Demistify: a large-eddy simulation (LES) and single-column model (SCM) intercomparison of radiation fog
-
Published:2022-01-10
Issue:1
Volume:22
Page:319-333
-
ISSN:1680-7324
-
Container-title:Atmospheric Chemistry and Physics
-
language:en
-
Short-container-title:Atmos. Chem. Phys.
Author:
Boutle IanORCID, Angevine WayneORCID, Bao Jian-Wen, Bergot Thierry, Bhattacharya Ritthik, Bott Andreas, Ducongé Leo, Forbes RichardORCID, Goecke Tobias, Grell Evelyn, Hill Adrian, Igel Adele L.ORCID, Kudzotsa InnocentORCID, Lac Christine, Maronga Bjorn, Romakkaniemi SamiORCID, Schmidli JuergORCID, Schwenkel JohannesORCID, Steeneveld Gert-JanORCID, Vié BenoîtORCID
Abstract
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.
Funder
Horizon 2020 Deutsches Klimarechenzentrum Deutsche Forschungsgemeinschaft
Publisher
Copernicus GmbH
Subject
Atmospheric Science
Reference42 articles.
1. Ahlgrimm, M. and Forbes, R.: Improving the representation of low clouds and
drizzle in the ECMWF model based on ARM observations from the Azores, Mon.
Weather Rev., 142, 668–685, 2014. a 2. Angevine, W. M., Olson, J., Kenyon, J., Gustafson, W. I., Endo, S., Suselj, K.,
and Turner, D. D.: Shallow Cumulus in WRF Parameterizations Evaluated against
LASSO Large-Eddy Simulations, Mon. Weather Rev., 146, 4303–4322,
https://doi.org/10.1175/MWR-D-18-0115.1, 2018. a 3. Baldauf, M., Seifert, A., Förstner, J., Majewski, D., Raschendorfer, M.,
and Reinhardt, T.: Operational Convective-Scale Numerical Weather Prediction
with the COSMO Model: Description and Sensitivities, Mon. Weather Rev., 139,
3887–3905, https://doi.org/10.1175/MWR-D-10-05013.1, 2011. a 4. Bašták Ďurán, I., Köhler, M., Eichhorn-Müller, A.,
Maurer, V., Schmidli, J., Schomburg, A., Klocke, D., Göcke, T.,
Schäfer, S., Schlemmer, L., and Dewani, N.: The ICON Single-Column Mode,
Atmosphere, 12, 906, https://doi.org/10.3390/atmos12070906, 2021. a 5. Beare, R. J., MacVean, M. K., Holtslag, A. A. M., Cuxart, J., Esau, I., Golaz,
J.-C., Jimenez, M. A., Khairoutdinov, M., Kosovic, B., Lewellen, D., Lund,
T. S., Lundquist, J. K., McCabe, A., Moene, A. F., Noh, Y., Raasch, S., and
Sullivan, P.: An Intercomparison of Large-Eddy Simulations of the Stable
Boundary Layer, Bound.-Lay. Meteorol., 118, 247–272,
https://doi.org/10.1007/s10546-004-2820-6, 2006. a, b
Cited by
17 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
|
|