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.     

Assessment of future climate change over East Asia due to the RCP scenarios downscaled by GRIMs-RMP

This study assesses future climate change over East Asia using the Global/Regional Integrated Model system—Regional Model Program (RMP). The RMP is forced by two types of future climate scenarios produced by the Hadley Center Global Environmental Model version 2 (HG2); the representative concentration pathways (RCP) 4.5 and 8.5 scenarios for the intergovernmental panel on climate change fifth assessment report (AR5). Analyses for the current (1980–2005) climate are performed to evaluate the RMP’s ability to reproduce precipitation and temperature. Two different future (2006–2050) simulations are compared with the current climatology to investigate the climatic change over East Asia centered in Korea. The RMP satisfactorily reproduces the observed seasonal mean and variation of precipitation and temperature. The spatial distribution of the simulated large-scale features and precipitation by the RMP is generally less reflective of current climatic conditions than that is given by the HG2, but their inter-annual variations in East Asia are better captured by the RMP. Furthermore, the RMP shows higher reproducibility of climate extremes including excessive heat wave and precipitation events over South Korea. In the future, strong warming is distinctly coupled with intensified monsoonal precipitation over East Asia. In particular, extreme weather conditions are increased and intensified over South Korea as follows: (1) The frequency of heat wave events with temperature greater than 30 °C is projected to increase by 131 and 111 % in the RCP 8.5 and 4.5 downscaling, relative to the current climate. (2) The RCP 8.5 downscaling shows the frequency and variability of heavy rainfall to increase by 24 and 31.5 %, respectively, while the statistics given by the RCP 4.5 downscaling are similar to those of the current climate.     

Hydroclimatological response to dynamically downscaled climate change simulations for Korean basins

We investigated the hydrological response to climate change simulations for three basins in South Korea. To provide fine-scale climate information to the PRMS hydrological model, an ECHO-G B2 simulation was dynamically downscaled using the RegCM3 double-nested system implementing two different convection schemes, namely, the Grell and the MIT-Emanuel (EMU) schemes. The daily minimum and maximum temperatures and precipitation from the nested domain for a grid spacing of 20 km are used as the input for the PRMS run. Two sets of multi-decadal simulations are performed over a reference period (1971–2000) and a future period (2021–2050). We focus on the differences of hydrological impacts in response to both simulations with different performances. Based on the validation of the reference simulations, the EMU simulation shows considerable improvement compared to the Grell simulation, indicating a reduction in the cold and dry biases during summer. This improvement is directly reflected in the hydrological simulation of evapotranspiration and runoff. However, using the RCM simulations without bias-correction showed the limitations of hydrologic simulation, especially snowmelt. Despite large differences in both reference simulations, the change signals of temperature and precipitation derived from the differences between the reference and future simulations show a similar pattern and sign. However, the differences in monthly change in precipitation and temperature between Grell and EMU caused the relatively large differences in runoff changes in the study areas.     

Shoreline evolution under climate change wave scenarios

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

Refinement of dynamically downscaled precipitation and temperature scenarios

A method for adjusting dynamically downscaled precipitation and temperature scenarios representing specific sites is presented. The method reproduces mean monthly values and standard deviations based on daily observations. The trend obtained in the regional climate model both for temperature and precipitation is maintained, and the frequency of modelled and observed rainy days shows better agreement. Thus, the method is appropriate for tailoring dynamically downscaled temperature and precipitation values for climate change impact studies. One precipitation and temperature scenario dynamically downscaled with HIRHAM from the Atmospheric-Ocean General Circulation Model at the Max-Planck Institute in Hamburg, ECHAM4/OPYC4 GSDIO with emission scenario IS92a, is chosen to illustrate the adjustment method.     

不同情景达到碳中和下中国区域气候变化的预估

利用第6次耦合模式比较计划(CMIP6)中的9个全球气候模式的模拟结果,通过CO₂浓度达峰时间确定SSP1-1.9和SSP1-2.6两种情景下的全球碳中和时间,预估了全球碳中和下中国区域气候较历史参考期(1995—2014年)的未来变化,分析不同时间达到碳中和下气候响应差异,并与未实现碳中和的SSP2-4.5情景下的气候变化对比。结果表明,SSP1-1.9和SSP1-2.6情景下全球达到碳中和的时间分别为2041年和2063年,相较于历史参考期,SSP1-1.9/SSP1-2.6下中国区域平均年气温上升1.22/1.58℃,平均年降水量增加7.1%/9.9%。SSP1-2.6(晚碳中和)较SSP1-1.9(早碳中和)情景下年均温增高约0.36℃,最大升温区位于西南及高原地区。对降水而言,晚碳中和较早碳中和全国平均年降水量增加约2.7%。全年及夏季降水量显著增加区主要在西北,新疆地区出现降水增加超过8%的大值区,冬季则集中于黄河中下游,增幅也超过8%。未碳中和的SSP2-4.5情景下中国区域的升温显著强于SSP1-2.6(碳中和)情景,年平均气温高约0.61℃,西北...     

Interdecadal variability of regional climate change: implications for the development of regional climate change scenarios

Summary Illustrative examples are discussed of the interdecadal variability features of the regional climate change signal in 5 AOGCM transient simulations. It is shown that the regional precipitation change signal is characterized by large variability at decadal to multidecadal scales, with the structure of the variability varying markedly across regions. Conversely, the regional temperature change signal shows low interdecadal variability. Results are compared across scenarios, models and different realizations with the same model. Our analysis indicates that, at the decadal scale, linear scaling of the regional climate change signal by the global temperature change works relatively well for temperature but less so for precipitation. The nonlinear fraction of the climate change signal tends to decrease with the magnitude of the signal. The implications of interdecadal variability for the generation of regional climate change scenarios are discussed, in particular concerning the use of multi-experiment ensembles to produce such scenarios.     

Integrated scenarios of acidification and climate change in Asia and Europe

Two integrated assessment models, one for climate change on a global scale (IMAGE 2) and another for the regional analysis of the impacts of acidifying deposition (RAINS), have been linked to assess the impacts of reducing sulphur emission on ecosystems in Asia and Europe. While such reductions have the beneficial effect of reducing the deposition of acidifying compounds and thus the exceedance of critical loads of ecosystems, they also reduce the global level of sulphate aerosols and thus enhance the impact of increased emissions of greenhouse gases, and consequently increase the risk of potential vegetation changes. The calculations indicate that about 70% of the ecosystems in Asia would be affected by either acid deposition or climate change in the year 2100 (up from 20% in 1990) for both sulphur emission scenarios (controlled and uncontrolled), whereas in Europe the impacted area would remain at a level of about 50%, with a dip early next century. More generally, the effects of reducing sulphur emissions and thus enhancing climate change would about balance for the Asian region, whereas for Europe the desirable impact of sulphur emission reductions would greatly outweigh its undesirable effects.     

Economics of climate change mitigation forest policy scenarios for Ukraine

Abstract

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

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。     

Global socio-economic and climate change mitigation scenarios through the lens of structural change

This paper analyses structural change in the economy as a key but largely unexplored aspect of global socio-economic and climate change mitigation scenarios. Structural change can actually drive energy and land use as much as economic growth and influence mitigation opportunities and barriers. Conversely, stringent climate policy is bound to induce specific structural and socio-economic transformations that are still insufficiently understood. We introduce Multi-Sectoral macroeconomic Integrated Assessment Models as tools to capture the key drivers of structural change and we conduct a multi-model study to assess main structural effects – changes of the sectoral composition and intensity of trade of global and regional economies – in a baseline and 2°C policy scenario by 2050. First, the range of baseline projections across models, for which we identify the main drivers, illustrates the uncertainty on future economic pathways – in emerging economies especially – and inform on plausible alternative futures with implications for energy use and emissions. Second, in all models, climate policy in the 2°C scenario imposes only a second-order impact on the economic structure at the macro-sectoral level – agriculture, manufacturing and services - compared to changes modelled in the baseline. However, this hides more radical changes for individual industries – within the energy sector especially. The study, which adopts a top-down framing of global structural change, represents a starting point to kick-start a conversation and propose a new research agenda seeking to improve understanding of the structural change effects in socio-economic and mitigation scenarios, and better inform policy assessments.     

A co-evolutionary approach to climate change impact assessment: Part I. Integrating socio-economic and climate change scenarios

Climate change policies currently pay disproportionately greater attention to the mitigation of climate change through emission reductions strategies than to adaptation measures. Realising that the world is already committed to some global warming, policy makers are beginning to turn their attention to the challenge of preparing society to adapt to the unfolding impacts at the local level. This two-part article presents an integrated, or `co-evolutionary', approach to using scenarios in adaptation and vulnerability assessment. Part I explains how climate and social scenarios can be integrated to better understand the inter-relationships between a changing climate and the dynamic evolution of social, economic and political systems. The integrated scenarios are then calibrated so that they can be applied `bottom up’ to local stakeholders in vulnerable sectors of the economy. Part I concludes that a co-evolutionary approach (1) produces a more sophisticated and dynamic account of the potential feedbacks between natural and human systems; (2) suggests that sustainability indicators are both a potentially valuable input to and an output of integrated scenario formulation and application. Part II describes how a broadly representative sample of public, private and voluntary organisations in the East Anglian region of the UK responded to the scenarios, and identifies future research priorities.     

Integrated assessment of biomass supply and demand in climate change mitigation scenarios

Biomass is often seen as a key component of future energy systems as it can be used for heat and electricity production, as a transport fuel, and a feedstock for chemicals. Furthermore, it can be used in combination with carbon capture and storage to provide so-called “negative emissions”. At the same time, however, its production will require land, possibly impacting food security, land-based carbon stocks, and other environmental services. Thus, the strategies adopted in the supply, conversion, and use of biomass have a significant impact on its effectiveness as a climate change mitigation measure. We use the IMAGE 3.0 integrated assessment model to project three different global, long term scenarios spanning different socioeconomic futures with varying rates of population growth, economic growth, and technological change, and investigate the role of biomass in meeting strict climate targets. Using these scenarios we highlight different possibilities for biomass supply and demand, and provide insights on the requirements and challenges for the effective use of this resource as a climate change mitigation measure. The results show that in scenarios meeting the 1.5 °C target, biomass could exceed 20% of final energy consumption, or 115–180 EJ_Prim/yr in 2050. Such a supply of bioenergy can only be achieved without extreme levels land use change if agricultural yields improve significantly and effective land zoning is implemented. Furthermore, the results highlight that strict mitigation targets are contingent on the availability of advanced technologies such as lignocellulosic fuels and carbon capture and storage.     

Non-Kyoto radiative forcing in long-run greenhouse gas emissions and climate change scenarios

Climate policies must consider radiative forcing from Kyoto greenhouse gases, as well as other forcing constituents, such as aerosols and tropospheric ozone that result from air pollutants. Non-Kyoto forcing constituents contribute negative, as well as positive forcing, and overall increases in total forcing result in increases in global average temperature. Non-Kyoto forcing modeling is a relatively new component of climate management scenarios. This paper describes and assesses current non-Kyoto radiative forcing modeling within five integrated assessment models. The study finds negative forcing from aerosols masking (offsetting) approximately 25 % of positive forcing in the near-term in reference non-climate policy projections. However, masking is projected to decline rapidly to 5–10 % by 2100 with increasing Kyoto emissions and assumed reductions in air pollution—with the later declining to as much as 50 % and 80 % below today’s levels by 2050 and 2100 respectively. Together they imply declining importance of non-Kyoto forcing over time. There are however significant uncertainties and large differences across models in projected non-Kyoto emissions and forcing. A look into the modeling reveals differences in base conditions, relationships between Kyoto and non-Kyoto emissions, pollution control assumptions, and other fundamental modeling. In addition, under climate policy scenarios, we find air pollution and resulting non-Kyoto forcing reduced to levels below those produced by air pollution policies alone—e.g., China sulfur emissions fall an additional 45–85 % by 2050. None of the models actively manage non-Kyoto forcing for climate implications. Nonetheless, non-Kyoto forcing may be influencing mitigation results, including allowable carbon dioxide emissions, and further evaluation is merited.     

Projections of uncertainties in climate change scenarios into expected winter wheat yields

Summary The crop model CERES-Wheat in combination with the stochastic weather generator were used to quantify the effect of uncertainties in selected climate change scenarios on the yields of winter wheat, which is the most important European cereal crop. Seven experimental sites with the high quality experimental data were selected in order to evaluate the crop model and to carry out the climate change impact analysis. The analysis was based on the multi-year crop model simulations run with the daily weather series prepared by the stochastic weather generator. Seven global circulation models (GCMs) were used to derive the climate change scenarios. In addition, seven GCM-based scenarios were averaged in order to derive the average scenario (AVG). The scenarios were constructed for three time periods (2025, 2050 and 2100) and two SRES emission scenarios (A2 and B1). The simulated results showed that: (1) Wheat yields tend to increase (40 out of 42 applied scenarios) in most locations in the range of 7.5–25.3% in all three time periods. In case of the CCSR scenario that predicts the most severe increase of air temperature, the yields would be reduced by 9.6% in 2050 and by 25.8% in 2100 if the A2 emission scenario would become reality. Differences between individual scenarios are large and statistically significant. Particularly for the time periods 2050 and 2100 there are doubts about the trend of the yield shifts. (2) The site effect was caused by the site-specific soil and climatic conditions. Importance of the site influence increases with increasing severity of imposed climatic changes and culminates for the emission scenario A2 and the time period 2100. The sustained tendency benefiting two warmest sites has been found as well as more positive response to the changed climatic conditions of the sites with deeper soil profiles. (3) Temperature variability proved to be an important factor and influenced both mean and standard deviation of the yields. Change of temperature variability by more than 25% leads to statistically significant changes in yield distribution. The effect of temperature variability decreases with increased values of mean temperature. (4) The study proved that the application of the AVG scenarios – despite possible objections of physical inconsistency – might be justifiable and convenient in some cases. It might bring results comparable to those derived from averaging outputs based on number of scenarios and provide more robust estimate than the application of only one selected GCM scenario.