Dynamic adaptive pathways in downscaled climate change scenarios

The parallel scenario process enables characterization of climate-related risks and response options to climate change under different socio-economic futures and development prospects. The process is based on representative concentration pathways, shared socio-economic pathways, and shared policy assumptions. Although this scenario architecture is a powerful tool for evaluating the intersection of climate and society at the regional and global level, more specific context is needed to explore and understand risks, drivers, and enablers of change at the national and local level. We discuss the need for a stronger recognition of such national-scale characteristics to make climate change scenarios more relevant at the national and local scale, and propose ways to enrich the scenario architecture with locally relevant details that enhance salience, legitimacy, and credibility for stakeholders. Dynamic adaptive pathways are introduced as useful tools to draw out which elements of a potentially infinite scenario space connect with decision-relevant aspects of particular climate-related and non-climate-related risks and response options. Reviewing adaptation pathways for New Zealand case studies, we demonstrate how this approach could bring the global-scale scenario architecture within reach of local-scale decision-making. Such a process would enhance the utility of scenarios for mapping climate-related risks and adaptation options at the local scale, involving appropriate stakeholder involvement.     

Future makers or future takers? A scenario analysis of climate change and the Great Barrier Reef

The extent to which nations and regions can actively shape the future or must passively respond to global forces is a topic of relevance to current discourses on climate change. In Australia, climate change has been identified as the greatest threat to the ecological resilience of the Great Barrier Reef, but is exacerbated by regional and local pressures. We undertook a scenario analysis to explore how two key uncertainties may influence these threats and their impact on the Great Barrier Reef and adjacent catchments in 2100: whether (1) global development and (2) Australian development is defined and pursued primarily in terms of economic growth or broader concepts of human well-being and environmental sustainability, and in turn, how climate change is managed and mitigated. We compared the implications of four scenarios for marine and terrestrial ecosystem services and human well-being. The results suggest that while regional actions can partially offset global inaction on climate change until about mid-century, there are probable threshold levels for marine ecosystems, beyond which the Great Barrier Reef will become a fundamentally different system by 2100 if climate change is not curtailed. Management that can respond to pressures at both global and regional scales will be needed to maintain the full range of ecosystem services. Modest improvements in human well-being appear possible even while ecosystem services decline, but only where regional management is strong. The future of the region depends largely on whether national and regional decision-makers choose to be active future ‘makers’ or passive future ‘takers’ in responding to global drivers of change. We conclude by discussing potential avenues for using these scenarios further with the Great Barrier Reef region's stakeholders.     

Towards extended shared socioeconomic pathways: A combined participatory bottom-up and top-down methodology with results from the Barents region

A major challenge in planning for adaptation to climate change is to assess future development not only in relation to climate but also in relation to social, economic and political changes that affect the capacity for adaptation or otherwise play a role in decision making. One approach is to use scenario methods. This article presents a methodology that combines top-down scenarios and bottom-up approaches to scenario building, with the aim of articulating local so-called extended socio-economic pathways. Specifically, we used the Shared Socioeconomic Pathways (SSPs) of the global scenario framework as developed by the climate research community to present boundary conditions about potential global change in workshop discussion with local and regional actors in the Barents region. We relate the results from these workshops to the different elements of the global SSPs and discuss potential and limitations of the method in relation to use in decision making processes.     

Food security or economic profitability? Projecting the effects of climate and socioeconomic changes on global skipjack tuna fisheries under three management strategies

We investigate the interactions between anthropogenic climate change, socioeconomic developments and tuna fishery management strategies. For this purpose, we use the APECOSM-E model to map the effects of climate change and commercial fishing on the distribution of skipjack tuna biomass in the three oceans, combined with a new bioeconomic module representing the rent or profit of skipjack fisheries. For forcing, we use Representative Concentration Pathway (RCP) 8.5, the highest emission scenario for greenhouse gas concentrations presented in the IPCC’s Fifth Assessment Report (AR5), and the IPCC Socioeconomic Shared Pathway (SSP) 3, which is characterized by low economic development and a strong increase in the world population. We first investigate the impact of climate change on regional skipjack abundance, catches and profits in three oceans (Atlantic, Indian and Pacific) in 2010, 2050 and 2095. We then study the effects of three management strategies (maximum sustainable yield or MSY, maximum economic yield or MEY, and zero rent or ZR) on the future distribution of fishing fleets between oceans and on global economic rent.Our model projections for 2050 and 2095 show an increase in global skipjack biomass compared to 2010 and major changes in its distribution, impacting local and regional fishing efforts. The Pacific Ocean will continue to dominate the skipjack market.In our modeling of management strategies, the currently predominant MSY strategy would have been unprofitable in 2010, due to a decreased catch per unit effort (CPUE). In the future, however, technological developments should increase fishing efficiency and make MSY profitable.In all the scenarios, a MEY strategy is more profitable than MSY but leads to the lowest catches and the highest prices. This raises ethical questions in a world where food security may become a top priority.In the scenarios where MSY generates an economic loss (e.g. 2010), a ZR strategy allows global stocks to be exploited at high but still profitable levels. Conversely, in the scenarios where MSY is profitable, (e.g. 2095) ZR leads to overfishing and smaller global catches.We conclude that the most appropriate management strategy at any time is likely to change as environmental and socioeconomic conditions evolve. The decision to follow one or other strategy is a complex one that must be regularly reviewed and updated.     

Linking regional stakeholder scenarios and shared socioeconomic pathways: Quantified West African food and climate futures in a global context

The climate change research community’s shared socioeconomic pathways (SSPs) are a set of alternative global development scenarios focused on mitigation of and adaptation to climate change. To use these scenarios as a global context that is relevant for policy guidance at regional and national levels, they have to be connected to an exploration of drivers and challenges informed by regional expertise.In this paper, we present scenarios for West Africa developed by regional stakeholders and quantified using two global economic models, GLOBIOM and IMPACT, in interaction with stakeholder-generated narratives and scenario trends and SSP assumptions. We present this process as an example of linking comparable scenarios across levels to increase coherence with global contexts, while presenting insights about the future of agriculture and food security under a range of future drivers including climate change.In these scenarios, strong economic development increases food security and agricultural development. The latter increases crop and livestock productivity leading to an expansion of agricultural area within the region while reducing the land expansion burden elsewhere. In the context of a global economy, West Africa remains a large consumer and producer of a selection of commodities. However, the growth in population coupled with rising incomes leads to increases in the region’s imports. For West Africa, climate change is projected to have negative effects on both crop yields and grassland productivity, and a lack of investment may exacerbate these effects. Linking multi-stakeholder regional scenarios to the global SSPs ensures scenarios that are regionally appropriate and useful for policy development as evidenced in the case study, while allowing for a critical link to global contexts.     

Co-use of existing scenario sets to extend and quantify the shared socioeconomic pathways

More often than not, assessments of future climate risks are based on future climatic conditions superimposed on current socioeconomic conditions only. The new IPCC-guided alternative global development trends, the shared socioeconomic pathways (SSPs), have the potential to enhance the integration of future socioeconomic conditions—in the form of socioeconomic scenarios—within assessments of future climate risks. Being global development pathways, the SSPs lack regional and sectoral details. To increase their suitability in sectoral and/or regional studies and their relevance for local stakeholders, the SSPs have to be extended. We propose here a new method to extend the SSPs that makes use of existing scenario studies, the (re)use of which has been underestimated so far. Our approach lies in a systematic matching of multiple scenario sets that facilitates enrichment of the global SSPs with regional and sectoral information, in terms of both storylines and quantitative projections. We apply this method to develop extended SSPs of human vulnerability in Europe and to quantify them for a number of key indicators at the sub-national level up to 2050, based on the co-use of the matched scenarios’ quantitative outputs. Results show that such a method leads to internally consistent extended SSPs with detailed and highly quantified narratives that are tightly linked to global contexts. This method also provides multiple entry points where the relevance of scenarios to local stakeholders can be tested and strengthened. The extended SSPs can be readily employed to explore future populations’ vulnerability to climate hazards under varying levels of socioeconomic development.     

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.     

Empirical testing of the visualizations of climate change mitigation scenarios with citizens: A comparison among Germany,Poland, and France

While scenarios are used extensively for communication about climate change mitigation, little is known about the interpretation of these scenarios by citizens. We conducted a cross-country empirical evaluation of scenario visualizations for global mitigation, using online surveys in Germany (N = 379), Poland (N = 223), and France (N = 225). Each respondent received visualizations of the required changes in global carbon dioxide emissions and composition of electricity supply (fossil fuels, nuclear, and renewable sources) for limiting global warming to 1.5 °C. We evaluated the effects of respondents’ demographics, prior beliefs, numeracy, and graph literacy on the reading accuracy and knowledge gains from the visualizations. We also included an experimental between-groups design on visualization format, where four groups received different graph formats (steep or gradual graphs with depictions of uncertainty ranges or scenario ensembles) and the fifth group received a table. Results showed that higher education level, numeracy, and graph literacy increased reading accuracy in all countries, while age reduced them. Respondents with prior beliefs about climate change mitigation that matched the information in the visualizations had also higher reading accuracy and knowledge gains. While the effects of different visualization formats were comparatively minor, customizing formats according to demographic and country differences was used to reduce adverse effects from these differences. These results emphasize the need to design visualizations that match characteristics of the intended audience and could inform better communication of climate change mitigation scenarios to non-expert audience.     

Creating regional climate change scenarios over southern South America for the 2020’s and 2050’s using the pattern scaling technique: validity and limitations

Dynamical downscaling of global climate simulations is the most adequate tool to generate regional projections of climate change. This technique involves at least a present climate simulation and a simulation of a future scenario, usually at the end of the twenty first century. However, regional projections for a variety of scenarios and periods, the 2020s or the 2050s, are often required by the impact community. The pattern scaling technique is used to estimate information on climate change for periods and scenarios not simulated by the regional model. We based our study on regional simulations performed over southern South America for present climate conditions and two emission scenarios at the end of the twenty first century. We used the pattern scaling technique to estimate mean seasonal changes of temperature and precipitation for the 2020s and the 2050s. The validity of the scalability assumptions underlying the pattern scaling technique for estimating near future regional climate change scenarios over southern South America is assessed. The results show that the pattern scaling works well for estimating mean temperature changes for which the regional changes are linearly related to the global mean temperature changes. For precipitation changes, the validity of the scalability assumption is weaker. The errors of estimating precipitation changes are comparable to those inherent to the regional model and to the projected changes themselves.     

Integrating top–down and bottom–up approaches to design global change adaptation at the river basin scale

The high uncertainty associated with the effect of global change on water resource systems calls for a better combination of conventional top–down and bottom–up approaches, in order to design robust adaptation plans at the local scale. The methodological framework presented in this article introduces “bottom–up meets top–down” integrated approach to support the selection of adaptation measures at the river basin level by comprehensively integrating the goals of economic efficiency, social acceptability, environmental sustainability and adaptation robustness. The top–down approach relies on the use of a chain of models to assess the impact of global change on water resources and its adaptive management over a range of climate projections. Future demand scenarios and locally prioritised adaptation measures are identified following a bottom–up approach through a participatory process with the relevant stakeholders and experts. The optimal combinations of adaptation measures are then selected using a hydro-economic model at basin scale for each climate projection. The resulting adaptation portfolios are, finally, climate checked to define a robust least-regret programme of measures based on trade-offs between adaptation costs and the reliability of supply for agricultural demands.This innovative approach has been applied to a Mediterranean basin, the Orb river basin (France). Mid-term climate projections, downscaled from 9 General Climate Models, are used to assess the uncertainty associated with climate projections. Demand evolution scenarios are developed to project agricultural and urban water demands on the 2030 time horizon. The results derived from the integration of the bottom–up and top–down approaches illustrate the sensitivity of the adaptation strategies to the climate projections, and provide an assessment of the trade-offs between the performance of the water resource system and the cost of the adaptation plan to inform local decision-making. The article contributes new methodological elements for the development of an integrated framework for decision-making under climate change uncertainty, advocating an interdisciplinary approach that bridges the gap between bottom–up and top–down approaches.     

Assessing the strength of regional changes in near-surface climate associated with a global warming of 2°C

In this study, the strength of the regional changes in near-surface climate associated with a global warming of 2°C with respect to pre-industrial times is assessed, distinguishing between 26 different regions. Also, the strength of these regional climate changes is compared to the strength of the respective changes associated with a markedly stronger global warming of 4.5°C. The magnitude of the regional changes in climate is estimated by means of a normalized regional climate change index, which considers changes in the mean as well as changes in the interannual variability of both near-surface temperature and precipitation. The study is based on two sets of four ensemble simulations with the ECHAM5/MPI-OM coupled climate model, each starting from different initial conditions. In one set of simulations (1860–2200), the greenhouse gas concentrations and sulphate aerosol load have been prescribed according to observations until 2000 and according to the SRES A1B scenario after 2000. In the other set of simulations (2020–2200), the greenhouse gas concentrations and sulphate aerosol load have been prescribed in such a way that the simulated global warming does not exceed 2°C with respect to pre-industrial times. The study reveals the strongest changes in near-surface climate in the same regions for both scenarios, i.e., the Sahara, Northern Australia, Southern Australia and Amazonia. The regions with the weakest changes in near-surface climate, on the other hand, vary somewhat between the two scenarios except for Western North America and Southern South America, where both scenarios show rather weak changes. The comparison between the magnitude of the regional changes in near-surface climate for the two scenarios reveals relatively strong changes in the 2°C-stabilization scenario at high northern latitudes, i.e., Northeastern Europe, Alaska and Greenland, and in Amazonia. Relatively weak regional climate changes in this scenario, on the other hand, are found for Eastern Asia, Central America, Central South America and Southern South America. The ratios between the regional changes in the near-surface climate for the two scenarios vary considerably between different regions. This illustrates a limitation of obtaining regional changes in near-surface climate associated with a particular scenario by means of scaling the regional changes obtained from a widely used “standard” scenario with the ratio of the changes in the global mean temperature projected by these two scenarios.     

Using Statistical Downscaling to Quantify the GCM-Related Uncertainty in Regional Climate Change Scenarios： A Case Study of Swedish Precipitation

There are a number of sources of uncertainty in regional climate change scenarios. When statistical downscaling is used to obtain regional climate change scenarios, the uncertainty may originate from the uncertainties in the global climate models used, the skill of the statistical model, and the forcing scenarios applied to the global climate model. The uncertainty associated with global climate models can be evaluated by examining the differences in the predictors and in the downscaled climate change scenarios based on a set of different global climate models. When standardized global climate model simulations such as the second phase of the Coupled Model Intercomparison Project （CMIP2） are used, the difference in the downscaled variables mainly reflects differences in the climate models and the natural variability in the simulated climates. It is proposed that the spread of the estimates can be taken as a measure of the uncertainty associated with global climate models. The proposed method is applied to the estimation of global-climate-model-related uncertainty in regional precipitation change scenarios in Sweden. Results from statistical downscaling based on 17 global climate models show that there is an overall increase in annual precipitation all over Sweden although a considerable spread of the changes in the precipitation exists. The general increase can be attributed to the increased large-scale precipitation and the enhanced westerly wind. The estimated uncertainty is nearly independent of region. However, there is a seasonal dependence. The estimates for winter show the highest level of confidence, while the estimates for summer show the least.     

A Regional, Multi-sectoral And Integrated Assessment Of The Impacts Of Climate And Socio-economic Change In The Uk

Policy makers and stakeholders are increasingly demanding impact assessments which produce policy-relevant guidance on the local impacts of global climate change. The ‘Regional Climate Change Impact and Response Studies in East Anglia and North West England’ (RegIS) study developed a methodology for stakeholder-led, regional climate change impact assessment that explicitly evaluated local and regional (sub-national) scale impacts and adaptation options, and cross-sectoral interactions between four major sectors driving landscape change (agriculture, biodiversity, coasts and floodplains and water resources). The ‘Drivers-Pressure-State-Impact-Response’ (DPSIR) approach provided a structure for linking the modelling and scenario techniques. A 5 × 5 km grid was chosen for numerical modelling input (climate and socio-economic scenarios) and output, as a compromise between the climate scenario resolution (10 × 10 km) and the detailed spatial resolution output desired by stakeholders. Fundamental methodological issues have been raised by RegIS which reflect the difficulty of multi-sectoral modelling studies at local scales. In particular, the role of scenarios, error propagation in linked models, model validity, transparency and transportability as well as the use of integrated assessment to evaluate adaptation options to climate change are examined. Integrated assessments will provide new insights which will compliment those derived by more detailed sectoral assessments.     

Greenhouse gas emissions from global cities under SSP/RCP scenarios, 1990 to 2100

Projections of greenhouse gas (GHG) emissions are critical to enable a better understanding and anticipation of future climate change under different socio-economic conditions and mitigation strategies. The climate projections and scenarios assessed by the Intergovernmental Panel on Climate Change, following the Shared Socioeconomic Pathway (SSP)-Representative Concentration Pathway (RCP) framework, have provided a rich understanding of the constraints and opportunities for policy action. However, the current emissions scenarios lack an explicit treatment of urban emissions within the global context. Given the pace and scale of urbanization, with global urban populations expected to increase from about 4.4 billion today to about 7 billion by 2050, there is an urgent need to fill this knowledge gap. Here, we estimate the share of global GHG emissions driven by urban areas from 1990 to 2100 based on the SSP-RCP framework. The urban consumption-based GHG emissions are presented in five regional aggregates and based on a combination of the urban population share, 2015 urban per capita CO₂eq carbon footprint, SSP-based national CO₂eq emissions, and recent analysis of urban per capita CO₂eq trends. We find that urban areas account for the majority of global GHG emissions in 2015 (61.8%). Moreover, the urban share of global GHG emissions progressively increases into the future, exceeding 80% in some scenarios by the end of the century. The combined urban areas in Asia and Developing Pacific, and Developed Countries account for 65.0% to 73.3% of cumulative urban consumption-based emissions between 2020 and 2100 across the scenarios. Given these dominant roles, we describe the implications for potential urban mitigation in each of the scenario narratives in order to meet the goal of climate neutrality within this century.     

Impacts of Climate Change on the Global Forest Sector

The path and magnitude of future anthropogenic emissions of carbon dioxide will likely influence changes in climate that may impact the global forest sector. These responses in the global forest sector may have implications for international efforts to stabilize the atmospheric concentration of carbon dioxide. This study takes a step toward including the role of global forest sector in integrated assessments of the global carbon cycle by linking global models of climate dynamics, ecosystem processes and forest economics to assess the potential responses of the global forest sector to different levels of greenhouse gas emissions. We utilize three climate scenarios and two economic scenarios to represent a range of greenhouse gas emissions and economic behavior. At the end of the analysis period (2040), the potential responses in regional forest growing stock simulated by the global ecosystem model range from decreases and increases for the low emissions climate scenario to increases in all regions for the high emissions climate scenario. The changes in vegetation are used to adjust timber supply in the softwood and hardwood sectors of the economic model. In general, the global changes in welfare are positive, but small across all scenarios. At the regional level, the changes in welfare can be large and either negative or positive. Markets and trade in forest products play important roles in whether a region realizes any gains associated with climate change. In general, regions with the lowest wood fiber production cost are able to expand harvests. Trade in forest products leads to lower prices elsewhere. The low-cost regions expand market shares and force higher-cost regions to decrease their harvests. Trade produces different economic gains and losses across the globe even though, globally, economic welfare increases. The results of this study indicate that assumptions within alternative climate scenarios and about trade in forest products are important factors that strongly influence the effects of climate change on the global forest sector.     

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.     

Drivers of mean climate change around the Netherlands derived from CMIP5

For the construction of regional climate change scenarios spanning a relevant fraction of the spread in climate model projections, an inventory of major drivers of regional climate change is needed. For the Netherlands, a previous set of regional climate change scenarios was based on the decomposition of local temperature/precipitation changes into components directly linked to the level of global warming, and components related to changes in the regional atmospheric circulation. In this study this decomposition is revisited utilizing the extensive modelling results from the CMIP5 model ensemble in support for the 5th IPCC assessment. Rather than selecting a number of GCMs based on performance metrics or relevant response features, a regression technique was developed to utilize all available model projections. The large number of projections allows a quantification of the separate contributions of emission scenarios, systematic model responses and natural variability to the total likelihood range. Natural variability plays a minor role in modelled differences in the global mean temperature response, but contributes for up to 50 % to the range of mean sea level pressure responses and local precipitation. Using key indicators (“steering variables”) for the temperature and circulation response, the range in local seasonal mean temperature and precipitation responses can be fairly well reproduced.     

The Shared Socioeconomic Pathways and their energy,land use,and greenhouse gas emissions implications: An overview

This paper presents the overview of the Shared Socioeconomic Pathways (SSPs) and their energy, land use, and emissions implications. The SSPs are part of a new scenario framework, established by the climate change research community in order to facilitate the integrated analysis of future climate impacts, vulnerabilities, adaptation, and mitigation. The pathways were developed over the last years as a joint community effort and describe plausible major global developments that together would lead in the future to different challenges for mitigation and adaptation to climate change. The SSPs are based on five narratives describing alternative socio-economic developments, including sustainable development, regional rivalry, inequality, fossil-fueled development, and middle-of-the-road development. The long-term demographic and economic projections of the SSPs depict a wide uncertainty range consistent with the scenario literature. A multi-model approach was used for the elaboration of the energy, land-use and the emissions trajectories of SSP-based scenarios. The baseline scenarios lead to global energy consumption of 400–1200 EJ in 2100, and feature vastly different land-use dynamics, ranging from a possible reduction in cropland area up to a massive expansion by more than 700 million hectares by 2100. The associated annual CO₂ emissions of the baseline scenarios range from about 25 GtCO₂ to more than 120 GtCO₂ per year by 2100. With respect to mitigation, we find that associated costs strongly depend on three factors: (1) the policy assumptions, (2) the socio-economic narrative, and (3) the stringency of the target. The carbon price for reaching the target of 2.6 W/m² that is consistent with a temperature change limit of 2 °C, differs in our analysis thus by about a factor of three across the SSP marker scenarios. Moreover, many models could not reach this target from the SSPs with high mitigation challenges. While the SSPs were designed to represent different mitigation and adaptation challenges, the resulting narratives and quantifications span a wide range of different futures broadly representative of the current literature. This allows their subsequent use and development in new assessments and research projects. Critical next steps for the community scenario process will, among others, involve regional and sectoral extensions, further elaboration of the adaptation and impacts dimension, as well as employing the SSP scenarios with the new generation of earth system models as part of the 6th climate model intercomparison project (CMIP6).     

Temperature scenarios for Norway: from regional to local scale

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

A study on combining global and regional climate model results for generating climate scenarios of temperature and precipitation for the Netherlands

Climate scenarios for the Netherlands are constructed by combining information from global and regional climate models employing a simplified, conceptual framework of three sources (levels) of uncertainty impacting on predictions of the local climate. In this framework, the first level of uncertainty is determined by the global radiation balance, resulting in a range of the projected changes in the global mean temperature. On the regional (1,000–5,000 km) scale, the response of the atmospheric circulation determines the second important level of uncertainty. The third level of uncertainty, acting mainly on a local scale of 10 (and less) to 1,000 km, is related to the small-scale processes, like for example those acting in atmospheric convection, clouds and atmospheric meso-scale circulations—processes that play an important role in extreme events which are highly relevant for society. Global climate models (GCMs) are the main tools to quantify the first two levels of uncertainty, while high resolution regional climate models (RCMs) are more suitable to quantify the third level. Along these lines, results of an ensemble of RCMs, driven by only two GCM boundaries and therefore spanning only a rather narrow range in future climate predictions, are rescaled to obtain a broader uncertainty range. The rescaling is done by first disentangling the climate change response in the RCM simulations into a part related to the circulation, and a residual part which is related to the global temperature rise. Second, these responses are rescaled using the range of the predictions of global temperature change and circulation change from five GCMs. These GCMs have been selected on their ability to simulate the present-day circulation, in particular over Europe. For the seasonal means, the rescaled RCM results obey the range in the GCM ensemble using a high and low emission scenario. Thus, the rescaled RCM results are consistent with the GCM results for the means, while adding information on the small scales and the extremes. The method can be interpreted as a combined statistical–dynamical downscaling approach, with the statistical relations based on regional model output.