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In order to study the small-scale structure of radition fog, large-eddy simulations (LESs) of a fog case are analysed. The LESs were performed at very high resolution -2 m in the horizontal and 1 m in the vertical. Despite uncertainties in the measurements, particularly for advection, the main characteristics of the fog layer were well captured by the model. Radiation fog forms in statically stable stratification near the ground. During the formation phase, small stripes occur in the middle of the fog layer, associated with a significant burst in the turbulent kinetic energy (TKE). During the development phase, the dynamics of the fog layer change significantly. The maximum of the variance moves to the top of the fog layer where horizontal rolls appear clearly. These eddies have their centre near the mean top of the fog layer and have a depth corresponding to about one third of the fog layer height. This leads to a maximum of TKE at the top of fog, and to very strong scatter on the liquid water content. The energy is clearly produced at a length-scale corresponding to the fog height. The turbulence is 3D homogeneous inside the fog layer, while it is better characterized by 2D turbulence near the top. During the dissipation phase, the radiative heating of the surface increases the convective structure of the fog. The dissipation of fog at ground level takes a long time (about 2 h), even if the soil conditions are homogeneous. The top of the stratus layer is homogeneous, while the spread of the base height reaches a value typical of the cloud thickness. Copyright

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Accurate short-term forecasts of low ceiling and visibility are vital to air traffic operation, in order to maximize the use of an airport. The research presented here uses specific local observations and a detailed numerical 1D model in an integrated approach. The goal of the proposed methodology is to improve the local prediction of poor visibility and low clouds at Paris's Charles de Gaulle International Airport. In addition to the development of an integrated observations and model-based forecasting system, this study will try to assess whether or not the increased local observing network yields improvements in short-term forecasts of low ceiling and poor visibility. Tests have been performed in a systematic manner during 5 months (the 2002/03 winter season). Encouraging results show that the inclusion of dedicated observations into the local 1D forecast system provides significant improvement to the forecast. Inspection of events indicates that the improvement in very short-term forecasts is a consequence of the ability of the forecast system to more accurately characterize the boundary layer processes, especially during night. Accurate forecast of low cloud seems more difficult since it strongly depends on the 3D mesoscale flow. This study also demonstrates that the use of a 1D model to forecast fogs and low clouds could only be beneficial if it is associated with local measurements and with a local assimilation scheme. The assimilation procedure used in this study is based on different steps: in the first step the atmospheric profiles are estimated in a one-dimensional variational data assimilation (1DVAR) framework, in the second step these atmospheric profiles are modified when fog and/or low clouds are detected, and in the third step the soil profiles are estimated in order to keep the consistency between the soil state and atmospheric measurements.