Climate change impacts on the energy system: a review of trends and gaps

Major transformation of the global energy system is required for climate change mitigation. However, energy demand patterns and supply systems are themselves subject to climate change impacts. These impacts will variously help and hinder mitigation and adaptation efforts, so it is vital they are well understood and incorporated into models used to study energy system decarbonisation pathways. To assess the current state of understanding of this topic and identify research priorities, this paper critically reviews the literature on the impacts of climate change on the energy supply system, summarising the regional coverage of studies, trends in their results and sources of disagreement. We then examine the ways in which these impacts have been represented in integrated assessment models of the electricity or energy system.Studies tend to agree broadly on impacts for wind, solar and thermal power stations. Projections for impacts on hydropower and bioenergy resources are more varied. Key uncertainties and gaps remain due to the variation between climate projections, modelling limitations and the regional bias of research interests. Priorities for future research include the following: further regional impact studies for developing countries; studies examining impacts of the changing variability of renewable resources, extreme weather events and combined hazards; inclusion of multiple climate feedback mechanisms in IAMs, accounting for adaptation options and climate model uncertainty.     

Assessing the robustness of adaptation decisions to climate change uncertainties: A case study on water resources management in the East of England

Projections of future climate change are plagued with uncertainties, causing difficulties for planners taking decisions on adaptation measures. This paper presents an assessment framework that allows the identification of adaptation strategies that are robust (i.e. insensitive) to climate change uncertainties. The framework is applied to a case study of water resources management in the East of England, more specifically to the Anglian Water Services’ 25 year Water Resource Plan (WRP). The paper presents a local sensitivity analysis (a ‘one-at-a-time’ experiment) of the various elements of the modelling framework (e.g., emissions of greenhouse gases, climate sensitivity and global climate models) in order to determine whether or not a decision to adapt to climate change is sensitive to uncertainty in those elements.Water resources are found to be sensitive to uncertainties in regional climate response (from general circulation models and dynamical downscaling), in climate sensitivity and in climate impacts. Aerosol forcing and greenhouse gas emissions uncertainties are also important, whereas uncertainties from ocean mixing and the carbon cycle are not. Despite these large uncertainties, Anglian Water Services’ WRP remains robust to the climate change uncertainties sampled because of the adaptation options being considered (e.g. extension of water treatment works), because the climate model used for their planning (HadCM3) predicts drier conditions than other models, and because ‘one-at-a-time’ experiments do not sample the combination of different extremes in the uncertainty range of parameters. This research raises the question of how much certainty is required in climate change projections to justify investment in adaptation measures, and whether such certainty can be delivered.     

Economic consequences of global climate change and mitigation on future hydropower generation

Hydropower generation plays a key role in mitigating GHG emissions from the overall power supply. Although the maximum achievable hydropower generation (MAHG) will be affected by climate change, it is seldom incorporated in integrated assessment models. In this study, we first used the H08 global hydrological model to project MAHG under two physical climate change scenarios. Then, we used the Asia-Pacific Integrated Model/Computable General Equilibrium integrated assessment model to quantify the economic consequences of the presence or absence of mitigation policy on hydropower generation. This approach enabled us to quantify the physical impacts of climate change and the effect of mitigation policy—together and in isolation—on hydropower generation and the economy, both globally and regionally. Although there was little overall global change, we observed substantial differences among regions in the MAHG average change (from ??71% in Middle East to 14% in Former Soviet Union in RCP8.5). We found that the magnitude of changes in regional gross domestic product (GDP) was small negative (positive) in Brazil (Canada) by 2100, for the no mitigation policy scenario. These consequences were intensified with the implementation of mitigation policies that enhanced the price competitiveness of hydropower against fossil fuel-powered technologies. Overall, our results suggested that there would be no notable globally aggregated impacts on GDP by 2100 because the positive effects in some regions were canceled out by negative effects in other regions.     

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.     

The benefits of quantifying climate model uncertainty in climate change impacts assessment: an example with heat-related mortality change estimates

The majority of climate change impacts assessments account for climate change uncertainty by adopting the scenario-based approach. This typically involves assessing the impacts for a small number of emissions scenarios but neglecting the role of climate model physics uncertainty. Perturbed physics ensemble (PPE) climate simulations offer a unique opportunity to explore this uncertainty. Furthermore, PPEs mean it is now possible to make risk-based impacts estimates because they allow for a range of estimates to be presented to decision-makers, which spans the range of climate model physics uncertainty inherent from a given climate model and emissions scenario, due to uncertainty associated with the understanding of physical processes in the climate model. This is generally not possible with the scenario-based approach. Here, we present the first application of a PPE to estimate the impact of climate change on heat-related mortality. By using the estimated impacts of climate change on heat-related mortality in six cities, we demonstrate the benefits of quantifying climate model physics uncertainty in climate change impacts assessment over the more common scenario-based approach. We also show that the impacts are more sensitive to climate model physics uncertainty than they are to emissions scenario uncertainty, and least sensitive to whether the climate change projections are from a global climate model or a regional climate model. The results demonstrate the importance of presenting model uncertainties in climate change impacts assessments if the impacts are to be placed within a climate risk management framework.     

The effect of global climate change, population distribution, and climate mitigation on building energy use in the U.S. and China

Climate change will affect the energy system in a number of ways, one of which is through changes in demands for heating and cooling in buildings. Understanding the potential effect of climate change on heating and cooling demands requires taking into account not only the manner in which the building sector might evolve over time, but also important uncertainty about the nature of climate change itself. In this study, we explore the uncertainty in climate change impacts on heating and cooling requirement by constructing estimates of heating and cooling degree days (HDD/CDDs) for both reference (no-policy) and 550 ppmv CO₂ concentration pathways built from three different Global Climate Models (GCMs) output and three scenarios of gridded population distribution. The implications that changing climate and population distribution might have for building energy consumption in the U.S. and China are then explored by using the results of HDD/CDDs as inputs to a detailed, building energy model, nested in the long-term global integrated assessment framework, Global Change Assessment Model (GCAM). The results across the modeled changes in climate and population distributions indicate that unabated climate change would cause building sector’s final energy consumption to decrease modestly (6 % decrease or less depending on climate models) in both the U.S. and China by the end of the century as decreased heating consumption more than offsets increased cooling using primarily electricity. However, global climate change virtually has negligible effect on total CO₂ emissions in the buildings sector in both countries. The results also indicate more substantial implications for the fuel mix with increases in electricity and decreases in other fuels, which may be consistent with climate mitigation goals. The variation in results across all scenarios due to variation of population distribution is smaller than variation due to the use of different climate models.     

Assessing climate change impacts on hydrology from an ensemble of regional climate models,model scales and linking methods – a case study on the Lule River basin

This paper investigates how using different regional climate model (RCM) simulations affects climate change impacts on hydrology in northern Europe using an offline hydrological model. Climate change scenarios from an ensemble of seven RCMs, two global climate models (GCMs), two global emissions scenarios and two RCMs of varying resolution were used. A total of 15 climate change simulations were included in studies on the Lule River basin in Northern Sweden. Two different approaches to transfer climate change from the RCMs to hydrological models were tested. A rudimentary estimate of change in hydropower potential on the Lule River due to climate change was also made. The results indicate an overall increase in river flow, earlier spring peak flows and an increase in hydropower potential. The two approaches for transferring the signal of climate change to the hydrological impacts model gave similar mean results, but considerably different seasonal dynamics, a result that is highly relevant for other types of climate change impacts studies.     

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.     

Adaptation of California’s electricity sector to climate change

Climate change is likely to pose considerable new challenges to California’s electricity sector. This paper primarily focuses on the adaptation challenges of an important component of the energy arena: electricity demand in the residential and commercial sectors and electricity supply. The primary challenge to California’s electricity sector will likely be the increase in demand for air conditioning as a result of rising temperatures. In addition, renewable energy sources, which are an increasing share of the electricity portfolio, are particularly vulnerable to climate change. Many of the key players have been actively considering the implications of climate change. Because electricity generation accounts for nearly 30% of greenhouse gas emissions, this sector has been a target of the state’s efforts to reduce emissions. Fortunately, many of the same tools can simultaneously improve the sector’s resilience to a changing climate. Demand management strategies and supply diversification are both important strategies. Local governments can play a central role in encouraging the adoption of more energy efficient building codes and the use of more renewable sources, such as solar energy. The positive steps taken by many local governments are encouraging. Steps to increase public awareness are an important, often missing component, however. Increases in research, development, and demonstration to improve system resiliency and develop new energy conservation tools are also needed.     

Multi-model assessment of global hydropower and cooling water discharge potential under climate change

Worldwide, 98% of total electricity is currently produced by thermoelectric power and hydropower. Climate change is expected to directly impact electricity supply, in terms of both water availability for hydropower generation and cooling water usage for thermoelectric power. Improved understanding of how climate change may impact the availability and temperature of water resources is therefore of major importance. Here we use a multi-model ensemble to show the potential impacts of climate change on global hydropower and cooling water discharge potential. For the first time, combined projections of streamflow and water temperature were produced with three global hydrological models (GHMs) to account for uncertainties in the structure and parametrization of these GHMs in both water availability and water temperature. The GHMs were forced with bias-corrected output of five general circulation models (GCMs) for both the lowest and highest representative concentration pathways (RCP2.6 and RCP8.5). The ensemble projections of streamflow and water temperature were then used to quantify impacts on gross hydropower potential and cooling water discharge capacity of rivers worldwide. We show that global gross hydropower potential is expected to increase between +2.4% (GCM-GHM ensemble mean for RCP 2.6) and +6.3% (RCP 8.5) for the 2080s compared to 1971–2000. The strongest increases in hydropower potential are expected for Central Africa, India, central Asia and the northern high-latitudes, with 18–33% of the world population living in these areas by the 2080s. Global mean cooling water discharge capacity is projected to decrease by 4.5-15% (2080s). The largest reductions are found for the United States, Europe, eastern Asia, and southern parts of South America, Africa and Australia, where strong water temperature increases are projected combined with reductions in mean annual streamflow. These regions are expected to affect 11–14% (for RCP2.6 and the shared socio-economic pathway (SSP)1, SSP2, SSP4) and 41–51% (RCP8.5–SSP3, SSP5) of the world population by the 2080s.     

Challenges for hydropower-based nationally determined contributions: a case study for Ecuador

Hydropower is the dominant renewable energy source to date, providing over two-thirds of all renewable electricity globally. For countries with significant hydropower potential, the technology is expected to play a major role in the energy transition needed to meet nationally determined contributions (NDCs) for greenhouse gas (GHG) emission reductions as laid out in the Paris Agreement. For the Republic of Ecuador, large hydropower is currently considered as the main means for attaining energy security, reducing electricity prices and mitigating GHG emissions in the long-term. However, uncertainty around the impacts of climate change, investment cost overruns and restrictions to untapped resources may challenge the future deployment of hydropower and consequently impact decarbonization efforts for Ecuador’s power sector. To address these questions, a partial equilibrium energy system optimization model for Ecuador (TIMES-EC) is used to simulate alternative electricity capacity expansion scenarios up to 2050. Results show that the share of total electricity supplied by hydropower in Ecuador might vary significantly between 53% to 81% by 2050. Restricting large hydropower due to social-environmental constraints can cause a fourfold increase in cumulative emissions compared to NDC implied levels, while a 25% reduction of hydropower availability due to climate change would cause cumulative emissions to double. In comparison, a more diversified power system (although more expensive) which limits the share of large hydropower and natural gas in favour of other renewables could achieve the expected NDC emission levels. These insights underscore the critical importance of undertaking detailed whole energy system analyses to assess the long-term challenges for hydropower deployment and the trade-offs among power system configuration, system costs and expected GHG emissions in hydropower-dependent countries, states and territories.

Key policy insights

• Ecuador’s hydropower-based NDC is highly vulnerable to the occurrence of a dry climate scenario and restrictions to deployment of large hydropower in the Amazon region.

• Given Ecuador’s seasonal runoff pattern, fossil-fuel or renewable thermoelectric backup will always be required, whatever the amount of hydropower installed.

• Ecuador’s NDC target for the power sector is achievable without the deployment of large hydropower infrastructure, through a more diversified portfolio with non-hydro renewables.

     

Assessing climate change impacts on the Iberian power system using a coupled water-power model

Climate change is expected to have a negative impact on the power system of the Iberian Peninsula; changes in river runoff are expected to reduce hydropower generation, while higher temperatures are expected to increase summer electricity demand, when water resources are already limited. However, these impacts have not yet been evaluated at the peninsular level. We coupled a hydrological model with a power market model to study three impacts of climate change on the current Iberian power system: changes in hydropower production caused by changes in precipitation and temperature, changes in temporal patterns of electricity demand caused by temperature changes, and changes in irrigation water use caused by temperature and precipitation changes. A stochastic dynamic programming approach was used to develop operating rules for the integrated system given hydrological uncertainty. We found that changes in precipitation will reduce runoff, decrease hydropower production (with accompanying increases in thermal generation), and increase irrigation water use, while higher temperatures will shift power demand from winter to summer months. The combined impact of these effects will generally make it more challenging to balance agricultural, power, and environmental objectives in the operation of Iberian reservoirs, though some impacts could be mitigated by better alignment between temporal patterns of irrigation and power demands.     

High resolution modeling of the regional impacts of climate change on irrigation water demand

In the Arkansas River Basin in southeastern Colorado, surface irrigation provides most of the water required for agriculture. Consequently, the region’s future could be significantly affected if climate change impacts the amount of water available for irrigation. A methodology to model the expected impacts of climate change on irrigation water demand in the region is described. The Integrated Decision Support Consumptive Use model, which accounts for spatial and temporal variability in evapotranspiration and precipitation, is used in conjunction with two climate scenarios from the Vegetation-Ecosystem Modeling and Analysis Project. The two scenarios were extracted and scaled down from two general circulation models (GCMs), the HAD from the Hadley Centre for Climate Prediction and Research and the CCC from the Canadian Climate Centre. The results show significant changes in the water demands of crops due to climate change. The HAD and CCC climate change scenarios both predict an increase in water demand. However, the projections of the two GCMs concerning the water available for irrigation differ significantly, reflecting the large degree of uncertainty concerning what the future impacts of climate change might be in the study region. As new or updated predictions become available, the methodology described here can be used to estimate the impacts of climate change.     

可计算一般均衡框架下的气候变化经济影响综合评估

气候变化是21世纪人类面临的重大挑战之一,并对自然系统和社会经济系统造成了各种负面影响。对气候变化的影响进行经济评估是气候变化研究中的重要问题。而可计算一般均衡框架下的综合评估模型（CGE_IAMs）是评估气候变化经济影响的有效手段之一,文中对气候变化影响经济评估的主要CGE_IAMs进行了文献调研,并对这些模型进行了比较分析。研究表明不同模型在温室气体排放、气候参数的处理方式以及气候影响的引入机制等方面有着较大区别,因而各模型对气候变化影响的经济评估结果也有一定的差异。此外,当前CGE_IAMs在评估气候变化经济影响时存在支撑数据未及时更新、方法不细致以及评估不全面等问题。未来该领域的相关研究应该更加关注于模型与支撑数据的精细化和开源化,此外还应加强CGE_IAMs中经济模块与复杂气候模式的耦合。     

Integrated Global System Model for Climate Policy Assessment: Feedbacks and Sensitivity Studies

Alternative policies to address global climate change are being debated in many nations and within the United Nations Framework Convention on Climate Change. To help provide objective and comprehensive analyses in support of this process, we have developed a model of the global climate system consisting of coupled sub-models of economic growth and associated emissions, natural fluxes, atmospheric chemistry, climate, and natural terrestrial ecosystems. The framework of this Integrated Global System Model is described and the results of sample runs and a sensitivity analysis are presented. This multi-component model addresses most of the major anthropogenic and natural processes involved in climate change and also is computationally efficient. As such, it can be used effectively to study parametric and structural uncertainty and to analyze the costs and impacts of many policy alternatives. Initial runs of the model have helped to define and quantify a number of feedbacks among the sub-models, and to elucidate the geographical variations in several variables that are relevant to climate science and policy. The effect of changes in climate and atmospheric carbon dioxide levels on the uptake of carbon and emissions of methane and nitrous oxide by land ecosystems is one potentially important feedback which has been identified. The sensitivity analysis has enabled preliminary assessment of the effects of uncertainty in the economic, atmospheric chemistry, and climate sub-models as they influence critical model results such as predictions of temperature, sea level, rainfall, and ecosystem productivity. We conclude that uncertainty regarding economic growth, technological change, deep oceanic circulation, aerosol radiative forcing, and cloud processes are important influences on these outputs.     

Uncertainty analysis of statistical downscaling models using general circulation model over an international wetland

Regression-based statistical downscaling model (SDSM) is an appropriate method which broadly uses to resolve the coarse spatial resolution of general circulation models (GCMs). Nevertheless, the assessment of uncertainty propagation linked with climatic variables is essential to any climate change impact study. This study presents a procedure to characterize uncertainty analysis of two GCM models link with Long Ashton Research Station Weather Generator (LARS-WG) and SDSM in one of the most vulnerable international wetland, namely “Shadegan” in an arid region of Southwest Iran. In the case of daily temperature, uncertainty is estimated by comparing monthly mean and variance of downscaled and observed daily data at a 95 % confidence level. Uncertainties were then evaluated from comparing monthly mean dry and wet spell lengths and their 95 % CI in daily precipitation downscaling using 1987–2005 interval. The uncertainty results indicated that the LARS-WG is the most proficient model at reproducing various statistical characteristics of observed data at a 95 % uncertainty bounds while the SDSM model is the least capable in this respect. The results indicated a sequences uncertainty analysis at three different climate stations and produce significantly different climate change responses at 95 % CI. Finally the range of plausible climate change projections suggested a need for the decision makers to augment their long-term wetland management plans to reduce its vulnerability to climate change impacts.     

Safe policies in an uncertain climate: an application of FUND

Various aspects of the role of uncertainty in greenhouse gas emission reduction policy are analyzed with the integrated assessment model FUND. FUND couples simple models of economy, climate, climate impacts, and emission abatement. Probability distribution functions are assumed for all major parameters in the model. Monte Carlo analyses are used to study the effects of parametric uncertainties. Uncertainties are found to be large and grow over time. Uncertainties about climate change impacts are more serious than uncertainties about emission reduction costs, so that welfare-maximizing policies are stricter under uncertainty than under certainty. This is more pronounced without than with international cooperation. Whether or not countries cooperate with one another is more important than whether or not uncertainty is considered. Meeting exogenously defined emission targets may be more or less difficult under uncertainty than under certainty, depending on the asymmetry in the uncertainty and the central estimate of interest. The major uncertainty in meeting emissions targets in each of a range of possible future is the timing of starting (serious) reduction policies. In a scenario aiming at a stable CO₂ concentration of 550 ppm, the start date varies 20 years for Annex I countries, and much longer for non-Annex countries. Atmospheric stabilization at 550 ppm does not avoid serious risks with regard to climate change impacts. At the long term, it is possible to avoid such risks but only through very strict emission control at high economic costs.     

Assessing Climate Change Implications for Water Resources Planning

Numerous recent studies have shown that existing water supply systems are sensitive to climate change. One apparent implication is that water resources planning methods should be modified accordingly. Few of these studies, however, have attempted to account for either the chain of uncertainty in projecting water resources system vulnerability to climate change, or the adaptability of system operation resulting from existing planning strategies. Major uncertainties in water resources climate change assessments lie in a) climate modeling skill; b) errors in regional downscaling of climate model predictions; and c) uncertainties in future water demands. A simulation study was designed to provide insight into some aspects of these uncertainties. Specifically, the question that is addressed is whether a different decision would be made in a reservoir reallocation decision if knowledge about future climate were incorporated (i.e., would planning based on climate change information be justified?). The case study is possible reallocation of flood storage to conservation (municipal water supply) on the Green River, WA. We conclude that, for the case study, reservoir reallocation decisions and system performance would not differ significantly if climate change information were incorporated in the planning process.     

Short-term distributional consequences of climate change impacts on the power sector: who gains and who loses?

Climate change tends to negatively affect the power sector, inter alia, by causing cooling problems in power plants and impairing the water supply required for hydropower generation. In the future, when global warming is expected to increase, autonomous adaptation to climate change via international electricity markets inducing reallocations of power generation may not be sufficient to prevent supply disruptions anymore. Furthermore, the consequent changes of supply patterns and electricity prices might cause an undesirable redistribution of wealth both between individual power suppliers and between suppliers and consumers. This study ascertains changes in European power supply patterns and electricity prices caused by on-going global warming as well as the associated redistribution of wealth for different climate change scenarios. The focus of the analysis is on short-term effects. Our results confirm that autonomous adaptation in the power sector should be complemented by planned public adaptation in order to preserve energy security and to prevent undesired distributional effects.     

The AVOID programme’s new simulations of the global benefits of stringent climate change mitigation

Quantitative simulations of the global-scale benefits of climate change mitigation are presented, using a harmonised, self-consistent approach based on a single set of climate change scenarios. The approach draws on a synthesis of output from both physically-based and economics-based models, and incorporates uncertainty analyses. Previous studies have projected global and regional climate change and its impacts over the 21st century but have generally focused on analysis of business-as-usual scenarios, with no explicit mitigation policy included. This study finds that both the economics-based and physically-based models indicate that early, stringent mitigation would avoid a large proportion of the impacts of climate change projected for the 2080s. However, it also shows that not all the impacts can now be avoided, so that adaptation would also therefore be needed to avoid some of the potential damage. Delay in mitigation substantially reduces the percentage of impacts that can be avoided, providing strong new quantitative evidence for the need for stringent and prompt global mitigation action on greenhouse gas emissions, combined with effective adaptation, if large, widespread climate change impacts are to be avoided. Energy technology models suggest that such stringent and prompt mitigation action is technologically feasible, although the estimated costs vary depending on the specific modelling approach and assumptions.