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The disaster risk community has notably shifted from a response-driven approach to making informed anticipatory action choices through impact-based forecasting (IBF). Algorithms are being developed and improved to increase impact prediction abilities, and to allow automatic triggers to reduce the reliance on human judgement. However, as complexities in modelling algorithms increase, it becomes more difficult for decision makers to interpret and explain the results. This reduces the accountability and transparency, and can lead to lower adoption of the models. Therefore, humanitarian decision-makers can benefit from a mechanism to evaluate different IBF approaches, which has not yet been developed. Through a case study of anticipatory action for tropical cyclones in the Philippines, we evaluated two very different approaches to IBF: (1) a statistical trigger model that uses a machine learning algorithm with several predictor variables, and (2) an elementary trigger model that combines damage curves and weighted overlay of vulnerability indicators, to predict the impact and prioritize areas for intervention. The models were evaluated based on their performance for damage prediction and their sensitivity to different risk indicators for Typhoon Kammuri (2019) in the Philippines. The study also proposed a way of characterising the explainability specific to an IBF model, and that gives clarity on which elements, and why, influence the results, done via a model card. To facilitate this process a prototype interactive decision portal was built, which shows decision makers the sensitivity of the results to variations in input parameters. The results show that in relative terms the elementary model performed better and would have allowed to maximise impact reduction through early action, suggesting that, for this particular case, complex was not necessarily a better choice. However, the uncertainty in both models due to limitations in the initial hazard forecast indicates that multiple models need to be evaluated for practical cases that cover different characteristics of the hazard and socio-vulnerable situations. For this, the evaluation framework we developed can be expanded across operational IBF projects.

In the face of climate change, development and humanitarian practitioners increasingly recognize the need to anticipate and manage multiple, concurrent risks. One prominent example of this increasing focus on anticipation is the rapid growth of Forecast-based Financing (FbF), in particular within Red Cross and Red Crescent (RCRC). To evaluate how anticipatory efforts managed multiple compounding risks during the COVID-19 pandemic, we examine how 14 RCRC Societies adapted their Early Action Protocols to COVID-19. Though many National Societies successfully adapted to the onset of the additional hazard of COVID-19, we find that multi-hazard risk management can be improved by: proactively developing guidelines that enable rapid adaptation of existing plans; more flexible funding mechanisms; surge capacity to provide additional human resources; and increasing local capacity and ownership for implementation to ensure supplies, skills, and decision-making authority are available when communication or travel is restricted. These findings align with wider recommendations for improving development, humanitarian, and climate adaptation practice towards local capacity and agency. They also add urgency to broader calls for more flexible disaster financing and more practitioner-oriented investment in climate risk and multi-hazard management.

Roundtable on Compound Hazards and COVID-19 What: An online panel with leading experts in compound hazard research, preparedness, and response, attended by over 80 online participants, met to discuss hazard response in the context of COVID-19. When: 30 June 2021 Where: Online, convened by the World Meteorological Organization and hosted by the American Geophysical Union Peer Reviewed "Article signat per 12 autors/es: Benjamin F. Zaitchik, Judy Omumbo, Rachel Lowe, Maarten van Aalst, Liana O. Anderson, Erich Fischer, Charlotte Norman, Joanne Robbins, Rosa Barciela, Juli Trtanj, Rosa von Borries, and Jürg Luterbacher"

Armed conflict increases people's vulnerability to climate extremes. Since many of these climate extremes are predictable beforehand, Early Warning Early Action (EWEA) can help protect people's lives, livelihoods, and wellbeing. While such EWEA systems exist in several countries, there is limited scientific knowledge about EWEA in conflict-affected countries where communities experience the compounding effects of both disaster and conflict risks. By doing a retrospective analysis of the most severe disaster events and historical forecast information, this paper examines whether global forecast models predicted historical floods in conflict-affected regions and whether forecast information was communicated for droughts. It analyses the historical forecast availability and communication for the most severe disaster events in 20 countries affected by protracted conflict over the last 20 years. These 72 disaster events were reported to affect approximately 150 million individuals and more than 150,000 were reported dead. The results show that heavy rainfall was predicted in advance for 48 out of 50 flood events, with lead times of more than three days and probabilities between 10 and 90%. In addition, in 16 out of 20 major drought events a low rainfall forecast was communicated in advance of the disaster declaration. We conclude that forecasts exist and could be used to provide early warnings in conflict-affected areas. Further research is needed as to what extent forecast warnings did lead to early action to protect populations affected by conflict.

Summary Growing evidence suggests that climate adaptation responses that do not incorporate equity considerations may worsen inequality and increase vulnerability. Using data from a systematic review of peer-reviewed empirical research on adaptation responses to climate change (n = 1,682), we present an assessment of how social equity is considered in adaptation across regions, sectors, and social groups. Roughly 60% of peer-reviewed literature on adaptation responses considers social equity by reporting on which marginalized groups were involved in planning or implementation. Articles on responses in Africa and Asia and those focusing on poverty reduction most frequently considered social equity. Equity was less likely to be considered in adaptation responses in Europe, Australasia, and North America, as well as in literature focused on cities. Income-based inequity was more frequently considered than gender, age, or Indigenous status. Ethnic and racial minorities, migrants, and people with disabilities were rarely considered. Attention to the levels and forms in which equity is integrated into adaptation research and practice is needed to ensure just adaptation.

The Intergovernmental Panel on Climate Change (IPCC) reports provide policy-relevant insights about climate impacts, vulnerabilities and adaptation through a process of peer-reviewed literature assessments underpinned by expert judgement. An iconic output from these assessments is the burning embers diagram, first used in the Third Assessment Report to visualize reasons for concern, which aggregate climate-change-related impacts and risks to various systems and sectors. These burning embers use colour transitions to show changes in the assessed level of risk to humans and ecosystems as a function of global mean temperature. In this Review, we outline the history and evolution of the burning embers and associated reasons for concern framework, focusing on the methodological approaches and advances. While the assessment framework and figure design have been broadly retained over time, refinements in methodology have occurred, including the consideration of different risks, use of confidence statements, more formalized protocols and standardized metrics. Comparison across reports reveals that the risk level at a given temperature has generally increased with each assessment cycle, reflecting accumulating scientific evidence. For future assessments, an explicit, transparent and systematic process of expert elicitation is needed to enhance comparability, quality and credibility of burning embers.

Southern Madagascar recently experienced a severe food security crisis, made significantly worse by well below average rainfall from July 2019 to June 2021. This exceptional drought has affected a region with high pre-existing levels of vulnerability to food insecurity (subsistence agriculture and pastoralism in the region is rain-fed only), while impacts have been compounded further by COVID-19 restrictions and pest infestations. The rainy seasons of both 2019/20 and 2020/21 saw just 60% of normal rainfall across the Grand South region and was estimated as a 1-in-135 year dry event, only surpassed in severity by the devastating drought of 1990–92. Based on a combination of observations and climate modelling, the likelihood of experiencing such poor rains in the region was not significantly increased due to human-caused climate change: while the observations and models combine to indicate a small shift toward more droughts like the 2019–2021 event as a consequence of climate change, these trends remain overwhelmed by natural variability. This result is consistent with previous research, with the Intergovernmental Panel on Climate Change (IPCC)’s Sixth Assessment Report concluding that any perceptible changes in drought will only emerge in this region if global mean temperatures exceed 2 °C above pre-industrial levels.

Towards the end of June 2021, temperature records were broken by several degrees Celsius in several cities in the Pacific northwest areas of the U.S. and Canada, leading to spikes in sudden deaths, and sharp increases in hospital visits for heat-related illnesses and emergency calls. Here we present a multi-model, multi-method attribution analysis to investigate to what extent human-induced climate change has influenced the probability and intensity of extreme heatwaves in this region. Based on observations and modeling, the occurrence of a heatwave with maximum daily temperatures (TXx) as observed in the area 45° N–52° N, 119° W–123° W, was found to be virtually impossible without human-caused climate change. The observed temperatures were so extreme that they lie far outside the range of historically observed temperatures. This makes it hard to quantify with confidence how rare the event was. In the most realistic statistical analysis, which uses the assumption that the heatwave was a very low probability event that was not caused by new nonlinearities, the event is estimated to be about a 1 in 1000 year event in today’s climate. With this assumption and combining the results from the analysis of climate models and weather observations, an event, defined as daily maximum temperatures (TXx) in the heatwave region, as rare as 1 in a 1000 years would have been at least 150 times rarer without human-induced climate change. Also, this heatwave was about 2 °C hotter than a 1 in 1000-year heatwave that at the beginning of the industrial revolution would have been (when global mean temperatures were 1.2 °C cooler than today). Looking into the future, in a world with 2 °C of global warming (0.8 °C warmer than today), a 1000-year event would be another degree hotter. It would occur roughly every 5 to 10 years in such global warming conditions. Our results provide a strong warning: our rapidly warming climate is bringing us into uncharted territory with significant consequences for health, well-being, and livelihoods. Adaptation and mitigation are urgently needed to prepare societies for a very different future.

Weather forecasts, climate change projections, and epidemiological predictions all represent domains that are using forecast data to take early action for risk management. However, the methods and applications of the modeling efforts in each of these three fields have been developed and applied with little cross-fertilization. This perspective identifies best practices in each domain that can be adopted by the others, which can be used to inform each field separately as well as to facilitate a more effective combined use for the management of compound and evolving risks. In light of increased attention to predictive modeling during the COVID-19 pandemic, we identify three major areas that all three of these modeling fields should prioritize for future investment and improvement: (1) decision support, (2) conveying uncertainty, and (3) capturing vulnerability. E Stephens and E Coughlan de Perez acknowledge support from the UK’s Natural Environment Research Council (NERC) and Foreign, Commonwealth and Development Office through the FATHUM (Forecasts for AnTicipatory HUManitarian action, grant number NE/P000525/1) project, part of the Science for Humanitarian Emergencies and Resilience (SHEAR) research programme. R Lowe was supported by a Royal Society Dorothy Hodgkin Fellowship. S Funk is funded by the Wellcome Trust (210758/Z/18/Z).

This panel discussion will seek to identify clear, near-term scientific messages on adaptation opportunities for the COP26 Adaptation and Resilience Theme priority. The session will address key questions such as: - What would you like to see in the CoP26 settlement to enhance capacity for adaptation nationally and internationally? - What would you like to see in the CoP26 settlement to realise the opportunity adaptation has for combating poverty nationally and internationally? - Can COVID-19 impacts on society and economy, and renewal investment plans be an opportunity to help focus the poverty alleviating opportunity of adaptation? - How might research funding and practice best enable innovative, pro-poor adaptation?

Extreme heat events impact people and ecosystems across the globe, and they are becoming more frequent and intense in a warming climate. Responses to heat span sectors and geographic boundaries. Prior research has documented technologies or options that can be deployed to manage extreme heat and examples of how individuals, communities, governments, and other stakeholder groups are adapting to heat. However, a comprehensive understanding of the current state of implemented heat adaptations—where, why, how, and to what extent they are occurring—has not been established. Here, we combine data from the Global Adaptation Mapping Initiative with a heat-specific systematic review to analyze the global extent and diversity of documented heat adaptation actions (n = 301 peer-reviewed articles). Data from 98 countries suggest that documented heat adaptations fundamentally differ by geographic region and national income. In high-income, developed countries, heat is overwhelmingly treated as a health issue, particularly in urban areas. However, in low and middle income, developing countries, heat adaptations focus on agricultural and livelihood-based impacts, primarily considering heat as a compound hazard with drought and other hydrological hazards. 63% of the heat-adaptation articles feature individuals or communities autonomously adapting, highlighting how responses to date have largely consisted of coping strategies. The current global status of responses to intensifying extreme heat, largely autonomous and incremental yet widespread, establishes a foundation for informed decision making as heat impacts around the world continue to increase.

East Africa experiences chronic food insecurity, with levels varying from year-to-year across the region. Given that much can be done to prevent this level of suffering before it happens, humanitarian agencies monitor early indicators of food insecurity to trigger early action. Forecasts of total seasonal rainfall are one tool used to monitor and anticipate food security outcomes. Factors beyond rainfall, such as conflict, are key determinants of whether lack of rainfall can become a problem. In this paper, we present a quantitative analysis that isolates the value of rainfall information in anticipating food security outcomes across livelihood groups in East Africa. Comparing observed rainfall and temperature with food security classifications, we quantify how much the chance of food insecurity increases when rainfall is low. Results differed dramatically among livelihood groups; pastoralists in East Africa more frequently experience food insecurity than do non-pastoralists, and 12 months of low rainfall greatly increases the chances of “crisis” and “emergency” food security in pastoralist regions. In non-pastoralist regions, the relationship with total rainfall is not as strong. Similar results were obtained for livelihood groups in Kenya and Ethiopia, with slightly differing results in Somalia. Given this, we evaluated the relevance of monitoring and forecasting seasonal total rainfall. Our quantitative results demonstrate that six months of rainfall observations can already indicate a heightened risk of food insecurity, a full six months before conditions deteriorate. Combining rainfall observations with seasonal forecasts can further change the range of possible outcomes to indicate higher or lower risk of food insecurity, but the added value of seasonal forecasts is noticeable only when they show a strong probability of below-normal rainfall.

In April 2017, over 70 scientists, policymakers and practitioners from 32 countries convened at the International Conference on Climate Risk Management in Nairobi, Kenya. This conference utilized innovative approaches to facilitate a process of constructive, critical reflection of the existing climate risk management knowledge base, as well as its relevance to decision-maker needs and views of the most vulnerable people. The conference articulated recommendations to the Intergovernmental Panel on Climate Change (IPCC) in the development of their Sixth Assessment Report (AR6)–in support of the Chair’s vision for AR6 to have a strong focus on solutions. This report highlights key recommendations distilled from these discussions in areas such as risk-framing approaches and risk metrics. The meeting also suggested that the next IPCC assessment could be strengthened by stronger interaction with practitioners and policymakers working at the forefront of implementing global climate and development agreements, especially in the most vulnerable contexts, and identified associated research priorities.

Real-world experience underscores the complexity of interactions among multiple drivers of climate change risk and of how multiple risks compound or cascade. However, a holistic framework for assessing such complex climate change risks has not yet been achieved. Clarity is needed regarding the interactions that generate risk, including the role of adaptation and mitigation responses. In this perspective, we present a framework for three categories of increasingly complex climate change risk that focus on interactions among the multiple drivers of risk, as well as among multiple risks. A significant innovation is recognizing that risks can arise both from potential impacts due to climate change and from responses to climate change. This approach encourages thinking that traverses sectoral and regional boundaries and links physical and socio-economic drivers of risk. Advancing climate change risk assessment in these ways is essential for more informed decision making that reduces negative climate change impacts. © 2021 The Authors

To accurately identify the most vulnerable areas to floods, physical (e.g., building material) and social (e.g., education, health, income of households) housing stock information is required. However, in developing countries, this information is often unreliable, unavailable or inaccessible, and manual data collection is time-consuming. This can lead to difficulties for humanitarians or policymakers in implementing appropriate disaster risk reduction and response interventions. Therefore, there is a need for the development of alternative approaches to data collection and analysis. An alternative approach to on-site vulnerability assessment is to extract physical vulnerability characteristics, such as land use type or rooftop material, from satellite or Unmanned Aerial Vehicle (UAV) imagery. However, other social or physical vulnerability information on the household level can often not be extracted from only the remote sensing data. This research develops an approach for integrating multiple data sources into a Geographic Information System to improve the completeness of data on different vulnerability indicators. This approach is applied on the housing stock of the Karonga district in Malawi. An Object-Based Image Analysis on UAV imagery is combined with a machine learning analysis of Mapillary data to enable remote identification of both rooftop ànd wall material. Depth-damage curves were created to describe the impact on the housing stock for different categories of physical vulnerability (such as building material) and levels of inundation. Moreover, local survey data is used for the creation of a social vulnerability index. Combined, the datasets represent the spatial distribution of housing stock vulnerability for multiple flood scenarios. This approach is useful in situations where proactive risk analyses must be carried out or where local-scale interventions, such as building strengthening- or flood awareness projects, have to be implemented. Finally, we give recommendations for scaling the methodology to areas where only lower resolution data is available.

With a global paradigm shift from post-disaster response aid to anticipatory action, the question on how anticipatory action relates to long-term climate adaptation and often government-led actions towards permanent disaster prevention becomes more relevant. With rising disaster risk, a framework that decision-makers can use to select between preventive and preparedness risk reduction efforts would be most useful. A model originally developed to compare permanent interventions to forecast-based action for floods was applied to wind-induced building damage due to tropical cyclones, focusing on a case study from the Philippines. We made use of a typhoon forecasting model based on the ensemble forecast from EMCWF, and modeled the wind footprint to estimate the wind speed in the case study area. A threshold was defined, similar to how it is done in actual operations by the Philippine Red Cross. If the forecasted typhoon exceeds a pre-set threshold in terms of wind speed, action to strengthen light-weight wooden houses with a Shelter Strengthening Kit (SSK) is taken. SSKs temporarily make these houses more resistant to withstand extreme winds, thereby reducing the impacts. This short term action is compared to a scenario in which lightweight wooden houses are permanently upgraded. Results give actors in humanitarian response, anticipatory action as well as permanent disaster prevention insight into which variables affect this balance. and help policymakers to allocate their scarce budgets in a cost-effective way. The framework, although developed for the Philippines, can also be replicated in other cyclone-prone countries.

Context: It is now widely accepted that the climate is changing, and that societal responses will need to be rapid and comprehensive to prevent the most severe impacts. A key milestone in global climate governance is to assess progress on adaptation. To-date, however, there has been negligible robust, systematic synthesis of progress on adaptation or adaptation-relevant responses globally. Aim: The purpose of this review protocol is to outline the methods used by the Global Adaptation Mapping Initiative (GAMI) to systematically review human adaptation responses to climate-related changes that have been documented globally since 2013 in the scientific literature. The broad question underpinning this review is: Are we adapting to climate change? More specifically, we ask ‘what is the evidence relating to human adaptation-related responses that can (or are) directly reducing risk, exposure, and/or vulnerability to climate change?’ This work responds to the recognition of the need for high-level syntheses of adaptation research to inform global and regional climate assessments.Methods: We review scientific literature 2013-2019 to identify documents empirically reporting on observed adaptation-related responses to climate change in human systems that can directly reduce risk. We exclude non-empirical (theoretical & conceptual) literature and adaptation in natural systems that occurs without human intervention. Included documents were coded across a set of questions focused on: Who is responding? What responses are documented? What is the extent of the adaptation-related response? What is the evidence that adaptation-related responses reduce risk, exposure and/or vulnerability? Once articles are coded, we conduct a quality appraisal of the coding and develop ‘evidence packages’ for regions and sectors. We supplement this systematic mapping with an expert elicitation exercise, undertaken to assess bias and validity of insights from included/coded literature vis a vis perceptions of real-world adaptation for global regions and sectors, with associated confidence assessments. Related protocols: This protocol represents Part 1 of a 5-part series outlining the phases of methods for this initiative. Part 1 provides an introduction to the Global Adaptation Mapping Initiative (GAMI) and an overview of methods.

We present the first systematic, global stocktake of the academic literature on human adaptation. We screen 48,316 documents and identify 1,682 articles that present empirical research documenting human efforts to reduce risk from climate change and associated hazards. Coding and synthesizing this literature highlights that the overall extent of adaptation across global regions and sectors is low. Adaptations are largely local and incremental rather than transformative. Behavioural adjustments by individuals and households are more prevalent than any other type of response, largely motivated by drought and precipitation variability. Local governments and civil society are engaging in risk reduction across all sectors and regions, particularly in response to flooding. Urban technological and infrastructural adaptations to flood risk are prevalent in Europe, while shifts in farming practices dominate reporting from Africa and Asia. Despite increasing evidence of adaptation responses, evidence that these responses are reducing risks (observed and projected) remains limited.

The last few years have seen an explosion of interest in extreme event attribution, the science of estimating the influence of human activities or other factors on the probability and other characteristics of an observed extreme weather or climate event. This is driven by public interest, but also has practical applications in decision-making after the event and for raising awareness of current and future climate change impacts. The World Weather Attribution (WWA) collaboration has over the last 5 years developed a methodology to answer these questions in a scientifically rigorous way in the immediate wake of the event when the information is most in demand. This methodology has been developed in the practice of investigating the role of climate change in two dozen extreme events world-wide. In this paper, we highlight the lessons learned through this experience. The methodology itself is documented in a more extensive companion paper. It covers all steps in the attribution process: the event choice and definition, collecting and assessing observations and estimating probability and trends from these, climate model evaluation, estimating modelled hazard trends and their significance, synthesis of the attribution of the hazard, assessment of trends in vulnerability and exposure, and communication. Here, we discuss how each of these steps entails choices that may affect the results, the common problems that can occur and how robust conclusions can (or cannot) be derived from the analysis. Some of these developments also apply to other attribution methodologies and indeed to other problems in climate science.

Assessing global progress on human adaptation to climate change is an urgent priority. Although the literature on adaptation to climate change is rapidly expanding, little is known about the actual extent of implementation. We systematically screened >48,000 articles using machine learning methods and a global network of 126 researchers. Our synthesis of the resulting 1,682 articles presents a systematic and comprehensive global stocktake of implemented human adaptation to climate change. Documented adaptations were largely fragmented, local and incremental, with limited evidence of transformational adaptation and negligible evidence of risk reduction outcomes. We identify eight priorities for global adaptation research: assess the effectiveness of adaptation responses, enhance the understanding of limits to adaptation, enable individuals and civil society to adapt, include missing places, scholars and scholarship, understand private sector responses, improve methods for synthesizing different forms of evidence, assess the adaptation at different temperature thresholds, and improve the inclusion of timescale and the dynamics of responses. Determining progress in adaptation to climate change is challenging, yet critical as climate change impacts increase. A stocktake of the scientific literature on implemented adaptation now shows that adaptation is mostly fragmented and incremental, with evidence lacking for its impact on reducing risk.

Climate change disproportionately affects marginalized groups in society. Growing evidence suggests that adaptation responses without equity considerations may worsen inequality and increase vulnerability. Using data from a systematic review of peer-reviewed empirical research on adaptation responses to climate change (n=1682), we present a large-n assessment of how social equity is integrated into adaptation across regions, sectors, and social groups. Roughly 60% of peer-reviewed literature on adaptation responses addressed social equity by documenting how historically marginalized groups were involved in planning, or targeted in implementation. Responses in Africa and those focusing on poverty reduction most frequently integrated social equity. Equity was less likely to be addressed in adaptation responses in Europe, Australasia, and North America, and in the urban sector. Income-based inequity was more frequently considered than gender, age, or Indigenous status. Ethnic and racial minorities, migrants, and people with disabilities were rarely considered. Renewed and rigorous attention to equity in adaptation research, policy, planning and implementation is needed to fill key gaps in knowledge and to ensure a more fair and just adaptation process and outcome.

The COVID-19 pandemic and anthropogenic climate change are global crises. We show how strongly these crises are connected, including the underlying societal inequities and problems of poverty, substandard housing, and infrastructure including clean water supplies. The origins of all these crises are related to modern consumptive industrialisation, including burning of fossil fuels, increasing human population density, and replacement of natural with human dominated ecosystems. Because business as usual is unsustainable on all three fronts, transformative responses are needed. We review the literature on risk management interventions, implications for COVID-19, for climate change risk and for equity associated with biodiversity, water and WaSH, health systems, food systems, urbanization and governance. This paper details the considerable evidence base of observed synergies between actions to reduce pandemic and climate change risks while enhancing social justice and biodiversity conservation. It also highlights constraints imposed by governance that can impede deployment of synergistic solutions. In contrast to the response to the COVID-19 pandemic, governance systems have procrastinated on addressing climate change and biodiversity loss as these are interconnected chronic crises. It is now time to address all three to avoid a multiplication of future crises across health, food, water, nature, and climate systems.

Over the last few years, methods have been developed to answer questions on the effect of global warming on recent extreme events. Many “event attribution” studies have now been performed, a sizeable fraction even within a few weeks of the event, to increase the usefulness of the results. In doing these analyses, it has become apparent that the attribution itself is only one step of an extended process that leads from the observation of an extreme event to a successfully communicated attribution statement. In this paper we detail the protocol that was developed by the World Weather Attribution group over the course of the last 4 years and about two dozen rapid and slow attribution studies covering warm, cold, wet, dry, and stormy extremes. It starts from the choice of which events to analyse and proceeds with the event definition, observational analysis, model evaluation, multi-model multi-method attribution, hazard synthesis, vulnerability and exposure analysis and ends with the communication procedures. This article documents this protocol. It is hoped that our protocol will be useful in designing future event attribution studies and as a starting point of a protocol for an operational attribution service.

The humanitarian sector is active at the global frontline of climate impacts, and has a track record in influencing the climate change policy agenda. Geoengineering is a humanitarian concern: the potential for deliberate large-scale intervention in the Earth's climate system has major implications in terms of impacts on the most vulnerable. Yet, so far the humanitarian community has largely been absent from geoengineering deliberations. Geoengineering may be perceived as too theoretical, too complex, and not imminent enough to merit attention. However, early engagement by the sector is imperative to ensure that humanitarian considerations are integrated into policy decisions. Those who can suffer the worst outcomes need to be involved; especially given the plausibility of “predatory geoengineering” where recklessly self-concerned actions may result in harmful consequences to others. This paper explores the humanitarian dimensions of geoengineering, specifically relating to solar radiation management (SRM). Drawing from the engagement of the Red Cross Red Crescent Climate Centre in SRM discussions, we discuss how to improve linkages between science, policy and humanitarian practice. We further propose the creation of a geoengineering risk management framework to ensure that the interests of the most vulnerable are considered and addressed - including the voices of all stakeholders.

This paper proposes a heat-wave definition for Bangladesh that could be used to trigger preparedness measures in a heat early warning system (HEWS) and explores the climate mechanisms associated with heat waves. A HEWS requires a definition of heat waves that is both related to human health outcomes and forecastable. No such definition has been developed for Bangladesh. Using a generalized additive regression model, a heat-wave definition is proposed that requires elevated minimum and maximum daily temperatures over the 95th percentile for 3 consecutive days, confirming the importance of nighttime conditions for health impacts. By this definition, death rates increase by about 20% during heat waves; this result can be used as an argument for public-health interventions to prevent heat-related deaths. Furthermore, predictability of these heat waves exists from weather to seasonal time scales, offering opportunities for a range of preparedness measures. Heat waves are associated with an absence of normal premonsoonal rainfall brought about by anomalously strong low-level westerly winds and weak southerlies, detectable up to approximately 10 days in advance. This circulation pattern occurs over a background of drier-than-normal conditions, with below-average soil moisture and precipitation throughout the heat-wave season from April to June. Low soil moisture increases the odds of heat-wave occurrence for 10–30 days, indicating that subseasonal forecasts of heat-wave risk may be possible by monitoring soil-moisture conditions.

The global impacts of river floods are substantial and rising. Effective adaptation to the increasing risks requires an in-depth understanding of the physical and socioeconomic drivers of risk. Whereas the modeling of flood hazard and exposure has improved greatly, compelling evidence on spatiotemporal patterns in vulnerability of societies around the world is still lacking. Due to this knowledge gap, the effects of vulnerability on global flood risk are not fully understood, and future projections of fatalities and losses available today are based on simplistic assumptions or do not include vulnerability. We show for the first time (to our knowledge) that trends and fluctuations in vulnerability to river floods around the world can be estimated by dynamic high-resolution modeling of flood hazard and exposure. We find that rising per-capita income coincided with a global decline in vulnerability between 1980 and 2010, which is reflected in decreasing mortality and losses as a share of the people and gross domestic product exposed to inundation. The results also demonstrate that vulnerability levels in low- and high-income countries have been converging, due to a relatively strong trend of vulnerability reduction in developing countries. Finally, we present projections of flood losses and fatalities under 100 individual scenario and model combinations, and three possible global vulnerability scenarios. The projections emphasize that materialized flood risk largely results from human behavior and that future risk increases can be largely contained using effective disaster risk reduction strategies.

Climate shocks contribute to a significant share of the humanitarian burden, and are a key factor in increasing poverty and food insecurity. Social protection is increasingly recognised as an instrument to help build resilience to climate risks through long-term, large-scale national systems. However, most experiences to date have focused on social protection’s role for chronic needs, or at best, shock-response, rather than on anticipation and prevention.This article argues that social protection can support more effective resilience building at scale by integrating early action and preparedness. We propose a concrete solution, namely linking a Forecast-based Financing mechanism to a social protection system to enable anticipatory actions based on forecast triggers and guaranteed funding ahead of a shock. Such a system may enhance scalability, timeliness, predictability and adequacy of social protection benefits. Key considerations for success of this emerging approach include sound analysis of forecast, risks, cost and benefits, and ring-fenced funding.

While climate variability and change affect global patterns of disease, there are few examples of methods that effectively integrate climate into health programming. This study examines a Red Cross Red Crescent pilot project in Kenya, Tanzania, Vietnam, and Indonesia that incorporated climate information and considerations in health operations. Our investigation looks at three elements of programming: baseline community perceptions of climate and health, integration of climate information in operations, and resulting community-level risk reduction behaviour. (1) Through community focus groups, semi-structured interviews, and household surveys, our research reveals that potential health effects of climate variability and change are a key concern at the community level. (2) Project implementors used climate information to design educational materials and health contingency plans to inform when and where disease prevention activities should be concentrated. This climate-based disease anticipation and improved sharing of incidence data aimed to quickly detect and respond to changing disease patterns in a variable climate. (3) Subsequently, community-level risk reduction behaviour significantly increased in project locations. This pilot is evidence that climate information and considerations can be readily integrated into health programming to account for changing risks, using existing disease prevention techniques to address priority concerns of vulnerable communities.

The Development & Climate Days celebrated its 10th anniversary at the United Nations Framework Convention on Climate Change COP 18 in Doha, Qatar (1–2 December 2012). With a vision of re-energizing the original purpose of bringing together policy-makers, practitioners and researchers for intensely participatory learning, dialogue and networking, this event convened over 200 negotiators, policy-makers, scientists, funding agencies and development practitioners. A highly interactive, out-of-the-box programme featured ‘speed networking’ icebreaker sessions, experiential learning games about climate risk management and development, sharply moderated discussions, high-level panels and a ‘Beyond the Film Festival’. Without support from the habitual Powerpoint presentation format, each of these sessions aimed to foster an environment of collaboration among participants, and inject serious fun into the climate and development dialogue processes. Key messages emerging from the event included: (i) considering ways ...

Too often, credible scientific early warning information of increased disaster risk does not result in humanitarian action. With financial resources tilted heavily towards response after a disaster, disaster managers have limited incentive and ability to process complex scientific data, including uncertainties. These incentives are beginning to change, with the advent of several new Forecast-based Financing systems that provide funding based on a forecast of an extreme event. Given the changing landscape, here we demonstrate a method to select and use appropriate forecasts for specific humanitarian disaster prevention actions, even in a data-scarce location. This action-based forecasting methodology takes into account the parameters of each action, such as action lifetime, when verifying a forecast. Forecasts are linked with action based on an understanding of (1) the magnitude of previous flooding events and (2) the willingness to act "in vain" for specific actions. This is applied in the context of the Uganda Red Cross Society Forecast-based Financing pilot project, with forecasts from the Global Flood Awareness System (GloFAS). Using this method, we define the "danger level" of flooding, and we select the probabilistic forecast triggers that are appropriate for specific actions. Results from this methodology can be applied globally across hazards, and fed into a financing system that ensures that automatic, pre-funded early action will be triggered by forecasts.

In 2008, the International Federation of Red Cross and Red Crescent Societies (IFRC) used a seasonal forecast for West Africa for the first time to implement an Early Warning, Early Action strategy for enhanced flood preparedness and response. Interviews with disaster managers suggest that this approach improved their capacity and response. Relief supplies reached flood victims within days, as opposed to weeks in previous years, thereby preventing further loss of life, illness, and setbacks to livelihoods, as well as augmenting the efficiency of resource use. This case demonstrates the potential benefits to be realised from the use of medium-to-long-range forecasts in disaster management, especially in the context of potential increases in extreme weather and climate-related events due to climate variability and change. However, harnessing the full potential of these forecasts will require continued effort and collaboration among disaster managers, climate service providers, and major humanitarian donors.