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.     

Future climate resources for tourism in Europe based on the daily Tourism Climatic Index

Climate is an important resource for many types of tourism. One of several metrics for the suitability of climate for sightseeing is Mieczkowski’s “Tourism Climatic Index” (TCI), which summarizes and combines seven climate variables. By means of the TCI, we analyse the present climate resources for tourism in Europe and projected changes under future climate change. We use daily data from five regional climate models and compare the reference period 1961–1990 to the A2 scenario in 2071–2100. A comparison of the TCI based on reanalysis data and model simulations for the reference period shows that current regional climate models capture the important climatic patterns. Currently, climate resources are best in Southern Europe and deteriorate with increasing latitude and altitude. With climate change the latitudinal band of favourable climate is projected to shift northward improving climate resources in Northern and Central Europe in most seasons. Southern Europe’s suitability for sightseeing tourism drops strikingly in the summer holiday months but is partially compensated by considerable improvements between October and April.     

Continental vegetation as a dynamic component of a global climate model: a preliminary assessment

A simplified vegetation distribution prediction scheme is used in combination with the Biosphere-Atmosphere Transfer Scheme (BATS) and coupled to a version of the NCAR Community Climate Model (CCM1) which includes a mixed-layer ocean. Employed in an off-line mode as a diagnostic tool, the scheme predicts a slightly darker and slightly rougher continental surface than when BATS' prescribed vegetation classes are used. The impact of tropical deforestation on regional climates, and hence on diagnosed vegetation, differs between South America and S.E. Asia. In the Amazon, the climatic effects of removing all the tropical forest are so marked that in only one of the 18 deforested grid elements could the new climate sustain tropical forest vegetation whereas in S.E. Asia in seven of the 9 deforested elements the climate could continue to support tropical forest. Following these off-line tests, the simple vegetation scheme has been coupled to the GCM as an interactive (or two-way) submodel for a test integration lasting 5.6 yr. It is found to be a stable component of the global climate system, producing only ~ 3% (absolute) interannual changes in the predicted percentages of continental vegetation, together with globally-averaged continental temperature increases of up to + 1.5 °C and evaporation increases of 0 to 5 W m^–2 and no discernible trends over the 67 months of integration. On the other hand, this interactive land biosphere causes regional-scale temperature differences of ± 10 °C and commensurate disturbances in other climatic parameters. Tuning, similar to the q-flux schemes used for ocean models, could improve the simulation of the present-day surface climate but, in the longer term, it will be important to focus on predicting the characteristics of the continental surface rather than simple vegetation classes. The coupling scheme will also have to allow for vegetation responses occurring over longer timescales so that the coupled system is buffered from sudden shocks.     

A weather-resolving index for assessing the impact of climate change on tourism related climate resources

This study develops and tests a Modified Climate Index for Tourism (MCIT) utilizing more than 50 years of hourly temperature, wind and significant weather data from contrasting climatic regions, Florida and Alaska. The index measures climate as a tourism resource by combining several tourism-related climate elements. It improves previous methods by incorporating variables that are more relevant to tourism activities, by addressing the overriding nature of some conditions, and by incorporating hourly observations rather than simple daily averages. The MCIT was tested using hourly weather observations from King Salmon, Alaska and Orlando, Florida. The results show that average temperature alone is not sufficient to represent tourism climate resources. For example, at both the Florida and Alaskan sites, showers and thunderstorms are more limiting factors than temperature during much of the year. When applied to past climate data, the proposed MCIT generates meaningful results that capture tourism-related climate variations and trends, including (a) the increasingly favorable tourism conditions in Alaska due to a lengthening of the warm season and (b) a decrease of ideal climatic conditions in central Florida due to the increased summer temperatures. Thus, the index has the potential to become a useful quantitative tool to be used in conjunction with climate models to predict the nature and magnitude of the impact of anticipated climate changes on tourism.     

Spatial changes of Extended De Martonne climatic zones affected by climate change in Iran

In order to better understand the effect associated with global climate change on Iran’s climate condition, it is important to quantify possible shifts in different climatic types in the future. To this end, monthly mean minimum and maximum temperature, and precipitation from 181 synoptic meteorological stations (average 1970–2005) have been collected from the meteorological organization of Iran. In this paper, to study spatial changes of Iran’s climatic zones affected by climate changes, Extended De Martonne’s classification (originally formulated by De Martonne and extended by Khalili (1992)) was used. Climate change scenarios were simulated in two future climates (average conditions during the 2050s and the 2080s) under each of the SRES A1B and A2, for the CSIRO-MK3, HadCM3, and CGCM3 climate models. Coarse outputs of GCMs were downscaled by delta method. We produced all maps for three time periods (one for the current and two for the future) according to Extended De Martonne’s classification. Finally, for each climatic zone, changes between the current and the future were compared. As the main result, simulated changes indicate shifts to warmer and drier zones. For example, in the current, extra arid-cold (A1.1m2) climate is covering the largest area of the country (21.4 %), whereas in both A1B and A2 scenarios in the 2050s and the 2080s, extra arid-moderate (A1.1m3) and extra arid-warm (A1.1m4) will be the climate and will occupy the largest area of the country, about 21 and 38 %, respectively. This analysis suggests that the global climate change will have a profound effect on the future distribution of severe aridity in Iran.     

Climate Change and Global Wine Quality

From 1950 to 1999 the majority of the world's highest quality wine-producing regions experienced growing season warming trends. Vintage quality ratings during this same time period increased significantly while year-to-year variation declined. While improved winemaking knowledge and husbandry practices contributed to the better vintages it was shown that climate had, and will likely always have, a significant role in quality variations. This study revealed that the impacts of climate change are not likely to be uniform across all varieties and regions. Currently, many European regions appear to be at or near their optimum growing season temperatures, while the relationships are less defined in the New World viticulture regions. For future climates, model output for global wine producing regions predicts an average warming of 2 ^∘C in the next 50 yr. For regions producing high-quality grapes at the margins of their climatic limits, these results suggest that future climate change will exceed a climatic threshold such that the ripening of balanced fruit required for existing varieties and wine styles will become progressively more difficult. In other regions, historical and predicted climate changes could push some regions into more optimal climatic regimes for the production of current varietals. In addition, the warmer conditions could lead to more poleward locations potentially becoming more conducive to grape growing and wine production.     

Rural livelihoods and climate variability in Ningxia, Northwest China

This study addresses the role of climate variability in the livelihoods of agricultural communities in Ningxia, Northwest China. Data sources comprise meteorological observations and official reports, complemented by questionnaires and focus group discussions designed around a livelihoods framework. Sample villages were located in three different agricultural systems: irrigated, mixed irrigated/grazing, and rainfed. Much of Ningxia is perennially dry and this is a significant limiting factor to agricultural production in the region, exacerbated by drought and buffered by irrigation mainly supplied from the Yellow River. Climate observations show stable temperatures from the 1950s to the 1980s followed by a positive trend (0.38°C/decade 1961–2010). Precipitation shows very modest trends and low decadal variability. Recent climate variability, particularly a drought from 2004–2006, was perceived to have had a significant effect on agricultural production and access to water, but it was not the only challenge respondents had faced. Susceptibility to drought was higher in the mixed irrigated and grazing and rainfed areas, due to farmers’ greater exposure to climatic hazards and because a higher proportion of their income originated from farming activities. Respondents were using a wide range of measures to retain and enhance soil moisture and maintain agricultural production. The discussion examines challenges in disentangling the role of climate within rapidly changing livelihood systems.     

青藏高原东北缘山地农户对气候变化的感知及适应策略——以湟水中游为例

以青藏高原东北缘山地地区不同海拔高度地理单元村落的农户为调查对象,进行气候变化、气象灾害的感知及适应策略等调查,采用感知强度公式及专家打分法分析农户气候变化感知以及所采用的适应策略,结果显示：1961—2013年湟水中游气候变化整体趋于暖干化,有84%的农户认为气候变暖,并对其生活造成了严重的影响;在不同海拔高度上的地理单元,农户对气象灾害的感知有明显差异,川水地区农户对沙尘的感知最强,浅山地区农户对虫害的感知最强,而脑山地区农户对连阴雨的感知最强;不同海拔高度的农户对适应策略的选择不同,川水地区农户主要采取“生产性+生活性+保障性”组合适应策略;浅山地区农户主要采取“生产性+生活性”组合适应策略;而脑山地区的农户则主要采取单一的“生产性”适应策略来应对气候变化所带来的影响。     

Application of the K?ppen classification for climatic zoning in the state of Minas Gerais, Brazil

The knowledge of the climatic conditions of a region is crucial for its agricultural development. It is also extremely important for understanding the fact that certain cultures have to develop under prevailing temperature and humidity conditions and assist in the adoption of a suitable irrigation technique, as well as its management and operationalization. The K?ppen system of climate classification is widely used for the identification of homogeneous climate zones as it considers only rainfall and temperature as the meteorological elements for classification. For this study, we used climatic databases of rainfall and temperature in a raster format, with a spatial resolution of 30″ of arc (an approximate area of 0.86?km²?pixel^?1), from 1961 to 1990. Through geoprocessing techniques, we obtained a map of climatic classification for the state of Minas Gerais. We found that the state has the following three major climatic groups: A, B and C, which correspond to tropical rainy, dry and warm temperate climates, respectively. The climate classes obtained were Aw, Am, BSh, Cwa and Cwb, with Aw, Cwa and Cwb classes occupying 99.89% of the territorial area of the state. The validation of the results showed a satisfactory agreement, with 93.75% reliability.     

天山北坡酿酒葡萄成熟期降雨特征及其影响分析

掌握新疆天山北坡酿酒葡萄成熟期降雨特征，对科学制定酿酒葡萄种植规划，采取趋利避害的生产管理技术措施具有实际意义。基于天山北坡35个气象站1961-2016年8-9月逐日降雨资料，采用线性趋势法和ArcGIS空间插值技术，对过去56a该区域酿酒葡萄成熟期（8-9月）降雨日数、降雨量、连阴雨天气次数、连阴雨天气降雨强度等要素的时空变化进行研究，并对照前人关于该区域酿酒葡萄种植气候适宜性区划成果，对酿酒葡萄不同适宜种植区葡萄成熟期降雨特征及其影响进行分析。结果表明：天山北坡酿酒葡萄成熟期（8-9月）降雨日数、降雨量、连阴雨天气次数、降雨强度、大量以上降雨日数的空间分布均总体呈现随海拔高度的升高而增加的特点。1961-2016年，研究区酿酒葡萄成熟期除降雨日数总体以-1.16d·10a-1的倾向率极显著 (P=0.001)减少，大量以上降雨日数以0.07d·10a-1的倾向率显著 (P=0.05)增多外，降雨量、连阴雨天气次数、连阴雨天气日数及其降雨量变化趋势均不显著。天山北坡酿酒葡萄种植气候最适宜和适宜区葡萄成熟期的降雨量、降雨日数、连阴雨天气次数、连阴雨天气日数及其降雨量都很小，期间总降雨量大多不足40 mm、降雨日数少于20 d、大量以上降雨日数不足1 d、连阴雨天气次数少于0.3次、连阴雨天气日数少于5d、连阴雨天气降雨量不足25mm，该分区降雨量以及连阴雨天气少，对提高酿酒葡萄产量和品质十分有利。酿酒葡萄次适宜种植区葡萄成熟期降雨天气稍多，降雨量40～90 mm、降雨日数20～25 d、大量以上降雨日数1～2 d、连阴雨天气次数0.3～1.0次、连阴雨天气日数5～8 d、连阴雨天气降雨量25～40 mm，对酿酒葡萄产量和品质有一定不利影响。天山北坡8-9月降雨量90 mm以上、降雨日数30d以上、大量以上降雨日数2d以上、连阴雨天气次数多于1.0次、连阴雨天气日数8d以上、连阴雨天气降雨量40 mm以上的区域均在海拔1500m以上的山区，该区域恰恰也是酿酒葡萄不适宜种植区，因此对酿酒葡萄无影响。综上所述，新疆天山北坡酿酒葡萄种植区尤其是适宜及最适宜种植区葡萄成熟期的降雨量、降雨日数、连阴雨天气次数和日数都较小，且近56a稳定少变，因此，对该区域酿酒葡萄生产的影响较小。     

未来气候变化对东北玉米品种布局的影响

为探求未来气候变化对我国东北玉米品种布局的影响,基于玉米生产潜力和气候资源利用率,结合区域气候模式输出的2011—2099年RCP_4.5,RCP_8.5两种气候背景气象资料和1961—2010年我国东北地区91个气象站的观测数据,分析了未来气候变化情况下,东北玉米品种布局、生产潜力、气候资源利用率的时空变化。结果表明:未来东北地区玉米可种植边界北移东扩,南部为晚熟品种,新扩展区域以早熟品种为主,不能种植区域减少。未来玉米生产潜力为南高北低,增加速率均高于历史情景,水分适宜度最低,而历史情景下温度是胁迫玉米生产的关键因子。未来东北玉米对气候资源利用率整体下降,其中RCP8.5情景利用率最低。     

Key climate indices in Switzerland; expected changes in a future climate

Climate indices facilitate the interpretation of expected climate change impacts for many sectors in society, economy, and ecology. The new localized data set of climatic change signals for temperature and precipitation presented by Zubler et al. (Clim Change, 2013) is applied for an analysis of frequently used climate indices in Switzerland. The indices considered are: number of summer days and tropical nights, growing season length, number of frost days and ice days, heating and cooling degree days, and the number of days with fresh snow. For the future periods 2020-49, 2045-74 and 2070–2099 the indices are computed using a delta-change approach based on the reference period 1980–2009 for the emission scenarios A1B, A2, and RCP3PD. The scenario data suggest the following relevant findings: (1) a doubling of the number of summer days by the end of the century under the scenarios A1B and A2, (2) an appearance of tropical nights even above 1500 m asl, (3) a possible reduction of the number of frost days by more than 3 months at altitudes higher than 2500 m asl, (4) a decline of heating degree days by about 30 % until the end of the century, and (5) the near disappearance of days with fresh snow at low altitudes. It is also shown that the end-of-the-century projections of all indices strongly depend on the chosen emission scenario.     

近43年来黑龙江气候变化对农作物产量影响的模拟研究

从近43年来黑龙江省各地气候变化趋势的角度出发, 利用黑龙江省1961—2003年逐日气象资料, 采用世界粮食研究模型 (WOFOST) 和气候变化趋势的数学分析方法, 计算并分析了近43年来黑龙江省各地各主要作物模拟产量变化趋势的空间特征和各地气候要素变化趋势的空间特征, 讨论了气候变化趋势对主要粮食作物模拟产量变化趋势的影响。结果表明:气候变化趋势的空间差异对各主要作物模拟产量变化趋势的空间分布具有重要影响, 但不同作物影响不同。近43年来黑龙江省玉米模拟产量变化趋势增加, 平均增加幅度为4.81%/10a, 气温变化趋势的增高是其模拟产量变化趋势增加的主要气候因素。黑龙江省大豆模拟产量变化趋势总体上呈降低趋势, 平均降低幅度为1.52%/10a;气候变化趋势对北部和南部区域的大豆模拟产量变化趋势作用不同, 气温变化趋势的增高是北部大豆优势种植区域模拟产量变化趋势增加的主要气候因素, 气温和降水量的相应变化趋势是南部大豆种植区域模拟产量变化趋势降低的主要气候因素。     

The impacts of climate change on agricultural production systems in China

Climate change can bring positive and negative effects on Chinese agriculture, but negative impacts tend to dominate. The annual mean surface temperature has risen about 0.5–0.8 °C. The precipitation trends have not been identified during the past 100 years in China, although the frequency and intensity of extreme weather/climate events have increased, especially of drought. Water scarcity, more frequent and serious outbreaks of insects and diseases, and soil degradation caused by climate change have impacted agro-environmental conditions. However, temperature rise prolonged the crop growth seasons and cold damages have reduced in Northeast China. The projection of climate change indicates that the surface temperature will continue to increase with about 3.9 to 6.0 °C and precipitation is expected to increase by 9 to 11 % at the end of 21st century in China. Climate warming will provide more heat and as a consequence, the boundary of the triple-cropping system (TCS) will extend northwards by as much as 200 to 300 km, from the Yangtze River Valley to the Yellow River Basin, and the current double-cropping system (DCS) will move to the central part of China, into the current single cropping system (SCS) area which will decrease in SCS surface area of 23.1 % by 2050. Climate warming will also affect the optimum location for the cultivation of China’s main crop varieties. If no measures are taken to adapt to climate changes, compared with the potential yield in 1961–1990, yields of irrigated wheat, corn and rice are projected to decrease by 2.2–6.7 %, 0.4 %–11.9 % and 4.3–12.4 % respectively in the 2050s. Climate warming will enhance potential evaporation and reduce the availability of soil moisture, thus causing a greater need for agricultural irrigation, intensifying the conflict between water supply and demand, especially in arid and semi-arid areas of China. With adequate irrigation, the extent of the reduction in yield of China’s corn and wheat can be improved by 5 % to 15 %, and rice by 5 % or so than the potential yield in 1961–1990. Adaptive measures can reduce the agricultural loss under climate change. If effective measures are taken in a timely way, then climate change in the next 30–50 years will not have a significant influence on China’s food security.     

不同气候适宜区的橡胶产胶潜力研究

基于2000-2015年MODISNPP遥感数据,利用橡胶产胶潜力模型得到了中国橡胶主产区年橡胶产胶潜力;利用橡胶树种植气候适宜性区划的研究成果,得到了中国橡胶主产区橡胶气候适宜区分布;在此基础上分析了不同气候适宜区橡胶产胶潜力的差异及不同高程上橡胶产胶能力的差异.结果表明:(1)中国橡胶主产区中,云南橡胶产胶潜力最高...     

Relationship between projected changes in future climatic suitability and demographic and functional traits of forest tree species in Spain

The response of plant species to future climate conditions is probably dependent on their ecological characteristics, including climatic niche, demographic rates and functional traits. Using forest inventory data from 27 dominant woody species in Spanish forests, we explore the relationships between species characteristics and projected changes in their average climatic suitability (occurrence of suitable climatic conditions for a species in a given territory) obtained by empirical niche-based models, under a business-as-usual climate change scenario (A1, HadCM3, 2001–2100). We hypothesize that most species will suffer a decline in climatic suitability, with a less severe for species (i) currently living in more arid climates or exhibiting a broader current climatic niche; (ii) with higher current growth rates; (iii) with functional traits related to resistance to water deficits. The analysis confirm our hypothesis since apart from a few Mediterranean species, most species decrease their climatic suitability in the region under future climate, characterized by increased aridity. Also, species living in warmer locations or under a wider range of climatic conditions tend to experience less decrease in climatic suitability. As hypothesized, a positive relationship was detected between current relative growth rates and increase in future climatic suitability. Nevertheless, current tree mortality did not correlate with changes in future climatic suitability. In contrast with our hypothesis, functional traits did not show a clear relationship with changes in climate suitability; instead species often presented idiosyncratic responses that, in some cases, could reflect past management. These results suggest that the extrapolation of species performance to future climatic scenarios based on current patterns of dominance is constrained by factors other than species autoecology, particularly human activity.     

两个30年气候平均值的差异及其对气候业务的影响

对陕西短期气候预测业务使用的39个气象站气候要素1971～2000年平均值与1961～1990年平均值进行比较,发现大部分地区年平均气温升高,晴天日数增加;年降水量、阴天日数、降水日数、年日照时数减少;年大风日数、沙尘暴日数、冰雹日数、雷暴日数减少等。把两个平均值放在长序列中分析,发现某些气象要素最近的气候平均值的差值在20世纪80～90年代期间的5～6个气候平均值每两个相邻平均值的差值中是最大的,说明陕西20世纪90年代气候较60年代干燥、温暖,且90年代气温高、降水少的特点十分突出。还对某些要素平均值改变对气候影响评价、气候预测业务产生的影响进行简要分析。     

Uncertainties in regional climate change prediction: a regional analysis of ensemble simulations with the HADCM2 coupled AOGCM

We analyze ensembles (four realizations) of historical and future climate transient experiments carried out with the coupled atmosphere-ocean general circulation model (AOGCM) of the Hadley Centre for Climate Prediction and Research, version HADCM2, with four scenarios of greenhouse gas (GHG) and sulfate forcing. The analysis focuses on the regional scale, and in particular on 21 regions covering all land areas in the World (except Antarctica). We examine seasonally averaged surface air temperature and precipitation for the historical period of 1961–1990 and the future climate period of 2046–2075. Compared to previous AOGCM simulations, the HADCM2 model shows a good performance in reproducing observed regional averages of summer and winter temperature and precipitation. The model, however, does not reproduce well observed interannual variability. We find that the uncertainty in regional climate change predictions associated with the spread of different realizations in an ensemble (i.e. the uncertainty related to the internal model variability) is relatively low for all scenarios and regions. In particular, this uncertainty is lower than the uncertainty due to inter-scenario variability and (by comparison with previous regional analyses of AOGCMs) with inter-model variability. The climate biases and sensitivities found for different realizations of the same ensemble were similar to the corresponding ensemble averages and the averages associated with individual realizations of the same ensemble did not differ from each other at the 5% confidence level in the vast majority of cases. These results indicate that a relatively small number of realizations (3 or 4) is sufficient to characterize an AOGCM transient climate change prediction at the regional scale. Received: 12 January 1998 / Accepted: 7 July 1999     

Mean and variance evolutions of the hot and cold temperatures in Europe

In this paper, we examine the trends of temperature series in Europe, for the mean as well as for the variance in hot and cold seasons. To do so, we use as long and homogenous series as possible, provided by the European Climate Assessment and Dataset project for different locations in Europe, as well as the European ENSEMBLES project gridded dataset and the ERA40 reanalysis. We provide a definition of trends that we keep as intrinsic as possible and apply non-parametric statistical methods to analyse them. Obtained results show a clear link between trends in mean and variance of the whole series of hot or cold temperatures: in general, variance increases when the absolute value of temperature increases, i.e. with increasing summer temperature and decreasing winter temperature. This link is reinforced in locations where winter and summer climate has more variability. In very cold or very warm climates, the variability is lower and the link between the trends is weaker. We performed the same analysis on outputs of six climate models proposed by European teams for the 1961–2000 period (1950–2000 for one model), available through the PCMDI portal for the IPCC fourth assessment climate model simulations. The models generally perform poorly and have difficulties in capturing the relation between the two trends, especially in summer.     

Uncertainties in projected impacts of climate change on European agriculture and terrestrial ecosystems based on scenarios from regional climate models

The uncertainties and sources of variation in projected impacts of climate change on agriculture and terrestrial ecosystems depend not only on the emission scenarios and climate models used for projecting future climates, but also on the impact models used, and the local soil and climatic conditions of the managed or unmanaged ecosystems under study. We addressed these uncertainties by applying different impact models at site, regional and continental scales, and by separating the variation in simulated relative changes in ecosystem performance into the different sources of uncertainty and variation using analyses of variance. The crop and ecosystem models used output from a range of global and regional climate models (GCMs and RCMs) projecting climate change over Europe between 1961–1990 and 2071–2100 under the IPCC SRES scenarios. The projected impacts on productivity of crops and ecosystems included the direct effects of increased CO₂ concentration on photosynthesis. The variation in simulated results attributed to differences between the climate models were, in all cases, smaller than the variation attributed to either emission scenarios or local conditions. The methods used for applying the climate model outputs played a larger role than the choice of the GCM or RCM. The thermal suitability for grain maize cultivation in Europe was estimated to expand by 30–50% across all SRES emissions scenarios. Strong increases in net primary productivity (NPP) (35–54%) were projected in northern European ecosystems as a result of a longer growing season and higher CO₂ concentrations. Changing water balance dominated the projected responses of southern European ecosystems, with NPP declining or increasing only slightly relative to present-day conditions. Both site and continental scale models showed large increases in yield of rain-fed winter wheat for northern Europe, with smaller increases or even decreases in southern Europe. Site-based, regional and continental scale models showed large spatial variations in the response of nitrate leaching from winter wheat cultivation to projected climate change due to strong interactions with soils and climate. The variation in simulated impacts was smaller between scenarios based on RCMs nested within the same GCM than between scenarios based on different GCMs or between emission scenarios.