Mean, interannual variability and trends in a regional climate change experiment over Europe. II: climate change scenarios (2071–2100)

We present an analysis of climate change over Europe as simulated by a regional climate model (RCM) nested within time-slice atmospheric general circulation model (AGCM) experiments. Changes in mean and interannual variability are discussed for the 30-year period of 2071–2100 with respect to the present day period of 1961–1990 under forcing from the A2 and B2 IPCC emission scenarios. In both scenarios, the European region undergoes substantial warming in all seasons, in the range of 1–5.5°C, with the warming being 1–2°C lower in the B2 than in the A2 scenario. The spatial patterns of warming are similar in the two scenarios, with a maximum over eastern Europe in winter and over western and southern Europe in summer. The precipitation changes in the two scenarios also show similar spatial patterns. In winter, precipitation increases over most of Europe (except for the southern Mediterranean regions) due to increased storm activity and higher atmospheric water vapor loadings. In summer, a decrease in precipitation is found over most of western and southern Europe in response to a blocking-like anticyclonic circulation over the northeastern Atlantic which deflects summer storms northward. The precipitation changes in the intermediate seasons (spring and fall) are less pronounced than in winter and summer. Overall, the intensity of daily precipitation events predominantly increases, often also in regions where the mean precipitation decreases. Conversely the number of wet days decreases (leading to longer dry periods) except in the winter over western and central Europe. Cloudiness, snow cover and soil water content show predominant decreases, in many cases also in regions where precipitation increases. Interannual variability of both temperature and precipitation increases substantially in the summer and shows only small changes in the other seasons. A number of statistically significant regional trends are found throughout the scenario simulations, especially for temperature and for the A2 scenario. The results from the forcing AGCM simulations and the nested RCM simulations are generally consistent with each other at the broad scale. However, significant differences in the simulated surface climate changes are found between the two models in the summer, when local physics processes are more important. In addition, substantial fine scale detail in the RCM-produced change signal is found in response to local topographical and coastline features.     

Interdecadal climate variability in the subpolar North Atlantic

The statistical relationships between various components of the subpolar North Atlantic air-sea-ice climate system are reexamined in order to investigate potential processes involved in interdecadal climate variability. It is found that sea surface temperature anomalies concentrated in the Labrador Sea region have a strong impact upon atmospheric sea level pressure anomalies over Greenland, which in turn influence the transport of freshwater and ice anomalies out of the Arctic Ocean, via Fram Strait. These freshwater and ice anomalies are advected around the subpolar gyre into the Labrador Sea affecting convection and the formation of Labrador Sea Water. This has an impact upon the transport of North Atlantic Current water into the subpolar gyre and thus, also upon sea surface temperatures in the region. An interdecadal negative feedback loop is therefore proposed as an internal source of climate variability within the subpolar North Atlantic. Through the lags associated with the correlations between different climatic components, observed horizontal advection time scales, and the use of Boolean delay equation models, the time scale for one cycle of this feedback loop is determined to have a period of about 21 years.     

Forest fire danger projections in the Mediterranean using ENSEMBLES regional climate change scenarios

We present future fire danger scenarios for the countries bordering the Mediterranean areas of Europe and north Africa building on a multi-model ensemble of state-of-the-art regional climate projections from the EU-funded project ENSEMBLES. Fire danger is estimated using the Canadian Forest Fire Weather Index (FWI) System and a related set of indices. To overcome some of the limitations of ENSEMBLES data for their application on the FWI System—recently highlighted in a previous study by Herrera et al. (Clim Chang 118:827–840, 2013)—we used an optimal proxy variable combination. A robust assessment of future fire danger projections is undertaken by disentangling the climate change signal from the uncertainty derived from the multi-model ensemble, unveiling a positive signal of fire danger potential over large areas of the Mediterranean. The increase in the fire danger signal is accentuated towards the latest part of the transient period, thus pointing to an elevated fire potential in the region with time. The fire-climate links under present and future conditions are further discussed building upon observed climate data and burned area records along a representative climatic gradient within the study region.     

The spread amongst ENSEMBLES regional scenarios: regional climate models, driving general circulation models and interannual variability

Various combinations of thirteen regional climate models (RCM) and six general circulation models (GCM) were used in FP6-ENSEMBLES. The response to the SRES-A1B greenhouse gas concentration scenario over Europe, calculated as the difference between the 2021–2050 and the 1961–1990 means can be viewed as an expected value about which various uncertainties exist. Uncertainties are measured here by variance explained for temperature and precipitation changes over eight European sub-areas. Three sources of uncertainty can be evaluated from the ENSEMBLES database. Sampling uncertainty is due to the fact that the model climate is estimated as an average over a finite number of years (30) despite a non-negligible interannual variability. Regional model uncertainty is due to the fact that the RCMs use different techniques to discretize the equations and to represent sub-grid effects. Global model uncertainty is due to the fact that the RCMs have been driven by different GCMs. Two methods are presented to fill the many empty cells of the ENSEMBLES RCM?×?GCM matrix. The first one is based on the same approach as in FP5-PRUDENCE. The second one uses the concept of weather regimes to attempt to separate the contribution of the GCM and the RCM. The variance of the climate response is analyzed with respect to the contribution of the GCM and the RCM. The two filling methods agree that the main contributor to the spread is the choice of the GCM, except for summer precipitation where the choice of the RCM dominates the uncertainty. Of course the implication of the GCM to the spread varies with the region, being maximum in the South-western part of Europe, whereas the continental parts are more sensitive to the choice of the RCM. The third cause of spread is systematically the interannual variability. The total uncertainty about temperature is not large enough to mask the 2021–2050 response which shows a similar pattern to the one obtained for 2071–2100 in PRUDENCE. The uncertainty about precipitation prevents any quantitative assessment on the response at grid point level for the 2021–2050 period. One can however see, as in PRUDENCE, a positive response in winter (more rain in the scenario than in the reference) in northern Europe and a negative summer response in southern Europe.     

Interannual variability and expected regional climate change over North America

This study aims to analyse the interannual variability simulated by several regional climate models (RCMs), and its potential for disguising the effect of seasonal temperature increases due to greenhouse gases. In order to accomplish this, we used an ensemble of regional climate change projections over North America belonging to the North American Regional Climate Change Program, with an additional pair of 140-year continuous runs from the Canadian RCM. We find that RCM-simulated interannual variability shows important departures from observed one in some cases, and also from the driving models’ variability, while the expected climate change signal coincides with estimations presented in previous studies. The continuous runs from the Canadian RCM were used to illustrate the effect of interannual variability in trend estimation for horizons of a decade or more. As expected, it can contribute to the existence of transitory cooling trends over a few decades, embedded within the expected long-term warming trends. A new index related to signal-to-noise ratio was developed to evaluate the expected number of years it takes for the warming trend to emerge from interannual variability. Our results suggest that detection of the climate change signal is expected to occur earlier in summer than in winter almost everywhere, despite the fact that winter temperature generally has a much stronger climate change signal. In particular, we find that the province of Quebec and northwestern Mexico may possibly feel climate change in winter earlier than elsewhere in North America. Finally, we show that the spatial and temporal scales of interest are fundamental for our capacity of discriminating climate change from interannual variability.     

东亚冬季风的年代际变化及其与全球气候变化的可能联系

对近年来中外关于东亚冬季风(EAWM)年代际变化问题研究进展做了回顾和评述,主要包括以下3个方面内容:(1)东亚冬季风明显受到全球气候变化的影响,从20世纪50年代开始,中国冬季气温经历了一次冷期(从20世纪50年代延续到80年代初中期),一次暖期(从20世纪80年代初中后期延续到21世纪初)和近10-15年(约从1998年开始)出现的气候变暖趋缓期(也称气候变暖停顿期)。(2)东亚冬季风主要表现出强-弱-强3阶段的特征,即从1950年到1986/1987年,明显偏强;从1986/1987年冬季开始,东亚冬季风减弱;约2005年之后,东亚冬季风开始由弱转强。与东亚冬季风的年代际变化特征相对应,东亚冬季大气环流以及中国冬季气温和寒潮都表现出一致的年代际变化。(3)东亚冬季风的年代际变化与大气环流和太平洋海表温度(SST)的区域模态变化密切相关。当北半球环状模/北极涛动(NAM/AO)和太平洋年代际振荡(PDO)处于负(正)位相,东亚冬季风偏强(弱),中国冬季气温偏低(高)。此外,北大西洋年代尺度振荡(AMO)对东亚冬季风也有重要影响,在AMO负位相时,对应东亚冷期(强冬季风),正位相对应暖期(弱冬季风)。因而海洋的年代际变化是造成东亚冬季风气候脉动的主要自然原因,而全球气候变暖对东亚冬季风强度的减弱也有明显影响。     

The economics of climate change in Mexico: implications for national/regional policy

The recent Mexican government study, The Economics of Climate Change in Mexico (ECCM), which has largely influenced Mexico's stance on climate change issues and international negotiations, is critically reviewed. Whilst the importance of such government-supported national studies as a first attempt to provide estimates on the anticipated costs of climate change is recognized, there is scope to strengthen the underlying analysis. It is argued that some of the key policy recommendations of ECCM are weakly supported by its analysis, that it has some methodological weaknesses, and that there are inconsistencies with the approach adopted in the Stern Review. Furthermore, it is likely that the estimated costs severely under-represent future climate change damages in the case of Mexico, which could deter drastic mitigation and adaptation efforts. New estimates of the costs of climate change are presented based on the impact functions of two integrated assessment models.

Policy relevance

Due to its large influence in building a regional view of what climate change could imply for Latin America, the analysis of the ECCM highlights the need to strengthen the analysis of national climate documents to ensure they properly support national/regional policy making. The academic evaluation of national climate change documents is a necessary prerequisite for the development of sound climate policy.     

A method for incorporating climate variability in climate change impact assessments: Sensitivity of river flows in the Eden catchment to precipitation scenarios

Interest in the impacts of climate change is ever increasing. This is particularly true of the water sector where understanding potential changes in the occurrence of both floods and droughts is important for strategic planning. Climate variability has been shown to have a significant impact on UK climate and accounting for this in future climate change projections is essential to fully anticipate potential future impacts. In this paper a new resampling methodology is developed which includes the variability of both baseline and future precipitation. The resampling methodology is applied to 13 CMIP3 climate models for the 2080s, resulting in an ensemble of monthly precipitation change factors. The change factors are applied to the Eden catchment in eastern Scotland with analysis undertaken for the sensitivity of future river flows to the changes in precipitation. Climate variability is shown to influence the magnitude and direction of change of both precipitation and in turn river flow, which are not apparent without the use of the resampling methodology. The transformation of precipitation changes to river flow changes display a degree of non-linearity due to the catchment’s role in buffering the response. The resampling methodology developed in this paper provides a new technique for creating climate change scenarios which incorporate the important issue of climate variability.     

Hydrologic impacts of climate change on the Nile River Basin: implications of the 2007 IPCC scenarios

We assess the potential impacts of climate change on the hydrology and water resources of the Nile River basin using a macroscale hydrology model. Model inputs are bias corrected and spatially downscaled 21st Century simulations from 11 General Circulation Models (GCMs) and two global emissions scenarios (A2 and B1) archived from the 2007 IPCC Fourth Assessment Report (AR4). While all GCMs agree with respect to the direction of 21st Century temperature changes, there is considerable variability in the magnitude, direction, and seasonality of projected precipitation changes. Our simulations show that, averaged over all 11 GCMs, the Nile River is expected to experience increase in streamflow early in the study period (2010–2039), due to generally increased precipitation. Streamflow is expected to decline during mid- (2040–2069) and late (2070–2099) century as a result of both precipitation declines and increased evaporative demand. The predicted multimodel average streamflow at High Aswan Dam (HAD) as a percentage of historical (1950–1999) annual average are 111 (114), 92 (93) and 84 (87) for A2 (B1) global emissions scenarios. Implications of these streamflow changes on the water resources of the Nile River basin were analyzed by quantifying the annual hydropower production and irrigation water release at HAD. The long-term HAD release for irrigation increases early in the century to 106 (109)% of historical, and then decreases to 87 (89) and 86 (84)% of historical in Periods II and III, respectively, for the A2 (B1) global emissions scenarios. Egypt’s hydropower production from HAD will be above the mean annual average historical value of about 10,000 GWH for the early part of 21st century, and thereafter will generally follow the streamflow trend, however with large variability among GCMs. Agricultural water supplies will be negatively impacted, especially in the second half of the century.     

Future change of climate in South America in the late twenty-first century: intercomparison of scenarios from three regional climate models

Regional climate change projections for the last half of the twenty-first century have been produced for South America, as part of the CREAS (Cenarios REgionalizados de Clima Futuro da America do Sul) regional project. Three regional climate models RCMs (Eta CCS, RegCM3 and HadRM3P) were nested within the HadAM3P global model. The simulations cover a 30-year period representing present climate (1961–1990) and projections for the IPCC A2 high emission scenario for 2071–2100. The focus was on the changes in the mean circulation and surface variables, in particular, surface air temperature and precipitation. There is a consistent pattern of changes in circulation, rainfall and temperatures as depicted by the three models. The HadRM3P shows intensification and a more southward position of the subtropical Pacific high, while a pattern of intensification/weakening during summer/winter is projected by the Eta CCS/RegCM3. There is a tendency for a weakening of the subtropical westerly jet from the Eta CCS and HadRM3P, consistent with other studies. There are indications that regions such of Northeast Brazil and central-eastern and southern Amazonia may experience rainfall deficiency in the future, while the Northwest coast of Peru-Ecuador and northern Argentina may experience rainfall excesses in a warmer future, and these changes may vary with the seasons. The three models show warming in the A2 scenario stronger in the tropical region, especially in the 5°N–15°S band, both in summer and especially in winter, reaching up to 6–8°C warmer than in the present. In southern South America, the warming in summer varies between 2 and 4°C and in winter between 3 and 5°C in the same region from the 3 models. These changes are consistent with changes in low level circulation from the models, and they are comparable with changes in rainfall and temperature extremes reported elsewhere. In summary, some aspects of projected future climate change are quite robust across this set of model runs for some regions, as the Northwest coast of Peru-Ecuador, northern Argentina, Eastern Amazonia and Northeast Brazil, whereas for other regions they are less robust as in Pantanal region of West Central and southeastern Brazil.     

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.     

Interdecadal variability over the North Pacific in a multi-century climate simulation

Interdecadal variability in the North Pacific region is investigated in a 500-y control integration of the Hamburg ECHAM+LSG coupled ocean-atmosphere general circulation model. The spectrum is predominantly red, but a significant peak with a period of about 18 y is detected in the spectrum of sea surface temperature (SST). This peak is shown to be associated with an irregular oscillation that involves both the model ocean and atmosphere. The SST, sea-level pressure, and geopotential height at 500 hPa all undergo a primarily standing oscillation with an extensive monopole structure centered near the date line. The surface anticyclone is situated to the northeast of the warm SST anomaly, and there is a small westward tilt with height; temporal changes are approximately in phase. The anomalous surface heat flux accompanying the warm phase of SST is primarily out of the ocean, but is compensated by anomalous warm advection by surface currents, allowing the SST anomaly to persist. Oceanic thermocline anomalies propagate northward in the western Pacific, and lag the atmosphere indicating a disequilibrium with the atmosphere; sub-surface thermal advection appears to play an important role. A comparison is made between the model's 18-y oscillation and oscillatory components identified in an analysis of the GISST observational SST dataset, which have periods of approximately 6 and roughly 30 y.     

Internal variability of regional climate models

 Two regional climate models have been applied to the task of generating an ensemble of realizations of the year 1982 with observed boundary conditions in areas covering parts of the Mediterranean countries. These realizations were generated by applying boundary conditions from the ECMWF ERA reanalysis project consecutively, carrying over the soil variables from the regional models from one iteration to the next. Monthly mean fields for six iterations of each model have been used as statistical ensembles in order to investigate the internal variability of the regional model dynamics. This internal variability is a necessary consequence of the non-linear physical feedback mechanisms of the RCM being active. A small value of internal variability will give better statistics for climate sensitivity signals, but will make these results less credible. The internal variability is important for the quantitative assessment of a climate sensitivity signal. With the present choice of models and integration domains the internal variabilities of surface fields and precipitation do reach levels that are less than, but in summer of comparable order of magnitude to, corresponding atmospheric variabilities of an atmospheric general circulation model. Received: 26 October 1999 / Accepted: 18 December 2000     

Shoreline evolution under climate change wave scenarios

This paper investigates changes in shoreline evolution caused by changes in wave climate. In particular, a number of nearshore wave climate scenarios corresponding to a ??present?? (1961?C1990) and a future time-slice (2071?C2100) are used to drive a beach evolution model to determine monthly and seasonal statistics. To limit the number of variables, an idealised shoreline segment is adopted. The nearshore wave climate scenarios are generated from wind climate scenarios through point wave hindcast and inshore transformation. The original wind forcing comes from regional climate change model experiments of different resolutions and/or driving global climate models, representing different greenhouse-gas emission scenarios. It corresponds to a location offshore the south central coast of England. Hypothesis tests are applied to map the degree of evidence of future change in wave and shoreline statistics relative to the present. Differential statistics resulting from different global climate models and future emission scenarios are also investigated. Further, simple, fast, and straightforward methods that are capable of accommodating a great number of climate change scenarios with limited data reduction requirements are proposed to tackle the problem under consideration. The results of this study show that there are statistically significant changes in nearshore wave climate conditions and beach alignment between current and future climate scenarios. Changes are most notable during late summer for the medium-high future emission scenario and late winter for the medium-low. Despite frequent disagreement between global climate change models on the statistical significance of a change, all experiments agreed in future seasonal trends. Finally, a point of importance for coastal management, material shoreline changes are generally linked to significant changes in future wave direction rather than wave height.     

Economics of climate change mitigation forest policy scenarios for Ukraine

Abstract

This article reveals the contribution of woodland expansion in Ukraine to climate change mitigation policies. The opportunities for climate change mitigation of three policy scenarios: (1) carbon storage in forests, (2) carbon storage and additional wood-for-fuel substitution, and (3) carbon storage with additional sink policy for wood products, are investigated by using a simulation technique, in combination with cost—benefit analysis. The article concludes that the Ukraine's forests and their expansion offer a low-cost opportunity for carbon sequestration. Important factors that influence the results are the discount rate and the time horizon considered in the models. The findings provide evidence that the storage climate change mitigation forest policy scenario is most viable for the country, under the assumptions considered in this research.     

Interannual variability and regional climate simulations

Summary An assessment is made of a regional climate model's skill in simulating the mean climatology and the interannual variability experienced in a specific region. To this end two ensembles comprising three realizations of month-long January and July simulations are undertaken with a limited are a operational NWP model. The modelling suite is driven at its lateral boundaries by analysed meteorological fields and the computational domain covers Europe and the North-western Atlantic with a horizontal resolution of 56 km.Validation is performed against both operational ECMWF analyses and objectively analysed precipitation fields from a network of ~ 1400 SYNOP rain gauge stations. Analysis of the simulated ensemble-mean climatology indicates that the model successfully reproduces both the winter and summer distributions of the primary dynamical and thermodynamical field, and also provides a reasonable representation of the measured precipitation over most of Europe. Typically the domain averaged model-biases are below 0.5 K for temperature and 0.1 g/kg for specific humidity. Analysis of the interannual variability reveals that the model captures the wintertime changes including that of the precipitation distribution, but in contrast the summertime precipitation totals for the individual years is not simulated satisfactorily and only partially reproduces the observed regional interannual variability.The latter shortcomings are related to the following factors. Firstly the model bias in the dynamical fields is somewhat larger for summer than winter, while at the same time summertime interannual variability is associated with weaker effects in the dynamical fields. Secondly the summertime precipitation distribution is more substantially affected by small-scale moist convection and surface hydrological processes. Together these two factors suggest that summertime precipitation over continental extratropical land masses might be intrinsically less predictable than wintertime synoptic scale precipitation.With 17 Figures     

Climate change in the northeastern US: regional climate model validation and climate change projections

A high resolution regional climate model (RCM) is used to simulate climate of the recent past and to project future climate change across the northeastern US. Different types of uncertainties in climate simulations are examined by driving the RCM with different boundary data, applying different emissions scenarios, and running an ensemble of simulations with different initial conditions. Empirical orthogonal functions analysis and K-means clustering analysis are applied to divide the northeastern US region into four climatologically different zones based on the surface air temperature (SAT) and precipitation variability. The RCM simulations tend to overestimate SAT, especially over the northern part of the domain in winter and over the western part in summer. Statistically significant increases in seasonal SAT under both higher and lower emissions scenarios over the whole RCM domain suggest the robustness of future warming. Most parts of the northeastern US region will experience increasing winter precipitation and decreasing summer precipitation, though the changes are not statistically significant. The greater magnitude of the projected temperature increase by the end of the twenty-first century under the higher emissions scenario emphasizes the essential role of emissions choices in determining the potential future climate change.     

Using Statistical Downscaling to Quantify the GCM-Related Uncertainty in Regional Climate Change Scenarios： A Case Study of Swedish Precipitation

There are a number of sources of uncertainty in regional climate change scenarios. When statistical downscaling is used to obtain regional climate change scenarios, the uncertainty may originate from the uncertainties in the global climate models used, the skill of the statistical model, and the forcing scenarios applied to the global climate model. The uncertainty associated with global climate models can be evaluated by examining the differences in the predictors and in the downscaled climate change scenarios based on a set of different global climate models. When standardized global climate model simulations such as the second phase of the Coupled Model Intercomparison Project （CMIP2） are used, the difference in the downscaled variables mainly reflects differences in the climate models and the natural variability in the simulated climates. It is proposed that the spread of the estimates can be taken as a measure of the uncertainty associated with global climate models. The proposed method is applied to the estimation of global-climate-model-related uncertainty in regional precipitation change scenarios in Sweden. Results from statistical downscaling based on 17 global climate models show that there is an overall increase in annual precipitation all over Sweden although a considerable spread of the changes in the precipitation exists. The general increase can be attributed to the increased large-scale precipitation and the enhanced westerly wind. The estimated uncertainty is nearly independent of region. However, there is a seasonal dependence. The estimates for winter show the highest level of confidence, while the estimates for summer show the least.     

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.