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Snow depth and sea ice thickness were observed applying an ice mass balance buoy (IMB) in the drifting ice station Tara during the International Polar Year in 2007. Detailed in situ observations on meteorological variables and surface fluxes were taken during May to August. For this study, the operational analyses and short-term forecasts from two numerical weather prediction (NWP) models (ECMWF and HIRLAM) were extracted for the Tara drift trajectory. We compared the IMB, meteorological and surface flux observations against the NWP products, also applying a one-dimensional thermodynamic sea ice model (HIGHTSI) to calculate the snow and ice mass balance and its sensitivity to atmospheric forcing. The modelled snow depth time series, controlled by NWP-based precipitation, was in line with the observed one. HIGHTSI reproduced well the snowmelt onset, the progress of the melt, and the first date of snow-free conditions. HIGHTSI performed well also in the late August freezing season. Challenges remain to model the “false bottom” observed during the melting season. The evolution of the vertical temperature profiles in snow and ice was better simulated when the model was forced by in situ observations instead of NWP results. During the melting period, the nonlinear ice temperature profile was successfully modelled with both forcing options. During spring and the melting season, total sea ice mass balance was most sensitive to uncertainties in NWP results for the downward longwave radiation, followed by the downward shortwave radiation, air temperature, and wind speed.

The vertical structure of the atmospheric boundary layer (ABL), simulated with the mesoscale modelWeather Research and Forecasting (WRF) as well as with its polar optimized version Polar WRF, was compared to tethered balloon soundings and mast observations taken in March and April 2009 from two Arctic fjords in Svalbard. From twelve short (48 h) simulations, the Quasi-Normal Scale Elimination scheme for the ABL and the NOAH land surface scheme for the surface were found to perform best and were selected for one long (16 day) simulation. The differences in performance of the standard WRF and Polar WRF were marginal. A warm bias, especially near the surface, was found in the modelled temperature profiles related to underestimated temperature inversion strength and depth. The modelled humidity inversions were generally deeper but weaker than the observed, and often occurred independently of temperature inversions. The largest errors in temperature and humidity occurred under high pressure conditions. Multiple temperature and humidity inversions were usually not captured byWRF. Compared to the compact sea ice east of Svalbard, the modelled temperature and humidity inversions were weaker and less frequent over the fjords. The biases in modelled wind speed profiles were closely related to low-level jets (LLJs); the modelled LLJs were stronger and deeper, and typically located at higher altitudes than the observed LLJs. Errors in the near-surface variables were notably reduced by applying post-processing equations based on othermodelled variables.