Masbou, Matthieu: LM-PAFOG - a new three-dimensional fog forecast model with parametrised microphysics. - Bonn, 2008. - Dissertation, Rheinische Friedrich-Wilhelms-Universität Bonn.
Online-Ausgabe in bonndoc: https://nbn-resolving.org/urn:nbn:de:hbz:5N-15692
@phdthesis{handle:20.500.11811/3694,
urn: https://nbn-resolving.org/urn:nbn:de:hbz:5N-15692,
author = {{Matthieu Masbou}},
title = {LM-PAFOG - a new three-dimensional fog forecast model with parametrised microphysics},
school = {Rheinische Friedrich-Wilhelms-Universität Bonn},
year = 2008,
note = {

The presence of fog and low clouds in the lower atmosphere can have a critical impact on both airborne and ground transports and is often connected with serious accidents. An improvement of fog forecasts in terms of localisation, duration and variations in visibility therefore holds an immense operational value for the field of transportation in conditions of low visibility. However, fog is generally a small scale phenomenon which is mostly affected by local advective transport, turbulent mixing at the surface as well as its microphysical structure. Therefore, a detailed description of the microphysical processes within the three-dimensional dynamical core of the forecast model is necessary. For this purpose, a new microphysical parametrisation based on the one-dimensional fog forecast model, PAFOG, was implemented in the “Lokal Modell” (LM), the nonhydrostatic mesoscale model of the German Meteorological Service. The implementation of cloud water droplets as a new prognostic variable allows a detailed definition of the sedimentation processes and the variations in visibility. A horizontal resolution of 2.8 km and a vertical resolution of 4 m describe the boundary layer processes, forecasted by LM-PAFOG. In the framework of the COST 722 intercomparison campaign, the evaluation of the LM-PAFOG forecasts, based on statistical study and case studies, points out the variability of the model performance between day and night time periods. Moreover, the comparisons with other fog forecast systems highlight the decisive influence of an adapted data assimilation scheme for the high grid resolution model, as well as the necessary calibration of a visibility parametrisation. Finally, due to the lack of information concerning the observed fog spatial extension, a verification scheme with MSG satellite products for fog and low stratus is tested.

},

url = {http://hdl.handle.net/20.500.11811/3694}
}

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