Future Climate Change in the European Alps

2020 ◽  
Author(s):  
Andreas Gobiet ◽  
Sven Kotlarski
Keyword(s):  
Climate Change ◽  
Snow Cover ◽  
Precipitation Extremes ◽  
Convective Precipitation ◽  
Future Climate Change ◽  
European Alps ◽  
Strong Wind ◽  
Alpine Area ◽  
Natural Snow ◽  
Precipitation Changes

The analysis of state-of-the-art regional climate projections indicates a number of robust changes of the climate of the European Alps by the end of this century. Among these are a temperature increase in all seasons and at all elevations and a significant decrease in natural snow cover. Precipitation changes, however, are more subtle and subject to larger uncertainties. While annual precipitation sums are projected to remain rather constant until the end of the century, winter precipitation is projected to increase. Summer precipitation changes will most likely be negative, but increases are possible as well and are covered by the model uncertainty range. Precipitation extremes are expected to intensify in all seasons. The projected changes by the end of the century considerably depend on the greenhouse-gas scenario assumed, with the high-end RCP8.5 scenario being associated with the most prominent changes. Until the middle of the 21st century, however, it is projected that climate change in the Alpine area will only slightly depend on the specific emission scenario. These results indicate that harmful weather events in the Alpine area are likely to intensify in future. This particularly refers to extreme precipitation events, which can trigger flash floods and gravitational mass movements (debris flows, landslides) and lead to substantial damage. Convective precipitation extremes (thunderstorms) are additionally a threat to agriculture, forestry, and infrastructure, since they are often associated with strong wind gusts that cause windbreak in forests and with hail that causes damage in agriculture and infrastructure. Less spectacular but still very relevant is the effect of soil erosion on inclined arable land, caused by heavy precipitation. At the same time rising temperatures lead to longer vegetation periods, increased evapotranspiration, and subsequently to higher risk of droughts in the drier valleys of the Alps. Earlier snowmelt is expected to lead to a seasonal runoff shift in many catchments and the projected strong decrease of the natural snow cover will have an impact on tourism and, last but not least, on the cultural identity of many inhabitants of the Alpine area.

Detection of precipitation and snow cover trends in the the European Alps over the last century using model and observational data

2020 ◽  
Author(s):  
Julien Beaumet ◽  
Martin Menegoz ◽  
Hubert Gallée ◽  
Vincent Vionnet ◽  
Xavier Fettweis ◽  
...  
Keyword(s):  
Climate Change ◽  
Snow Cover ◽  
Observational Data ◽  
Snow Depth ◽  
European Alps ◽  
Temperature Changes ◽  
In Situ Observations ◽  
Precipitation Changes ◽  
High Elevations

<p><span>The European Alps are particularly sensitive to climate change. Compared to temperature, changes in precipitation are more challenging to detect and attribute to ongoing anthropic climate change </span><span>mainly </span><span>as a result of large inter-annual variability, </span><span>lack of reliable measurements at high elevations</span><span> and opposite signals depending on the season or the elevation considered. However, changes in precipitation and snow cover have significant socio-environmental impact mostly trough water resource availability. These changes are investigated within the framework of the Trajectories initiative (</span><span><span></span></span><span>). The variability and changes in precipitation and snow cover in the European Alps has been simulated with the MAR regional climate model at a 7 km horizontal resolution driven by ERA20C (1902-2010) and ERA5 (1979-2018) reanalyses. </span></p><p><span>For precipitation, MAR outputs were compared with EURO-4M, SAFRAN, SPAZM and E-OBS reanalyses as well as in-situ observations. The model was shown to reproduce correctly seasonal and inter-annual variability. The spatial biases of the model have the same order of magnitude as the differences between the three observational data sets. Model experiment has been used to detect precipitation changes over the last century. An increase in winter precipitation is simulated over the North-western part of the Alps at high altitudes (>1500m). Significant decreases in summer precipitation were found in many low elevation areas, especially the Po Plain while no significant trends where found at high elevations. Because of large internal variability, precipitation changes are significant (pvalue<0.05) only when considering their evolution over long period, typically 60-100 years in both model and observations.</span></p><p><span>Snow depth and water equivalent (SWE) in the French Alps simulated with MAR have been compared to the SAFRAN-Crocus reanalyses and to in-situ observations. MAR was found to simulate a realistic distribution of SWE as function of the elevation in the French Alpine massifs, although it underestimates SWE at low elevations in the Pre-Alps. Snow cover over the whole European Alps is evaluated using MODIS satellite data. Finally, trends in snow cover and snow depth are highlighted as well as their relationships with the precipitation and temperature changes over the last century. </span></p>

Characterization of extreme meteo-hydrological events in the Alpine Region: historical picture and future scenarios

2020 ◽  
Author(s):  
Matteo Pesce ◽  
Larisa Tarasova ◽  
Ralf Merz ◽  
Jost von Hardenberg ◽  
Alberto Viglione
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Temporal Dynamics ◽  
Regional Scale ◽  
Alpine Region ◽  
Precipitation Extremes ◽  
Climate Indices ◽  
European Alps ◽  
Flood Events ◽  
River Flood

<p>In the European Alps, climate change has determined changes in extreme precipitation and river flood events, which impact the population living downstream with increasing frequency. The objectives of our work are:</p><ol><li>to determine what types of precipitation extremes and river flood events occur in the Alpine Region, based on their generating mechanisms (e.g., frontal convergence storms, convective storms, snow-melt floods, rain-on-snow floods, short and long rain floods, flash floods, ...)</li> <li>to determine the spatial and seasonal distribution of these event types (e.g., their dependence on elevation, geographical location, catchment size, ...) and how precipitation extremes relate to the floods they produce (e.g., the role of snow precipitation and accumulation)</li> <li>to determine whether the event type distribution is changing and will change in the future (e.g., due to climate change).  </li> </ol><p>To these aims, we will compile and analyze historical time series of precipitation and discharge in order to identify events in terms of intensity, duration, and spatial extent. We will use the ETCCDI indices as a measure of the precipitation distribution and hydrograph separation techniques for flow events, following the methodology of Tarasova et al. (2018). We will then characterize each event in terms of generation mechanisms. Furthermore, we will analyze the frequency and magnitude of the different event types in different locations and time of the year and determine whether clusters exist by applying automatic techniques (e.g. K-means clustering algorithm). Finally, we will correlate statistics of precipitation and flood event types with climate indices related to large scale atmospheric circulation, such as Atmospheric Blocking, NAO, etc. (Ciccarelli et al. 2008). Results will be then used for the projection of future storm and flood scenarios.</p><p>We will first apply the methodology in Piedmont by comparing the station-based time series with the NWIOI dataset (ARPA Piemonte) and reanalysis datasets by ECMWF (ERA5, ERA5-Land). We will use a rainfall-runoff model at the daily and sub-daily timescale, through calibration at the regional scale, useful for the simulation of soil saturation and snowpack. We expect to find a statistical correlation between the different datasets, but with changing statistical features over space and time within the single datasets. We aim to provide a detailed picture of the different types of events according to the spatial location and season. The results will be useful, from a scientific perspective, to better understand storm and flood regimes and their change in the Alpine Region, and, from a practical perspective, to better mitigate the risk associated with the occurrence of extreme events.      </p><p>Ciccarelli, N., Von Hardenberg, J., Provenzale, A., Ronchi, C., Vargiu, A., & Pelosini, R. (2008). Climate variability in north-western Italy during the second half of the 20th century. Global and Planetary Change, 63(2-3), 185-195. https://doi.org/10.1016/j.gloplacha.2008.03.006</p><p>Tarasova, L., Basso, S., Zink, M., & Merz, R. (2018). Exploring controls on rainfall-runoff events: 1. Time series-based event separation and temporal dynamics of event runoff response in Germany. Water Resources Research, 54, 7711–7732. https://doi.org/10.1029/2018WR022587</p>

Avalanche flow regime transitions in a changing climate

2020 ◽  
Author(s):  
Camille Ligneau ◽  
Betty Sovilla ◽  
Johan Gaume
Keyword(s):  
Climate Change ◽  
Snow Cover ◽  
Flow Regime ◽  
Flow Regimes ◽  
Future Climate Change ◽  
Hazard Mapping ◽  
Snow Avalanches ◽  
Avalanche Flow ◽  
Regime Transitions ◽  
Snow Temperature

<p>In the near future, climate change will impact the snow cover in Alpine regions. Higher precipitations and warmer temperatures are expected at lower altitude, leading to larger gradients of snow temperature, snow water content and snow depth between the top and the bottom of slopes. As a consequence, climate change will also indirectly influence the behavior of snow avalanches.</p><p>The present work aims to investigate how changes in snow cover properties will affect snow avalanches dynamics. Experimental studies allowed to characterize different avalanche flow regimes which result from particular combinations of snow physical and mechanical properties. In particular, expected variations of snow temperatures with elevation will cause more frequent and more extreme flow regime transitions inside the same avalanche. For example, a fast avalanche characterized by cold and low-cohesive snow in the upper part of the avalanche track will transform more frequently into a slow flow made of wet and heavy snow when the avalanche will entrain warm snow along the slope. A better understanding of these flow regime transitions, which have already been largely reported, is crucial, because it affects both daily danger assessment (e.g. forecasting services, road controls) and hazard mapping of avalanches.</p><p>To date, most avalanche modeling methods are not considering temperature effects and are then unable to simulate flow regime transitions and unprecedented scenarios. Our goal is then to develop a model capable of simulating reported flow regimes, flow transitions and the interactions between the snow cover and the flow (erosion, entrainment). Since these elements are not yet fully understood, we firstly model these mesoscopic processes using a 2D Discrete Element Model (DEM) in which varying particle cohesion and friction mimic the effect of changes in snow temperature. Flow regimes are simulated by granular assemblies put into motion by gravity on an inclined slope, which interact with a granular and erodible bed surface. Simulations are calibrated using experimental data coming from the avalanche test site located in Vallée de la Sionne, which record avalanches since more than 20 years. This modeling will then be used as an input to improve slope-scale models and make them more appropriate for avalanche risk management in the context of climate change.</p>

scholarly journals Reversibility of Historical and Future Climate Change with a Complex Earth System Model

2021 ◽  
Author(s):  
Shili Yang ◽  
Di Tian ◽  
JieMing Chou ◽  
Ting Wei ◽  
Xian Zhu ◽  
...  
Keyword(s):  
Climate Change ◽  
Surface Temperature ◽  
Earth System Model ◽  
Meridional Overturning Circulation ◽  
System Model ◽  
Convective Precipitation ◽  
Future Climate Change ◽  
Earth System ◽  
Initial Values ◽  
Precipitation Total

Abstract The reversibility of a wide range of components of the earth system was investigated by comparing forward and time-reversed historical and future simulations of a coupled earth system model known as the Beijing Normal University earth system model. Many characteristics of the climate system, including the surface temperature, ocean heat content (OHC), convective precipitation, total runoff, ground evaporation, soil moisture, sea ice extent and Atlantic Meridional Overturning Circulation, did not fully return to their initial values when the historical or future natural and anthropogenic forcing agents were reversed. The surface temperature and OHC declines lagged behind the decline in greenhouse gases (GHGs). Reverses in other variables occurred in direct response to the decline in GHGs. The sea level increased, even after all of the forces returned to the original values. Furthermore, most of the climate variables did not return to their original values because of thermal inertial. The end states of variables, other than those related to thermal storage, mainly depended on the original state of the natural and anthropogenic forces, and were unaffected by the future growth rate of the GHGs. The climate policy implication of this study is that climate change cannot be completely reversed even if all the external forces are returned to their initial values.

scholarly journals Scenarios of Future Snow Conditions in Styria (Austrian Alps)

2015 ◽  
Vol 16 (1) ◽  
pp. 261-277 ◽  
Author(s):  
Thomas Marke ◽  
Ulrich Strasser ◽  
Florian Hanzer ◽  
Johann Stötter ◽  
Renate Anna Irma Wilcke ◽  
...  
Keyword(s):  
Climate Change ◽  
Snow Cover ◽  
Impact Analysis ◽  
Season Length ◽  
Average Decrease ◽  
Climate Change Effects ◽  
Scenario Period ◽  
Natural Snow ◽  
Snow Conditions ◽  
Projected Changes

Abstract A hydrometeorological model chain is applied to investigate climate change effects on natural and artificial snow conditions in the Schladming region in Styria (Austria). Four dynamically refined realizations of the IPCC A1B scenario covering the warm/cold and wet/dry bandwidth of projected changes in temperature and precipitation in the winter half-year are statistically downscaled and bias corrected prior to their application as input for a physically based, distributed energy-balance snow model. However, owing to the poor skills in the reproduction of past climate and snow conditions in the considered region, one realization had to be removed from the selection to avoid biases in the results of the climate change impact analysis. The model’s capabilities in the simulation of natural and artificial snow conditions are evaluated and changes in snow conditions are addressed by comparing the number of snow cover days, the length of the ski season, and the amounts of technically produced snow as simulated for the past and the future. The results for natural snow conditions indicate decreases in the number of snow cover days and the ski season length of up to >25 and >35 days, respectively. The highest decrease in the calculated ski season length has been found for elevations between 1600 and 2700 m MSL, with an average decrease rate of ~2.6 days decade−1. For the exemplary ski site considered, the ski season length simulated for natural snow conditions decreases from >50 days at present to ~40 days in the 2050s. Technical snow production allows the season to be prolonged by ~80 days and hence allows ski season lengths of ~120 days until the end of the scenario period in 2050.

Future Climate Change Impacts on Snow and Water Resources of the Fraser River Basin, British Columbia

2017 ◽  
Vol 18 (2) ◽  
pp. 473-496 ◽  
Author(s):  
Siraj ul Islam ◽  
Stephen J. Déry ◽  
Arelia T. Werner
Keyword(s):  
Climate Change ◽  
British Columbia ◽  
Snow Cover ◽  
River Basin ◽  
Snow Water Equivalent ◽  
Climate Change Impacts ◽  
Snow Accumulation ◽  
Low Flow ◽  
Future Climate Change ◽  
Fraser River

Abstract Changes in air temperature and precipitation can modify snowmelt-driven runoff in snowmelt-dominated regimes. This study focuses on climate change impacts on the snow hydrology of the Fraser River basin (FRB) of British Columbia (BC), Canada, using the Variable Infiltration Capacity model (VIC). Statistically downscaled forcing datasets based on 12 models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) are used to drive VIC for two 30-yr time periods, a historical baseline (1980–2009) and future projections (2040–69: 2050s), under representative concentration pathways (RCPs) 4.5 and 8.5. The ensemble-based VIC simulations reveal widespread and regionally coherent spatial changes in snowfall, snow water equivalent (SWE), and snow cover over the FRB by the 2050s. While the mean precipitation is projected to increase slightly, the fraction of precipitation falling as snow is projected to decrease by nearly 50% in the 2050s compared to the baseline. Snow accumulation and snow-covered area are projected to decline substantially across the FRB, particularly in the Rocky Mountains. Onset of springtime snowmelt in the 2050s is projected to be nearly 25 days earlier than historically, yielding more runoff in the winter and spring for the Fraser River at Hope, BC, and earlier recession to low-flow volumes in summer. The ratio of snowmelt contribution to runoff decreases by nearly 20% in the Stuart and Nautley subbasins of the FRB in the 2050s. The decrease in SWE and loss of snow cover is greater from low to midelevations than in high elevations, where temperatures remain sufficiently cold for precipitation to fall as snow.

Assessing impacts of future potential climate change scenarios on snow cover area by using cellular automata models and Montecarlo simulations

2020 ◽  
Author(s):  
David Pulido-Velazquez ◽  
Antonio-Juan Collados-Lara ◽  
Eulogio Pardo-Igúzquiza
Keyword(s):  
Climate Change ◽  
Cellular Automata ◽  
Snow Cover ◽  
Future Climate Change ◽  
Climate Change Scenarios ◽  
Snow Cover Area ◽  
Multiple Series ◽  
The Future ◽  
Delta Change ◽  
Precipitation And Temperature

<p>Climate change will modify the availability of snow resources in the future. Thus developing methodologies to assess impacts of potential future climate change scenarios on snow variables is a key subject. In this work we combine several previous developed methodologies (downscaling climate change scenarios to local scale, cellular automata models, and stochastic weather generators) to assess impacts of future climate change scenarios and its uncertainty on snow cover area through a Montecarlo simulation. The cellular automata model uses climatic indices (precipitation and temperature) as driving variables to estimate snow cover area. Future scenarios of these variables can be generated using bias correction and delta change approaches and different regional climate models. The stochastic weather generators allow us to produce multiple series of precipitation and temperature based on the statistical characteristics of the future local scenarios generated. These multiple series can be used as inputs of the cellular automata model in order to assess the future snow cover area and its uncertainty. The main advantages of the proposed methodology are its applicability in cases with limited information and in mountain ranges scales. The methodology has been applied to the Sierra Nevada mountain range in southern Spain. This area has a Mediterranean climate very sensitive to climate change. Using the future precipitation and temperature scenarios generated considering the Representative Concentration Pathways 8.5 (RCP8.5) for the period 2071–2100, we obtain a significant reduction in snow cover area, with mean values of 59.0% for the local scenarios generated with a delta change approach, and 61.7% for those one generated with the bias correction approach.</p><p>This research has been partially supported by the SIGLO-AN project (RTI2018-101397-B-I00) from the Spanish Ministry of Science, Innovation and Universities (Programa Estatal de I+D+I orientada a los Retos de la Sociedad).</p>

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