Multi-Criteria Evaluation of Snowpack Simulations in Complex Alpine Terrain Using Satellite and In Situ Observations

Jesús Revuelto,Pascal Sirguey,Samuel Morin,Grégoire Lecourt,Matthieu Lafaysse,Antoine Rabatel,Vincent Vionnet,Thomas Condom,Alessandra Viani,Delphine Six,Luc Charrois,Marie Dumont,Isabella Zin

doi:10.3390/rs10081171

Abstract

This work presents an extensive evaluation of the Crocus snowpack model over a rugged and highly glacierized mountain catchment (Arve valley, Western Alps, France) from 1989 to 2015. The simulations were compared and evaluated using in-situ point snow depth measurements, in-situ seasonal and annual glacier surface mass balance, snow covered area evolution based on optical satellite imagery at 250 m resolution (MODIS sensor), and the annual equilibrium-line altitude of glaciers, derived from satellite images (Landsat, SPOT, and ASTER). The snowpack simulations were obtained using the Crocus snowpack model driven by the same, originally semi-distributed, meteorological forcing (SAFRAN) reanalysis using the native semi-distributed configuration, but also a fully distributed configuration. The semi-distributed approach addresses land surface simulations for discrete topographic classes characterized by elevation range, aspect, and slope. The distributed approach operates on a 250-m grid, enabling inclusion of terrain shadowing effects, based on the same original meteorological dataset. Despite the fact that the two simulations use the same snowpack model, being potentially subjected to same potential deviation from the parametrization of certain physical processes, the results showed that both approaches accurately reproduced the snowpack distribution over the study period. Slightly (although statistically significantly) better results were obtained by using the distributed approach. The evaluation of the snow cover area with MODIS sensor has shown, on average, a reduction of the Root Mean Squared Error (RMSE) from 15.2% with the semi-distributed approach to 12.6% with the distributed one. Similarly, surface glacier mass balance RMSE decreased from 1.475 m of water equivalent (W.E.) for the semi-distributed simulation to 1.375 m W.E. for the distribution. The improvement, observed with a much higher computational time, does not justify the recommendation of this approach for all applications; however, for simulations that require a precise representation of snowpack distribution, the distributed approach is suggested.

Highlights

The dynamics of the accumulation and melting of snow and ice in mountain areas has major effects on the timing and level of discharge from rivers in downstream areas
The snow depth evolution shows the ability of the SAFRAN–Crocus model chain to reproduce the temporal evolution of snow at these observation stations, taking into account their altitude and terrain shadowing masks, based on a meteorological analysis performed at the scale of the entire Mont-Blanc massif
Mainly coming from deviations on the forecasted snow precipitations amounts are neglected, we can conceive that the snow depth temporal evolution is well reproduced

Summary

Introduction

The dynamics of the accumulation and melting of snow and ice in mountain areas has major effects on the timing and level of discharge from rivers in downstream areas. One-sixth of the Earth’s population depends directly on the water supply from snow and ice melt in mountain areas [1]. Some of the most dangerous natural hazards in mountain areas are directly related to the distribution of the snowpack and ice, and their evolution over time. This is the case for snow avalanches [14], and floods in mountain rivers and downstream areas [15]. To enable anticipation of the occurrence of snow-related hazards and to reduce the threat to populations and infrastructure [16,17]; various models have been developed to reproduce and forecast the evolution of the snowpack on a daily or sub-daily basis

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Conclusion