Assessing Factorial Snow Model 2.0 Performance in Forest Terrain - With Experimental Sub-Canopy Micro-Meteorological Observations
Examensarbete för masterexamen
This thesis is assessing the snow model FSM 2.0 in predictions of snow dynamics in forest terrain. Two versions of the model have been used. One with default settings and another with alternative local parameterizations of canopy characteristic for input data. Experimental data acquisition was conducted in sub-alpine forest terrain, during the 2019 snow season, Landwasser Valley of Graubunden Canton in Switzerland. Site locations were selected to cover dense and canopy gap structures. Processing and analyzing of field data was done in parallel to the field work. Observed data proves the significance of implementing local parameters in forest snow modeling. Results from the FSM 2.0 assessment show that using local canopy characteristics for the site characteristics input data, improves model predictions for incoming longwave radiaton for both dense and canopy gap sites. It also clearly improves incoming shortwave radiation for dense sites, and makes a fair prediction for canopy gap sites.
Snow Hydrology , Snow model , forest snow , snow dynamics , snow in forest , sub-canopy meteorological data , Snow Energy Balance , canopy characteristics , LiDAR , small scale canopy parameters