Regional and global climate projections increase mid-century yield variability and crop productivity in Belgium

The impact of mid-century climatic changes on crop productivity of winter wheat, maize, potato and sugar beet was assessed for a temperate maritime climate in the Flemish Region, Belgium. Climatic projections of multiple regional and global climate models (RCMs from the EU-ENSEMBLES project and GCMs from the Coupled Model Intercomparison Project phase 3) were stochastically downscaled by the LARS-WG weather generator for use in the crop models AquaCrop and Sirius. Primarily positive effects on mean yield were simulated. Crops benefitted from elevated CO₂, and from more radiation interception if the cropping period was adapted in response to higher temperatures. However, increased productivity was linked with increased susceptibility to water stress and greater inter-annual yield variability, particularly with adapted management. Impacts differed among and within ensembles of climate models, and among crops and environments. Although RCMs may be more suitable for local impact assessments than GCMs, inter-ensemble differences and contingent wider ranges of impacts with GCM projections found in this study indicate that applying RCMs driven by a limited number of GCMs alone would not give the full range of possible impacts. Further, this study suggests that the simulated intermodel variation can be larger than spatial variation within the region. These findings advocate the use of both GCM and RCM ensembles in assessments where temperature and precipitation are central, such as for crop production.     

Projecting canopy cover change in Tasmanian eucalypt forests using dynamically downscaled regional climate models

Loss of forest cover is a likely consequence of climate change in many parts of the world. To test the vulnerability of eucalypt forests in Australia’s island state of Tasmania, we modelled tree canopy cover in the period 2070–2099 under a high-emission scenario using the current climate–canopy cover relationship in conjunction with output from a dynamically downscaled regional climate model. The current climate–canopy cover relationship was quantified using Random Forest modelling, and the future climate projections were provided by three dynamically downscaled general circulation model (GCM) simulations. Three GCMs were used to show a range of projections for the selected scenario. We also explored the sensitivity of key endemic and non-endemic Tasmanian eucalypts to climate change. All GCMs suggested that canopy cover should remain stable (proportional cover change <10 %) across ~70 % of the Tasmanian eucalypt forests. However, there were geographic areas where all models projected a decline in canopy cover due to increased summer temperatures and lower precipitation, and in addition, all models projected an increase in canopy cover in the coldest part of the state. The model projections differed substantially for other areas. Tasmanian endemic species appear vulnerable to climate change, but species that also occur on the mainland are likely to be less affected. Given these changes, restoration and carbon sequestration plantings must consider the species and provenances most suitable for future, rather than present, climates.     

24个CMIP5模式对长江流域模拟能力评估

根据1961~2005年长江流域气象站点的实测月降水量和气温数据,采用第5期全球耦合模式比较计划CMIP5(the Fifth Phase of Coupled Model Intercomparison Project)中24个全球气候模式(GCM)的模拟结果,通过计算模拟变量和观测变量平均值的相对误差、归一化的均方根误差、时间和空间相关系数,采用M-K趋势分析方法,分别选用在长江流域模拟气温和降水较好的5个模式进行集合平均,从时间的演变规律和空间的分布特征两方面,检验该模式集合对长江流域模拟气温和降水的能力。研究结果表明:各个模式模拟气温的能力要明显好于模拟降水的能力,但模拟气温较好的模式模拟降水的能力并不一定突出;模式集合的结果表明:在时间尺度上,模式集合平均结果与观测值拟合程度较好,且模式集合的结果振荡幅度较观测值小;在空间尺度上,模式集合的空间分布趋势与观测值大致相同,说明采用的模式集合结果用于预估未来长江流域降水的时空分布特征和演变规律是可行的。     

Coastal vulnerability assessment of the predicted sea level rise in the coastal zone of Krishna–Godavari delta region,Andhra Pradesh,east coast of India

The Krishna–Godavari coastal region in east coast of India has a 525.15-km-long coastline with low-lying tidal mudflats, beaches, mangrove swamp, creek and tidal channels. Recently, the increasing frequency of tropical cyclones in the Bay of Bengal, i.e., Phylin and Hudhud in Andhra Pradesh coast, and the devastating impact of the 2004 tsunami in India increased the significance in assessing the vulnerability of the coastal lands to inundation and flooding, notably in the context of climate change-induced sea level rise. This study aims to estimate a coastal vulnerability index (CVI) for the coastal subregion of Krishna–Godavari delta and to use the calculated index to evaluate the vulnerability of 14 coastal talukas of the Krishna–Godavari delta region. This CVI is calculated by using four geological and three physical parameters characterizing the vulnerability of the study coastal region, including regional slope, coastal elevation, geomorphology, significant wave height, mean tidal range and relative sea level using different conventional and remotely sensed data. Using a composite coastal vulnerability index based on the relative risk rating of those parameters, each of the 14 coastal talukas was classified according to their vulnerability. The CVI results depict that coasts are least and most vulnerable to inundation, flooding and erosion of coastal lands where geological parameters are more efficient to CVI. The paper alerts to decision makers and planners to mitigate the natural disaster and manage the coastal zone and is a primary step toward prioritizing coastal lands for climate change adaptation strategies in the view of increased storminess and projected sea level rise.     

Integrating regional perceptions into climate change adaptation: a transdisciplinary case study from Germany’s North Sea Coast

Coastal protection strategies increasingly have to take into account the effects of climate change. At present, engineering and natural science models that assess the impact of global climatic transformations on regional coastal zones and their protection structures remain rather detached from the knowledge and insights of regional practitioners. The main thesis of this contribution, using a case study from the North Sea Coast of Germany, is that innovative coastal protection requires not only interdisciplinary research but transdisciplinary collaboration in order to develop a viable adaptation strategy. The investigation of the social dimension of climate change and coastal protection strategies, using qualitative interviews with organized regional stakeholders, climate researchers and coastal engineers, as well as a representative public survey, contributes to a comprehensive understanding of regional perceptions with respect to climate change and coastal protection.     

Freshwater stress on small island developing states: population projections and aridity changes at 1.5 and 2 °C

Small island developing states (SIDS) face multiple threats from anthropogenic climate change, including potential changes in freshwater resource availability. Due to a mismatch in spatial scale between SIDS landforms and the horizontal resolution of global climate models (GCMs), SIDS are mostly unaccounted for in GCMs that are used to make future projections of global climate change and its regional impacts. Specific approaches are required to address this gap between broad-scale model projections and regional, policy-relevant outcomes. Here, we apply a recently developed methodology that circumvents the GCM limitation of coarse resolution in order to project future changes in aridity on small islands. These climate projections are combined with independent population projections associated with shared socioeconomic pathways (SSPs) to evaluate overall changes in freshwater stress in SIDS at warming levels of 1.5 and 2 °C above pre-industrial levels. While we find that future population growth will dominate changes in projected freshwater stress especially toward the end of the century, projected changes in aridity are found to compound freshwater stress for the vast majority of SIDS. For several SIDS, particularly across the Caribbean region, a substantial fraction (~?25%) of the large overall freshwater stress projected under 2 °C at 2030 can be avoided by limiting global warming to 1.5 °C. Our findings add to a growing body of literature on the difference in climate impacts between 1.5 and 2 °C and underscore the need for regionally specific analysis.     

Probabilistic impacts of climate change on flood frequency using response surfaces I: England and Wales

The impacts of climate change on hydrology are an important focus of research around the world, but the use of large ensembles to drive impact models is not necessarily straightforward and has to be redone when new projections are released. Here, an alternative sensitivity framework approach is demonstrated, using a set of typical response surfaces alongside the probabilistic UK Climate Projections (UKCP09). These projections comprise sets of 10,000 changes in a number of variables, available for 10 river-basin regions covering England and Wales. Estimates of the potential range of impacts on 20-year return period flood peaks are presented for different types of catchment in each region. Regional average impact ranges are compared for a number of time horizons and emissions scenarios. Results show clear differences in impacts between catchments of different types and between regions. South-East England has the highest impacts with the greatest uncertainty range, while the Dee region has the lowest impacts and smallest uncertainty range. Regional differences are due to both spatial differences in projections and a differing regional balance in the number of catchments of each type. Ease of application of multiple projections is a clear advantage of this sensitivity-based approach to impact assessment, which could be extended to other regions and sectors.     

Mid-21st century climate and weather extremes in Cyprus as projected by six regional climate models

We present climate change projections and apply indices of weather extremes for the Mediterranean island Cyprus using data from regional climate model (RCM) simulations driven by the IPCC A1B scenario within the ENSEMBLES project. Daily time-series of temperature and precipitation were used from six RCMs for a reference period 1976–2000 and for 2026–2050 (‘future‘) for representative locations, applying a performance selection among neighboring model grid-boxes. The annual average temperatures of the model ensemble have a ±1.5°C bias from the observations (negative for maximum and positive for minimum temperature), and the models underestimate annual precipitation totals by 4–17%. The climatological annual cycles for the observations fall within the 1σ range of the 6-model average, highlighting the strength of using multi-model output. We obtain reasonable agreement between models and observations for the temperature-related indices of extremes for the recent past, while the comparison is less good for the precipitation-related extremes. For the future, the RCM ensemble shows significant warming of 1°C in winter to 2°C in the summer for both maximum and minimum temperatures. Rainfall is projected to decrease by 2–8%, although this is not statistically significant. Our results indicate the shift of the mean climate to a warmer state, with a relatively strong increase in the warm extremes. The precipitation frequency is projected to decrease at the inland Nicosia and at the coastal Limassol, while the mountainous Saittas could experience more frequent 5–15 mm/day rainfall. In future, very hot days are expected to increase by more than 2 weeks/year and tropical nights by 1 month/year. The annual number of consecutive dry days shows a statistically significant increase (of 9 days) in Limassol. These projected changes of the Cyprus climate may adversely affect ecosystems and the economy of the island and emphasize the need for adaptation strategies.     

Exploring the efficiency of bias corrections of regional climate model output for the assessment of future crop yields in Europe

Excessive summer drying and reduced growing season length are expected to reduce European crop yields in future. This may be partly compensated by adapted crop management, increased CO₂ concentration and technological development. For food security, changes in regional to continental crop yield variability may be more important than changes in mean yields. The assessment of changes in regional and larger scale crop variability requires high resolution and spatially consistent future weather, matching a specific climate scenario. Such data could be derived from regional climate models (RCMs), which provide changes in weather patterns. In general, RCM output is heavily biased with respect to observations. Due to the strong nonlinear relation between meteorological input and crop yields, the application of this biased output may result in large biases in the simulated crop yield changes. The use of RCM output only makes sense after sufficient bias correction. This study explores how RCM output can be bias corrected for the assessment of changes in European and subregional scale crop yield variability due to climate change. For this, output of the RCM RACMO of the Royal Netherlands Meteorological Institute was bias corrected and applied within the crop simulation model WOrld FOod STudies to simulate potential and water limited yields of three divergent crops: winter wheat, maize and sugar beets. The bias correction appeared necessary to successfully reproduce the mean yields as simulated with observational data. It also substantially improved the year-to-year variability of seasonal precipitation and radiation within RACMO, but some bias in the interannual variability remained. This is caused by the fact that the applied correction focuses on mean and daily variability. The interannual variability of growing season length, and as a consequence the potential yields too, appeared even deteriorated. Projected decrease in mean crop yields is well in line with earlier studies. No significant change in crop yield variability was found. Yet, only one RCM is analysed in this study, and it is recommended to extend this study with more climate models and a slightly adjusted bias correction taking into account the variability of larger time scales as well.     

Physical basis of coastal adaptation on tropical small islands

Small tropical islands are widely recognized as having high exposure and vulnerability to climate change and other natural hazards. Ocean warming and acidification, changing storm patterns and intensity, and accelerated sea-level rise pose challenges that compound the intrinsic vulnerability of small, remote, island communities. Sustainable development requires robust guidance on the risks associated with natural hazards and climate change, including the potential for island coasts and reefs to keep pace with rising sea levels. Here we review these issues with special attention to their implications for climate-change vulnerability, adaptation, and disaster risk reduction in various island settings. We present new projections for 2010–2100 local sea-level rise (SLR) at 18 island sites, incorporating crustal motion and gravitational fingerprinting, for a range of Intergovernmental Panel on Climate Change global projections and a semi-empirical model. Projected 90-year SLR for the upper limit A1FI scenario with enhanced glacier drawdown ranges from 0.56 to 1.01 m for islands with a measured range of vertical motion from ?0.29 to +0.10 m. We classify tropical small islands into four broad groups comprising continental fragments, volcanic islands, near-atolls and atolls, and high carbonate islands including raised atolls. Because exposure to coastal forcing and hazards varies with island form, this provides a framework for consideration of vulnerability and adaptation strategies. Nevertheless, appropriate measures to adjust for climate change and to mitigate disaster risk depend on a place-based understanding of island landscapes and of processes operating in the coastal biophysical system of individual islands.     

Assessment of regional climate change impacts on Hungarian landscapes

The assessment of regional climate change impacts combined with the sensitivity of landscape functions by predictive modelling of hazardous landscape processes is a new fundamental field of research. In particular, this study investigates the effects of changing weather extremes on meso-regional-scale landscape vulnerability. Climatic-exposure parameter analysis was performed on a predicted climate change scenario. The exposure to climate change was analysed on the basis of the original data of the meso-scale IPCC A1B climate scenario from the REMO and ALADIN regional models for the periods of 2021–2050 and 2071–2100, and the regional types of climate change impacts were calculated by using cluster analysis. Selected climate exposure parameters of the REMO and ALADIN models were analysed, in particular, for extreme events (days with precipitation greater than 30 mm, heat waves, dry periods, wet periods) and for daily temperature and precipitation. The landscape functions impacted by climate change are proxies for the main recent and future problematic processes in Hungary. Soil erosion caused by water, drought, soil erosion caused by wind, mass movement and flash floods were analysed for the time periods of 1961–1990, 2021–2050 and 2071–2100. Based on the sensitivity thresholds for the impact assessments, the landscape functional sensitivity indicators were interpreted, and an integrative summary of the five indicators was made, differentiating the regions facing only a few or multiple sensitivities. In Central Hungary, the increasing exposure and sensitivity to droughts will be a serious problem when following the REMO scenario. In several regions, most indicators will change the sensitivity threshold from a tolerable risk to an increased or very high risk.     

The viticultural system and climate change: coping with long-term trends in temperature and rainfall in Roussillon,France

Mediterranean viticulture could suffer from hotter and drier growing seasons over the coming decades. The present article focuses on the wine-producing area Côtes-du-Roussillon-Villages near Perpignan, in southern France. We used observational daily data (1925–2010) from Perpignan weather station and daily outputs (2001–2060) of the regional climate model ARPEGE-RETIC-V4 from Météo-France with scenarios A2, A1B and B1, to assess the exposure of the regional wine system to changes in temperature and precipitation, both in the recent past and the coming decades (1925–2060). Temperatures during the growing season and summer temperature extremes have been increasing continuously since the mid-1980s and are projected to increase faster from the mid-2040s. Precipitation is highly variable and very low in summer, and projections suggest greater uncertainty, and more extreme drought events could be expected. The analysis of climate data was complemented by thirty-two in-depth interviews with local actors of the wine industry to assess the impacts of climate change on their activities and potential adaptive options. Producers reported negative impacts of recent changes in climate in conjunction with a difficult economic situation. Analyses of historical, social and economic backgrounds are important to fully conceptualize the nature and extent of climate change risks in the region. This case study provides important insights into the roles of non-climatic factors in the generation of vulnerability for Mediterranean agricultural systems facing rapid climate change.     

Projected changes in heat wave characteristics in the eastern Mediterranean and the Middle East

According to observed twentieth century temperature trends and twenty-first century climate model projections, the region that encompasses the eastern Mediterranean and the Middle East (EMME) is identified as a climate change hot spot. We extend previous studies by a comprehensive climatology of heat waves in the EMME based on regional climate model simulations for the recent past and the end of the twenty-first century. A percentile-based definition of heat waves is used to account for local climatic conditions. Spatial patterns of several heat wave properties are assessed and associated with atmospheric circulation regimes over specific locations. To cover a range of possible future climates, we use three SRES emission scenarios. According to our results, all indices that characterize heat wave severity will strongly increase compared with the control period of 1961–1990. The northern part of the EMME could be exposed to increased heat wave amplitudes by 6–10 °C, and the southern part may experience 2–3 months more combined hot days and tropical nights. Heat wave peak temperatures will be higher due to the overall mean warming as well as stronger summer anticyclonic conditions. The projected changes will affect human health and the environment in multiple ways and call for impact studies to support the development of adaptation strategies.     

Statistical downscaling for climate change projections in the Mediterranean region: methods and results

Besides dynamical downscaling by regional climate models, statistical downscaling (SD) is a major tool to derive climate change projections on regional or even local scales. For the Mediterranean area, an increasing number of downscaling studies based on different statistical techniques have been published in the last two decades with a broad range of sometimes differing results relating to different variables and regional domains. This paper gives a short review of these Mediterranean downscaling studies mainly considering the following two aspects: (1) what kind of progress has been realized in this field since the early 1990s? The review addresses the inclusion of extremes in downscaling assessments, the development of probabilistic approaches, the extension of predictor sets, the use of ensembles for both dynamical model simulations and statistical model assessments, the consideration of non-stationarities in the predictor–predictand relationships, and some advances related to synoptic downscaling. (2) What are the main regional climate change signals in the Mediterranean area, considering agreed and controversial points also with respect to dynamical models? Best accordance among future projections can be found in seasonal temperatures with lower rates of warming in winter and spring, and, in most cases, higher ones in summer and autumn. Different results are obtained for the intra-annual range of extreme temperatures, but high-temperature conditions are generally expected to increase. Regarding seasonal precipitation, predominant reductions are indicated for spring, summer, and autumn. For winter, however, projections are distinctly different (GCMs: rainfall decrease; RCMs: increase only in the northernmost parts of the Mediterranean region; SD: widespread increases in the northern and western parts in several studies). Different results are obtained for rainfall extremes, but the entire precipitation distribution tends to shift towards higher and lower values. Apart from some sub-regional deviations, there is a predominant increase in future dry period durations. For near-surface winds, only a few studies are available, and they project some decline mainly for the winter season.     

Obstacles to climate change adaptation decisions: a case study of sea-level rise and coastal protection measures in Kiribati

International aid is increasingly focused on adaptation to climate change. At recent meetings of the parties to the United Nations Framework Convention on Climate Change, the developed world agreed to rapidly increase international assistance to help the developing world respond to the impacts of climate change. In this paper, we examine the decision-making challenges facing internationally supported climate change adaptation projects, using the example of efforts to implement coastal protection measures (e.g. sea walls, mangrove planting) in Kiribati. The central equatorial Pacific country is home to the Kiribati Adaptation Project, the first national-level climate change adaptation project supported by the World Bank. Drawing on interview and document research conducted over an 8-year period, we trace the forces influencing decisions about coastal protection measures, starting from the variability and uncertainty in climate change projections, through the trade-offs between different measures, to the social, political, and economic context in which decisions are finally made. We then discuss how sub-optimal adaptation measures may be implemented despite years of planning, consultation, and technical studies. This qualitative analysis of the real-world process of climate change adaptation reveals that embracing a culturally appropriate and short-term (~20 years) planning horizon, while not ignoring the longer-term future, may reduce the influence of scientific uncertainty on decisions and provide opportunities to learn from mistakes, reassess the science, and adjust suboptimal investments. The limiting element in this approach to adaptation is likely to be the availability of consistent, long-term financing.     

Climate change impacts,vulnerability and adaptive capacity of the electrical energy sector in Cyprus

The purpose of this study was to investigate the climate change impacts, vulnerability and adaptive capacity of the electrical energy sector in Cyprus. Spatial vulnerability of the island was assessed using the degree-day indicator to investigate heating and cooling demands in the near future using daily temperature projections from regional climate models (RCMs). Using daily electrical energy consumption data for the present climate, an impact model linking consumption and temperature was constructed and this relationship was projected to the future climate using the data from the RCMs and assuming the same technology use. Our impact model results showed that for the period between November and April (‘cold period’), a decreasing trend in electrical energy consumption is evident due to warmer conditions in the near future, while for the period between May and October (‘warm period’), an increasing trend in electricity consumption is evident as warmer conditions dominate by 2050. Regarding the spatial vulnerability assessment, the cooling degree-day indicator testified that major increases in cooling demand, between 100 and 200 degree-days, are expected in inland and southern regions during the summer in the near future. In addition, increases of about 20–50 degree-days are anticipated during autumn. Conversely, energy demand for heating is projected to decrease during spring and winter, especially in the higher elevation parts of the island. More precisely, reductions of about 30–75 degree-days are projected during spring, while greater reductions of about 60–90 degree-days are expected during winter in heating demand, especially for in the near future. The ability of the energy sector to adapt and follow these changes was deemed to be satisfactory reducing the overall vulnerability of the sector to future climate change.     

Building blocks of economic resilience to climate change: a south east Australian fisheries example

Climate change will impact on ecological, social, and economic elements of fisheries; however, the three are seldom considered in an integrated fashion. We develop a fishery-level assessment of economic resilience to climate change for the Tasmanian rock lobster fishery, a linked social–ecological system. We outline the main climate change forcing influences that link climate change to the fishery via changes in lobster abundance, distribution, and phenology. Using a bottom-up approach, we identify twelve economic attributes strongly related to the fisheries’ economic resilience to climate change. Resilience attributes are grouped according to the level of the economic domain (business, sectoral, and governance). Attributes are then evaluated to determine the overall economic resilience of the rock lobster fishery in the context of the specific nature of predicted climate change effects. We identify areas of low resilience in the economic sub-system for this fishery. Evaluating the economic resilience of regional fisheries using this integrated, interdisciplinary framework provides a practical, parsimonious, and conceptually sound basis for undertaking comprehensive and contextually tailored assessments of climate change impacts and economic vulnerability. The framework can be extended to include a broader range of climate change impacts and the social domain of the human sub-system.     

Regionalization of climate scenarios impacts on maize production and the role of cultivar and planting date as an adaptation strategy

Understanding climate change and its impacts on crops is crucial to determine adaptation strategies. Simulations of climate change impacts on agricultural systems are often run for individual sites. Nevertheless, the scaling up of crop model results can bring a more complete picture, providing better inputs for the decision-making process. The objective of this paper was to present a procedure to assess the regional impacts of climate scenarios on maize production, as well as the effect of crop cultivars and planting dates as an adaptation strategy. The focus region is Santa Catarina State, Brazil. The identification of agricultural areas cultivated with annual crops was done for the whole state, followed by the coupling of soil and weather information necessary for the crop modeling procedure (using crop model and regional circulation models). The impact on maize yields, so as the effect of adaptation strategies, was calculated for the 2012–2040 period assuming different maize cultivars and planting dates. Results showed that the exclusion of non-agricultural areas allowed the crop model to correctly simulate local and regional production. Simulations run without adaptation strategies for the 2012–2040 period showed reductions of 11.5–13.5 % in total maize production, depending on the cultivar. By using the best cultivar for each agricultural area, total state production was increased by 6 %; when using both adaptation strategies—cultivar and best planting date—total production increased by 15 %. This analysis showed that cultivar and planting date are feasible adaptation strategies to mitigate deleterious effects of climate scenarios, and crop models can be successfully used for regional assessments.     

A “toad’s eye” view of drought: regional socio-natural vulnerability and responses in 2002 in Northwest Colorado

Drought is a part of the normal climate variability and the life and livelihoods of the Western United States. However, drought can also be a high impact or extreme event in some cases, such as the exceptional 2002 drought that had deleterious impacts across the Western United States. Studies of long-term climate variability along with climate change projections indicate that the Western United States should expect much more severe and extended drought episodes than experienced over the last century when most modern water law and policies were developed, such as the 1922 Colorado River Compact. This paper will discuss research examining regional socio-natural climate vulnerability and adaptive response capacities to the 2002 drought in the Yampa–White Basins region of Colorado across sectors and will demonstrate how a bottom-up or “toad’s eye” approach to understanding drought is paramount to complement top-down, instrumental data-driven analyses of drought. The results of empirical observations through interviews and participant observation in combination with analysis of drought indicators will be presented. Implications for adaptation research and planning for climate variability and change will be discussed.     

An integrated decision-support process for adaptation planning: climate change as impetus for scenario planning in an agricultural region of Canada

The amount of information required to adapt to climate change is vast: downscaled climate projections, information on environmental impact, sectoral performance, external drivers, regional strategies, policies and practices. It can be argued that most of this information is accessible at the community/regional level, and thus, the important challenges to adaptation are not information gaps, but constraints created by fragmented planning decisions and a sector-by-sector basis for financial and human resource allocations. To strategically address this through adaptation planning, we developed and tested a place-based decision-making framework that creates an integrated platform for considering regional and global sectoral drivers in Eastern Ontario, Canada. Using available socioeconomic and biophysical information from regional authorities, alternative future scenarios were used to describe the range of socioeconomic futures and their vulnerabilities to climate change. We found that: (1) integration of diverse sets of available data (rather than narrowly focused sectoral assessments) helped identify shared common objectives (maximizing the long-term environmental, economic, social well-being within the region), (2) a high degree of congruence existed as the key drivers of change, irrespective of sector, (3) exploring the future scenarios highlighted shared regional priorities and helped identify adaptation priorities requiring more integrated regional planning.