C21F-04
Sensitivity of surface mass balance based on direct measurements made on four distinct French alpine glaciers over the last two decades, and melt models performances comparison.

Tuesday, 15 December 2015: 08:45
3009 (Moscone West)
Marion Reveillet, LGGE Laboratoire de Glaciologie et Géophysique de l’Environnement, Saint Martin d'Hères, France
Abstract:
Assessing the sensitivity of the surface mass balance of glaciers to climate variables is crucial in order to build numerical models and simulate accurately their future evolution. In this study, a large set of surface mass balance measurements made on four French alpine glaciers with distinctive features, over more than 20 years is used to investigate accumulation and ablation sensitivities. Results show that the temporal variability of accumulation is fairly well explained by the temporal variability of precipitation, with the spatial patterns of accumulation well reproduced from one year to another. Statistical analyses of the elevation, slope, curvature, Topographic Position Index (TPI), distance to a steep slope and to the next ridge are performed and show thatonly altitude plays a significant role on the spatial distribution of snow accumulation. Also, temporal variability of snow and ice ablation is mainly driven by temperature and the spatial variability of summer surface mass balance is largely explained by solar radiation. Based on these sensitivities, a simplified energy balance model issuggested and compared to other melt models. Models show a similar level of performance, but this performance is highly variable between glaciers. Two decades-long simulations using the simplified model proposed here and assuming a temporally stable temperature relationship show steady empirical parameters, thereby suggesting that a set of parameters calibrated over a short period of time can be used for long term melt modeling. We additionally tested the consistency of parameters between glaciers of the French Alps. The results of applying a set of parameters computed using data measurements over one glacier, to another, suggest a good transferability, with only a small decrease in the model performances.