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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.

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 LANFEX field campaign. 7 of the SCMs represent single-column equivalents of operational numerical weather prediction (NWP) models, whilst 3 are research-grade SCMs designed for fog simulation, and the LES 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 (CDNC) conditions. The main SCM bias appears to be toward over-development 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 parametrization, as it is to the underlying aerosol or CDNC. [ABSTRACT FROM AUTHOR]

This numerical study focuses on a dense fog event that occurred during the night of 21-22 January 2008 in the Grand Casablanca region, on the northwestern coast of Morocco. This fog event, which lasted for 15 h, is simulated by the mesoscale non-hydrostatic model Meso-NH and analyzed using conventional meteorological observations from two synoptic stations of the region, Meteosat Second Generation ( MSG) satellite imagery and the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-Interim reanalysis. Results demonstrate that this fog event included the formation of radiation fog over a continental zone and its extension to the coastal zone through the lowering of low-stratus clouds, which is in agreement with observations and is captured well by the Meso-NH model. Sensitivity experiments show that coastal fog prediction improves with improved sea-surface temperature. Model skill also depends on the adjustment of microphysical parameters when a single-moment microphysical scheme is used, and on reliable initial conditions. [ABSTRACT FROM AUTHOR]

Large-eddy simulations (LES) of radiation fog were performed over an airport area to study the effect of urban canopy on fog. These LES were performed with the Meso-NH research model at very high resolution: 1.5 m in the horizontal and 1 m in the vertical and over a domain 4.5 km × 1.5 km. The blocking effect of the airport buildings led to strong wind shear and consequently to the production of turbulent kinetic energy (TKE). The airport buildings also had a strong effect on vertical velocity, with a subsidence region behind the buildings. The increase of both turbulence and vertical velocity strongly modified the fog formation. The fog layer took more time to form in the airport area, but the increase in turbulence facilitated the vertical development of the fog layer. The fog took 1.5 h to form over the whole simulated airport area. The fog height was heterogeneous during the formation phase, with the formation of very low clouds locally. The effect of airport buildings on vertical velocity could explain these heterogeneities of the fog height. During the mature phase of the fog, the buildings had little impact on the fog layer characteristics. The fog dynamics were mainly controlled by processes at its top. These results suggest that the inclusion of high levels of detail in the building representation remains important for the local forecasting of fog formation. Particularly, small-scale heterogeneities can explain the spatial variability of fog formation. It seems necessary to take small-scale variability of the urban canopy into account for local and accurate forecasts of fog formation over airport areas. [ABSTRACT FROM AUTHOR]