2022
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Projections of future sea-level change are characterized by both quantifiable uncertainty and by ambiguity. Both types of uncertainty are relevant to users of sea-level projections, particularly those making long-term investment and planning decisions with multigenerational consequences. Communicating information about both types is thus a central challenge faced by scientists who generate sea-level projections to support decision-making. Diverse approaches to communicating uncertainty in future sea-level projections have been taken over the last several decades, but the literature evaluating these approaches is limited and not systematic. Here, we review how the Intergovernmental Panel on Climate Change (IPCC) has approached uncertainty in sealevel projections in past assessment cycles and how this information has been interpreted by national and subnational assessments, as well as alternative approaches used by recent US subnational assessments. The evidence reviewed here generally supports the explicit approach to communicating both types of uncertainty adopted by the IPCC Sixth Assessment Report (AR6).
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Sea level rise (SLR) will increase adaptation needs along low-lying coasts worldwide. Despite centuries of experience with coastal risk, knowledge about the effectiveness and feasibility of societal adaptation on the scale required in a warmer world remains limited. This paper contrasts end-century SLR risks under two warming and two adaptation scenarios, for four coastal settlement archetypes (Urban Atoll Islands, Arctic Communities, Large Tropical Agricultural Deltas, Resource-Rich Cities). We show that adaptation will be substantially beneficial to the continued habitability of most low-lying settlements over this century, at least until the RCP8.5 median SLR level is reached. However, diverse locations worldwide will experience adaptation limits over the course of this century, indicating situations where even ambitious adaptation cannot sufficiently offset a failure to effectively mitigate greenhouse-gas emissions.
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Climate variability and climate change influence human migration both directly and indirectly through a variety of channels that are controlled by individual and household socioeconomic, cultural, and psychological processes as well as public policies and network effects. Characterizing and predicting migration flows are thus extremely complex and challenging. Among the quantitative methods available for predicting such flows is the widely used gravity model that ignores the network autocorrelation among flows and thus may lead to biased estimation of the climate effects of interest. In this study, we use a network model, the additive and multiplicative effects model for network (AMEN), to investigate the effects of climate variability, migrant networks, and their interactions on South African internal migration. Our results indicate that prior migrant networks have a significant influence on migration and can modify the association between climate variability and migration flows. We also reveal an otherwise obscure difference in responses to these effects between migrants moving to urban and non-urban destinations. With different metrics, we discover diverse drought effects on these migrants; for example, the negative standardized precipitation index (SPI) with a timescale of 12 months affects the non-urban-oriented migrants’ destination choices more than the rainy season rainfall deficit or soil moisture do. Moreover, we find that socioeconomic factors such as the unemployment rate are more significant to urban-oriented migrants, while some unobserved factors, possibly including the abolition of apartheid policies, appear to be more important to non-urban-oriented migrants.
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Future coastal flood hazard at many locations will be impacted by both tropical cyclone (TC) change and relative sea-level rise (SLR). Despite sea level and TC activity being influenced by common thermodynamic and dynamic climate variables, their future changes are generally considered independently. Here, we investigate correlations between SLR and TC change derived from simulations of 26 Coupled Model Intercomparison Project Phase 6 models. We first explore correlations between SLR and TC activity by inference from two large-scale factors known to modulate TC activity: potential intensity (PI) and vertical wind shear. Under the high emissions SSP5-8.5, SLR is strongly correlated with PI change (positively) and vertical wind shear change (negatively) over much of the western North Atlantic and North West Pacific, with global mean surface air temperature (GSAT) modulating the co-variability. To explore the impact of the joint changes on flood hazard, we conduct climatological–hydrodynamic modeling at five sites along the US East and Gulf Coasts. Positive correlations between SLR and TC change alter flood hazard projections, particularly at Wilmington, Charleston and New Orleans. For example, if positive correlations between SLR and TC changes are ignored in estimating flood hazard at Wilmington, the average projected change to the historical 100 years storm tide event is under-estimated by 12%. Our results suggest that flood hazard assessments that neglect the joint influence of these factors and that do not reflect the full distribution of GSAT change may not accurately represent future flood hazard.
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Estimates of changes in the frequency or height of contemporary extreme sea levels (ESLs) under various climate change scenarios are often used by climate and sea level scientists to help communicate the physical basis for societal concern regarding sea level rise. Changes in ESLs (i.e., the hazard) are often represented using various metrics and indicators that, when anchored to salient impacts on human systems and the natural environment, provide useful information to policy makers, stakeholders, and the general public. While changes in hazards are often anchored to impacts at local scales, aggregate global summary metrics generally lack the context of local exposure and vulnerability that facilitates translating hazards into impacts. Contextualizing changes in hazards is also needed when communicating the timing of when projected ESL frequencies cross critical thresholds, such as the year in which ESLs higher than the design height benchmark of protective infrastructure (e.g., the 100-year water level) are expected to occur within the lifetime of that infrastructure. We present specific examples demonstrating the need for such contextualization using a simple flood exposure model, local sea level rise projections, and population exposure estimates for 414 global cities. We suggest regional and global climate assessment reports integrate global, regional, and local perspectives on coastal risk to address hazard, vulnerability and exposure simultaneously.
2021
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2020
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2019
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Despite considerable advances in process understanding, numerical modeling, and the observational record of ice sheet contributions to global mean sea-level rise (SLR) since the Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change, severe limitations remain in the predictive capability of ice sheet models. As a consequence, the potential contributions of ice sheets remain the largest source of uncertainty in projecting future SLR. Here, we report the findings of a structured expert judgement study, using unique techniques for modeling correlations between inter- and intra-ice sheet processes and their tail dependences. We find that since the AR5, expert uncertainty has grown, in particular because of uncertain ice dynamic effects. For a +2 °C temperature scenario consistent with the Paris Agreement, we obtain a median estimate of a 26 cm SLR contribution by 2100, with a 95th percentile value of 81 cm. For a +5 °C temperature scenario more consistent with unchecked emissions growth, the corresponding values are 51 and 178 cm, respectively. Inclusion of thermal expansion and glacier contributions results in a global total SLR estimate that exceeds 2 m at the 95th percentile. Our findings support the use of scenarios of 21st century global total SLR exceeding 2 m for planning purposes. Beyond 2100, uncertainty and projected SLR increase rapidly. The 95th percentile ice sheet contribution by 2200, for the +5 °C scenario, is 7.5 m as a result of instabilities coming into play in both West and East Antarctica. Introducing process correlations and tail dependences increases estimates by roughly 15%.
Global mean sea-level rise (SLR), which during the last quarter century has occurred at an accelerating rate (1), averaging about +3 mm⋅y−1, threatens coastal communities and ecosystems worldwide. Adaptation measures accounting for the changing hazard, including building or raising permanent or movable structures such as surge barriers and sea walls, enhancing nature-based defenses such as wetlands, and selective retreat of populations and facilities from areas threatened by episodic flooding or permanent inundation, are being planned or implemented in several countries. Risk assessment for such adaptation efforts requires projections of future SLR, including careful characterization and evaluation of uncertainties (2) and regional projections that account for ocean dynamics, gravitational and rotational effects, and vertical land motion (3). During the nearly 40 y since the first modern, scientific assessments of SLR, understanding of the various causes of this rise has advanced substantially. Improvements during the past decade include closing the historic sea-level budget, attributing global mean SLR to human activities, confirming acceleration of SLR since the nineteenth century and during the satellite altimetry era, and developing analytical frameworks for estimating regional and local mean sea level and extreme water level changes. Nonetheless, long-term SLR projections remain acutely uncertain, in large part because of inadequate understanding of the potential future behaviors of the Greenland and Antarctic ice sheets and their responses to future global climate change. This limitation is especially troubling, given that the ice sheet influence on SLR has been increasing since the 1990s (4) and has overtaken mountain glaciers to become the largest barystatic (mass) contribution to SLR (5). In addition, for any given future climate scenario, the ice sheets constitute the component with the largest uncertainties by a substantial margin, especially beyond 2050 (6).
Advances since the Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (7) include improved process understanding and representation in deterministic ice sheet models (8, 9), probabilistic projections calibrated against these models and the observational record (10), and new semiempirical models, based on the historical relationship between temperature and sea-level changes. Each of these approaches has limitations that stem from factors including poorly understood processes, poorly constrained boundary conditions, and a short (∼25 y) satellite observation record of ice sheets that does not capture the time scales of internal variability in the ice sheet climate system. As a consequence, it is unclear to what extent recent observed ice sheet changes (11) are a result of internal variability (ice sheet weather) or external forcing (ice sheet climate).
Where other methods are intractable for scientific or practical reasons, structured expert judgement (SEJ), using calibrated expert responses, provides a formal approach for estimating uncertain quantities according to current scientific understanding. It has been used in a wide range of applications, including natural and anthropogenic hazards such as earthquakes, volcanic eruptions, vector-borne disease spread, and nuclear waste security (12). That said, it should not be regarded as a substitute for fundamental research into driving processes, but instead as a source of complementary insights into the current state of knowledge and, in particular, the extent of the uncertainties (12). An SEJ study conducted in advance of the AR5 (13) (hereafter BA13) provided valuable insights into the uncertainties around ice sheet projections, as assessed at that time.
Since then, regional- and continental-scale, process-based modeling of ice sheets has advanced substantially (8, 9, 14–16), with the inclusion of new positive feedbacks that could potentially accelerate mass loss, and negative feedbacks that could potentially slow it. These include solid Earth and gravitational processes (17, 18), Antarctic marine ice cliff instability (19), and the influences of organic and inorganic impurities on the albedo of the Greenland Ice Sheet (20). The importance of these feedbacks is an area of continuing research. Therefore, alternative approaches must be exploited to assess future SLR and, critically, its associated uncertainties (21), to serve the more immediate needs of the science and policy communities.
Here, we report the findings of an SEJ exercise undertaken in 2018 via separate, 2-d workshops held in the United States and United Kingdom, involving 22 experts (hereafter SEJ2018). Details of how experts were selected are provided in SI Appendix, Note 1. The questions and format of the workshops were identical, so that the findings could be combined using an impartial weighting approach (Methods). SEJ (as opposed to other types of expert elicitation) weights each expert using objective estimates of their statistical accuracy and informativeness (22), determined using experts’ uncertainty evaluations over a set of seed questions from their field with ascertainable values (Methods). The approach is analogous to weighting climate models based on their skill in capturing a relevant property, such as the regional 20th century surface air temperature record (23). In SEJ, the synthetic expert (i.e., the performance weighted [PW] combination of all of the experts’ judgments) in general outperforms an equal weights (EW) combination in terms of statistical accuracy and informativeness, as illustrated in SI Appendix, Fig. S3. The approach is particularly effective at identifying those experts who are able to quantify their uncertainties with high statistical accuracy for specified problems rather than, for example, experts with restricted domains of knowledge or even high scientific reputation (12).
The participating experts quantified their uncertainties for three physical processes relevant to ice sheet mass balance: accumulation, discharge, and surface runoff. They did this for each of the Greenland, West Antarctic, and East Antarctic ice sheets (GrIS, WAIS, and EAIS, respectively), and for two schematic temperature change scenarios. The first temperature trajectory (denoted L) stabilized in 2100 at +2 °C above preindustrial global mean surface air temperature (defined as the average for 1850–1900), and the second (denoted H) stabilized at +5 °C (SI Appendix, Fig. S1). The experts generated values for four dates: 2050, 2100, 2200, and 2300. Experts also quantified the dependence between accumulation, runoff, and discharge within each of the three ice sheets, and between each ice sheet for discharge only, for the H scenario in 2100. We used temperature trajectories rather than emissions scenarios to isolate the experts’ judgements about the relationship between global mean surface air temperature change and ice sheet changes from judgements about climate sensitivity.
An important and unique element of SEJ2018 was the elicitation of intra- and inter-ice sheet dependencies (SI Appendix, Note 1.5). Two features of dependence were elicited: a central dependence and an upper tail dependence. The former captures the probability that one variable exceeds its median given that the other variable exceeds its median, whereas the latter captures the probability that one variable exceeds its 95th percentile given that the other exceeds its 95th percentile. It is well known that these two types of dependence are, in general, markedly different, a property that is not captured by the usual Gaussian dependence model. The latter always imposes tail independence, regardless of the degree of central dependence, and can produce large errors when applied inappropriately (24). For example, if GrIS discharge exceeds its 95th percentile, what is the probability that runoff will also exceed its 95th percentile? This probability may be substantially higher than the independent probability of 5%, and ignoring tail dependence may lead to underestimating the probability of high SLR contributions. On the basis of each expert’s responses, a joint distribution was constructed to capture the dependencies among runoff, accumulation, and discharge for GrIS, WAIS, and EAIS, with dependence structures chosen, per expert, to capture central and tail dependences (Methods and SI Appendix, Note 1.5). In BA13, heuristic dependency values were applied on the basis of simple assumptions about the response of processes to a common forcing.
To help interpret the findings, experts were also asked to provide qualitative and rank-order information on what they regard to be the leading processes that could influence ice dynamics and surface mass balance (snowfall minus ablation); henceforth, this is termed the descriptive rationale. Further details can be found in the SI Appendix. The combined sea-level contribution from all processes and ice sheets was determined assuming either independence or dependence. Here, we focus on the findings with dependence; we examine the effect of the elicited dependencies and the approach taken in SI Appendix, Note 1.5.
The ice sheet contributions were expressed as anomalies from the 2000–2010 mean states, which were predefined (SI Appendix, Table S7). The baseline sea-level contribution for this period was prescribed as 0.76 mm⋅y−1 (0.56, 0.20, and 0.00 mm⋅y−1 for GrIS, WAIS, and EAIS, respectively) and has been added to the elicited values discussed here. This is close to an observationally derived value of 0.79 mm⋅y−1 for the same period, which was published subsequently to the SEJ workshops (4).
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2018
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Heat waves (HWs) are among the most damaging climate extremes to human society. Climate models consistently project that HW frequency, severity, and duration will increase markedly over this century. For urban residents, the urban heat island (UHI) effect further exacerbates the heat stress resulting from HWs. Here we use a climate model to investigate the interactions between the UHI and HWs in 50 cities in the United States under current climate and future warming scenarios. We examine UHI2m (defined as urban-rural difference in 2m-height air temperature) and UHIs (defined as urban-rural difference in radiative surface temperature). Our results show significant sensitivity of the interaction between UHI and HWs to local background climate and warming scenarios. Sensitivity also differs between daytime and nighttime. During daytime, cities in the temperate climate region show significant synergistic effects between UHI and HWs in current climate, with an average of 0.4 K higher UHI2m or 2.8 K higher UHIs during HWs than during normal days. These synergistic effects, however, diminish in future warmer climates. In contrast, the daytime synergistic effects for cities in dry regions are insignificant in the current climate, but emerge in future climates. At night, the synergistic effects are similar across climate regions in the current climate, and are stronger in future climate scenarios. We use a biophysical factorization method to disentangle the mechanisms behind the interactions between UHI and HWs that explain the spatial-temporal patterns of the interactions. Results show that the difference in the increase of urban versus rural evaporation and enhanced anthropogenic heat emissions (air conditioning energy use) during HWs are key contributors to the synergistic effects during daytime. The contrast in water availability between urban and rural land plays an important role in determining the contribution of evaporation. At night, the enhanced release of stored and anthropogenic heat during HWs are the primary contributors to the synergistic eff
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The present study examines the lifetime evolution of outer tropical cyclone (TC) size and structure in the North Atlantic (NA) and western North Pacific (WNP). The metric for outer TC size is the radius at which the azimuthal-mean 10-m azimuthal wind equals 8 m s−1 (r8) derived from the NCEP Climate Forecast System Reanalysis (CFSR) and GFDL High-Resolution Forecast-Oriented Low Ocean Resolution model (HiFLOR). Radial profiles of the azimuthal-mean 10-m azimuthal wind are also analyzed to demonstrate that the results are robust across a broad range of wind radii. The analysis shows that most TCs in both basins are characterized by 1) minimum lifetime r8 at genesis, 2) subsequent substantial increases in r8 as the TC wind field expands, 3) peak r8 values occurring near or after the midpoint of the TC lifetime, and 4) nontrivial decreases in r8 and outer winds during the latter part of the TC lifetime. Compared to the NA, WNP TCs are systematically larger up until the end of their lifetime, exhibit r8 growth and decay rates that are larger in magnitude, and are characterized by an earlier onset of lifetime maximum r8 near their lifetime midpoint. In both basins, the TCs exhibiting the largest r8 increases are the longest lived, especially those that traverse the longest distances (i.e., recurving TCs). Finally, analysis of TCs undergoing extratropical transition (ET) shows that NA TCs exhibit negligible changes in r8 during ET, while WNP ET cases either show r8 decreases (CFSR) or negligible changes in r8 (HiFLOR).
Abstract
Sea-level rise (SLR) is magnifying the frequency and severity of extreme sea levels (ESLs) that can cause coastal flooding. The rate and amount of global mean sea-level (GMSL) rise is a function of the trajectory of global mean surface temperature (GMST). Therefore, temperature stabilization targets (e.g. 1.5 °C and 2.0 °C of warming above pre-industrial levels, as from the Paris Agreement) have important implications for coastal flood risk. Here, we assess, in a global network of tide gauges, the differences in the expected frequencies of ESLs between scenarios that stabilize GMST warming at 1.5 °C, 2.0 °C, and 2.5 °C above pre-industrial levels. We employ probabilistic, localized SLR projections and long-term hourly tide gauge records to estimate the expected frequencies of historical and future ESLs for the 21st and 22nd centuries. By 2100, under 1.5 °C, 2.0 °C, and 2.5 °C GMST stabilization, the median GMSL is projected to rise 48 cm (90% probability of 28–82 cm), 56 cm (28–96 cm), and 58 cm (37–93 cm), respectively. As an independent comparison, a semi-empirical sea level model calibrated to temperature and GMSL over the past two millennia estimates median GMSL rise within 7–8 cm of these projections. By 2150, relative to the 2.0 °C scenario and based on median sea level projections, GMST stabilization of 1.5 °C spares the inundation of lands currently home to about 5 million people, including 60 000 individuals currently residing in Small Island Developing States. We quantify projected changes to the expected frequency of historical 10-, 100-, and 500-year ESL events using frequency amplification factors that incorporate uncertainty in both local SLR and historical return periods of ESLs. By 2150, relative to a 2.0 °C scenario, the reduction in the frequency amplification of the historical 100 year ESL event arising from a 1.5 °C GMST stabilization is greatest in the eastern United States, with ESL event frequency amplification being reduced by about half at most tide gauges. In general, smaller reductions are projected for Small Island Developing States.
2017
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Greenland Ice Sheet (GIS) might have lost a large amount of its volume during the last interglacial and may do so again in the future due to climate warming. In this study, we test whether the climate response to the glacial meltwater is sensitive to its discharging location. Two fully coupled atmosphere–ocean general circulation models, CM2G and CM2M, which have completely different ocean components are employed to do the test. In each experiment, a prescribed freshwater flux of 0.1 Sv is discharged from one of the four locations around Greenland—Petermann, 79 North, Jacobshavn and Helheim glaciers. The results from both models show that the AMOC weakens more when the freshwater is discharged from the northern GIS (Petermann and 79 North) than when it is discharged from the southern GIS (Jacobshavn and Helheim), by 15% (CM2G) and 31% (CM2M) averaged over model year 50–300 (CM2G) and 70–300 (CM2M), respectively. This is due to easier access of the freshwater from northern GIS to the deepwater formation site in the Nordic Seas. In the long term (> 300 year), however, the AMOC change is nearly the same for freshwater discharged from any location of the GIS. The East Greenland current accelerates with time and eventually becomes significantly faster when the freshwater is discharged from the north than from the south. Therefore, freshwater from the north is transported efficiently towards the south first and then circulates back to the Nordic Seas, making its impact to the deepwater formation there similar to the freshwater discharged from the south. The results indicate that the details of the location of meltwater discharge matter if the short-term (< 300 years) climate response is concerned, but may not be critical if the long-term (> 300 years) climate response is focused upon.
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This study investigated how subsurface and atmospheric leakage from geologic CO2 storage reservoirs could impact the deployment of Carbon Capture and Storage (CCS) in the global energy system. The Leakage Risk Monetization Model was used to estimate the costs of leakage for representative CO2 injection scenarios, and these costs were incorporated into the Global Change Assessment Model. Worst-case scenarios of CO2 leakage risk, which assume that all leakage pathway permeabilities are extremely high, were simulated. Even with this extreme assumption, the associated costs of monitoring, treatment, containment, and remediation resulted in minor shifts in the global energy system. For example, the reduction in CCS deployment in the electricity sector was 3% for the “high” leakage scenario, with replacement coming from fossil fuel and biomass without CCS, nuclear power, and renewable energy. In other words, the impact on CCS deployment under a realistic leakage scenario is likely to be negligible. We also quantified how the resulting shifts will impact atmospheric CO2 concentrations. Under a carbon tax that achieves an atmospheric CO2 concentration of 480 ppm in 2100, technology shifts due to leakage costs would increase this concentration by less than 5 ppm. It is important to emphasize that this increase does not result from leaked CO2 that reaches the land surface, which is minimal due to secondary trapping in geologic strata above the storage reservoir. The overall conclusion is that leakage risks and associated costs will likely not interfere with the effectiveness of policies for climate change mitigation.
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Mechanisms such as ice‐shelf hydrofracturing and ice‐cliff collapse may rapidly increase discharge from marine‐based ice sheets. Here, we link a probabilistic framework for sea‐level projections to a small ensemble of Antarctic ice‐sheet (AIS) simulations incorporating these physical processes to explore their influence on global‐mean sea‐level (GMSL) and relative sea‐level (RSL). We compare the new projections to past results using expert assessment and structured expert elicitation about AIS changes. Under high greenhouse gas emissions (Representative Concentration Pathway [RCP] 8.5), median projected 21st century GMSL rise increases from 79 to 146 cm. Without protective measures, revised median RSL projections would by 2100 submerge land currently home to 153 million people, an increase of 44 million. The use of a physical model, rather than simple parameterizations assuming constant acceleration of ice loss, increases forcing sensitivity: overlap between the central 90% of simulations for 2100 for RCP 8.5 (93–243 cm) and RCP 2.6 (26–98 cm) is minimal. By 2300, the gap between median GMSL estimates for RCP 8.5 and RCP 2.6 reaches >10 m, with median RSL projections for RCP 8.5 jeopardizing land now occupied by 950 million people (versus 167 million for RCP 2.6). The minimal correlation between the contribution of AIS to GMSL by 2050 and that in 2100 and beyond implies current sea‐level observations cannot exclude future extreme outcomes. The sensitivity of post‐2050 projections to deeply uncertain physics highlights the need for robust decision and adaptive management frameworks.
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The Paris Agreement cemented a new framework for global climate policy based on the voluntary and non-legally binding emission reduction actions by both developed and developing countries. The building blocks strategy for climate action discussed in this Special Issue is well adapted to and strongly complements this new structure. Building blocks focus on multiple transnational mechanisms for mobilizing a wide range of both public and private actors to take actions that reduce emissions by capturing incentives other than climate mitigation as such. The initial commitments by countries under the Paris Agreement are insufficient to meet the level of action required to stabilize the global climate system at a safe level. As such, new voluntary action by public and private actors will be required. The building blocks strategy, and the examples presented in this Special Issue, offers answers to the question of how to generate and design smaller-scale initiatives.
The Paris Agreement cemented an entirely new framework for the global climate regime, one based on countries’ voluntary emissions limitation plans (nationally determined contributions or NDCs) and which includes participation by both developing and developed countries on a continuum of mitigation capability rather than a dichotomy. The previous framework, embodied in the principles of the UNFCCC and the Kyoto Protocol, aimed for universal agreement on economy-wide, binding, top-down quantitative targets and timetables for developed countries while excepting developing countries. Given the inherent difficulties in reaching international agreement under this approach (Stewart et al. 2013a), decomposition of climate policy into smaller problem-solving components was proposed as a crucial step toward effective global cooperation (Aldy and Stavins 2007; Victor 2011).
Despite the Paris Agreement being potentially the best agreement which could have been reached under the circumstances (Bodansky 2016), it is insufficiently ambitious to limit the global mean temperature increase to 2 °C (UNFCCC 2015)—additional climate action will be required. As the NDCs were supposedly the maximum that countries were able or willing to do individually, any additional action over the same period will be taken primarily by non-state actors or countries acting cooperatively in other contexts. And although there has been increased climate action by non-state actors, this has not happened at a convincing scale in the context of a 2 °C objective.
While the concept of bottom-up action on climate is not novel—it was much discussed during the lull in the international negotiations and international climate action in advance of Copenhagen (Aldy and Stavins 2007)—the Paris Agreement is novel in that it brings disaggregated bottom-up action into an international framework. Some climate negotiators have suggested that a focus on non-state actors will reduce the pressure on countries to fulfill their NDCs and to make more ambitious commitments in the future. Therefore, to be most effective, the additional action should seek to strengthen the international regime created in Paris.
This Special Issue is focused on how to incentivize this additional climate action through a building blocks strategy and to do so in a way that enhances the Paris Agreement. The building blocks strategy is a bottom-up strategy designed to create an array of smaller-scale, specialized initiatives for transnational cooperation in particular sectors and/or geographic areas with a wide range of participants—private sector, NGOs, international organizations, and subnational and local governments, as well as national governments. Key to the building blocks initiatives are a focus on the non-climate incentives of actions that also have a climate benefit. Such incentives include private economic benefits, reduction of local and regional air pollution, economic development and energy security for countries, and mission advancement for development funders.
The building blocks strategy provides not only a theory of action but also a template for designing these initiatives and offers suggestions on how to generate momentum to develop these initiatives. It can strengthen the Paris Agreement in three ways: (1) by providing additional climate action by state and non-state actors in the short term; (2) by understanding opportunities and costs of increased action, it can help countries to increase the ambition in subsequent NDCs; and (3) by developing transparency and monitoring systems in building blocks initiatives, they may provide best practices and examples for the development of similar systems under the Paris Agreement, which are currently thinly defined (Bodansky 2016).
In this introduction to the Special Issue, we first provide a summary of the theory of building blocks that we have developed in greater detail in several earlier publications (Stewart et al. 2013a, b, 2015). We articulate the specific institutional logics of the building blocks strategy—clubs, institutional linkages, and dominant market actors—providing examples of initiatives that follow these logics. As well, we introduce the other papers of the Special Issue, noting how they complement and extend the building blocks proposal. Finally, we discuss how the building blocks can enhance the Paris Agreement and how the Paris Agreement can, in turn, enhance the development and stability of building
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The reasons for concern framework communicates scientific understanding about risks in relation to varying levels of climate change. The framework, now a cornerstone of the IPCC assessments, aggregates global risks into five categories as a function of global mean temperature change. We review the framework’s conceptual basis and the risk judgments made in the most recent IPCC report, confirming those judgments in most cases in the light of more recent literature and identifying their limitations. We point to extensions of the framework that offer complementary climate change metrics to global mean temperature change and better account for possible changes in social and ecological system vulnerability. Further research should systematically evaluate risks under alternative scenarios of future climatic and societal conditions.
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2016
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While there is considerable interest in understanding the climate–migration relationship, particularly in the context of concerns about global climatic change, little is known about its underlying mechanisms. In the paper, we combine a rich panel data on annual bilateral international migration flows with an extensive data on climate variability across the countries to investigate in-depth the climate–migration link. We find a positive and statistically significant relationship between temperature and international outmigration only in the most agriculture-dependent countries, consistent with the widely documented adverse impact of temperature on agricultural productivity. Further, the temperature–migration relationship is nonlinear and resembles the nonlinear temperature–yield relationship. In addition, migration flows to current major destinations are especially temperature-sensitive. Policies to address issues related to climate-induced international migration would be more efficient if focused on the agriculture-dependent countries and especially people in those countries whose livelihoods depend on agriculture.
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