Climate-related Extreme Events Research Articles

Running dry: The U.S. Southwest's drift into a drier climate state

AbstractChanges in precipitation have far‐reaching consequences on human society and ecosystems as has been demonstrated by recent severe droughts in California and the Oklahoma region. Droughts are beside tropical cyclones the most costly weather and climate related extreme events in the U.S. We apply a weather type (WT) analysis to reanalysis data from 1979–2014 that characterize typical weather conditions over the contiguous United States. This enables us to assign precipitation trends within 1980–2010 to changes in WT frequencies and changes in precipitation intensities. We show that in the North Atlantic and Midwest region precipitation intensity changes are the major driver of increasing precipitation trends. In the U.S. Southwest, however, WT frequency changes lead to a significant precipitation decrease of up to −25% related to an increase in anticyclonic conditions in the North East Pacific. This trend is partly counteracted by increasing precipitation intensities.

Future differential vulnerability to natural disasters by level of education

The present paper looks at the implications of anticipated changes in population size and composition for the projected number of deaths from natural disasters Building on empirical evidence from cross-country time series of factors associated with natural disaster fatalities since 1970 in 174 countries, the paper first highlights the major role of education in enabling people to cope with weather extremes in the past. Using the five demographic scenarios implied by the Shared Socioeconomic Pathways (SSPs), which include trajectories for the future of educational expansion, this evidence is translated in the second part of the paper into projections of the number of deaths from climate-related extreme natural events for six major world regions. Assuming constant hazard, we demonstrate the importance of including in assessments of future vulnerability not only the projected population size but the full population heterogeneity by age, sex and level of education.

Vulnerability assessment for loss of access to drinking water due to extreme weather events

Climate-related extreme weather events can result in the loss of drinking water access. We assessed the relative vulnerability of 3143 United States (U.S.) counties to loss of drinking water access due to droughts, floods, and cyclones. Five vulnerability assessment models from the literature were compared, each differing in the aggregation method used to combine the three determinants of vulnerability (V) – exposure (E), sensitivity (S), and adaptive capacity (AC). Exposure scores were calculated using historical occurrence data, sensitivity scores were determined from the intrinsic resilience of the drinking water technologies, and adaptive capacity scores were calculated from nine socioeconomic indicators. Our results showed that models V = E + S + AC and V = E + S–AC were the same, as were models V = E × S × AC and V = E × S ÷ AC. Between these two model forms (form 1: V = E + S + AC and V = E + S–AC; form 2: V = E × S × AC and V = E × S ÷ AC), scores from one model form could be used to predict scores from the second model form, with R-squared values ranging from 0.61 to 0.82 depending on the extreme weather event type. A fifth model, V = (E–AC) × S was not found to correlate with any of the other four models. We used V = E + S + AC as our reference model as this resulted in a more uniform distribution of counties in each of the five intervals of vulnerability. Comparing the vulnerability scores identified the counties with greatest vulnerability to losing access to drinking water due to floods, droughts, and cyclones. Our results can be used to inform evidence-based decisions such as allocation of resources and implementation of adaptation strategies.

Susceptibility assessment of urban tree species in Cambridge, MA, from future climatic extremes

The City of Cambridge, Massachusetts, recognizes the value of the city’s urban forest in terms of air quality, lower wind speeds, esthetics, energy conservation, reduced noise pollution, habitat value, decreased runoff, and bolstering of local businesses and property values. The density, composition, and location of street and city park trees comprising the urban forest will be influenced by future climate-driven extreme weather events. In this study, we have developed an approach for assessing impacts of multiple extreme weather scenarios likely to become more frequent under climate change and subsequently influence the composition of street and park trees. This potential for loss of trees as a result of one (or more) of these climate-related extreme weather events is considered to be one indicator of the susceptibility of Cambridge’s urban forest to climate-related weather events. The scenarios considered were a hurricane/tropical storm similar to tropical storm Sandy in 2012, heat stress, snow or ice loading (e.g., loss of tree limbs), Asian longhorn beetle or emerald ash borer infestations, and the cumulative effect from the addition of all these scenarios. The literature was used to assess the sensitivity of tree species to each threat and determine the anticipated loss of individuals from each species. The results are a reasonable indication of the more tolerant tree species in Cambridge and their locations. This assessment of susceptibility can inform proactive management of the urban forest.

Integrating social–ecological vulnerability assessments with climate forecasts to improve local climate adaptation planning for coral reef fisheries in Papua New Guinea

A major gap exists in integrating climate projections and social–ecological vulnerability analyses at scales that matter, which has affected local-scale adaptation planning and actions to date. We address this gap by providing a novel methodology that integrates information on: (i) the expected future climate, including climate-related extreme events, at the village level; (ii) an ecological assessment of the impacts of these climate forecasts on coral reefs; and (iii) the social adaptive capacity of the artisanal fishers, to create an integrated vulnerability assessment on coastal communities in five villages in Papua New Guinea. We show that, despite relatively proximate geographies, there are substantial differences in both the predicted extreme rainfall and temperature events and the social adaptive capacity among the five fishing-dependent communities, meaning that they have likely different vulnerabilities to future climate change. Our methodology shows that it is possible to capture social information and integrate this with climate and ecological modeling in ways that are best suited to address the impacts of climate-mediated environmental changes currently underway across different scales.

Climate variability and changes in the major cities of Bangladesh: observations, possible impacts and adaptation

High population density, inadequate infrastructure and low adaptive capacity have made the urban population of Bangladesh highly vulnerable to climate change. Trends in climate and climate-related extreme events in five major cities have been analyzed in this paper to decipher the variability and ongoing changes in urban Bangladesh. An analysis of 55 years (1958–2012) of daily rainfall and temperature data using nonparametric statistical methods shows a significant increase in annual and seasonal mean daily maximum and minimum temperatures in all five cities. A significant increase in climate-related extreme events, such as heavy rainfall events (>20 mm), hot days (>32 °C) and hot nights (>25 °C), is also observed. Climate model results suggest that these trends will continue through the twenty-first century. Vulnerability of urban livelihoods and physical structures to climate change is estimated by considering certainty and timing of impacts. It has been predicted that public health and urban infrastructures, viz. water and power supply, would be the imminent affected sectors in the urban areas of Bangladesh. Adaptation measures that can be adopted to mitigate the negative impacts of climate change are also discussed.

Mapping Natural Hazard Impacts on Road Infrastructure—The Extreme Precipitation in Baden-Württemberg, Germany, June 2013

Infrastructures in Europe have been affected by impacts of extreme natural events with increasing frequency over the past decades. One of the most recent examples is the flooding that affected parts of Germany in June 2013. Global warming is expected to change patterns of climate-related extreme events affecting infrastructure. This article presents an explanatory approach. Based on an observational design, causal connections between the occurrence and patterns of extreme events and related road infrastructure impacts are analyzed. The hazard mapping case study in the state of Baden-Wurttemberg combines traffic information and data on the June 2013 extreme precipitation in Germany. It examines the precipitation occurrence and road infrastructure impact characteristics in Baden-Wurttemberg and identifies spatiotemporal hazard patterns. The article suggests further research needs and fields of application for risk mapping in climate change adaptation research in Germany.

Analysis of non-stationary climate-related extreme events considering climate change scenarios: an application for multi-hazard assessment in the Dar es Salaam region, Tanzania

In this paper we have put forward a Bayesian framework for the analysis and testing of possible non-stationarities in extreme events. We use the extreme value theory to model temperature and precipitation data in the Dar es Salaam region, Tanzania. Temporal trends are modeled writing the location parameter of the generalized extreme value distribution in terms of deterministic functions of explanatory covariates. The analyses are performed using synthetic time series derived from a Regional Climate Model. The simulations, performed in an area around the Dar es Salaam city, Tanzania, take into account two Representative Concentration Pathways scenarios from the Intergovernmental Panel on Climate Change. Our main interest is to analyze extremes with high spatial and temporal resolution and to pursue this requirement we have adopted an individual grid box analysis approach. The approach presented in this paper is composed of the following key elements: (1) an advanced Bayesian method for the estimation of model parameters, (2) a rigorous procedure for model selection, and (3) uncertainty assessment and propagation. The results of our analyses are intended to be used for quantitative hazard and risk assessment and are presented in terms of hazard curves and probabilistic hazard maps. In the case study we found that for both the temperature and precipitation data, a linear trend in the location parameter was the only model performing better than the stationary one in the areas where evidence against the stationary model exists.

Understanding the adaptation deficit: Why are poor countries more vulnerable to climate events than rich countries?

Poor countries are more heavily affected by extreme weather events and future climate change than rich countries. One of the reasons for this is the so-called adaptation deficit, that is, limits in the ability of poorer countries to adapt. This paper analyses the link between income and adaptation to climate events theoretically and empirically. We postulate that the adaptation deficit may be due to two factors: A demand effect, whereby the demand for the good “climate security” increases with income, and an efficiency effect, which works as a spill-over externality on the supply-side: Adaptation productivity in high-income countries is enhanced because of factors like better public services and stronger institutions. Using panel data from the Munich Re natural catastrophe database we find strong evidence for a demand effect for adaptation to two climate-related extreme events, tropical cyclones and floods. Evidence on the efficiency effect is more equivocal. There are some indications that adaptation in rich countries might be more efficient, but the evidence is far from conclusive. The implication for research is that better data, in particular on adaptation effort, need to be collected to understand adaptation efficiency. In terms of policy, we conclude that inclusive growth policies (which boost adaptation demand) should be an important component of international efforts to close the adaptation deficit.

Towards networked governance: improving interagency communication and collaboration for disaster risk management and climate change adaptation in Australia

Major disasters, such as bushfires or floods, place significant stress on scarce public resources. Climate change is likely to exacerbate this stress. An integrated approach to disaster risk management (DRM) and climate change adaptation (CCA) could reduce the stress by encouraging the more efficient use of pooled resources and expertise. A comparative analysis of three extreme climate-related events that occurred in Australia between 2009 and 2011 indicated that a strategy to improve interagency communication and collaboration would be a key factor in this type of policy/planning integration. These findings are in accord with the concepts of Joined-up Government and Network Governance. Five key reforms are proposed: developing a shared policy vision; adopting multi-level planning; integrating legislation; networking organisations; and establishing cooperative funding. These reforms are examined with reference to the related research literature in order to identify potential problems associated with their implementation. The findings are relevant for public policy generally but are particularly useful for CCA and DRM.

Modeling Hotspots of Climate Change in the Sahel Using Object-Based Regionalization of Multidimensional Gridded Datasets

The population of subsaharan Africa, and particularly of the countries of the Sahel and western Africa, is one of the most vulnerable to climate change and climate-related extreme events. To provide updated information for targeted climate change adaptation measures, we modeled hotspots of climate change and related extreme events in an integrative manner. This was achieved by constructing a spatial composite indicator of cumulative climate change impact, which integrates four climate- and hazard-related subindicators: seasonal temperature trends, seasonal precipitation trends, drought occurrences, and major flood events. The analysis is based on time-series of freely available continuous, gridded geo-spatial datasets, including remote sensing data. The aggregation of the four subindicators was performed by making use of a regionalization approach, based on segmentation techniques widely used in the remote sensing community in the field of object-based image analysis. Following the approach presented in this paper, 19 hotspots with most severe climatic changes were identified, evaluated, and mapped. The method enables not only the prioritization of intervention areas, but also allows decomposing the identified hotspots into their underlying subindicators, and thus additional information for effective climate change adaptation measures can be provided.

A New HadGEM3-A-Based System for Attribution of Weather- and Climate-Related Extreme Events

Abstract A new system for attribution of weather and climate extreme events has been developed based on the atmospheric component of the latest Hadley Centre model. The model is run with either observational data of sea surface temperature and sea ice or estimates of what their values would be without the effect of anthropogenic climatic forcings. In that way, ensembles of simulations are produced that represent the climate with and without the effect of human influences. A comparison between the ensembles provides estimates of the change in the frequency of extremes due to anthropogenic forcings. To evaluate the new system, reliability diagrams are constructed, which compare the model-derived probability of extreme events with their observed frequency. The ability of the model to reproduce realistic distributions of relevant climatic variables is another key aspect of the system evaluation. Results are then presented from analyses of three recent high-impact events: the 2009/10 cold winter in the United Kingdom, the heat wave in Moscow in July 2010, and floods in Pakistan in July 2010. An evaluation assessment indicates the model can provide reliable results for the U.K. and Moscow events but not for Pakistan. It is found that without anthropogenic forcings winters in the United Kingdom colder than 2009/10 would be 7–10 times (best estimate) more common. Although anthropogenic forcings increase the likelihood of heat waves in Moscow, the 2010 event is found to be very uncommon and associated with a return time of several hundred years. No reliable attribution assessment can be made for high-precipitation events in Pakistan.

Predictability of extreme events in a nonlinear stochastic-dynamical model

The objective of this work is to evaluate the potential of reduced order models to reproduce the extreme event and predictability characteristics of higher dimensional dynamical systems. A nonlinear toy model is used which contains key features of comprehensive climate models. First, we demonstrate that the systematic stochastic mode reduction strategy leads to a reduced order model with the same extreme value characteristics as the full dynamical models for a wide range of time-scale separations. Second, we find that extreme events in this model follow a generalized Pareto distribution with a negative shape parameter; thus extreme events are bounded in this model. Third, we show that a precursor approach has good forecast skill for extreme events. We then find that the reduced stochastic models capture the predictive skill of extreme events of the full dynamical models well. Consistent with previous studies we also find that the larger the extreme events, the better predictable they are. Our results suggest that systematically derived reduced order models have the potential to be used for the modeling and statistical prediction of weather- and climate-related extreme events and, possibly, in other areas of science and engineering too.

Social Protection and Climate Change

Climate change has already resulted in climate-related extreme events of greater frequency and/or intensity. This, along with long-term changes in average conditions (whether in temperature or rainfall), is likely to continue to have a major impact on livelihoods. Developing countries will be especially affected by such events – and more specifically, the poor people in developing countries – because of their geographical exposure and their greater reliance on climate-sensitive sectors such as agriculture. Social protection offers a wide range of instruments (e.g. cash transfers, insurance products, pension schemes and employment guarantee schemes) that can be used to support households that are particularly vulnerable to both the ongoing and acute impacts of climate changes. Although the evidence base showing how these measures can help those affected prevent and cope with climate challenges is still limited, this paper aims to provide a condensed review of the current knowledge and evidence about the role of social protection in reducing the impact of climate change on the poorest populations and provides a series of recommendations for both social protection and climate change practitioners and for strengthening the evidence base.

Framing adaptation to climate-related extreme events

Whilst mitigation has dominated policy and research agendas in recent years there is an increasing recognition that communities also need to be preparing for change that is unavoidable, partially a consequence of anthropogenic greenhouse gases already emitted to the atmosphere. The perceived need for adaptation has also received additional impetus through the high public profile now given to the impacts of current day weather variability, particularly the significant economic and social costs associated with recent extreme events. However, being a relatively new focus for both research and policy communities; practical evidence of the extent, feasibility, efficiency, and cost effectiveness of potential adaptation options remains largely lacking. In response, this paper seeks to make a contribution to this embryonic but evolving knowledge base by considering the theoretical underpinnings of adaptation and ultimately how this translates into practice ‘in the real world’. The analytical commentary, based on a bottom-up approach involving iterative engagement with key stakeholders and experts, reflects on the identification of measures that are either innovative or examples of good practice in reducing or transferring climate risks, as well as considering those ‘enabling’ institutional structures and processes that act to support implementation on the ground. The paper concludes by synthesising the key findings to date in order to highlight some of the opportunities for, and barriers to, adaptation activity.

Estimating least-developed countries’ vulnerability to climate-related extreme events over the next 50 years

When will least developed countries be most vulnerable to climate change, given the influence of projected socio-economic development? The question is important, not least because current levels of international assistance to support adaptation lag more than an order of magnitude below what analysts estimate to be needed, and scaling up support could take many years. In this paper, we examine this question using an empirically derived model of human losses to climate-related extreme events, as an indicator of vulnerability and the need for adaptation assistance. We develop a set of 50-year scenarios for these losses in one country, Mozambique, using high-resolution climate projections, and then extend the results to a sample of 23 least-developed countries. Our approach takes into account both potential changes in countries' exposure to climatic extreme events, and socio-economic development trends that influence countries' own adaptive capacities. Our results suggest that the effects of socio-economic development trends may begin to offset rising climate exposure in the second quarter of the century, and that it is in the period between now and then that vulnerability will rise most quickly. This implies an urgency to the need for international assistance to finance adaptation.

On the climatology of persistent heavy rainfall events in China

Persistent heavy rainfall events (PHR events) comprise one category of weather-and climate-related extreme events. Based on daily rainfall data measured in China during the period of 1951–2004, several quantitative criteria were developed to define PHR events by means of their precipitation intensity, temporal duration, spatial extent and persistence. Then a semi-objective classification based on these criteria was applied to summer daily rainfall data to identify all PHR events. A total of 197 events were observed during the study period. All events were further classified into 5 categories according to their comprehensive intensity; into 3 types according to their circulation regime; and into 8 groups according to the geographic locations of their rainbands. Based on these different classifications, finally, the behaviors of 130 PHR events identified as the most severe, severe and moderate categories since the year of 1951, including characteristics of the spatial and temporal distributions of their frequencies, intensities, and rainbands, were investigated in order to present a comprehensive description of the PHR events. The results will be helpful to the future study of revealing and understanding the processes that govern the production of the PHR events and to the improvement of the forecasts of the PHR events.

The emerging global-warming market-driver in the energy sector: A status report

The financial institutions have in recent years been progressively awakening to a severe threat inherent in human-enhancement of the greenhouse effect. Insurance companies, and increasingly banks and pension funds, have come to fear that a warming world holds the danger of unmanageable property-catastrophe losses triggered by an increase in extreme climate-related events, plus a spectrum of major knock-on problems for debt and equity investments. This emerging greenhouse market-driver now has major implications for corporate strategy in both the financial and energy sectors.