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An adequate representation of the interaction between the land surface and the atmosphere is critical for both numerical weather prediction and climate models. The surface energy and mass balances are tightly coupled to the terrestrial water cycle, mainly through the state of soil moisture. An inadequate representation of the terrestrial water cycle will deteriorate the state of the land surface model and introduce biases to the atmospheric model. The validation of land surface models is challenging, as there are very few observations and the soil is highly heterogeneous. In this paper, a validation framework for land surface schemes based on catchment mass balances is presented. The main focus of our development lies in the application to kilometer-resolution numerical weather prediction and climate models, although the approach is scalable in both space and time. The methodology combines information from multiple observation-based datasets. Observational uncertainties are estimated by using independent sets of observations. It is shown that the combination of observation-based datasets and river discharge measurements close the water balance fairly well for the chosen catchments. As a showcase application, the framework is then applied to compare and validate four different versions of TERRA ML, the land surface scheme of the COSMO numerical weather prediction and climate model over five mesoscale catchments in Switzerland ranging from 105 to 1713 km². Despite large observational uncertainties, validation results clearly suggest that errors in terrestrial storage changes are closely linked to errors in runoff generation and emphasize the crucial role of infiltration processes. [ABSTRACT FROM AUTHOR]

The correct simulation of fog and low stratus (FLS) is a difficult task for numerical weather prediction (NWP) models. The Swiss Plateau experiences many days with FLS in winter. Most NWP models employ terrain‐following vertical coordinates. As a consequence, the typically flat cloud top is intersected by sloping coordinate surfaces above hilly terrain such as the Swiss Plateau. Horizontal advection across the sloping coordinate surfaces leads to spurious numerical diffusion which promotes erroneous FLS dissipation. To address this problem, we propose a new vertical coordinate formulation which features a local smoothing of the model levels. We demonstrate the positive impact of the new vertical coordinate formulation on a case study in detail and for a full month using the COSMO model. The improved vertical coordinate formulation is not yet sufficient to obtain perfect FLS forecasts, it is however a crucial aspect to consider on the way thereto. Plain Language Summary: In Switzerland, the Swiss Plateau is prone to occurrence of fog and low stratus clouds (FLS) in winter. High‐resolution weather prediction models are an important tool to predict FLS. However, they often struggle to provide accurate FLS forecasts. Among other model aspects which need to be improved, one issue is the determination of the computational mesh: Most weather models employ a mesh which follows the terrain at the Earth's surface, leading to grid cells that are tilted with respect to the horizontal at altitudes where FLS occur. The structure as well as the top of a FLS layer typically is horizontal. Thus, the cells of the computational mesh are at an angle with respect to the dominant physical processes that the model has to represent. We show that a sloping mesh is detrimental for the forecasting of FLS since it promotes premature dissipation of the clouds. For a widely used weather model, we propose a new way to determine the computational mesh leading to a smoother and flatter computational mesh over the Swiss Plateau. The model is still not able to yield perfect FLS forecasts, but in some cases the use of the new mesh leads to considerable forecast improvements. Key Points: Terrain‐following vertical coordinates feature sloping vertical coordinate surfaces in the atmospheric boundary layerSpurious numerical diffusion associated with advection across sloping coordinate surfaces promotes dissipation of fog and low stratusLocal smoothing of the vertical coordinate surfaces improves forecasts of fog and low stratus [ABSTRACT FROM AUTHOR]