## Materials and Methods
### Processes of Mass and Energy Transfer--PROMET Model Component  
For the retrieval of the spatially distributed snow information and forecast capabilities, the hydrological part of the coupled land surface process model PROMET [22] was chosen. It is a raster-based model that has been developed to spatially simulate the elements of the land surface water balance including vegetation, soil moisture, snow cover, reservoirs, and river discharge. PROMET incorporates a four-layer soil model and considers lateral flows along hill slopes. Due to its raster-based architecture, the model allows for the assimilation of remote sensing data for distributed hydrological applications [31]. PROMET solves the water and energy balance for hourly time steps and calculates the run-off of river basins, while it strictly conserves mass and energy. It thus allows for the validation of the complete process chain, from rainfall over soil-moisture dynamics to vegetation controlled evapotranspiration and finally routed run-off, against measured discharges on the basin and sub-basin scale. PROMET has successfully been applied for a variety of hydrological studies in medium-to large-sized watersheds [22; 31; 32; 33]. Required input data consist of raster-based GIS information, characterizing the spatial distribution of land use patterns, soil types and topographic features. In addition, parameters describing the characteristics of the soil and land use or crop categories are supplied through tabular input. For the application on the island of Newfoundland, we set up a basic model environment based on a freely available digital elevation model (DEM), from which the river network was automatically  
Figure 4: (**a**) Sentinel-1 IW mode composite for the Island of Newfoundland for 30 April 2017; (**b**) derived map of wet snow area (blue) from Sentinel-1 data. derived and lakes or reservoirs were inserted as structures. Land use information was derived from EO data sources (GlobCover), as soil map the Harmonized Soil Map of the World [34] is used. All spatial input data as well as the model grid itself have a resolution of 0.00833 degrees (<1 km\({}^{2}\)). The parameterization of the catchment characteristics followed the internal standardized procedure developed by VISTA, purely based on GIS and EO data. As the PROMET model is physically based, it does not require a calibration. Further fine-tuning of parameters would be possible, but were, however, not conducted due to missing information e.g., on reservoir management and limited validation data. PROMET can be driven by high resolution (1 h) time series of meteorological station network records, using the measured meteorological parameters. However, due to the specific characterization of our study area, only a sparse meteorological station network was available, which was not sufficient for our service target. Moreover, even in case of a sufficient number of meteorological stations, the amount of continuously provided information, e.g., on radiation and humidity or dew point are often missing or inaccurate. To overcome the lack of meteorological station data, we used global and regional climate model data as input, similar as presented by [PERSON] [35]. For the application in Newfoundland, we used data provided by Government of Canada as part of their High Resolution Deterministic Prediction System (HRDPS). This system is a set of nested limited-area model (LAM) forecast grids from the non-hydrostatic version of the Global Environmental Multiscale (GEM) model with a 2.5 km horizontal grid spacing. The fields in the HRDPS high resolution data set are made available as GRIB2 for four times a day for the Pan-Canadian domain for a 48-h forecast period [36]. Those data sets are consistent in temporal (1 h) and spatial (2.5 km) resolution. We adapted the import routines for the meteorology and selected the appropriate parameters for the model forcing to perform calculations of the snow and run-off situation with hourly temporal resolution.