Impacts

Participatory Integrated Assessement (IA) methods complement analytical methods like IA-modeling in their explicit inclusion of stakeholders and decision-makers in the assessment. Integrated Assessment is perceived as a process of social learning involving scientists, stakeholders, policymakers and the society at large. We introduce a new approach to provide expert knowledge for participatory integrated assessments of regional climate change: `Interactive Citizen's Information Tools' (ICITs). ICITs provide citizens with expert knowledge about causes of climate change, potential impacts, and policy options to address anthropogenic climate change. In this paper we discuss the development and application of IMPACTS in IA-focus groups in Switzerland. IMPACTS is based on user-friendly hypermedia technologies and allows citizens to get informed on a broad range of potential climate change impacts – with an emphasison prevailing uncertainties. IA-focus groups are deliberative group discussions that make use of computer tools to support the discussion and assessment. The goal of IA-focus groups is to elicit how informed citizens judge the risks of anthropogenic climate change. Experiences with IMPACTS showed that the combination of focus groups with ICITs is a feasible and promising approach for a participatory IA of regional climate change, in particular, and of complex environmental issues, in general.     

The atmospheric boundary layer — advances in knowledge and application

We summarise major activities and advances in boundary-layer knowledge in the 25 years since 1970, with emphasis on the application of this knowledge to surface and boundary-layer parametrisation schemes in numerical models of the atmosphere. Progress in three areas is discussed: (i) the mesoscale modelling of selected phenomena; (ii) numerical weather prediction; and (iii) climate simulations. Future trends are identified, including the incorporation into models of advanced cloud schemes and interactive canopy schemes, and the nesting of high resolution boundary-layer schemes in global climate models.     

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.     

Turning climate change information into economic and health impacts

The PRUDENCE project has generated a set of spatially and temporally high-resolution climate data, which provides new opportunities for assessing the impacts of climate variability and change on economic and human systems in Europe. In this context, we initiated the development of new approaches for linking climate change information and economic studies. We have considered a number of case studies that illustrate how linkages can be established between geographically detailed climate data and economic information. The case studies included wheat production in agriculture, where regional climate data has been linked to farm enterprise data in an integrated model of physical conditions, production inputs and outputs, and farm management practices. Similarly, temperature data were used to assess consequences of extreme heat and excess mortality in urban areas. We give an introduction of an analytical approach for assessing economic impacts of climate change and discuss how economic concepts and valuation paradigms can be applied to climate change impact evaluation. A number of methodological difficulties encountered in economic assessments of climate change impacts are described and a number of issues related to social and private aspects of costs are highlighted. It is argued that, in particular, detailed climate information matters in relation to understanding how private agents react to observed climate data.     

Agricultural Impact Assessment, Vulnerability, and the Scope for Adaptation

Climate change assessments which have considered climate impacts of a 2xCO₂ climate, using models of the global agricultural system, have found small impacts on overall production, but larger regional changes. Production shifts among regions can be considered one mechanism for adaptation. Adaptation at the farm level, through changes in crops, cultivars, and production practices, is another adaptation mechanism. Existing studies differ in how important these mechanisms will be. Studies that have considered yield effects at specific sites have found very wide ranges of impacts. A useful way to evaluate the impacts of climate change, given the uncertainty about future impacts, is to consider vulnerability. Studies have defined vulnerability in terms of yield, farm profitability, regional economy, and hunger. Vulnerability and climate impacts, particularly in terms of higher order effects on profitability and sustainability, will depend on how society and the economy develop. Lower income populations and marginal agricultural regions, particularly arid or flood prone areas, are most vulnerable to climate change.     

The Effects of Spatial Scale of Climate Scenarios on Economic Assessments: An Example from U.S. Agriculture

The appropriate level of spatial resolution for climate scenarios is a key uncertainty in climate impact studies and regional integrated assessments. To the extent that such uncertainty may affect the magnitude of economic estimates of climate change, it has implications for the public policy debates concerning the efficiency of CO₂ control options. In this article, we investigate the effects that different climate scenario resolutions have on economic estimates of the impacts of future climate changeon agriculture in the United States. These results are derived via a set of procedures and an analytical model that has been used previously in climate change assessments. The results demonstrate that the spatial scale of climate scenarios affects the estimates of both regional changes in crop yields and the economic impact on the agricultural sector as a whole. An assessment based on the finer scale climatological information consistently yielded a less favorable assessment of the implications of climate change. Regional indicators of economic activity were of opposite sign in some regions, based on the scenario scale. Such differences in economic magnitudes or signs are potentially important in examining whether past climate change assessments may misstate the economic consequences of such changes. The results reported here suggest that refinement of the spatial scale of scenarios should be carefully considered in future impacts research.     

Incorporating Catastrophes into Integrated Assessment: Science, Impacts, and Adaptation

Incorporating potential catastrophic consequences into integrated assessment models of climate change has been a top priority of policymakers and modelers alike. We review the current state of scientific understanding regarding three frequently mentioned geophysical catastrophes, with a view toward their implications for integrated assessment modeling. This review finds inadequacies in widespread model assumptions regarding the nature of catastrophes themselves and climate change impacts more generally. The possibility of greatly postponed consequences from near- and medium-term actions suggests that standard discounting practices are inappropriate for the analysis of climate catastrophe. Careful consideration of paleoclimate and geophysical modeling evidence regarding the possibility of changes in ocean circulation suggests a reframing of the source of climate change damages in economic models, placing changes in climate predictability, rather than gradual changes in mean values, at the focus of economic damage assessments. The implications of decreases in predictability for the modeling of adaptation are further discussed.     

Impact of Climate Change on Indian Agriculture: A Review

During the recent decade, with the growing recognition of the possibility of climate change and clear evidence of observed changes in climate during 20^th century, an increasing emphasis on food security and its regional impacts has come to forefront of the scientific community. In recent times, the crop simulation models have been used extensively to study the impact of climate change on agricultural production and food security. The output provided by the simulation models can be used to make appropriate crop management decisions and to provide farmers and others with alternative options for their farming system. It is expected that in the coming decades with the increased use of computers, the use of simulation models by farmers and professionals as well as policy and decision makers will increase. In India, substantial work has been done in last decade aimed at understanding the nature and magnitude of change in yield of different crops due to projected climate change. This paper presents an overview of the state of the knowledge of possible effect of the climate variability and change on food grain production in India. An erratum to this article can be found at     

Understanding and enhancing climate information use in water management

This paper expands our understanding of water manager's climate information (CI) use and of the effectiveness of interactive research efforts in improving use by quantitatively measuring usability both within and outside the interactive research model. Using a mixed method approach (i.e., interviews and surveys), data was collected across five states and hundreds of water managers to understand the production of CI by scientists at two Regional Integrated Sciences and Assessments (RISAs) employing an interactive approach and the use of that information by water managers in the corresponding RISA regions. This study finds that RISAs are effective in three important ways: first, in co-producing usable information and achieving a high rate of information use among RISA clients; second, in overcoming barriers to information use arising from negative perceptions about the usability and reliability of CI; and, finally, in fostering innovation. RISA information use is contingent on sustained scientist-client interaction and is enabled by users' willingness and capacity making RISAs most effective in reaching the largest, most capable users. These users and those who use CI from other sources do so as a strategy to manage risk. This research suggests areas for enhancing RISA CI uptake: structuring RISAs as consortia, cultivating relationships with knowledge brokers and capitalizing on existing knowledge networks, and increasing public education and outreach. Beyond the interactive research models, findings suggest CI uptake may be enhanced by building capabilities for long-term water planning at water systems and bolstering public science citizenship and climate literacy.     

Do weak AR4 models bias projections of future climate changes over Australia?

Regional climate projections using climate models commonly use an “all-model” ensemble based on data sets such as the Intergovernmental Panel on Climate Change’s (IPCC) 4th Assessment (AR4). Some regional assessments have omitted models based on specific criteria. We use a criteria based on the capacity of climate models to simulate the observed probability density function calculated using daily data, model-by-model and region-by-region for each of the AR4 models over Australia. We demonstrate that by omitting those climate models with relatively weak skill in simulating the observed probability density functions of maximum and minimum temperature and precipitation, different regional projections are obtained. Differences include: larger increases in the mean maximum and mean minimum temperatures, but smaller increases in the annual maximum and minimum temperatures. There is little impact on mean precipitation but the better models simulate a larger increase in the annual rainfall event combined with a larger decrease in the number of rain days. The weaker models bias the amount of mean warming towards lower increases, bias annual maximum temperatures to excessive warming and bias precipitation such that the amount of the annual rainfall event is under-estimated. We suggest that omitting weak models from regional scale estimates of future climate change helps clarify the nature and scale of the projected impacts of global warming.     

The impact of agricultural trade approaches on global economic modeling

Researchers explore future economic and climate scenarios using global economic and integrated assessment models to understand long-term interactions between human development and global environmental changes. However, differences in trade modeling approaches are an important source of uncertainty in these types of assessments, particularly for regional projections. In this study, we modified the Global Change Analysis Model (GCAM) to include a novel logit-based Armington trade structure, to examine two approaches to modeling trade: (1) an approach that represents segmented regional markets (SRM), and (2) an approach that represents integrated world markets (IWM). Our results demonstrate that assuming IWM, i.e., homogeneous product modeling and neglecting economic geography, could lead to lower cropland use (i.e., by 115 million hectares globally) and terrestrial carbon fluxes (i.e., by 25%) by the end of the century under the default GCAM scenario, compared with the logit-based Armington SRM structure. The results are highly heterogeneous across regions, with more pronounced regional trade responses driven by global market integration. Our study highlights the critical role that assumptions about future trade paradigms play in global economic and integrated assessment modeling. The results imply that closer harmonization of trade modeling approaches and trade parameter values could increase the convergence of regional results among models in model intercomparison studies.     

Is interactive air sea coupling relevant for simulating the future climate of Europe?

Climate Dynamics - The majority of regional climate change assessments for the Euro-CORDEX region is based on high resolution atmosphere models. These models use prescribed lower boundary...     

Danger is all around: Eliciting expert perceptions for managing climate change through a mental models approach

It has long been acknowledged that understandings of risk are influenced by external or ‘objective’ assessments, and by internal or ‘subjective’ value judgements. In-depth research has been undertaken on how lay people perceive climate change and related risks, whereas work on expert opinions is more limited. This paper reports on 22 ‘expert’ interpretations elicited through a mental models approach, and encapsulated in a ‘meta’-influence diagram, denoting three conceptualisations of danger in relation to climate change: (i) human influence upon the climate system; (ii) impacts upon natural and human communities; and (iii) threat to the status quo, especially in the form of mitigation measures and related costs. These conceptualisations raise questions about how experts bring to bear their knowledge, values and understanding of climatic and social systems in articulating such discourses. This paper also discusses the implications of such diverse perspectives on managing climate change.     

Sources of knowledge and ignorance in climate research

Ignorance is an inevitable component of climate change research, and yet it has not been specifically catered for in standard uncertainty guidance documents for climate assessments. Reports of ignorance in understanding require context to explain how such ignorance does and does not affect understanding more generally. The focus of this article is on dynamical sources of ignorance in regional climate change projections. A key source of ignorance in the projections is the resolution-limited treatment of dynamical instabilities in the ocean component of coupled climate models. A consequence of this limitation is that it is very difficult to quantify uncertainty in regional projections of climate variables that depend critically upon the details of the atmospheric flow. The standard methods for quantifying or reducing uncertainty in regional projections are predicated on the models capturing and representing the key dynamical instabilities, which is doubtful for present coupled models. This limitation does not apply to all regional projections, nor does it apply to the fundamental findings of greenhouse climate change. Much of what is known is not highly flow-dependent and follows from well grounded radiative physics and thermodynamic principles. The growing field of applications of regional climate projections would benefit from a more critical appraisal of ignorance in these projections.     

East African food security as influenced by future climate change and land use change at local to regional scales

Climate change impacts food production systems, particularly in locations with large, vulnerable populations. Elevated greenhouse gases (GHG), as well as land cover/land use change (LCLUC), can influence regional climate dynamics. Biophysical factors such as topography, soil type, and seasonal rainfall can strongly affect crop yields. We used a regional climate model derived from the Regional Atmospheric Modeling System (RAMS) to compare the effects of projected future GHG and future LCLUC on spatial variability of crop yields in East Africa. Crop yields were estimated with a process-based simulation model. The results suggest that: (1) GHG-influenced and LCLUC-influenced yield changes are highly heterogeneous across this region; (2) LCLUC effects are significant drivers of yield change; and (3) high spatial variability in yield is indicated for several key agricultural sub-regions of East Africa. Food production risk when considered at the household scale is largely dependent on the occurrence of extremes, so mean yield in some cases may be an incomplete predictor of risk. The broad range of projected crop yields reflects enormous variability in key parameters that underlie regional food security; hence, donor institutions’ strategies and investments might benefit from considering the spatial distribution around mean impacts for a given region. Ultimately, global assessments of food security risk would benefit from including regional and local assessments of climate impacts on food production. This may be less of a consideration in other regions. This study supports the concept that LCLUC is a first-order factor in assessing food production risk.     

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.     

Local-scale climate scenarios for impact studies and risk assessments: integration of early 21st century ENSEMBLES projections into the ELPIS database

We present the integration of early 21st century climate projections for Europe based on simulations carried out within the EU-FP6 ENSEMBLES project with the LARS-WG stochastic weather generator. The aim was to upgrade ELPIS, a repository of local-scale climate scenarios for use in impact studies and risk assessments that already included global projections from the CMIP3 ensemble and regional scenarios for Japan. To obtain a more reliable simulation of daily rainfall and extremes, changes in wet and dry series derived from daily ENSEMBLES outputs were taken into account. Kernel average smoothers were used to reduce noise arising from sampling artefacts. Examples of risk analyses based on 25-km climate projections from the ENSEMBLES ensemble of regional climate models illustrate the possibilities offered by the updated version of ELPIS. The results stress the importance of tailored information for local-scale impact assessments at the European level.     

On the regional distribution of mitigation costs in a global cap-and-trade regime

This paper analyzes the regional distribution of climate change mitigation costs in a global cap-and-trade regime. Four stylized burden-sharing rules are considered, ranging from GDP-based permit allocations to schemes that foresee a long-term convergence of per-capita emission permits. The comparison of results from three structurally different hybrid, integrated energy-economy models allows us to derive robust insights as well as identify sources of uncertainty with respect to the regional distribution of the costs of climate change mitigation. We find that regional costs of climate change mitigation may deviate substantially from the global mean. For all models, the mitigation cost average of the four scenarios is higher for China than for the other macro-regions considered. Furthermore, China suffers above-world-average mitigation costs for most burden-sharing rules in the long-term. A decomposition of mitigation costs into (a) primary (domestic) abatement costs and (b) permit trade effects, reveals that the large uncertainty about the future development of carbon prices results in substantial uncertainties about the financial transfers associated with carbon trade for a given allocation scheme. This variation also implies large uncertainty about the regional distribution of climate policy costs.     

The concepts and development of a participatory regional integrated assessment tool

This paper provides an overview of the development of the ‘Regional Impact Simulator’ – a user friendly software tool designed to allow stakeholders to perform integrated assessments of the effects of climate and/or socio-economic change on the important sectors and resources of two contrasting UK regions. This includes the assessment of agriculture, water resources, biodiversity and coastal and river flooding. The tool arose from the need to further develop the methods applied in the earlier RegIS project, which was the first local to regional integrated assessment in the UK. The limitations of RegIS included very long run times, a limited number of simulations, incomplete linkages between models and no allowance for scenario uncertainty. Based upon the stakeholder needs identified within RegIS, a series of guiding principles were developed with Steering Committee stakeholders, which informed the concept of the ‘Regional Impact Simulator’ including functionality, appearance and complexity. An Integrated Assessment Methodology based upon the Drivers-Pressure-State-Impact-Response (DPSIR) framework facilitated the integration of multiple models, scenarios and datasets within the software interface. The development of the ‘Regional Impact Simulator’ provides a test-bed for further studies of stakeholder-led, regional, integrated assessment, and provides an opportunity to learn the many lessons in undertaking such studies.