Projected changes in drought occurrence under future global warming from multi-model,multi-scenario,IPCC AR4 simulations

Recent and potential future increases in global temperatures are likely to be associated with impacts on the hydrologic cycle, including changes to precipitation and increases in extreme events such as droughts. We analyze changes in drought occurrence using soil moisture data for the SRES B1, A1B and A2 future climate scenarios relative to the PICNTRL pre-industrial control and 20C3M twentieth century simulations from eight AOGCMs that participated in the IPCC AR4. Comparison with observation forced land surface model estimates indicates that the models do reasonably well at replicating our best estimates of twentieth century, large scale drought occurrence, although the frequency of long-term (more than 12-month duration) droughts are over-estimated. Under the future projections, the models show decreases in soil moisture globally for all scenarios with a corresponding doubling of the spatial extent of severe soil moisture deficits and frequency of short-term (4–6-month duration) droughts from the mid-twentieth century to the end of the twenty-first. Long-term droughts become three times more common. Regionally, the Mediterranean, west African, central Asian and central American regions show large increases most notably for long-term frequencies as do mid-latitude North American regions but with larger variation between scenarios. In general, changes under the higher emission scenarios, A1B and A2 are the greatest, and despite following a reduced emissions pathway relative to the present day, the B1 scenario shows smaller but still substantial increases in drought, globally and for most regions. Increases in drought are driven primarily by reductions in precipitation with increased evaporation from higher temperatures modulating the changes. In some regions, increases in precipitation are offset by increased evaporation. Although the predicted future changes in drought occurrence are essentially monotonic increasing globally and in many regions, they are generally not statistically different from contemporary climate (as estimated from the 1961–1990 period of the 20C3M simulations) or natural variability (as estimated from the PICNTRL simulations) for multiple decades, in contrast to primary climate variables, such as global mean surface air temperature and precipitation. On the other hand, changes in annual and seasonal means of terrestrial hydrologic variables, such as evaporation and soil moisture, are essentially undetectable within the twenty-first century. Changes in the extremes of climate and their hydrological impacts may therefore be more detectable than changes in their means.     

Going to the Extremes

Projections of changes in climate extremes are critical to assessing the potential impacts of climate change on human and natural systems. Modeling advances now provide the opportunity of utilizing global general circulation models (GCMs) for projections of extreme temperature and precipitation indicators. We analyze historical and future simulations of ten such indicators as derived from an ensemble of 9 GCMs contributing to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR4), under a range of emissions scenarios. Our focus is on the consensus from the GCM ensemble, in terms of direction and significance of the changes, at the global average and geographical scale. The climate extremes described by the ten indices range from heat-wave frequency to frost-day occurrence, from dry-spell length to heavy rainfall amounts. Historical trends generally agree with previous observational studies, providing a basic sense of reliability for the GCM simulations. Individual model projections for the 21st century across the three scenarios examined are in agreement in showing greater temperature extremes consistent with a warmer climate. For any specific temperature index, minor differences appear in the spatial distribution of the changes across models and across scenarios, while substantial differences appear in the relative magnitude of the trends under different emissions rates. Depictions of a wetter world and greater precipitation intensity emerge unequivocally in the global averages of most of the precipitation indices. However, consensus and significance are less strong when regional patterns are considered. This analysis provides a first overview of projected changes in climate extremes from the IPCC-AR4 model ensemble, and has significant implications with regard to climate projections for impact assessments. An erratum to this article is available at . An erratum to this article can be found at     

Climate change impact assessment: the role of climate extremes in crop yield simulation

This work was aimed at assessing the role of climate extremes in climate change impact assessment of typical winter and summer Mediterranean crops by using Regional Circulation Model (RCM) outputs as drivers of a modified version of the CropSyst model. More specifically, climate change effects were investigated on sunflower (Helianthus annuus L.) and winter wheat (Triticum aestivum L.) development and yield under the A2 and B2 scenarios of the IPCC Special Report on Emissions Scenarios (SRES). The direct impact of extreme climate events (i.e. heat stress at anthesis stage) was also included. The increase in both mean temperatures and temperature extremes under A2 and B2 scenarios (2071?C2100) resulted in: a general advancement of the main phenological stages, shortening of the growing season and an increase in the frequency of heat stress during anthesis with respect to the baseline (1961?C1990). The potential impact of these changes on crop yields was evaluated. It was found that winter and summer crops may possess a different fitting capacity to climate change. Sunflower, cultivated in the southern regions of the Mediterranean countries, was more prone to the direct effect of heat stress at anthesis and drought during its growing cycle. These factors resulted in severe yield reduction. In contrast, the lower frequency of heat stress and drought allowed the winter wheat crop to attain increased yields with respect to the baseline period. It can be concluded that the impact of extreme events should be included in crop-modelling approaches, otherwise there is the risk of underestimating crop yield losses, which in turn would result in the application of incorrect policies for coping with climate change.     

Towards a better understanding of changes in wintertime cold extremes over Europe: a pilot study with CNRM and IPSL atmospheric models

Recent winter seasons have evidenced that global warming does not exclude the occurrence of exceptionally cold and/or snowy episodes in the Northern mid-latitudes. The expected rarefaction of such events is likely to exacerbate both their societal and environmental impacts. This paper therefore aims to evaluate model uncertainties underlying the fate of wintertime cold extremes over Europe. Understanding why climate models (1) still show deficiencies in simulating present-day features and (2) differ in their responses under future scenarios for the twentyfirst century indeed constitutes a crucial challenge. Here we propose a weather-regime approach in order to separate the contributions of large-scale circulation and non-dynamical processes to biases or changes in the simulated mean and extreme temperatures. We illustrate our methodology from the wintertime occurrence of extremely cold days in idealized atmosphere-only experiments performed with two of the CMIP5 climate models (CNRM-CM5 and IPSL-CM5A-LR). First we find that most of the present-day temperature biases are due to systematic errors in non-dynamical processes, while the main features of the large-scale dynamics are well captured in such experiments driven by observed sea-surface temperatures, with the exception of a generalized underestimation of blocking episodes. Then we show that uncertainties associated with changes in large-scale circulation modulate the depletion in cold extremes under an idealized scenario for the late twentyfirst century. These preliminary results suggest that the original methodology proposed in this paper can be helpful for understanding spreads of larger model-ensembles when simulating the response of temperature extremes to climate change.     

Projections of temperature and precipitation extremes in the North Western Mediterranean Basin by dynamical downscaling of climate scenarios at high resolution (1971–2050)

The North Western Mediterranean basin (NWMB) is characterised by a highly complex topography and an important variability of temperature and precipitation patterns. Downscaling techniques are required to capture these features, identify the most vulnerable areas to extreme changes and help decision makers to design strategies of mitigation and adaptation to climate change. A Regional Climate Model, WRF-ARW, is used to downscale the IPCC-AR4 ECHAM5/MPI-OM General Circulation Model results with high resolution (10 km), considering three different emissions scenarios (B1, A1B and A2) for 2001–2050. Model skills to reproduce observed extremes are assessed for a control period, 1971–2000, using the ERA40 reanalysis to drive the WRF-ARW simulations. A representative set of indices for temperature and precipitation extremes is projected. The modelling system correctly reproduces amplitude and frequency of extremes and provides a high degree of detail on variability over neighbouring areas. However, it tends to overestimate the persistence of wet events and consequently slightly underestimate the length of dry periods. Drier and hotter conditions are generally projected for the NWMB, with significant increases in the duration of droughts and the occurrence of heavy precipitation events. The projected increase in the number of tropical nights and extreme temperatures could have a negative effect on human health and comfort conditions. Simulations allow defining specifically vulnerable areas, such as the Ebro Valley or the Pyrenees, and foreseeing impacts on socio-economic activities in the region.     

Multimodel ensemble projections of future climate extreme changes in the Haihe River Basin,China

Exploring the characteristic of the extreme climatic events, especially future projection is considerably important in assessing the impacts of climatic change on hydrology and water resources system. We investigate the future patterns of climate extremes (2001–2099) in the Haihe River Basin (HRB) derived from Coupled General Circulation Model (CGCM) multimodel ensemble projections using the Bayesian Model Average (BMA) approach, under a range of emission scenarios. The extremes are depicted by three extreme temperature indices (i.e., frost days (FD), growing season length (GSL), and T _min >90th percentile (TN90)) and five extreme precipitation indices (i.e., consecutive dry days (CDD), precipitation ≥10 mm (R10), maximum 5-day precipitation total (R5D), precipitation >95th percentile (R95T), and simple daily intensity index (SDII)). The results indicate frost days display negative trend over the HRB in the 21st century, particularly in the southern basin. Moreover, a greater season length and more frequent warm nights are also projected in the basin. The decreasing CDD, together with the increasing R10, R5D, R95T, and SDII in the 21st century indicate that the extreme precipitation events will increase in their intensity and frequency in the basin. Meanwhile, the changes of all eight extremes climate indices under A2 and A1B scenarios are more pronounced than in B1. The results will be of practical significance in mitigation of the detrimental effects of variations of climatic extremes and improve the regional strategy for water resource and eco-environment management, particularly for the HRB characterized by the severe water shortages and fragile ecological environment.     

淮河流域水文极值预测模型研究

为探索气候变化影响下水文极值的非平稳性和预测方法,建立了水文极值非平稳广义极值（GEV）分布的统计预测模型。利用1952-2010年淮河上游流域累计面雨量和流量年最大值资料、同期500 hPa环流特征量资料以及17个CMIP5模式对环流特征量的模拟结果,筛选出对水文极值影响显著的年平均北半球极涡强度指数作为GEV分布参数的预测因子。分析了在RCP2.6、RCP4.5和RCP8.5情景下2006-2050年淮河上游流域水文极值对气候变化的响应。结果表明,10年以下与10年以上重现期的水文极值在非平稳过程中呈现前者下降而后者上升的相反变化趋势;多模型预测的集合平均在未来情景中均呈现上升趋势,情景排放量越大增幅越大,重现期越长增幅也越大。与极值的常态相比,极值的极端态更易受气候变化影响。     

气候变化对石羊河流域重点治理规划的影响

根据IPCC全球气候变化情景,分析了石羊河流域未来可能气候变化趋势及其对流域河川径流量的影响。利用宏观经济水资源模型,研究了不同径流变化情景对石羊河流域治理规划效果的影响。结果表明：若石羊河流域未来径流量减少15%,对流域现状发展模式和治理模式经济影响将分别为29.8%和7.2%。石羊河综合治理可提高流域应对气候变化风险的能力,减小气候变化对流域社会经济的影响。     

气候变化对石羊河流域重点治理规划的影响

 根据IPCC全球气候变化情景,分析了石羊河流域未来可能气候变化趋势及其对流域河川径流量的影响。利用宏观经济水资源模型,研究了不同径流变化情景对石羊河流域治理规划效果的影响。结果表明：若石羊河流域未来径流量减少15%,对流域现状发展模式和治理模式经济影响将分别为29.8%和7.2%。石羊河综合治理可提高流域应对气候变化风险的能力,减小气候变化对流域社会经济的影响。     

Modelling daily temperature extremes: recent climate and future changes over Europe

Probability distributions of daily maximum and minimum temperatures in a suite of ten RCMs are investigated for (1) biases compared to observations in the present day climate and (2) climate change signals compared to the simulated present day climate. The simulated inter-model differences and climate changes are also compared to the observed natural variability as reflected in some very long instrumental records. All models have been forced with driving conditions from the same global model and run for both a control period and a future scenario period following the A2 emission scenario from IPCC. We find that the bias in the fifth percentile of daily minimum temperatures in winter and at the 95th percentile of daily maximum temperature during summer is smaller than 3 (±5°C) when averaged over most (all) European sub-regions. The simulated changes in extreme temperatures both in summer and winter are larger than changes in the median for large areas. Differences between models are larger for the extremes than for mean temperatures. A comparison with historical data shows that the spread in model predicted changes in extreme temperatures is larger than the natural variability during the last centuries.     

Possible impacts of climate change on extreme weather events at local scale in south–central Canada

Synoptic weather typing and regression-based downscaling approaches have become popular in evaluating the impacts of climate change on a variety of environmental problems, particularly those involving extreme impacts. One of the reasons for the popularity of these approaches is their ability to categorize a complex set of meteorological variables into a coherent index, facilitating the projection of changes in frequency and intensity of future daily extreme weather events and/or their impacts. This paper illustrated the capability of the synoptic weather typing and regression methods to analyze climatic change impacts on a number of extreme weather events and environmental problems for south–central Canada, such as freezing rain, heavy rainfall, high-/low-streamflow events, air pollution, and human health. These statistical approaches are helpful in analyzing extreme events and projecting their impacts into the future through three major steps or analysis procedures: (1) historical simulation modeling to identify extreme weather events or their impacts, (2) statistical downscaling to provide station-scale future hourly/daily climate data, and (3) projecting changes in the frequency and intensity of future extreme weather events and their impacts under a changing climate. To realize these steps, it is first necessary to conceptualize the modeling of the meteorology, hydrology and impacts model variables of significance and to apply a number of linear/nonlinear regression techniques. Because the climate/weather validation process is critical, a formal model result verification process has been built into each of these three steps. With carefully chosen physically consistent and relevant variables, the results of the verification, based on historical observations of the outcome variables simulated by the models, show a very good agreement in all applications and extremes tested to date. Overall, the modeled results from climate change studies indicate that the frequency and intensity of future extreme weather events and their impacts are generally projected to significantly increase late this century over south–central Canada under a changing climate. The implications of these increases need be taken into consideration and integrated into policies and planning for adaptation strategies, including measures to incorporate climate change into engineering infrastructure design standards and disaster risk reduction measures. This paper briefly summarized these climate change research projects, focusing on the modeling methodologies and results, and attempted to use plain language to make the results more accessible and interesting to the broader informed audience. These research projects have been used to support decision-makers in south–central Canada when dealing with future extreme weather events under climate change.     

Observed Changes in One-in-20 Year Extremes of Canadian Surface Air Temperatures

Weather and climate extremes are often associated with substantial adverse impacts on society and the environment. Assessment of changes in extremes is of great and broad interest. This study first homogenizes daily minimum and maximum surface air temperatures recorded at 146 stations in Canada. In order to assess changes in one-in-20 year extremes (i.e., extremes with a 20-year return period) in temperature, annual maxima and minima of both daily minimum temperatures and daily maximum temperatures are derived from the homogenized daily temperature series and analyzed with a recently developed extreme value analysis approach based on a tree of generalized extreme value distributions (including stationary and non-stationary cases). The procedure is applied to estimate the changes over the period 1911 to 2010 at 115 stations, located mainly in southern Canada, and over the period 1961 to 2010 at 146 stations across Canada (including 37 stations in the North). The results show that warming is strongest for extreme low temperature and weakest for extreme high temperature and is much stronger in the Canadian Arctic than in southern Canada. Warming is stronger in winter than in summer and stronger during nighttime than daytime of the same season.     

Cold Temperature Extremes in Russia and Risks of Critical Temperature Impacts on Infrastructure Facilities

The features of changes and variability for cold temperature extremes over Russia are analyzed using observational data for the period from the middle of the 20th century. The impact is assessed that observed changes in thermal regime make on the characteristics of rare extremes which are used as standard parameters for designing infrastructure facilities. The results are interpreted in terms of the power system operation reliability. The risk assessment for critical temperature impacts indicates the important regional features of climate change effect on extreme energy loads and requirements for power capacities during the cold season.     

Climate change scenarios of precipitation extremes in Central Europe from ENSEMBLES regional climate models

The study examines future scenarios of precipitation extremes over Central Europe in an ensemble of 12 regional climate model (RCM) simulations with the 25-km resolution, carried out within the European project ENSEMBLES. We apply the region-of-influence method as a pooling scheme when estimating distributions of extremes, which consists in incorporating data from a ‘region’ (set of gridboxes) when fitting an extreme value distribution in any single gridbox. The method reduces random variations in the estimates of parameters of the extreme value distribution that result from large spatial variability of heavy precipitation. Although spatial patterns differ among the models, most RCMs simulate increases in high quantiles of precipitation amounts when averaged over the area for the late-twenty-first century (2070–2099) climate in both winter and summer. The sign as well as the magnitude of the projected change vary only little for individual parts of the distribution of daily precipitation in winter. In summer, on the other hand, the projected changes increase with the quantile of the distribution in all RCMs, and they are negative (positive) for parts of the distribution below (above) the 98% quantile if averaged over the RCMs. The increases in precipitation extremes in summer are projected in spite of a pronounced drying in most RCMs. Although a rather general qualitative agreement of the models concerning the projected changes of precipitation extremes is found in both winter and summer, the uncertainties in climate change scenarios remain large and would likely further increase considerably if a more complete ensemble of RCM simulations driven by a larger suite of global models and with a range of possible scenarios of the radiative forcing is available.     

Mediterranean climate extremes in synoptic downscaling assessments

The behaviour of precipitation and maximum temperature extremes in the Mediterranean area under climate change conditions is analysed in the present study. In this context, the ability of synoptic downscaling techniques in combination with extreme value statistics for dealing with extremes is investigated. Analyses are based upon a set of long-term station time series in the whole Mediterranean area. At first, a station-specific ensemble approach for model validation was developed which includes (1) the downscaling of daily precipitation and maximum temperature values from the large-scale atmospheric circulation via analogue method and (2) the fitting of extremes by generalized Pareto distribution (GPD). Model uncertainties are quantified as confidence intervals derived from the ensemble distributions of GPD-related return values and described by a new metric called “ratio of overlapping”. Model performance for extreme precipitation is highest in winter, whereas the best models for maximum temperature extremes are set up in autumn. Valid models are applied to a 30-year period at the end of the twenty-first century (2070–2099) by means of ECHAM5/MPI-OM general circulation model data for IPCC SRES B1 scenario. The most distinctive future changes are observed in autumn in terms of a strong reduction of precipitation extremes in Northwest Iberia and the Northern Central Mediterranean area as well as a simultaneous distinct increase of maximum temperature extremes in Southwestern Iberia and the Central and Southeastern Mediterranean regions. These signals are checked for changes in the underlying dynamical processes using extreme-related circulation classifications. The most important finding connected to future changes of precipitation extremes in the Northwestern Mediterranean area is a reduction of southerly displaced deep North Atlantic cyclones in 2070–2099 as associated with a strengthened North Atlantic Oscillation. Thus, the here estimated future changes of extreme precipitation are in line with the discourse about the influence of North Atlantic circulation variability on the changing climate in Europe.     

Climate-change effects on extreme precipitation in central Europe: uncertainties of scenarios based on regional climate models

Observations as well as most climate model simulations are generally in accord with the hypothesis that the hydrologic cycle should intensify and become highly volatile with the greenhouse-gas-induced climate change, although uncertainties of these projections as well as the spatial and seasonal variability of the changes are much larger than for temperature extremes. In this study, we examine scenarios of changes in extreme precipitation events in 24 future climate runs of ten regional climate models, focusing on a specific area of the Czech Republic (central Europe) where complex orography and an interaction of other factors governing the occurrence of heavy precipitation events result in patterns that cannot be captured by global models. The peaks-over-threshold analysis with increasing threshold censoring is applied to estimate multi-year return levels of daily rainfall amounts. Uncertainties in scenarios of changes for the late 21st century related to the inter-model and within-ensemble variability and the use of the SRES-A2 and SRES-B2 greenhouse gas emission scenarios are evaluated. The results show that heavy precipitation events are likely to increase in severity in winter and (with less agreement among models) also in summer. The inter-model and intra-model variability and related uncertainties in the pattern and magnitude of the change is large, but the scenarios tend to agree with precipitation trends recently observed in the area, which may strengthen their credibility. In most scenario runs, the projected change in extreme precipitation in summer is of the opposite sign than a change in mean seasonal totals, the latter pointing towards generally drier conditions in summer. A combination of enhanced heavy precipitation amounts and reduced water infiltration capabilities of a dry soil may severely increase peak river discharges and flood-related risks in this region.     

Downscaling daily precipitation over the Yellow River source region in China: a comparison of three statistical downscaling methods

Three statistical downscaling methods are compared with regard to their ability to downscale summer (June–September) daily precipitation at a network of 14 stations over the Yellow River source region from the NCEP/NCAR reanalysis data with the aim of constructing high-resolution regional precipitation scenarios for impact studies. The methods used are the Statistical Downscaling Model (SDSM), the Generalized LInear Model for daily CLIMate (GLIMCLIM), and the non-homogeneous Hidden Markov Model (NHMM). The methods are compared in terms of several statistics including spatial dependence, wet- and dry spell length distributions and inter-annual variability. In comparison with other two models, NHMM shows better performance in reproducing the spatial correlation structure, inter-annual variability and magnitude of the observed precipitation. However, it shows difficulty in reproducing observed wet- and dry spell length distributions at some stations. SDSM and GLIMCLIM showed better performance in reproducing the temporal dependence than NHMM. These models are also applied to derive future scenarios for six precipitation indices for the period 2046–2065 using the predictors from two global climate models (GCMs; CGCM3 and ECHAM5) under the IPCC SRES A2, A1B and B1scenarios. There is a strong consensus among two GCMs, three downscaling methods and three emission scenarios in the precipitation change signal. Under the future climate scenarios considered, all parts of the study region would experience increases in rainfall totals and extremes that are statistically significant at most stations. The magnitude of the projected changes is more intense for the SDSM than for other two models, which indicates that climate projection based on results from only one downscaling method should be interpreted with caution. The increase in the magnitude of rainfall totals and extremes is also accompanied by an increase in their inter-annual variability.     

Estimating the Impact of Global Change on Flood and Drought Risks in Europe: A Continental, Integrated Analysis

Most studies on the impact of climate change on regional water resources focus on long-term average flows or mean water availability, and they rarely take the effects of altered human water use into account. When analyzing extreme events such as floods and droughts, the assessments are typically confined to smaller areas and case studies. At the same time it is acknowledged that climate change may severely alter the risk of hydrological extremes over large regional scales, and that human water use will put additional pressure on future water resources. In an attempt to bridge these various aspects, this paper presents a first-time continental, integrated analysis of possible impacts of global change (here defined as climate and water use change) on future flood and drought frequencies for the selected study area of Europe. The global integrated water model WaterGAP is evaluated regarding its capability to simulate high and low-flow regimes and is then applied to calculate relative changes in flood and drought frequencies. The results indicate large ‘critical regions’ for which significant changes in flood or drought risks are expected under the proposed global change scenarios. The regions most prone to a rise in flood frequencies are northern to northeastern Europe, while southern and southeastern Europe show significant increases in drought frequencies. In the critical regions, events with an intensity of today's 100-year floods and droughts may recur every 10–50 years by the 2070s. Though interim and preliminary, and despite the inherent uncertainties in the presented approach, the results underpin the importance of developing mitigation and adaptation strategies for global change impacts on a continental scale.     

USE OF A STOCHASTIC WEATHER GENERATOR IN THE DEVELOPMENT OF CLIMATE CHANGE SCENARIOS

Climate change scenarios with a high spatial and temporal resolution are required in the evaluation of the effects of climate change on agricultural potential and agricultural risk. Such scenarios should reproduce changes in mean weather characteristics as well as incorporate the changes in climate variability indicated by the global climate model (GCM) used. Recent work on the sensitivity of crop models and climatic extremes has clearly demonstrated that changes in variability can have more profound effects on crop yield and on the probability of extreme weather events than simple changes in the mean values. The construction of climate change scenarios based on spatial regression downscaling and on the use of a local stochastic weather generator is described. Regression downscaling translated the coarse resolution GCM grid-box predictions of climate change to site-specific values. These values were then used to perturb the parameters of the stochastic weather generator in order to simulate site-specific daily weather data. This approach permits the incorporation of changes in the mean and variability of climate in a consistent and computationally inexpensive way. The stochastic weather generator used in this study, LARS-WG, has been validated across Europe and has been shown to perform well in the simulation of different weather statistics, including those climatic extremes relevant to agriculture. The importance of downscaling and the incorporation of climate variability are demonstrated at two European sites where climate change scenarios were constructed using the UK Met. Office high resolution GCM equilibrium and transient experiments.     

Projected shifts of wine regions in response to climate change

This research simulates the impact of climate change on the distribution of the most important European wine regions using a comprehensive suite of spatially informative layers, including bioclimatic indices and water deficit, as predictor variables. More specifically, a machine learning approach (Random Forest, RF) was first calibrated for the present period and applied to future climate conditions as simulated by HadCM3 General Circulation Model (GCM) to predict the possible spatial expansion and/or shift in potential grapevine cultivated area in 2020 and 2050 under A2 and B2 SRES scenarios. Projected changes in climate depicted by the GCM and SRES scenarios results in a progressive warming in all bioclimatic indices as well as increasing water deficit over the European domain, altering the climatic profile of each of the grapevine cultivated areas. The two main responses to these warmer and drier conditions are 1) progressive shifts of existing grapevine cultivated area to the north–northwest of their original ranges, and 2) expansion or contraction of the wine regions due to changes in within region suitability for grapevine cultivation. Wine regions with climatic conditions from the Mediterranean basin today (e.g., the Languedoc, Provence, Côtes Rhône Méridionales, etc.) were shown to potentially shift the most over time. Overall the results show the potential for a dramatic change in the landscape for winegrape production in Europe due to changes in climate.