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. In Norway, 30 % of the annual precipitation falls as snow.Knowledge of the snow reservoir is therefore important for energy productionand water resource management. The land surface model SURFEX with thedetailed snowpack scheme Crocus (SURFEX/Crocus) has been run with a gridspacing of 1 km over an area in southern Norway for 2 years (1 September2014–31 August 2016). Experiments were carried out using two differentforcing data sets: (1) hourly forecasts from the operational weather forecastmodel AROME MetCoOp (2.5 km grid spacing) including post-processedtemperature (500 m grid spacing) and wind, and (2) gridded hourly observationsof temperature and precipitation (1 km grid spacing) combined withmeteorological forecasts from AROME MetCoOp for the remaining weathervariables required by SURFEX/Crocus. We present an evaluation of the modelledsnow depth and snow cover in comparison to 30 point observations of snow depthand MODIS satellite images of the snow-covered area. The evaluationfocuses on snow accumulation and snowmelt. Both experiments are capable ofsimulating the snowpack over the two winter seasons, but there is anoverestimation of snow depth when using meteorological forecasts from AROMEMetCoOp (bias of 20 cm and RMSE of 56 cm), although the snow-covered areain the melt season is better represented by this experiment. Theerrors, when using AROME MetCoOp as forcing, accumulate over the snow season.When using gridded observations, the simulation of snow depth issignificantly improved (the bias for this experiment is 7 cm and RMSE 28 cm),but the spatial snow cover distribution is not well captured during themelting season. Underestimation of snow depth at high elevations (due to thelow elevation bias in the gridded observation data set) likely causes thesnow cover to decrease too soon during the melt season, leading tounrealistically little snow by the end of the season. Our results show thatforcing data consisting of post-processed NWP data (observations assimilatedinto the raw NWP weather predictions) are most promising for snowsimulations, when larger regions are evaluated. Post-processed NWP dataprovide a more representative spatial representation for both high mountainsand lowlands, compared to interpolated observations. There is, however, anunderestimation of snow ablation in both experiments. This is generally dueto the absence of wind-induced erosion of snow in the SURFEX/Crocus model,underestimated snowmelt and biases in the forcing data.

Forcing the SURFEX/Crocus snow model with combined hourly meteorological forecasts and gridded observations in southern Norway