This study evaluates the representation of the life cycle of a radiation fog case‐study observed at the Cabauw 213 m tower (Netherlands) facility by the Weather Research and Forecasting (WRF) single‐column model, and aims to advance the understanding of the model behaviour, which will assist in setting research priorities for the future. First an ensemble of 16 WRF configurations that vary in parametrization schemes for the planetary boundary layer, land surface, long‐wave radiation, and microphysics are evaluated. Next, we perform a sensitivity study to examine which physical process is most crucial in modelling the fog, i.e. soil heat diffusivity, the CO₂ concentration (representing clear‐sky long‐wave radiation), the vapour diffusion to droplets, and the turbulent mixing. Subsequently, we study whether these perturbations can improve the model representation, and on the other hand whether they can explain the model behaviour of the 16 ensemble members. Results are displayed in process diagrams. We find that the behaviour of the ensemble can be explained by variations in the soil heat diffusivity and the turbulent mixing. However, their sensitivities orient in approximately the same direction, and as such, errors in the formulation of the boundary‐layer scheme can be hidden by compensating errors in the land‐surface scheme. In addition, we find that simultaneous perturbations in the soil heat diffusivity and turbulent mixing do not result in the same results as superposing the individual perturbations.

Land cover (LC) data incorporation, for weather modeling purposes, highlights many problems. The straightforward Single Level Mode (SLM) aggregation is not adapted for high‐resolution LC maps, with a high number of classes, because it could generate false classifications. We propose a Multi‐Level Mode (MLM) aggregation method that includes a hierarchical structure. This study focuses on the Corine Land Cover (CLC) data set. Differences between MLM and SLM methods are small at the finest horizontal resolution and increase to a value of around 16% at 9‐km horizontal resolution. To further integrate CLC data into WRF (Weather Research Forecasting model), we included a dedicated table of physical parameters next to using the classical conversion toward the USGS one. To evaluate the LC impact on the modeled boundary layer, we used WRF at 1 km to simulate a 4‐day period with diurnal cycles of valley winds in the heterogeneous western pre‐Alps area. We tested three LCs (USGS, MODIS, and CLC), where CLC has two physical parameter tables and two aggregation methods. CLC performs better than other tested LCs. The CLC aggregation methods revealed limited differences between the simulated variables, although the MLM method gives better results. Since these comparisons are restricted to a single location with the same LC type, the differences between various simulations regarding atmospheric parameters probably result from horizontal advection from upwind areas where surface conditions differ. Extended time series with multiple locations and diverse meteorological conditions need to be considered to reinforce the results presented here.

In an overall approach aiming at the development and qualification of various tools designed to diagnose and/or forecast the flows at the local scale in complex terrain, we qualified a numerical model based on the WRF platform and operated in a two-way nested domain mode, down to a horizontal resolution of 111 m for the smallest domain. The area in question is the Cadarache valley (CV), in southeast France, which is surrounded by hills and valleys of various sizes. The CV dimensions (1 km wide and 100 m deep) favor the development of local flows greatly influenced by the diurnal cycle and are prone to thermal stratification, especially during stable conditions. This cycle was well documented due to permanent observations and dedicated field campaigns. These observations were used to evaluate the performance of the model on a specific day among the intensive observation periods carried out during the KASCADE-2017 campaign. The model reproduced the wind flow and its diurnal cycle well, notably at the local CV scale, which constitutes considerable progress with respect to the performances of previous WRF simulations conducted in this area with kilometric resolution, be it operational weather forecasts or dedicated studies conducted on specific days. The diurnal temperature range is underestimated however, together with the stratification intensity of the cold pool observed at night. Consequently, the slope drainage flows along the CV sidewalls are higher in the simulation than in the observations, and the resulting scalar fields (such as specific humidity) are less heterogeneous in the model than in the observations.

The purpose of this paper is to present a practical method for quick determination of potential radiological doses and contaminations by fallout from nuclear detonations, or other releases, that includes the contributions from all nuclides. We precalculate individual (total) activities of all radionuclides from any initial cocktail and all their ingrowing progeny at a set of pinpoints in time with a logarithmic time-spacing. This is combined with the set of dose conversion factors (DCC) for any exposure pathway to obtain a time-dependent cocktail for the whole release as if it is one substance. An atmospheric dispersion model then provides the thinning coefficient of the released material to give local concentrations and dose rates. Progeny ingrowth is illustrated for pure ²³⁸U and for a nuclear reactor that has been shut down. Efficient dose assessment is demonstrated for fallout from nuclear detonations and compared with the traditional approach of preselecting nuclides for specific endpoints and periods-of-interest. The compound cocktail DCC reduces the assessment of contaminations and potential dose-effects from fallout after a nuclear detonation to (the atmospheric dispersion of) only one tracer substance, representing any cocktail of nuclides and their progeny. This removes the need to follow all separate nuclides or an endpoint-specific preselection of “most important nuclides.” As the cocktail DCCs can be precalculated and the atmospheric dispersion of only one tracer substance has to be modelled, our method is fast. The model for calculating cocktail DCCs is freely available, easily coupled to any regular atmospheric dispersion model, and therefore ready for operational use by others.