Simon Gascoin

Centre d'Études Spatiales de la Biosphère

Author Statistics

Papers

Citation

H-Index

i-10 index

Research Trends

Author Order

Document Type

Co-Authors

César Deschamps‐Berger

Centre d'Études Spatiales de la Biosphère

Marie Dumont

Météo-France

ÉB

Étienne Berthier

Laboratoire d’Études en Géophysique et Océanographie Spatiales

Esteban Alonso‐González

Instituto Pirenaico de Ecología

Juan Ignacio López‐Moreno

Instituto Pirenaico de Ecología

Lahoucine Hanich

Cadi Ayyad University

Olivier Hagolle

Centre National d'Études Spatiales

Lionel Jarlan

Centre d'Études Spatiales de la Biosphère

Pascal Fanise

Centre d'Études Spatiales de la Biosphère

Christophe Kinnard

Université du Québec à Trois-Rivières

Cooperative Institutions

Centre National de la Recherche Scientifique

391

Institut de Recherche pour le Développement

222

Université de Toulouse

198

Université Toulouse III - Paul Sabatier

152

Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement

145

Centre d'Études Spatiales de la Biosphère

117

Université Grenoble Alpes

100

Météo-France

Centre National de Recherches Météorologiques

Centre National d'Études Spatiales

Author Statistics

Papers

Citation

H-Index

i-10 index

Research Field

Snow Dataset For Mount-Lebanon (2011-2016) - Beta

Zenodo (CERN European Organization for Nuclear Research) (2017)

Abbas Fayad Simon Gascoin Ghaleb Faour Pascal Fanise Laurent Drapeau

We present a comprehensive snow dataset for Mont-Lebanon. The dataset includes continuous meteorological observations from three high elevation automatic weather stations (AWS), snowpack field measurements collected at 30 different snow courses (elevation range 1300-2900 m a.s.l.), and post-processed MODIS snow products. Meteorological and snow observations are presented for the snow seasons (November-June) between 2011 and 2016 for Mzar (MZA, 2294 m a.s.l.), 2014-2016 for the Cedars (CED, 2834 m a.s.l.), and 2015-2016 for Laqlouq (LAQ, 1830 m a.s.l.). Meteorological and snow data includes snow depth, temperature, relative humidity, incoming and reflected solar radiation, wind speed and direction, and atmospheric pressure measured at 30-min interval. Snow depth, snow density, and snow water equivalent were measured at the 30 different snow courses during snow season 2015 and 2016 with an average revisit time of 11.4 days. Post-processed daily MODIS snow cover area (SCA) and snow cover duration (SCD) products are presented for the three snow dominated basins (Abou Ali, Ibrahim, and El Kelb) and cover the time period from 01 September 2011 to 31 August 2016. The current dataset is at doi:10.5281/zenodo.321405.

Mount

BETA (programming language)

10.5281/zenodo.291405

Cite

Citations (0)

Dependence of bare soil albedo on soil moisture on the moraine of the Zongo glacier (Bolivia): Implications for land surface modeling

Journal of Geophysical Research Atmospheres (2009)

Simon Gascoin Agnès Ducharne Pierre Ribstein Yves Lejeune Patrick Wagnon

Although the dependence of bare soil albedo on soil moisture is a familiar observation, it is not commonly represented in climate modeling. We investigate the impact of this dependence in a land surface model using meteorological data collected on the moraine of a Bolivian glacier. The relationship which is implemented to simulate albedo variations with soil moisture is deduced from a previous field study. The model is set up at the scale of the meteorological station plot to have the most accurate control on the model calibration and validation. A snow parameter is modified to account for the fact that the model was designed for larger cell sizes. Water content measurements are used to calibrate the parameter controlling the vertical water fluxes within the soil surface layer. This allows us to enhance the model's ability to capture the fast changes in surface soil moisture. The comparison of simulated ground heat flux and outgoing longwave radiations with observations shows that the model performs well despite the fact that all other parameters are set a priori on the basis of local properties of the surface. The results show that the dependence of bare soil albedo on soil moisture, which causes an increase in the net radiation, importantly influences the turbulent fluxes at the annual and monthly time scales. The mean annual evaporation is increased by 12%. As a consequence, this parameterization modifies the computed runoff, which is reduced by more than 5% during the rainy season.

Albedo (alchemy)

10.1029/2009jd011709

Cite

Citations (8)

Pleiades snow dataset from stereo-images

Zenodo (CERN European Organization for Nuclear Research) (2023)

Ange Haddjeri César Deschamps‐Berger Simon Gascoin

Snow depth satellite observation datasets made from Pleiades stereo-images, used in the evaluation of the SURFEX/Crocus/SnowPappus simulation system. Datasets are in the NETCDF4_CLASSIC format. The observed snow depth field is named 'DSN_T_ISBA' with a 250m horizontal resolution. Datasets projections are 'EPSG:2154' and is described in the Projection_Type field. Datasets are CF Compliant.

Pleiades

10.5281/zenodo.10037253

Cite

Citations (0)

Effect of Digital Elevation Model Resolution on the Simulation of the Snow Cover Evolution in the High Atlas

Water Resources Research (2019)

Mohamed Wassim Baba Simon Gascoin Christophe Kinnard Ahmed Marchane Lahoucine Hanich

Abstract The snow melt from the High Atlas represents a crucial water resource for crop irrigation in the semiarid regions of Morocco. Recent studies have used assimilation of snow cover area data from high‐resolution optical sensors to compute the snow water equivalent and snow melt in other mountain regions. These techniques however require large model ensembles, and therefore it is a challenge to determine the adequate model resolution that yields accurate results with reasonable computation time. Here we study the sensitivity of an energy balance model to the resolution of the model grid for a pilot catchment in the High Atlas. We used a time series of 8‐m resolution snow cover area maps with an average revisit time of 7.5 days to evaluate the model results. The digital elevation model was generated from Pléiades stereo images and resampled from 8 to 30, 90, 250, 500, and 1,000 m. The results indicate that the model performs well from 8 to 250 m but the agreement with observations drops at 500 m. This is because significant features of the topography were too smoothed out to properly characterize the spatial variability of meteorological forcing, including solar radiation. We conclude that a resolution of 250 m might be sufficient in this area. This result is consistent with the shape of the semivariogram of the topographic slope, suggesting that this semivariogram analysis could be used to transpose our conclusion to other study regions.

Elevation (ballistics)

Variogram

Snowmelt

10.1029/2018wr023789

Cite

Citations (62)

Snow depth and land surface cover in Tuolumne basin (California) from Pléiades images

Zenodo (CERN European Organization for Nuclear Research) (2020)

Deschamps-Berger César Simon Gascoin Étienne Berthier Amaury Dehecq

This dataset contains products calculated from Pléiades images. Details about the products are available in https://doi.org/10.5194/tc-2020-15. These products were used in Figure 4. - pleiades_elevation_difference_raw_winter_minus_summer.tif : raw difference of digital elevation models (DEMs) calculated from Pléiades stereo images. - pleiades_snow_depth_winter.tif : difference of DEMs on snow terrain only (where pleiades_land_surface_cover_winter.tif==1 with morphological erosion) - pleiades_land_surface_cover_winter.tif : land cover surface in the winter images (1= snow, 2=forest, 3= stable terrain, 4=water) - pleiades_land_surface_cover_summer.tif : land cover surface in the summer images (1= snow, 2=forest, 3= stable terrain, 4=water) - elevation_difference_style.qml : qgis style used for elevation difference and snow depth. - land_surface_cover_style.qml : qgis style used for land cover surface.

Land Cover

10.5281/zenodo.4013939

Cite

Citations (0)

Reply on RC2

Simon Gascoin

Abstract. The High Resolution Snow & Ice Monitoring Service was launched in 2020 to provide near-real-time, pan-European snow and ice information at 20 m resolution from Sentinel-2 observations. Here we present an evaluation of the snow detection using a database of snow depth observations from 1764 stations across Europe over the hydrological year 2016–2017. We find a good agreement between both datasets with an accuracy (proportion of correct classifications) of 94 % and kappa of 0.81. More accurate (+6 % kappa) retrievals are obtained by excluding low-quality pixels at the cost of a reduced coverage (−13 % data).

Kappa

10.5194/tc-2021-172-ac2

Cite

Citations (0)

Evaluation of high-resolution snowpack simulations from global datasets and comparison with Sentinel-1 snow depth retrievals in the Sierra Nevada, USA

Hydrology and earth system sciences (2025)

Laura Sourp Simon Gascoin Lionel Jarlan Vanessa Pedinotti K. J. Bormann

Abstract. The spatial distribution of mountain snow water equivalent (SWE) is key information for water management. We implement a tool to simulate snowpack properties at high resolution (100 m) by using only global datasets of meteorology, land cover and elevation. The meteorological data are obtained from ERA5, which makes the method applicable in near real time (5 d latency). We evaluate the output using 49 SWE maps derived from airborne lidar surveys in the Sierra Nevada. We find very good agreement at the catchment scale using uncalibrated lapse rates. Larger biases at the model grid scale are especially evident at high elevation but do not alter the catchment-scale snow mass accuracy. We additionally compare the simulated snow depth to Sentinel-1 retrievals and find a similar accuracy with respect to synchronous airborne lidar surveys. However, Sentinel-1 snow depth products are sparse and often masked during the melt season, whereas ERA5–SnowModel provides a spatially and temporally continuous SWE.

Snowpack

Water equivalent

10.5194/hess-29-597-2025

Cite

Citations (0)

Black carbon and dust alter the response of mountain snow cover under climate change

Nature Communications (2022)

Marion Réveillet Marie Dumont Simon Gascoin Matthieu Lafaysse Pierre Nabat

Abstract By darkening the snow surface, mineral dust and black carbon (BC) deposition enhances snowmelt and triggers numerous feedbacks. Assessments of their long-term impact at the regional scale are still largely missing despite the environmental and socio-economic implications of snow cover changes. Here we show, using numerical simulations, that dust and BC deposition advanced snowmelt by 17 ± 6 days on average in the French Alps and the Pyrenees over the 1979–2018 period. BC and dust also advanced by 10-15 days the peak melt water runoff, a substantial effect on the timing of water resources availability. We also demonstrate that the decrease in BC deposition since the 1980s moderates the impact of current warming on snow cover decline. Hence, accounting for changes in light-absorbing particles deposition is required to improve the accuracy of snow cover reanalyses and climate projections, that are crucial for better understanding the past and future evolution of mountain social-ecological systems.

Snowmelt

Deposition

Mineral dust

Meltwater

Global Change

10.1038/s41467-022-32501-y

Cite

Citations (58)

List of contributors

Elsevier eBooks (2020)

Nassim Aït-Mouheb Clément Albergel Antoine Allam Jalel Aouissi Nicolas Baghdadi

10.1016/b978-0-12-818086-0.09994-5

Cite

Citations (0)

Role of Saharan dust and black carbon deposition on snow cover in the French mountain ranges over the last 39 years.

Marion Réveillet Marie Dumont Simon Gascoin Pierre Nabat Matthieu Lafaysse

Light absorbing particles such as black carbon(BC) or mineral dust are known to darken the snow surface when deposited on the snow cover and amplify several snow-albedo feedbacks, drastically modifying the snowpack evolution and the snow cover duration. Mineral dust deposition on snow is generally more variablein time than black carbon deposition and can exhibit both a high inter and intra annual variability. In France, the Alps and the Pyrenees mountain ranges are affected by large dust deposition events originating from the Sahara . The aim of this study is to quantify the impact of these impurities on the snow cover variability over the last 39 years (1979-2018).For that purpose, the detailed snowpack model Crocus with an explicit representation of impurities is forced by SAFRAN meteorological reanalysis and a downscaling of the simulated deposition fluxes from a regional climate model (ALADIN-Climate). Different simulations are performed: (i) considering dust and/or BC (i.e. explicit representation), (ii) without impurities and (iii) considering an implicit representation (i.e. empirical parameterization based on a decreasing law of the albebo with snow age).Simulations are compared at point scale to the snow depth measured at more than 200 Meteo-France&#8217;s stations in each massif, and spatially evaluated over the 2000-2018 period in comparing thesnow cover area, snow cover duration and the Jacard index to MODIS snow products. Scores are generally better when considering the explicit representation of the impurities than when using the snow age as a proxy for light absorbing particles content.Results indicate that dust and BC have a significant impact on the snow cover duration with strong variations in the magnitude of the impact from one year to another and from one location to another.We also investigate the contribution of light absorbing particles depositionto snow cover inter-annual variability based on statistical approaches.

Snowpack

Deposition

Albedo (alchemy)

Mineral dust

10.5194/egusphere-egu2020-15209

Cite

Citations (0)