Validation of the WRF 3D and single-column model over snow-covered surfaces in stable conditions

Modeling the atmospheric stable boundary layer (SBL) remains challenging, especially over snow-covered polar surfaces. For example in the Arctic, many global and regional climate model outputs diverge from one another, as well as from observations e.g. for near surface variables such as temperature, wind speed and humidity. The SBL is affected by many small-scale physical processes, such as turbulent mixing, the coupling of the atmosphere and the underlying medium, radiation, the presence of clouds or fog, subsidence, advection, gravity waves and drainage and katabatic flows. The ongoing challenges in SBL modeling are related to these physical processes and their interactions, which are either not completely understood, or are represented incompletely.

Single-column models (SCMs) are a widely used and convenient tool to evaluate the physical processes in the boundary layer and can thus be used to enhance the understanding of SBL processes. Therefore in this study the SCM version of the Weather Research and Forecasting (WRF) mesoscale meteorological model is evaluated for stable conditions over snow-covered surfaces. In order to validate the model performance with observations, the SCM needs to be driven by realistic forcings of the 3D atmospheric field (Baas et al., 2010). Therefore first the WRF 3D model will be evaluated after which its output can be used as input for the WRF SCM.

This study is performed for three different land use types using data from the Cabauw site in the Netherlands, the Sodankylä site in Finland and the Halley station on Antarctica. Here the land uses are snow over grass/cropland, snow in an evergreen needleleaf forest and snow on an ice sheet, respectively. In this way we try to distinguish between the model performances for different land use types. Furthermore the Sodankylä site was chosen to study the model performance for different wind regimes, allowed by the relatively frequent occurrence of cloud-free days during the periods with snow cover. In this way a large range of synoptic conditions is represented.