Three-dimensional fog forecasting in complex terrain

Fog in complex terrain shows large temporal and spatial variations that can onlybe simulated with a three-dimensional model, but more modifications than simplyincreasing the resolution are needed. For a better representation of fog, we presenta second-moment cloud water scheme with a parametrization of the K¨ohler theorywhich is combined with the mixed-phase Ferrier microphysics scheme. The moredetailed PAFOG microphysics produce many differences to the first-moment Ferrierscheme and are responsible for the typically low liquid water content of fog. Theinclusion of droplet sedimentation in the Ferrier scheme cannot reproduce theresults obtained with PAFOG, as there is a large sensitivity to the sedimentationvelocity. With explicitly predicted droplet number concentrations, sedimentationof cloud water can be modelled with variable fall speeds, which mainly affects thevertical distribution of cloud water and the end of the fog’s life cycle. The complextopography of the Swiss Alps and their surroundings are used for model testing. Asthe focus is on the model’s ability to forecast the spatial distribution of fog, cloudpatterns derived from high-resolution MSG satellite data, rather than few pointobservations from ground stations, are used. In a five-day period of anticyclonicconditions, the satellite-observed fog patterns showed large day-to-day variationsfrom almost no fog to large areas of fog. This variability was very well predicted inthe three-dimensional fog forecast. Furthermore, the second-moment cloud waterscheme shows a better agreement with the satellite observations than its first-moment counterpart. For model initialization, the complex topography is actuallya simplifying factor, as cold air flow and pooling dominate the more uncertainprocesses of evapotranspiration or errors in the soil moisture field.