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Demistify: A large-eddy simulation (LES) and single-column model (SCM) intercomparison of radiation fog

Research output: Contribution to journalArticleResearchpeer review

Authors

  • Ian Boutle
  • Wayne Angevine
  • Jian Wen Bao
  • Thierry Bergot
  • Bjorn Maronga
  • Johannes Schwenkel

External Research Organisations

  • Met Office
  • University of Colorado Boulder
  • National Oceanic and Atmospheric Administration
  • Universite de Toulouse
  • Goethe University Frankfurt
  • University of Bonn
  • European Centre for Medium-Range Weather Forecasts
  • Deutscher Wetterdienst (DWD)
  • University of California at Davis
  • Finnish Meteorological Institute
  • Wageningen University and Research
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Details

Original languageEnglish
Pages (from-to)319-333
Number of pages15
JournalAtmospheric chemistry and physics
Volume22
Issue number1
Publication statusPublished - 10 Jan 2022

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.

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Cite this

Demistify: A large-eddy simulation (LES) and single-column model (SCM) intercomparison of radiation fog. / Boutle, Ian; Angevine, Wayne; Bao, Jian Wen et al.
In: Atmospheric chemistry and physics, Vol. 22, No. 1, 10.01.2022, p. 319-333.

Research output: Contribution to journalArticleResearchpeer review

Boutle, I, Angevine, W, Bao, JW, Bergot, T, Bhattacharya, R, Bott, A, Ducongé, L, Forbes, R, Goecke, T, Grell, E, Hill, A, Igel, AL, Kudzotsa, I, Lac, C, Maronga, B, Romakkaniemi, S, Schmidli, J, Schwenkel, J, Steeneveld, GJ & Vié, B 2022, 'Demistify: A large-eddy simulation (LES) and single-column model (SCM) intercomparison of radiation fog', Atmospheric chemistry and physics, vol. 22, no. 1, pp. 319-333. https://doi.org/10.5194/acp-22-319-2022
Boutle, I., Angevine, W., Bao, J. W., Bergot, T., Bhattacharya, R., Bott, A., Ducongé, L., Forbes, R., Goecke, T., Grell, E., Hill, A., Igel, A. L., Kudzotsa, I., Lac, C., Maronga, B., Romakkaniemi, S., Schmidli, J., Schwenkel, J., Steeneveld, G. J., & Vié, B. (2022). Demistify: A large-eddy simulation (LES) and single-column model (SCM) intercomparison of radiation fog. Atmospheric chemistry and physics, 22(1), 319-333. https://doi.org/10.5194/acp-22-319-2022
Boutle I, Angevine W, Bao JW, Bergot T, Bhattacharya R, Bott A et al. Demistify: A large-eddy simulation (LES) and single-column model (SCM) intercomparison of radiation fog. Atmospheric chemistry and physics. 2022 Jan 10;22(1):319-333. doi: 10.5194/acp-22-319-2022
Boutle, Ian ; Angevine, Wayne ; Bao, Jian Wen et al. / Demistify : A large-eddy simulation (LES) and single-column model (SCM) intercomparison of radiation fog. In: Atmospheric chemistry and physics. 2022 ; Vol. 22, No. 1. pp. 319-333.
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title = "Demistify: A large-eddy simulation (LES) and single-column model (SCM) intercomparison of radiation fog",
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.",
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Download

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T2 - A large-eddy simulation (LES) and single-column model (SCM) intercomparison of radiation fog

AU - Boutle, Ian

AU - Angevine, Wayne

AU - Bao, Jian Wen

AU - Bergot, Thierry

AU - Bhattacharya, Ritthik

AU - Bott, Andreas

AU - Ducongé, Leo

AU - Forbes, Richard

AU - Goecke, Tobias

AU - Grell, Evelyn

AU - Hill, Adrian

AU - Igel, Adele L.

AU - Kudzotsa, Innocent

AU - Lac, Christine

AU - Maronga, Bjorn

AU - Romakkaniemi, Sami

AU - Schmidli, Juerg

AU - Schwenkel, Johannes

AU - Steeneveld, Gert Jan

AU - Vié, Benoît

N1 - Funding Information: Juerg Schmidli was supported by the Hans Ertel Centre for Weather Research of DWD (The Atmospheric Boundary Layer in Numerical Weather Prediction) grant number 4818DWDP4. Ritthik Bhattacharya was supported by MeteoSwiss (project number 123001738). This work used resources of the Deutsches Klimarechenzentrum (DKRZ) granted by its Scientific Steering Committee (WLA) under project ID bb1096. Innocent Kudzotsa and Sami Romakkaniemi were supported by the Horizon 2020 Research and Innovation Programme (grant no. 821205). Johannes Schwenkel was supported by the German Research Foundation (grant no. MA 6383/1-2)

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N2 - 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.

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