Precipitation or evapotranspiration? Bayesian analysis of potential error sources in the simulation of sub-basin discharges in the Czech Elbe River basin

A global change assessment required detailed simulation of water availability in the Elbe River basin in Central Europe (148,268?km2). Using the spatially semi-distributed, eco-hydrological model SWIM, spatial calibration was applied. For 225 sub-areas covering the model domain (134,890?km2), evapotranspiration and groundwater dynamics were individually adjusted. The calibration aimed at good correspondences with long-term run-off contributions and the hydrographs for two extreme years. Measured run-off was revised from water management effects to produce quasi-natural discharges for calibration. At some gauges, there were large volume differences between these reference data and the simulations of the spatially uncalibrated model. Most affected were some sub-basins in the Czech part of the basin where the density of available climate stations was much lower than the German part. Thus, both erroneous precipitation data and systematic flaws in the evapotranspiration module of SWIM could have caused the differences. In order to identify the major error source and to validate the choice of spatial calibration parameters (evapotranspiration and groundwater dynamic corrections), MCMC analyses were made for three Czech areas. Optional precipitation correction had been considered by a third calibration parameter in the MCMC assessment. In two of the three cases, it can be shown that evapotranspiration corrections are preferable as precipitation errors are negligible. In the third case, where the analyses indicate a substantial error in precipitation data, an interpolation problem of the climate data at the edge of the model domain could be found. Hence, the applied method shows its potential to identify specific sources of uncertainty in hydrological modelling.     

Climate change impacts on a pine stand in Central Siberia

The objective of this paper is to analyse the impacts of climate change on a pine forest stand in Central Siberia (Zotino) to assess benefits and risks for such forests in the future. We use the regional statistical climate model STARS to develop a set of climate change scenarios assuming a temperature increase by mid-century of 1, 2, 3 and 4 K. The process-based forest growth model 4C is applied to a 200-year-old pine forest to analyse impacts on carbon and water balance as well as the risk of fire under these climate change scenarios. The climate scenarios indicate precipitation increases mainly during winter and decreases during summer with increasing temperature trend. They cause rising forest productivity up to about 20 % in spite of increasing respiration losses. At the same time, the water-use efficiency increases slightly from 2.0 g C l^?1 H₂O under current climate to 2.1 g C l^?1 H₂O under 4 K scenario indicating that higher water losses from increasing evapotranspiration do not appear to lead to water limitations for the productivity at this site. The simulated actual evaporation increases by up to 32 %, but the climatic water balance decreases by up to 20 % with increasing temperature trend. In contrast, the risk of fire indicated by the Nesterov index clearly increases. Our analysis confirms increasing productivity of the boreal pine stand but also highlights increasing drought stress and risks from abiotic disturbances which could cancel out productivity gains.     

Vulnerability of Catalan (NW Mediterranean) ports to wave overtopping due to different scenarios of sea level rise

The overtopping of port breakwaters may affect the assets located at the breakwater lee side. If adaptation measures are not taken, the sea level rise will increase the overtopping discharges putting those assets at significant risk. This study compares, at a regional scale, overtopping discharges over port breakwaters for three storm conditions (return periods of 1, 5 and 50 years) under present climate as well as for three scenarios of sea level rise based on recent projections. The results indicate that, for the worst storm and sea level rise conditions, the overtopping discharge would not be negligible (larger than 1 l/s/m) in 35 ports (84 %), in contrast to only 18 ports (42 %) being affected under present conditions. In addition, in 28 ports (65 %) the overtopping would be at least one order of magnitude larger than for present conditions. In the case of large storms, in 2 ports the overtopping discharge exceeds 200 l/s/m (the discharge that can initiate breakwater damage) under present conditions, while in the worst scenario of sea level rise the number of ports exceeding this value would be 7. On the other hand, the vulnerability of each port for which overtopping flow is greater than an acceptable discharge flux is assessed, and regional maps of vulnerability are plotted. For the worst storm conditions, 23 % of the Catalan ports have risks associated with overtopping under present climate conditions. This percentage would increase to 47 % in the worst sea level rise scenario.     

Productivity of rainfed wheat as affected by climate change scenario in northeastern Punjab, India

Wheat (Triticum aestivum L.) is grown as a rainfed crop in the sub-mountainous region of the Punjab state of India, with low crop and water productivity. The present study aims to assess the effect of climate change scenario (A1B) derived from PRECIS—a regional climate model—on wheat yield and water productivity. After minimizing bias in the model climate data for mid-century (2021–2050), evapotranspiration (ET) and yield of wheat crop were simulated using Decision Support System for Agrotechnology Transfer, version 4.5, model. In the changed climate, increased temperature would cause reduction in wheat yield to the extent of 4, 32 and 61 % in the mid-century periods between 2021–2030, 2031–2040 and 2041–2050, respectively, by increasing water stress and decreasing utilization efficiency of photosynthetically active radiation. The decreases in crop water productivity would be 40, 56 and 76 %, respectively, which are caused by decreased yield and increased ET. Planting of wheat up to November 25 till the years 2030–2031 seems to be helpful to mitigate the climate change effect, but not beyond that.     

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.     

Future heat-related climate change impacts on tourism industry in Cyprus

Tourism is a vital sector of Cyprus economy, attracting millions of tourists every year and providing economic growth and employment for the country. The aim of this study was to investigate the impacts of projected climate change in the tourism industry in Cyprus (Republic of Cyprus) using both “Tourism Climate Index” (TCI) and “Beach Climate Index” (BCI). TCI refers to tourism activities mainly related to sightseeing, nature-based tourism, and religious tourism etc., while BCI represents beach tourism that constitutes 85 % of tourism activities in Cyprus. The projections of climate change impacts in tourism are performed for 2071–2100 period, using regional climate model output employing the A1B greenhouse gas emissions scenario. The 1961–1990 period is used as the control run to compare the respective results of the future projections. The significant warming anticipated in the distant future (increases in annual and summer temperatures close to 4 °C) will have adverse impacts on Cyprus tourism industry regarding sightseeing tourism. TCI results for the distant future period show only acceptable conditions for general tourism activities during summer in contrast with the good/very good conditions in the present climate. Conversely, this type of tourism seems to be benefited in shoulder seasons, i.e., during spring and autumn; TCI and hence tourist activities improve in the distant future in relation to the present climate. On the other hand, concerning beach tourism, future projections indicate that it will not be negatively affected by future climate change and any changes will be positive.     

Climate change and coastal vulnerability assessment: scenarios for integrated assessment

Coastal vulnerability assessments still focus mainly on sea-level rise, with less attention paid to other dimensions of climate change. The influence of non-climatic environmental change or socio-economic change is even less considered, and is often completely ignored. Given that the profound coastal changes of the twentieth century are likely to continue through the twenty-first century, this is a major omission, which may overstate the importance of climate change, and may also miss significant interactions of climate change with other non-climate drivers. To better support climate and coastal management policy development, more integrated assessments of climatic change in coastal areas are required, including the significant non-climatic changes. This paper explores the development of relevant climate and non-climate drivers, with an emphasis on the non-climate drivers. While these issues are applicable within any scenario framework, our ideas are illustrated using the widely used SRES scenarios, with both impacts and adaptation being considered. Importantly, scenario development is a process, and the assumptions that are made about future conditions concerning the coast need to be explicit, transparent and open to scientific debate concerning their realism and likelihood. These issues are generic across other sectors.

Uncertainty in the difference between maps of future land change scenarios

It is essential to measure whether maps of various scenarios of future land change are meaningfully different, because differences among such maps serve to inform land management. This paper compares the output maps of different scenarios of future land change in a manner that contrasts two different approaches to account for the uncertainty of the simulated projections. The simpler approach interprets the scenario storyline concerning the quantity of each land change transition as assumption, and then considers the range of possibilities concerning the value added by a simulation model that specifies the spatial allocation of land change. The more complex approach estimates the uncertainty of future land maps based on a validation measurement with historic data. The technique is illustrated by a case study that compares two scenarios of future land change in the Plum Island Ecosystems of northeastern Massachusetts, in the United States. Results show that if the model simulates only the spatial allocation of the land changes given the assumed quantity of each transition, then there is a clearly bounded range for the difference between the raw scenario maps; but if the uncertainties are estimated by validation, then the uncertainties can be so great that the output maps do not show meaningful differences. We discuss the implications of these results for a future research agenda of land change modeling. We conclude that a productive approach is to use the simpler method to distinguish clearly between variations in the scenario maps that are due to scenario assumptions versus variations due to the simulation model.     

高精度区域气候模式对淮河流域降水的模拟评估

利用CCLM（COSMO model in Climate Mode）高精度区域气候模式输出的淮河流域逐日降水数据，计算了年降水量、降水强度、大雨日数和强降水量4个降水指数，首先通过与1961～2010年流域内气象站点的降水观测数据进行对比，检验CCLM模式对淮河流域降水的模拟能力。结果表明，CCLM模式能够很好的模拟淮河流域降水的年际变化和空间分布特征，在4个降水指数中，对年降水量的模拟效果最佳。CCLM模式在SRES-A1B（中排放）情景下的降水预估数据显示，2011～2050年淮河流域降水整体将呈增加趋势，增幅在70 mm之内，降水量年际变率较大，波动范围达-40%～60%，很有可能造成未来旱涝灾害的频繁发生。空间分布上，流域南部和中部在未来40年内降水呈增加趋势，增幅不超过67%，其他区域则呈减少趋势，减幅不超过106%     

长江流域土地利用/覆被变化的大尺度水文效应

土地利用/覆被变化(LUCC)对流域水文过程具有重要的长期影响作用。针对土地利用覆被变化对大型流域水文过程的影响程度,利用构建的长江流域分布式水文模型分析了土地利用变化情景下的水文效应特征。结果显示:分布式水文模型综合考虑了下垫面土壤、坡度、植被等特征,可以较好的反映降水发生后水分在不同土壤、植被和地形条组合件下,蒸散、地表和地下径流等组分的运移过程。根据不同土地覆被类型的径流成分差异,以及长江流域实际可供调节的土地利用方式,流域现有土地利用格局中农林地依然具有较大的转换空间。根据典型流域中预设的农林地转换情景下的径流效应看,各种情景虽然对流域径流总量变化影响较小,但对蒸散、地表径流和基流可以产生显著影响。其中,林地增加使基流最高提升超过15%,同时可使地表径流下降近5%,两者对蒸散的改变在1%左右,对径流总量变化幅度则只有0.7%左右。不同情景下的水文响应模式反映了未来土地利用调整的水文效应,因此可以基于不同的径流效应,开展有利于综合发挥流域持水能力的空间规划,提升林地所占比重。     

Projections of industrial water withdrawal under shared socioeconomic pathways and climate mitigation scenarios

We estimated global future industrial water withdrawal (IWW) by considering socioeconomic driving forces, climate mitigation, and technological improvements, and by using the output of the Asia–Pacific Integrated Model/Computable General Equilibrium (AIM/CGE) model. We carried out this estimation in three steps. First, we developed a sector- and region-specific regression model for IWW. The model utilized and analyzed cross-country panel data using historical statistics of IWW for 10 sectors and 42 countries. Second, we estimated historical IWW by applying a regression model. Third, we projected future IWW from the output of AIM/CGE. For future projections, we considered and included multiple socioeconomic assumptions, namely different shared socioeconomic pathways (SSPs) with and without climate mitigation policy. In all of the baseline scenarios, IWW was projected to increase throughout the twenty-first century, but growth through the latter half of the century is likely to be modest mainly due to the effects of decreased water use intensity. The projections for global total IWW ranged from 461 to 1,560 km³/year in 2050 and from 196 to 1,463 km³/year in 2100. The effects of climate mitigation on IWW were both negative and positive, depending on the SSPs. We attributed differences among scenarios to the balance between the choices of carbon capture and storage (CCS) and renewable energy. A smaller share of CCS was accompanied by a larger share of non-thermal renewable energy, which requires a smaller amount of water withdrawal per unit of energy production. Renewable energy is, therefore, less water intensive than thermal power with CCS with regard to decarbonizing the power system.     

Identifying opportunities for long-lasting habitat conservation and restoration in Hawaii’s shifting climate

Conservation efforts in isolated archipelagos such as Hawaii often focus on habitat-based conservation and restoration efforts that benefit multiple species. Unfortunately, identifying locations where such efforts are safer from climatic shifts is still challenging. We aimed to provide a method to approximate these potential habitat shifts for similar data- and research-limited contexts. We modeled the relationship between climate and the potential distribution of native biomes across the Hawaiian archipelago to provide a first approximation of potential native biome shifts under end-of-century projected climate. Our correlative model circumvents the lack of data necessary for the parameterization of mechanistic vegetation models in isolated and data-poor islands. We identified locations consistently expected to remain the same in terms of the native biome compatibility by the end of the century with a robust evaluation of sources of uncertainty in our projections. Our results show that, despite large differences in climate projections considered, 35% of the areas considered are consistently projected to maintain their current compatibility to native biomes. By integrating our native biome compatibility projections with maps of current actual cover, we identified areas ideal for long-term habitat conservation and restoration. Our modeling approach can be used with relatively simple data; offers multiple forms of projection confidence estimates, model calibration, and variable selection routines; and is compatible with ensemble projections. This method is not only applicable to potential native cover, as done in this study, but to any set of vegetation classes that are related to environmental predictors available for modeling.     

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.     

Framing climate uncertainty: socio-economic and climate scenarios in vulnerability and adaptation assessments

Scenarios have become a powerful tool in integrated assessment and policy analysis for climate change. Socio-economic and climate scenarios are often combined to assess climate change impacts and vulnerabilities across different sectors and to inform risk management strategies. Such combinations of scenarios can also play an important role in enabling the interaction between experts and other stakeholders, framing issues and providing a means for making explicit and dealing with uncertainties. Drawing on experience with the application of scenarios to climate change assessments in recent Dutch research, the paper argues that scenario approaches need to be matched to the frames of stakeholders who are situated in specific decision contexts. Differentiated approaches (top-down, bottom-up and interactive) are needed to address the different frames and decision-making contexts of stakeholders. A framework is proposed to map scenarios and decision contexts onto two dimensions: the spatial scale of the context and the starting point of approach used in scenario development (top-down, bottom-up or incident-driven). Future climate and socio-economic scenario development will be shaped by the need to become better aligned with multiple interacting uncertainties salient to stakeholders.     

Using qualitative scenarios to understand regional environmental change in the Canadian North

This paper discusses the application of qualitative scenarios to understand community vulnerability and adaptation responses, based on a case study in the Slave River Delta region of the Northwest Territories, Canada. Three qualitative, graphic scenarios of possible alternative futures were developed, focusing on two main drivers: climate change and resource development. These were used as a focal point for discussions with a cross-section of residents from the community during focus groups, interviews and a community workshop. Significant overlap among the areas of perceived vulnerability is evident among scenarios, particularly in relation to traditional land use. However, each scenario also offers insights about specific challenges facing community members. Climate change was perceived to engender mostly negative livelihood impacts, whereas resource development was expected to trigger a mix of positive and negative impacts, both of which may be more dramatic than in the “climate change only” scenario. The scenarios were also used to identify adaptation options specific to individual drivers of change, as well as more universally applicable options. Identified adaptation options were generally aligned with five sectors—environment and natural resources, economy, community management and development, infrastructure and services, and information and training—which effectively offer a first step towards prioritization of “no regrets” measures. From an empirical perspective, while the scenarios highlighted the need for bottom-up measures, they also elucidated discussion about local agency in adaptation and enabled the examination of multi-dimensional impacts on different community sub-groups. An incongruity emerged between the suite of technically oriented adaptation options and more socially and behaviourally oriented barriers to implementation. Methodologically, the qualitative scenarios were flexible, socially inclusive and consistent with the Indigenous worldview; allowed the incorporation of different knowledge systems; addressed future community vulnerability and adaptation; and led to the identification of socially feasible and bottom-up adaptation outcomes. Despite some caveats regarding resource requirements for participatory scenario development, qualitative scenarios offer a versatile tool to address a range of vulnerability and adaptation issues in the context of other Indigenous communities.     

Forest fires and adaptation options in Europe

This paper presents a quantitative assessment of adaptation options in the context of forest fires in Europe under projected climate change. A standalone fire model (SFM) based on a state-of-the-art large-scale forest fire modelling algorithm is used to explore fuel removal through prescribed burnings and improved fire suppression as adaptation options. The climate change projections are provided by three climate models reflecting the SRES A2 scenario. The SFM’s modelled burned areas for selected test countries in Europe show satisfying agreement with observed data coming from two different sources (European Forest Fire Information System and Global Fire Emissions Database). Our estimation of the potential increase in burned areas in Europe under “no adaptation” scenario is about 200 % by 2090 (compared with 2000–2008). The application of prescribed burnings has the potential to keep that increase below 50 %. Improvements in fire suppression might reduce this impact even further, e.g. boosting the probability of putting out a fire within a day by 10 % would result in about a 30 % decrease in annual burned areas. By taking more adaptation options into consideration, such as using agricultural fields as fire breaks, behavioural changes, and long-term options, burned areas can be potentially reduced further than projected in our analysis.     

Assessing the implications of a 1.5 °C temperature limit for the Jamaican agriculture sector

Despite recent calls to limit future increases in the global average temperature to well below 2 °C, little is known about how different climatic thresholds will impact human society. Future warming trends have significant global food security implications, particularly for small island developing states (SIDS) that are recognized as being among the most vulnerable to global climate change. In the case of the Caribbean, any significant change in the region’s climate is likely to have significant adverse effects on the agriculture sector. This paper explores the potential biophysical impacts of a +?1.5 °C warming scenario on several economically important crops grown in the Caribbean island of Jamaica. Also, it explores differences to a >?2.0 °C warming scenario, which is more likely, if the current policy agreements cannot be complied with by the international community. We use the ECOCROP niche model to estimate how predicted changes in future climate could affect the growing conditions of several commonly cultivated crops from both future scenarios. We then discuss some key policy considerations for Jamaica’s agriculture sector, specifically related to the challenges posed to future adaptation pathways amidst growing climate uncertainty and complexity. Our model results show that even an increase less than +?1.5 °C is expected to have an overall negative impact on crop suitability and a general reduction in the range of crops available to Jamaican farmers. This observation is instructive as increases above the +?1.5 °C threshold would likely lead to even more irreversible and potentially catastrophic changes to the sustainability of Jamaica’s agriculture sector. The paper concludes by outlining some key considerations for future action, paying keen attention to the policy relevance of a +?1.5 °C temperature limit. Given little room for optimism with respect to the imminent changes that SIDS will need to confront in the near future, broad-based policy engagement by stakeholders in these geographies is paramount, irrespective of the climate warming scenario.     

近52a西南地区潜在蒸散发时空变化特征

潜在蒸散发对水资源评价和气候变化均具有重要意义。采用Penman-Monteith公式和气象观测资料计算了中国西南地区90个气象站的潜在蒸散发,并采用多种统计方法分析了潜在蒸散发的时空变化特征。结果表明:(1)西南地区近52a的平均潜在蒸散发为3 209.8 mm,其中云南省潜在蒸散发最高(3 664.7 mm),其次为四川省(3 015.0 mm)、重庆市(2 972.4 mm)、贵州省(2 958.0 mm)。四季潜在蒸散发空间分布特征与年不同,从大到小排序为夏季,春季,秋季,冬季。(2)西南地区整体呈增加趋势(0.9 mm/10 a),其中31个站点呈减少趋势(p0.1),17个站点呈增加趋势(p0.1),其余站点变化趋势不显著。大部分站点春季(55.6%)和夏季(63.3%)呈减少趋势,秋季(62.2%)和冬季(58.9%)则呈增加趋势。(3)经MannKendall突变检验,该区整体潜在蒸散发的突变时间为1995年(p0.05);单个站点突变检验显示,76个站点发生突变,突变年份集中于1980s,未发生突变的站点主要分布于青藏高原东缘。整体上看,近52a来西南地区潜在蒸散发略呈增加趋势,并存在突变点,但部分站点存在相反的变化趋势,这和复杂的地形环境和气候特征有较大关系,体现出西南地区水文气象变化的独特性。     

Glacier response to current climate change and future scenarios in the northwestern Italian Alps

We analyze longtime series of annual snout positions of several valley glaciers in the northwestern Italian Alps, together with a high-resolution gridded dataset of temperature and precipitation available for the last 50 years. Glacier snout fluctuations are on average negative during this time span, albeit with a period of glacier advance between about 1970 and 1990. To determine which climatic variables best correlate with glacier snout fluctuations, we consider a large set of seasonal predictors, based on our climatic dataset, and determine the most significant drivers by a stepwise regression technique. This in-depth screening indicates that the average glacier snout fluctuations strongly respond to summer temperature and winter precipitation variations, with a delay of 5 and 10 year, respectively. Snout fluctuations display also a significant (albeit weak) response to concurrent (same year) spring temperature and precipitation conditions. A linear regressive model based on these four climatic variables explains up to 93 % of the variance, which becomes 89 % when only the two delayed variables are taken into account. When employed for out-of-sample projections, the empirical model displays high prediction skill, and it is thus used to estimate the average glacier response to different climate change scenarios (RCP4.5, RCP8.5, A1B), using both global and regional climate models. In all cases, glacier snout fluctuations display a negative trend, and the glaciers of this region display an accelerated retreat, leading to a further regression of the snout position. By 2050, the retreat is estimated to be between about 300 and 400 m with respect to the current position. Glacier regression is more intense for the RCP8.5 and A1B scenarios, as it could be expected from the higher severity of these emission pathways.     

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.