Statistical downscaling of daily climate variables for climate change impact assessment over New South Wales, Australia

This paper outlines a new statistical downscaling method based on a stochastic weather generator. The monthly climate projections from global climate models (GCMs) are first downscaled to specific sites using an inverse distance-weighted interpolation method. A bias correction procedure is then applied to the monthly GCM values of each site. Daily climate projections for the site are generated by using a stochastic weather generator, WGEN. For downscaling WGEN parameters, historical climate data from 1889 to 2008 are sorted, in an ascending order, into 6 climate groups. The WGEN parameters are downscaled based on the linear and non-linear relationships derived from the 6 groups of historical climates and future GCM projections. The overall averaged confidence intervals for these significant linear relationships between parameters and climate variables are 0.08 and 0.11 (the range of these parameters are up to a value of 1.0) at the observed mean and maximum values of climate variables, revealing a high confidence in extrapolating parameters for downscaling future climate. An evaluation procedure is set up to ensure that the downscaled daily sequences are consistent with monthly GCM output in terms of monthly means or totals. The performance of this model is evaluated through the comparison between the distributions of measured and downscaled climate data. Kruskall-Wallis rank (K-W) and Siegel-Tukey rank sum dispersion (S-T) tests are used. The results show that the method can reproduce the climate statistics at annual, monthly and daily time scales for both training and validation periods. The method is applied to 1062 sites across New South Wales (NSW) for 9 GCMs and three IPCC SRES emission scenarios, B1, A1B and A2, for the period of 1900–2099. Projected climate changes by 7 GCMs are also analyzed for the A2 emission scenario based on the downscaling results.     

A weather-resolving index for assessing the impact of climate change on tourism related climate resources

This study develops and tests a Modified Climate Index for Tourism (MCIT) utilizing more than 50 years of hourly temperature, wind and significant weather data from contrasting climatic regions, Florida and Alaska. The index measures climate as a tourism resource by combining several tourism-related climate elements. It improves previous methods by incorporating variables that are more relevant to tourism activities, by addressing the overriding nature of some conditions, and by incorporating hourly observations rather than simple daily averages. The MCIT was tested using hourly weather observations from King Salmon, Alaska and Orlando, Florida. The results show that average temperature alone is not sufficient to represent tourism climate resources. For example, at both the Florida and Alaskan sites, showers and thunderstorms are more limiting factors than temperature during much of the year. When applied to past climate data, the proposed MCIT generates meaningful results that capture tourism-related climate variations and trends, including (a) the increasingly favorable tourism conditions in Alaska due to a lengthening of the warm season and (b) a decrease of ideal climatic conditions in central Florida due to the increased summer temperatures. Thus, the index has the potential to become a useful quantitative tool to be used in conjunction with climate models to predict the nature and magnitude of the impact of anticipated climate changes on tourism.     

Adapting to climate change: Public water supply in England and Wales

This paper describes an assessment of the ways in which water supply companies in England and Wales are adapting to climate change, evaluated in the context of a model of the adaptation process. The four components of the model are (i) awareness of and concern about the potential impacts of climate change, (ii) adaptation strategy, (iii) the concept of an adaptation space from which options are selected, and (iv) the notion that three groups of factors influence awareness, strategy and option selection: susceptibility to change, internal characteristics of the organisation, and regulatory and market context.Public water supply in England and Wales is provided by private sector companies, subject to environmental and economic regulation. Hydrological simulations suggest that climate change has the potential to reduce the reliability of supply sources over the next few decades. The industry in December 2004 completed a review of investment requirements over the next five years.Awareness of climate change is high in the water industry, but by developing assessment procedures and incorporating them into the investment review the regulators forced companies to consider explicitly the potential impacts of climate change in a consistent and rigorous manner. These analyses combined climate change with other pressures on water resources, and in practice companies did not attribute specific investment decisions or proposals to climate change or indeed any other individual drivers. The broad strategy adopted by all water supply companies – to maintain standards of service – is determined by regulatory controls and market considerations, but the degree of concern about the impacts of climate change and precise adaptation options necessary to address supply-demand imbalances varied between water supply companies, reflecting local geographic conditions. The water supply companies and regulators have different perspectives on the relative merits of supply-side and demand-side measures, reflecting different organisational priorities.The 2004 investment review determined that no specific actions were necessary to deal with future climate change, but that measures set in place – in terms of methodologies and investment in investigations into specific resource developments – provided a sound foundation for more specific actions in the next investment review in five years time. The paper concludes by summarising the factors assisting and constraining adaptation over the next few decades.     

Potential impact of climate change on the water availability of South Saskatchewan River Basin

The potential hydrologic impact of climatic change on three sub-basins of the South Saskatchewan River Basin (SSRB) within Alberta, namely, Oldman, Bow and Red Deer River basins was investigated using the Modified Interactions Soil-Biosphere-Atmosphere (MISBA) land surface scheme of Kerkhoven and Gan (Advances in Water Resources 29:808–826 2006). The European Centre for Mid-range Weather Forecasts global re-analysis (ERA-40) climate data, Digital Elevation Model of the National Water Research Institute, land cover data and a priori soil parameters from the Ecoclimap global data set were used to drive MISBA to simulate the runoff of SSRB. Four SRES scenarios (A21, A1FI, B21 and B11) of four General Circulation Models (CCSRNIES, CGCM2, ECHAM4 and HadCM3) of IPCC were used to adjust climate data of the 1961–1990 base period (climate normal) to study the effect of climate change on SSRB over three 30-year time periods (2010–2039, 2040–2069, 2070–2099). The model results of MISBA forced under various climate change projections of the four GCMs with respect to the 1961–1990 normal show that SSRB is expected to experience a decrease in future streamflow and snow water equivalent, and an earlier onset of spring runoff despite of projected increasing trends in precipitation over the 21st century. Apparently the projected increase in evaporation loss due to a warmer climate over the 21st century will offset the projected precipitation increase, leading to an overall decreasing trend in the basin runoff of SSRB. Finally, a Gamma probability distribution function was fitted to the mean annual maximum flow and mean annual mean flow data simulated for the Oldman, Bow and Red Deer River Basins by MISBA to statistically quantify the possible range of uncertainties associated with SRES climate scenarios projected by the four GCMs selected for this study.     

A co-evolutionary approach to climate change impact assessment: Part I. Integrating socio-economic and climate change scenarios

Climate change policies currently pay disproportionately greater attention to the mitigation of climate change through emission reductions strategies than to adaptation measures. Realising that the world is already committed to some global warming, policy makers are beginning to turn their attention to the challenge of preparing society to adapt to the unfolding impacts at the local level. This two-part article presents an integrated, or `co-evolutionary', approach to using scenarios in adaptation and vulnerability assessment. Part I explains how climate and social scenarios can be integrated to better understand the inter-relationships between a changing climate and the dynamic evolution of social, economic and political systems. The integrated scenarios are then calibrated so that they can be applied `bottom up’ to local stakeholders in vulnerable sectors of the economy. Part I concludes that a co-evolutionary approach (1) produces a more sophisticated and dynamic account of the potential feedbacks between natural and human systems; (2) suggests that sustainability indicators are both a potentially valuable input to and an output of integrated scenario formulation and application. Part II describes how a broadly representative sample of public, private and voluntary organisations in the East Anglian region of the UK responded to the scenarios, and identifies future research priorities.     

Double exposure: assessing the impacts of climate change within the context of economic globalization

This paper considers synergisms between the impacts of two global processes, climate change and economic globalization. Both processes entail long-term changes that will have differential impacts throughout the world. Despite widespread recognition that there will be “winners” and “losers” with both climate change and globalization, the two issues are rarely examined together. In this paper, we introduce the concept of double exposure as a framework for examining the simultaneous impacts of climate change and globalization. Double exposure refers to the fact that certain regions, sectors, ecosystems and social groups will be confronted both by the impacts of climate change, and by the consequences of globalization. By considering the joint impacts of the two processes, new sets of winners and losers emerge.     

Regional climate change experiments over southern South America. I: present climate

We present an analysis of a regional simulation of present-day climate (1981–1990) over southern South America. The regional model MM5 was nested within time-slice global atmospheric model experiments conducted by the HadAM3H model. We evaluate the capability of the model in simulating the observed climate with emphasis on low-level circulation patterns and surface variables, such as precipitation and surface air mean, maximum and minimum temperatures. The regional model performance was evaluated in terms of seasonal means, seasonal cycles, interannual variability and extreme events. Overall, the regional model is able to capture the main features of the observed mean surface climate over South America, its seasonal evolution and the regional detail due to topographic forcing. The observed regional patterns of surface air temperatures (mean, maxima and minima) are well reproduced. Biases are mostly within 3°C, temperature being overestimated over central Argentina and underestimated in mountainous regions during all seasons. Biases in northeastern Argentina and southeastern Brazil are positive during austral spring season and negative in other seasons. In general, maximum temperatures are better represented than minimum temperatures. Warm bias is larger during austral summer for maximum temperature and during austral winter for minimum temperature, mainly over central Argentina. The broad spatial pattern of precipitation and its seasonal evolution are well captured; however, the regional model overestimates the precipitation over the Andes region in all seasons and in southern Brazil during summer. Precipitation amounts are underestimated over the La Plata basin from fall to spring. Extremes of precipitation are better reproduced by the regional model compared with the driving model. Interannual variability is well reproduced too, but strongly regulated by boundary conditions, particularly during summer months. Overall, taking into account the quality of the simulation, we can conclude that the regional model is capable in reproducing the main regional patterns and seasonal cycle of surface variables. The present reference simulation constitutes the basis to examine the climate change simulations resulting from the A2 and B2 forcing scenarios which are being reported in a separate study.     

Improving impact assessment methods: climate change and the health of indigenous Australians

Climate impact assessment has evolved as a range of tools, critical in evaluating potential impacts of climate change. This field has been driven by global concerns and is dominated by western scientific philosophies. Amid claims that it is failing in its role of informing policy, key issues implicated in application of assessment techniques are considered for the case of indigenous health in northern Australia. An argument is made for local scale studies which foster stakeholder involvement and focus on social, cultural and political landscapes; studies which produce outcomes of relevance to stakeholders and planners, as well as scientists and researchers.     

Twentieth century north atlantic climate change. Part I: assessing determinism

Boreal winter North Atlantic climate change since 1950 is well described by a trend in the leading spatial structure of variability, known as the North Atlantic Oscillation (NAO). Through diagnoses of ensembles of atmospheric general circulation model (AGCM) experiments, we demonstrate that this climate change is a response to the temporal history of sea surface temperatures (SSTs). Specifically, 58 of 67 multi-model ensemble members (87%), forced with observed global SSTs since 1950, simulate a positive trend in a winter index of the NAO, and the spatial pattern of the multi-model ensemble mean trend agrees with that observed. An ensemble of AGCM simulations with only tropical SST forcing further suggests that variations in these SSTs are of primary importance. The probability distribution function (PDF) of 50-year NAO index trends from the forced simulations are, moreover, appreciably different from the PDF of a control simulation with no interannual SST variability, although chaotic atmospheric variations are shown to yield substantial 50-year trends. Our results thus advance the view that the observed linear trend in the winter NAO index is a combination of a strong tropically forced signal and an appreciable noise component of the same phase. The changes in tropical rainfall of greatest relevance include increased rainfall over the equatorial Indian Ocean, a change that has likely occurred in nature and is physically consistent with the observed, significant warming trend of the underlying sea surface.     

Dissecting indices of aridity for assessing the impacts of global climate change

There is great interest in understanding how climate change will impact aridity through the interaction of precipitation changes with rising temperatures. The Aridity Index (AI), Climatic Moisture Deficit (CMD), and Climatic Moisture Surplus (CMS) are metrics commonly used to quantify and map patterns in aridity and water cycling. Here we show that these metrics have different patterns of change under future climate—based on an ensemble of nine general circulation climate models—and the different metrics are appropriate for different purposes. Based on these differences between the metrics, we propose that aridity can be dissected into three different types—hydrological (CMS), agricultural (CMD), and meteorological. In doing this, we propose a novel modified version of the Aridity Index, called AI+, that can be useful for assessing changes in meteorological aridity. The AI?+?is based on the same ratio between precipitation and evapotranspiration as the traditional AI, but unlike the traditional AI, the AI?+?only accounts for changes to precipitation during months when precipitation is less than reference/potential evapotranspiration (i.e. there is a deficit). Moreover, we show that the traditional AI provides a better estimate of change in moisture surplus driven by changes to precipitation during the wet season, rather than changes in deficit that occur during the drier seasons. These results show that it is important to select the most appropriate metric for assessing climate driven changes in aridity.     

Assessing the influence of climate model uncertainty on EU-wide climate change impact indicators

Despite an increasing understanding of potential climate change impacts in Europe, the associated uncertainties remain a key challenge. In many impact studies, the assessment of uncertainties is underemphasised, or is not performed quantitatively. A key source of uncertainty is the variability of climate change projections across different regional climate models (RCMs) forced by different global circulation models (GCMs). This study builds upon an indicator-based NUTS-2 level assessment that quantified potential changes for three climate-related hazards: heat stress, river flood risk, and forest fire risk, based on five GCM/RCM combinations, and non-climatic factors. First, a sensitivity analysis is performed to determine the fractional contribution of each single input factor to the spatial variance of the hazard indicators, followed by an evaluation of uncertainties in terms of spread in hazard indicator values due to inter-model climate variability, with respect to (changes in) impacts for the period 2041–70. The results show that different GCM/RCM combinations lead to substantially varying impact indicators across all three hazards. Furthermore, a strong influence of inter-model variability on the spatial patterns of uncertainties is revealed. For instance, for river flood risk, uncertainties appear to be particularly high in the Mediterranean, whereas model agreement is higher for central Europe. The findings allow for a hazard-specific identification of areas with low vs. high model agreement (and thus confidence of projected impacts) within Europe, which is of key importance for decision makers when prioritising adaptation options.     

气候变化对农业的影响研究进展

本文着重介绍了近几年气候变化对农业影响的最新研究进展，其中包括气象因子对农业生态环境的影响、二氧化碳浓度增加、气候变化对农作物光合作用、生长发育、产量、品质、种类、地理分布、种植制度、农业灾害以及农业成本等领域最新研究进展，最后指出了存在的问题以及研究展望。     

A comparative assessment of the potential impact of climate change on the ski industry in New Zealand and Australia

In this paper we assess the impact of climate change, at a micro-scale for a selection of four sites in New Zealand and Australia. These sites are representative of the key destination ski regions. In contrast to previous work, our work will for the first time, allow for a direct comparison between these two countries and enable both an estimate of the absolute impacts at a given site, as well as the relative impacts between the two countries. This direct comparison is possible because we have used exactly the same snow model, the same 3 global climate models (GCMs) and the same techniques to calibrate the model for all locations. We consider the changes in natural snow at these locations for the 2030–2049 and 2080–2099 time periods, for one mid-range emissions scenario (A1B). This future scenario is compared to simulations of current, 1980–1999, snow at these locations. We did not consider the snowmaking or economic components of the ski industry vulnerability, only the modelled changes in the natural snow component. At our New Zealand sites, our model indicates that by the 2040s there will be on average between 90 % and 102 % of the current maximum snow depth (on 31 August) and by the 2090s this will be on average reduced to between 46 % and 74 %. In Australia, our models estimates that by the 2040s there will be on average between 57 % and 78 % of the current maximum snow depth and by the 2090s this will be on average further reduced to between 21 % and 29 %. In terms of days with snowdepths equal to or exceeding a ski industry useable levels of 0.30 m, at our lowest elevation, and most sensitive sites, we observe a change from 125 days (current) to 99–126 (2040s) and 52–110 (2090s) in New Zealand. In Australia, a reduction from 94 to 155 days (current) to 81–114 (2040s) and 0–75 (2090s) is observed. In each case the changes are highly depended on the GCM used to drive the climate change scenario. While the absolute changes will have direct impacts at each location, so too will the relative changes with respect to future potential Australia–New Zealand tourism flows, and beyond. Our study provides an approach by which other regions or countries with climate sensitive tourism enterprises could assess the relative impacts and therefore the potential wider ranging ramifications with respect to destination attractiveness.     

Agreeing to disagree: uncertainty management in assessing climate change, impacts and responses by the IPCC

Dealing consistently with risk and uncertainty across the IPCC reports is a difficult challenge. Huge practical difficulties arise from the Panel’s scale and interdisciplinary context, the complexity of the climate change issue and its political context. The key question of this paper is if the observed differences in the handling of uncertainties by the three IPCC Working Groups can be clarified. To address this question, the paper reviews a few key issues on the foundations of uncertainty analysis, and summarizes the history of the treatment of uncertainty by the IPCC. One of the key findings is that there is reason to agree to disagree: the fundamental differences between the issues covered by the IPCC’s three interdisciplinary Working Groups, between the type of information available, and between the dominant paradigms of the practitioners, legitimately lead to different approaches. We argue that properly using the IPCC’s Guidance Notes for Lead Authors for addressing uncertainty, adding a pedigree analysis for key findings, and particularly communicating the diverse nature of uncertainty to the users of the assessment would increase the quality of the assessment. This approach would provide information about the nature of the uncertainties in addition to their magnitude and the confidence assessors have in their findings.     

气候变化对农业的影响研究进展

本文着重介绍了近几年气候变化对农业影响的最新研究进展,其中包括气象因子对农业生态环境的影响、二氧化碳浓度增加、气候变化对农作物光合作用、生长发育、产量、品质、种类、地理分布、种植制度、农业灾害以及农业成本等领域最新研究进展,最后指出了存在的问题以及研究展望.     

Evaluation of three simulation approaches for assessing yield of rainfed sunflower in a Mediterranean environment for climate change impact modelling

The determination of the impact of climate change on crop yield at a regional scale requires the development of new modelling methodologies able to generate accurate yield estimates with reduced available data. In this study, different simulation approaches for assessing yield have been evaluated. In addition to two well-known models (AquaCrop and Stewart function), a methodological proposal considering a simplified approach using an empirical model (SOM) has been included in the analysis. This empirical model was calibrated using rainfed sunflower experimental field data from three sites located in Andalusia, southern Spain, and validated using two additional locations, providing very satisfactory results compared with the other models with higher data requirements. Thus, only requiring weather data (accumulated rainfall from the beginning of the season fixed on September 1st, and maximum temperature during flowering) the approach accurately described the temporal and spatial yield variability observed (RMSE?=?391 kg ha^?1). The satisfactory results for assessing yield of sunflower under semi-arid conditions obtained in this study demonstrate the utility of empirical approaches with few data requirements, providing an excellent decision tool for climate change impact analyses at a regional scale, where available data is very limited.     

Climate change impact assessment: the role of climate extremes in crop yield simulation

This work was aimed at assessing the role of climate extremes in climate change impact assessment of typical winter and summer Mediterranean crops by using Regional Circulation Model (RCM) outputs as drivers of a modified version of the CropSyst model. More specifically, climate change effects were investigated on sunflower (Helianthus annuus L.) and winter wheat (Triticum aestivum L.) development and yield under the A2 and B2 scenarios of the IPCC Special Report on Emissions Scenarios (SRES). The direct impact of extreme climate events (i.e. heat stress at anthesis stage) was also included. The increase in both mean temperatures and temperature extremes under A2 and B2 scenarios (2071?C2100) resulted in: a general advancement of the main phenological stages, shortening of the growing season and an increase in the frequency of heat stress during anthesis with respect to the baseline (1961?C1990). The potential impact of these changes on crop yields was evaluated. It was found that winter and summer crops may possess a different fitting capacity to climate change. Sunflower, cultivated in the southern regions of the Mediterranean countries, was more prone to the direct effect of heat stress at anthesis and drought during its growing cycle. These factors resulted in severe yield reduction. In contrast, the lower frequency of heat stress and drought allowed the winter wheat crop to attain increased yields with respect to the baseline period. It can be concluded that the impact of extreme events should be included in crop-modelling approaches, otherwise there is the risk of underestimating crop yield losses, which in turn would result in the application of incorrect policies for coping with climate change.     

Future changes of the atmospheric composition and the impact of climate change

The development of the future atmospheric chemical composition is investigated with respect to NO _y and O₃ by means of the off‐line coupled dynamic‐chemical general circulation model ECHAM3/CHEM. Two time slice experiments have been performed for the years 1992 and 2015, which include changes in sea surface temperatures, greenhouse gas concentrations, emissions of CFCs, NO _x and other species, i.e., the 2015 simulation accounts for changes in chemically relevant emissions and for a climate change and its impact on air chemistry. The 2015 simulation clearly shows a global increase in ozone except for large areas of the lower stratosphere, where no significant changes or even decreases in the ozone concentration are found. For a better understanding of the importance of (A) emissions like NO _x and CFCs, (B) future changes of air temperature and water vapour concentration, and (C) other dynamical parameters, like precipitation and changes in the circulation, diabatic circulation, stratosphere‐troposphere‐exchange, the simulation of the future atmosphere has been performed stepwise. This method requires a climate‐chemistry model without interactive coupling of chemical species. Model results show that the direct effect of emissions (A) plays a major rôle for the composition of the future atmosphere, but they also clearly show that climate change (B and C) has a significant impact and strongly reduces the NO _y and ozone concentration in the lower stratosphere.