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Discussion papers
https://doi.org/10.5194/tc-2019-31
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-2019-31
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 28 Feb 2019

Submitted as: research article | 28 Feb 2019

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This discussion paper is a preprint. A revision of this manuscript was accepted for the journal The Cryosphere (TC) and is expected to appear here in due course.

Uncertainties in the spatial distribution of snow sublimation in the semi-arid Andes of Chile

Marion Réveillet1, Shelley MacDonell1, Simon Gascoin2, Christophe Kinnard3, Stef Lhermitte4, and Nicole Schaffer1 Marion Réveillet et al.
  • 1Centro de Estudios Avanzados en Zonas Áridas (CEAZA), ULS-Campus Andrés Bello, Raúl Britan 1305, La Serena, Chile
  • 2Centre d'Etudes Spatiales de la Biosphère (CESBIO), Université de Toulouse, CNRS/CNES/IRD/INRA/UPS, 31400 Toulouse, France
  • 3Département des Sciences de l'Environnement, Université du Québec à Trois-Rivières, 3351 Boul. des Forges, Trois-Rivières, QC, G9A5H7, Canada
  • 4Department of Geoscience & Remote Sensing, Delft University of Technology, Delft, The Netherlands

Abstract. In the semi-arid Andes of Chile, farmers and industry in the cordillera lowlands depend on water from snowmelt, as annual rainfall is insufficient to meet their needs. Despite the importance of snow cover for water resources in this region, understanding of snow depth distribution and snow mass balance is limited. Whilst the effect of wind on snow cover pattern distribution has been assessed, the relative importance of melt versus sublimation has only been studied at the point-scale over one catchment. Analyzing relative ablation rates and evaluating uncertainties are critical for understanding snow depth sensitivity to variations in climate and simulating the evolution of the snow pack over a larger area and over time. Using a distributed snowpack model (SnowModel), this study aims to simulate melt and sublimation rates over the instrumented watershed of La Laguna (3150–5630 m above sea level, 30° S), during two hydrologically contrasted years. The model is calibrated and forced with meteorological data from nine Automatic Weather Stations (AWS) located in the watershed, and atmospheric simulation outputs from the Weather Research and Forecasting (WRF) model. Results of simulations indicate first a large uncertainty in sublimation ratios depending on the forcing. The melt/sublimation ratios increased by 100 % if forced with WRF compared to AWS data due to the cold bias and precipitation over-estimation observed in WRF output in this region. Second, the simulations indicate similar sublimation ratios for both years, but ratios vary with elevation with a relative increase in melt at higher elevations. Finally results indicate that snow persistence has a significant impact on the sublimation ratio due to higher melt rates.

Marion Réveillet et al.
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Marion Réveillet et al.
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