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Adaptation decision‐scientists increasingly use real‐option analysis to consider the value of learning about future climate variable development in adaptation decisions. Toward this end learning scenarios are needed, which are scenarios that provide information on future variable values seen not only from today (as static scenarios), but also seen from future moments in time. Decision‐scientists generally develop learning scenarios themselves, mostly through time‐independent (stationary) or highly simplified methods. The climate learning scenarios thus attained generally only poorly represent the uncertainties of state‐of‐the‐art climate science and thus may lead to biased decisions. This paper first motivates the need for learning scenarios by providing a simple example to illustrate characteristics and benefits of learning scenarios. Next, we analyze how well learning scenarios represent climate uncertainties in the context of sea level rise and present a novel method called direct fit to generate climate learning scenarios that outperforms existing methods. This is illustrated by quantifying the difference of the sea level rise learning scenarios created with both methods to the original underlying scenario. The direct fit method is based on pointwise probability distributions, for example, boxplots, and hence can be applied to static scenarios as well as ensemble trajectories. Furthermore, the direct fit method offers a much simpler process for generating learning scenarios from static or "ordinary" climate scenarios. Plain Language Summary: Many climate change adaptation decisions require large investments in infrastructure (e.g., dikes), while at the same time future projections about critical variables (e.g., sea level rise) are highly uncertain. Decision‐scientists address these challenges with methods based on flexibility and staged decision‐making. For example, a coastal decision‐maker could implement a dike with a wider foundation, and, if necessary, upgrade the dike height in the future. The decision‐maker will learn by observing future sea level rise if higher dike protection levels are actually necessary in the future. In order to assess whether it is economically beneficial to wait for future learning through observations, and thus to justify additional expenses for flexible infrastructure investments, learning scenarios are required. Learning scenarios provide projections of critical variables seen from today and from future moments in time. For example, learning scenarios of sea level rise contain sea level rise projections seen from 2050 onward, depending on a certain amount of sea level rise observed until 2050. In this paper, we provide a simple example to illustrate coastal decision‐making with a learning scenario, propose a new method to generate learning scenarios, and apply this method to generate sea level rise learning scenarios. Key Points: We show how climate learning scenarios can be applied for improving and justifying investments in flexible long‐lasting infrastructureWe develop sea level rise learning scenarios based on Intergovernmental Panel on Climate Change sixth Assessment Report using a novel method termed direct fitOur new method reduces the average deviation of learning scenarios from the original data by 83% compared to standard methods [ABSTRACT FROM AUTHOR]

Climate services are tools or products that aim to support climate‐informed decision making for the adaptation to climate change. The market for climate services is dominated by public institutions, despite the efforts made by the European Commission to increase private enterprise in the market. The business model perspective has been proposed as a framework for enabling market growth through the development of appropriate business models for the provision of climate services. However, there is a lack of structured knowledge on how to approach climate service design and development from a business model standpoint. In this contribution, we first analyze the role of stakeholders in the design and development of climate services and identify opportunities for engaging users in the creation process. Afterward, we explain our approach to climate service design and development using a business model perspective. To illustrate the proposed approach, we describe the co‐creation of a climate service to support the adaptation to climate change of the urban water supply system in Valencia, Spain, and discuss the main findings and lessons learned from applying this approach. Plain Language Summary: Climate services are customized products that support climate change adaptation. The uptake of climate services by users from the private sphere has been minimal during the last decade. Many reasons have been provided for this, but the main issue is the lack of communication between final users and developers during the design process. In this contribution, a business model perspective has been applied for the creation of climate services in order to bridge the gap between users and developers. Key Points: Climate services are the result of the combination of scientific and practice‐based knowledgeThis paper describes a method for the co‐creation of climate services using a business focus approachThe approach is applied to co‐design & co‐develop a climate service for the adaptation of the Valencia water supply system to climate change [ABSTRACT FROM AUTHOR]

As global mean sea level continues to rise, thresholds corresponding to coastal inundation impacts are exceeded more frequently. This paper aims to relate sea level rise (SLR) observations and projections to their physical on‐the‐ground impacts. Using a large coastal city as an example, we show that in Sydney, Australia, frequencies of minor coastal inundation have increased from 1.6 to 7.8 days per year between 1914 and present day. We attribute over 80% of the observed coastal inundation events between 1970 and 2015 to the predominantly anthropogenic increases in global mean sea level. Further, we find that impact‐producing coastal inundation will occur weekly by 2050 under high‐ and medium‐emission/SLR scenarios and daily by 2100 under high emissions. The proportion of tide‐only coastal inundation events (i.e., where no storm surge is required to exceed flood thresholds) will increase with SLR, such that most coastal inundation events, including those considered historically severe, will become a predictable consequence of SLR and astronomical tides. These findings are important for coastal managers as frequency, severity, and predictability of inundation impacts can all now be related to the amount of SLR (e.g., a planning allowance or SLR projection). By incorporating known historical inundation events, this allows contextualization, visualization, and localization of global SLR and the changing nature of future coastal inundation risk. Plain Language Summary: As sea levels rise, the daily highest tide reaches higher and further inland, and as a result, we see coastal flooding more frequently. Coastal flooding is when roads, carparks, walking paths, gardens, and, in more extreme cases, homes and businesses are impacted by high sea levels. Using Sydney, Australia, as an example, we find that most coastal flooding events we observe today would not have happened without human‐caused sea level rise. Further, coastal flooding is expected to occur in Sydney on average once per week by 2050 and every day by 2100 if high greenhouse gas emissions continue. In the past, the most severe coastal flooding impacts, such as flooding of main roads and private property, only occurred with large coastal storm events. However, we find that these severe floods will occur much more frequently as sea levels continue to rise, as they will eventually occur on the daily high tides. As the timing and heights of daily high tides are driven by the Sun, Moon, and the seasons, these severe coastal floods will become very predictable. This will have implications for the coastal and emergency managers tasked to deal with this changing risk. Key Points: We quantify the roles that tides and increasing mean sea level have on coastal inundation in Sydney, AustraliaFuture exceedances of current impact thresholds will be mainly tide driven, with minimal role for ocean, weather, and climate variabilityWe develop a framework for generating projections of the frequency and severity of coastal inundation impacts, to inform adaptation [ABSTRACT FROM AUTHOR]

The lack of capacity for climate change adaptation at the subnational level has been highlighted as a key barrier to implementing the UNFCCC National Adaptation Plans. At the same time, the adaptive capacity of local governance is highly context sensitive, making a "one‐size fits all" approach inappropriate. Thus, a versatile methodological approach for application in various local contexts is required. There are several indicator‐based local governance assessment methods for evaluating the effectiveness of local governance for climate change adaptation. However, they fall short of identifying and prioritizing between key factors within local governance for enhancing adaptive capacity and driving positive change. Building on adaptation theory, the authors propose combining two methodological approaches, the Capital Approach Framework for evaluating the adaptive capacity of local governance and Fuzzy Cognitive Mapping for identifying leverage points, into one integrated modeling approach, which can be applied by local researchers. This paper describes the process and benefits of combining the methodological approaches, with an example provided as supporting information. Assisting decision‐makers and policy planners from subnational governance in identifying leverage points to focus and maximize impact of capacity‐enhancing measures would make a key contribution for successful implementation of the UNFCCC National Adaptation Plans. Key Points: This research responds to the need for identifying clear pathways to enhance subnational capacity for climate change adaptationTwo research approaches have been combined, one for measuring the state of governance systems and one for identifying pathways [ABSTRACT FROM AUTHOR]

Despite increasing exposure to flooding and associated financial damages, estimates suggest more than two‐thirds of flood‐exposed properties are currently uninsured. This low adoption rate could undermine the climate resilience of communities and weaken the financial solvency of the United States National Flood Insurance Program. We study whether repeated exposure to flood events, especially the disaster‐scale floods that are expected to become more frequent in a warming climate, could spur insurance adoption. Using improved estimates of residential insurance take‐up in locations where such insurance is voluntary, and exploiting variation in the frequency and severity of flood events over time, we quantify how flood events impact local insurance demand. We find that a flood disaster declaration in a given year increases the take‐up rate of insurance by 7% in the following year, but that the effect diminishes in subsequent years and is gone after 5 years. This effect is more short‐lived in counties in inland states that do not border the Gulf and Atlantic coasts. We also find that the effect of a flood on take‐up is substantially larger if there was also a flood in the previous year, and that recent disasters are more salient for homeowners whose primary residences are exposed to a disaster declaration compared to non‐primary residences. Overall, these findings suggest that relying on households to self‐adapt to increasing flood risks in a changing climate is insufficient for closing the insurance protection gap. Plain Language Summary: Disaster‐scale floods are expected to become more frequent in a warming climate, impacting areas where insurance is not mandated. Many flood‐exposed properties are currently uninsured, potentially undermining the climate resilience of communities. We investigate whether households might adapt to the changing flood risk by purchasing and maintaining insurance over time. We find that while disaster‐scale floods increase insurance demand, this effect is temporary, even among counties experiencing consecutive disaster‐scale flood years. This effect is more salient among inland counties as well as among homeowners whose primary residence is exposed to a disaster‐scale flood. We conclude that relying on households to self‐adapt by maintaining insurance is insufficient for closing the insurance protection gap. Key Points: Increasing flood risk is impacting areas where flood insurance is not currently mandatedConsecutive disaster‐scale flood years increase insurance take‐up, but this effect diminishes over timeRelying on the autonomous adaptation of households will be insufficient for closing the insurance protection gap [ABSTRACT FROM AUTHOR]

Abstract: Transboundary river basins experience complex coordination challenges during droughts. The multiscale nature of drought creates potential for spillovers when upstream adaptation decisions have cascading impacts on downstream regions. This paper advances the institutional analysis and development (IAD) framework to examine drought adaptation decision‐making in a multijurisdictional context. We integrate concepts of risk management into the IAD framework to characterize drought across its natural and human dimensions. A global analysis identifies regions where severe droughts combine with institutional fragmentation to require coordinated adaptation. We apply the risk‐based IAD framework to examine drought adaptation in the Rio Bravo/Grande—an archetypical transboundary river shared by the United States and Mexico and by multiple states within each country. The analysis draws on primary data and a questionnaire with 50 water managers in four distinct, yet interlinked, “institutional catchments,” which vary in terms of their drought characteristics, socioeconomic attributes, and governance arrangements. The results highlight the heterogeneity of droughts and uneven distribution of their impacts due to the interplay of drought hazards and institutional fragmentation. Transboundary water sharing agreements influence the types and sequence of interactions between upstream and downstream jurisdictions, which we describe as spillovers that involve both conflict and cooperation. Interdependent jurisdictions often draw on informal decision‐making venues (e.g., data sharing, operational decisions) due to the higher transaction costs and uncertainty associated with courts and planning processes, yet existing coordination and conflict resolution venues have proven insufficient for severe, sustained droughts. Observatories will be needed to measure and manage the cascading risks of drought. [ABSTRACT FROM AUTHOR]

Climate change‐induced shifts in snow storage and snowmelt patterns pose risks for adverse impacts to people, the environment, and irrigated agriculture. Existing research primarily focuses on evaluating these risks to irrigated agriculture at large scales, overlooking the role of local context in shaping risk dynamics. Consequently, many "at‐risk" areas lack insight into how adaptation strategies for managing risk through water supply augmentation or water conservation vary across contexts and over time. To address this gap, we develop a comprehensive index for evaluating irrigated agriculture's risk and adaptation potential to changes in snow at local scales and apply it throughout the western US. Results confirm trends toward escalating risk for changes in snow storage and snowmelt patterns over the century. However, substantial heterogeneity in the extent and drivers of risk exists due to variability in localized interactions between declines in water supply (approximately −9% ± 13% by 2100) and increased agricultural demand (approximately 7% ± 5% by 2100). Despite an existing focus on supply augmentation as a critical adaptation strategy to reduce risk, we show its effectiveness diminishes for many areas over time, declining to an average of −54% of historical augmentation potential by 2100. Conserving water through historical changes in crop acreage and type emerges as a more stable adaptation measure, reducing demand by 7%–8% regardless of time. While particularly relevant for higher elevation, less intensive agricultural settings in snowmelt‐dependent regions, findings underscore the need for strategies that support local‐scale, context‐appropriate adaptation to effectively manage escalating risk as snow changes. Plain Language Summary: Climate change‐induced shifts in snow storage and snowmelt patterns threaten water supplies for irrigated agriculture, necessitating adaptation. In agriculture, adaptation requires balancing water supply and demand locally, which is often overlooked in larger‐scale analyses. We develop a framework for evaluating risk and adaptation at local scales in the agricultural sector and apply it to the western US, which is broadly at risk for adverse effects (i.e., physical harm, economic losses, and socio‐cultural damage) if water demand cannot be met. Changing snow dynamics negatively impact many local areas over time, although impacts can often be reduced through supply augmentation and water conservation. While the degree of risk and the effectiveness of these adaptation strategies vary across regions and time, increasing demand and supply volatility diminishes opportunities for supply augmentation. This trend underscores the importance of supporting context‐appropriate adaptations for agricultural communities facing increased risk to their water supplies. Key Points: Changes to snow storage and release patterns pose localized and heterogeneous risks to irrigated agriculture, which accelerate in the futurePotential to manage risk from less snow by augmenting water storage is limited by water supply‐demand imbalances in many locations over timeConserving water by reducing demand could buffer irrigated agriculture against increased risk even as augmentation potential diminishes [ABSTRACT FROM AUTHOR]

Flood losses have steadily increased in the past and are expected to grow even further owing to climate and socioeconomic change. The reduction of flood vulnerability, for example, through adaptation, plays a key role in the mitigation of future flood risk. However, lacking knowledge about vulnerability dynamics, which arise from the interaction between floods and the ensuing response by society, limits the scope of current risk projections. We present a socio‐hydrological method for flood risk assessment that simulates the interaction between society and flooding continuously, including changes in vulnerability through collective (structural) and private (non structural) measures. Our probabilistic approach quantifies uncertainties and exploits empirical data to chart risk dynamics including how society copes with flooding. In a case study for the commercial sector in Dresden, Germany, we show that increased adaptation is necessary to counteract the expected four‐fold growth in flood risk due to transient hydroclimatic and socioeconomic boundary conditions. We further use our holistic approach to identify solutions for effective long‐term adaptation, demonstrating that integrated adaptation strategies (i.e., combined structural and non structural measures) can reduce the average risk by up to 60% at the study site. Ultimately, our case study highlights the benefit of the model for robust flood risk assessment as it can capture unintended, adverse feedbacks of adaptation measures such as the levee effect. Consequently, our socio‐hydrological method contributes to a more systemic and reliable flood risk assessment that can inform adaptation planning by exploring the possible system evolutions comprehensively including unlikely futures. Plain Language Summary: The rise in flood losses due to climate and societal changes calls for effective strategies to reduce risks. Understanding how floods interact with society and affect vulnerability is crucial in addressing this challenge. However, current flood risk assessments lack this comprehensive insight. We have developed a novel method that integrates floods and society into a single model, enabling us to comprehend how society's vulnerability to floods changes over time. Our approach examines how communities respond to floods, considering both collective (like constructing levees) and private actions (such as individual property precautions). By factoring in uncertainties and utilizing real‐world data, we improve our understanding of societal flood adaptation. Using the commercial sector in Dresden, Germany, as a case study, we reveal a potential four‐fold increase in future flood risk due to climate and socioeconomic shifts. We propose a combination of collective and private measures, potentially reducing flood risk by up to 60% at the study site. In summary, our method is capable of simulating a wide range of potential futures and uncovering unforeseen challenges that may arise when societies attempt to shield themselves from floods. This aids in robust flood risk management and facilitates better planning for adaptation. Key Points: We present a socio‐hydrological model for continuous flood risk projection that captures vulnerability dynamics and quantifies uncertaintyOur case study highlights the need for effective adaptation to intensifying flood risk and the potential of integrated flood risk managementThe robust flood risk assessment method explores the possibility space comprehensively including adverse feedbacks such as the levee effect [ABSTRACT FROM AUTHOR]

Abstract Adaptation decision‐scientists increasingly use real‐option analysis to consider the value of learning about future climate variable development in adaptation decisions. Toward this end learning scenarios are needed, which are scenarios that provide information on future variable values seen not only from today (as static scenarios), but also seen from future moments in time. Decision‐scientists generally develop learning scenarios themselves, mostly through time‐independent (stationary) or highly simplified methods. The climate learning scenarios thus attained generally only poorly represent the uncertainties of state‐of‐the‐art climate science and thus may lead to biased decisions. This paper first motivates the need for learning scenarios by providing a simple example to illustrate characteristics and benefits of learning scenarios. Next, we analyze how well learning scenarios represent climate uncertainties in the context of sea level rise and present a novel method called direct fit to generate climate learning scenarios that outperforms existing methods. This is illustrated by quantifying the difference of the sea level rise learning scenarios created with both methods to the original underlying scenario. The direct fit method is based on pointwise probability distributions, for example, boxplots, and hence can be applied to static scenarios as well as ensemble trajectories. Furthermore, the direct fit method offers a much simpler process for generating learning scenarios from static or “ordinary” climate scenarios.

Simulations of crop yield due to climate change vary widely between models, locations, species, management strategies, and Representative Concentration Pathways (RCPs). To understand how climate and adaptation affects yield change, we developed a meta‐model based on 8703 site‐level process‐model simulations of yield with different future adaptation strategies and climate scenarios for maize, rice, wheat and soybean. We tested 10 statistical models, including some machine learning models, to predict the percentage change in projected future yield relative to the baseline period (2000–2010) as a function of explanatory variables related to adaptation strategy and climate change. We used the best model to produce global maps of yield change for the RCP4.5 scenario and identify the most influential variables affecting yield change using Shapley additive explanations. For most locations, adaptation was the most influential factor determining the projected yield change for maize, rice and wheat. Without adaptation under RCP4.5, all crops are expected to experience average global yield losses of 6%–21%. Adaptation alleviates this average projected loss by 1–13 percentage points. Maize was most responsive to adaptive practices with a projected mean yield loss of −21% [range across locations: −63%, +3.7%] without adaptation and −7.5% [range: −46%, +13%] with adaptation. For maize and rice, irrigation method and cultivar choice were the adaptation types predicted to most prevent large yield losses, respectively. When adaptation practices are applied, some areas are predicted to experience yield gains, especially at northern high latitudes. These results reveal the critical importance of implementing adequate adaptation strategies to mitigate the impact of climate change on crop yields. Plain Language Summary: Computer simulations are commonly used to predict how crop yield may change under future climate conditions and land management practices. For four major crops (maize, rice, wheat and soybean), we tested different statistical methods to synthesize thousands of computer simulations of crop yield change under future climate into one meta‐model which can be used to predict crop yield at any location where that crop is grown. We then predicted the change in crop yield under a likely future climate scenario (Representative Concentration Pathway 4.5) and identified which variables most explained the crop yield change. Considering both adaptive management status (whether or not adaptation practices were applied) and climate factors (average temperature, change in temperature, average precipitation, change in precipitation, CO2 concentration), we found that adaptation status was the most influential factor determining the predicted yield change for most crops. Managing cropland adaptively in the future can reduce predicted yield losses by 1–13 percentage points relative to maintaining the same management practices. We discuss which types of management practices may be the most useful for different crops, as well as which areas of the world are expected to gain or lose crop yield in the future. Key Points: Under future climate scenario Representative Concentration Pathway 4.5, average global yields of maize, rice, wheat, and soybean are projected to decrease by 6%–21%Implementing adaptive management practices could reduce this loss by 1–13 percentage points relative to maintaining the same practicesSome areas of the world, such as northern high latitudes, may see future yield increases if adaptation practices are applied [ABSTRACT FROM AUTHOR]

Adaptation is key to minimizing heatwaves' societal burden; however, our understanding of adaptation capacity across the socioeconomic spectrum is incomplete. We demonstrate that observed heatwave trends in the past four decades were most pronounced in the lowest‐quartile income region of the world resulting in >40% higher exposure from 2010 to 2019 compared to the highest‐quartile income region. Lower‐income regions have reduced adaptative capacity to warming, which compounds the impacts of higher heatwave exposure. We also show that individual contiguous heatwaves engulfed up to 2.5‐fold larger areas in the recent decade (2010–2019) as compared to the 1980s. Widespread heatwaves can overwhelm the power grid and nullify the electricity dependent adaptation efforts, with significant implications even in regions with higher adaption capacity. Furthermore, we compare projected global heatwave exposure using per‐capita gross domestic product as an indicator of adaptation capacity. Hypothesized rapid adaptation in high‐income regions yields limited changes in heatwave exposure through the 21st century. By contrast, lagged adaptation in the lower‐income region translates to escalating heatwave exposure and increased heat‐stress inequality. The lowest‐quartile income region is expected to experience 1.8‐ to 5‐fold higher heatwave exposure than each higher income region from 2060 to 2069. This inequality escalates by the end of the century, with the lowest‐quartile income region experiencing almost as much heatwave exposure as the three higher income regions combined from 2090 to 2099. Our results highlight the need for global investments in adaptation capabilities of low‐income countries to avoid major climate‐driven human disasters in the 21st century. Plain Language Summary: We show that heatwave exposure has disproportionately increased in the lowest‐income regions globally compared to the highest‐income regions over the past four decades. We also show that emerging heat hazards (e.g., shock heatwaves—the first heatwave of the season—and widespread contiguous extreme heat events) intensified in the past four decades and are expected to increase in the future across the globe, jeopardizing adaptation efforts even in wealthy countries. We use climate projections to evaluate future changes in heat‐stress inequality globally. In doing so, we incorporate the fact that high‐income countries have greater institutional and individual capacity to rapidly adapt to climate change than low‐income countries. Our findings demonstrate continued increases in heatwave exposure inequality because of delays in adaptation capacity in the developing world, compounded by a higher emergence of warming in low‐latitude areas where most of the low‐income countries occur. These results highlight the urgency to scale adaptation efforts in the low‐income regions to minimize heat‐stress inequality. Key Points: Heatwave exposure in the recent decade was >40% higher in the lowest‐quartile income region of the world than the highest‐quartileRapid adaptation capacity in higher‐income regions can buffer climate change‐driven increases in heatwave exposureLagged adaptation in the lower‐income regions translates to escalating impacts and increasing heat‐stress inequality [ABSTRACT FROM AUTHOR]

Increasing coastal flooding threatens urban centers worldwide. Projections of physical damages to structures and their contents can characterize the monetary scale of risk, but they lack relevant socioeconomic context. The impact of coastal flooding on communities hinges not only on the cost, but on the ability of households to pay for the damages. Here, we repurpose probabilistic risk assessment to analyze the monetary and social risk associated with coastal flooding in the San Francisco Bay Area for 2020–2060. We show that future coastal flooding could financially ruin a substantial number of households by burdening them with flood damage costs that exceed discretionary household income. We quantify these impacts at the census block group scale by computing the percentage of households without discretionary income, before and after coastal flooding costs. We find that for several coastal communities in San Mateo County more than 50% of households will be facing financial instability, highlighting the need for immediate policy interventions that target existing, socially produced risk rather than waiting for potentially elusive certainty in sea level rise projections. We emphasize that the percentage of financially unstable households is particularly high in racially diverse and historically disadvantaged communities, highlighting the connection between financial instability and inequity. While our estimates are specific to the San Francisco Bay Area, our granular, household‐level perspective is transferable to other urban centers and can help identify the specific challenges that different communities face and inform appropriate adaptation interventions. Plain Language Summary: Increasing coastal flooding threatens urban centers worldwide. Projections of physical damages to structures and their contents can characterize the monetary loss, but they lack relevant socioeconomic context. The impact of coastal flooding on communities hinges not only on the cost, but on the ability of households to pay for the damages. Here, we show that future coastal flooding could financially destabilize a substantial number of households by burdening them with flood damage costs that exceed discretionary funds that households have left over after covering costs of living. We compute the percentage of households without discretionary income, before and after projected coastal flooding costs. We demonstrate that this percentage is larger than 50% for several communities in San Mateo County, highlighting the need for immediate policy intervention that targets existing, socially produced risk rather than waiting for potentially elusive certainty in sea level rise projections. Across all flood‐affected census block groups in the County, we project increases in financial instability by an average of 17% from 2020 to 2060. This methodology is transferable to other urban centers and can help identify the specific challenges that different communities face and inform appropriate adaptation interventions. Key Points: We analyze the monetary and social risk associated with coastal flooding for communities in the San Francisco Bay Area over the coming decades, 2020–2060In some San Mateo County communities, existing financial strain and costs associated with future coastal flooding put more than half of households at risk of displacement or bankruptcyGreater certainty in sea level rise is not necessary to identify communities with high financial instability and design adaptation interventions [ABSTRACT FROM AUTHOR]

The need for explicitly considering equity in climate change adaptation planning is increasingly being recognized. However, evaluations of adaptation often adopt an aggregated perspective, while disaggregation of results is important to learn about who benefits when and where. A typical example is adaptation of rice agriculture in the Vietnam Mekong Delta (VMD). Efforts focused on flood protection have mainly benefitted large‐scale farmers while harming small‐scale farmers. To investigate the distributional consequences of adaptation policies in the VMD, we assess both aggregate total output and equity indicators, as well as disaggregated impacts in terms of district‐level farming profitability. Doing so requires an adequate representation of the multisectoral dynamics between the human and biophysical systems which influence farming profitability. We develop a spatially explicit integrated assessment model that couples inundation, sedimentation, soil fertility and nutrient dynamics, and behavioral land‐use change and farming profitability calculation. We find that inter‐district inequality responds in a non‐linear way to climatic and socio‐economic changes and choices of adaptation policies. The patterns of who wins and who loses could change substantially when a different policy is implemented or if a slightly different uncertain future materializes. We also find that there is no simple ranking of alternative adaptation policies, so one should make trade‐offs based on agreed preferences. Accounting for equity implies exploring the distribution of outcomes over different groups over a range of uncertain futures. Only by accounting for multisectoral dynamics can planners anticipate the equity consequences of adaptation and prepare additional measures to aid the worse‐off actors. Plain Language Summary: Adaptation planning should strive for not only maximizing welfare outcomes, but also ensuring equitable outcomes among affected people. Supporting equitable adaptation planning requires looking beyond only at aggregated indicators. In this study, we evaluate the distributional outcomes of alternative adaptation policies under various scenarios to the profitability of rice farming in the Vietnam Mekong Delta. To do this, we have to explicitly account for multisectoral dynamics surrounding the agriculture sector. This is because adaptation policies and uncertain factors target different parts of the systems and interact in a non‐linear way. Hence, if we zoom in to just one sector (e.g., flood impacts to farmer's profitability), we would overlook the inherent interconnectedness between the different sectors in the system. We therefore develop an integrated assessment model encompassing multiple sectors, including inundation and sedimentation dynamics, soil fertility and nutrient dynamics, and behavioral land‐use change and farming profitability. Using this model, we find that even a slight change in uncertain scenarios or implemented adaptation policies could lead to distinctive inequality patterns between farmers across the 23 districts. Our study suggests that to support an equitable adaptation planning, one must incorporate the complex multisectoral dynamics that give shape to inequalities. Key Points: Understanding who wins and who loses under different futures can help planners in anticipating and ameliorating future inequalitiesWe show how inequality patterns are sensitive to external uncertainties and adaptation policiesExploring inequality patterns requires accounting for multisectoral dynamics, which often has implications for the modeling choices [ABSTRACT FROM AUTHOR]

Coastal climate adaptation public works, such as storm surge barriers and levees, are central elements of several current proposals to limit damages from coastal storms and sea‐level rise in the United States. Academic analysis of these public works projects is dominated by technocratic and engineering‐driven frameworks. However, social conflict, laws, political incentives, governance structures, and other political factors have played pivotal roles in determining the fate of government‐led coastal flood risk reduction efforts. Here, we review the ways in which politics has enabled or hindered the conception, design, and implementation of coastal risk reduction projects in the U.S. We draw from the literature in natural hazards, infrastructure, political science, and climate adaptation and give supporting examples. Overall, we find that (1) multiple floods are often needed to elicit earnest planning; (2) strong and continuous leadership from elected officials is necessary to advance projects; (3) stakeholder participation during the design stage has improved outcomes; (4) legal challenges to procedural and substantive shortcomings under environmental protection statutes present an enduring obstacle to implementing megastructure proposals. Plain Language Summary: Major U.S. cities like New York, Boston, Norfolk, and Houston are investigating the use of storm surge barriers, levees, and other coastal flood protection megaprojects to limit damages from coastal storms and sea‐level rise. Determining the feasibility of such public works projects is largely dominated by technocratic and engineering‐driven frameworks (for example, benefit‐cost analysis). However, experience with similar public infrastructure and natural hazard preparedness projects suggests that social conflict and politics have been crucial in their conception, design, and implementation. In this review, we highlight the role of interest mobilization, political leadership, stakeholder participation, and legal challenges as a result of environmental protection laws in both creating and overcoming political obstacles. Better understanding the social and political factors that enable or hinder the implementation of storm surge barriers, levees, and other coastal flood protection megaprojects could encourage strategies and policies that are less likely to result in deadlocks, delays, or failure, thus saving valuable time and planning resources. Key Points: Social conflict and politics are crucial factors in the conception, design, and implementation of coastal flood protection megaprojectsPolitical incentives can hinder efforts to add adaptation works to government agendasEnvironmental protection laws, siting issues, and fragmented decision‐making add complexity to implementation [ABSTRACT FROM AUTHOR]

Abstract As global mean sea level continues to rise, thresholds corresponding to coastal inundation impacts are exceeded more frequently. This paper aims to relate sea level rise (SLR) observations and projections to their physical on‐the‐ground impacts. Using a large coastal city as an example, we show that in Sydney, Australia, frequencies of minor coastal inundation have increased from 1.6 to 7.8 days per year between 1914 and present day. We attribute over 80% of the observed coastal inundation events between 1970 and 2015 to the predominantly anthropogenic increases in global mean sea level. Further, we find that impact‐producing coastal inundation will occur weekly by 2050 under high‐ and medium‐emission/SLR scenarios and daily by 2100 under high emissions. The proportion of tide‐only coastal inundation events (i.e., where no storm surge is required to exceed flood thresholds) will increase with SLR, such that most coastal inundation events, including those considered historically severe, will become a predictable consequence of SLR and astronomical tides. These findings are important for coastal managers as frequency, severity, and predictability of inundation impacts can all now be related to the amount of SLR (e.g., a planning allowance or SLR projection). By incorporating known historical inundation events, this allows contextualization, visualization, and localization of global SLR and the changing nature of future coastal inundation risk.

Abstract The lack of capacity for climate change adaptation at the subnational level has been highlighted as a key barrier to implementing the UNFCCC National Adaptation Plans. At the same time, the adaptive capacity of local governance is highly context sensitive, making a “one‐size fits all” approach inappropriate. Thus, a versatile methodological approach for application in various local contexts is required. There are several indicator‐based local governance assessment methods for evaluating the effectiveness of local governance for climate change adaptation. However, they fall short of identifying and prioritizing between key factors within local governance for enhancing adaptive capacity and driving positive change. Building on adaptation theory, the authors propose combining two methodological approaches, the Capital Approach Framework for evaluating the adaptive capacity of local governance and Fuzzy Cognitive Mapping for identifying leverage points, into one integrated modeling approach, which can be applied by local researchers. This paper describes the process and benefits of combining the methodological approaches, with an example provided as supporting information. Assisting decision‐makers and policy planners from subnational governance in identifying leverage points to focus and maximize impact of capacity‐enhancing measures would make a key contribution for successful implementation of the UNFCCC National Adaptation Plans.

Abstract Transboundary river basins experience complex coordination challenges during droughts. The multiscale nature of drought creates potential for spillovers when upstream adaptation decisions have cascading impacts on downstream regions. This paper advances the institutional analysis and development (IAD) framework to examine drought adaptation decision‐making in a multijurisdictional context. We integrate concepts of risk management into the IAD framework to characterize drought across its natural and human dimensions. A global analysis identifies regions where severe droughts combine with institutional fragmentation to require coordinated adaptation. We apply the risk‐based IAD framework to examine drought adaptation in the Rio Bravo/Grande—an archetypical transboundary river shared by the United States and Mexico and by multiple states within each country. The analysis draws on primary data and a questionnaire with 50 water managers in four distinct, yet interlinked, “institutional catchments,” which vary in terms of their drought characteristics, socioeconomic attributes, and governance arrangements. The results highlight the heterogeneity of droughts and uneven distribution of their impacts due to the interplay of drought hazards and institutional fragmentation. Transboundary water sharing agreements influence the types and sequence of interactions between upstream and downstream jurisdictions, which we describe as spillovers that involve both conflict and cooperation. Interdependent jurisdictions often draw on informal decision‐making venues (e.g., data sharing, operational decisions) due to the higher transaction costs and uncertainty associated with courts and planning processes, yet existing coordination and conflict resolution venues have proven insufficient for severe, sustained droughts. Observatories will be needed to measure and manage the cascading risks of drought.

State and local governments, businesses, community organizations, and the general public are taking an increasingly significant role in climate impact assessment. Driven by impacts to constituents and customers and threats to human health, essential services, and property values, local organizations are on the front lines of responding to climate change. National and international efforts such as the U.S. National Climate Assessment and Intergovernmental Panel on Climate Change provide fundamental scientific understanding as well as methods and modeling tools. Subnational climate assessments can build on this foundation and tailor models and analyses to specific local or decision contexts. However, subnational climate assessment and adaptation presents new scientific and research challenges, such as those related to downscaling climate models, simulating extreme events, and understanding local values and institutional practices. As state, local, and sectoral assessments become more common across the nation, there is a critical opportunity to share learnings and identify challenges and pitfalls. Building off a National Academies of Sciences, Engineering, and Medicine activity focusing exclusively on subnational climate assessment, we consider the methods and results from a variety of examples to synthesize findings about current practices and the future of subnational climate assessment. Plain Language Summary: Climate assessments provide descriptions of the current and future impacts of climate change. Such assessments have long been a part of national and international activities on climate change. Increasingly, state and local governments, businesses, and other groups have begun climate assessments that address possible impacts from climate change specific to their constituents or customers. When taking national and international efforts to a local level, two important challenges arise. One is related to the challenge of applying science and modeling developed for the large scale to a smaller scale. The second is the need to translate technical analysis into usable information for decision makers and the public. Here we build off of a workshop convened by the National Academies of Sciences, Engineering, and Medicine to consider these issues. Key Points: State and local governments and others are taking an increasingly significant role in climate impact assessmentSuch assessments present analytical challenges from downscaling national models, simulating extremes, and integrating local perspectivesThe evolution of California's assessments, in its fourth iteration, reflects the demands for climate assessments to translate science into response activities [ABSTRACT FROM AUTHOR]

Enhancing the capacity of social‐ecological systems (SES) to adapt to climate change is of crucial importance. While gradual climate change impacts have been the main focus of much recent research, much less is known about how SES are impacted by climate extremes and how they adapt. Here, based on an advanced conceptualization of social‐ecological resilience, performed by an interdisciplinary group of scientists, we outline three major challenges for operationalizing the resilience concept with particular focus on climate extremes. First, we discuss the necessary steps required to identify and measure relevant variables for capturing the full response spectrum of the coupled social and ecological components of SES. Second, we examine how climate extreme impacts on coupling flows in SES can be quantified by learning from past societal transitions or adaptations to climate extremes and resulting changes in ecosystem service supply. Last, we explore how to identify management options for maintaining and enhancing social‐ecological resilience under a changing regime of climate extremes. We conclude that multiple pathways within adaptation and mitigation strategies which enhance the adaptive capacity of SES to absorb climate extremes will open the way toward a sustainable future. Plain Language Summary: Ecosystems and society are closely coupled and are both affected by climate change. Climate extremes are expected to occur more often and/or get more intense under climate change. We ask the following question: How can ecosystems and society, which can be described as so‐called social‐ecological systems, withstand climate extremes and can therefore become more resilient? To achieve this, we use the concept of social‐ecological resilience and identify three challenges that scientists, decision makers, and practitioners need to work on to improve the adaptive capacity of social‐ecological systems to climate extremes. We need to describe and measure the main drivers of climate extremes that impact ecosystems and society and those variables that describe the adaptive capacity and all possible responses of ecosystems and society. Ecosystems and society are coupled: Ecosystems provide ecosystem services to society, and society manages ecosystems. These coupling flows also change under the impact of climate extremes. We still do not fully understand how climate extremes impact these coupling flows or how they can be measured. Because society has influenced ecosystems for many centuries and millennia in many regions of the world, these coupling flows also often have a long history; as such we cannot expect ecosystems and society to adapt to climate extremes separately. We can learn about impacts from past extreme events to continuously improve the management of ecosystems and increase the adaptive capacity of social‐ecological systems. Such management options range from adaptations of land management to institutional practices which are often necessary in order to be useful in helping the affected region immediately after a climate extreme event. Key Points: Climate extremes impact the resilience of social‐ecological systems; their adaptation requires knowledge on ecological and social mechanismsRelevant ecological and social variables document the impact of climate extremes on the coupling flows, enabling management optionsThree challenges remain to advance our understanding on adapting social‐ecological systems for a resilient and sustainable future [ABSTRACT FROM AUTHOR]

Increasing temperature trends are expected to impact yields of major field crops by affecting various plant processes, such as phenology, growth, and evapotranspiration. However, future projections typically do not consider the effects of agronomic adaptation in farming practices. We use an ensemble of seven Global Gridded Crop Models to quantify the impacts and adaptation potential of field crops under increasing temperature up to 6 K, accounting for model uncertainty. We find that without adaptation, the dominant effect of temperature increase is to shorten the growing period and to reduce grain yields and production. We then test the potential of two agronomic measures to combat warming‐induced yield reduction: (i) use of cultivars with adjusted phenology to regain the reference growing period duration and (ii) conversion of rainfed systems to irrigated ones in order to alleviate the negative temperature effects that are mediated by crop evapotranspiration. We find that cultivar adaptation can fully compensate global production losses up to 2 K of temperature increase, with larger potentials in continental and temperate regions. Irrigation could also compensate production losses, but its potential is highest in arid regions, where irrigation expansion would be constrained by water scarcity. Moreover, we discuss that irrigation is not a true adaptation measure but rather an intensification strategy, as it equally increases production under any temperature level. In the tropics, even when introducing both adapted cultivars and irrigation, crop production declines already at moderate warming, making adaptation particularly challenging in these areas. Plain Language Summary: Global warming affects yields of grain crops, which are at the base of human diets. We use crop models to quantify its impacts on global crop production and to assess how adaptation could compensate for the adverse effects. We find that up to 2 K of increased temperature production can be maintained at the current level by using new cultivars, selected to maintain current growing period length under warming. Irrigation, as another management strategy, is shown to have the potential to increase yields in dry regions if water is available. However, models do not indicate that irrigation reduces the crops' sensitivity to warming. We find large differences in the yield response to warming and adaptation across climatic regions. While continental and temperate regions may benefit from higher temperatures but also show sizable adaptation potentials, tropical and arid regions show largest temperature impacts and smaller adaptation potentials. After all, these two crop management options appear effective to balance the effects of moderate warming but cannot fully compensate impacts above 2 K of warming. Key Points: Without agronomic adaptation, the dominant effect of temperature increase is to shorten growing periods and to reduce yields and productionAdaptation via cultivars that maintain current growing periods under warming can compensate global production losses up to 2 KIrrigation would act as intensification rather than true adaptation, as it hardly affects the sensitivity of crop yields to warming [ABSTRACT FROM AUTHOR]

Sea‐level rise sits at the frontier of usable climate climate change research, because it involves natural and human systems with long lags, irreversible losses, and deep uncertainty. For example, many of the measures to adapt to sea‐level rise involve infrastructure and land‐use decisions, which can have multigenerational lifetimes and will further influence responses in both natural and human systems. Thus, sea‐level science has increasingly grappled with the implications of (1) deep uncertainty in future climate system projections, particularly of human emissions and ice sheet dynamics; (2) the overlay of slow trends and high‐frequency variability (e.g., tides and storms) that give rise to many of the most relevant impacts; (3) the effects of changing sea level on the physical exposure and vulnerability of ecological and socioeconomic systems; and (4) the challenges of engaging stakeholder communities with the scientific process in a way that genuinely increases the utility of the science for adaptation decision making. Much fundamental climate system research remains to be done, but many of the most critical issues sit at the intersection of natural sciences, social sciences, engineering, decision science, and political economy. Addressing these issues demands a better understanding of the coupled interactions of mean and extreme sea levels, coastal geomorphology, economics, and migration; decision‐first approaches that identify and focus research upon those scientific uncertainties most relevant to concrete adaptation choices; and a political economy that allows usable science to become used science. Plain Language Summary: The impacts of sea‐level rise pose growing threats to coastal communities, economies, and ecosystems, and decisions made today—in areas like land‐use policies, coastal development, and infrastructure investment—will affect exposure and vulnerability for generations to come. Thus, the usability of sea‐level science is a pressing concern. Ensuring usability requires grappling with deep uncertainty in long‐term sea‐level projections, the relationship between long‐term trends and the impacts of short‐lived extreme events, and the ways in which the physical coast, as well as people and ecosystems along the coast, respond to increasingly frequent flooding. At the same time, it also requires more extensive and deliberate stakeholder engagement throughout the scientific process, as well as cognizance of the political economy of linking stakeholder‐engaged science to action. Key Points: Understanding coastal evolution requires accounting for interactions of sea‐level change, geomorphology, socioeconomics, and human responsesDeep uncertainty in sea‐level rise projections and impacts exists on timescales relevant to infrastructure and planning decisionsAdaptation under deep uncertainty requires co‐production, iterative risk management, and awareness of political economy [ABSTRACT FROM AUTHOR]

Population growth and climate change will combine to pose substantial challenges for water management in the United States. Projections of water supply and demand over the 21st century show that in the absence of further adaptation efforts, serious water shortages are likely in some regions. Continued improvements in water use efficiency are likely but will be insufficient to avoid future shortages. Some adaptation measures that have been effective in the past, most importantly large additions to reservoir storage, have little promise. Other major adaptations commonly used in the past, especially instream flow removals and groundwater mining, can substantially lower shortages but have serious external costs. If those costs are to be avoided, transfers from irrigated agriculture probably will be needed and could be substantial. Plain Language Summary: This study estimates the likelihood of water shortages over the remainder of the 21st century in 204 watersheds covering the contiguous United States. The estimates are based on monthly projections of water demand and renewable water supply in light of population growth and climate change, taking into account water storage and transbasin diversion capacities. The study then examines several possible adaptations to projected shortages, including water withdrawal efficiency improvements, reservoir storage enhancements, demand reductions, instream flow reductions, and groundwater depletions. Results provide a broad measure of the relative efficacy of the adaptation measures and show when and where the measures are likely to be helpful. Key Points: Climate change and population growth will combine to increase the likelihood of water shortages in many areas of the United StatesExpected improvements in water use efficiency will be insufficient to avoid impending water shortagesReductions in agricultural irrigation will be essential to contain shortages in other water use sectors and avoid excess groundwater drawdown or environmental flow losses [ABSTRACT FROM AUTHOR]

Private precaution is an important component in contemporary flood risk management and climate adaptation. However, quantitative knowledge about vulnerability reduction via private precautionary measures is scarce and their effects are hardly considered in loss modeling and risk assessments. However, this is a prerequisite to enable temporally dynamic flood damage and risk modeling, and thus the evaluation of risk management and adaptation strategies. To quantify the average reduction in vulnerability of residential buildings via private precaution empirical vulnerability data (n = 948) is used. Households with and without precautionary measures undertaken before the flood event are classified into treatment and nontreatment groups and matched. Postmatching regression is used to quantify the treatment effect. Additionally, we test state‐of‐the‐art flood loss models regarding their capability to capture this difference in vulnerability. The estimated average treatment effect of implementing private precaution is between 11 and 15 thousand EUR per household, confirming the significant effectiveness of private precautionary measures in reducing flood vulnerability. From all tested flood loss models, the expert Bayesian network‐based model BN‐FLEMOps and the rule‐based loss model FLEMOps perform best in capturing the difference in vulnerability due to private precaution. Thus, the use of such loss models is suggested for flood risk assessments to effectively support evaluations and decision making for adaptable flood risk management. Plain Language Summary: Private precautionary measures such as adapted building use, sealing basements and purchasing flood barriers reduce flood damage to residential buildings. Using an empirical dataset consisting of 948 flooded households in Germany, we estimate that the average loss reducing effect of implementing private precautionary measures is 11‐15 thousand EUR per household. This is approximately equal to 27% of the average building loss suffered by the flooded households (48000 EUR). Despite this significant risk mitigation effect, these precautionary measures are hardly considered in flood risk assessment modelling. This results in biased flood loss predictions being used for evaluating risk management strategies. Hence, we compare state‐of‐the‐art flood loss models in respect to their ability to account for building loss reduction due to private precaution. From all tested flood loss models, the expert Bayesian Network based model BN‐FLEMOps and the rule‐based loss model FLEMOps are best able to capture the damage reducing effect of private precaution. These models can be valuable for evaluating adaptable flood risk management strategies. Key Points: Private precaution significantly reduces the flood vulnerability of private households as shown by robust empirical matching methodsState‐of‐the‐art flood damage models differ strongly based on their ability to capture differences in vulnerability of private householdsMethodology applied and validated using an extensive object‐level flood damage data set from Germany [ABSTRACT FROM AUTHOR]

Climate change increases workers' exposure to heat stress. To prevent heat‐related illnesses, according to occupational‐health recommendations, labor capacity must be reduced. However, this preventive measure is expected to be costly, and the costs are likely to rise as the scale and scope of climate change impacts increase over time. Shifting the start of the working day to earlier in the morning could be an effective adaptation measure for avoiding the impacts of labor capacity reduction. However, the plausibility and efficacy of such an intervention have never been quantitatively assessed. Here we investigate whether working time shifts can offset the economic impacts of labor capacity reduction due to climate change. Incorporating a temporally (1 hr) and spatially (0.5° × 0.5°) high‐resolution heat exposure index into an integrated assessment model, we calculated the working time shift necessary to offset labor capacity reduction and economic loss under hypothetical with‐ and without‐realistic‐adaptation scenarios. The results of a normative scenario analysis indicated that a global average shift of 5.7 (4.0–6.1) hours is required, assuming extreme climate conditions in the 2090s. Although a realistic (<3 hr) shift nearly halves the economic cost, a substantial cost corresponding to 1.6% (1.0–2.4%) of global total gross domestic product is expected to remain. In contrast, if stringent climate‐change mitigation is achieved, a realistic shift limits the remaining cost to 0.14% (0.12–0.47%) of global total gross domestic product. Although shifting working time is shown to be effective as an adaptation measure, climate‐change mitigation remains indispensable to minimize the impact. Plain Language Summary: Outdoor workers are exposed to excessive heat stress particularly in hot seasons and its impact is expected to increase as a result of climate change. This will reduce the capability of labor and eventually cause economic loss. Shifting working time to earlier morning, when it is cooler than during midday, can be an effective way to reduce the effect of heat stress. In this study, we investigated the effectiveness and plausibility of a working time shift as an adaptation measure to climate change. Although a working time shift was shown to be effective to reduce the effect of heat stress, the required amount of shift was beyond the realistic range unless stringent climate‐change mitigation was achieved. If society tries to avoid the economic impacts of climate change on outdoor labor only by working time shifts, outdoor workers in many regions will need to start working well before dawn. Climate‐change mitigation and other adaptation measures (e.g., mechanization of work, body cooling, etc.) are also inevitable to minimize the impact of climate change. Key Points: Increased heat exposure due to climate change will reduce labor capacityEfficacy and plausibility of working time shift as an adaptation measure to avoid heat stress is evaluatedWorking time shift is insufficient to offset the impact without stringent climate‐change mitigation [ABSTRACT FROM AUTHOR]

Abstract: Most existing coastal climate‐adaptation planning processes, and the research supporting them, tightly focus on how to use land use planning, policy tools, and infrastructure spending to reduce risks from rising seas and changing storm conditions. While central to community response to sea level rise, we argue that the exclusive nature of this focus biases against and delays decisions to take more discontinuous, yet proactive, actions to adapt—for example, relocation and aggressive individual protection investments. Public policies should anticipate real estate market responses to risk reduction to avoid large costs—social and financial—when and if sea level rise and other climate‐related factors elevate the risks to such high levels that discontinuous responses become the least bad alternative. [ABSTRACT FROM AUTHOR]

Abstract: With minimal moral hazard and adverse selection, weather index insurance promises financial resilience to farmers struck by harsh weather conditions through swift compensation at affordable premium. Despite these advantages, the very nature of indexing gives rise to production basis risk as the selected weather indexes do not sufficiently correspond to actual damages. To address this problem, we develop a stochastic yield model, built upon a stochastic soil moisture model driven by marked Poisson rainfall. Our analysis shows that even under similar temperature and rainfall amount yields can differ significantly; this was empirically supported by a 2‐year field experiment in which rain‐fed maize was grown under very similar total rainfall. Here, the year with more intense, less‐frequent rainfall produces a better yield—a rare counter evidence to most climate change projections. Through a stochastic yield model, we demonstrate the crucial roles of rainfall intensity and frequency in determining the yield. Importantly, the model allows us to compute rainfall pattern‐related basis risk inherent in cumulative rain index insurance. The model results and a case study herein clearly show that total rainfall is a poor indicator of yield, imposing unnecessary production basis risk on farmers and false‐positive payouts on insurers. Incorporating rainfall intensity and frequency in the design of rain index insurance can offer farmers better protection, while maintaining the attractive features of the weather index insurance and thus fulfilling its promise of financial resilience. [ABSTRACT FROM AUTHOR]

We combine socioeconomic data from a large-scale household survey with historical climate data to map the climate sensitivity of availability and access dimensions of food security in Mali, and infer the ways in which at-risk communities may have been impacted by persistent climatic shift. Thirty years after 1982-1984, the period of most intense drought during the protracted late 20th century drying of the Sahel, the impact of drought on livelihoods and food security is still recognizable in the Sahelian center of Mali. This impact is expressed in the larger fraction of households in this Sahelian center of the country-the agro-ecological transition between pastoralism in the north, and sedentary agriculture in the south-who practice agriculture but not livestock raising, despite environmental conditions that are suitable to their combination. These households have lower food security and rely more frequently on detrimental nutrition-based coping strategies, such as reducing the quantity or quality of meals. In contrast, the more food secure households show a clear tendency toward livelihood diversification away from subsistence agriculture. These households produce less of what they consume, yet spend less on food in proportion. The analysis points to the value of interdisciplinary research-in this case bridging climate science and vulnerability analysis-to gain a dynamical understanding of complex systems, understanding which may be exploited to address real-world challenges, offering lessons about food security and local adaptation strategies in places among the most vulnerable to climate. [ABSTRACT FROM AUTHOR]