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

<p>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 1971–2008 and shows a large spatial variability. This study evidences seasonal and altitudinal contrasts of climate trends over the Alps. A significant (pvalue< 0.05) increase in mean winter precipitation is simulated in the northwestern Alps over 1903–2010, 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 (<10%) and not significant above 1500ma.s.l. Over 1903–2010, 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<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 1970–2010, 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 (< 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 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.</p>

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 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 A regional climate model hindcast for Siberia – assessing the added value of snow water equivalent using ESA GlobSnow and reanalyses

2012 ◽  
Vol 6 (6) ◽  
pp. 4637-4671
Author(s):  
K. Klehmet ◽  
B. Geyer ◽  
B. Rockel
Keyword(s):  
Regional Climate Model ◽  
Snow Cover ◽  
Large Scale ◽  
Snow Water Equivalent ◽  
Climate Model ◽  
Regional Climate ◽  
Snow Accumulation ◽  
Added Value ◽  
Snow Cover Extent ◽  
Snow Water

Abstract. This study analyzes the added value of a regional climate model hindcast of CCLM compared to global reanalyses in providing a reconstruction of recent past snow water equivalent (SWE) for Siberia. Consistent regional climate data in time and space is necessary due to lack of station data in that region. We focus on SWE since it represents an important snow cover parameter in a region where snow has the potential to feed back to the climate of the whole Northern Hemisphere. The simulation was performed in a 50 km grid spacing for the period 1948 to 2010 using NCEP Reanalysis 1 as boundary forcing. Daily observational reference data for the period of 1987–2010 was obtained by the satellite derived SWE product of ESA DUE GlobSnow that enables a large scale assessment. The analyses includes comparisons of the distribution of snow cover extent, example time series of monthly SWE for January and April, regional characteristics of long-term monthly mean, standard deviation and temporal correlation averaged over subregions. SWE of CCLM is compared against the SWE information of NCEP-R1 itself and three more reanalyses (NCEP-R2, NCEP-CFSR, ERA-Interim). We demonstrate a significant added value of the CCLM hindcast during snow accumulation period shown for January for many subregions compared to SWE of NCEP-R1. NCEP-R1 mostly underestimates SWE during whole snow season. CCLM overestimates SWE compared to the satellite-derived product during April – a month representing the beginning of snow melt in southern regions. We illustrate that SWE of the regional hindcast is more consistent in time than ERA-Interim and NCEP-R2 and thus add realistic detail.

Snow cover response to climate change in a high alpine and half-glacierized basin in Switzerland

2010 ◽  
Vol 41 (3-4) ◽  
pp. 230-240 ◽  
Author(s):  
Jan Magnusson ◽  
Tobias Jonas ◽  
Ignacio López-Moreno ◽  
Michael Lehning
Keyword(s):  
Climate Change ◽  
Snow Cover ◽  
Snow Water Equivalent ◽  
Climate Model ◽  
Regional Climate ◽  
Longwave Radiation ◽  
Hydrological Regime ◽  
Surface Model ◽  
Snow Pack ◽  
Emission Scenarios

In alpine areas, the accumulation and melting of snow controls the hydrological regime. Even in watersheds where glacier melt dominates, the snow pack strongly influences the stream-flow dynamics. Prognostic simulations of the response of the snow pack to climate change were conducted in a high alpine and half-glacierized basin in central Switzerland. The snow cover and glacier were simulated using a high-resolution alpine surface model. The simulations cover a reference period (1981–2007) and two predictions (2071–2100) where the measured records of temperature, precipitation and longwave radiation were modified using six regional climate model projections for two different emission scenarios of greenhouse gases. The results show that the snow season shortens by one month at the beginning of the winter and by one and a half months at the end of the season, compared to today. The maximum snow water equivalent decreases by 27% on average. The difference in the response of the snow pack to a change in climate between the emission scenarios is rather small. The most pronounced effects of a warming climate are simulated for the highest altitudes, where all snow completely melts during summer and no snow remains for glacier accumulation.

scholarly journals Future snowfall in the Alps: projections based on the EURO-CORDEX regional climate models

2018 ◽  
Vol 12 (1) ◽  
pp. 1-24 ◽  
Author(s):  
Prisco Frei ◽  
Sven Kotlarski ◽  
Mark A. Liniger ◽  
Christoph Schär
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Regional Climate Models ◽  
European Alps ◽  
Emission Scenarios ◽  
Heavy Snowfall ◽  
Rcp Scenarios ◽  
Near Surface ◽  
The Alps

Abstract. Twenty-first century snowfall changes over the European Alps are assessed based on high-resolution regional climate model (RCM) data made available through the EURO-CORDEX initiative. Fourteen different combinations of global and regional climate models with a target resolution of 12 km and two different emission scenarios are considered. As raw snowfall amounts are not provided by all RCMs, a newly developed method to separate snowfall from total precipitation based on near-surface temperature conditions and accounting for subgrid-scale topographic variability is employed. The evaluation of the simulated snowfall amounts against an observation-based reference indicates the ability of RCMs to capture the main characteristics of the snowfall seasonal cycle and its elevation dependency but also reveals considerable positive biases especially at high elevations. These biases can partly be removed by the application of a dedicated RCM bias adjustment that separately considers temperature and precipitation biases.Snowfall projections reveal a robust signal of decreasing snowfall amounts over most parts of the Alps for both emission scenarios. Domain and multi-model mean decreases in mean September–May snowfall by the end of the century amount to −25 and −45 % for representative concentration pathway (RCP) scenarios RCP4.5 and RCP8.5, respectively. Snowfall in low-lying areas in the Alpine forelands could be reduced by more than −80 %. These decreases are driven by the projected warming and are strongly connected to an important decrease in snowfall frequency and snowfall fraction and are also apparent for heavy snowfall events. In contrast, high-elevation regions could experience slight snowfall increases in midwinter for both emission scenarios despite the general decrease in the snowfall fraction. These increases in mean and heavy snowfall can be explained by a general increase in winter precipitation and by the fact that, with increasing temperatures, climatologically cold areas are shifted into a temperature interval which favours higher snowfall intensities. In general, percentage changes in snowfall indices are robust with respect to the RCM postprocessing strategy employed: similar results are obtained for raw, separated, and separated–bias-adjusted snowfall amounts. Absolute changes, however, can differ among these three methods.

scholarly journals Evaluating Snow in EURO-CORDEX Regional Climate Models with Observations for the European Alps: Biases and Their Relationship to Orography, Temperature, and Precipitation Mismatches

Atmosphere ◽  
2019 ◽  
Vol 11 (1) ◽  
pp. 46
Author(s):  
Michael Matiu ◽  
Marcello Petitta ◽  
Claudia Notarnicola ◽  
Marc Zebisch
Keyword(s):  
Snow Cover ◽  
Snow Depth ◽  
Large Scale ◽  
Climate Models ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Horizontal Resolution ◽  
Winter Period ◽  
European Alps ◽  
Temperature And Precipitation

Climate models are important tools to assess current and future climate. While they have been extensively used for studying temperature and precipitation, only recently regional climate models (RCMs) arrived at horizontal resolutions that allow studies of snow in complex mountain terrain. Here, we present an evaluation of the snow variables in the World Climate Research Program Coordinated Regional Downscaling Experiment (EURO-CORDEX) RCMs with gridded observations of snow cover (from MODIS remote sensing) and temperature and precipitation (E-OBS), as well as with point (station) observations of snow depth and temperature for the European Alps. Large scale snow cover dynamics were reproduced well with some over- and under-estimations depending on month and RCM. The orography, temperature, and precipitation mismatches could on average explain 31% of the variability in snow cover bias across grid-cells, and even more than 50% in the winter period November–April. Biases in average monthly snow depth were remarkably low for reanalysis driven RCMs (<approx. 30 cm), and large for the GCM driven ones (up to 200 cm), when averaged over all stations within 400 m of altitude difference with RCM orography. Some RCMs indicated low snow cover biases and at the same time high snow depth biases, and vice versa. In summary, RCMs showed good skills in reproducing alpine snow cover conditions with regard to their limited horizontal resolution. Detected shortcomings in the models depended on the considered snow variable, season and individual RCM.

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

2020 ◽  
Vol 24 (11) ◽  
pp. 5355-5377
Author(s):  
Martin Ménégoz ◽  
Evgenia Valla ◽  
Nicolas C. Jourdain ◽  
Juliette Blanchet ◽  
Julien Beaumet ◽  
...  
Keyword(s):  
Climate Model ◽  
Regional Climate ◽  
Vertical Gradient ◽  
Southern Alps ◽  
P Value ◽  
Northwestern Part ◽  
Positive Trend ◽  
European Alps ◽  
The Alps ◽  
Wet Spells

Abstract. Changes in precipitation over the European Alps are investigated with the regional climate model MAR (Modèle Atmosphérique Régional) 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 interannual variability and the seasonal cycle of precipitation over the European Alps. The relatively high resolution allows us 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 d−1 km−1) in summer and 38 % km−1 (1.15 mm d−1 km−1) in winter, on average, over 1971–2008 and shows a large spatial variability. A significant (p value < 0.05) increase in mean winter precipitation is simulated in the northwestern Alps over 1903–2010, with changes typically reaching 20 % to 40 % per century. This increase is mainly explained by a stronger simple daily intensity index (SDII) and is associated with less-frequent but longer wet spells. 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 much smaller (<10 %) and not significant above 1500 m a.s.l. Below this level, the summer drying is explained by a reduction in the number of wet days, reaching 20 % per century over the northwestern part of the Alps and 30 % to 50 % per century in the southern part of the Alps. It is associated with shorter but more-frequent wet spells. The centennial trends are modulated over the last decades, with the drying occurring in the plains in winter also affecting high-altitude areas during this season and with a positive trend of autumn precipitation occurring only over the last decades all over the Alps. Maximum daily precipitation index (Rx1day) takes its highest values in autumn in both the western and the eastern parts of the southern Alps, locally reaching 50 to 70 mm d−1 on average over 1903–2010. Centennial maxima up to 250 to 300 mm d−1 are simulated in the southern Alps, in France and Italy, as well as in the Ticino valley in Switzerland. Over 1903–2010, seasonal 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 (p value < 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 1970–2010, suggesting a recent acceleration of the increase in extreme precipitation, whereas earlier periods with strong precipitation also occurred, in particular during the 1950s and 1960s.

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.

Biascorrected projections of snow cover fraction from EURO-CORDEX regional climate models with MODIS remote sensing observations for the European Alps

2020 ◽  
Author(s):  
Michael Matiu ◽  
Marcello Petitta ◽  
Claudia Notarnicola ◽  
Marc Zebisch
Keyword(s):  
Remote Sensing ◽  
Snow Cover ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Climate Projections ◽  
European Alps ◽  
Hydrological Models ◽  
Snow Cover Fraction

&lt;p&gt;Snow is a key environmental parameter in mountains, and in this changing climate reductions in snow are expected. Traditionally, future estimates of snow are based on dedicated snow/hydrological models forced by climate projections, which, however, are computationally intensive and which decouple hydrology from climate forcing. Recently, regional climate models (RCM) have been used as an alternative, although snow is only an auxiliary parameter in RCMs and not as accurately represented as compared to dedicated snow models. Nonetheless, RCMs encompass the climate-hydrology feedbacks, cover large areas, and have recently become available in moderate horizontal resolutions.&lt;/p&gt;&lt;p&gt;Here, we skip the need to biascorrect the input variables to the snow/hydrological models (i.e. temperature, precipitation, &amp;#8230;) and use observations to directly biascorrect the target variable, i.e. snow cover. Quantile delta mapping (QDM), a trend preserving bias correction method, is used to correct biases in EURO-CORDEX RCMs that provide snow cover fraction as output (CCLM4-8-17, ALADIN63, WRF331F, WRF381P, RACMO22E, RCA4) using remote sensing observations of snow cover from MODIS for the European Alps. As such, snow cover biases were accounted for, which originated mostly from orographic mismatches as well as temperature and precipitation biases. Model ensemble means were calculated for two emission scenarios (rcp26 and rcp85; with 6 and 21 GCM-RCM combinations available). The biascorrected projections can be used to put the climate model projections into context of current observations thus facilitating interpretations.&lt;/p&gt;&lt;p&gt;These are results from CliRSnow, a project that aims at providing bias corrected and downscaled projections of snow cover for the whole Alpine region until 2100. This project has received funding from the European Union&amp;#8217;s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 795310.&lt;/p&gt;

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