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As climate change continues to alter local weather patterns, it is important to understand how people are experiencing such changes because personal experience may affect mitigation and adaptation policy preferences and behaviors. Local weather conditions are also an easily accessible source of information that, aggregated over time, may enable people to detect long-term climate trends and update their beliefs about global warming. However, motivated reasoning—the tendency to fit information to conclusions that correspond with a preexisting belief—may limit the accuracy of local weather perceptions. This paper focuses on perceptions of seasonal weather in Norway and examines evidence for motivated reasoning consistent with pre-existing beliefs about climate change, using a national panel survey combined with high-resolution seasonal climate observations. Respondents’ perceptions are sensitive to observed differences in both temperature and precipitation, but respondents are more likely to accurately perceive local precipitation than local temperature. Controlling for observed conditions, beliefs about global climate change had a large effect on perceptions of seasonal temperature, and smaller effects on perceptions of seasonal precipitation. These findings provide evidence that individual perceptions of seasonal weather are related to local conditions, but they are also likely to be motivated by beliefs about global climate change. [ABSTRACT FROM AUTHOR]

There is a growing concern that countries should reduce their dependence on fossil fuels for electricity generation and look to other cleaner technologies. Hydroelectricity is one such option. However, given that hydropower is dependent on rainfall and associated runoff for power generation, it is susceptible to both the positive and negative impacts of climate change, such as increases in temperature and changes in precipitation and runoff. In this paper, impacts on hydropower generation have been organised as either changes in long-term trends or short-term variability and shocks. These impacts could either manifest themselves as direct impacts on hydropower generation potential or as indirect impacts (or ancillary impacts) such as increased competition for water. Citing examples from around the world, this paper investigates the scale of these projected impacts, and the potential cost implication of inaction. It concludes by making recommendations for possible adaptive options to build resilience in response to local impacts. [ABSTRACT FROM AUTHOR]

Effective national and regional policy guidance on climate change adaptation relies on robust scientific evidence. This two-part series of papers develops and implements a novel scenario-neutral framework enabling an assessment of the vulnerability of flood flows in British catchments to climatic change, to underpin the development of guidance for the flood management community. In this first part, the sensitivity of the 20-year return period flood peak (RP20) to changes in precipitation (P), temperature (T) and potential evapotranspiration (PE) is systematically assessed for 154 catchments. A sensitivity domain of 4,200 scenarios is applied combining 525 and 8 sets of P and T/PE mean monthly changes, respectively, with seasonality incorporated using a single-phase harmonic function. Using the change factor method, the percentage change in RP20 associated with each scenario of the sensitivity domain is calculated, giving flood response surfaces for each catchment. Using a clustering procedure on the response surfaces, the 154 catchments are divided into nine groups: flood sensitivity types. These sensitivity types show that some catchments are (very) sensitive to changes in P but others buffer the response, while the location of catchments of the same type does not show any strong geographical pattern. These results reflect the range of hydrological processes found in Britain, and demonstrate the potential importance of catchment properties (physical and climatic) in the propagation of change in climate to change in floods, and so in characterising the sensitivity types (covered in the companion paper). [ABSTRACT FROM AUTHOR]

Interest in the impacts of climate change is ever increasing. This is particularly true of the water sector where understanding potential changes in the occurrence of both floods and droughts is important for strategic planning. Climate variability has been shown to have a significant impact on UK climate and accounting for this in future climate change projections is essential to fully anticipate potential future impacts. In this paper a new resampling methodology is developed which includes the variability of both baseline and future precipitation. The resampling methodology is applied to 13 CMIP3 climate models for the 2080s, resulting in an ensemble of monthly precipitation change factors. The change factors are applied to the Eden catchment in eastern Scotland with analysis undertaken for the sensitivity of future river flows to the changes in precipitation. Climate variability is shown to influence the magnitude and direction of change of both precipitation and in turn river flow, which are not apparent without the use of the resampling methodology. The transformation of precipitation changes to river flow changes display a degree of non-linearity due to the catchment's role in buffering the response. The resampling methodology developed in this paper provides a new technique for creating climate change scenarios which incorporate the important issue of climate variability. [ABSTRACT FROM AUTHOR]

Both statistical and dynamical downscaling methods are well established techniques to bridge the gap between the coarse information produced by global circulation models and the regional-to-local scales required by the climate change Impacts, Adaptation, and Vulnerability (IAV) communities. A number of studies have analyzed the relative merits of each technique by inter-comparing their performance in reproducing the observed climate, as given by a number of climatic indices (e.g. mean values, percentiles, spells). However, in this paper we stress that fair comparisons should be based on indices that are not affected by the calibration towards the observed climate used for some of the methods. We focus on precipitation (over continental Spain) and consider the output of eight Regional Climate Models (RCMs) from the EURO-CORDEX initiative at 0.44 resolution and five Statistical Downscaling Methods (SDMs) -analog resampling, weather typing and generalized linear models- trained using the Spain044 observational gridded dataset on exactly the same RCM grid. The performance of these models is inter-compared in terms of several standard indices -mean precipitation, 90th percentile on wet days, maximum precipitation amount and maximum number of consecutive dry days- taking into account the parameters involved in the SDM training phase. It is shown, that not only the directly affected indices should be carefully analyzed, but also those indirectly influenced (e.g. percentile-based indices for precipitation) which are more difficult to identify. We also analyze how simple transformations (e.g. linear scaling) could be applied to the outputs of the uncalibrated methods in order to put SDMs and RCMs on equal footing, and thus perform a fairer comparison. [ABSTRACT FROM AUTHOR]

This paper presents the earliest temperature observations, scheduled every 3-4 h in the 1654-1670 period, which have been recovered and analysed for the first time. The observations belong to the Medici Network, the first international network of meteorological observations, based on eleven stations, the two main ones being Florence and Vallombrosa, Italy. All observations were made with identical thermometers and operational methodology, including outdoor exposure in the shade and in the sunshine to evaluate solar heating, state of the sky, wind direction and precipitation frequency. This paper will consider only the regular temperature series taken in the shade. The observations were made with the newly invented spirit-in-glass thermometer, also known as Little Florentine Thermometer (LFT). The readings have been transformed into modern units of temperature (°C) and time (TMEC). The LFT has been analysed in detail: how it was made, its linearity, calibration and performances. Since the middle of the LIA, the climate in Florence has shown less than 0.18°C warming. However, although the yearly average showed little change, the seasonal departures are greater, i.e. warmer summers, colder winters and unstable mid seasons. The temperature in the Vallombrosa mountain station, 1,000 m a.m.s.l, apparently rose more, i.e. 1.41°C. A discussion is made on the interpretation of this finding: how much it is affected by climate change or bias. A continuous swinging of the temperature was observed in the Mediterranean area, as documented by the long instrumental observations over the 1654-2009 period. However, changes in vegetation, or exposure bias might have contributed to reduce the homogeneity of the series over the centuries. [ABSTRACT FROM AUTHOR]

The first part of this paper demonstrated the existence of bias in GCM-derived precipitation series, downscaled using either a statistical technique (here the Statistical Downscaling Model) or dynamical method (here high resolution Regional Climate Model HadRM3) propagating to river flow estimated by a lumped hydrological model. This paper uses the same models and methods for a future time horizon (2080s) and analyses how significant these projected changes are compared to baseline natural variability in four British catchments. The UKCIP02 scenarios, which are widely used in the UK for climate change impact, are also considered. Results show that GCMs are the largest source of uncertainty in future flows. Uncertainties from downscaling techniques and emission scenarios are of similar magnitude, and generally smaller than GCM uncertainty. For catchments where hydrological modelling uncertainty is smaller than GCM variability for baseline flow, this uncertainty can be ignored for future projections, but might be significant otherwise. Predicted changes are not always significant compared to baseline variability, less than 50% of projections suggesting a significant change in monthly flow. Insignificant changes could occur due to climate variability alone and thus cannot be attributed to climate change, but are often ignored in climate change studies and could lead to misleading conclusions. Existing systematic bias in reproducing current climate does impact future projections and must, therefore, be considered when interpreting results. Changes in river flow variability, important for water management planning, can be easily assessed from simple resampling techniques applied to both baseline and future time horizons. Assessing future climate and its potential implication for river flows is a key challenge facing water resource planners. This two-part paper demonstrates that uncertainty due to hydrological and climate modelling must and can be accounted for to provide sound, scientifically-based advice to decision makers. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

This paper is among the first to report on the full integration of basin-scale models that include projections of the demand and supply of water and energy for residential, commercial, industrial, and agricultural sector users. We link two widely used regional planning models that allow one to study the impact of rising climate variability on water and electricity use in Sacramento, California. Historic data combined with the current energy and water system configuration was used to assess the implications of changes in temperature and precipitation. Climate simulations suggest that electricity imports to the region would increase during hot dry spells, when regional power production is most constrained. In particular, regional imports of electricity would increase over 35 % in hot dry years, assuming a 4 °C increase in average temperature and a 25 % decrease in average precipitation. [ABSTRACT FROM AUTHOR]

The African Development Bank has called for $40 Billion USD per year over the coming decades to be provided to African countries to address development issues directly related to climate change. The current study addresses a key component of these issues, the effect of climate change on the road infrastructure of Malawi, Mozambique, and Zambia. The study incorporates a stressor-response approach to estimate the effects of projected precipitation, temperature, and flooding changes on the paved and unpaved road infrastructure of these countries. The paper highlights the result of running 425 climate scenarios for each road type and policy option from 2010 to 2050. Based on this broad analysis, it is estimated that the three southern African countries are facing a potential $596 million price tag based on median climate scenarios to maintain and repair roads as a result of damages directly related to temperature and precipitation changes from potential climate change through 2050. The challenge for policy makers is to determine the potential risk that a country is facing based on the uncertainties associated with the multiple aspects of climate change modeling. [ABSTRACT FROM AUTHOR]

Worldwide climate is likely to become more variable or extreme with increases in intense precipitation. In Mediterranean areas, climate change will increase the risks of droughts, flash floods and soil erosion. Despite rainfall intensity being a key factor in erosive processes, in these areas information on extreme rainfall intensity and the associated erosivity, based on high-temporal resolution data, is either non homogeneous or scarce. These parameters thus need to be assessed in order to highlight suitable adaptation strategies. In this paper, an hourly rainfall intensity (RI) data series is analyzed together with the corresponding 1-min rainfall intensity maximum (RIm) of 23 rainfall gauges located in Tuscany, Italy, in an area highly vulnerable to erosion. The aim is to look for temporal trends (1989-2010) in extreme rainfall intensity and erosivity. Fixed effect logistic regression shows statistically significant temporal increases in the number of RI and RIm exceedances over the 95th percentile threshold. Winter is shown to be the season with the strongest increasing trend in coastal and inland rainfall gauge groups, followed by spring for the coastal group and autumn for the inland group. Linear regressions show that in the inland group there is a temporal increase in rainfall erosivity and on a seasonal basis, the highest increase is observed in autumn. By contrast, for the coastal group this increasing trend is only detectable for spring and winter. Such an increase in rainfall erosivity and its potential continuation could have a strong adverse effect on Mediterranean land conservation. [ABSTRACT FROM AUTHOR]

This paper analyzes the meteorological drought events in Paraguay in the period of 1964 to 2011, using the Standardized Precipitation Index (SPI). The objective is to determine if the frequency and/or severity of droughts has increased or decreased in the last years, in response of climate change. They The southernmost parts of the country are affected by severe droughts producing damage to soybean and corn crop during the rainy season (October-March) especially during the summer of 2008-2009. The years of 1967, 1968, 1978, 1979, 2000 and 2008 was identified as severe to extreme drought events and coincides with La Niña event. However, the relationship between all drought events, especially those agricultural droughts and La Niña is not clear, suggesting the necessity of new research, focusing on new drivers to explain the cause of the droughts. The economy of Paraguay, based for good part on agriculture, is clearly vulnerable to droughts. Even though no undeniable increasing trend in drought frequency/severity was detected, contingency plans to diminish drought impacts ought to be elaborated. [ABSTRACT FROM AUTHOR]

West Cornwall is the most south westerly part of mainland United Kingdom with a strong maritime climate. This paper analyses the earliest archived instrumental meteorological records collected in West Cornwall (SW England). Observations were obtained from the Met Office archive (Camborne 1957-2010; Culdrose 1985-2011), Trengwainton Garden (1940-2010), and from the Royal Cornwall Polytechnic Society, (data for Falmouth (1880-1952) and Helston (1843-1888)). Homogeneity tests were used (Levene and Brown-Forsythe tests) to exclude any trends not related to climate variability. The data exhibit trends in annual mean and maximum temperatures over the timescales analysed, and show a general temperature increase in the 20th and 21st century. Annual and seasonal temperature change was found to vary locally with strongly positive trends in autumn, spring and summer seasons. Trends in precipitation are positive only for the 19th century and only for one station. Correlation with the North Atlantic Oscillation (NAO) index gives negative results for precipitation data. However correlation with the NAO index is positive with temperature, especially in the winter season. Return period analysis shows a decrease in intensity and frequency of extreme precipitation events in the post-1975 period (Camborne and Trengwainton Garden stations). Climate change in the 20th century and future continued warming is likely to have major implications on biodiversity in this region. [ABSTRACT FROM AUTHOR]

Ongoing global warming not only involves changes in temperature and the global mean; it affects more or less every part of the climate. Regional temperature changes are often greater or smaller than corresponding changes in the global mean. In some cases the direction of change may also be different. For example, temperature changes are higher over land than over the ocean. Precipitation increases in some regions but decreases in others. Changes in extreme events may differ from changes in the corresponding mean. Present scientific knowledge clearly indicates that the already observed global trend towards warmer conditions will continue and that it will be accompanied by changes in yet other aspects of climate. This paper highlights, as a brief review, aspects of our changing climate from the available scientific knowledge with a bearing on the energy sector. Its focus is on temperature and precipitation, with some consideration of wind and sea level, among others. While uncertainties remain as far as the magnitude of future global-scale changes is concerned, and even more so their many regional patterns, significant changes are foreseen in, for example, global and regional temperature and precipitation, sea level rise, and in the characteristics of various extreme events. [ABSTRACT FROM AUTHOR]

This paper discusses the coal cycle from exploration through mining to end uses and environmental remediation, primarily from the perspective of elements in the cycle that are most vulnerable to the impacts of climatic change. The differences between resource estimates are noted. Coal transport by rail, barge, and ocean-going vessels are compared. The major end-use technologies are mentioned in the context of the coal value chain. Water availability is identified as a major uncertainty that could be further complicated by climate change. The major flows that are produced by down-stream cleanup of environmental emissions are discussed in terms of the movement of bulk solids. Typical impacts of temperature change, changes in precipitation, sea level rise, and decrease in sea ice in this cycle are summarized. Finally, while noting the negative impacts of climate changes in the Arctic, the opportunities that may arise from these are also discussed. [ABSTRACT FROM AUTHOR]

The terms 'weather extremes' and 'climate extremes' are widely used in meteorology, often in relation to climate change. This paper reviews the empirical investigations into parallel changes in extreme events and climate change published in recent years and looks at their relevance for the global energy system. Empirical investigation into the correlation of extremes with global warming covers five groups: changes in temperature, precipitation, wind (storm) extremes, tropical and extra-tropical circulation phenomena. For temperature extremes, extensive analyses demonstrate that extreme hot days and nights will likely become more frequent, and extreme cold days and nights less frequent. Intense precipitation events will likely become more frequent in most continental regions. Scientific confidence in the trends of the frequency, duration, and intensity of tropical cyclones, is still low. A poleward shift is observed for extratropical cyclones, whereas no convincing tendencies of many smaller-scale phenomena, for example, tornados, or hail, can yet be detected. All these extremes have serious implications for the energy sector. [ABSTRACT FROM AUTHOR]

In this paper we analyze some caveats found in the state-of-the-art ENSEMBLES regional projections dataset focusing on precipitation over Spain, and highlight the need of a task-oriented validation of the GCM-driven control runs. In particular, we compare the performance of the GCM-driven control runs (20C3M scenario) with the ERA40-driven ones ('perfect' boundary conditions) in a common period (1961-2000). Large deviations between the results indicate a large uncertainty/bias for the particular RCM-GCM combinations and, hence, a small confidence for the corresponding transient simulations due to the potential nonlinear amplification of biases. Specifically, we found large biases for some RCM-GCM combinations attributable to RCM in-house problems with the particular GCM coupling. These biases are shown to distort the corresponding climate change signal, or 'delta', in the last decades of the 21st century, considering the A1B scenario. Moreover, we analyze how to best combine the available RCMs to obtain more reliable projections. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

This paper addresses deficiencies of stochastic Weather Generators (WGs) in terms of reproduction of low-frequency variability and extremes, as well as the unanticipated effects of changes to precipitation occurrence under climate change scenarios on secondary variables. A new weather generator (named IWG) is developed in order to resolve such deficiencies and improve WGs performance. The proposed WG is composed of three major components, including a stochastic rainfall model able to reproduce realistic rainfall series containing extremes and inter-annual monthly variability, a multivariate daily temperature model conditioned to the rainfall occurrence, and a suitable multi-variate monthly generator to fit the low-frequency variability of daily maximum and minimum temperature series. The performance of IWG was tested by comparing statistical characteristics of the simulated and observed weather data, and by comparing statistical characteristics of the simulated runoff outputs by a daily rainfall-runoff model fed by the generated and observed weather data. Furthermore, IWG outputs are compared with those of the well-known LARS-WG weather generator. The tested characteristics are a variety of different daily statistics, low-frequency variability, and distribution of extremes. It is concluded that the performance of the IWG is acceptable, better than LARS-WG in the majority of tests, especially in reproduction of extremes and low-frequency variability of weather and runoff series. [ABSTRACT FROM AUTHOR]

Little is known about climate change and its impacts for the arid coastal and mountainous regions in northern Chile. The Elqui river basin, part of the Norte Chico of Chile between 27ºS and 33ºS latitude, is located south of the hyper-arid Atacama desert. Despite water scarcity, agricultural development in this region has been enhanced by agronomic practices and the marketing of valuable products. This paper characterizes the actual climate conditions and presents an overview and analyses of past climate variability, and future possible climate trends, emphasizing those relevant to agriculture. Precipitation shows an important decrease during the first decades of the past century. Runoff shows decreasing trends for the first half of the past century and increases for 1960 to 1985. Drought appears to be increasing. Statistical downscaling was accomplished using the Long Ashton Research Station Weather Generator. Both future periods of 2011 to 2030 and 2046-65 showed trends to higher minimum and maximum temperature. The number of hot days (maximum temperature greater than or equal to 30°C) has a strong increasing trend during October to April. Even though the downscaled results for precipitation do not show trends, the continuation of the present trend of low amounts is a concern. We discuss some implications of climatic changes for agriculture and we emphasize the importance of adaptation, especially to deal with water scarcity. [ABSTRACT FROM AUTHOR]

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 km) 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. [ABSTRACT FROM AUTHOR]

Drastic changes were detected in glacial systems of the Antarctic Peninsula in the last decades. The observed phenomena comprise the disintegration of ice shelves, acceleration and thinning of glaciers, and retreat of glacier fronts. However, due to the lack of consistent systematic observations in particular of the higher parts of the glacial systems, it is difficult to predict further responses of the Antarctic Peninsula glaciers to climatic change. The present paper analyses spatial and temporal variations of changes in the dry-snow line altitude on the Antarctic Peninsula as extracted from a time series (1992–2005) of ERS-1/2 SAR and Envisat ASAR data. Upward changes in dry-snow line altitude were observed in general, and are attributed to extreme high-temperature events impacting the central plateaus of the Antarctic Peninsula and the increasing duration of warming periods. A mean decrease in dry-snow line altitude was detected on the west side of the peninsula and is identified as a response to recorded increase in precipitation and accumulation. These results validate the capability of SAR data for deriving superficial parameters of glaciers to be used as indicators of climatic changes in high-latitude regions where operational restrictions limit conventional meteorological observations. [ABSTRACT FROM AUTHOR]

This paper compares precipitation, maximum and minimum air temperature and solar radiation estimates from the Hadley Centre's HadRM3 regional climate model (RCM), (50x50 km grid cells), with observed data from 15 meteorological station in the UK, for the period 1960-90. The aim was to investigate how well the HadRM3 is able to represent weather characteristics for a historical period (hindcast) for which validation data exist. The rationale was to determine if the HadRM3 data contain systematic errors and to investigate how suitable the data are for use in climate change impact studies at particular locations. Comparing modelled and observed data helps assess and quantify the uncertainty introduced to climate impact studies. The results show that the model performs very well for some locations and weather variable combinations, but poorly for others. Maximum temperature estimations are generally good, but minimum temperature is overestimated and extreme cold events are not represented well. For precipitation, the model produces too many small events leading to a serious under estimation of the number of dry days (zero precipitation), whilst also over- or underestimating the mean annual total. Estimates represent well the temporal distribution of precipitation events. The model systematically over-estimates solar radiation, but does produce good quality estimates at some locations. It is concluded that the HadRM3 data are unsuitable for detailed (i.e. daily time step simulation model based) site-specific impacts studies in their current form. However, the close similarity between modelled and observed data for the historical case raises the potential for using simple adjustment methods and applying these to future projection data. [ABSTRACT FROM AUTHOR]

This paper aims at proposing a way to get round the intrinsic deadlocks of the economic assessment of climate change impacts (absence of consistent baseline scenario and of credible description of adaptation behaviours under uncertainty). First, we use climate scenarios from two models of the PRUDENCE project (HadRM3H and ARPEGE) to search for cities whose present climates can be considered as reasonable analogues of the future climates of 17 European cities. These analogues meet rather strict criteria in terms of monthly mean temperature, total annual precipitations and monthly mean precipitations. Second, we use these analogues as a heuristic tool to understand the main features of the adaptation required by climate change. The availability of two analogues for each city provides a useful estimate of the impact of uncertainty on the required adaptation efforts. Third, we carry out a cost assessment for various adaptation strategies, taking into account the cost of possible ill-adaptations due to wrong anticipations in a context of large uncertainty (from sunk-costs to lock-in in suboptimal adaptation choices). We demonstrate the gap between an enumerative approach under perfect expectation and a calculation accounting for uncertainty and spillover effects on economic growth. [ABSTRACT FROM AUTHOR]

This paper compares how well satellite versus weather station measurements of climate predict agricultural performance in Brazil, India, and the United States. Although weather stations give accurate measures of ground conditions, they entail sporadic observations that require interpolation where observations are missing. In contrast, satellites have trouble measuring some ground phenomenon such as precipitation but they provide complete spatial coverage of various parameters over a landscape. The satellite temperature measurements slightly outperform the interpolated ground station data but the precipitation ground measurements generally outperform the satellite surface wetness index. In India, the surface wetness index outperforms station precipitation but this may be reflecting irrigation, not climate. The results suggest that satellites provide promising measures of temperature but that ground station data may still be preferred for measuring precipitation in rural settings. [ABSTRACT FROM AUTHOR]

This study applies the Ricardian technique to estimate the effect of climate change on the smallholder agriculture sector in Sri Lanka. The main contribution of the paper is the use of household-level data to analyze long-term climate impacts on farm profitability. Household-level data allows us to control for a host of factors such as human and physical capital available to farmers as well as adaptation mechanisms at the farm level. We find that non-climate variables explain about half the variation in net revenues. However, our results suggest that climate change will have a significant impact on smallholder profitability. In particular, reductions in precipitation during key agricultural months can be devastating. At the national level, a change in net revenues of between--23% and+22% is likely depending on the climate change scenario simulated. These impacts will vary considerably across geographic areas from losses of 67% to gains that more than double current net revenues. The largest adverse impacts are anticipated in the dry zones of the North Central region and the dry zones of the South Eastern regions of Sri Lanka. On the other hand, the intermediate and wet zones are likely to benefit, mostly due to the predicted increase in rainfall. [ABSTRACT FROM AUTHOR]

Estimates of forest vegetation carbon storage in China varied due to different methods used in the assessments. In this paper, we estimated the forest vegetation carbon storage from the Fourth Forest Inventory Data (FFID) in China using a modified volume-derived method. Results showed that total carbon storage and mean carbon density of forest vegetation in China were 3.8 Pg C (about 1.1% of the global vegetation carbon stock) and 41.32 Mg/ha, respectively. In addition, based on linear multiple regression equation and factor analysis method, we analyzed contributions of biotic and abiotic factors (including mean forest age, mean annual temperature, annual precipitation, and altitude) to forest carbon storage. Our results indicated that forest vegetation carbon storage was more sensitive to changes of mean annual temperature than other factors, suggesting that global warming would seriously affect the forest carbon storage. [ABSTRACT FROM AUTHOR]

This paper reconstructs precipitation variability in the southern Canadian Cordillera over the past 3-400 years using dendroclimatological techniques. Fifty-three total ring-width (RW) chronologies, 28 earlywood (EW) and 28 latewood (LW) chronologies were developed from open-grown, low-elevation stands of Pseudotsuga meoziesii (Douglas-fir) and Pious pooderosa (ponderosa pine) across the southern Canadian Cordillera. RW, EW and LW chronologies from both species were used to develop 13 annual (prior July to current June) precipitation reconstructions across the region. The reconstructions range in length from 165 to 688 years, pass verification tests and capture 39-64% of the variance in the instrumental record. Coincident, prolonged intervals of dry conditions are estimated for the years: 1717-1732, 1839-1859, 1917-1941 and 1968-1979. Shorter dry intervals are identified between 1581-1586, 1626-1630, 1641-1653 1701-1708, 1756-1761, 1768-1772, 1793-1800, 1868-1875, 1889-1897 and 1985-1989. The historic drought of the 1920-1930s was the longest but not the most intense across this area in the last 300 years. Wet conditions occur in the majority of reconstructions for the years: 1689-1700, 1750-55, 1778-1789, 1800-1830, 1880-1890, 1898-1916 and 1942-1960. These data, in conjunction with data from adjacent areas, are used to provide the first maps of decadal precipitation anomalies for the region between 1700 and 1990. [ABSTRACT FROM AUTHOR]

This paper measures the economic impacts of climate change on China's agriculture based on the Ricardian model. By using county-level cross-sectional data on agricultural net revenue, climate, and other economic and geographical data for 1275 agriculture dominated counties, we find that under most climate change scenarios both higher temperature and more precipitation would have an overall positive impact on China's agriculture. However, the impacts vary seasonally and regionally. Autumn effect is the most positive, but spring effect is the most negative. Applying the model to five climate scenarios in the year 2050 shows that the East, the Central part, the South, the northern part of the Northeast, and the Plateau would benefit from climate change, but the Southwest, the Northwest and the southern part of the Northeast may be negatively affected. In the North, most scenarios show that they may benefit from climate change. In summary, all of China would benefit from climate change in most scenarios. [ABSTRACT FROM AUTHOR]