Assessing climate change impacts,sea level rise and storm surge risk in port cities: a case study on Copenhagen

This study illustrates a methodology to assess the economic impacts of climate change at a city scale and benefits of adaptation, taking the case of sea level rise and storm surge risk in the city of Copenhagen, capital of Denmark. The approach is a simplified catastrophe risk assessment, to calculate the direct costs of storm surges under scenarios of sea level rise, coupled to an economic input–output (IO) model. The output is a risk assessment of the direct and indirect economic impacts of storm surge under climate change, including, for example, production and job losses and reconstruction duration, and the benefits of investment in upgraded sea defences. The simplified catastrophe risk assessment entails a statistical analysis of storm surge characteristics, geographical-information analysis of population and asset exposure combined with aggregated vulnerability information. For the city of Copenhagen, it is found that in absence of adaptation, sea level rise would significantly increase flood risks. Results call for the introduction of adaptation in long-term urban planning, as one part of a comprehensive strategy to manage the implications of climate change in the city. Mitigation policies can also aid adaptation by limiting the pace of future sea level rise.     

The economic value of delaying adaptation to sea-level rise: An application to coastal properties in Connecticut

The magnitude and frequency of coastal storms are expected to increase with rising global sea levels, which necessitates evaluating coastal flood adaptation measures. This study examines an important issue in the context of coastal flood protection, namely, the decision when to adopt protection measures. For any given coastal region, our benefit-cost framework allows us to determine the optimal timing of initiating protection that maximizes expected net benefits. We present an application of this framework to a coastal area in Connecticut. Our results suggest that the optimal timing of adopting protection may vary across different census blocks within the study area. We find that using a relatively low discount rate in the benefit-cost analysis implies greater heterogeneity in the timing decisions and earlier overall adoption, whereas, with higher discount rates, the timing decisions are reduced to a choice between early protection and no protection at all. If possible negative environmental and aesthetic impacts of sea barriers are taken into account, delaying protection would become more desirable, with the extent of delay being sensitive to the relative magnitude of one-time costs (e.g., loss of ocean view and recreational opportunities) vs. continuous costs (e.g., shoreline erosion and loss of wetlands).     

Spatial variations of sea-level rise and impacts: An application of DIVA

Due to complexities of creating sea-level rise scenarios, impacts of climate-induced sea-level rise are often produced from a limited number of models assuming a global uniform rise in sea level. A greater number of models, including those with a pattern reflecting regional variations would help to assure reliability and a range of projections, indicating where models agree and disagree. This paper determines how nine new patterned-scaled sea-level rise scenarios (plus the uniform and patterned ensemble mean rises) influence global and regional coastal impacts (wetland loss, dry land loss due to erosion and the expected number of people flooded per year by extreme sea levels). The DIVA coastal impacts model was used under an A1B scenario, and assumed defences were not upgraded as conditions evolved. For seven out of nine climate models, impacts occurred at a proportional rate to global sea-level rise. For the remaining two models, higher than average rise in sea level was projected in northern latitudes or around populated coasts thus skewing global impact projections compared with the ensemble global mean. Regional variability in impacts were compared using the ensemble mean uniform and patterned scenarios: The largest relative difference in impacts occurred around the Mediterranean coast, and the largest absolute differences around low-lying populated coasts, such as south, south-east and east Asia. Uniform projections of sea-level rise impacts remain a useful method to determine global impacts, but improved regional scale models of sea-level rise, particularly around semi-enclosed seas and densely populated low-lying coasts will provide improved regional impact projections and a characterisation of their uncertainties.     

Modelling the combined impacts of sea-level rise and land subsidence on storm tides induced flooding of the Huangpu River in Shanghai, China

This paper presents a scenario-based study that investigates the interaction between sea-level rise and land subsidence on the storm tides induced fluvial flooding in the Huangpu river floodplain. Two projections of relative sea level rise (RSLR) were presented (2030 and 2050). Water level projections at the gauging stations for different return periods were generated using a simplified algebraic summation of the eustatic sea-level rise, land subsidence and storm tide level. Frequency analysis with relative sea level rise taken into account shows that land subsidence contributes to the majority of the RSLR (between 60 % and 70 %). Furthermore, a 1D/2D coupled flood inundation model (FloodMap) was used to predict the river flow and flood inundation, after calibration using the August 1997 flood event. Numerical simulation with projected RSLR suggests that, the combined impact of eustatic sea-level rise and land subsidence would be a significantly reduced flood return period for a given water level, thus effective degradation of the current flood defences. In the absence of adaptation measures, storm flooding will cause up to 40 % more inundation, particularly in the upstream of the river.     

Impact assessments and policy responses to sea-level rise in three US states: An exploration of human-dimension uncertainties

Uncertainties in the human dimensions of global change deeply affect the assessment and responses to climate change impacts such as sea-level rise (SLR). This paper explores the uncertainties in the assessment process and in state-level policy and management responses of three US states to SLR. The findings reveal important political, economic, managerial, and social factors that enable or constrain SLR responses; question disasters as policy windows; and uncover new policy opportunities in the history of state coastal policies. Results suggest that a more realistic, and maybe more useful picture of climate change impacts will emerge if assessments take more seriously the locally embedded realities and constraints that affect individual decision-makers’ and communal responses to climate change.     

An assessment of the physical impacts of sea-level rise and coastal adaptation: a case study of the eastern coast of Ghana

Sea-level rise is a major coastal issue in the 21st century because many of the world??s built assets are located in the coastal zone. Coastal erosion and flooding are serious threats along the coast of Ghana, particularly, the eastern coast where the Volta delta is located. Past human interventions, climate change and the resultant rise in sea-levels, increased storm intensity and torrential rainfall have been blamed for these problems. Accelerated sea-level rise and storm surge pose serious threat to coastal habitat, bio-diversity and socio-economic activities in the coastal zone of Ghana and elsewhere. There is the need for an holistic assessment of the impacts of sea-level rise on the coast zone in order to formulate appropriate adaptation policies and strategies to mitigate the possible effects. Using the eastern coast of Ghana as a case study, this paper assesses the physical impacts of accelerated sea level rise and storm surge on the coastal environment. It evaluates adaptation policies and plans that could be implemented to accommodate the present and any future impacts. Field investigation and Geographic Information System (GIS) are among the methods used for the assessment. The outcome of the assessment has provided comprehensive knowledge of the potential impacts of accelerated sea-level rise and storm surge on the eastern coast. It has facilitated identification of management units, the appraisal of alternate adaptation policies and the selection of the best policy options based upon the local conditions and environmental sustainability. Among other things, this paper reveals that the eastern coast of Ghana is highly vulnerable to accelerated sea-level rise and therefore, requires sustainable adaptation policies and plans to manage the potential impacts. It recommends that various accommodation policies, which enable areas to be occupied for longer before eventual retreat, could be adapted to accommodate vulnerable settlements in the eastern coast of Ghana.     

Potential impacts of sea-level rise on the Mid- and Upper-Atlantic Region of the United States

We made projections of relative sea-level rise, horizontal inundation, and the associated impacts on people and infrastructure in the coastal portion of the Mid- and Upper-Atlantic Region (MUAR) of the United States. The output of five global climate models (GCMs) run under two greenhouse gas scenarios was used in combination with tide gauge observations to project sea-level increases ranging from 200 to 900 mm by 2100, depending on location, GCM and scenario. The range mainly reflects equal contributions of spatial variability (due to subsidence) and GCM uncertainty, with a smaller fraction of the range due to scenario uncertainty. We evaluated 30-m Digital Elevation Models (DEMs) using 10-m DEMs and LIDAR data at five locations in the MUAR. We found average RMS differences of 0.3 m with the 10-m DEMs and 1.2 m with the LIDAR data, much lower than the reported mean RMS errors of 7 m for the 30-m DEMs. Using the 30-m DEMs, the GCM- and scenario-means of projected sea-level rise, and local subsidence estimates, we estimated a total inundation of 2,600 km² for the MUAR by 2100. Inundation area increases to 3,800 km² at high tide if we incorporate local tidal ranges in the analysis. About 510,000 people and 1,000 km of road lie within this area. Inundation area per length of coastline generally increases to south, where relative sea-level rise is greater and relief is smaller. More economically developed states, such as New York and New Jersey, have the largest number of people and infrastructure exposed to risk of inundation due to sea-level rise.     

Incorporating uncertainty of future sea-level rise estimates into vulnerability assessment: A case study in Kahului, Maui

Accurate sea-level rise (SLR) vulnerability assessments are essential in developing effective management strategies for coastal systems at risk. In this study, we evaluate the effect of combining vertical uncertainties in Light Detection and Ranging (LiDAR) elevation data, datum transformation and future SLR estimates on estimating potential land area and land cover loss, and whether including uncertainty in future SLR estimates has implications for adaptation decisions in Kahului, Maui. Monte Carlo simulation is used to propagate probability distributions through our inundation model, and the output probability surfaces are generalized as areas of high and low probability of inundation. Our results show that considering uncertainty in just LiDAR and transformation overestimates vulnerable land area by about 3 % for the high probability threshold, resulting in conservative adaptation decisions, and underestimates vulnerable land area by about 14 % for the low probability threshold, resulting in less reliable adaptation decisions for Kahului. Not considering uncertainty in future SLR estimates in addition to LiDAR and transformation has variable effect on SLR adaptation decisions depending on the land cover category and how the high and low probability thresholds are defined. Monte Carlo simulation is a valuable approach to SLR vulnerability assessments because errors are not required to follow a Gaussian distribution.     

The economic impact of extreme sea-level rise: Ice sheet vulnerability and the social cost of carbon dioxide

The possibility of extreme sea-level rise is one of the commonly cited reasons for concern about climate change. Major increases in sea level would likely be driven by the melting or collapse of major ice sheets. This possibility has implications for the social cost of carbon dioxide, which is a key policy value as well as a useful summary measure of damage caused by greenhouse gas emissions.This paper extends earlier work on the importance of low-probability, high-impact events for the social cost of carbon dioxide to incorporate the possibility of extreme sea-level rise.To estimate its impact, an integrated assessment model is used, which allows a probabilistic assessment of climate change damages based on the linkages between the economic and climate systems. In the model, the generic discontinuity damage is replaced with the possibility of large-scale damage from factors that are taken to be correlated with temperature rise and, crucially for this paper, explicit consideration of extreme sea-level rise.Estimates of the amount of increase in the social cost of carbon dioxide that can be expected from incorporating extreme sea-level rise show that the increase is significant, though not especially large in percentage terms.The paper contributes to the literature of how to represent uncertain climate impacts in integrated assessment models and the associated estimation of the social cost of carbon dioxide.     

Local values for fairer adaptation to sea-level rise: A typology of residents and their lived values in Lakes Entrance,Australia

Understanding the values and socio-economic characteristics of people at risk from climate change will inform how people feel about the likely distribution of impacts, as well as adaptation responses. This knowledge is necessary if adaptation is to achieve distributive fairness now and into the future. This study advances methods and analyses used in values-based adaptation research by using segmentation to explain the diversity of values that exist within a community, and on this basis identify particular groups at risk. A telephone survey was conducted with residents of Lakes Entrance, Australia—a coastal community already adapting to projected sea-level rise. The purpose was to determine the priorities residents place on a range of lived values—valuations that individuals make about what is important in their lives and the places they live. The telephone survey data was then analysed using cluster analysis to develop a lived values typology of residents. The analysis revealed that there are at least eight types of residents living in Lakes Entrance and that each group of residents has a unique set of lived values that will be differentially affected by sea-level rise and adaptation. The findings indicate that if sea-level rise adaptation policy is to be distributively fair it needs to develop a suite of adaptation responses that ensure that the lived values of each group of residents, and thus a diversity of values, are maintained or enhanced.     

The effects of aggressive mitigation on steric sea level rise and sea ice changes

With an increasing political focus on limiting global warming to less than 2 °C above pre-industrial levels it is vital to understand the consequences of these targets on key parts of the climate system. Here, we focus on changes in sea level and sea ice, comparing twenty-first century projections with increased greenhouse gas concentrations (using the mid-range IPCC A1B emissions scenario) with those under a mitigation scenario with large reductions in emissions (the E1 scenario). At the end of the twenty-first century, the global mean steric sea level rise is reduced by about a third in the mitigation scenario compared with the A1B scenario. Changes in surface air temperature are found to be poorly correlated with steric sea level changes. While the projected decreases in sea ice extent during the first half of the twenty-first century are independent of the season or scenario, especially in the Arctic, the seasonal cycle of sea ice extent is amplified. By the end of the century the Arctic becomes sea ice free in September in the A1B scenario in most models. In the mitigation scenario the ice does not disappear in the majority of models, but is reduced by 42 % of the present September extent. Results for Antarctic sea ice changes reveal large initial biases in the models and a significant correlation between projected changes and the initial extent. This latter result highlights the necessity for further refinements in Antarctic sea ice modelling for more reliable projections of future sea ice.     

The effects of adaptation and mitigation on coastal flood impacts during the 21st century. An application of the DIVA and IMAGE models

This paper studies the effects of mitigation and adaptation on coastal flood impacts. We focus on a scenario that stabilizes concentrations at 450 ppm-CO₂-eq leading to 42 cm of global mean sea-level rise in 1995–2100 (GMSLR) and an unmitigated one leading to 63 cm of GMSLR. We also consider sensitivity scenarios reflecting increased tropical cyclone activity and a GMSLR of 126 cm. The only adaptation considered is upgrading and maintaining dikes. Under the unmitigated scenario and without adaptation, the number of people flooded reaches 168 million per year in 2100. Mitigation reduces this number by factor 1.4, adaptation by factor 461 and both options together by factor 540. The global annual flood cost (including dike upgrade cost, maintenance cost and residual damage cost) reaches US$ 210 billion per year in 2100 under the unmitigated scenario without adaptation. Mitigation reduces this number by factor 1.3, adaptation by factor 5.2 and both options together by factor 7.8. When assuming adaptation, the global annual flood cost relative to GDP falls throughout the century from about 0.06 % to 0.01–0.03 % under all scenarios including the sensitivity ones. From this perspective, adaptation to coastal flood impacts is meaningful to be widely applied irrespective of the level of mitigation. From the perspective of a some less-wealthy and small island countries, however, annual flood cost can amount to several percent of national GDP and mitigation can lower these costs significantly. We conclude that adaptation and mitigation are complimentary policies in coastal areas.     

The climatic impacts of land surface change and carbon management, and the implications for climate-change mitigation policy

Strategies to mitigate anthropogenic climate change recognize that carbon sequestration in the terrestrial biosphere can reduce the build-up of carbon dioxide in the Earth’s atmosphere. However, climate mitigation policies do not generally incorporate the effects of these changes in the land surface on the surface albedo, the fluxes of sensible and latent heat to the atmosphere, and the distribution of energy within the climate system. Changes in these components of the surface energy budget can affect the local, regional, and global climate. Given the goal of mitigating climate change, it is important to consider all of the effects of changes in terrestrial vegetation and to work toward a better understanding of the full climate system. Acknowledging the importance of land surface change as a component of climate change makes it more challenging to create a system of credits and debits wherein emission or sequestration of carbon in the biosphere is equated with emission of carbon from fossil fuels. Recognition of the complexity of human-caused changes in climate does not, however, weaken the importance of actions that would seek to minimize our disturbance of the Earth’s environmental system and that would reduce societal and ecological vulnerability to environmental change and variability.     

The global impacts of US climate policy: a model simulation using GCAM-TU and MAGICC

To assess the potential impacts of the US withdrawal from the Paris Agreement, this study applied GCAM-TU (an updated version of the Global Change Assessment Model) to simulate global and regional emission pathways of energy-related CO₂, which show that US emissions in 2100 would reduce to ?2.4?Gt, ?0.7?Gt and ?0.2?Gt under scenarios of RCP2.6, RCP3.7 and RCP4.5, respectively. Two unfavourable policy scenarios were designed, assuming a temporary delay and a complete stop for US mitigation actions after 2015. Simulations by the Model for the Assessment of Greenhouse-gas Induced Climate Change (MAGICC) indicate that the temperature increase by 2100 would rise by 0.081°C–0.161°C compared to the three original RCPs (Representative Concentration Pathways) if US emissions were kept at their 2015 levels until 2100. The probability of staying below 2°C would decrease by 6–9% even if the US resumes mitigation efforts for achieving its Nationally Determined Contribution (NDC) target after 2025. It is estimated by GCAM-TU that, without US participation, increased reduction efforts are required for the rest of the world, including developing countries, in order to achieve the 2°C goal, resulting in 18% higher global cumulative mitigation costs from 2015 to 2100.

Key policy insights

• President Trump’s climate policies, including planned withdrawal from the Paris Agreement, cast a shadow on international climate actions, and would lower the likelihood of achieving the 2°C target.

• To meet the 2°C target without the US means increased reduction efforts and mitigation costs for the rest of the world, and considerable economic burdens for major developing areas.

• Active state-, city- and enterprise-level powers should be supported to keep the emission reduction gap from further widening even with reduced mitigation efforts from the US federal government.

     

The economics of climate change impacts and policy benefits at city scale: a conceptual framework

Cities are particularly vulnerable to climate change and climate extremes in part because they concentrate many activities, people and wealth in limited areas. As a result they represent an important scale for assessment and understanding of climate change impacts. This paper provides a conceptual and methodological framework for urban economic impact assessment of climate change. The focus of the paper is on model-based analysis of future scenarios, including a framing of uncertainty for these projections, as one valuable input into the decision-making process. The paper highlights the main assessment difficulties, methods and tools, and selected examples across these areas. A number of challenges are unique to climate change impact assessment and others are unique to the problem of working at local scales. The paper also identifies the need for additional research, including the need for more integrated and systemic approaches to address climate change as a part of the urban development challenge as well as the need to assess the economic impacts of climate change and response policy at local scale.     

Uncertainty, learning and ambiguity in economic models on climate policy: some classical results and new directions

We present how uncertainty and learning are classically studied in economic models. Specifically, we study a standard expected utility model with two sequential decisions, and consider two particular cases of this model to illustrate how uncertainty and learning may affect climate policy. While uncertainty has generally a negative effect on welfare, learning has always a positive, and thus opposite, effect. The effects of both uncertainty and learning on decisions are less clear. Neither uncertainty nor learning can be used as a general argument to increase or reduce emissions today without studying the specific intertemporal costs and benefits. Considering limits in applying the expected utility framework to climate change problems, we then consider a more recent framework with ambiguity-aversion which accounts for situations of imprecise or multiple probability distributions. We discuss both the impact of ambiguity-aversion on decisions and difficulties in applying such a non-expected utility framework to a dynamic context.