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1.
There is a deep disconnect between scientific and public concern about climate change. One reason is that global climate change is a fairly abstract concept with little perceived relevance, so a key challenge is to translate climate-change projections into locally concrete examples of potential impacts. Here we use climate analog analyses as an alternative method for identifying and communicating climate-change impacts. Our analysis uses multiple downscaled general circulation models for the state of Wisconsin, at 0.1 decimal degree resolution, and identifies contemporary locations in North America that are the most similar to the projected future climates for Wisconsin. We assess the uncertainties inherent in climate-change projections among greenhouse gas emission scenarios, time windows (mid-21st century vs. late 21st-century) and different combinations of climate variables. For all future scenarios and simulations, contemporary climatic analogs within North America were found for Wisconsin’s future climate. Closest analogs are primarily 200–500 km to the south-southwest of their Wisconsin reference location. Temperature has the largest effect on choice of climatic analog, but precipitation is the greatest source of uncertainty. Under the higher-end emission scenarios, the contemporary climatic analogs for Wisconsin’s end-21st-century climates are almost entirely outside the state. Climate-analog analyses offer a place-based means of assessing climate impacts that is complementary to the species-based approaches of species distributional models, and carries no assumptions about the characterization and conservatism of species niches. The analog method is simple and flexible, and can be readily extended to other regions and other environmental variables.  相似文献   

2.
Ensembles of climate model simulations are required for input into probabilistic assessments of the risk of future climate change in which uncertainties are quantified. Here we document and compare aspects of climate model ensembles from the multi-model archive and from perturbed physics ensembles generated using the third version of the Hadley Centre climate model (HadCM3). Model-error characteristics derived from time-averaged two-dimensional fields of observed climate variables indicate that the perturbed physics approach is capable of sampling a relatively wide range of different mean climate states, consistent with simple estimates of observational uncertainty and comparable to the range of mean states sampled by the multi-model ensemble. The perturbed physics approach is also capable of sampling a relatively wide range of climate forcings and climate feedbacks under enhanced levels of greenhouse gases, again comparable with the multi-model ensemble. By examining correlations between global time-averaged measures of model error and global measures of climate change feedback strengths, we conclude that there are no simple emergent relationships between climate model errors and the magnitude of future global temperature change. Algorithms for quantifying uncertainty require the use of complex multivariate metrics for constraining projections.  相似文献   

3.
This study aims to evaluate the performance of two mainstream downscaling techniques: statistical and dynamical downscaling and to compare the differences in their projection of future climate change and the resultant impact on wheat crop yields for three locations across New South Wales, Australia. Bureau of Meteorology statistically- and CSIRO dynamically-downscaled climate, derived or driven by the CSIRO Mk 3.5 coupled general circulation model, were firstly evaluated against observed climate data for the period 1980–1999. Future climate projections derived from the two downscaling approaches for the period centred on 2055 were then compared. A stochastic weather generator, LARS-WG, was used in this study to derive monthly climate changes and to construct climate change scenarios. The Agricultural Production System sIMulator-Wheat model was then combined with the constructed climate change scenarios to quantify the impact of climate change on wheat grain yield. Statistical results show that (1) in terms of reproducing the past climate, statistical downscaling performed better over dynamical downscaling in most of the cases including climate variables, their mean, variance and distribution, and study locations, (2) there is significant difference between the two downscaling techniques in projected future climate change except the mean value of rainfall across the three locations for most of the months; and (3) there is significant difference in projected wheat grain yields between the two downscaling techniques at two of the three locations.  相似文献   

4.
Ecological sensitivity: a biospheric view of climate change   总被引：2，自引：0，他引：2  
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5.
Increased understanding of the substantial threat climate change poses to agriculture has not been met with a similarly improved understanding of how best to respond. Here we examine likely shifts in crop climates in Sub-Saharan Africa under climate change to 2050, and explore the implications for agricultural adaptation, with particular focus on identifying priorities in crop breeding and the conservation of crop genetic resources. We find that for three of Africa's primary cereal crops – maize, millet, and sorghum – expected changes in growing season temperature are considerable and dwarf changes projected for precipitation, with the warmest recent temperatures on average cooler than almost 9 out of 10 expected observations by 2050. For the “novel” crop climates currently unrepresented in each country but likely extant there in 2050, we identify current analogs across the continent. The majority of African countries will have novel climates over at least half of their current crop area by 2050. Of these countries, 75% will have novel climates with analogs in the current climate of at least five other countries, suggesting that international movement of germplasm will be necessary for adaptation. A more troubling set of countries – largely the hotter Sahelian countries – will have climates with few analogs for any crop. Finally, we identify countries, such as Sudan, Cameroon, and Nigeria, whose current crop areas are analogs to many future climates but that are poorly represented in major genebanks – promising locations in which to focus future genetic resource conservation efforts.  相似文献   

6.
Reconciling food, fiber and energy production with biodiversity conservation is among the greatest challenges of the century, especially in the face of climate change. Model-based scenarios linking climate, land use and biodiversity can be exceptionally useful tools for decision support in this context. We present a modeling framework that links climate projections, private land use decisions including farming, forest and urban uses and the abundances of common birds as an indicator of biodiversity. Our major innovation is to simultaneously integrate the direct impacts of climate change and land use on biodiversity as well as indirect impacts mediated by climate change effects on land use, all at very fine spatial resolution. In addition, our framework can be used to evaluate incentive-based conservation policies in terms of land use and biodiversity over several decades. The results for our case study in France indicate that the projected effects of climate change dominate the effects of land use on bird abundances. As a conservation policy, implementing a spatially uniform payment for pastures has a positive effect in relatively few locations and only on the least vulnerable bird species.  相似文献   

7.
Changes in climate as projected by state-of-the-art climate models are likely to result in novel combinations of climate and topo-edaphic factors that will have substantial impacts on the distribution and persistence of natural vegetation and animal species. We have used multivariate techniques to quantify some of these changes; the method employed was the Multivariate Spatio-Temporal Clustering (MSTC) algorithm. We used the MSTC to quantitatively define ecoregions for the People’s Republic of China for historical and projected future climates. Using the Köppen–Trewartha classification system we were able to quantify some of the temperature and precipitation relationships of the ecoregions. We then tested the hypothesis that impacts to environments will be lower for ecoregions that retain their approximate geographic locations. Our results showed that climate in 2050, as projected from anthropogenic forcings using the Hadley Centre HadCM3 general circulation model, were sufficient to create novel environmental conditions even where ecoregions remained spatially stable; cluster number was found to be of paramount importance in detecting novelty. Continental-scale analyses are generally able to locate potentially static ecoregions but they may be insufficient to define the position of those reserves at a grid cell-by-grid cell basis.  相似文献   

8.
David R. Gray 《Climatic change》2008,87(3-4):361-383
The relationship between outbreak characteristics of the spruce budworm and the combination of climate, forest composition, and spatial location was examined in eastern Canada by the method of constrained ordination. Approximately 54% of the spatial variability in outbreak pattern, as described by a matrix of four outbreak characteristics, was explained by the spatial pattern of the climate (a matrix of six variables), forest composition (a matrix of seven variables), and spatial location (a matrix of two variables). The relationships between outbreak variables and climate variables were highlighted, and future outbreak characteristics of the spruce budworm were projected using simulations of a global circulation model for the period 2081–2100 where CO2 concentrations reach a maximum of approximately 550 ppm. Future outbreaks are predicted to be an average of approximately 6 years longer with an average of 15% greater defoliation. The methodology is described and the potential effects of climate change on landscape-scale outbreaks of the insect are discussed.  相似文献   

9.
Climate change is predicted to cause voluntary and forced internal migration on an unprecedented scale in the coming decades. Yet, research on host communities that will be on the front lines in receiving the climate migrants has thus far been a neglected area within climate change research. Inspired by previous research on psychological distance’s impact on people’s behavior and attitudes, this article develops a conceptual framework proposing that spatial, attitudinal, experiential, and social proximities between migrants and host community members are central to understanding how attitudes toward internal climate migrants form and develop. Using multivariate regression analysis, the article applies the framework to a survey conducted among over 630 long-term residents in Satkhira District of Bangladesh, one of the most climate-exposed districts in the country. Supporting our hypotheses, we find evidence that host–migrant proximities shape attitudes toward internal climate migrants. Although the host community’s capacity to receive migrants matters for attitudes toward them, the results for the proximity variables underscore that these attitudes are profoundly relational, positional, and complex. In particular, we provide evidence that shorter spatial distance to highly exposed areas and attitudinal distance to fellow citizens in terms of values and worldviews improve host community members’ attitudes toward migrants. Further, the results for social proximity bring out the positional nature of attitudes, as they become more negative when socio-economic differences to migrants increase.  相似文献   

10.
Regional or local scale hydrological impact studies require high resolution climate change scenarios which should incorporate some assessment of uncertainties in future climate projections. This paper describes a method used to produce a multi-model ensemble of multivariate weather simulations including spatial–temporal rainfall scenarios and single-site temperature and potential evapotranspiration scenarios for hydrological impact assessment in the Dommel catchment (1,350 km2) in The Netherlands and Belgium. A multi-site stochastic rainfall model combined with a rainfall conditioned weather generator have been used for the first time with the change factor approach to downscale projections of change derived from eight Regional Climate Model (RCM) experiments for the SRES A2 emission scenario for the period 2071–2100. For winter, all downscaled scenarios show an increase in mean daily precipitation (catchment average change of +9% to +40%) and typically an increase in the proportion of wet days, while for summer a decrease in mean daily precipitation (−16% to −57%) and proportion of wet days is projected. The range of projected mean temperature is 7.7°C to 9.1°C for winter and 19.9°C to 23.3°C for summer, relative to means for the control period (1961–1990) of 3.8°C and 16.8°C, respectively. Mean annual potential evapotranspiration is projected to increase by between +17% and +36%. The magnitude and seasonal distribution of changes in the downscaled climate change projections are strongly influenced by the General Circulation Model (GCM) providing boundary conditions for the RCM experiments. Therefore, a multi-model ensemble of climate change scenarios based on different RCMs and GCMs provides more robust estimates of precipitation, temperature and evapotranspiration for hydrological impact assessments, at both regional and local scale.  相似文献   

11.
As the global climate warms due to increasing greenhouse gases, the regional climate of the Gulf of Mexico and Caribbean region will also change. This study presents the latest estimates of the expected changes in temperature, precipitation, tropical cyclone activity, and sea level. Changes in temperature and precipitation are derived from climate model simulations produced for the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR4), by comparing projections for the mid- and late-21st century to the late 20th century and assuming a “middle-of-the-road” scenario for future greenhouse gas emissions. Regional simulations from the North America Regional Climate Change Program (NARCCAP) are used to corroborate the IPCC AR4 rainfall projections over the US portion of the domain. Changes in tropical cyclones and sea level are more uncertain, and our understanding of these variables has changed more since IPCC AR4 than in the case of temperature and precipitation. For these quantities, the current state of knowledge is described based on the recent peer-reviewed literature.  相似文献   

12.
Climate is an important resource for many types of tourism. One of several metrics for the suitability of climate for sightseeing is Mieczkowski’s “Tourism Climatic Index” (TCI), which summarizes and combines seven climate variables. By means of the TCI, we analyse the present climate resources for tourism in Europe and projected changes under future climate change. We use daily data from five regional climate models and compare the reference period 1961–1990 to the A2 scenario in 2071–2100. A comparison of the TCI based on reanalysis data and model simulations for the reference period shows that current regional climate models capture the important climatic patterns. Currently, climate resources are best in Southern Europe and deteriorate with increasing latitude and altitude. With climate change the latitudinal band of favourable climate is projected to shift northward improving climate resources in Northern and Central Europe in most seasons. Southern Europe’s suitability for sightseeing tourism drops strikingly in the summer holiday months but is partially compensated by considerable improvements between October and April.  相似文献   

13.
Statistical downscaling methods are commonly used to address the scale mismatch between coarse resolution Global Climate Model output and the regional or local scales required for climate change impact assessments. The effectiveness of a downscaling method can be measured against four broad criteria: consistency with the existing baseline data in terms of means, trends and distributional characteristics; consistency with the broader scale climate data used to generate the projections; the degree of transparency and repeatability; and the plausibility of results produced. Many existing downscaling methods fail to fulfil all of these criteria. In this paper we examine a block bootstrap simulation technique combined with a quantile prediction and matching method for simulating future daily climate data. By utilising this method the distributional properties of the projected data will be influenced by the distribution of the observed data, the trends in predictors derived from the Global Climate Models and the relationship of these predictors to the observed data. Using observed data from several climate stations in Vanuatu and Fiji and out-of-sample validation techniques, we show that the method is successful at projecting various climate characteristics including the variability and auto-correlation of daily temperature and rainfall, the correlations between these variables and between spatial locations. This paper also illustrates how this novel method can produce more effective point scale projections and a more credible alternative to other approaches in the Pacific region.  相似文献   

14.
Observing the full range of climate change impacts at the local scale is difficult. Predicted rates of change are often small relative to interannual variability, and few locations have sufficiently comprehensive long-term records of environmental variables to enable researchers to observe the fine-scale patterns that may be important to understanding the influence of climate change on biological systems at the taxon, community, and ecosystem levels. We examined a 50-year meteorological and hydrological record from the Hubbard Brook Experimental Forest (HBEF) in New Hampshire, an intensively monitored Long-Term Ecological Research site. Of the examined climate metrics, trends in temperature were the most significant (ranging from 0.7 to 1.3 °C increase over 40–50 year records at 4 temperature stations), while analysis of precipitation and hydrologic data yielded mixed results. Regional records show generally similar trends over the same time period, though longer-term (70–102 year) trends are less dramatic. Taken together, the results from HBEF and the regional records indicate that the climate has warmed detectably over 50 years, with important consequences for hydrological processes. Understanding effects on ecosystems will require a diversity of metrics and concurrent ecological observations at a range of sites, as well as a recognition that ecosystems have existed in a directionally changing climate for decades, and are not necessarily in equilibrium with the current climate.  相似文献   

15.
This study presents a model-based risk assessment of wheat production under projected climate change by 2080 in eight locations of South Australia. The vulnerability of wheat production under future climate change was quantitatively evaluated via a risk analysis in which the identification of critical yield thresholds applies. Research results show that risk (conditional probability of not exceeding the critical yield thresholds) increased more or less across all locations under the most likely climate change. Wheat production in drier areas such as Minnipa, Orroroo and Wanbi will not be economically viable under the most likely climate change. Intensive studies on adaptation are now required.  相似文献   

16.
Climate change impacts food production systems, particularly in locations with large, vulnerable populations. Elevated greenhouse gases (GHG), as well as land cover/land use change (LCLUC), can influence regional climate dynamics. Biophysical factors such as topography, soil type, and seasonal rainfall can strongly affect crop yields. We used a regional climate model derived from the Regional Atmospheric Modeling System (RAMS) to compare the effects of projected future GHG and future LCLUC on spatial variability of crop yields in East Africa. Crop yields were estimated with a process-based simulation model. The results suggest that: (1) GHG-influenced and LCLUC-influenced yield changes are highly heterogeneous across this region; (2) LCLUC effects are significant drivers of yield change; and (3) high spatial variability in yield is indicated for several key agricultural sub-regions of East Africa. Food production risk when considered at the household scale is largely dependent on the occurrence of extremes, so mean yield in some cases may be an incomplete predictor of risk. The broad range of projected crop yields reflects enormous variability in key parameters that underlie regional food security; hence, donor institutions’ strategies and investments might benefit from considering the spatial distribution around mean impacts for a given region. Ultimately, global assessments of food security risk would benefit from including regional and local assessments of climate impacts on food production. This may be less of a consideration in other regions. This study supports the concept that LCLUC is a first-order factor in assessing food production risk.  相似文献   

17.
The Niger River is the third largest river in the African continent. Nine riparian countries share its basin, which rank all among the world’s thirty poorest. Existing challenges in West Africa, including endemic poverty, inadequate infrastructure and weak adaptive capacity to climate variability, make the region vulnerable to climate change. In this study, a risk-based methodology is introduced and demonstrated for the analysis of climate change impacts on planned infrastructure investments in water resources systems in the Upper and Middle Niger River Basin. The methodology focuses on identifying the vulnerability of the Basin’s socio-economic system to climate change, and subsequently assessing the likelihood of climate risks by using climate information from a multi-run, multi-GCM ensemble of climate projections. System vulnerabilities are analyzed in terms of performance metrics of hydroelectricity production, navigation, dry and rainy season irrigated agriculture, flooding in the Inner Delta of the Niger and the sustenance of environmental flows. The study reveals low to moderate risks in terms of stakeholder-defined threshold levels for most metrics in the 21st Century. The highest risk levels were observed for environmental flow targets. The findings indicate that the range of projected changes in an ensemble of CMIP3 GCM projections imply only relatively low risks of unacceptable climate change impacts on the present large-scale infrastructure investment plan for the Basin.  相似文献   

18.
Climate and land use patterns are expected to change dramatically in the coming century, raising concern about their effects on wildfire patterns and subsequent impacts to human communities. The relative influence of climate versus land use on fires and their impacts, however, remains unclear, particularly given the substantial geographical variability in fire-prone places like California. We developed a modeling framework to compare the importance of climatic and human variables for explaining fire patterns and structure loss for three diverse California landscapes, then projected future large fire and structure loss probability under two different climate (hot-dry or warm-wet) and two different land use (rural or urban residential growth) scenarios. The relative importance of climate and housing pattern varied across regions and according to fire size or whether the model was for large fires or structure loss. The differing strengths of these relationships, in addition to differences in the nature and magnitude of projected climate or land use change, dictated the extent to which large fires or structure loss were projected to change in the future. Despite this variability, housing and human infrastructure were consistently more responsible for explaining fire ignitions and structure loss probability, whereas climate, topography, and fuel variables were more important for explaining large fire patterns. For all study areas, most structure loss occurred in areas with low housing density (from 0.08 to 2.01 units/ha), and expansion of rural residential land use increased structure loss probability in the future. Regardless of future climate scenario, large fire probability was only projected to increase in the northern and interior parts of the state, whereas climate change had no projected impact on fire probability in southern California. Given the variation in fire-climate relationships and land use effects, policy and management decision-making should be customized for specific geographical regions.  相似文献   

19.
Regional climate change patterns identified by cluster analysis   总被引：1，自引：0，他引：1  
Climate change caused by anthropogenic greenhouse emissions leads to impacts on a global and a regional scale. A quantitative picture of the projected changes on a regional scale can help to decide on appropriate mitigation and adaptation measures. In the past, regional climate change results have often been presented on rectangular areas. But climate is not bound to a rectangular shape and each climate variable shows a distinct pattern of change. Therefore, the regions over which the simulated climate change results are aggregated should be based on the variable(s) of interest, on current mean climate as well as on the projected future changes. A cluster analysis algorithm is used here to define regions encompassing a similar mean climate and similar projected changes. The number and the size of the regions depend on the variable(s) of interest, the local climate pattern and on the uncertainty introduced by model disagreement. The new regions defined by the cluster analysis algorithm include information about regional climatic features which can be of a rather small scale. Comparing the regions used so far for large scale regional climate change studies and the new regions it can be shown that the spacial uncertainty of the projected changes of different climate variables is reduced significantly, i.e. both the mean climate and the expected changes are more consistent within one region and therefore more representative for local impacts.  相似文献   

20.
Nearly all of Ethiopia’s agriculture is dependent on rainfall, particularly the amount and seasonal occurrence. Future climate change predictions agree that changes in rainfall, temperature, and seasonality will impact Ethiopia with dramatic consequences. When, where, and how these changes will transpire has not been adequately addressed. The objective of our study was to model how projected climate change scenarios will spatially and temporally impact cereal production, a dietary staple for millions of Ethiopians. We used Maxent software fit with crop data collected from household surveys and bioclimatic variables from the WorldClim database to develop spatially explicit models of crop production in Ethiopia. Our results were extrapolated to three climate change projections (i.e., Canadian Centre for Climate Modeling and Analysis, Hadley Centre Coupled Model v3, and Commonwealth Scientific and Industrial Research Organization), each having two emission scenarios. Model evaluations indicated that our results had strong predictability for all four cereal crops with area under the curve values of 0.79, 0.81, 0.79, and 0.83 for teff, maize, sorghum, and barley, respectively. As expected, bioclimatic variables related to rainfall were the greatest predictors for all four cereal crops. All models showed similar decreasing spatial trends in cereal production. In addition, there were geographic shifts in land suitability which need to be accounted for when assessing overall vulnerability to climate change. The ability to adapt to climate change will be critical for Ethiopia’s agricultural system and food security. Spatially explicit models will be vital for developing early warning systems, adaptive strategies, and policy to minimize the negative impacts of climate change on food production.  相似文献   

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