Hydrological impact of the new ECMWF multi-Layer snow scheme

Zsoter, E., Arduini, G., Prudhomme, C., Stephens, E. ORCID: https://orcid.org/0000-0002-5439-7563 and Cloke, H. ORCID: https://orcid.org/0000-0002-1472-868X (2022) Hydrological impact of the new ECMWF multi-Layer snow scheme. Atmosphere, 13 (5). 727. ISSN 2073-4433 doi: 10.3390/atmos13050727

Abstract/Summary

The representation of snow is a crucial aspect of land-surface modelling, as it has a strong influence on energy and water balances. Snow schemes with multiple layers have been shown to better de-scribe the snowpack evolution and bring improvements to soil freezing and some hydrological processes. In this paper, the wider hydrological impact of the multi-layer snow scheme, implemented in the ECLand model, was analyzed globally on hundreds of catchments. ERA5-forced reanalysis simulations of ECLand were coupled to CaMa-Flood, as the hydrodynamic model to produce river discharge. Different sensitivity experiments were conducted to evaluate the impact of the ECLand snow and soil freezing scheme changes on the terrestrial hydrological processes, with particular focus on permafrost. It was found that the default multi-layer snow scheme can generally improve the river discharge simulation, with the exception of permafrost catchments, where snowmelt-driven floods are largely underestimated, due to the lack of surface runoff. It was also found that appropriate changes in the snow vertical discretization, destructive metamorphism, snow-soil thermal conductivity and soil freeze temperature could lead to large river discharge improvements in permafrost by adjusting the evolution of soil temperature, infiltration and the partitioning between surface and subsurface runoff.

Item Type	Article
URI	https://reading-clone.eprints-hosting.org/id/eprint/105034
Item Type	Article
Refereed	Yes
Divisions	Science > School of Archaeology, Geography and Environmental Science > Department of Geography and Environmental Science Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
Publisher	MDPI
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