Differences and sensitivities in potential hydrologic impact of climate change to regional-scale Athabasca and Fraser River basins of the leeward and windward sides of the Canadian Rocky Mountains respectively

Sensitivities to the potential impact of Climate Change on the water resources of the Athabasca River Basin (ARB) and Fraser River Basin (FRB) were investigated. The Special Report on Emissions Scenarios (SRES) of IPCC projected by seven general circulation models (GCM), namely, Japan’s CCSRNIES, Canada’s CGCM2, Australia’s CSIROMk2b, Germany’s ECHAM4, the USA’s GFDLR30, the UK’s HadCM3, and the USA’s NCARPCM, driven under four SRES climate scenarios (A1FI, A2, B1, and B2) over three 30-year time periods (2010–2039, 2040–2069, 2070–2100) were used in these studies. The change fields over these three 30-year time periods are assessed with respect to the 1961–1990, 30-year climate normal and based on the 1961–1990 European Community Mid-Weather Forecast (ECMWF) re-analysis data (ERA-40), which were adjusted with respect to the higher resolution GEM forecast archive of Environment Canada, and used to drive the Modified ISBA (MISBA) of Kerkhoven and Gan (Adv Water Resour 29(6):808–826, 2006). In the ARB, the shortened snowfall season and increased sublimation together lead to a decline in the spring snowpack, and mean annual flows are expected to decline with the runoff coefficient dropping by about 8% per °C rise in temperature. Although the wettest scenarios predict mild increases in annual runoff in the first half of the century, all GCM and emission combinations predict large declines by the end of the twenty-first century with an average change in the annual runoff, mean maximum annual flow and mean minimum annual flow of −21%, −4.4%, and −41%, respectively. The climate scenarios in the FRB present a less clear picture of streamflows in the twenty-first century. All 18 GCM projections suggest mean annual flows in the FRB should change by ±10% with eight projections suggesting increases and 10 projecting decreases in the mean annual flow. This stark contrast with the ARB results is due to the FRB’s much milder climate. Therefore under SRES scenarios, much of the FRB is projected to become warmer than 0°C for most of the calendar year, resulting in a decline in FRB’s characteristic snow fed annual hydrograph response, which also results in a large decline in the average maximum flow rate. Generalized equations relating mean annual runoff, mean annual minimum flows, and mean annual maximum flows to changes in rainfall, snowfall, winter temperature, and summer temperature show that flow rates in both basins are more sensitive to changes in winter than summer temperature.     

Using regional climate model data to simulate historical and future river flows in northwest England

Daily rainfall and temperature data were extracted from the multi-ensemble HadRM3H regional climate model (RCM) integrations for control (1960–1990) and future (2070–2100) time-slices. This dynamically downscaled output was bias-corrected on observed mean statistics and used as input to hydrological models calibrated for eight catchments which are critical water resources in northwest England. Simulated daily flow distributions matched observed from Q₉₅ to Q₅, suggesting that RCM data can be used with some confidence to examine future changes in flow regime. Under the SRES A2 (UKCIP02 Medium-High) scenario, annual runoff is projected to increase slightly at high elevation catchments, but reduce by ~16% at lower elevations. Impacts on monthly flow distribution are significant, with summer reductions of 40–80% of 1961–90 mean flow, and winter increases of up to 20%. This changing seasonality has a large impact on low flows, with Q₉₅ projected to decrease in magnitude by 40–80% in summer months, with serious consequences for water abstractions and river ecology. In contrast, high flows (> Q₅) are projected to increase in magnitude by up to 25%, particularly at high elevation catchments, providing an increased risk of flooding during winter months. These changes will have implications for management of water resources and ecologically important areas under the EU Water Framework Directive.     

A multi-model ensemble of downscaled spatial climate change scenarios for the Dommel catchment, Western Europe

Regional or local scale hydrological impact studies require high resolution climate change scenarios which should incorporate some assessment of uncertainties in future climate projections. This paper describes a method used to produce a multi-model ensemble of multivariate weather simulations including spatial–temporal rainfall scenarios and single-site temperature and potential evapotranspiration scenarios for hydrological impact assessment in the Dommel catchment (1,350 km²) in The Netherlands and Belgium. A multi-site stochastic rainfall model combined with a rainfall conditioned weather generator have been used for the first time with the change factor approach to downscale projections of change derived from eight Regional Climate Model (RCM) experiments for the SRES A2 emission scenario for the period 2071–2100. For winter, all downscaled scenarios show an increase in mean daily precipitation (catchment average change of +9% to +40%) and typically an increase in the proportion of wet days, while for summer a decrease in mean daily precipitation (−16% to −57%) and proportion of wet days is projected. The range of projected mean temperature is 7.7°C to 9.1°C for winter and 19.9°C to 23.3°C for summer, relative to means for the control period (1961–1990) of 3.8°C and 16.8°C, respectively. Mean annual potential evapotranspiration is projected to increase by between +17% and +36%. The magnitude and seasonal distribution of changes in the downscaled climate change projections are strongly influenced by the General Circulation Model (GCM) providing boundary conditions for the RCM experiments. Therefore, a multi-model ensemble of climate change scenarios based on different RCMs and GCMs provides more robust estimates of precipitation, temperature and evapotranspiration for hydrological impact assessments, at both regional and local scale.     

2011—2050年长江流域气候变化预估问题的探讨

利用长江流域1961—2008年观测气象资料,对IPCC 第四次评估报告中12个全球气候模式及所有模式集合平均进行比较验证,结果表明：MIUB_ECHO_G模式对该地区降水模拟能力较强,NCAR_CCSM3模式对温度模拟效果较好。进一步利用MIUB_ECHO_G模式和NCAR_CCSM3模式结果在SRES-A2、-A1B、-B1 3种排放情景下的降水和温度数据,分析2011—2050年3种排放情景下长江流域降水和温度变化特征。结果表明,2011—2050年长江流域降水变化趋势不明显,温度呈增加趋势,增幅在2℃内。     

21世纪珠江流域水文过程对气候变化的响应

应用HBV-D水文模型和多个气候模式预估了不同温室气体排放情景下珠江主干流西江的径流过程,分析了21世纪水资源量和洪水频率的变化。结果表明：2050年后年降水量和年径流量较基准期（1961—1990年）明显增加;流域平均的月降水量和径流量在5—10月间均呈增加趋势,12月至次年2月呈减少趋势;年最大1 d和7 d洪量逐渐增加,重现期逐渐缩短。2030年前枯水期径流增加有望缓解枯水期用水压力,而2050年之后丰水期径流量以及洪水强度、发生频率的增加将给珠江流域防汛抗洪带来更大压力,在制订气候变化对流域水资源影响适应性对策时应考虑这两方面的影响。     

未来气候变化对黄河流域水文过程的影响

使用NASA/NCAR有限区域大气环流模型FvGCM结果驱动高分辨率区域气候模式RegCM3 (20 km),进行1961～1990年当代气候模拟(控制试验)和2071～2100年IPCC A2排放情景下未来气候模拟(A2情景模拟试验)。将RegCM3径流模拟结果同大尺度汇流模型LRM [分辨率0.25°(纬度)×0.25°(经度)]相连接,模拟预估未来气候变化对我国黄河流域水文过程的影响。结果表明:相对于当代气候,未来黄河流域呈现气温升高、降水增加(夏季7～8月降水减少)和蒸发增大的趋势,且空间分布极不均匀,造成河川径流在5～10月减少,加剧流域夏季的水资源短缺;未来气温升高使得融雪径流增加,可能导致更早和更大的春季径流,使径流过程发生季节性迁移,引起黄河流域水资源年内分配发生变化。     

Uncertainty in hydrologic impacts of climate change in the Sierra Nevada, California, under two emissions scenarios

A hydrologic model was driven by the climate projected by 11 GCMs under two emissions scenarios (the higher emission SRES A2 and the lower emission SRES B1) to investigate whether the projected hydrologic changes by 2071–2100 have a high statistical confidence, and to determine the confidence level that the A2 and B1 emissions scenarios produce differing impacts. There are highly significant average temperature increases by 2071–2100 of 3.7°C under A2 and 2.4°C under B1; July increases are 5°C for A2 and 3°C for B1. Two high confidence hydrologic impacts are increasing winter streamflow and decreasing late spring and summer flow. Less snow at the end of winter is a confident projection, as is earlier arrival of the annual flow volume, which has important implications on California water management. The two emissions pathways show some differing impacts with high confidence: the degree of warming expected, the amount of decline in summer low flows, the shift to earlier streamflow timing, and the decline in end-of-winter snow pack, with more extreme impacts under higher emissions in all cases. This indicates that future emissions scenarios play a significant role in the degree of impacts to water resources in California.     

Temperature scenarios for Norway: from regional to local scale

Scenarios with daily time resolution are frequently used in research on the impacts of climate change. These are traditionally developed by regional climate models (RCMs). The spatial resolution, however, is usually too coarse for local climate change analysis, especially in regions with complex topography, such as Norway. The RCM used, HIRHAM, is run with lateral boundary forcing provided from two global medium resolution models; the ECHAM4/OPYC3 from MPI and the HadAM3H from the Hadley centre. The first is run with IPCC SRES emission scenario B2, the latter is run with IPCC SRES emission scenarios A2 and B2. All three scenarios represent the future time period 2071–2100. Both models have a control run, representing the present climate (1961–1990). Daily temperature scenarios are interpolated from HIRHAM to Norwegian temperature stations. The at-site HIRHAM-temperatures, both for the control and scenario runs, are adjusted to be locally representative. Mean monthly values and standard deviations based on daily values of the adjusted HIRHAM-temperatures, as well as the cumulative distribution curve of daily seasonal temperatures, are conclusive with observations for the control period. Residual kriging are used on the adjusted daily HIRHAM-temperatures to obtain high spatial temperature scenarios. Mean seasonal temperature grids are obtained. By adjusting the control runs and scenarios and improving the spatial resolution of the scenarios, the absolute temperature values are representative at a local scale. The scenarios indicate larger warming in winter than in summer in the Scandinavian regions. A marked west–east and south–north gradient is projected for Norway, where the largest increase is in eastern and northern regions. The temperature of the coldest winter days is projected to increase more than the warmer temperatures.     

典型相关分析方法对21世纪江淮流域极端降水的预估试验

利用1961—1990年江淮流域逐日降水资料、NCEP/NCAR再分析资料和HadCM3 SRES A1B情景下模式预估资料,采用典型相关分析统计降尺度方法,评估降尺度模型对当前极端降水指数的模拟能力,并对21世纪中期和末期的极端降水变化进行预估。结果表明：通过降尺度能够有效改善HadCM3对区域气候特征的模拟能力,极端降水指数气候平均态相对误差降低了30%～100%,但降尺度结果仍然在冬季存在湿偏差、夏季存在干偏差;在SRES A1B排放情景下,该区域大部分站点的极端强降水事件将增多,强度增大,极端强降水指数的变化幅度高于平均降水指数,且夏季增幅高于冬季;冬季极端降水贡献率（R95t）在21世纪中期和末期的平均增幅分别为14%和25%,夏季则分别增加24%和32%。     

Fluvial flood risk in Europe in present and future climates

In this work we evaluate the implications of climate change for future fluvial flood risk in Europe, considering climate developments under the SRES A2 (high emission) and B2 (low emission) scenario. We define flood risk as the product of flood probability (or hazard), exposure of capital and population, and vulnerability to the effect of flooding. From the European flood hazard simulations of Dankers and Feyen (J Geophys Res 114:D16108. doi:, 2009) discharges with return periods of 2, 5, 10, 20, 50, 100, 250 and 500 years were extracted and converted into flood inundation extents and depths using a planar approximation approach. Flood inundation extents and depths were transformed into direct monetary damage using country specific flood depth-damage functions and land use information. Population exposure was assessed by overlaying the flood inundation information with data on population density. By linearly interpolating damages and population exposed between the different return periods, we constructed damage and population exposure probability functions under present and future climate. From the latter expected annual damages (EAD) and expected annual population exposed (EAP) were calculated. To account for flood protection the damage and population exposure probability functions were truncated at design return periods based on the country GDP/capita. Results indicate that flood damages are projected to rise across much of Western Europe. Decreases in flood damage are consistently projected for north-eastern parts of Europe. For EU27 as a whole, current EAD of approximately €6.4 billion is projected to amount to €14–21.5 billion (in constant prices of 2006) by the end of this century, depending on the scenario. The number of people affected by flooding is projected to rise by approximately 250,000 to 400,000. Notwithstanding these numbers are subject to uncertainty, they provide an indication of potential future developments in flood risk in a changing climate.     

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.     

Implications of 21st century climate change for the hydrology of Washington State

Pacific Northwest (PNW) hydrology is particularly sensitive to changes in climate because snowmelt dominates seasonal runoff, and temperature changes impact the rain/snow balance. Based on results from the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR4), we updated previous studies of implications of climate change on PNW hydrology. PNW 21st century hydrology was simulated using 20 Global Climate Models (GCMs) and 2 greenhouse gas emissions scenarios over Washington and the greater Columbia River watershed, with additional focus on the Yakima River watershed and the Puget Sound which are particularly sensitive to climate change. We evaluated projected changes in snow water equivalent (SWE), soil moisture, runoff, and streamflow for A1B and B1 emissions scenarios for the 2020s, 2040s, and 2080s. April 1 SWE is projected to decrease by approximately 38–46% by the 2040s (compared with the mean over water years 1917–2006), based on composite scenarios of B1 and A1B, respectively, which represent average effects of all climate models. In three relatively warm transient watersheds west of the Cascade crest, April 1 SWE is projected to almost completely disappear by the 2080s. By the 2080s, seasonal streamflow timing will shift significantly in both snowmelt dominant and rain–snow mixed watersheds. Annual runoff across the State is projected to increase by 2–3% by the 2040s; these changes are mainly driven by projected increases in winter precipitation.     

Bayesian multi-model projection of climate: bias assumptions and interannual variability

Current climate change projections are based on comprehensive multi-model ensembles of global and regional climate simulations. Application of this information to impact studies requires a combined probabilistic estimate taking into account the different models and their performance under current climatic conditions. Here we present a Bayesian statistical model for the distribution of seasonal mean surface temperatures for control and scenario periods. The model combines observational data for the control period with the output of regional climate models (RCMs) driven by different global climate models (GCMs). The proposed Bayesian methodology addresses seasonal mean temperatures and considers both changes in mean temperature and interannual variability. In addition, unlike previous studies, our methodology explicitly considers model biases that are allowed to be time-dependent (i.e. change between control and scenario period). More specifically, the model considers additive and multiplicative model biases for each RCM and introduces two plausible assumptions (“constant bias” and “constant relationship”) about extrapolating the biases from the control to the scenario period. The resulting identifiability problem is resolved by using informative priors for the bias changes. A sensitivity analysis illustrates the role of the informative prior. As an example, we present results for Alpine winter and summer temperatures for control (1961–1990) and scenario periods (2071–2100) under the SRES A2 greenhouse gas scenario. For winter, both bias assumptions yield a comparable mean warming of 3.5–3.6°C. For summer, the two different assumptions have a strong influence on the probabilistic prediction of mean warming, which amounts to 5.4°C and 3.4°C for the “constant bias” and “constant relation” assumptions, respectively. Analysis shows that the underlying reason for this large uncertainty is due to the overestimation of summer interannual variability in all models considered. Our results show the necessity to consider potential bias changes when projecting climate under an emission scenario. Further work is needed to determine how bias information can be exploited for this task.     

Global high resolution versus Limited Area Model climate change projections over Europe: quantifying confidence level from PRUDENCE results

Four high resolution atmospheric general circulation models (GCMs) have been integrated with the standard forcings of the PRUDENCE experiment: IPCC-SRES A2 radiative forcing and Hadley Centre sea surface temperature and sea-ice extent. The response over Europe, calculated as the difference between the 2071–2100 and the 1961–1990 means is compared with the same diagnostic obtained with nine Regional Climate Models (RCM) all driven by the Hadley Centre atmospheric GCM. The seasonal mean response for 2m temperature and precipitation is investigated. For temperature, GCMs and RCMs behave similarly, except that GCMs exhibit a larger spread. However, during summer, the spread of the RCMs—in particular in terms of precipitation—is larger than that of the GCMs. This indicates that the European summer climate is strongly controlled by parameterized physics and/or high-resolution processes. The temperature response is larger than the systematic error. The situation is different for precipitation. The model bias is twice as large as the climate response. The confidence in PRUDENCE results comes from the fact that the models have a similar response to the IPCC-SRES A2 forcing, whereas their systematic errors are more spread. In addition, GCM precipitation response is slightly but significantly different from that of the RCMs.     

How the “Best” Models Project the Future Precipitation Change in China

Projected changes in summer precipitation characteristics in China during the 21st century are assessed using the monthly precipitation outputs of the ensemble of three “best” models under the Special Report on Emissions Scenarios (SRES) A1B, A2, and B1 scenarios. The excellent reproducibility of the models both in spatial and temporal patterns for the precipitation in China makes the projected summer precipitation change more believable for the future 100 years. All the three scenarios experiments indicate a consistent enhancement of summer precipitation in China in the 21st century. However, the projected summer precipitation in China demonstrates large variability between sub-regions. The projected increase in precipitation in South China is significant and persistent, as well as in North China. Meanwhile, in the early period of the 21st century, the region of Northeast China is projected to be much drier than the present. But, this situation changes and the precipitation intensifies later, with a precipitation anomaly increase of 12.4%–20.4% at the end of the 21st century. The region of the Xinjiang Province probably undergoes a drying trend in the future 100 years, and is projected to decrease by 1.7%–3.6% at the end of the 21st century. There is no significant long-term change of the projected summer precipitation in the lower reaches of the Yangtze River valley. A high level of agreement of the ensemble of the regional precipitation change in some parts of China is found across scenarios but smaller changes are projected for the B1 scenario and slightly larger changes for the A2 scenario.     

A comparison of statistical downscaling and climate change factor methods: impacts on low flows in the River Thames, United Kingdom

Strategic-scale assessments of climate change impacts are often undertaken using the change factor (CF) methodology whereby future changes in climate projected by General Circulation Models (GCMs) are applied to a baseline climatology. Alternatively, statistical downscaling (SD) methods apply climate variables from GCMs to statistical transfer functions to estimate point-scale meteorological series. This paper explores the relative merits of the CF and SD methods using a case study of low flows in the River Thames under baseline (1961–1990) and climate change conditions (centred on the 2020s, 2050s and 2080s). Archived model outputs for the UK Climate Impacts Programme (UKCIP02) scenarios are used to generate daily precipitation and potential evaporation (PE) for two climate change scenarios via the CF and SD methods. Both signal substantial reductions in summer precipitation accompanied by increased PE throughout the year, leading to reduced flows in the Thames in late summer and autumn. However, changes in flow associated with the SD scenarios are generally more conservative and complex than that arising from CFs. These departures are explained in terms of the different treatment of multidecadal natural variability, temporal structuring of daily climate variables and large-scale forcing of local precipitation and PE by the two downscaling methods.     

未来气候变化情景下长江上游年径流量变化趋势研究

依据政府间气候变化委员会(IPCC)第五次评估报告(AR5)未来不同排放情景(RCPs)下的多模式(CMIP5)气温和降水预估结果,构建基于气温和降水的未来径流量预估模型,并以宜昌站为例分析了不同模式不同排放情景下未来80年(2020～2099年)长江上游年径流量的变化趋势。多模式集合平均预估结果表明:在99%的置信水平下,未来80年长江上游年径流量在RCP2.6排放情景下呈不显著增加趋势,在RCP4.5排放情景下呈不显著减小趋势,而在RCP8.5排放情景下则呈显著减小趋势;在RCP2.6、RCP4.5和RCP8.5排放情景下未来80年长江上游年径流量预估均值相对于1961～2000年分别减少6.42%、10.99%和13.25%;同时,未来80年长江上游年径流量变化具有一定的年代际特征,在RCP2.6和RCP4.5排放情景下21世纪初期偏多、中期偏少而后期变化并不明显,在RCP8.5排放情景下则是21世纪中期以前偏多而中期以后明显偏少。本研究方法可为未来气候变化情景预估分析提供技术参考,本研究成果可供气候变化背景下长江上游乃至长江流域水资源开发利用及对策分析提供决策依据。      

Projection and possible causes of summer precipitation in eastern China using self-organizing map

Self-organizing map (SOM) is used to simulate summer daily precipitation over the Yangtze–Huaihe river basin in Eastern China, including future projections. SOM shows good behaviors in terms of probability distribution of daily rainfall and spatial distribution of rainfall indices, as well as consistency of multi-model simulations. Under RCP4.5 Scenario, daily rainfall at most sites (63%) is projected to shift towards larger values. For the early 21st century (2016–2035), precipitation in the central basin increases, yet decreases occur over the middle reaches of the Yangtze River as well as a part of its southeast area. For the late 21st century (2081–2100), the mean precipitation and extreme indices experience an overall increase except for a few southeast stations. The total precipitation in the lower reaches of the Yangtze River and in its south area is projected to increase from 7% at 1.5 °C global warming to 11% at 2 °C, while the intensity enhancement is more significant in southern and western sites of the domain. A clustering allows to regroup all SOM nodes into four distinct regimes. Such regional synoptic regimes show remarkable stability for future climate. The overall intensification of precipitation in future climate is linked to the occurrence-frequency rise of a wet regime which brings longitudinally closer the South Asia High (eastward extended) and the Western Pacific Subtropical High (westward extended), as well as the reduction of a dry pattern which makes the two atmospheric centers of action move away from each other.     

Projected potential vegetation change in China under the SRES A2 and B2 scenarios

The ability of seven global coupled ocean-atmosphere models to reproduce East Asian monthly surface temperature and precipitation climatologies during 1961 1990 is evaluated. January and July climate differences during the 2050s and 2090s relative to 1961-1990 projected by the seven-model ensemble under the Special Report on Emission Scenarios （SRES） A2 and B2 scenarios are then briefly discussed. These projections, together with the corresponding atmospheric CO2 concentrations under the SRES A2 and B2 scenarios, are subsequently used to drive the biome model BIOME3 to simulate potential vegetation distribution in China during the 2050s and 2090s. It is revealed that potential vegetation belts during the 2050s shift northward greatly in central and eastern China compared to those during 1961-1990. In contrast, potential vegetation change is slight in western China on the whole. The spatial pattern of potential vegetation during the 2090s is generally similar to that during the 2050s, but the range of potential vegetation change against 1961 1990 is more extensive during the 2090s than the 2050s, particularly in western China. Additionally, there exists model-dependent uncertainty of potential vegetation change under the SRES A2 scenario during the 2090s, which is due to the scatter of projected climate change by the models. The projected change in potential vegetation under the SRES A2 scenario during the 2090s is attributable to surface temperature change south of 35°N and to the joint changes of surface temperature, precipitation, and atmospheric CO2 concentration north of 35°N.     

Historical and potential changes of precipitation and temperature of Alberta subjected to climate change impact: 1900–2100

We investigated changes to precipitation and temperature of Alberta for historical and future periods. First, the Mann-Kendall test and Sen’s slope were used to test for historical trends and trend magnitudes from the climate data of Alberta, respectively. Second, the Special Report on Emissions Scenarios (SRES) (A1B, A2, and B1) of CMIP3 (Phase 3 of Coupled Model Intercomparison Project), projected by seven general circulation models (GCM) of the Intergovernmental Panel on Climate Change (IPCC) for three 30 years periods (2020s, 2050s, and 2080s), were used to evaluate the potential impact of climate change on precipitation and temperature of Alberta. Third, trends of projected precipitation and temperature were investigated, and differences between historical versus projected trends were estimated. Using the 50-km resolution dataset from CANGRD (Canadian Grid Climate Data), we found that Alberta had become warmer and somewhat drier for the past 112 years (1900–2011), especially in central and southern Alberta. For observed precipitation, upward trends mainly occurred in northern Alberta and at the leeward side of Canadian Rocky Mountains. However, only about 13 to 22 % of observed precipitation showed statistically significant increasing trends at 5 % significant level. Most observed temperature showed significant increasing trends, up to 0.05 °C/year in DJF (December, January, and February) in northern Alberta. GCMs’ SRES projections indicated that seasonal precipitation of Alberta could change from ?25 to 36 %, while the temperature would increase from 2020s to 2080s, with the largest increase (6.8 °C) in DJF. In all 21 GCM-SRES cases considered, precipitation in both DJF and MAM (March, April, and May) is projected to increase, while temperature is consistently projected to increase in all seasons, which generally agree with the trends of historical precipitation and temperature. The SRES A1B scenario of CCSM3 might project more realistic future climate for Alberta, where its water resources can become more critical in the future as its streamflow is projected to decrease continually in the future.