Reliable estimates of future climate change in the Alps are relevant for large parts of the European society. At the same time, the complex Alpine region poses considerable challenges to climate ...models, which translate to uncertainties in the climate projections. Against this background, the present study reviews the state-of-knowledge about 21st century climate change in the Alps based on existing literature and additional analyses. In particular, it explicitly considers the reliability and uncertainty of climate projections.
Results show that besides Alpine temperatures, also precipitation, global radiation, relative humidity, and closely related impacts like floods, droughts, snow cover, and natural hazards will be affected by global warming.
Under the A1B emission scenario, about 0.25°C warming per decade until the mid of the 21st century and accelerated 0.36°C warming per decade in the second half of the century is expected. Warming will probably be associated with changes in the seasonality of precipitation, global radiation, and relative humidity, and more intense precipitation extremes and flooding potential in the colder part of the year. The conditions of currently record breaking warm or hot winter or summer seasons, respectively, may become normal at the end of the 21st century, and there is indication for droughts to become more severe in the future. Snow cover is expected to drastically decrease below 1500–2000m and natural hazards related to glacier and permafrost retreat are expected to become more frequent.
Such changes in climatic parameters and related quantities will have considerable impact on ecosystems and society and will challenge their adaptive capabilities.
•Warming is expected to accelerate throughout the 21st century in the Alpine region.•Seasonal shifts in precipitation, global radiation, and relative humidity are expected.•Precipitation and temperature extremes are expected to intensify.•Snow cover is expected to drastically decrease below 1500–2000m elevation.•Further changes related to droughts and natural hazards are expected.
Climate impact studies constitute the basis for the formulation of adaptation strategies. Usually such assessments apply statistically postprocessed output of climate model projections to force ...impact models. Increasingly, time series with daily resolution are used, which require high consistency, for instance with respect to transition probabilities (TPs) between wet and dry days and spell durations. However, both climate models and commonly applied statistical tools have considerable uncertainties and drawbacks. This paper compares the ability of 1) raw regional climate model (RCM) output, 2) bias-corrected RCM output, and 3) a conventional weather generator (WG) that has been calibrated to match observed TPs to simulate the sequence of dry, wet, and very wet days at a set of long-term weather stations across Switzerland. The study finds systematic biases in TPs and spell lengths for raw RCM output, but a substantial improvement after bias correction using the deterministic quantile mapping technique. For the region considered, bias-corrected climate model output agrees well with observations in terms of TPs as well as dry and wet spell durations. For the majority of cases (models and stations) bias-corrected climate model output is similar in skill to a simple Markov chain stochastic weather generator. There is strong evidence that bias-corrected climate model simulations capture the atmospheric event sequence more realistically than a simple WG.
An analysis is presented of an ensemble of regional climate model (RCM) experiments from the ENSEMBLES project in terms of mean winter snow water equivalent (SWE), the seasonal evolution of snow ...cover, and the duration of the continuous snow cover season in the European Alps. Two sets of simulations are considered, one driven by GCMs assuming the SRES A1B greenhouse gas scenario for the period 1951–2099, and the other by the ERA-40 reanalysis for the recent past. The simulated SWE for Switzerland for the winters 1971–2000 is validated against an observational data set derived from daily snow depth measurements. Model validation shows that the RCMs are capable of simulating the general spatial and seasonal variability of Alpine snow cover, but generally underestimate snow at elevations below 1,000 m and overestimate snow above 1,500 m. Model biases in snow cover can partly be related to biases in the atmospheric forcing. The analysis of climate projections for the twenty first century reveals high inter-model agreement on the following points: The strongest relative reduction in winter mean SWE is found below 1,500 m, amounting to 40–80 % by mid century relative to 1971–2000 and depending upon the model considered. At these elevations, mean winter temperatures are close to the melting point. At higher elevations the decrease of mean winter SWE is less pronounced but still a robust feature. For instance, at elevations of 2,000–2,500 m, SWE reductions amount to 10–60 % by mid century and to 30–80 % by the end of the century. The duration of the continuous snow cover season shows an asymmetric reduction with strongest shortening in springtime when ablation is the dominant factor for changes in SWE. We also find a substantial ensemble-mean reduction of snow reliability relevant to winter tourism at elevations below about 1,800 m by mid century, and at elevations below about 2,000 m by the end of the century.
This work analyses three uncertainty sources affecting the observation‐based gridded data sets: station density, interpolation methodology and spatial resolution. For this purpose, we consider ...precipitation in two countries, Poland and Spain, three resolutions (0.11, 0.22 and 0.44°), three interpolation methods, both areal‐ and point‐representative implementations, and three different densities of the underlying station network (high/medium/low density). As a result, for each resolution and interpolation approach, nine different grids have been obtained for each country and inter‐compared using a variance decomposition methodology.
Results indicate larger differences among the data sets for Spain than for Poland, mainly due to the larger spatial variability and complex orography of the former region. The variance decomposition points out to station density as the most influential factor, independent of the season, the areal‐ or point‐representative implementation and the country considered, and slightly increasing with the spatial resolution. In contrast, the decomposition is stable when extreme precipitation indices are considered, in particular for the 50‐year return value.
Finally, the uncertainty due to station sub‐sampling inside a particular grid box decreases with the number of stations used in the averaging/interpolation. In the case of spatially homogeneous grid boxes, the interpolation approach obtains similar results for all the parameters, excepting the wet day frequency, independently of the number of stations. When there is a more significant internal variability in the grid box, the interpolation is more sensitive to the number of stations, pointing out to a minimum stations’ density for the target resolution (six to seven stations).
The uncertainty due to the stations density, interpolation method and resolution has been analysed for the precipitation in two countries, Poland and Spain, by means a variance decomposition analysis. The results reflect that the main factor in the development of gridded data sets is the underlying station's density for both mean and extreme precipitation. In addition, a minimum density of six to seven stations per grid box has been identified to reach an effective resolution of 0.44.
Ambitious climate change mitigation plans call for a significant increase in the use of renewables, which could, however, make the supply system more vulnerable to climate variability and changes. ...Here we evaluate climate change impacts on solar photovoltaic (PV) power in Europe using the recent EURO-CORDEX ensemble of high-resolution climate projections together with a PV power production model and assuming a well-developed European PV power fleet. Results indicate that the alteration of solar PV supply by the end of this century compared with the estimations made under current climate conditions should be in the range (-14%;+2%), with the largest decreases in Northern countries. Temporal stability of power generation does not appear as strongly affected in future climate scenarios either, even showing a slight positive trend in Southern countries. Therefore, despite small decreases in production expected in some parts of Europe, climate change is unlikely to threaten the European PV sector.
The Karakoram and the Himalayan mountain range accommodate a large number of glaciers and are the major source of several perennial rivers downstream. To interactively describe to response of ...glaciers to climate change, a glacier parameterization scheme has been developed and implemented into the regional climate model REMO. The scheme simulates the mass balance as well as changes of the areal extent of glaciers on a subgrid scale. The parameterization scheme is for the first time applied to the region. A regional glacier inventory is compiled and is used to initialize glacier area and volume. Over the highly complex and data sparse region, the simulated mass balance largely agrees with observations including the positive Karakoram anomaly. The simulated equilibrium line altitude is well captured although a systematic underestimation is apparent. REMO simulates the glacier‐climate interaction reasonably well; it has clear potential to be used for future climate assessments.
Key Points
Regional climate model coupled with dynamic glacier parameterization scheme
Mass balance and ELA for Karakoram‐Himalayas glaciers
A new high-resolution regional climate change ensemble has been established for Europe within the World Climate Research Program Coordinated Regional Downscaling Experiment (EURO-CORDEX) initiative. ...The first set of simulations with a horizontal resolution of 12.5 km was completed for the new emission scenarios RCP4.5 and RCP8.5 with more simulations expected to follow. The aim of this paper is to present this data set to the different communities active in regional climate modelling, impact assessment and adaptation. The EURO-CORDEX ensemble results have been compared to the SRES A1B simulation results achieved within the ENSEMBLES project. The large-scale patterns of changes in mean temperature and precipitation are similar in all three scenarios, but they differ in regional details, which can partly be related to the higher resolution in EURO-CORDEX. The results strengthen those obtained in ENSEMBLES, but need further investigations. The analysis of impact indices shows that for RCP8.5, there is a substantially larger change projected for temperature-based indices than for RCP4.5. The difference is less pronounced for precipitation-based indices. Two effects of the increased resolution can be regarded as an added value of regional climate simulations. Regional climate model simulations provide higher daily precipitation intensities, which are completely missing in the global climate model simulations, and they provide a significantly different climate change of daily precipitation intensities resulting in a smoother shift from weak to moderate and high intensities.
The objective of the present work is to compare the projections of surface solar radiation (SSR) simulated by four regional climate models (CCLM, RCA4, WRF, ALADIN) with the respective fields of ...their ten driving CMIP5 global climate models. First the annual and seasonal SSR changes are examined in the regional and in the global climate models based on the RCP8.5 emission scenarios. The results show significant discrepancies between the projected SSR, the multi-model mean of RCMs indicates a decrease in SSR of −0.60 W/m
2
per decade over Europe, while the multi-model mean of the associated GCMs used to drive the RCMs gives an increase in SSR of +0.39 W/m
2
per decade for the period of 2006–2100 over Europe. At seasonal scale the largest differences appear in spring and summer. The different signs of SSR projected changes can be interpreted as the consequence of the different behavior of cloud cover in global and regional climate models. Cloudiness shows a significant decline in GCMs with −0.24% per decade which explains the extra income in SSR, while in case of the regional models no significant changes in cloudiness can be detected. The reduction of SSR in RCMs can be attributed to increasing atmospheric absorption in line with the increase of water vapor content. Both global and regional models overestimate SSR in absolute terms as compared to surface observations, in line with an underestimation of cloud cover. Regional models further have difficulties to adequately reproduce the observed trends in SSR over the past decades.
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.
Wind energy resource is subject to changes in climate. To investigate the impacts of climate change on future European wind power generation potential, we analyze a multi-model ensemble of the most ...recent EURO-CORDEX regional climate simulations at the 12 km grid resolution. We developed a mid-century wind power plant scenario to focus the impact assessment on relevant locations for future wind power industry. We found that, under two greenhouse gas concentration scenarios, changes in the annual energy yield of the future European wind farms fleet as a whole will remain within 5% across the 21st century. At country to local scales, wind farm yields will undergo changes up to 15% in magnitude, according to the large majority of models, but smaller than 5% in magnitude for most regions and models. The southern fleets such as the Iberian and Italian fleets are likely to be the most affected. With regard to variability, changes are essentially small or poorly significant from subdaily to interannual time scales.
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