Simulating the future wind energy resource of Ireland using the COSMO‐CLM model

We consider the impact of climate change on the wind energy resource of Ireland using an ensemble of regional climate model (RCM) simulations. The RCM used in this work is the Consortium for Small‐scale Modelling–climate limited‐area modelling (COSMO‐CLM) model. The COSMO‐CLM model was evaluated by performing simulations of the past Irish climate, driven by European Centre for Medium‐Range Weather Forecasts ERA‐40 data, and comparing the output with observations. For the investigation of the influence of the future climate under different climate scenarios, the Max Planck Institute's global climate model, ECHAM5, was used to drive the COSMO‐CLM model. Simulations are run for a control period 1961–2000 and future period 2021–2060. To add to the number of ensemble members, the control and future simulations were driven by different realizations of the ECHAM5 data. The future climate was simulated using the Intergovernmental Panel on Climate Change emission scenarios, A1B and B1. The research was undertaken to consolidate, and as a continuation of, similar research using the Rossby Centre's RCA3 RCM to investigate the effects of climate change on the future wind energy resource of Ireland. The COSMO‐CLM projections outlined in this study agree with the RCA3 projections, with both showing substantial increases in 60 m wind speed over Ireland during winter and decreases during summer. The projected changes of both studies were found to be statistically significant over most of Ireland. The agreement of the COSMO‐CLM and RCA3 simulation results increases our confidence in the robustness of the projections. Copyright © 2012 John Wiley & Sons, Ltd.     

Climate change implications for wind power resources in the Northwest United States

Using statistically downscaled output from four general circulation models (GCMs), we have investigated scenarios of climate change impacts on wind power generation potential in a five-state region within the Northwest United States (Idaho, Montana, Oregon, Washington, and Wyoming). All GCM simulations were extracted from the standardized set of runs created for the Intergovernmental Panel on Climate Change (IPCC). Analysis of model runs for the 20th century (20c3m) simulations revealed that the direct output of wind statistics from these models is of relatively poor quality compared with observations at airport weather stations within each state. When the GCM output was statistically downscaled, the resulting estimates of current climate wind statistics are substantially better. Furthermore, in looking at the GCM wind statistics for two IPCC future climate scenarios from the Special Report on Emissions Scenarios (SRES A1B and A2), there was significant disagreement in the direct model output from the four GCMs. When statistical downscaling was applied to the future climate simulations, a more coherent story unfolded related to the likely impact of climate change on the region's wind power resource. Specifically, the results suggest that summertime wind speeds in the Northwest may decrease by 5–10%, while wintertime wind speeds may decrease by relatively little, or possibly increase slightly. When these wind statistics are projected to typical turbine hub heights and nominal wind turbine power curves are applied, the impact of the climate change scenarios on wind power may be as high as a 40% reduction in summertime generation potential.     

Projected changes in wind speed and its energy potential in China using a high‐resolution regional climate model

Following its commitment to Paris Agreement in 2015, China has started to explore potential renewable energy solutions with low carbon emissions to mitigate global warming. Though wind energy is one of the most cost‐effective solutions and has been favored for climate policy development around the world, its high sensitivity to climate change raises some critical issues for the long‐term effectiveness in providing sustainable energy supply. Particularly, how wind speed and its energy potential in China will change in the context of global warming is still not well understood. In this paper, we simulate the near‐surface wind speed over China using the PRECIS regional climate modeling system under different RCP emission scenarios for assessing the possible changes in wind speed and wind energy availability over China throughout the 21^st century. Overall, the PRECIS model can reasonably reproduce the mesoscale climatological near‐surface wind speed and directions as documented in reanalysis data across most regions of China, while some local discrepancies are reported in the southwestern regions. In the future, the annual mean wind speed would be decreasing in most regions of China, except for a slightly increase in the southeast. The expected changes in wind speed are characterized with different amplitudes and rates under different RCP emission scenarios. The changes in the spatial distribution of wind speed seem to be sensitive for RCP climate emission scenarios, especially in the late 21^st century. The spatiotemporal changes in wind energy potential exhibit a similar behavior to those in near‐surface wind speed, but the magnitudes of these changes are larger. In general, the wind power density is expected to increase by over 5% in winter in the major wind fields in China (ie, Northwest, Northcentral and Northeast), while significant decreases (by about 6% on average) are projected for other seasons (ie, spring, summer and autumn). By contrast, the wind energy potential in the northeast would increase over most months in the year, especially in winter and summer. The results of this research are of great importance for understanding where and to what extent the wind energy can be utilized to contribute renewable energy system development in China in support of its long‐term climate change mitigation commitment.     

Vulnerability of wind power resources to climate change in the continental United States

Renewable energy resources will play a key role in meeting the world's energy demand over the coming decades. Unfortunately, these resources are all susceptible to variations in climate, and hence vulnerable to climate change. Recent findings in the atmospheric science literature suggest that the impacts of greenhouse gas induced warming are likely to significantly alter climate patterns in the future. In this paper we investigate the potential impacts of climate change on wind speeds and hence on wind power, across the continental US. General Circulation Model output from the Canadian Climate Center and the Hadley Center were used to provide a range of possible variations in seasonal mean wind magnitude. These projections were used to investigate the vulnerability of current and potential wind power generation regions. The models were generally consistent in predicting that the US will see reduced wind speeds of 1.0 to 3.2% in the next 50 years, and 1.4 to 4.5% over the next 100 years. In both cases the Canadian model predicted larger decreases in wind speeds. At regional scales the two models showed some similarities in early years of simulations (e.g. 2050), but diverged significantly in their predictions for 2100. Hence, there is still a great deal of uncertainty regarding how wind fields will change in the future. Nevertheless, the two models investigated here are used as possible scenarios for use in investigating regional wind power vulnerabilities, and point to the need to consider climate variability and long term climate change in citing wind power facilities.     

Projected changes in wind energy potentials over Iberia

Wind energy potential in Iberia is assessed for recent–past (1961–2000) and future (2041–2070) climates. For recent–past, a COSMO-CLM simulation driven by ERA-40 is used. COSMO-CLM simulations driven by ECHAM5 following the A1B scenario are used for future projections. A 2 MW rated power wind turbine is selected. Mean potentials, inter-annual variability and irregularity are discussed on annual/seasonal scales and on a grid resolution of 20 km. For detailed regional assessments eight target sites are considered. For recent–past conditions, the highest daily mean potentials are found in winter over northern and eastern Iberia, particularly on high-elevation or coastal regions. In northwestern Iberia, daily potentials frequently reach maximum wind energy output (50 MWh day⁻¹), particularly in winter. Southern Andalucía reveals high potentials throughout the year, whereas the Ebro valley and central-western coast show high potentials in summer. The irregularity in annual potentials is moderate (<15% of mean output), but exacerbated in winter (40%). Climate change projections show significant decreases over most of Iberia (<2 MWh day⁻¹). The strong enhancement of autumn potentials in Southern Andalucía is noteworthy (>2 MWh day⁻¹). The northward displacement of North Atlantic westerly winds (autumn–spring) and the strengthening of easterly flows (summer) are key drivers of future projections.     

Projection of global wind and solar resources over land in the 21st century

This study modelled projected spatiotemporal changes in global wind and solar resources over land in the 21^st century under the RCP2.6 and RCP8.5 climate scenarios using an ensemble mean drawn from 11 Coupled Model Inter-comparison Project Phase 5 (CMIP5) models. These models’ performances were verified by comparing historical global near-surface wind speed and downward surface solar radiation over land. Compared to the baseline historical period 1985–2005, the distribution of relative projected changes in global wind and solar resources had great spatial and seasonal discrepancies. Under both climate scenarios, projected wind resources throughout the 21^st century presented a decreasing trend in Asia and Europe but an increasing trend in the low-latitude Americas. In comparison, projected global solar resources over land generally showed an increasing trend throughout the 21^st century, especially in Europe, eastern Asia, and eastern North America. Moreover, wind resources in the Americas had their most significant decrease and increase in January and July, respectively, while in Asia and Europe the decreasing trend as most prominent in January and October, respectively. The most significant increases in solar resources in the Americas, Asia, and Europe happened in October and July, respectively. Discrepancies between the variation trends of future global wind and solar resources suggest the complexity and nonlinearity of these resources’ responses to future climate change.     

Characterization of the wind speed variability and future change in the Iberian Peninsula and the Balearic Islands

Wind energy is susceptible to global climate change because it could alter the wind patterns. Then, improvement of our knowledge of wind field variability is crucial to optimize the use of wind resources in a given region. Here, we quantify the effects of climate change on the surface wind speed field over the Iberian Peninsula and Balearic Islands using an ensemble of four regional climate models driven by a global climate model. Regions of the Iberian Peninsula with coherent temporal variability in wind speed in each of the models are identified and analysed using cluster analysis. These regions are continuous in each model and exhibit a high degree of overlap across the models. The models forced by the European Reanalysis Interim (ERA‐Interim) reanalysis are validated against the European Climate Assessment and Dataset wind. We find that regional models are able to simulate with reasonable skill the spatial distribution of wind speed at 10 m in the Iberian Peninsula, identifying areas with common wind variability. Under the Special Report on Emissions Scenarios (SRES) A1B climate change scenario, the wind speed in the identified regions for 2031–2050 is up to 5% less than during the 1980–1999 control period for all models. The models also agree on the time evolution of spatially averaged wind speed in each region, showing a negative trend for all of them. These tendencies depend on the region and are significant at p = 5% or slightly more for annual trends, while seasonal trends are not significant in most of the regions and seasons. Copyright © 2015 John Wiley & Sons, Ltd.     

Projected impacts of climate change on wind energy density in the United States

Wind-generated electricity is a growing renewable energy resource. Because wind results from the uneven heating (and resulting pressure gradients) of the Earth, future wind resources may be affected by anticipated climate change. Many studies have used global and regional climate models to predict trends in the future wind resource over the continental United States. While some of these studies identified regions that are expected to gain wind energy, their results often come with a high degree of uncertainty, and lack of agreement across different climate models. In this paper we focus on wind energy density as a measure of the available wind resource over the continental United States. We estimate the change in wind energy density from the period 1968–2000 to the period 2038–2070 by using output from four regional climate models from the North American Regional Climate Change Assessment Program (NARCCAP). We find strong agreement across all 4 models that the wind energy resource is expected to increase in parts of Kansas, Oklahoma, and northern Texas – a region already in possession of both large scale generating capacity and political support for wind energy.     

基于统计降尺度的黄河源区气象极值预测

针对全球气候变化对水文过程及极值事件的影响,在HadCM3的A2、B2情景下,应用统计降尺度模型(SDSM)预测了黄河源区未来气温、降雨和蒸发极值的变化趋势,并讨论了模拟效果。结果表明,模型对温度极值的捕捉效果不错,但降雨和蒸发略差,尤其是降水量、蒸发量较大的夏秋季。多数降水极值指标的变化趋势能成功模拟,而对量的捕捉能力是随指标变化的,黄河源区未来不同季节平均气温、蒸发的平均值、极值均呈增加趋势,最大持续干旱日显著减少,极端降雨强度在春秋季节大幅增加。这些变化将对高原寒区的水文及生态环境带来积极影响。     

Long-term trends of heat stress and energy use implications in subtropical climates

Past and future trends of human comfort in terms of heat and cold stresses under the local subtropical climates using measured meteorological data as well as predictions from general climate models were investigated. Summer discomfort showed an increasing trend (and winter discomfort a decreasing trend) over the past 41 years from 1968 to 2008. Monthly mean minimum and maximum temperatures and moisture content predictions from a general climate model (MIROC3.2-H) were used to determine summer and winter discomfort for future years (2009–2100) based on two emissions scenarios B1 and A1B (low and medium forcing). The 92-year (2009–2100) mean cold stress would be reduced from the 41-year (1968–2008) mean value of 8.7 to about three for both emissions scenarios. The 92-year mean heat stress would be 115.9 and 120.6 for B1 and A1B, respectively, representing 31.6% and 36.9% increase over the 1968–2008 long-term average of 88.1. These suggest that the already small winter heating requirement in subtropical Hong Kong would become even more insignificant in future years, whereas the increasing trend of summer discomfort would result in more cooling demand in the built environment.     

An investigation of the impacts of climate change on wave energy generation: The Wave Hub,Cornwall, UK

In this paper a generic methodology is presented that allows the impacts of climate change on wave energy generation from a wave energy converter (WEC) to be quantified. The methodology is illustrated by application to the Wave Hub site off the coast of Cornwall, UK. Control and future wave climates were derived using wind fields output from a set of climate change experiments. Control wave conditions were generated from wind data between 1961 and 2000. Future wave conditions were generated using two IPCC wind scenarios from 2061 to 2100, corresponding to intermediate and low greenhouse gas emissions (IPCC scenarios A1B and B1 respectively). The quantitative comparison between future scenarios and the control condition shows that the available wave power will increase by 2–3% in the A1B scenario. In contrast, the available wave power in the B1 scenario will decrease by 1–3%, suggesting, somewhat paradoxically, that efforts to reduce greenhouse gas emissions may reduce the wave energy resource. Meanwhile, the WEC energy will yield decrease by 2–3% in both A1B and B1 scenarios, which is mainly due to the relatively low efficiency of energy extraction from steeper waves by the specific WEC considered. Although those changes are relatively small compared to the natural variability, they may have significance when considered over the lifetime of a wave energy farm. Analysis of downtime under low and high thresholds suggests that the distribution of wave heights at the Wave Hub will have a wider spread due to the impacts of climate change, resulting in longer periods of generation loss. Conversely, the estimation of future changes in joint wave height-period distribution provides indications on how the response and power matrices of WECs could be modified in order to maintain or improve energy extraction in the future.     

基于RUSLE的未来降雨条件下江苏省沿江地区土壤侵蚀预估

近年来极端气候事件频发,多地区强降雨的增多加重了土壤侵蚀程度。采用世界气候研究计划组织的耦合模式比较计划第五阶段实验计划(CMIP5)中BCC_CSM1.1模式在RCP2.6、RCP4.5、RCP8.5三种气候变化情景下的未来降雨降尺度输出结果,结合GIS和修正的通用土壤流失方程(RUSLE)预估江苏省沿江地区未来土壤侵蚀程度,并分析未来不同气候变化情景下土壤侵蚀与降雨的相关性及空间分布特征。结果表明,不同气候变化情景下,江苏省沿江地区的平均土壤侵蚀模数为1.58~1.65t/(hm^2·a),土壤侵蚀总量为764.70×10^4~794.65×10^4t/a,土壤侵蚀占总土地面积的32.503%~32.504%,土壤侵蚀烈度与降雨量大小呈正相关。     

基于多模型的黄河源区径流极值情景预测

基于HadCM3提供的未来情景,采用HBV模型、新安江模型、TOP模型和径流极值的评估方法,分析和预测了气候变化下黄河源区径流量的变化情况。结果表明,三个模型均能较好地模拟黄河源区唐乃亥站的历史径流系列;在A2和B2情景下,黄河源区未来多年平均径流量呈减少趋势,径流年内分配的变化表现为夏、秋季节的径流量显著减少,而冬、春季节的径流变化趋势随水文模型的变化而变化;未来高流量事件的发生频率呈减少趋势,洪水强度可能会进一步缓和,而冬季低流量事件频繁发生的可能性增加。     

Wind climate from the regional climate model REMO

Selected outputs from simulations with the regional climate model REMO from the Max Planck Institute, Hamburg, Germany were studied in connection with wind energy resource assessment. It was found that the mean wind characteristics based on observations from six mid‐latitude stations are well described by the standard winds derived from the REMO pressure data. The mean wind parameters include the directional wind distribution, directional and omni‐directional mean values and Weibull fitting parameters, spectral analysis and interannual variability of the standard winds. It was also found that, on average, the wind characteristics from REMO are in better agreement with observations than those derived from the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) re‐analysis pressure data. The spatial correlation of REMO surface winds in Europe is consistent with that of the NCEP/NCAR surface winds, as well as published observations over Europe at synoptic scales. Therefore, REMO outputs are well suited for wind energy assessment application in Northern Europe. Copyright © 2009 John Wiley & Sons, Ltd.     

Building envelope design for climate change mitigation: a case study of hotels in Greece

This paper presents results of a study of the impact of future climate change scenarios as developed by the Intergovernmental Panel on Climate Change and implemented in weather files for specific future time slices (2020, 2050 and 2080) for the three climatic regions of Greece on the design of the external envelope of a hotel building in Greece. The impact of climate change on the hotel is assessed via hourly simulations of a calibrated model developed using the software TRNSYS. Additionally, the paper aims to identify optimal refurbishment strategies, given the constraints of the existing case-study building when transposed to the three different climatic zones in Greece. Two modes of the hotel building were studied: ‘all year’ and ‘seasonally’ operated. It was found that different external envelope energy-efficient strategies can be applied depending on the climatic zone and whether the hotel is all-year or seasonally operated.     

The potential distribution of bioenergy crops in Europe under present and future climate

We have derived maps of the potential distribution of 26 promising bioenergy crops in Europe, based on simple rules for suitable climatic conditions and elevation. Crops suitable for temperate and Mediterranean climates were selected from four groups: oilseeds (e.g. oilseed rape, sunflower), starch crops (e.g. potatoes), cereals (e.g. barley) and solid biofuel crops (e.g. sorghum, Miscanthus). The impact of climate change under different scenarios and GCMs on the potential future distribution of these crops was determined, based on predicted future climatic conditions. Climate scenarios based on four IPCC SRES emission scenarios, A1FI, A2, B1 and B2, implemented by four global climate models, HadCM3, CSIRO2, PCM and CGCM2, were used. The potential distribution of temperate oilseeds, cereals, starch crops and solid biofuels is predicted to increase in northern Europe by the 2080s, due to increasing temperatures, and decrease in southern Europe (e.g. Spain, Portugal, southern France, Italy, and Greece) due to increased drought. Mediterranean oil and solid biofuel crops, currently restricted to southern Europe, are predicted to extend further north due to higher summer temperatures. Effects become more pronounced with time and are greatest under the A1FI scenario and for models predicting the greatest climate forcing. Different climate models produce different regional patterns. All models predict that bioenergy crop production in Spain is especially vulnerable to climate change, with many temperate crops predicted to decline dramatically by the 2080s. The choice of bioenergy crops in southern Europe will be severely reduced in future unless measures are taken to adapt to climate change.     

The impact of climate change on the European energy system

Climate change can affect the economy via many different channels in many different sectors. The POLES global energy model has been modified to widen the coverage of climate change impacts on the European energy system. The impacts considered are changes in heating and cooling demand in the residential and services sector, changes in the efficiency of thermal power plants, and changes in hydro, wind (both on- and off-shore) and solar PV electricity output. Results of the impacts of six scenarios on the European energy system are presented, and the implications for European energy security and energy imports are presented.Main findings include: demand side impacts (heating and cooling in the residential and services sector) are larger than supply side impacts; power generation from fossil-fuel and nuclear sources decreases and renewable energy increases; and impacts are larger in Southern Europe than in Northern Europe.There remain many more climate change impacts on the energy sector that cannot currently be captured due to a variety of issues including: lack of climate data, difficulties translating climate data into energy-system-relevant data, lack of detail in energy system models where climate impacts act. This paper does not attempt to provide an exhaustive analysis of climate change impacts in the energy sector, it is rather another step towards an increasing coverage of possible impacts.     

Review of climate change issues: A forcing function perspective in agricultural and energy innovation

Climate change is observed globally, and the projections predict that the change will continue in the future for quite a long time. The mitigation and adaptation to climate change, however, are offering tremendous business opportunities around the world, especially for businesses operating in the agri‐food, energy, finance, and health sectors, water infrastructure, built environments, and other relevant services. When the severity of heat waves is considered, for instance, it would become quite clear that the demand for cooling would accelerate, putting further stress on energy supply and increasing the risk of electricity black outs. Similarly, the projections also provide warnings about increased drought risk in many regions around the globe, and even worse, it should also be emphasized that 60% more food will be needed globally, while 100% more demand for food is projected in developing countries by the year 2050. While all these are being projected, we are experiencing progressively increasing stress on our global freshwater resources, which are worsened further by climate change‐driven impacts and water pollution. Consequently, reducing agri‐food production systems' susceptibility to climate change and strengthening the resilience of such systems are extremely important to sustain and improve the livelihoods of billions of people around the globe. Moreover, reducing emissions due to fossil fuels consumption and production is vital for the whole global population, and agri‐food and energy sectors have tremendous potentials for reducing inefficiencies and emissions while simultaneously playing their crucial roles in food and energy security as well as poverty reduction. Both of these sectors are facing significant climate change‐driven challenges, which provide ample opportunities for cutting‐edge novel knowledge and innovative products, processes, services, and policies. And due to the reciprocal relationships between climate change and agri‐food and energy innovations, in return, complementing the other forms, such innovations will speed up the climate change mitigation and adaptation processes.     

Simulating subhourly variability of wind power output

As installed wind power capacity grows, subhourly variability in wind power output becomes increasingly important for determining the system flexibility needs, operating reserve requirements, and cost associated with wind integration. This paper presents a new methodology for simulating subhourly wind power output based on hourly average time series, which are often produced for system planning analyses, for both existing wind plants and expanded, hypothetical portfolios of wind plants. The subhourly model has an AR(p)‐ARCH(q) structure with exogenous input in the heteroskedasticity term. Model coefficients may be fit directly to high‐pass filtered historical data if it exists; for sets of wind plants containing hypothetical plants for which there are no historical data, this paper presents a method to determine model coefficients based on wind plant capacities, capacity factors, and pairwise distances. Unlike predecessors, the model presented in this paper is independent of wind speed data, captures explicitly the high variability associated with intermediate levels of power output, and captures distance‐dependent correlation between the power output of wind plants across subhourly frequencies. The model is parameterized with 1‐minute 2014 plant‐level wind power data from Electric Reliability Council of Texas (ERCOT) and validated out‐of‐sample against analogous 2015 data. The expanded‐capacity model, fit to 2014 data, produces accurate subhourly time series for the 2015 wind fleet (a 49% capacity expansion) based only on the 2015 system's wind plant capacities, capacity factors, and pairwise distances. This supports its use in simulating subhourly fleet aggregate wind power variability for future high‐wind scenarios.     

The Hydropower Potential Assessment Tool (HPAT): Evaluation of run-of-river resource potential for any global land area and application to Falls Creek,Oregon, USA

Small-scale hydropower systems are popular both in the United States and much of the developing world due to the emphasis on renewable energy and the general cost-competitiveness of hydroelectric power generation. We present a novel modeling package, referred to as the Hydropower Potential Assessment Tool (HPAT), to assess historic and projected future small-scale run-of-river hydropower resource potential at a single location or distributed over a study region. HPAT implements a fully-distributed streamflow model, which is coupled to a digital elevation model to assess hydropower resource potential. To demonstrate HPAT, we implement the models for a privately-owned run-of-river facility on Falls Creek outside of Sweet Home, Oregon, USA. We use an ensemble of Global Climate Models (GCMs) for two future climate scenarios to project a plausible range of future changes at this site. For the Falls Creek facility, HPAT projects that the timing of peak streamflow will shift from spring to winter and that mean annual hydropower potential will likely decrease slightly from average 1980–2010 historic conditions through the end of the 21st century. All inputs to HPAT are globally available, except for streamflow observations necessary for calibration.