A snow quality assessment tool based on new techniques and sámi knowledge (Snow4all)

Purpose and goal

Our aim is to develop a snow forecast tool. We innovatively combined the development and application of new scientific methods and techniques with indigenous Sámi knowledge. The information we provide support reindeer herding communities to adapt to effects of the rapidly changing climate. Snow forecasts are of interest also to the hydropower, transport and tourism sectors.

Expected results and effects

Forecast information on snow conditions will aid reindeer herders in decisions of how to best use their grazing resources and inform about the challenges arising when more land is planned to be exploited by energy production, mining and forestry due to the green transition. The results on snow density and layering can be further used to improve satellite-based estimates of snow water equivalent, which is an important parameter for hydropower reservoir management, avalanche risk and flood forecasting.

Planned approach and implementation

The strong cross-disciplinary science and technology team has expertise in climate change impacts, weather and snow monitoring, UAV platforms, snow and hydrological modelling, data assimilation, and remote sensing. The Sámi knowledge was crucial for this project. Empirical field data (from SITES and SMHI) was used to calibrate and validate a snowpack model and remotely sensed data by drones. A detailed dataset on the snow conditions for the Laevas reindeer herding community grazing area (2015-2021) was generated combining the models, observations and data assimilation tools.