

publication date

  • January 10, 2022

has restriction

  • gold

Date in CU Experts

  • May 18, 2022 8:20 AM

Full Author List

  • Boutle I; Angevine W; Bao J-W; Bergot T; Bhattacharya R; Bott A; Ducongé L; Forbes R; Goecke T; Grell E

author count

  • 20

Other Profiles

Electronic International Standard Serial Number (EISSN)

  • 1680-7324

Additional Document Info

start page

  • 319

end page

  • 333


  • 22


  • 1