• Energy Research

AbstractPeople affected by conflict are particularly vulnerable to climate shocks and climate change, yet little is known about climate change adaptation in fragile contexts. While climate events are one of the many contributing drivers of conflict, feedback from conflict increases vulnerability, thereby creating conditions for a vicious cycle of conflict. In this study, we carry out a systematic review of peer-reviewed literature, taking from the Global Adaptation Mapping Initiative (GAMI) dataset to documenting climate change adaptation occurring in 15 conflict-affected countries and compare the findings with records of climate adaptation finance flows and climate-related disasters in each country. Academic literature is sparse for most conflict-affected countries, and available studies tend to have a narrow focus, particularly on agriculture-related adaptation in rural contexts and adaptation by low-income actors. In contrast, multilateral and bilateral funding for climate change adaptation addresses a greater diversity of adaptation needs, including water systems, humanitarian programming, and urban areas. Even among the conflict-affected countries selected, we find disparity, with several countries being the focus of substantial research and funding, and others seeing little to none. Results indicate that people in conflict-affected contexts are adapting to climate change, but there is a pressing need for diverse scholarship across various sectors that documents a broader range of adaptation types and their results.

AbstractAnomalous conditions in the oceans and atmosphere have the potential to be used to enhance the predictability of flood events, enabling earlier warnings to reduce risk. In the Amazon basin, extreme flooding is consistently attributed to warmer or cooler conditions in the tropical Pacific and Atlantic oceans, with some evidence linking floods to other hydroclimatic drivers such as the Madden–Julian Oscillation (MJO). This review evaluates the impact of several hydroclimatic drivers on rainfall and river discharge regimes independently, aggregating all the information of previous studies to provide an up‐to‐date depiction of what we currently know and do not know about how variations in climate impact flooding in the Amazon. Additionally, 34 major flood events that have occurred since 1950 in the Amazon and their attribution to climate anomalies are documented and evaluated. This review finds that despite common agreement within the literature describing the relationship between phases of climate indices and hydrometeorological variables, results linking climate anomalies and flood hazard are often limited to correlation rather than to causation, while the understanding of their usefulness for flood forecasting is weak. There is a need to understand better the ocean–atmosphere response mechanisms that led to previous flood events. In particular, examining the oceanic and atmospheric conditions preceding individual hydrological extremes, as opposed to composite analysis, could provide insightful information into the magnitude and spatial distribution of anomalous sea surface temperatures required to produce extreme floods. Importantly, such an analysis could provide meaningful thresholds on which to base seasonal flood forecasts.

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 536 responses.

Extreme temperatures are one of the leading causes of death and disease in both developed and developing countries, and heat extremes are projected to rise in many regions. To reduce risk, heatwave plans and cold weather plans have been effectively implemented around the world. However, much of the world's population is not yet protected by such systems, including many data-scarce but also highly vulnerable regions. In this study, we assess at a global level where such systems have the potential to be effective at reducing risk from temperature extremes, characterizing (1) long-term average occurrence of heatwaves and coldwaves, (2) seasonality of these extremes, and (3) short-term predictability of these extreme events three to ten days in advance. Using both the NOAA and ECMWF weather forecast models, we develop global maps indicating a first approximation of the locations that are likely to benefit from the development of seasonal preparedness plans and/or short-term early warning systems for extreme temperature. The extratropics generally show both short-term skill as well as strong seasonality; in the tropics, most locations do also demonstrate one or both. In fact, almost 5 billion people live in regions that have seasonality and predictability of heatwaves and/or coldwaves. Climate adaptation investments in these regions can take advantage of seasonality and predictability to reduce risks to vulnerable populations.

Abstract Extreme weather and climate events associated with El Niño and La Niña cause massive societal impacts. Therefore, observations and forecasts are used around the world to prepare for such events. However, global warming has caused warm El Niño events to seem bigger than they are, while cold La Niña events seem smaller, in the commonly used Niño3.4 index (sea surface temperature (SST) anomalies over 5∘ S–5∘ N, 120–170∘ W). We propose a simple and elegant adjustment, defining a relative Niño3.4 index as the difference between the original SST anomaly and the anomaly over all tropical oceans (20∘ S–20∘ N). This relative index describes the onset of convection better, is not contaminated by global warming and can be monitored and forecast in real-time. We show that the relative Niño3.4 index is better in line with effects on rainfall and would be more useful for preparedness for El Niño and La Niña in a changing climate and for El Niño—Southern Oscillation research.