Modelling the changing face of snow
Many mountainous regions depend heavily upon the contribution of snowmelt to local drinking water supplies. Unfortunately, climate change is increasing the risk associated with this water resource by changing the location, frequency and intensity of snowfall events. The ENVISNOW project was funded by the Fifth Framework Programme to improve our knowledge of and ability to predict snow parameters. During ENVISNOW, the Norwegian Water Resources and Energy Directorate (NVE) attempted to model the seasonal evolution of Snow Covered Area (SCA) and Snow Water Equivalent (SWE). They employed a rainfall-runoff model which they fed with precipitation and temperature data from the High Resolution Limited Area Model (HIRLAM). The model was run at high resolution (1km x 1km) for three large catchment areas in Norway. The hydrologists at NVE subsequently carried out a statistical analysis of the model output. They found high levels of skewness in the modelled SWE at the beginning of the snow season when accumulation dominates. The same was true at the end of the season when ablation eclipses accumulation, while in between skewness declined. NVE also learned that spatial variation in precipitation caused by changes in land coverage could strongly influence SCA. Specifically, alpine and forested areas adjacent to one another often presented dissimilar patterns of SCA. Finally, it should be noted that NVE's findings support the recent trend in snow modelling of treating SWE as a gamma distributed variable.
