Forcing the SURFEX/Crocus snow model with combined hourly meteorological forecasts and gridded observations in southern Norway
Abstract. In Norway, thirty percent of the annual precipitation falls as snow. Knowledge of the snow reservoir is therefore important for energy production and water resource management. The land surface model SURFEX with the detailed snowpack scheme Crocus (SURFEX/Crocus) has been run with a grid spacing of approximately 1 km over an area in southern Norway for two years (01 September 2014–31 August 2016), using two different forcing data sets: 1) hourly meteorological forecasts from the operational weather forecast model AROME MetCoOp (2.5 km grid spacing), and 2) gridded hourly observations of temperature and precipitation (1 km grid spacing) in combination with the meteorological forecasts from AROME MetCoOp. We present an evaluation of the modeled snow depth and snow cover, as compared to point observations of snow depth and to MODIS satellite images of the snow-covered area. The evaluation focuses on snow accumulation and snow melt. The results are promising. Both experiments are capable of simulating the snow pack over the two winter seasons, but there is an overestimation of snow depth when using only meteorological forecasts from AROME MetCoOp, although the snow-covered area throughout the melt season is better represented by this experiment. The errors, when using AROME MetCoOp as forcing, accumulate over the snow season, showing that assimilation of snow depth observations into SURFEX/Crocus might be necessary when using only meteorological forecasts as forcing. When using gridded observations, the simulation of snow depth is significantly improved, which shows that using a combination of gridded observations and meteorological forecasts to force a snowpack model is very useful and can give better results than only using meteorological forecasts. There is however an underestimation of snow ablation in both experiments. This is mainly due to the absence of wind-induced erosion of snow in the SURFEX/Crocus model, underestimated snow melt and biases in the forcing data.