Showing papers in "Climatic Change in 2016"

The impacts of climate change on river flood risk at the global scale

Abstract: This paper presents an assessment of the implications of climate change for global river flood risk. It is based on the estimation of flood frequency relationships at a grid resolution of 0.5 × 0.5°, using a global hydrological model with climate scenarios derived from 21 climate models, together with projections of future population. Four indicators of the flood hazard are calculated; change in the magnitude and return period of flood peaks, flood-prone population and cropland exposed to substantial change in flood frequency, and a generalised measure of regional flood risk based on combining frequency curves with generic flood damage functions. Under one climate model, emissions and socioeconomic scenario (HadCM3 and SRES A1b), in 2050 the current 100-year flood would occur at least twice as frequently across 40 % of the globe, approximately 450 million flood-prone people and 430 thousand km2 of flood-prone cropland would be exposed to a doubling of flood frequency, and global flood risk would increase by approximately 187 % over the risk in 2050 in the absence of climate change. There is strong regional variability (most adverse impacts would be in Asia), and considerable variability between climate models. In 2050, the range in increased exposure across 21 climate models under SRES A1b is 31–450 million people and 59 to 430 thousand km2 of cropland, and the change in risk varies between −9 and +376 %. The paper presents impacts by region, and also presents relationships between change in global mean surface temperature and impacts on the global flood hazard. There are a number of caveats with the analysis; it is based on one global hydrological model only, the climate scenarios are constructed using pattern-scaling, and the precise impacts are sensitive to some of the assumptions in the definition and application.

A global assessment of the impact of climate change on water scarcity

Abstract: This paper presents a global scale assessment of the impact of climate change on water scarcity. Patterns of climate change from 21 Global Climate Models (GCMs) under four SRES scenarios are applied to a global hydrological model to estimate water resources across 1339 watersheds. The Water Crowding Index (WCI) and the Water Stress Index (WSI) are used to calculate exposure to increases and decreases in global water scarcity due to climate change. 1.6 (WCI) and 2.4 (WSI) billion people are estimated to be currently living within watersheds exposed to water scarcity. Using the WCI, by 2050 under the A1B scenario, 0.5 to 3.1 billion people are exposed to an increase in water scarcity due to climate change (range across 21 GCMs). This represents a higher upper-estimate than previous assessments because scenarios are constructed from a wider range of GCMs. A substantial proportion of the uncertainty in the global-scale effect of climate change on water scarcity is due to uncertainty in the estimates for South Asia and East Asia. Sensitivity to the WCI and WSI thresholds that define water scarcity can be comparable to the sensitivity to climate change pattern. More of the world will see an increase in exposure to water scarcity than a decrease due to climate change but this is not consistent across all climate change patterns. Additionally, investigation of the effects of a set of prescribed global mean temperature change scenarios show rapid increases in water scarcity due to climate change across many regions of the globe, up to 2 °C, followed by stabilisation to 4 °C.

Strongly increasing heat extremes in the Middle East and North Africa (MENA) in the 21st century

Abstract: The ensemble results of CMIP5 climate models that applied the RCP4.5 and RCP8.5 scenarios have been used to investigate climate change and temperature extremes in the Middle East and North Africa (MENA). Uncertainty evaluation of climate projections indicates good model agreement for temperature but much less for precipitation. Results imply that climate warming in the MENA is strongest in summer while elsewhere it is typically stronger in winter. The summertime warming extends the thermal low at the surface from South Asia across the Middle East over North Africa, as the hot desert climate intensifies and becomes more extreme. Observations and model calculations of the recent past consistently show increasing heat extremes, which are projected to accelerate in future. The number of warm days and nights may increase sharply. On average in the MENA, the maximum temperature during the hottest days in the recent past was about 43 °C, which could increase to about 46 °C by the middle of the century and reach almost 50 °C by the end of the century, the latter according to the RCP8.5 (business-as-usual) scenario. This will have important consequences for human health and society.

Particulate Air Pollution from Wildfires in the Western US under Climate Change.

Abstract: Wildfire can impose a direct impact on human health under climate change. While the potential impacts of climate change on wildfires and resulting air pollution have been studied, it is not known who will be most affected by the growing threat of wildfires. Identifying communities that will be most affected will inform development of fire management strategies and disaster preparedness programs. We estimate levels of fine particulate matter (PM2.5) directly attributable to wildfires in 561 western US counties during fire seasons for the present-day (2004–2009) and future (2046–2051), using a fire prediction model and GEOS-Chem, a 3-D global chemical transport model. Future estimates are obtained under a scenario of moderately increasing greenhouse gases by mid-century. We create a new term “Smoke Wave,” defined as ≥2 consecutive days with high wildfire-specific PM2.5, to describe episodes of high air pollution from wildfires. We develop an interactive map to demonstrate the counties likely to suffer from future high wildfire pollution events. For 2004–2009, on days exceeding regulatory PM2.5 standards, wildfires contributed an average of 71.3 % of total PM2.5. Under future climate change, we estimate that more than 82 million individuals will experience a 57 % and 31 % increase in the frequency and intensity, respectively, of Smoke Waves. Northern California, Western Oregon and the Great Plains are likely to suffer the highest exposure to widlfire smoke in the future. Results point to the potential health impacts of increasing wildfire activity on large numbers of people in a warming climate and the need to establish or modify US wildfire management and evacuation programs in high-risk regions. The study also adds to the growing literature arguing that extreme events in a changing climate could have significant consequences for human health.

Projections of future floods and hydrological droughts in Europe under a +2°C global warming

Abstract: We present an assessment of the impacts of a +2°C global warming on extreme floods and hydrological droughts (1 in 10 and 1 in 100 year events) in Europe using eleven bias-corrected climate model simulations from CORDEX Europe and three hydrological models. The results show quite contrasted results between northern and southern Europe. Flood magnitudes are expected to increase significantly south of 60oN, except for some regions (Bulgaria, Poland, south of Spain) where the results are not significant. The sign of these changes are particularly robust in large parts of Romania, Ukraine, Germany, France and North of Spain. North of this line, floods are projected to decrease in most of Finland, NW Russia and North of Sweden, with the exception of southern Sweden and some coastal areas in Norway where floods may increase. The results concerning extreme droughts are less robust, especially for drought duration where the spread of the results among the members is quite high in some areas. Anyway, drought magnitude and duration may increase in Spain, France, Italy, Greece, the Balkans, south of the UK and Ireland. Despite some remarkable differences among the hydrological models’ structure and calibration, the results are quite similar from one hydrological model to another. Finally, an analysis of floods and droughts together shows that the impact of a +2°C global warming will be most extreme for France, Spain, Portugal, Ireland, Greece and Albania. These results are particularly robust in southern France and northern Spain.

Multi-hazard assessment in Europe under climate change

Abstract: While reported losses of climate-related hazards are at historically high levels, climate change is likely to enhance the risk posed by extreme weather events. Several regions are likely to be exposed to multiple climate hazards, yet their modeling in a joint scheme is still at the early stages. A multi-hazard framework to map exposure to multiple climate extremes in Europe along the twenty-first century is hereby presented. Using an ensemble of climate projections, changes in the frequency of heat and cold waves, river and coastal flooding, streamflow droughts, wildfires and windstorms are evaluated. Corresponding variations in expected annual exposure allow for a quantitative comparison of hazards described by different process characteristics and metrics. Projected changes in exposure depict important variations in hazard scenarios, especially those linked to rising temperatures, and spatial patterns largely modulated by local climate conditions. Results show that Europe will likely face a progressive increase in overall climate hazard with a prominent spatial gradient towards south-western regions mainly driven by the rise of heat waves, droughts and wildfires. Key hotspots emerge particularly along coastlines and in floodplains, often highly populated and economically pivotal, where floods and windstorms could be critical in combination with other climate hazards. Projected increases in exposure will be larger for very extreme events due to their pronounced changes in frequency. Results of this appraisal provide useful input for forthcoming European disaster risk and adaptation policy.

Percentile indices for assessing changes in heavy precipitation events

Abstract: Many climate studies assess trends and projections in heavy precipitation events using precipitation percentile (or quantile) indices. Here we investigate three different percentile indices that are commonly used. We demonstrate that these may produce very different results and thus require great care with interpretation. More specifically, consideration is given to two intensity-based indices and one frequency-based index, namely (a) all-day percentiles, (b) wet-day percentiles, and (c) frequency indices based on the exceedance of a percentile threshold. Wet-day percentiles are conditionally computed for the subset of wet events (with precipitation exceeding some threshold, e.g. 1 mm/d for daily precipitation). We present evidence that this commonly used methodology can lead to artifacts and misleading results if significant changes in the wet-day frequency are not accounted for. Percentile threshold indices measure the frequency of exceedance with respect to a percentile-based threshold. We show that these indices yield an assessment of changes in heavy precipitation events that is qualitatively consistent with all-day percentiles, but there are substantial differences in quantitative terms. We discuss the reasons for these effects, present a theoretical assessment, and provide a series of examples using global and regional climate models to quantify the effects in typical applications. Application to climate model output shows that these considerations are relevant to a wide range of typical climate-change applications. In particular, wet-day percentiles generally yield different results, and in most instances should not be used for the impact-oriented assessment of changes in heavy precipitation events.

Fuel moisture sensitivity to temperature and precipitation: climate change implications

Abstract: The objective of this paper is to examine the sensitivity of fuel moisture to changes in temperature and precipitation and explore the implications under a future climate. We use the Canadian Forest Fire Weather Index System components to represent the moisture content of fine surface fuels (Fine Fuel Moisture Code, FFMC), upper forest floor (duff) layers (Duff Moisture Code, DMC) and deep organic soils (Drought Code, DC). We obtained weather data from 12 stations across Canada for the fire season during the 1971–2000 period and with these data we created a set of modified weather streams from the original data by varying the daily temperatures by 0 to +5 °C in increments of 1 °C and the daily precipitation from −40 to 40 % in increments of 10 %. The fuel moistures were calculated for all the temperature and precipitation combinations. When temperature increases we find that for every degree of warming, precipitation has to increase by more than 15 % for FFMC, about 10 % for DMC and about 5 % for DC to compensate for the drying caused by warmer temperatures. Also, we find in terms of the number of days equal to or above an FFMC of 91, a critical value for fire spread, that no increase in precipitation amount alone could compensate for a temperature increase of 1 °C. Results from three General Circulation Models (GCMs) and three emission scenarios suggest that this sensitivity to temperature increases will result in a future with drier fuels and a higher frequency of extreme fire weather days.

Extreme weather events and climate change concern

Abstract: This paper examines whether experience of extreme weather events—such as excessive heat, droughts, flooding, and hurricanes—increases an individual’s level concern about climate change. We bring together micro-level geospatial data on extreme weather events from NOAA’s Storm Events Database with public opinion data from multiple years of the Cooperative Congressional Election Study to study this question. We find evidence of a modest, but discernible positive relationship between experiencing extreme weather activity and expressions of concern about climate change. However, the effect only materializes for recent extreme weather activity; activity that occurred over longer periods of time does not affect public opinion. These results are generally robust to various measurement strategies and model specifications. Our findings contribute to the public opinion literature on the importance of local environmental conditions on attitude formation.

Natural hazards in Australia: droughts

Abstract: Droughts are a recurrent and natural part of the Australian hydroclimate, with evidence of drought dating back thousands of years. However, our ability to monitor, attribute, forecast and manage drought is exposed as insufficient whenever a drought occurs. This paper summarises what is known about drought hazard, as opposed to the impacts of drought, in Australia and finds that, unlike other hydroclimatic hazards, we currently have very limited ability to tell when a drought will begin or end. Understanding, defining, monitoring, forecasting and managing drought is also complex due to the variety of temporal and spatial scales at which drought occurs and the diverse direct and indirect causes and consequences of drought. We argue that to improve understanding and management of drought, three key research challenges should be targeted: (1) defining and monitoring drought characteristics (i.e. frequency, start, duration, magnitude, and spatial extent) to remove confusion between drought causes, impacts and risks and better distinguish between drought, aridity, and water scarcity due to over-extractions; (2) documenting historical (instrumental and pre-instrumental) variation in drought to better understand baseline drought characteristics, enable more rigorous identification and attribution of drought events or trends, inform/evaluate hydrological and climate modelling activities and give insights into possible future drought scenarios; (3) improving the prediction and projection of drought characteristics with seasonal to multidecadal lead times and including more realistic modelling of the multiple factors that cause (or contribute to) drought so that the impacts of natural variability and anthropogenic climate change are accounted for and the reliability of long-term drought projections increases.

Global fossil energy markets and climate change mitigation – an analysis with REMIND

Abstract: We analyze the dynamics of global fossil resource markets under different assumptions for the supply of fossil fuel resources, development pathways for energy demand, and climate policy settings. Resource markets, in particular the oil market, are characterized by a large discrepancy between costs of resource extraction and commodity prices on international markets. We explain this observation in terms of (a) the intertemporal scarcity rent, (b) regional price differentials arising from trade and transport costs, (c) heterogeneity and inertia in the extraction sector. These effects are captured by the REMIND model. We use the model to explore economic effects of changes in coal, oil and gas markets induced by climate-change mitigation policies. A large share of fossil fuel reserves and resources will be used in the absence of climate policy leading to atmospheric GHG concentrations well beyond a level of 550 ppm CO2-eq. This result holds independently of different assumptions about energy demand and fossil fuel availability. Achieving ambitious climate targets will drastically reduce fossil fuel consumption, in particular the consumption of coal. Conventional oil and gas as well as non-conventional oil reserves are still exhausted. We find the net present value of fossil fuel rent until 2100 at 30tril.US$ with a large share of oil and a small share of coal. This is reduced by 9 and 12tril.US$ to achieve climate stabilization at 550 and 450 ppm CO2-eq, respectively. This loss is, however, overcompensated by revenues from carbon pricing that are 21 and 32tril.US$, respectively. The overcompensation also holds under variations of energy demand and fossil fuel supply.

Natural hazards in Australia: extreme bushfire.

Abstract: Bushfires are one of the most frequent natural hazards experienced in Australia. Fires play an important role in shaping the landscape and its ecological dynamics, but may also have devastating effects that cause human injuries and fatalities, as well as broad-scale environmental damage. While there has been considerable effort to quantify changes in the occurrence of bushfire in Australia, a comprehensive assessment of the most extreme bushfire cases, which exact the greatest economic and environmental impacts, is lacking. In this paper we reflect upon recently developed understanding of bushfire dynamics to consider (i) historical changes in the occurrence of extreme bushfires, and (ii) the potential for increasing frequency in the future under climate change projections. The science of extreme bushfires is still a developing area, thus our conclusions about emerging patterns in their occurrence should be considered tentative. Nonetheless, historical information on noteworthy bushfire events suggests an increased occurrence in recent decades. Based on our best current understanding of how extreme bushfires develop, there is strong potential for them to increase in frequency in the future. As such there is a pressing need for a greater understanding of these powerful and often destructive phenomena.

Projections of climate change effects on discharge and inundation in the Amazon basin

Abstract: Climate change and its effects on the hydrologic regime of the Amazon basin can impact biogeochemical processes, transportation, flood vulnerability, fisheries and hydropower generation. We examined projections of climate change on discharge and inundation extent in the Amazon basin using the regional hydrological model MGB-IPH with 1-dimensional river hydraulic and water storage simulation in floodplains. Future projections (2070–2099) were obtained from five GCMs from IPCC’s Fifth Assessment Report CMIP5. Climate projections have uncertainty and results from different climate models did not agree in total Amazon flooded area or discharge anomalies along the main stem river. Overall, model runs agree better with wetter (drier) conditions over western (eastern) Amazon. Results indicate that increased mean and maximum river discharge for large rivers draining the Andes in the northwest contributes to increased mean and maximum discharge and inundation extent over Peruvian floodplains and Solimoes River (annual mean-max: +9 % - +18.3 %) in western Amazonia. Decreased river discharges (mostly dry season) are projected for eastern basins, and decreased inundation extent at low water (annual min) in the central (−15.9 %) and lower Amazon (−4.4 %).

Coastal sea level changes: Observed and projected during the 20th and 21st century.

Abstract: Timeseries of observed and projected sea level changes for the 20th and 21st century are analyzed at various coastal locations around the world that are vulnerable to climate change. Observed time series are from tide gauges and altimetry, as well as from reconstructions over the last 50 years. CMIP5 coupled atmosphere-ocean model output of regional sea-level and associated uncertainty estimates are merged with scenario-independent contributions from GIA and dynamic ice to provide time series of coastal sea-level projections to the end of the 21st century. We focus on better quantifying the regional departure of coastal sea level rise from its global average, identify the reasons for the regional departure, and quantify the reasons for the uncertainty in these regional projections. Many of these coastal sea level projections are lower than the global mean change in sea level due to glacial isostatic adjustment, and gravitational changes from loss of land ice and terrestrially stored ground water. In most coastal regions, local deviations from the global mean vary up to ±20 cm which, depending on the location, differ substantially in their underlying causes.

Farmer’s intended and actual adoption of climate change mitigation and adaptation strategies

Abstract: A growing body of work aims to understand the impacts of climate change on agriculture as well as farmer’s perceptions of climate change and their likeliness to adopt adapting and mitigating behaviors. Despite this, little work has considered how intention to adopt differs from actual adoption of climate change practices in agriculture. Applying the Theory of Planned Behavior we aim to assess whether different factors affect intended versus actual adoption of climate behaviors among farmers in New Zealand. Data were collected through mixed methods (37 interviews and a telephone survey of 490 farmers) in two regions of New Zealand 2010–2012. Through multiple regression models we test hypotheses related to the Theory of Planned Behavior around the role of attitudes, subjective norms, and perceived capacity in affecting intended and actual adoption. Results suggest that there are different drivers of intended and actual adoption of climate change practices. Climate change attitudes and belief is only associated with intended not actual adoption. We find no evidence that subjective norms (climate change policy support) significantly influence either intention or actual adoption. Only perceived capacity and self-efficacy were important predictors of both intended and actual adoption. These results suggest a disconnect between intended and actual behavior change and that using data about intention as a guiding factor for program and policy design may not be prudent. Furthermore, fostering perceived capacity and self-efficacy for individuals may be crucial for encouraging both intended and actual adoption of climate adapting and mitigating behaviors.

Shorter snow cover duration since 1970 in the Swiss Alps due to earlier snowmelt more than to later snow onset

Abstract: Global warming has strong impacts on snow cover, which in turn affects ecosystems, hydrological regimes and winter tourism. Only a few long-term snow series are available worldwide, especially at high elevation. Here, we analyzed several snowpack characteristics over the period 1970–2015 at eleven meteorological stations, spanning elevations from 1139 to 2540 m asl in the Swiss Alps. Snow cover duration has significantly shortened at all sites, on average by 8.9 days decade−1. This shortening was largely driven by earlier snowmelt (on average 5.8 days decade−1) and partly by later snow onset but the latter was significant in only ~30 % of the stations. On average, the snow season now starts 12 days later and ends 26 days earlier than in 1970. Overall, the annual maximum snow depth has declined from 3.9 to 10.6 % decade−1 and was reached 7.8 ± 0.4 to 12.0 ± 0.4 days decade−1 earlier, though these trends hide a high inter-annual and decadal variability. The number of days with snow on the ground has also significantly decreased at all elevations, in all regions and for all thresholds from 1 to 100 cm. Overall, our results demonstrate a marked decline in all snowpack parameters, irrespective of elevation and region, and whether for drier or wetter locations, with a pronounced shift of the snowmelt in spring, in connection with reinforced warming during this season.

Assessing vulnerability: an integrated approach for mapping adaptive capacity, sensitivity, and exposure

Abstract: Making decisions and efficiently allocating resources to reduce the vulnerability of coastal communities requires, among other things, an understanding of the factors that make a society vulnerable to climate and coastal hazards. One way of doing this is through the analysis of spatial data. We demonstrate how to apply GIS methods to spatially represent socioeconomic vulnerability in Grenada, a tropical small island developing state (SIDS) in the Eastern Caribbean. Our model combines spatial features representing variables of social sensitivity, community adaptive capacity, and community exposure to flooding in an integrated vulnerability index. We draw from the fields of climate change adaptation, disaster management, and poverty and development to select our variables enabling unique, cross sector, applications of our assessment. Mapping our results illustrates that vulnerability to flooding is not evenly distributed across the country and is not driven by the same factors in all areas of Grenada. This indicates a need for the implementation of different strategies in communities across Grenada to help effectively reduce vulnerability to climate and coastal hazards. The approach presented in this paper can be used to address national issues on climate change adaptation, disaster management, and poverty and development and more effectively utilize funds in order to reduce community vulnerability to natural hazards today and in the future.

Global warming-related tree growth decline and mortality on the north-eastern Tibetan plateau

Abstract: Semi-arid forests at the limit of their existence close to the Gobi Desert in Inner Asia might be vulnerable to warming-induced drought stress. Yet, not much is known about the impact of global-change-type droughts on these forests. Here, we show that warming-related tree mortality is recently taking place in high-elevation semi-arid Qinghai spruce (Picea crassifolia Kom.) forests of the north-eastern margin of the Tibetan Plateau (Qilian Mountains). Tree-ring samples were collected from 24 Qinghai spruce forest plots (20 m × 20 m) at three elevations (2600, 2700, 2800 m) along eight elevation transects on north-facing slopes. Three lines of evidence suggest that these forests are increasingly at risk of increased tree mortality as a consequence of global warming, (i) a strong precipitation and air humidity dependence of radial growth, (ii) increasing frequency of missing tree rings, and (iii) a rising tree mortality rate in recent decades. The recent drought episode on the north-eastern Tibetan Plateau may represent a precursor of future global-change-type drought events in large parts of Inner Asia. Warming-related tree mortality of the semi-arid forests may be interpreted as early-warning signs for the densely populated artificial oases surrounding the Gobi Desert, which largely depend on river run-off from the mountain forests on the edge of the Tibetan Plateau.

Increasing flood risk under climate change: a pan-European assessment of the benefits of four adaptation strategies

Abstract: Future flood risk in Europe is likely to increase due to a combination of climatic and socio-economic drivers. Effective adaptation strategies need to be implemented to limit the impact of river flooding on population and assets. This research builds upon a recently developed flood risk assessment framework at European scale to explore the benefits of adaptation against extreme floods. The effect of implementing four different adaptation measures is simulated in the modeling framework. Measures include the rise of flood protections, reduction of the peak flows through water retention, reduction of vulnerability and relocation to safer areas. Their sensitivity is assessed in several configurations under a high-end global warming scenario over the time range 1976–2100. Results suggest that the future increase in expected damage and population affected by river floods can be compensated through different configurations of adaptation measures. The adaptation efforts should favor measures targeted at reducing the impacts of floods, rather than trying to avoid them. Conversely, adaptation plans only based on rising flood protections have the effect of reducing the frequency of small floods and exposing the society to less-frequent but catastrophic floods and potentially long recovery processes.

Country-Specific Effects of Climate Variability on Human Migration.

Abstract: Involuntary human migration is among the social outcomes of greatest concern in the current era of global climate change. Responding to this concern, a growing number of studies have investigated the consequences of short to medium-term climate variability for human migration using demographic and econometric approaches. These studies have provided important insights, but at the same time have been significantly limited by lack of expertise in the use of climate data, access to cross-national data on migration, and attention to model specification. To address these limitations, we link data on internal and international migration over a 6-year period from 9812 origin households in Kenya, Uganda, Nigeria, Burkina Faso and Senegal to high-resolution gridded climate data from both station and satellite sources. Analyses of these data using several plausible specifications reveal that climate variability has country-specific effects on migration: Migration tends to increase with temperature anomalies in Uganda, tends to decrease with temperature anomalies in Kenya and Burkina Faso, and shows no consistent relationship with temperature in Nigeria and Senegal. Consistent with previous studies, precipitation shows weak and inconsistent relationships with migration across countries. These results challenge generalizing narratives that foresee a consistent migratory response to climate change across the globe.

A comparison of changes in river runoff from multiple global and catchment-scale hydrological models under global warming scenarios of 1 °C, 2 °C and 3 °C

Abstract: We present one of the first climate change impact assessments on river runoff that utilises an ensemble of global hydrological models (Glob-HMs) and an ensemble of catchment-scale hydrological models (Cat-HMs), across multiple catchments: the upper Amazon, Darling, Ganges, Lena, upper Mississippi, upper Niger, Rhine and Tagus. Relative changes in simulated mean annual runoff (MAR) and four indicators of high and low extreme flows are compared between the two ensembles. The ensemble median values of changes in runoff with three different scenarios of global-mean warming (1, 2 and 3 °C above pre-industrial levels) are generally similar between the two ensembles, although the ensemble spread is often larger for the Glob-HM ensemble. In addition the ensemble spread is normally larger than the difference between the two ensemble medians. Whilst we find compelling evidence for projected runoff changes for the Rhine (decrease), Tagus (decrease) and Lena (increase) with global warming, the sign and magnitude of change for the other catchments is unclear. Our model results highlight that for these three catchments in particular, global climate change mitigation, which limits global-mean temperature rise to below 2 °C above preindustrial levels, could avoid some of the hydrological hazards that could be seen with higher magnitudes of global warming.

The effects of extreme drought on climate change beliefs, risk perceptions, and adaptation attitudes

Abstract: The role of extreme weather events in shaping people’s climate change beliefs and adaptation attitudes has been extensively studied and discussed in academic literature, the popular press, and policy circles. In this manuscript, we contribute to the debate by using data from pre- and post-extreme event surveys to examine the effects of the 2012 Midwestern US drought on agricultural advisors’ climate change beliefs, adaptation attitudes, and risk perceptions. We found that neither climate change beliefs nor attitudes toward adaptation changed significantly as a result of the drought. Risk perceptions did change, however, with advisors becoming more concerned about risks from drought and pests and less concerned about risks related to flooding and ponding. Though increased risk perceptions were significantly associated with more favorable adaptation attitudes, the effects were not large enough to cause an overall shift to more favorable attitudes toward adaptation. The results suggest that extreme climate events might not cause significant shifts in climate beliefs, at least not immediately. Additionally, the results caution that policy designs that rely on increasing risk perceptions to motivate action on climate change may be overestimating the effects of extreme events on feeling at risk, at least in the context of buffered systems such as large commercial agriculture in the US.

Evaluating the stationarity assumption in statistically downscaled climate projections: is past performance an indicator of future results?

Abstract: Empirical statistical downscaling (ESD) methods seek to refine global climate model (GCM) outputs via processes that glean information from a combination of observations and GCM simulations. They aim to create value-added climate projections by reducing biases and adding finer spatial detail. Analysis techniques, such as cross-validation, allow assessments of how well ESD methods meet these goals during observational periods. However, the extent to which an ESD method’s skill might differ when applied to future climate projections cannot be assessed readily in the same manner. Here we present a “perfect model” experimental design that quantifies aspects of ESD method performance for both historical and late 21st century time periods. The experimental design tests a key stationarity assumption inherent to ESD methods – namely, that ESD performance when applied to future projections is similar to that during the observational training period. Case study results employing a single ESD method (an Asynchronous Regional Regression Model variant) and climate variable (daily maximum temperature) demonstrate that violations of the stationarity assumption can vary geographically, seasonally, and with the amount of projected climate change. For the ESD method tested, the greatest challenges in downscaling daily maximum temperature projections are revealed to occur along coasts, in summer, and under conditions of greater projected warming. We conclude with a discussion of the potential use and expansion of the perfect model experimental design, both to inform the development of improved ESD methods and to provide guidance on the use of ESD products in climate impacts analyses and decision-support applications.

Is robustness really robust? How different definitions of robustness impact decision-making under climate change

Abstract: Robust decision-making is being increasingly used to support environmental resources decisions and policy analysis under changing climate and society. In this context, a robust decision is a decision that is as much as possible insensitive to a large degree of uncertainty and ensures certain performance across multiple plausible futures. Yet, the concept of robustness is neither unique nor static. Multiple robustness metrics, such as maximin, optimism-pessimism, max regret, have been proposed in the literature, reflecting diverse optimistic/pessimistic attitudes by the decision maker. Further, these attitudes can evolve in time as a response to sequences of favorable (or adverse) events, inducing possible dynamic changes in the robustness metrics. In this paper, we explore the impact of alternative definitions of robustness and their evolution in time for a case of water resources system management under changing climate. We study the decisions of the Lake Como operator, who is called to regulate the lake by balancing irrigation supply and flood control, under an ensemble of climate change scenarios. Results show a considerable variability in the system performance across multiple robustness metrics. In fact, the mis-definition of the actual decision maker’s attitude biases the simulation of its future decisions and produces a general underestimation of the system performance. The analysis of the dynamic evolution of the decision maker’s preferences further confirms the potentially strong impact of changing robustness definition on the decision-making outcomes. Climate change impact assessment studies should therefore include the definition of robustness among the uncertain parameters of the problem in order to analyze future human decisions under uncertainty.

Towards low carbon development in China: a comparison of national and global models

Abstract: The RoSE (Roadmaps to Sustainable Energy Futures) project provides a coordinated, model-based analysis to manage the transition from carbon intensive to low carbon economies using several global integrated assessment models to explore different GHG stabilization scenarios. China TIMES provides a detailed description of the Chinese energy system that can be used to check the realism of transition scenarios for China against global models. A reference scenario with China’s target of lowering its carbon intensity by 40–45 % by 2020 compared to the 2005 level is considered, and 12 carbon constraint scenarios with different levels of carbon intensity reduction beyond 2020 are simulated by China TIMES. The results of carbon emissions pathways and energy system transitions in different scenarios are analyzed. The results from China TIMES are compared to those for both the reference and carbon policy scenarios (550 ppm CO2eq and 450 ppm CO2eq stabilization targets) for four global models, GCAM, IPAC, REMIND, and WITCH. The differences in decarbonizaton pathways across models are mainly attributed to different model structures and modeling approaches, different reference scenario definitions, different policy targets, differences in model assumptions concerning technology availability and techno-economic characteristics of the technologies, and differences in the estimation of the energy demand response to climate policy. The path towards low carbon development for China includes challenges and opportunities. Substantial efforts may be required to transform the economic development mode, to speed up innovation, R&D, and deployment of advanced low carbon technologies, to strengthen institutions, to advocate low carbon lifestyles, and to enhance international cooperation.

Rapid scale-up of negative emissions technologies: social barriers and social implications

Abstract: Negative emissions technologies have garnered increasing attention in the wake of the Paris target to curb global warming to 1.5 °C. However, much of the literature on carbon dioxide removal focuses on technical feasibility, and several significant social barriers to scale-up of these technologies have been glossed over. This paper reviews the existing literature on the social implications of rapidly ramping up carbon dioxide removal. It also explores the applicability of previous empirical social science research on intersecting topics, with examples drawn from research on first- and second-generation biofuels and forest carbon projects. Social science fieldwork and case studies of land use change, agricultural and energy system change, and technology adoption and diffusion can help in both anticipating the social implications of emerging negative emissions technologies and understanding the factors that shape trajectories of technological development. By integrating empirical research on public and producer perceptions, barriers to adoption, conditions driving new technologies, and social impacts, projections about negative emissions technologies can become more realistic and more useful to climate change policymaking.

Selecting climate simulations for impact studies based on multivariate patterns of climate change.

Abstract: In climate change impact research it is crucial to carefully select the meteorological input for impact models. We present a method for model selection that enables the user to shrink the ensemble to a few representative members, conserving the model spread and accounting for model similarity. This is done in three steps: First, using principal component analysis for a multitude of meteorological parameters, to find common patterns of climate change within the multi-model ensemble. Second, detecting model similarities with regard to these multivariate patterns using cluster analysis. And third, sampling models from each cluster, to generate a subset of representative simulations. We present an application based on the ENSEMBLES regional multi-model ensemble with the aim to provide input for a variety of climate impact studies. We find that the two most dominant patterns of climate change relate to temperature and humidity patterns. The ensemble can be reduced from 25 to 5 simulations while still maintaining its essential characteristics. Having such a representative subset of simulations reduces computational costs for climate impact modeling and enhances the quality of the ensemble at the same time, as it prevents double-counting of dependent simulations that would lead to biased statistics.

Climatic and societal impacts of a volcanic double event at the dawn of the Middle Ages

Abstract: Volcanic activity in and around the year 536 CE led to severe cold and famine, and has been speculatively linked to large-scale societal crises around the globe. Using a coupled aerosol-climate model, with eruption parameters constrained by recently re-dated ice core records and historical observations of the aerosol cloud, we reconstruct the radiative forcing resulting from a sequence of two major volcanic eruptions in 536 and 540 CE. We estimate that the decadal-scale Northern Hemisphere (NH) extra-tropical radiative forcing from this volcanic “double event” was larger than that of any period in existing reconstructions of the last 1200 years. Earth system model simulations including the volcanic forcing show peak NH mean temperature anomalies reaching more than −2 °C, and show agreement with the limited number of available maximum latewood density temperature reconstructions. The simulations also produce decadal-scale anomalies of Arctic sea ice. The simulated cooling is interpreted in terms of probable impacts on agricultural production in Europe, and implies a high likelihood of multiple years of significant decreases in crop production across Scandinavia, supporting the theory of a connection between the 536 and 540 eruptions and evidence of societal crisis dated to the mid-6th century.

Allowances for evolving coastal flood risk under uncertain local sea-level rise

Abstract: Estimates of future flood hazards made under the assumption of stationary mean sea level are biased low due to sea-level rise (SLR). However, adjustments to flood return levels made assuming fixed increases of sea level are also inadequate when applied to sea level that is rising over time at an uncertain rate. SLR allowances—the height adjustment from historic flood levels that maintain under uncertainty the annual expected probability of flooding—are typically estimated independently of individual decision-makers’ preferences, such as time horizon, risk tolerance, and confidence in SLR projections. We provide a framework of SLR allowances that employs complete probability distributions of local SLR and a range of user-defined flood risk management preferences. Given non-stationary and uncertain sea-level rise, these metrics provide estimates of flood protection heights and offsets for different planning horizons in coastal areas. We illustrate the calculation of various allowance types for a set of long-duration tide gauges along U.S. coastlines.

The relative importance of climate change and population growth for exposure to future extreme droughts

Abstract: The human consequences of drought are normally addressed in terms of “water scarcity” originating from human water use. In these terms, a common prediction to the next few decades is that population growth, not climate change, will be the dominant factor determining numbers living under such scarcity. Here we address the relative importance of increasing human caused extreme drought and increasing population for numbers of humans likely to be directly exposed in the future to such drought. Using the Standardized Precipitation Evapotranspiration Index (SPEI) in conjunction with an ensemble of 16 CMIP5 climate models we find that, by 2081-2100 under the high emissions scenario RCP 8.5, average worldwide monthly population exposed to extreme drought (SPEI < -2) will increase by 386.8 million to 472.3 million (+426.6% from the current 89.7 million). Anthropogenic climate change is responsible for approximately 230.0 million (59.5%) of that increase with population growth responsible for only 35.5 million (9.2%); the climate change-population growth interaction explains the remaining 121.1 million (31.4%). At the national level, 129 countries will experience increase in drought exposure mainly due to climate change alone; 23 countries primarily due to population growth; and 38 countries primarily due to the interaction between climate change and population growth. Given inherently large uncertainties, projections of future climate impacts should be accepted with caution especially those directed to the regional level, to future population trends, and, of course, where technological, social and security changes are possible.