156 research outputs found

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

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    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

    Assessment of uncertainty in river flow projections for the Mekong River using multiple GCMs and hydrological models

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    Hydrological model-related uncertainty is often ignored within climate change hydrological impact assessments. A MIKE SHE model is developed for the Mekong using the same data as an earlier semi-distributed, conceptual model (SLURP). The model is calibrated and validated using discharge at 12 gauging stations. Two sets of climate change scenarios are investigated. The first is based on a 2 °C increase in global mean temperature (the hypothesised threshold of ‘dangerous’ climate change), as simulated by seven GCMs. There are considerable differences in scenario discharge between GCMs, ranging from catchment-wide increases in mean discharge (up to 12.7%; CCCMA CGCM31, NCAR CCSM30), decreases (up to 21.6% in the upper catchments; CSIRO Mk30, IPSL CM4), and spatially varying responses (UKMO HadCM3 and HadGEM1, MPI ECHAM5). Inter-GCM differences are largely driven by differences in precipitation. The second scenario set (HadCM3, increases in global mean temperature of 1–6 °C) shows consistently greater discharge (maximum: 28.7%) in the upper catchment as global temperature increases, primarily due to increasing precipitation. Further downstream, discharge is strongly influenced by increasing PET, which outweighs impacts of elevated upstream precipitation and causes consistent discharge reductions for higher temperatures (maximum: −5.3% for the main Mekong). MIKE SHE results for all scenarios are compared with those from the SLURP catchment model and the Mac-PDM.09 global hydrological model. Although hydrological model-related uncertainty is evident, its magnitude is smaller than that associated with choice of GCM. In most cases, the three hydrological models simulate the same direction of change in mean discharge. Mac-PDM.09 simulates the largest discharge increases when they occur, which is responsible for some differences in direction of change at downstream gauging stations for some scenarios, especially HadCM3. Inter-hydrological model differences are likely attributed to alternative model structures, process representations and PET methods (Linacre for MIKE SHE and SLURP, Penman–Monteith for Mac-PDM.09)

    Projecting Future Heat-Related Mortality under Climate Change Scenarios: A Systematic Review

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    Background: Heat-related mortality is a matter of great public health concern, especially in the light of climate change. Although many studies have found associations between high temperatures and mortality, more research is needed to project the future impacts of climate change on heat-related mortality

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

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    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

    Global-scale climate impact functions: the relationship between climate forcing and impact

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    Although there is a strong policy interest in the impacts of climate change corresponding to different degrees of climate change, there is so far little consistent empirical evidence of the relationship between climate forcing and impact. This is because the vast majority of impact assessments use emissions-based scenarios with associated socio-economic assumptions, and it is not feasible to infer impacts at other temperature changes by interpolation. This paper presents an assessment of the global-scale impacts of climate change in 2050 corresponding to defined increases in global mean temperature, using spatially-explicit impacts models representing impacts in the water resources, river flooding, coastal, agriculture, ecosystem and built environment sectors. Pattern-scaling is used to construct climate scenarios associated with specific changes in global mean surface temperature, and a relationship between temperature and sea level used to construct sea level rise scenarios. Climate scenarios are constructed from 21 climate models to give an indication of the uncertainty between forcing and response. The analysis shows that there is considerable uncertainty in the impacts associated with a given increase in global mean temperature, due largely to uncertainty in the projected regional change in precipitation. This has important policy implications. There is evidence for some sectors of a non-linear relationship between global mean temperature change and impact, due to the changing relative importance of temperature and precipitation change. In the socio-economic sectors considered here, the relationships are reasonably consistent between socio-economic scenarios if impacts are expressed in proportional terms, but there can be large differences in absolute terms. There are a number of caveats with the approach, including the use of pattern-scaling to construct scenarios, the use of one impacts model per sector, and the sensitivity of the shape of the relationships between forcing and response to the definition of the impact indicator

    Cross‐scale intercomparison of climate change impacts simulated by regional and global hydrological models in eleven large river basins

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    Ideally, the results from models operating at different scales should agree in trend direction and magnitude of impacts under climate change. However, this implies that the sensitivity to climate variability and climate change is comparable for impact models designed for either scale. In this study, we compare hydrological changes simulated by 9 global and 9 regional hydrological models (HM) for 11 large river basins in all continents under reference and scenario conditions. The foci are on model validation runs, sensitivity of annual discharge to climate variability in the reference period, and sensitivity of the long-term average monthly seasonal dynamics to climate change. One major result is that the global models, mostly not calibrated against observations, often show a considerable bias in mean monthly discharge, whereas regional models show a better reproduction of reference conditions. However, the sensitivity of the two HM ensembles to climate variability is in general similar. The simulated climate change impacts in terms of long-term average monthly dynamics evaluated for HM ensemble medians and spreads show that the medians are to a certain extent comparable in some cases, but have distinct differences in other cases, and the spreads related to global models are mostly notably larger. Summarizing, this implies that global HMs are useful tools when looking at large-scale impacts of climate change and variability. Whenever impacts for a specific river basin or region are of interest, e.g. for complex water management applications, the regional-scale models calibrated and validated against observed discharge should be used

    Integrating personality research and animal contest theory: aggressiveness in the green swordtail <i>Xiphophorus helleri</i>

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    &lt;p&gt;Aggression occurs when individuals compete over limiting resources. While theoretical studies have long placed a strong emphasis on context-specificity of aggression, there is increasing recognition that consistent behavioural differences exist among individuals, and that aggressiveness may be an important component of individual personality. Though empirical studies tend to focus on one aspect or the other, we suggest there is merit in modelling both within-and among-individual variation in agonistic behaviour simultaneously. Here, we demonstrate how this can be achieved using multivariate linear mixed effect models. Using data from repeated mirror trials and dyadic interactions of male green swordtails, &lt;i&gt;Xiphophorus helleri&lt;/i&gt;, we show repeatable components of (co)variation in a suite of agonistic behaviour that is broadly consistent with a major axis of variation in aggressiveness. We also show that observed focal behaviour is dependent on opponent effects, which can themselves be repeatable but were more generally found to be context specific. In particular, our models show that within-individual variation in agonistic behaviour is explained, at least in part, by the relative size of a live opponent as predicted by contest theory. Finally, we suggest several additional applications of the multivariate models demonstrated here. These include testing the recently queried functional equivalence of alternative experimental approaches, (e. g., mirror trials, dyadic interaction tests) for assaying individual aggressiveness.&lt;/p&gt
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