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.     

Evaluation of SDSM developed by annual and monthly sub-models for downscaling temperature and precipitation in the Jhelum basin, Pakistan and India

The study evaluates statistical downscaling model (SDSM) developed by annual and monthly sub-models for downscaling maximum temperature, minimum temperature, and precipitation, and assesses future changes in climate in the Jhelum River basin, Pakistan and India. Additionally, bias correction is applied on downscaled climate variables. The mean explained variances of 66, 76, and 11 % for max temperature, min temperature, and precipitation, respectively, are obtained during calibration of SDSM with NCEP predictors, which are selected through a quantitative procedure. During validation, average R ² values by the annual sub-model (SDSM-A)—followed by bias correction using NCEP, H3A2, and H3B2—lie between 98.4 and 99.1 % for both max and min temperature, and 77 to 85 % for precipitation. As for the monthly sub-model (SDSM-M), followed by bias correction, average R ² values lie between 98.5 and 99.5 % for both max and min temperature and 75 to 83 % for precipitation. These results indicate a good applicability of SDSM-A and SDSM-M for downscaling max temperature, min temperature, and precipitation under H3A2 and H3B2 scenarios for future periods of the 2020s, 2050s, and 2080s in this basin. Both sub-models show a mean annual increase in max temperature, min temperature, and precipitation. Under H3A2, and according to both sub-models, changes in max temperature, min temperature, and precipitation are projected as 0.91–3.15 °C, 0.93–2.63 °C, and 6–12 %, and under H3B2, the values of change are 0.69–1.92 °C, 0.56–1.63 °C, and 8–14 % in 2020s, 2050s, and 2080s. These results show that the climate of the basin will be warmer and wetter relative to the baseline period. SDSM-A, most of the time, projects higher changes in climate than SDSM-M. It can also be concluded that although SDSM-A performed well in predicting mean annual values, it cannot be used with regard to monthly and seasonal variations, especially in the case of precipitation unless correction is applied.     

The global-scale impacts of climate change on water resources and flooding under new climate and socio-economic scenarios

This paper presents a preliminary assessment of the relative effects of rate of climate change (four Representative Concentration Pathways - RCPs), assumed future population (five Shared Socio-economic Pathways - SSPs), and pattern of climate change (19 CMIP5 climate models) on regional and global exposure to water resources stress and river flooding. Uncertainty in projected future impacts of climate change on exposure to water stress and river flooding is dominated by uncertainty in the projected spatial and seasonal pattern of change in climate. There is little clear difference in impact between RCP2.6, RCP4.5 and RCP6.0 in 2050, and between RCP4.5 and RCP6.0 in 2080. Impacts under RCP8.5 are greater than under the other RCPs in 2050 and 2080. For a given RCP, there is a difference in the absolute numbers of people exposed to increased water resources stress or increased river flood frequency between the five SSPs. With the ‘middle-of-the-road’ SSP2, climate change by 2050 would increase exposure to water resources stress for between approximately 920 and 3,400 million people under the highest RCP, and increase exposure to river flood risk for between 100 and 580 million people. Under RCP2.6, exposure to increased water scarcity would be reduced in 2050 by 22-24 %, compared to impacts under the RCP8.5, and exposure to increased flood frequency would be reduced by around 16 %. The implications of climate change for actual future losses and adaptation depend not only on the numbers of people exposed to changes in risk, but also on the qualitative characteristics of future worlds as described in the different SSPs. The difference in ‘actual’ impact between SSPs will therefore be greater than the differences in numbers of people exposed to impact.     

An assessment of regional vulnerability of rice to climate change in India

A simulation analysis was carried out using the InfoCrop-rice model to quantify impacts and adaptation gains, as well as to identify vulnerable regions for irrigated and rain fed rice cultivation in future climates in India. Climates in A1b, A2, B1 and B2 emission scenarios as per a global climate model (MIROC3.2.HI) and a regional climate model (PRECIS) were considered for the study. On an aggregated scale, the mean of all emission scenarios indicate that climate change is likely to reduce irrigated rice yields by ~4 % in 2020 (2010–2039), ~7 % in 2050 (2040–2069), and by ~10 % in 2080 (2070–2099) climate scenarios. On the other hand, rainfed rice yields in India are likely to be reduced by ~6 % in the 2020 scenario, but in the 2050 and 2080 scenarios they are projected to decrease only marginally (<2.5 %). However, spatial variations exist for the magnitude of the impact, with some regions likely to be affected more than others. Adaptation strategies comprising agronomical management can offset negative impacts in the near future—particularly in rainfed conditions—but in the longer run, developing suitable varieties coupled with improved and efficient crop husbandry will become essential. For irrigated rice crop, genotypic and agronomic improvements will become crucial; while for rainfed conditions, improved management and additional fertilizers will be needed. Basically climate change is likely to exhibit three types of impacts on rice crop: i) regions that are adversely affected by climate change can gain in net productivity with adaptation; ii) regions that are adversely affected will still remain vulnerable despite adaptation gains; and iii) rainfed regions (with currently low rainfall) that are likely to gain due to increase in rainfall can further benefit by adaptation. Regions falling in the vulnerable category even after suggested adaptation to climate change will require more intensive, specific and innovative adaptation options. The present analysis indicates the possibility of substantial improvement in yields with efficient utilization of inputs and adoption of improved varieties.     

Potential overwintering boundary and voltinism changes in the brown planthopper, <Emphasis Type="Italic">Nilaparvata lugens</Emphasis>, in China in response to global warming

The brown planthopper Nilaparvata lugens (Stål) is a major rice insect pest in China and other Asian countries. This study assessed a potential northward shift in the overwintering boundaries and changes in the overwintering areas and voltinism of this planthopper species in China in response to global warming. Temperature data generated by 15 Global Circulation Models (GCMs) from 2010 to 2099 were employed to analyze the planthopper’s overwintering boundaries and overwintering areas in conjunction with three Special Report on Emissions Scenarios (SRES). Planthopper voltinism from 1961 to 2050 was analyzed in scenario A2 using degree-day models with projections from the regional circulation model (RCM) Providing Regional Climates for Impacts Studies (PRECIS). In both analyses, 1961–1990 served as the baseline period. Both the intermittent and constant overwintering boundaries were projected to shift northward; these shifts were more pronounced during later time periods and in scenarios A2 and A1B. The intermittent overwintering area was modeled to increase by 11, 24 and 44 %, and the constant overwintering area, by 66, 206 and 477 %, during the 2020s, 2050s and 2080s, respectively. Planthopper voltinism will increase by <0.5, 0.5–1.0 and 1.0–1.4 generations in northern, central and southern China, respectively, in 2021–2050. Our results suggest that the brown planthopper will overwinter in a much larger region and will produce more generations under future climate warming scenarios. As a result, the planthopper will exert an even greater threat to China’s rice production in the future.     

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.     

An assessment of the current and future thermal regimes of three streams located in the Wenatchee River basin, Washington State: some implications for regional river basin systems

We examine summer temperature patterns in the Wenatchee River and two of its major tributaries Icicle and Nason Creeks, located in the Pacific Northwest region of the United States. Through model simulations we evaluate the cooling effects of mature riparian vegetation corridors along the streams and potential increases due to global warming for the 2020s–2080s time horizons. Site potential shade influences are smaller in the mainstream due to its relatively large size and reduced canopy density in the lower reaches, proving a modest reduction of about 0.3°C of the stream length average daily maximum temperature, compared with 1.5°C and 2.8°C in Icicle and Nason Creeks. Assuming no changes in riparian vegetation shade, stream length-average daily maximum temperature could increase in the Wenatchee River from 1–1.2°C by the 2020s to 2°C in the 2040s and 2.5–3.6°C in the 2080s, reaching 27–30°C in the warmest reaches. The cooling effects from the site potential riparian vegetation are likely to be offset by the climate change effects in the Wenatchee River by the 2020s. Buffers of mature riparian vegetation along the banks of the tributaries could prevent additional water temperature increases associated with climate change. By the end of the century, assuming site potential shade, the tributaries could have a thermal condition similar to today’s condition which has less shade. In the absence of riparian vegetation restoration, at typical summer low flows, stream length average daily mean temperatures could reach about 16.4–17°C by the 2040s with stream length average daily maxima around 19.5–20.6°C, values that can impair or eliminate salmonid rearing and spawning. Modeled increases in stream temperature due to global warming are determined primarily by the projected reductions in summer streamflows, and to a lesser extent by the increases in air temperature. The findings emphasize the importance of riparian vegetation restoration along the smaller tributaries, to prevent future temperature increases and preserve aquatic habitat.     

云南初夏干湿演变特征和基于CMIP6模式模拟的预估分析

使用1961—2020年的观测数据和2021—2080年的模式预估数据,首先分析了云南初夏干燥度指数（aridity index,AI）的演变特征和影响因子相对贡献,然后采用国际耦合模式比较计划第六阶段（CMIP6）中的20个全球模式,对SSP1-2.6、SSP2-4.5以及SSP5-8.5情景下云南初夏未来干湿变化进行了预估研究。结果表明：(1) 1961—2020年云南初夏气候整体湿润,但为变干燥的趋势,有明显的年代际变化特征,1960s、1970s以及2000s气候相对湿润,其余年代相对干燥,2000s（2010s）为1961年以来最湿润（干燥）的10年。(2) 2021—2080年在3种排放情景下,云南初夏气候较1995—2014年均为变干燥的趋势,SSP1-2.6、SSP2-4.5以及SSP5-8.5情景下,AI分别减少13.9%、17.9%以及24.9%,西南部将可能是湿润度降幅最大值中心。(3) 1961—2020年,降水对云南初夏气候干湿变化的贡献大于潜在蒸散量;而2021—2080年,潜在蒸散量对气候变干燥的贡献大于降水量,且随排放情景的增高和时间推移,其贡献将逐渐增大。     

Temperature change and macroinvertebrate biodiversity: assessments of organism vulnerability and potential distributions

Peninsular environments are ecosystems that are one of the most vulnerable to global warming. Despite the importance of conserving regional biodiversity, peninsular environments are among the least studied with respect to the influences of global warming. In this study, we used data on benthic macroinvertebrate communities from 521 sites across Korea (a nationwide scale) to evaluate the potential impact of temperature increases on river ecosystems. Weighted averaging regression models (WARMs) were used to project the relationships between relative macroinvertebrate abundance and water temperature, based on the temperature data of the Intergovernmental Panel on Climate Change (IPCC) A1B scenario. Maximum tolerance water temperatures were used to quantify the risks to macroinvertebrates at the catchment and national scales. Ambient air temperatures in the 2090s were projected to increase by an average of 3.4?ºC relative to the baseline of the 2000s at the national scale. Mayflies, stoneflies and caddisflies were identified as potentially the most sensitive taxa to global warming. The impact of global warming on macroinvertebrates was predicted to be minimal prior to the 2060s; however, by the 2080s, species loss was predicted to be 55 %. Potential distribution ranges of cold water species in the future decades were expected to decrease continuously over time, while those of warm species were expected to increase from the 2000s to the 2040s and then decrease until the 2080s. Our projections may be useful for understanding how climate parameters affect the biogeographical patterns of aquatic biodiversity from a thermal-preference perspective.     

气候变化条件下雅砻江流域未来径流变化趋势研究

雅砻江为我国重要的水电基地,未来气候变化条件下流域径流变化将直接影响雅砻江梯级水库群运行安全和发电调度,因此研究气候变化对雅砻江流域径流的影响十分必要。首先建立了流域月尺度的SWAT模型,然后使用统计降尺度模型（SDSM）模拟未来2006—2100年流域内各站点的气象数据,最后使用流域SWAT模型对未来2006—2100年月径流进行模拟。结果表明,未来雅砻江流域径流呈上升趋势,且增幅随着辐射强迫的增加同步增大,RCP2.6、RCP4.5、RCP8.5这3种典型浓度路径下年平均径流增幅分别为8.9%、12.5%、16.7%,且2020S（2006—2035年)、2050S（2036—2065年)、2080S（2066—2100年）这3个时期年径流量呈现不同的变化趋势,其中RCP2.6浓度路径下为先逐步增加达到峰值后略有减少,RCP4.5浓度路径下为先逐步增加达到峰值后趋于稳定,RCP8.5浓度路径下为持续增加。流域径流年内分配方面,3种典型浓度路径下汛期径流占全年比例在2020S、2050S、2080S这3个时期均为先降后升趋势,整个预测期总体为降低趋势,RCP2.6、RCP4.5及RCP8.5这3种浓度路径下整个预测期的均值分别由基准期的75.9%降低为72.9%、72.0%、71.2%。径流增加会对流域洪水特性产生较大影响,为此应该修正流域设计洪水计算结果和调整防洪调度方案,以降低雅砻江流域梯级水库群因气候变化而产生的运行风险,并提高发电调度效率。     

Sea water surface energy balance in the Arctic fjord (Hornsund,SW Spitsbergen) in May–November 2014

Maize is grown by millions of smallholder farmers in South Asia (SA) under diverse environments. The crop is grown in different seasons in a year with varying exposure to weather extremes, including high temperatures at critical growth stages which are expected to increase with climate change. This study assesses the impact of current and future heat stress on maize and the benefit of heat-tolerant varieties in SA. Annual mean maximum temperatures may increase by 1.4–1.8 °C in 2030 and 2.1–2.6 °C in 2050, with large monthly, seasonal, and spatial variations across SA. The extent of heat stressed areas in SA could increase by up to 12 % in 2030 and 21 % in 2050 relative to the baseline. The impact of heat stress and the benefit from heat-tolerant varieties vary with the level of temperature increase and planting season. At a regional scale, climate change would reduce rainfed maize yield by an average of 3.3–6.4 % in 2030 and 5.2–12.2 % in 2050 and irrigated yield by 3–8 % in 2030 and 5–14 % in 2050 if current varieties were grown under the future climate. Under projected climate, heat-tolerant varieties could minimize yield loss (relative to current maize varieties) by up to 36 and 93 % in 2030 and 33 and 86 % in 2050 under rainfed and irrigated conditions, respectively. Heat-tolerant maize varieties, therefore, have the potential to shield maize farmers from severe yield loss due to heat stress and help them adapt to climate change impacts.     

Simulation of extreme precipitation indices in the Yangtze River basin by using statistical downscaling method (SDSM)

In this study, the applicability of the statistical downscaling model (SDSM) in modeling five extreme precipitation indices including R10 (no. of days with precipitation ≥10?mm?day^?1), SDI (simple daily intensity), CDD (maximum number of consecutive dry days), R1d (maximum 1-day precipitation total) and R5d (maximum 5-day precipitation total) in the Yangtze River basin, China was investigated. The investigation mainly includes the calibration and validation of SDSM model on downscaling daily precipitation, the validation of modeling extreme precipitation indices using independent period of the NCEP reanalysis data, and the projection of future regional scenarios of extreme precipitation indices. The results showed that: (1) there existed good relationship between the observed and simulated extreme precipitation indices during validation period of 1991–2000, the amount and the change pattern of extreme precipitation indices could be reasonably simulated by SDSM. (2) Under both scenarios A2 and B2, during the projection period of 2010–2099, the changes of annual mean extreme precipitation indices in the Yangtze River basin would be not obvious in 2020s; while slightly increase in the 2050s; and significant increase in the 2080s as compared to the mean values of the base period. The summer might be the more distinct season with more projected increase of each extreme precipitation indices than in other seasons. And (3) there would be distinctive spatial distribution differences for the change of annual mean extreme precipitation indices in the river basin, but the most of Yangtze River basin would be dominated by the increasing trend.     

Global warming and hurricanes: the potential impact of hurricane intensification and sea level rise on coastal flooding

Tens of millions of people around the world are already exposed to coastal flooding from tropical cyclones. Global warming has the potential to increase hurricane flooding, both by hurricane intensification and by sea level rise. In this paper, the impact of hurricane intensification and sea level rise are evaluated using hydrodynamic surge models and by considering the future climate projections of the Intergovernmental Panel on Climate Change. For the Corpus Christi, Texas, United States study region, mean projections indicate hurricane flood elevation (meteorologically generated storm surge plus sea level rise) will, on average, rise by 0.3 m by the 2030s and by 0.8 m by the 2080s. For catastrophic-type hurricane surge events, flood elevations are projected to rise by as much as 0.5 m and 1.8 m by the 2030s and 2080s, respectively.     

Climate change impacts on sugarcane attainable yield in southern Brazil

This study evaluated the effects of climate change on sugarcane yield, water use efficiency, and irrigation needs in southern Brazil, based on downscaled outputs of two general circulation models (PRECIS and CSIRO) and a sugarcane growth model. For three harvest cycles every year, the DSSAT/CANEGRO model was used to simulate the baseline and four future climate scenarios for stalk yield for the 2050s. The model was calibrated for the main cultivar currently grown in Brazil based on five field experiments under several soil and climate conditions. The sensitivity of simulated stalk fresh mass (SFM) to air temperature, CO₂ concentration [CO₂] and rainfall was also analyzed. Simulated SFM responses to [CO₂], air temperature and rainfall variations were consistent with the literature. There were increases in simulated SFM and water usage efficiency (WUE) for all scenarios. On average, for the current sugarcane area in the State of São Paulo, SFM would increase 24 % and WUE 34 % for rainfed sugarcane. The WUE rise is relevant because of the current concern about water supply in southern Brazil. Considering the current technological improvement rate, projected yields for 2050 ranged from 96 to 129 t?ha^?1, which are respectively 15 and 59 % higher than the current state average yield.     

Aerosol and ozone changes as forcing for climate evolution between 1850 and 2100

Global aerosol and ozone distributions and their associated radiative forcings were simulated between 1850 and 2100 following a recent historical emission dataset and under the representative concentration pathways (RCP) for the future. These simulations were used in an Earth System Model to account for the changes in both radiatively and chemically active compounds, when simulating the climate evolution. The past negative stratospheric ozone trends result in a negative climate forcing culminating at ?0.15 W m^?2 in the 1990s. In the meantime, the tropospheric ozone burden increase generates a positive climate forcing peaking at 0.41 W m^?2. The future evolution of ozone strongly depends on the RCP scenario considered. In RCP4.5 and RCP6.0, the evolution of both stratospheric and tropospheric ozone generate relatively weak radiative forcing changes until 2060–2070 followed by a relative 30 % decrease in radiative forcing by 2100. In contrast, RCP8.5 and RCP2.6 model projections exhibit strongly different ozone radiative forcing trajectories. In the RCP2.6 scenario, both effects (stratospheric ozone, a negative forcing, and tropospheric ozone, a positive forcing) decline towards 1950s values while they both get stronger in the RCP8.5 scenario. Over the twentieth century, the evolution of the total aerosol burden is characterized by a strong increase after World War II until the middle of the 1980s followed by a stabilization during the last decade due to the strong decrease in sulfates in OECD countries since the 1970s. The cooling effects reach their maximal values in 1980, with ?0.34 and ?0.28 W m^?2 respectively for direct and indirect total radiative forcings. According to the RCP scenarios, the aerosol content, after peaking around 2010, is projected to decline strongly and monotonically during the twenty-first century for the RCP8.5, 4.5 and 2.6 scenarios. While for RCP6.0 the decline occurs later, after peaking around 2050. As a consequence the relative importance of the total cooling effect of aerosols becomes weaker throughout the twenty-first century compared with the positive forcing of greenhouse gases. Nevertheless, both surface ozone and aerosol content show very different regional features depending on the future scenario considered. Hence, in 2050, surface ozone changes vary between ?12 and +12 ppbv over Asia depending on the RCP projection, whereas the regional direct aerosol radiative forcing can locally exceed ?3 W m^?2.     

Tracking suitable habitat for tree populations under climate change in western North America

An important criticism of bioclimate envelope models is that many wide-ranging species consist of locally adapted populations that may all lag behind their optimal climate habitat under climate change, and thus should be modeled separately. Here, we apply a bioclimate envelope model that tracks habitat of individual populations to estimate adaptational lags for 15 wide-ranging forest tree species in western North America. An ensemble classifier modeling approach (RandomForest) was used to spatially project the climate space of tree populations under observed climate trends (1970s to 2000s) and multi-model projections for the 2020s, 2050s and 2080s. We find that, on average, populations already lag behind their optimal climate niche by approximately 130 km in latitude, or 60 m in elevation. For the 2020s we expect an average lag of approximately 310 km in latitude or 140 m in elevation, with the most pronounced geographic lags in the Rocky Mountains and the boreal forest. We show that our results could in principle be applied to guide assisted migration of planting stock in reforestation programs using a general formula where 100 km north shift is equivalent to approximately 44 m upward shift in elevation. However, additional non-climatic factors should be considered when matching reforestation stock to suitable planting environments.     

Glacial mass balance changes in the Karakoram and Himalaya based on CMIP5 multi-model climate projections

The impact of future climate change on the glaciers in the Karakoram and Himalaya (KH) is investigated using CMIP5 multi-model temperature and precipitation projections, and a relationship between glacial accumulation-area ratio and mass balance developed for the region based on the last 30 to 40 years of observational data. We estimate that the current glacial mass balance (year 2000) for the entire KH region is -6.6?±?1 Gta^?1, which decreases about sixfold to -35?±?2 Gta^?1 by the 2080s under the high emission scenario of RCP8.5. However, under the low emission scenario of RCP2.6 the glacial mass loss only doubles to -12?±?2 Gta^?1 by the 2080s. We also find that 10.6 and 27 % of the glaciers could face ‘eventual disappearance’ by the end of the century under RCP2.6 and RCP8.5 respectively, underscoring the threat to water resources under high emission scenarios.     

Effects of projected climate change on energy supply and demand in the Pacific Northwest and Washington State

Climate strongly affects energy supply and demand in the Pacific Northwest (PNW) and Washington State (WA). We evaluate potential effects of climate change on the seasonality and annual amount of PNW hydropower production, and on heating and cooling energy demand. Changes in hydropower production are estimated by linking simulated streamflow scenarios produced by a hydrology model to a simulation model of the Columbia River hydro system. Changes in energy demand are assessed using gridded estimates of heating degree days (HDD) and cooling degree days (CDD) which are then combined with population projections to create energy demand indices that respond both to climate, future population, and changes in residential air conditioning market penetration. We find that substantial changes in the amount and seasonality of energy supply and demand in the PNW are likely to occur over the next century in response to warming, precipitation changes, and population growth. By the 2040s hydropower production is projected to increase by 4.7–5.0% in winter, decrease by about 12.1–15.4% in summer, with annual reductions of 2.0–3.4%. Larger decreases of 17.1–20.8% in summer hydropower production are projected for the 2080s. Although the combined effects of population growth and warming are projected to increase heating energy demand overall (22–23% for the 2020s, 35–42% for the 2040s, and 56–74% for the 2080s), warming results in reduced per capita heating demand. Residential cooling energy demand (currently less than one percent of residential demand) increases rapidly (both overall and per capita) to 4.8–9.1% of the total demand by the 2080s due to increasing population, cooling degree days, and air conditioning penetration.