Surface mass balance of glaciers in the French Alps: distributed modeling and sensitivity to climate change

Gerbaux, M.; Genthon, Christophe; Etchevers, Pierre; Vincent, Christian; Dedieu, Jean Pierre

doi:10.3189/172756505781829133

Cited by 100 publications

(119 citation statements)

References 34 publications

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“…Considering only fully snowcovered pixels further permitted to ignore the compounded effects arising from the mixture of spectral responses and bi-directional reflectance of different targets. The sub-pixel snow cover fraction was determined based on its linear relationship with the Normalized Difference Snow Index (NDSI) after the atmospheric and topographic corrections (Salomonson and Appel, 2006;Hall and Riggs, 2007). Thus, all nonshaded pixels whose NDSI was larger than 0.7 were considered to be fully covered.…”

Section: Retrieval Methods Based On Look-up Tables Built Using Disortmentioning

confidence: 99%

“…Durand et al, 1999;Bellaire et al, 2011), mountain hydrology (e.g. Braun et al, 1994;Magnusson et al, 2011) and glacier mass balance (Obleitner and Lehning, 2004;Gerbaux et al, 2005). However, there have been few examples of direct assimilation of satellite data into models of such a degree of complexity (Toure et al, 2011).…”

Section: A Mary Et Al: Mountain Snow Ssa From Modismentioning

confidence: 99%

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Intercomparison of retrieval algorithms for the specific surface area of snow from near-infrared satellite data in mountainous terrain, and comparison with the output of a semi-distributed snowpack model

Mary¹,

Dumont

Dedieu

et al. 2013

The Cryosphere

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Abstract. This study compares different methods to retrieve the specific surface area (SSA) of snow from satellite radiance measurements in mountainous terrain. It aims at addressing the effect on the retrieval of topographic corrections of reflectance, namely slope and aspect of terrain, multiple reflections on neighbouring slopes and accounting (or not) for the anisotropy of snow reflectance. Using MODerate resolution Imaging Spectrometer (MODIS) data for six different clear sky scenes spanning a wide range of snow conditions during the winter season 2008-2009 over a domain of 46 × 50 km in the French Alps, we compared SSA retrievals with and without topographic correction, with a spherical or non-spherical snow reflectance model and, in spherical case, with or without anisotropy corrections. The retrieved SSA values were compared to field measurements and to the results of the detailed snowpack model Crocus, fed by driving data from the SAFRAN meteorological analysis. It was found that the difference in terms of surface SSA between retrieved values and SAFRAN-Crocus output was minimal when the topographic correction was taken into account, when using a retrieval method assuming disconnected spherical snow grains. In this case, the root mean square deviation was 9.4 m 2 kg −1 and the mean difference was 0.1 m 2 kg −1 , based on 3170 pairs of observation and simulated values. The added-value of the anisotropy correction was not significant in our case, which may be explained by the presence of mixed pixels and surface roughness. MODIS retrieved data show SSA variations with elevation and aspect which are physically consistent and in good agreement with SAFRAN-Crocus outputs. The variability of the MODIS retrieved SSA within the topographic classes of the model was found to be relatively small (3.9 m 2 kg −1 ). This indicates that semi-distributed snowpack simulations in mountainous terrain with a sufficiently large number of classes provides a representation of the snowpack variability consistent with the scale of MODIS 500 m pixels.

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Section: Retrieval Methods Based On Look-up Tables Built Using Disortmentioning

confidence: 99%

Section: A Mary Et Al: Mountain Snow Ssa From Modismentioning

confidence: 99%

Intercomparison of retrieval algorithms for the specific surface area of snow from near-infrared satellite data in mountainous terrain, and comparison with the output of a semi-distributed snowpack model

Mary¹,

Dumont

Dedieu

et al. 2013

The Cryosphere

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show abstract

“…yr −1 for snow accumulation and from 0.1 to 0.4 m w.e. yr −1 for ablation (Cogley and Adams, 1998;Gerbaux et al, 2005;Thibert et al, 2008;Huss et al, 2009). Additional errors stem from the spatial integration procedure and from the glacier hypsometry changing over time .…”

Section: Direct Mass Balance Measurementsmentioning

confidence: 99%

Decay of a long-term monitored glacier: Careser Glacier (Ortles-Cevedale, European Alps)

et al. 2013

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Abstract. The continuation of valuable, long-term glacier observation series is threatened by the accelerated mass loss which currently affects a large portion of so-called "benchmark" glaciers. In this work we present the evolution of the Careser Glacier, from the beginning of systematic observation at the end of the 19th century to its current condition in 2012. In addition to having one of the longest and richest observation records among the Italian glaciers, Careser is unique in the Italian Alps for its 46 yr mass balance series that started in 1967. In the present study, variations in the length, area and volume of the glacier since 1897 are examined, updating and validating the series of direct mass balance observations and adding to the mass balance record into the past using the geodetic method. The glacier is currently strongly out of balance and in rapid decay; its average mass loss rate over the last 3 decades was 1.5 m water equivalent per year, increasing to 2.0 m water equivalent per year in the last decade. Although these rates are not representative at a regional scale, year-to-year variations in mass balance show an unexpected increase in correlation with other glaciers in the Alps, during the last 3 decades. If mass loss continues at this pace, the glacier will disappear within a few decades, putting an end to this unique observation series.

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“…Following this line, there have been increasing efforts to quantify the parametric and predictive uncertainty of mass-and energy-balance models (e.g. Franz et al, 2010;He et al, 2011;Schmucki et al, 2014;Gurgiser et al, 2013;Gerbaux et al, 2005;Fujita, 2008;Radić and Hock, 2006;Greuell and Oerlemans, 1986;Oerlemans, 1992;Braithwaite and Zhang, 2000). Some of these also consider the investigation of effects on the energy and mass balance of glaciers or ice sheets (e.g.…”

mentioning

confidence: 99%

Assessing the uncertainty of glacier mass-balance simulations in the European Arctic based on variance decomposition

Sauter

Obleitner

2015

Geosci. Model Dev.

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Abstract. State-of-the-art numerical snowpack models essentially rely on observational data for initialization, forcing, parametrization, and validation. Such data are available in increasing amounts, but the propagation of related uncertainties in simulation results has received rather limited attention so far. Depending on their complexity, even small errors can have a profound effect on simulations, which dilutes our confidence in the results. This paper aims at quantification of the overall and fractional contributions of some archetypical measurement uncertainties on snowpack simulations in arctic environments. The sensitivity pattern is studied at two sites representing the accumulation and ablation area of the Kongsvegen glacier (Svalbard), using the snowpack scheme Crocus. The contribution of measurement errors on model output variance, either alone or by interaction, is decomposed using global sensitivity analysis. This allows one to investigate the temporal evolution of the fractional contribution of different factors on key model output metrics, which provides a more detailed understanding of the model's sensitivity pattern. The analysis demonstrates that the specified uncertainties in precipitation and long-wave radiation forcings had a strong influence on the calculated surfaceheight changes and surface-energy balance components. The model output sensitivity patterns also revealed some characteristic seasonal imprints. For example, uncertainties in longwave radiation affect the calculated surface-energy balance throughout the year at both study sites, while precipitation exerted the most influence during the winter and at the upper site. Such findings are valuable for identifying critical parameters and improving their measurement; correspondingly, updated simulations may shed new light on the confidence of results from snow or glacier mass-and energy-balance models. This is relevant for many applications, for example in the fields of avalanche and hydrological forecasting.

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Surface mass balance of glaciers in the French Alps: distributed modeling and sensitivity to climate change

Cited by 100 publications

References 34 publications

Intercomparison of retrieval algorithms for the specific surface area of snow from near-infrared satellite data in mountainous terrain, and comparison with the output of a semi-distributed snowpack model

Intercomparison of retrieval algorithms for the specific surface area of snow from near-infrared satellite data in mountainous terrain, and comparison with the output of a semi-distributed snowpack model

Decay of a long-term monitored glacier: Careser Glacier (Ortles-Cevedale, European Alps)

Assessing the uncertainty of glacier mass-balance simulations in the European Arctic based on variance decomposition

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