Impacts of socio-economic and climate change scenarios on wetlands: linking water resource and biodiversity meta-models

A meta-modelling approach has been adopted to link simulations of low and high water flows with simulations of suitable climate space for a selection of fen and bog species with differing drought and flood tolerance. The linked meta-models were used to examine the impacts of socio-economic and climate change scenarios on wetlands in two contrasting regions of the UK. The hydrological model shows that low and high flows are sensitive to climate change and to the regional distribution of abstractions and discharges. Where there are large changes in urbanisation, flows are more sensitive to socio-economic change. The changes in high flows have little impact on the species selected, but changes in low flows result in a number of areas becoming marginal or unsuitable due to dryness. At the regional scale, adaptation options appear to be limited and mostly involve, for surface water-influenced wetlands, increased water imports (either directly through increased non-consumptive water demand or indirectly through river augmentation), which may not be consistent with the socio-economic scenario or be feasible. This paper shows, therefore, that changes in hydrological regime are important for the future of wetlands and that these may depend as much on the future socio-economic situation as the projected changes in climate.     

Towards the Construction of Climate Change Scenarios

Climate impacts assessments need regional scenarios of climate change for a wide range of projected emissions. General circulation models (GCMs) are the most promising approach to providing such information, but as yet there is considerable uncertainty in their regional projections and they are still too costly to run for a large number of emission scenarios. Simpler models have been used to estimate global-mean temperature changes under a range of scenarios. In this paper we investigate whether a fixed pattern from a GCM experiment scaled by global-mean temperature changes from a simple model provides an acceptable estimate of the regional climate change over a range of scenarios. Changes estimated using this approximate approach are evaluated by comparing them with results from ensembles of a coupled ocean-atmosphere model. Five specific emissions scenarios are considered. For increases in greenhouse gases only, the 'error' in annual mean temperature for the cases considered is smaller than the sampling error due to the model's internal variability. The method may break down for scenarios of stabilisation of concentrations, because the patterns change as the model approaches equilibrium. The inclusion of large local perturbations due to sulphate aerosols can lead to significant deviations of the temperature pattern from that obtained using greenhouse gases alone. Combining separate patterns for the responses to greenhouse gases and aerosols may improve the accuracy of approximation. Finally, the accuracy of the scaling approach is more difficult to assess for deriving changes in regional precipitation because many of the regional changes are not statistically significant in the climate change projections considered here. If precipitation changes are only marginally significant in other models, the apparent disagreement between different models may be as much due to sampling error as to genuine differences in model response.     

Implications of CO2 global warming on great lakes ice cover

Statistical ice cover models were used to project daily mean basin ice cover and annual ice cover duration for Lakes Superior and Erie. Models were applied to a 1951–80 base period and to three 30-year steady double carbon dioxide (2 × CO₂) scenarios produced by the Geophysical Fluid Dynamics Laboratory (GFDL), the Goddard Institute of Space Studies (GISS), and the Oregon State University (OSU) general circulation models. Ice cover estimates were made for the West, Central, and East Basins of Lake Erie and for the West, East, and Whitefish Bay Basins of Lake Superior. Average ice cover duration for the 1951– 80 base period ranged from 13 to 16 weeks for individual lake basins. Reductions in average ice cover duration under the three 2 × CO₂ scenarios for individual lake basins ranged from 5 to 12 weeks for the OSU scenario, 8 to 13 weeks for the GISS scenario, and 11 to 13 weeks for GFDL scenario. Winters without ice formation become common for Lake Superior under the GFDL scenario and under all three 2 × CO₂ scenarios for the Central and East Basins of Lake Erie. During an average 2 × CO₂ winter, ice cover would be limited to the shallow areas of Lakes Erie and Superior. Because of uncertainties in the ice cover models, the results given here represent only a first approximation and are likely to represent an upper limit of the extent and duration of ice cover under the climate change projected by the three 2 × CO₂scenarios. Notwithstanding these limitations, ice cover projected by the 2 × CO₂ scenarios provides a preliminary assessment of the potential sensitivity of the Great Lakes ice cover to global warming. Potential environmental and socioeconomic impacts of a 2 × CO₂ warming include year-round navigation, change in abundance of some fish species in the Great Lakes, discontinuation or reduction of winter recreational activities, and an increase in winter lake evaporation.     

Climate change scenarios of heat waves in Central Europe and their uncertainties

The study examines climate change scenarios of Central European heat waves with a focus on related uncertainties in a large ensemble of regional climate model (RCM) simulations from the EURO-CORDEX and ENSEMBLES projects. Historical runs (1970–1999) driven by global climate models (GCMs) are evaluated against the E-OBS gridded data set in the first step. Although the RCMs are found to reproduce the frequency of heat waves quite well, those RCMs with the coarser grid (25 and 50 km) considerably overestimate the frequency of severe heat waves. This deficiency is improved in higher-resolution (12.5 km) EURO-CORDEX RCMs. In the near future (2020–2049), heat waves are projected to be nearly twice as frequent in comparison to the modelled historical period, and the increase is even larger for severe heat waves. Uncertainty originates mainly from the selection of RCMs and GCMs because the increase is similar for all concentration scenarios. For the late twenty-first century (2070–2099), a substantial increase in heat wave frequencies is projected, the magnitude of which depends mainly upon concentration scenario. Three to four heat waves per summer are projected in this period (compared to less than one in the recent climate), and severe heat waves are likely to become a regular phenomenon. This increment is primarily driven by a positive shift of temperature distribution, but changes in its scale and enhanced temporal autocorrelation of temperature also contribute to the projected increase in heat wave frequencies.     

SIMULATION OF REGIONAL CLIMATE OVER CHINA WITH CHINESE REGIONAL CLIMATE MODEL

In this paper,we present the results simulated with the Chinese regional climate model nestedin NCAR CCM1 GCM through one-way nesting approach.The model has been run for 14 months.The NCAR CCM1(1992)is at rhomboidal truncation(R15),while the horizontal resolution ofthe Chinese regional climate model is 100 km.It is found that the Chinese regional climate modelhas some advantages in simulating the surface air temperature and precipitation over the generalclimate model,because of the improved land surface parameterization.     

Climate change in the 21st century simulated by HadGEM2-AO under representative concentration pathways

We present climate responses of Representative Concentration Pathways (RCPs) using the coupled climate model HadGEM2-AO for the Coupled Model Intercomparison Project phase 5 (CMIP5). The RCPs are selected as standard scenarios for the IPCC Fifth Assessment Report and these scenarios include time paths for emissions and concentrations of greenhouse gas and aerosols and land-use/land cover. The global average warming and precipitation increases for the last 20 years of the 21st century relative to the period 1986-2005 are +1.1°C/+2.1% for RCP2.6, +2.4°C/+4.0% for RCP4.5, +2.5°C/+3.3% for RCP6.0 and +4.1°C/+4.6% for RCP8.5, respectively. The climate response on RCP 2.6 scenario meets the UN Copenhagen Accord to limit global warming within two degrees at the end of 21st century, the mitigation effect is about 3°C between RCP2.6 and RCP8.5. The projected precipitation changes over the 21st century are expected to increase in tropical regions and at high latitudes, and decrease in subtropical regions associated with projected poleward expansions of the Hadley cell. Total soil moisture change is projected to decrease in northern hemisphere high latitudes and increase in central Africa and Asia whereas near-surface soil moisture tends to decrease in most areas according to the warming and evaporation increase. The trend and magnitude of future climate extremes are also projected to increase in proportion to radiative forcing of RCPs. For RCP 8.5, at the end of the summer season the Arctic is projected to be free of sea ice.     

A regional climate model downscaling projection of China future climate change

Climate changes over China from the present (1990–1999) to future (2046–2055) under the A1FI (fossil fuel intensive) and A1B (balanced) emission scenarios are projected using the Regional Climate Model version 3 (RegCM3) nests with the National Center for Atmospheric Research (NCAR) Community Climate System Model (CCSM). For the present climate, RegCM3 downscaling corrects several major deficiencies in the driving CCSM, especially the wet and cold biases over the Sichuan Basin. As compared with CCSM, RegCM3 produces systematic higher spatial pattern correlation coefficients with observations for precipitation and surface air temperature except during winter. The projected future precipitation changes differ largely between CCSM and RegCM3, with strong regional and seasonal dependence. The RegCM3 downscaling produces larger regional precipitation trends (both decreases and increases) than the driving CCSM. Contrast to substantial trend differences projected by CCSM, RegCM3 produces similar precipitation spatial patterns under different scenarios except autumn. Surface air temperature is projected to consistently increase by both CCSM and RegCM3, with greater warming under A1FI than A1B. The result demonstrates that different scenarios can induce large uncertainties even with the same RCM-GCM nesting system. Largest temperature increases are projected in the Tibetan Plateau during winter and high-latitude areas in the northern China during summer under both scenarios. This indicates that high elevation and northern regions are more vulnerable to climate change. Notable discrepancies for precipitation and surface air temperature simulated by RegCM3 with the driving conditions of CCSM versus the model for interdisciplinary research on climate under the same A1B scenario further complicated the uncertainty issue. The geographic distributions for precipitation difference among various simulations are very similar between the present and future climate with very high spatial pattern correlation coefficients. The result suggests that the model present climate biases are systematically propagate into the future climate projections. The impacts of the model present biases on projected future trends are, however, highly nonlinear and regional specific, and thus cannot be simply removed by a linear method. A model with more realistic present climate simulations is anticipated to yield future climate projections with higher credibility.     

Assessing the strength of regional changes in near-surface climate associated with a global warming of 2°C

In this study, the strength of the regional changes in near-surface climate associated with a global warming of 2°C with respect to pre-industrial times is assessed, distinguishing between 26 different regions. Also, the strength of these regional climate changes is compared to the strength of the respective changes associated with a markedly stronger global warming of 4.5°C. The magnitude of the regional changes in climate is estimated by means of a normalized regional climate change index, which considers changes in the mean as well as changes in the interannual variability of both near-surface temperature and precipitation. The study is based on two sets of four ensemble simulations with the ECHAM5/MPI-OM coupled climate model, each starting from different initial conditions. In one set of simulations (1860–2200), the greenhouse gas concentrations and sulphate aerosol load have been prescribed according to observations until 2000 and according to the SRES A1B scenario after 2000. In the other set of simulations (2020–2200), the greenhouse gas concentrations and sulphate aerosol load have been prescribed in such a way that the simulated global warming does not exceed 2°C with respect to pre-industrial times. The study reveals the strongest changes in near-surface climate in the same regions for both scenarios, i.e., the Sahara, Northern Australia, Southern Australia and Amazonia. The regions with the weakest changes in near-surface climate, on the other hand, vary somewhat between the two scenarios except for Western North America and Southern South America, where both scenarios show rather weak changes. The comparison between the magnitude of the regional changes in near-surface climate for the two scenarios reveals relatively strong changes in the 2°C-stabilization scenario at high northern latitudes, i.e., Northeastern Europe, Alaska and Greenland, and in Amazonia. Relatively weak regional climate changes in this scenario, on the other hand, are found for Eastern Asia, Central America, Central South America and Southern South America. The ratios between the regional changes in the near-surface climate for the two scenarios vary considerably between different regions. This illustrates a limitation of obtaining regional changes in near-surface climate associated with a particular scenario by means of scaling the regional changes obtained from a widely used “standard” scenario with the ratio of the changes in the global mean temperature projected by these two scenarios.     

Creating regional climate change scenarios over southern South America for the 2020’s and 2050’s using the pattern scaling technique: validity and limitations

Dynamical downscaling of global climate simulations is the most adequate tool to generate regional projections of climate change. This technique involves at least a present climate simulation and a simulation of a future scenario, usually at the end of the twenty first century. However, regional projections for a variety of scenarios and periods, the 2020s or the 2050s, are often required by the impact community. The pattern scaling technique is used to estimate information on climate change for periods and scenarios not simulated by the regional model. We based our study on regional simulations performed over southern South America for present climate conditions and two emission scenarios at the end of the twenty first century. We used the pattern scaling technique to estimate mean seasonal changes of temperature and precipitation for the 2020s and the 2050s. The validity of the scalability assumptions underlying the pattern scaling technique for estimating near future regional climate change scenarios over southern South America is assessed. The results show that the pattern scaling works well for estimating mean temperature changes for which the regional changes are linearly related to the global mean temperature changes. For precipitation changes, the validity of the scalability assumption is weaker. The errors of estimating precipitation changes are comparable to those inherent to the regional model and to the projected changes themselves.     

Sensitivity Studies of the Impacts of Climate Change on White Nile Flows

Several exploratory studies are presented on the sensitivity of the water balance of the White Nile to climate change, using both observed and stochastic time series to drive the models. Example results are presented using various assumed climate change scenarios and results from a General Circulation Model (GCM). The relative merits and shortcomings of each modelling approach are also discussed. A simple analytical model for Lake Victoria is also used to illustrate some of the overall features of the lake's likely response. Particular difficulties with the White Nile system are that, due to the huge area of open water in the basin, transient responses to short-lived events can occur over timescales comparable with those for which long term climate change impacts are being studied, and predicted changes in flows are extremely sensitive to estimates for the rainfall and evaporation at lake and swamp surfaces. Of the modelling approaches considered, the network simulation approach with stochastic inputs is recommended as a way of smoothing out these transient effects, and assessing the uncertainty in the results due to inaccuracies in the data, the model parameters and the climate change predictions. The paper concludes with a brief discussion of some other areas of uncertainty in the hydrological modelling of White Nile flows and possible alternative external forcing mechanisms for flows in the next few decades.     

Uncertainties in projected impacts of climate change on European agriculture and terrestrial ecosystems based on scenarios from regional climate models

The uncertainties and sources of variation in projected impacts of climate change on agriculture and terrestrial ecosystems depend not only on the emission scenarios and climate models used for projecting future climates, but also on the impact models used, and the local soil and climatic conditions of the managed or unmanaged ecosystems under study. We addressed these uncertainties by applying different impact models at site, regional and continental scales, and by separating the variation in simulated relative changes in ecosystem performance into the different sources of uncertainty and variation using analyses of variance. The crop and ecosystem models used output from a range of global and regional climate models (GCMs and RCMs) projecting climate change over Europe between 1961–1990 and 2071–2100 under the IPCC SRES scenarios. The projected impacts on productivity of crops and ecosystems included the direct effects of increased CO₂ concentration on photosynthesis. The variation in simulated results attributed to differences between the climate models were, in all cases, smaller than the variation attributed to either emission scenarios or local conditions. The methods used for applying the climate model outputs played a larger role than the choice of the GCM or RCM. The thermal suitability for grain maize cultivation in Europe was estimated to expand by 30–50% across all SRES emissions scenarios. Strong increases in net primary productivity (NPP) (35–54%) were projected in northern European ecosystems as a result of a longer growing season and higher CO₂ concentrations. Changing water balance dominated the projected responses of southern European ecosystems, with NPP declining or increasing only slightly relative to present-day conditions. Both site and continental scale models showed large increases in yield of rain-fed winter wheat for northern Europe, with smaller increases or even decreases in southern Europe. Site-based, regional and continental scale models showed large spatial variations in the response of nitrate leaching from winter wheat cultivation to projected climate change due to strong interactions with soils and climate. The variation in simulated impacts was smaller between scenarios based on RCMs nested within the same GCM than between scenarios based on different GCMs or between emission scenarios.     

On the simulation of Laurentian Great Lakes water levels under projections of global climate change

A new method is proposed to estimate future net basin supplies and lake levels for the Laurentian Great Lakes based on GCM projections of global climate change. The method first dynamically downscales the GCM simulation with a regional climate model, and then bias—corrects the simulated net basin supply in order to be used directly in a river—routing/lake level scheme. This technique addresses two weaknesses in the traditional approach, whereby observed sequences of climate variables are perturbed with fixed ratios or differences derived directly from GCMs in order to run evaporation and runoff models. Specifically, (1) land surface—atmosphere feedback processes are represented, and (2) changes in variability can be analyzed with the new approach. The method is demonstrated with a single, high resolution simulation, where small changes in future mean lake levels for all the upper Great Lakes are found, and an increase in seasonal range—especially for Lake Superior—is indicated. Analysis of a small ensemble of eight lower resolution regional climate model simulations supports these findings. In addition, a direct comparison with the traditional approach based on the same GCM projections used as the driving simulations in this ensemble shows that the new method indicates smaller declines in level for all the upper Great Lakes than has been reported previously based on the traditional method, though median differences are only a few centimetres in each case.     

The AVOID programme’s new simulations of the global benefits of stringent climate change mitigation

Quantitative simulations of the global-scale benefits of climate change mitigation are presented, using a harmonised, self-consistent approach based on a single set of climate change scenarios. The approach draws on a synthesis of output from both physically-based and economics-based models, and incorporates uncertainty analyses. Previous studies have projected global and regional climate change and its impacts over the 21st century but have generally focused on analysis of business-as-usual scenarios, with no explicit mitigation policy included. This study finds that both the economics-based and physically-based models indicate that early, stringent mitigation would avoid a large proportion of the impacts of climate change projected for the 2080s. However, it also shows that not all the impacts can now be avoided, so that adaptation would also therefore be needed to avoid some of the potential damage. Delay in mitigation substantially reduces the percentage of impacts that can be avoided, providing strong new quantitative evidence for the need for stringent and prompt global mitigation action on greenhouse gas emissions, combined with effective adaptation, if large, widespread climate change impacts are to be avoided. Energy technology models suggest that such stringent and prompt mitigation action is technologically feasible, although the estimated costs vary depending on the specific modelling approach and assumptions.     

Impact of reservoir operation and climate change on the hydrological regime of the Sesan and Srepok Rivers in the Lower Mekong Basin

The transboundary Sesan and Srepok sub-basins (2S) are the “hot-spot” areas for reservoir development in the Lower Mekong region, with 12 reservoirs built in the Vietnam territory. This study examines the impacts of reservoir operations in Vietnam and projected climate change on the downstream hydrologic regime of the 2S Rivers by jointly applying the Soil Water Assessment Tool (SWAT) and Water Evaluation and Planning (WEAP) models. Different scenarios of reservoir operation are considered and simulated to assess their impact on annual, seasonal, and monthly flow regimes under maximum hydropower capacity generation with and without taking into account the minimum flow requirement downstream near the Vietnam border with Cambodia. The precipitation and temperature projections from the high-resolution regional climate model HadGEM3-RA under two Representative Concentration Pathways, 4.5 and 8.5, of HadGEM2-AO are used as future climate change scenarios for the impact assessment. The study results show that reservoir operation leads to an increase in the dry season stream flows and a decrease in the wet season stream flows. The monthly flow regime exhibits considerable changes for both the Sesan and Srepok Rivers but with different magnitudes and patterns of increase and decrease. Climate change is likely to induce considerable changes in stream flows, though these changes are comparatively lower than those caused by reservoir operation. Climate change is likely to have both counterbalancing and reinforcing effects over the impact of reservoir operation, reducing changes during dry season but increasing changes in most of the other months.     

USE OF A STOCHASTIC WEATHER GENERATOR IN THE DEVELOPMENT OF CLIMATE CHANGE SCENARIOS

Climate change scenarios with a high spatial and temporal resolution are required in the evaluation of the effects of climate change on agricultural potential and agricultural risk. Such scenarios should reproduce changes in mean weather characteristics as well as incorporate the changes in climate variability indicated by the global climate model (GCM) used. Recent work on the sensitivity of crop models and climatic extremes has clearly demonstrated that changes in variability can have more profound effects on crop yield and on the probability of extreme weather events than simple changes in the mean values. The construction of climate change scenarios based on spatial regression downscaling and on the use of a local stochastic weather generator is described. Regression downscaling translated the coarse resolution GCM grid-box predictions of climate change to site-specific values. These values were then used to perturb the parameters of the stochastic weather generator in order to simulate site-specific daily weather data. This approach permits the incorporation of changes in the mean and variability of climate in a consistent and computationally inexpensive way. The stochastic weather generator used in this study, LARS-WG, has been validated across Europe and has been shown to perform well in the simulation of different weather statistics, including those climatic extremes relevant to agriculture. The importance of downscaling and the incorporation of climate variability are demonstrated at two European sites where climate change scenarios were constructed using the UK Met. Office high resolution GCM equilibrium and transient experiments.     

Paleo-reconstructed net basin supply scenarios and their effect on lake levels in the upper great lakes

Paleo-reconstructed hydrologic records offer the potential to evaluate water resources system performance under conditions that may be more extreme than seen in the historical record. This study uses a stochastic simulation framework consisting of a non-homogeneous Markov chain model (NHMM) to simulate the climate state using Palmer Drought Severity Index (PDSI)-reconstructed data, and K-nearest neighbor (K-NN) to resample observational net basin supply magnitudes for the Great Lakes of North America. The method was applied to generate 500 plausible simulations, each with 100 years of monthly net basin supply for the Upper Great Lakes, to place the observed data into a longer temporal context. The range of net basin supply sequences represents what may have occurred in the past 1,000 years and which can occur in future. The approach was used in evaluation of operational plans for regulation of Lake Superior outflows with implications for lake levels of Superior, Michigan, Huron and Erie, and their interconnecting rivers. The simulations generally preserved the statistics of the observed record while providing new variability statistics. The framework produced a variety of high and low net basin supply sequences that provide a broader estimate of the likelihood of extreme lake levels and their persistence than with the historical record. The method does not rely on parametrically generated net basin supply values unlike parametric stochastic simulation techniques, yet still generates new variability through the incorporation of the paleo-record. The process described here generated new scenarios that are plausible based on the paleo and historic record. The evaluation of Upper Great Lakes regulation plans, subject to these scenarios, was used to evaluate robustness of the regulation plans. While the uncertain future climate cannot be predicted, one can evaluate system performance on a wide range of plausible climate scenarios.     

Climate Change Scenarios for the Hudson Bay Region: An Intermodel Comparison

General circulation models (GCMs) are unanimous in projecting warmer temperatures in an enhanced CO₂ atmosphere, with amplification of this warming in higher latitudes. The Hudson Bay region, which is located in the Arctic and subarctic regions of Canada, should therefore be strongly influenced by global warming. In this study, we compare the response of Hudson Bay to a transient warming scenario provided by six-coupled atmosphere-ocean models. Our analysis focuses on surface temperature, precipitation, sea-ice coverage, and permafrost distribution. The results show that warming is expected to peak in winter over the ocean, because of a northward retreat of the sea-ice cover. Also, a secondary warming peak is observed in summer over land in the Canadian and Australian-coupled GCMs, which is associated with both a reduction in soil moisture conditions and changes in permafrost distribution. In addition, a relationship is identified between the retreat of the sea-ice cover and an enhancement of precipitation over both land and oceanic surfaces. The response of the sea-ice cover and permafrost layer to global warming varies considerably among models and thus large differences are observed in the projected regional increase in temperature and precipitation. In view of the important feedbacks that a retreat of the sea-ice cover and the distribution of permafrost are likely to play in the doubled and tripled CO₂ climates of Hudson Bay, a good representation of these two parameters is necessary to provide realistic climate change scenarios. The use of higher resolution regional climate model is recommended to develop scenarios of climate change for the Hudson Bay region.     

Extreme precipitation over the Maritime Alps and associated weather regimes simulated by a regional climate model: Present-day and future climate scenarios

Summary We use the regional climate model RegCM nested within time-slice atmospheric general circulation model experiments to investigate the possible changes of intense and extreme precipitation over the French Maritime Alps in response to global climate change. This is a region with complex orography where heavy and/or extended precipitation episodes induced catastrophic floods during the last decades. Output from a 30-year simulation of present-day climate (1961–1990) is first analysed and compared with NCEP reanalysed 700 hPa geopotential heights (Z700) and daily precipitation observations from the Alpine Precipitation Climatology (1966–1999). Two simulations under forcing from the A2 and B2 IPCC emission scenarios for the period 2071–2100 are used to investigate projected changes in extreme precipitation for our region of interest. In general, the model overestimates the annual cycle of precipitation. The climate change projections show some increase of precipitation, mostly outside the warm period for the B2 scenario, and some increase in the variability of the annual precipitation totals for the A2 scenario. The model reproduces the main observed patterns of the spatial leading EOFs in the Z700 field over the Atlantic-European domain. The simulated large scale circulation (LSC) variability does not differ significantly from that of the reanalysis data provided the EOFs are computed on the same domain. Two similar clusters of LSC corresponding to heavy precipitation days were identified for both simulated and observed data and their patterns do not change significantly in the climate change scenarios. The analysis of frequency histograms of extreme indices shows that the control simulation systematically underestimates the observed heavy precipitation expressed as the 90^th percentile of rainday amounts in all seasons except summer and better reproduces the greatest 5-day precipitation accumulation. The main hydrological changes projected for the Maritime Alps consist of an increase of most intense wet spell precipitation during winters for both scenarios and during autumn for the B2 scenario. Case studies of heavy precipitation events show that the RegCM is capable to reproduce the physical mechanisms responsible for heavy precipitation over our region of interest.     

Social,environmental and health vulnerability to climate change in the Brazilian Northeastern Region

A regional vulnerability study in relation to the projected patterns of climate change (A2 and B2 scenarios) was developed for the Brazilian Northeastern region. An aggregated Vulnerability Index was constructed for each of the nine States of the region, based on the following information: population projections; climate-induced migration scenarios; disease trends; desertification rates; economic projections (GDP and employment) and projections for health care costs. The results obtained shall subsidize public policies for the protection of the human population from the projected impacts of regional changes in climate patterns.     

Past and future changes in climate and hydrological indicators in the US Northeast

To assess the influence of global climate change at the regional scale, we examine past and future changes in key climate, hydrological, and biophysical indicators across the US Northeast (NE). We first consider the extent to which simulations of twentieth century climate from nine atmosphere-ocean general circulation models (AOGCMs) are able to reproduce observed changes in these indicators. We then evaluate projected future trends in primary climate characteristics and indicators of change, including seasonal temperatures, rainfall and drought, snow cover, soil moisture, streamflow, and changes in biometeorological indicators that depend on threshold or accumulated temperatures such as growing season, frost days, and Spring Indices (SI). Changes in indicators for which temperature-related signals have already been observed (seasonal warming patterns, advances in high-spring streamflow, decreases in snow depth, extended growing seasons, earlier bloom dates) are generally reproduced by past model simulations and are projected to continue in the future. Other indicators for which trends have not yet been observed also show projected future changes consistent with a warmer climate (shrinking snow cover, more frequent droughts, and extended low-flow periods in summer). The magnitude of temperature-driven trends in the future are generally projected to be higher under the Special Report on Emission Scenarios (SRES) mid-high (A2) and higher (A1FI) emissions scenarios than under the lower (B1) scenario. These results provide confidence regarding the direction of many regional climate trends, and highlight the fundamental role of future emissions in determining the potential magnitude of changes we can expect over the coming century.

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