Autor: |
Vionnet, V., Fortin, V., Dominé, F., Royer, A., Mazzotti, G., Woolley, G., Abrahamowicz, M., Lafaysse, M., Rutter, N., Wake, L., Derksen, C., Bélair, S. |
Jazyk: |
angličtina |
Rok vydání: |
2023 |
Zdroj: |
XXVIII General Assembly of the International Union of Geodesy and Geophysics (IUGG) |
Popis: |
The current development of spaceborne missions to retrieve snow water equivalent requires state-of-the-art modelling systems able to provide accurate estimation of snowpack properties across large areas with contrasted climate and vegetation. In the context of the Terrestrial Snow Mass Mission under development at the Canadian Space Agency, the detailed snowpack model Crocus has been implemented in the Soil Vegetation and Snow (SVS) model. For each grid cell, SVS simulates the snowpack evolution (i) over ground without standing vegetation, (ii) in shrub vegetation and (iii) below trees. For each tile, the model includes the representation of the main snow/vegetation interaction processes. In this study, the ability of SVS/Crocus to simulate snowpack properties is tested along a 4000-km latitudinal transect (47°N to 83°N) in northeastern Canada covering a transition from the boreal forest to arctic ecosystems. Crocus is run at 10-km resolution along this transect over a 13-year period (2007-2019) driven by a meteorological reanalysis recently developed at Environment and Climate Change Canada. A unique dataset of detailed snowpits at multiple sites along the transect is used to evaluate the ability of the model to simulate snowpack properties (SWE, depth-hoar fraction, density and SSA profiles). Results highlight the sensitivity of model results to key physical processes (wind-induced compaction, effect of basal vegetation). Systematic errors were found in snowpack properties and may be explained by missing physical processes in the model such as water vapour fluxes. This work constitutes the first step towards the development of a new pan-Canadian snow modelling system. |
Databáze: |
OpenAIRE |
Externí odkaz: |
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