scholarly journals Twentieth century temperature and snow cover changes in the French Alps

2021 ◽  
Vol 21 (4) ◽  
Author(s):  
Julien Beaumet ◽  
Martin Ménégoz ◽  
Samuel Morin ◽  
Hubert Gallée ◽  
Xavier Fettweis ◽  
...  
Keyword(s):  
Twentieth Century ◽  
Mass Balance ◽  
Snow Cover ◽  
Snow Water Equivalent ◽  
Climate Model ◽  
Glacier Mass Balance ◽  
European Alps ◽  
French Alps ◽  
Snow Cover Duration ◽  
High Elevations

AbstractChanges in snow cover associated with the warming of the French Alps greatly influence social-ecological systems through their impact on water resources, mountain ecosystems, economic activities, and glacier mass balance. In this study, we investigated trends in snow cover and temperature over the twentieth century using climate model and reanalysis data. The evolution of temperature, precipitation and snow cover in the European Alps has been simulated with the Modèle Atmospherique Régional (MAR) applied with a 7-km horizontal resolution and driven by ERA-20C (1902-2010) and ERA5 (1981–2018) reanalyses data. Snow cover duration and snow water equivalent (SWE) simulated with MAR are compared to the SAFRAN - SURFEX-ISBA-Crocus - MEPRA meteorological and snow cover reanalysis (S2M) data across the French Alps (1958–2018) and in situ glacier mass balance measurements. MAR outputs provide a realistic distribution of SWE and snow cover duration as a function of elevation in the French Alps. Large disagreements are found between the datasets in terms of absolute warming trends over the second part of the twentieth century. MAR and S2M trends are in relatively good agreement for the decrease in snow cover duration, with higher decreases at low elevation ($\sim $ ∼ 5–10%/decade). Consistent with other studies, the highest warming rates in MAR occur at low elevations (< 1000 m a.s.l) in winter, whereas they are found at high elevations (> 2000 m a.s.l) in summer. In spring, warming trends show a maximum at intermediate elevations (1500 to 1800 m). Our results suggest that higher warming at these elevations is mostly linked to the snow-albedo feedback in spring and summer caused by the disappearance of snow cover at higher elevation during these seasons. This work has evidenced that depending on the season and the period considered, enhanced warming at higher elevations may or may not be found. Additional analysis in a physically comprehensive way and more high-quality dataset, especially at high elevations, are still required to better constrain and quantify climate change impacts in the Alps and its relation to elevation.

scholarly journals Contrasting seasonal changes in temperature, precipitation and snow cover simulated over the European Alps during the twentieth century

2021 ◽  
Author(s):  
Martin Ménégoz ◽  
Julien Beaumet ◽  
Hubert Gallée ◽  
Xavier Fettweis ◽  
Samuel Morin ◽  
...  
Keyword(s):  
Snow Cover ◽  
Snow Water Equivalent ◽  
Climate Model ◽  
Decadal Variability ◽  
Regional Climate ◽  
Horizontal Resolution ◽  
Glacier Mass Balance ◽  
European Alps ◽  
Climate Trends ◽  
The Alps

&lt;p&gt;The evolution of temperature, precipitation and snow cover in the European Alps have been simulated with the regional climate model MAR applied with a 7 kilometre horizontal resolution and driven by the ERA-20C (1902-2010) and the ERA5 reanalyses (1981-2018). A comparison with observational datasets, including French and Swiss local meteorological stations, in-situ glacier mass balance measurements and reanalysis product demonstrates high model skill for snow cover duration and snow water equivalent (SWE) as well as for the climatology and the inter-annual variability of both temperature and precipitation. The relatively high resolution allows to estimate the meteorological variables up to 3000m.a.s.l. The vertical gradient of precipitation simulated by MAR over the European Alps reaches 33% km-1 (1.21 mmd-1.km-1) in summer and 38%km-1 (1.15mmd mmd-1.km-1) in winter, on average over 1971&amp;#8211;2008 and shows a large spatial variability. This study evidences seasonal and altitudinal contrasts of climate trends over the Alps. A significant (pvalue&lt; 0.05) increase in mean winter precipitation is simulated in the northwestern Alps over 1903&amp;#8211;2010, with changes typically reaching 20% to 40% per century, a signal strongly modulated by multi-decadal variability during the second part of the century. A general drying is found in summer over the same period, exceeding 20% to 30% per century in the western plains and 40% to 50% per century in the southern plains surrounding the Alps but remaining smaller (&lt;10%) and not significant above 1500ma.s.l. Over 1903&amp;#8211;2010, the maximum of daily precipitation (Rx1day) shows a general and significant increase at the annual timescale and also during the four seasons, reaching local values between 20% and 40% per century over large parts of the Alps and the Apennines. Trends of Rx1day are significant (pvalue&lt;0.05) only when considering long time series, typically 50 to 80 years depending on the area considered. Some of these trends are nonetheless significant when computed over 1970&amp;#8211;2010, suggesting a recent acceleration of the increase in extreme precipitation. Rx1day increase occurs where the annual correlation between temperature and intense precipitation is high. The highest warming rates in MAR are found at low elevations (&lt; 1000 m a.s.l) in winter, whereas they are found at high elevations (&gt; 2000 m a.s.l) in summer. In spring, warming trends show a maximum at intermediate elevations (1500 m to 1800 m). Our results suggest that higher warming at these elevations is mostly linked with the snow-albedo feedback in spring and summer.&lt;/p&gt;

scholarly journals Statistical adaptation of ALADIN RCM outputs over the French Alps – application to future climate and snow cover

2012 ◽  
Vol 6 (4) ◽  
pp. 785-805 ◽  
Author(s):  
M. Rousselot ◽  
Y. Durand ◽  
G. Giraud ◽  
L. Mérindol ◽  
I. Dombrowski-Etchevers ◽  
...  
Keyword(s):  
Snow Cover ◽  
Snow Water Equivalent ◽  
Climate Model ◽  
Regional Climate ◽  
Control Period ◽  
Shortwave Radiation ◽  
Change Scenario ◽  
Analysis Model ◽  
French Alps ◽  
Snow Model

Abstract. In this study, snowpack scenarios are modelled across the French Alps using dynamically downscaled variables from the ALADIN Regional Climate Model (RCM) for the control period (1961–1990) and three emission scenarios (SRES B1, A1B and A2) for the mid- and late 21st century (2021–2050 and 2071–2100). These variables are statistically adapted to the different elevations, aspects and slopes of the Alpine massifs. For this purpose, we use a simple analogue criterion with ERA40 series as well as an existing detailed climatology of the French Alps (Durand et al., 2009a) that provides complete meteorological fields from the SAFRAN analysis model. The resulting scenarios of precipitation, temperature, wind, cloudiness, longwave and shortwave radiation, and humidity are used to run the physical snow model CROCUS and simulate snowpack evolution over the massifs studied. The seasonal and regional characteristics of the simulated climate and snow cover changes are explored, as is the influence of the scenarios on these changes. Preliminary results suggest that the snow water equivalent (SWE) of the snowpack will decrease dramatically in the next century, especially in the Southern and Extreme Southern parts of the Alps. This decrease seems to result primarily from a general warming throughout the year, and possibly a deficit of precipitation in the autumn. The magnitude of the snow cover decline follows a marked altitudinal gradient, with the highest altitudes being less exposed to climate change. Scenario A2, with its high concentrations of greenhouse gases, results in a SWE reduction roughly twice as large as in the low-emission scenario B1 by the end of the century. This study needs to be completed using simulations from other RCMs, since a multi-model approach is essential for uncertainty analysis.

scholarly journals Statistical adaptation of ALADIN RCM outputs over the French alpine massifs – application to future climate and snow cover

2012 ◽  
Vol 6 (1) ◽  
pp. 171-210 ◽  
Author(s):  
M. Rousselot ◽  
Y. Durand ◽  
G. Giraud ◽  
L. Mérindol ◽  
I. Dombrowski-Etchevers ◽  
...  
Keyword(s):  
Snow Cover ◽  
Snow Water Equivalent ◽  
Climate Model ◽  
Regional Climate ◽  
Control Period ◽  
Shortwave Radiation ◽  
Change Scenario ◽  
Analysis Model ◽  
French Alps ◽  
Snow Model

Abstract. In this study, snowpack scenarios are modelled across the French Alps using dynamically downscaled variables from the ALADIN Regional Climate Model (RCM) for the control period (1961–1990) and three emission scenarios (SRES B1, A1B and A2) by the mid- and late of the 21st century (2021–2050 and 2071–2100). These variables are statistically adapted to the different elevations, aspects and slopes of the alpine massifs. For this purpose, we use a simple analogue criterion with ERA40 series as well as an existing detailed climatology of the French Alps (Durand et al., 2009a) that provides complete meteorological fields from the SAFRAN analysis model. The resulting scenarios of precipitation, temperature, wind, cloudiness, longwave and shortwave radiation, and humidity are used to run the physical snow model CROCUS and simulate snowpack evolution over the massifs studied. The seasonal and regional characteristics of the simulated climate and snow cover changes are explored, as is the influence of the scenarios on these changes. Preliminary results suggest that the Snow Water Equivalent (SWE) of the snowpack will decrease dramatically in the next century, especially in the Southern and Extreme Southern part of the Alps. This decrease seems to result primarily from a general warming throughout the year, and possibly a deficit of precipitation in the autumn. The magnitude of the snow cover decline follows a marked altitudinal gradient, with the highest altitudes being less exposed to climate change. Scenario A2, with its high concentrations of greenhouse gases, results in a SWE reduction roughly twice as large as in the low-emission scenario B1 by the end of the century. This study needs to be completed using simulations from other RCMs, since a multi-model approach is essential for uncertainty analysis.

scholarly journals Contrasting seasonal changes in total and intense precipitation in the European Alps from 1903 to 2010

2020 ◽  
Author(s):  
Martin Ménégoz ◽  
Evgenia Valla ◽  
Nicolas C. Jourdain ◽  
Juliette Blanchet ◽  
Julien Beaumet ◽  
...  
Keyword(s):  
High Resolution ◽  
Spatial Variability ◽  
Seasonal Changes ◽  
Seasonal Cycle ◽  
Climate Model ◽  
Regional Climate ◽  
Vertical Gradient ◽  
P Value ◽  
European Alps ◽  
High Elevations

Abstract. Changes of precipitation over the European Alps are investigated with the regional climate model MAR applied with a 7-km resolution over the period 1903–2010 using the reanalysis ERA-20C as forcing. A comparison with several observational datasets demonstrates that the model is able to reproduce the climatology as well as both the inter-annual variability and the seasonal cycle of precipitation over the European Alps. The relatively high resolution allows to estimate precipitation at high elevations. The vertical gradient of precipitation simulated by MAR over the European Alps reaches 33 % km−1 (1.21 mm.day−1.km−1) in summer and 38 % km−1 (1.15 mm.day−1.km−1) in winter, on average over 1971–2008 and shows a large spatial variability. A significant (p-value 

scholarly journals A snow cover climatology for the Pyrenees from MODIS snow products

2014 ◽  
Vol 11 (11) ◽  
pp. 12531-12571 ◽  
Author(s):  
S. Gascoin ◽  
O. Hagolle ◽  
M. Huc ◽  
L. Jarlan ◽  
J.-F. Dejoux ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Snow Cover ◽  
Snow Water Equivalent ◽  
Remote Sensing Data ◽  
Landsat Images ◽  
Forested Areas ◽  
Land Cover Map ◽  
Hydropower Production ◽  
Snow Cover Duration

Abstract. The seasonal snow in the Pyrenees is critical for hydropower production, crop irrigation and tourism in France, Spain and Andorra. Complementary to in situ observations, satellite remote sensing is useful to monitor the effect of climate on the snow dynamics. The MODIS daily snow products (Terra/MOD10A1 and Aqua/MYD10A1) are widely used to generate snow cover climatologies, yet it is preferable to assess their accuracies prior to their use. Here, we use both in situ snow observations and remote sensing data to evaluate the MODIS snow products in the Pyrenees. First, we compare the MODIS products to in situ snow depth (SD) and snow water equivalent (SWE) measurements. We estimate the values of the SWE and SD best detection thresholds to 40 mm water equivalent (we) and 105 mm respectively, for both MOD10A1 and MYD10A1. Kappa coefficients are within 0.74 and 0.92 depending on the product and the variable. Then, a set of Landsat images is used to validate MOD10A1 and MYD10A1 for 157 dates between 2002 and 2010. The resulting accuracies are 97% (κ = 0.85) for MOD10A1 and 96% (κ = 0.81) for MYD10A1, which indicates a good agreement between both datasets. The effect of vegetation on the results is analyzed by filtering the forested areas using a land cover map. As expected, the accuracies decreases over the forests but the agreement remains acceptable (MOD10A1: 96%, κ = 0.77; MYD10A1: 95%, κ = 0.67). We conclude that MODIS snow products have a sufficient accuracy for hydroclimate studies at the scale of the Pyrenees range. Using a gapfilling algorithm we generate a consistent snow cover climatology, which allows us to compute the mean monthly snow cover duration per elevation band. We finally analyze the snow patterns for the atypical winter 2011–2012. Snow cover duration anomalies reveal a deficient snowpack on the Spanish side of the Pyrenees, which seems to have caused a drop in the national hydropower production.

scholarly journals Evaluation of CLASS Snow Simulation over Eastern Canada

2017 ◽  
Vol 18 (5) ◽  
pp. 1205-1225 ◽  
Author(s):  
Diana Verseghy ◽  
Ross Brown ◽  
Libo Wang
Keyword(s):  
Snow Cover ◽  
Land Surface ◽  
Snow Water Equivalent ◽  
Climate Model ◽  
Regional Climate ◽  
Eastern Canada ◽  
Fractional Snow Cover ◽  
Forest Regions ◽  
Snow Water ◽  
Snow Model

Abstract The Canadian Land Surface Scheme (CLASS), version 3.6.1, was run offline for the period 1990–2011 over a domain centered on eastern Canada, driven by atmospheric forcing data dynamically downscaled from ERA-Interim using the Canadian Regional Climate Model. The precipitation inputs were adjusted to replicate the monthly average precipitation reported in the CRU observational database. The simulated fractional snow cover and the surface albedo were evaluated using NOAA Interactive Multisensor Snow and Ice Mapping System and MODIS data, and the snow water equivalent was evaluated using CMC, Global Snow Monitoring for Climate Research (GlobSnow), and Hydro-Québec products. The modeled fractional snow cover agreed well with the observational estimates. The albedo of snow-covered areas showed a bias of up to −0.15 in boreal forest regions, owing to neglect of subgrid-scale lakes in the simulation. In June, conversely, there was a positive albedo bias in the remaining snow-covered areas, likely caused by neglect of impurities in the snow. The validation of the snow water equivalent was complicated by the fact that the three observation-based datasets differed widely. Also, the downward adjustment of the forcing precipitation clearly resulted in a low snow bias in some regions. However, where the density of the observations was high, the CLASS snow model was deemed to have performed well. Sensitivity tests confirmed the satisfactory behavior of the current parameterizations of snow thermal conductivity, snow albedo refreshment threshold, and limiting snow depth and underlined the importance of snow interception by vegetation. Overall, the study demonstrated the necessity of using a wide variety of observation-based datasets for model validation.

scholarly journals Future Climate Change and Its Impact on Runoff Generation from the Debris-Covered Inylchek Glaciers, Central Tian Shan, Kyrgyzstan

Water ◽  
2018 ◽  
Vol 10 (11) ◽  
pp. 1513 ◽  
Author(s):  
Wilfried Hagg ◽  
Elisabeth Mayr ◽  
Birgit Mannig ◽  
Mark Reyers ◽  
David Schubert ◽  
...  
Keyword(s):  
Mass Balance ◽  
Hydrological Model ◽  
Climate Model ◽  
Global Climate Model ◽  
Future Climate ◽  
Fine Tuning ◽  
Future Climate Change ◽  
Tarim River ◽  
Glacier Mass Balance ◽  
Tian Shan

The heavily debris-covered Inylchek glaciers in the central Tian Shan are the largest glacier system in the Tarim catchment. It is assumed that almost 50% of the discharge of Tarim River are provided by glaciers. For this reason, climatic changes, and thus changes in glacier mass balance and glacier discharge are of high impact for the whole region. In this study, a conceptual hydrological model able to incorporate discharge from debris-covered glacier areas is presented. To simulate glacier melt and subsequent runoff in the past (1970/1971–1999/2000) and future (2070/2071–2099/2100), meteorological input data were generated based on ECHAM5/MPI-OM1 global climate model projections. The hydrological model HBV-LMU was calibrated by an automatic calibration algorithm using runoff and snow cover information as objective functions. Manual fine-tuning was performed to avoid unrealistic results for glacier mass balance. The simulations show that annual runoff sums will increase significantly under future climate conditions. A sensitivity analysis revealed that total runoff does not decrease until the glacier area is reduced by 43%. Ice melt is the major runoff source in the recent past, and its contribution will even increase in the coming decades. Seasonal changes reveal a trend towards enhanced melt in spring, but a change from a glacial-nival to a nival-pluvial runoff regime will not be reached until the end of this century.

scholarly journals Extrapolating glacier mass balance to the mountain-range scale: the European Alps 1900–2100

2012 ◽  
Vol 6 (4) ◽  
pp. 713-727 ◽  
Author(s):  
M. Huss
Keyword(s):  
Mass Balance ◽  
Multiple Regression ◽  
Volume Change ◽  
Data Series ◽  
Glacier Mass Balance ◽  
Mountain Range ◽  
European Alps ◽  
Ice Volume ◽  
Area Reduction

Abstract. This study addresses the extrapolation of in-situ glacier mass balance measurements to the mountain-range scale and aims at deriving time series of area-averaged mass balance and ice volume change for all glaciers in the European Alps for the period 1900–2100. Long-term mass balance series for 50 Swiss glaciers based on a combination of field data and modelling, and WGMS data for glaciers in Austria, France and Italy are used. A complete glacier inventory is available for the year 2003. Mass balance extrapolation is performed based on (1) arithmetic averaging, (2) glacier hypsometry, and (3) multiple regression. Given a sufficient number of data series, multiple regression with variables describing glacier geometry performs best in reproducing observed spatial mass balance variability. Future mass changes are calculated by driving a combined model for mass balance and glacier geometry with GCM ensembles based on four emission scenarios. Mean glacier mass balance in the European Alps is −0.31 ± 0.04 m w.e. a−1 in 1900–2011, and −1 m w.e. a−1 over the last decade. Total ice volume change since 1900 is −96 ± 13 km3; annual values vary between −5.9 km3 (1947) and +3.9 km3 (1977). Mean mass balances are expected to be around −1.3 m w.e. a−1 by 2050. Model results indicate a glacier area reduction of 4–18% relative to 2003 for the end of the 21st century.

Latest Advances in Fractional Snow Cover Mapping on MODIS Data by Machine Learning Algorithms

2020 ◽  
Author(s):  
Semih Kuter ◽  
Zuhal Akyurek
Keyword(s):  
Machine Learning ◽  
Snow Cover ◽  
General Circulation ◽  
Snow Water Equivalent ◽  
Machine Learning Algorithms ◽  
Multivariate Adaptive Regression Splines ◽  
Support Vector ◽  
Landsat 8 ◽  
European Alps ◽  
Fractional Snow Cover

&lt;p&gt;Spatial extent of snow has been declared as an essential climate variable. Accurate modeling of snow cover is crucial for the better prediction of snow water equivalent and, consequently, for the success of general circulation and weather forecasting models as well as climate change and hydrological studies. This presentation mainly focuses on the representation of the latest findings of our efforts in fractional snow cover mapping on MODIS images by data-driven machine learning methodologies. For this purpose, a dataset composed of 20 MODIS - Landsat 8 image pairs acquired between Apr 2013 and Dec 2016 over European Alps were employed. Artificial neural networks (ANN), multivariate adaptive regression splines (MARS), support vector regression (SVR) and random forest (RF) models were trained and tested by using reference FSC maps generated from higher spatial resolution Landsat 8 binary snow maps. ANN, MARS, SVR and RF models exhibited quite good performance with average R &amp;#8776; 0.93, whereas the agreement between the reference FSC maps and the MODIS&amp;#8217; own product MOD10A1 (C5) was slightly poorer with R &amp;#8776; 0.88.&lt;/p&gt;

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