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Emission Scenarios (emission + scenario)

Distribution by Scientific Domains

Earth and Environmental Science	43%
Life Sciences	34%

Selected Abstracts

Downscaled GCM projections of winter and summer mass balance for Peyto Glacier, Alberta, Canada (2000,2100) from ensemble simulations with ECHAM5-MPIOM

INTERNATIONAL JOURNAL OF CLIMATOLOGY, Issue 11 2009
Christoph Matulla
Abstract We apply a direct downscaling approach to generate ensembles of local-scale glacier mass balance projections from coarse-scale general circulation model (GCM) data. The general modes of the atmospheric circulation over a large geographical region are linked statistically to Peyto Glacier's winter and summer balance separately. Our study focuses on the generation of ensemble projections derived from simulations with ECHAM5-MPIOM forced with Intergovernmental Panel on Climate Change - Special Report on Emission Scenarios (IPCC-SRES) A1B and B1. The resulting ensembles of mass balance projections show a moderate increase in winter balance and a steep decrease in summer balance. Together these results suggest continued frontal recession and downwasting of Peyto Glacier and a shift of the equilibrium line altitude by at least 100 m above that estimated for the 1966,2001 period suggesting that very little of the glacier will remain by 2100. Copyright © 2008 Crown in the right of Canada. Published by John Wiley & Sons, Ltd. [source]

Will climate change be beneficial or detrimental to the invasive swede midge in North America?

GLOBAL CHANGE BIOLOGY, Issue 8 2008
Contrasting predictions using climate projections from different general circulation models
Abstract Climate change may dramatically affect the distribution and abundance of organisms. With the world's population size expected to increase significantly during the next 100 years, we need to know how climate change might impact our food production systems. In particular, we need estimates of how future climate might alter the distribution of agricultural pests. We used the climate projections from two general circulation models (GCMs) of global climate, the Canadian Centre for Climate Modelling and Analysis GCM (CGCM2) and the Hadley Centre model (HadCM3), for the A2 and B2 scenarios from the Special Report on Emissions Scenarios in conjunction with a previously published bioclimatic envelope model (BEM) to predict the potential changes in distribution and abundance of the swede midge, Contarinia nasturtii, in North America. The BEM in conjunction with either GCM predicted that C. nasturtii would spread from its current initial invasion in southern Ontario and northwestern New York State into the Canadian prairies, northern Canada, and midwestern United States, but the magnitude of risk depended strongly on the GCM and the scenario used. When the CGCM2 projections were used, the BEM predicted an extensive shift in the location of the midges' climatic envelope through most of Ontario, Quebec, and the maritime and prairie provinces by the 2080s. In the United States, C. nasturtii was predicted to spread to all the Great Lake states, into midwestern states as far south as Colorado, and west into Washington State. When the HadCM3 was applied, southern Ontario, Saskatchewan, and Washington State were not as favourable for C. nasturtii by the 2080s. Indeed, when used with the HadCM3 climate projections, the BEM predicted the virtual disappearance of ,very favourable' regions for C. nasturtii. The CGCM2 projections generally caused the BEM to predict a small increase in the mean number of midge generations throughout the course of the century, whereas, the HadCM3 projections resulted in roughly the same mean number of generations but decreased variance. Predictions of the likely potential of C. nasturtii spatial spread are thus strongly dependent on the source of climate projections. This study illustrates the importance of using multiple GCMs in combination with multiple scenarios when studying the potential for spatial spread of an organism in response to climate change. [source]

Projecting future N2O emissions from agricultural soils in Belgium

GLOBAL CHANGE BIOLOGY, Issue 1 2007
CAROLINE ROELANDT
Abstract This study analyses the spatial and temporal variability of N2O emissions from the agricultural soils of Belgium. Annual N2O emission rates are estimated with two statistical models, MCROPS and MGRASS, which take account of the impact of changes in land use, climate, and nitrogen-fertilization rate. The models are used to simulate the temporal trend of N2O emissions between 1990 and 2050 for a 10, latitude and longitude grid. The results are also aggregated to the regional and national scale to facilitate comparison with other studies and national inventories. Changes in climate and land use are derived from the quantitative scenarios developed by the ATEAM project based on the Intergovernmental Panel on Climate Change-Special Report on Emissions Scenarios (IPCC-SRES) storylines. The average N2O flux for Belgium was estimated to be 8.6 × 106 kg N2O-N yr,1 (STD = 2.1 × 106 kg N2O-N yr,1) for the period 1990,2000. Fluxes estimated for a single year (1996) give a reasonable agreement with published results at the national and regional scales for the same year. The scenario-based simulations of future N2O emissions show the strong influence of land-use change. The scenarios A1FI, B1 and B2 produce similar results between 2001 and 2050 with a national emission rate in 2050 of 11.9 × 106 kg N2O-N yr,1. The A2 scenario, however, is very sensitive to the reduction in agricultural land areas (,14% compared with the 1990 baseline), which results in a reduced emission rate in 2050 of 8.3 × 106 kg N2O-N yr,1. Neither the climatic change scenarios nor the reduction in nitrogen fertilization rate could explain these results leading to the conclusion that N2O emissions from Belgian agricultural soils will be more markedly affected by changes in agricultural land areas. [source]

Estimating the evolution of vegetation cover and its hydrological impact in the Mekong River basin in the 21st century

HYDROLOGICAL PROCESSES, Issue 9 2008
Hiroshi Ishidaira
Abstract The terrestrial biosphere plays a key role in regional energy and water cycles. Thus, for long-term hydrological predictions, possible future changes in vegetation cover must be understood. This study examined the evolution of vegetation cover in the 21st century and its estimated impact on river discharge in the Mekong River basin. Based on climatic predictions (TYN SC 2·03) under the Intergovernmental Panel on Climate Change Special Report on Emissions Scenarios (IPCC SRES) A1FI, A2, B1, and B2, changes in vegetation type and the leaf area index (LAI) were simulated using a Lund-Potsdam-Jena-Dynamic Global Vegetation Model (LPJ-DGVM) and Terrestrial Biogeochemical Cycle Model (BIOME-BGC). The estimated LAI was then used in the rainfall-runoff analysis in the Yamanashi Distributed Hydrological Model (YHyM). The simulation results indicated a significant change in vegetation type mainly on the Tibetan Plateau and in mountainous areas, with the degree of change differing for each SRES scenario; LAI increases around the edge of the Tibetan Plateau and decreases in the lower reaches of the basin; and more conspicuous changes in river discharge in upstream areas than in the middle to lower reaches, mainly due to increases in precipitation in the plateau region. After the 2050s, the results suggested changes in river discharge will be slowed due to changes in evapotranspiration. Copyright © 2008 John Wiley & Sons, Ltd. [source]

Climate change scenarios and models yield conflicting predictions about the future risk of an invasive species in North America

AGRICULTURAL AND FOREST ENTOMOLOGY, Issue 3 2010
Anna M. Mika
1The pea leafminer Liriomyza huidobrensis (Blanchard) (Diptera: Agromyzidae) is an invasive species in North America and a serious economic pest on a wide variety of crops. We developed a bioclimatic envelope model (BEM) for this species and examined the envelope's potential location in North America under various future climates. 2We compared the future bioclimatic envelopes for L. huidobrensis using either simple scenarios comprising uniform changes in temperature/precipitation or climate projections from general circulation models (GCMs). Our simple scenarios were: (i) an increase of 0.1°C per degree in latitude with a 20% increase in summer precipitation and a 20% decrease in winter precipitation and (ii) an overall increase of 3°C everywhere, also with the same changes in precipitation. For GCM-modelled climate change, we used the Canadian Centre for Climate Modelling and Analysis GCM (CGCM2) and the Hadley Centre climate model (HadCM3), each in combination with two scenarios from the Special Report on Emissions Scenarios (A2 and B2). 3The BEM results using the simple scenarios were more similar to each other than to the results obtained using GCM projections. The results were also qualitatively different (i.e. spatially different and divergent) depending on which GCM-scenario combination was used. 4This modelling exercise illustrates that: (i) results using first approximation simple climate change scenarios can give predictions very different from those that use GCM-modelled climate projections (comprising a result that has worrying implications for empirical impact research) and that (ii) different GCM-models using the same scenario can give very different results (implying strong model dependency in projected biological impacts). [source]

Assessment of climate-change impacts on alpine discharge regimes with climate model uncertainty

HYDROLOGICAL PROCESSES, Issue 10 2006
Pascal Horton
Abstract This study analyses the uncertainty induced by the use of different state-of-the-art climate models on the prediction of climate-change impacts on the runoff regimes of 11 mountainous catchments in the Swiss Alps having current proportions of glacier cover between 0 and 50%. The climate-change scenarios analysed are the result of 19 regional climate model (RCM) runs obtained for the period 2070,2099 based on two different greenhouse-gas emission scenarios (the A2 and B2 scenarios defined by the Intergovernmental Panel on Climate Change) and on three different coupled atmosphere-ocean general circulation models (AOGCMs), namely HadCM3, ECHAM4/OPYC3 and ARPEGE/OPA. The hydrological response of the study catchments to the climate scenarios is simulated through a conceptual reservoir-based precipitation-runoff transformation model called GSM-SOCONT. For the glacierized catchments, the glacier surface corresponding to these future scenarios is updated through a conceptual glacier surface evolution model. The results obtained show that all climate-change scenarios induce, in all catchments, an earlier start of the snowmelt period, leading to a shift of the hydrological regimes and of the maximum monthly discharges. The mean annual runoff decreases significantly in most cases. For the glacierized catchments, the simulated regime modifications are mainly due to an increase of the mean temperature and the corresponding impacts on the snow accumulation and melting processes. The hydrological regime of the catchments located at lower altitudes is more strongly affected by the changes of the seasonal precipitation. For a given emission scenario, the simulated regime modifications of all catchments are highly variable for the different RCM runs. This variability is induced by the driving AOGCM, but also in large part by the inter-RCM variability. The differences between the different RCM runs are so important that the predicted climate-change impacts for the two emission scenarios A2 and B2 are overlapping. Copyright © 2006 John Wiley & Sons, Ltd. [source]

An assessment of temperature and precipitation change projections over Italy from recent global and regional climate model simulations

INTERNATIONAL JOURNAL OF CLIMATOLOGY, Issue 1 2010
Erika Coppola
Abstract We present an assessment of climate change projections over the Italian peninsula for the 21st century from the CMIP3 global and PRUDENCE regional model experiments. We consider the A2, A1B, B2 and B1 emission scenarios. The climate change signal over Italy varies seasonally, with maximum warming in summer (up to several °C) and minimum in winter, decreased precipitation over the entire peninsula in summer (locally up to ,40%) and a dipolar precipitation change pattern in winter (increase to the north and decrease to the south). Inter-annual variability increases in all seasons for precipitation and in summer for temperature, while it decreases for winter temperature. The seasonal temperature anomaly probability density functions (PDFs) show a shift as well as a broadening and flattening in future climate conditions, especially in summer. This implies larger increases for extreme hot seasons than mean summer temperatures. The seasonal precipitation anomaly PDFs are greatly affected in summer, with a strong increase of very dry seasons. Moreover, seasons with large precipitation amounts tend to increase in future climate conditions, i.e. we find an increase of very dry (drought prone) and very wet (flood prone) seasons. The magnitude of future climate change depends on the emission scenario and the temperature and precipitation change signals show substantial fine-scale structure in response to the topographical forcing of the Italian major mountain systems. In addition, the change signal is greater than the inter-model standard deviation for temperature in all seasons and for precipitation in the summer. Finally, the CMIP3 ensemble captures the observed 20th century trends of temperature and precipitation change over northern Italy. A broad agreement between the projections obtained with the CMIP3 and PRUDENCE ensembles is found, which adds robustness to the findings. Copyright © 2009 Royal Meteorological Society [source]

The behavior of extreme cold air outbreaks under greenhouse warming

INTERNATIONAL JOURNAL OF CLIMATOLOGY, Issue 9 2006
S. Vavrus
Abstract Climate model output is used to analyze the behavior of extreme cold-air outbreaks (CAOs) under recent and future climatic conditions. The study uses daily output from seven GCMs run under late-twentieth century and projected twenty-first century radiative conditions (SRES A1B greenhouse gas emission scenario). We define a CAO as an occurrence of two or more consecutive days during which the local mean daily surface air temperature is at least two standard deviations below the local wintertime mean temperature. In agreement with observations, the models generally simulate modern CAOs most frequently over western North America and Europe and least commonly over the Arctic. These favored regions for CAOs are located downstream from preferred locations of atmospheric blocking. Future projections indicate that CAOs,defined with respect to late-twentieth century climatic conditions,will decline in frequency by 50 to 100% in most of the Northern Hemisphere during the twenty-first century. Certain regions, however, show relatively small changes and others actually experience more CAOs in the future, due to atmospheric circulation changes and internal variability that counter the thermodynamic tendency from greenhouse forcing. These areas generally experience greater near-surface wind flow from the north or the continent during the twenty-first century and/or are especially prone to atmospheric blocking events. Simulated reductions in CAOs are smallest in western North America, the North Atlantic, and in southern regions of Europe and Asia. The Eurasian pattern is driven by a strong tendency for the models to produce sea-level pressure (SLP) increases in the vicinity of the Mediterranean Sea (intermodel mean of 3 hPa), causing greater advection of continental air from northern and central Asia, while the muted change over western North America is due to enhanced ridging along the west coast and the increased frequency of blocking events. The North Atlantic response is consistent with a slowdown of the thermohaline circulation, which either damps the warming regionally or results in a cooler mean climate in the vicinity of Greenland. Copyright © 2006 Royal Meteorological Society. [source]

Gene movement and genetic association with regional climate gradients in California valley oak (Quercus lobata Née) in the face of climate change

MOLECULAR ECOLOGY, Issue 17 2010
VICTORIA L. SORK
Abstract Rapid climate change jeopardizes tree populations by shifting current climate zones. To avoid extinction, tree populations must tolerate, adapt, or migrate. Here we investigate geographic patterns of genetic variation in valley oak, Quercus lobata Née, to assess how underlying genetic structure of populations might influence this species' ability to survive climate change. First, to understand how genetic lineages shape spatial genetic patterns, we examine historical patterns of colonization. Second, we examine the correlation between multivariate nuclear genetic variation and climatic variation. Third, to illustrate how geographic genetic variation could interact with regional patterns of 21st Century climate change, we produce region-specific bioclimatic distributions of valley oak using Maximum Entropy (MAXENT) models based on downscaled historical (1971,2000) and future (2070,2100) climate grids. Future climatologies are based on a moderate-high (A2) carbon emission scenario and two different global climate models. Chloroplast markers indicate historical range-wide connectivity via colonization, especially in the north. Multivariate nuclear genotypes show a strong association with climate variation that provides opportunity for local adaptation to the conditions within their climatic envelope. Comparison of regional current and projected patterns of climate suitability indicates that valley oaks grow in distinctly different climate conditions in different parts of their range. Our models predict widely different regional outcomes from local displacement of a few kilometres to hundreds of kilometres. We conclude that the relative importance of migration, adaptation, and tolerance are likely to vary widely for populations among regions, and that late 21st Century conditions could lead to regional extinctions. [source]

Regional Climate Models for Hydrological Impact Studies at the Catchment Scale: A Review of Recent Modeling Strategies

GEOGRAPHY COMPASS (ELECTRONIC), Issue 7 2010
Claudia Teutschbein
This article reviews recent applications of regional climate model (RCM) output for hydrological impact studies. Traditionally, simulations of global climate models (GCMs) have been the basis of impact studies in hydrology. Progress in regional climate modeling has recently made the use of RCM data more attractive, although the application of RCM simulations is challenging due to often considerable biases. The main modeling strategies used in recent studies can be classified into (i) very simple constructed modeling chains with a single RCM (S-RCM approach) and (ii) highly complex and computing-power intensive model systems based on RCM ensembles (E-RCM approach). In the literature many examples for S-RCM can be found, while comprehensive E-RCM studies with consideration of several sources of uncertainties such as different greenhouse gas emission scenarios, GCMs, RCMs and hydrological models are less common. Based on a case study using control-run simulations of fourteen different RCMs for five Swedish catchments, the biases of and the variability between different RCMs are demonstrated. We provide a short overview of possible bias-correction methods and show that inter-RCM variability also has substantial consequences for hydrological impact studies in addition to other sources of uncertainties in the modeling chain. We propose that due to model bias and inter-model variability, the S-RCM approach is not advised and ensembles of RCM simulations (E-RCM) should be used. The application of bias-correction methods is recommended, although one should also be aware that the need for bias corrections adds significantly to uncertainties in modeling climate change impacts. [source]

Projected changes in the organic carbon stocks of cropland mineral soils of European Russia and the Ukraine, 1990,2070

GLOBAL CHANGE BIOLOGY, Issue 2 2007
JO SMITH
Abstract In this paper, we use the Rothamsted Carbon Model to estimate how cropland mineral soil carbon stocks are likely to change under future climate, and how agricultural management might influence these stocks in the future. The model was run for croplands occurring on mineral soils in European Russia and the Ukraine, representing 74 Mha of cropland in Russia and 31 Mha in the Ukraine. The model used climate data (1990,2070) from the HadCM3 climate model, forced by four Intergovernmental Panel on Climate Change (IPCC) emission scenarios representing various degrees of globalization and emphasis on economic vs. environmental considerations. Three land use scenarios were examined, business as usual (BAU) management, optimal management (OPT) to maximize profit, and soil sustainability (SUS) in which profit was maximized within the constraint that soil carbon must either remain stable or increase. Our findings suggest that soil organic carbon (SOC) will be lost under all climate scenarios, but less is lost under the climate scenarios where environmental considerations are placed higher than purely economic considerations (IPCC B1 and B2 scenarios) compared with the climate associated with emissions resulting from the global free market scenario (IPCC A1FI scenario). More SOC is lost towards the end of the study period. Optimal management is able to reduce this loss of SOC, by up to 44% compared with business as usual management. The soil sustainability scenario could be run only for a limited area, but in that area was shown to increase SOC stocks under three climate scenarios, compared with a loss of SOC under business as usual management in the same area. Improved agricultural soil management will have a significant role to play in the adaptation to, and mitigation of, climate change in this region. Further, our results suggest that this adaptation could be realized without damaging profitability for the farmers, a key criteria affecting whether optimal management can be achieved in reality. [source]

Assessment of climate-change impacts on alpine discharge regimes with climate model uncertainty

An assessment of temperature and precipitation change projections over Italy from recent global and regional climate model simulations

Comparison of suitable drought indices for climate change impacts assessment over Australia towards resource management

INTERNATIONAL JOURNAL OF CLIMATOLOGY, Issue 10 2008
F. Mpelasoka
Abstract Droughts have significant environmental and socio-economic impacts in Australia. This emphasizes Australia's vulnerability to climate variability and limitations of adaptive capacity. Two drought indices are compared for their potential utility in resource management. The Rainfall Deciles-based Drought Index is a measure of rainfall deficiency while the Soil-Moisture Deciles-based Drought Index is a measure of soil-moisture deficiency attributed to rainfall and potential evaporation. Both indices were used to assess future drought events over Australia under global warming attributed to low and high greenhouse gas emission scenarios (SRES B1 and A1F1 respectively) for 30-year periods centred on 2030 and 2070. Projected consequential changes in rainfall and potential evaporation were based on results from the CCCma1 and Mk2 climate models, developed by the Canadian Climate Center and the Australian Commonwealth Scientific and Industrial Research Organisation (CSIRO) respectively. A general increase in drought frequency associated with global warming was demonstrated by both indices for both climate models, except for the western part of Australia. Increases in the frequency of soil-moisture-based droughts are greater than increases in meteorological drought frequency. By 2030, soil-moisture-based drought frequency increases 20,40% over most of Australia with respect to 1975,2004 and up to 80% over the Indian Ocean and southeast coast catchments by 2070. Such increases in drought frequency would have major implications for natural resource management, water security planning, water demand management strategies, and drought relief payments. Copyright © 2007 Royal Meteorological Society [source]

Statistical downscaling of extremes of daily precipitation and temperature and construction of their future scenarios

INTERNATIONAL JOURNAL OF CLIMATOLOGY, Issue 5 2008
Yeshewatesfa Hundecha
Abstract Two statistical downscaling methods have been tested in terms of their ability to construct indices of extremes of daily precipitation and temperatures from large-scale atmospheric variables with the aim of developing a tool for the construction of future scenarios of the extremes. One of the methods implements an approach for constructing seasonal indices of extremes of precipitation and temperature from seasonal measures of large-scale variables, while the other method implements a stochastic model for generating daily series of precipitation and temperature whose parameters are conditioned on large-scale circulation patterns. While both models generally tend to perform fairly well in reproducing indices of precipitation in winter, their performance for the summer season is not attractive. For indices of temperature, the performance of both models is better than the corresponding performance for indices of precipitation and the seasonal variation in performance is less prominent. The models were applied to construct scenarios of the extremes for the end of the 21st century using predictor sets simulated by the Hadley Centre GCM (HadAM3P) forced by two of the special report on emission scenarios (SRES) emission scenarios. Both models project an increase in both the mean daily minimum and mean daily maximum temperatures for future climate change scenarios in all seasons. The summer increase is accompanied by an increase in the inter-annual variability of the temperatures. On the other hand, they show consistency in the direction of the projected changes in indices of precipitation only in winter, where they projected an increase in both the magnitude and frequency of extremes as well as the mean precipitation. The disparity in the changes simulated by the two models revealed the existence of considerable inter-model uncertainty in predicting changes for future climate. Copyright © 2007 Royal Meteorological Society [source]

Predicting population consequences of ocean climate change for an ecosystem sentinel, the seabird Cassin's auklet

GLOBAL CHANGE BIOLOGY, Issue 7 2010
SHAYE G. WOLF
Abstract Forecasting the ecological effects of climate change on marine species is critical for informing greenhouse gas mitigation targets and developing marine conservation strategies that remain effective and increase species' resilience under changing climate conditions. Highly productive coastal upwelling systems are predicted to experience substantial effects from climate change, making them priorities for ecological forecasting. We used a population modeling approach to examine the consequences of ocean climate change in the California Current upwelling ecosystem on the population growth rate of the planktivorous seabird Cassin's auklet (Ptychoramphus aleuticus), a demographically sensitive indicator of marine climate change. We use future climate projections for sea surface temperature and upwelling intensity from a regional climate model to forecast changes in the population growth rate of the auklet population at the important Farallon Island colony in central California. Our study projected that the auklet population growth rate will experience an absolute decline of 11,45% by the end of the century, placing this population on a trajectory toward extinction. In addition, future changes in upwelling intensity and timing of peak upwelling are likely to vary across auklet foraging regions in the California Current Ecosystem (CCE), producing a mosaic of climate conditions and ecological impacts across the auklet range. Overall, the Farallon Island Cassin's auklet population has been declining during recent decades, and ocean climate change in this century under a mid-level emissions scenario is projected to accelerate this decline, leading toward population extinction. Because our study species has proven to be a sensitive indicator of oceanographic conditions in the CCE and a powerful predictor of the abundance of other important predators (i.e. salmon), the significant impacts we predicted for the Cassin's auklet provide insights into the consequences that ocean climate change may have for other plankton predators in this system. [source]

Downy mildew (Plasmopara viticola) epidemics on grapevine under climate change

GLOBAL CHANGE BIOLOGY, Issue 7 2006
SALINARI FRANCESCA
Abstract As climate is a key agro-ecosystem driving force, climate change could have a severe impact on agriculture. Many assessments have been carried out to date on the possible effects of climate change (temperature, precipitation and carbon dioxide concentration changes) on plant physiology. At present however, likely effects on plant pathogens have not been investigated deeply. The aim of this work was to simulate future scenarios of downy mildew (Plasmopara viticola) epidemics on grape under climate change, by combining a disease model to output from two general circulation models (GCMs). Model runs corresponding to the SRES-A2 emissions scenario, characterized by high projections of both population and greenhouse gas emissions from present to 2100, were chosen in order to investigate impacts of worst-case scenarios, among those currently available from IPCC. Three future decades were simulated (2030, 2050, 2080), using as baseline historical series of meteorological data collected from 1955 to 2001 in Acqui Terme, an important grape-growing area in the north-west of Italy. Both GCMs predicted increase of temperature and decrease of precipitation in this region. The simulations obtained by combining the disease model to the two GCM outputs predicted an increase of the disease pressure in each decade: more severe epidemics were a direct consequence of more favourable temperature conditions during the months of May and June. These negative effects of increasing temperatures more than counterbalanced the effects of precipitation reductions, which alone would have diminished disease pressure. Results suggested that, as adaptation response to future climate change, more attention would have to be paid in the management of early downy mildew infections; two more fungicide sprays were necessary under the most negative climate scenario, compared with present management regimes. At the same time, increased knowledge on the effects of climate change on host,pathogen interactions will be necessary to improve current predictions. [source]

Modelling carbon balances of coastal arctic tundra under changing climate

GLOBAL CHANGE BIOLOGY, Issue 1 2003
Robert F. Grant
Abstract Rising air temperatures are believed to be hastening heterotrophic respiration (Rh) in arctic tundra ecosystems, which could lead to substantial losses of soil carbon (C). In order to improve confidence in predicting the likelihood of such loss, the comprehensive ecosystem model ecosys was first tested with carbon dioxide (CO2) fluxes measured over a tundra soil in a growth chamber under various temperatures and soil-water contents (,). The model was then tested with CO2 and energy fluxes measured over a coastal arctic tundra near Barrow, Alaska, under a range of weather conditions during 1998,1999. A rise in growth chamber temperature from 7 to 15 °C caused large, but commensurate, rises in respiration and CO2 fixation, and so no significant effect on net CO2 exchange was modelled or measured. An increase in growth chamber , from field capacity to saturation caused substantial reductions in respiration but not in CO2 fixation, and so an increase in net CO2 exchange was modelled and measured. Long daylengths over the coastal tundra at Barrow caused an almost continuous C sink to be modelled and measured during most of July (2,4 g C m,2 d,1), but shortening daylengths and declining air temperatures caused a C source to be modelled and measured by early September (,1 g C m,2 d,1). At an annual time scale, the coastal tundra was modelled to be a small C sink (4 g C m,2 y,1) during 1998 when average air temperatures were 4 °C above normal, and a larger C sink (16 g C m,2 y,1) during 1999 when air temperatures were close to long-term normals. During 100 years under rising atmospheric CO2 concentration (Ca), air temperature and precipitation driven by the IS92a emissions scenario, modelled Rh rose commensurately with net primary productivity (NPP) under both current and elevated rates of atmospheric nitrogen (N) deposition, so that changes in soil C remained small. However, methane (CH4) emissions were predicted to rise substantially in coastal tundra with IS92a-driven climate change (from ,20 to ,40 g C m,2 y,1), causing a substantial increase in the emission of CO2 equivalents. If the rate of temperature increase hypothesized in the IS92a emissions scenario had been raised by 50%, substantial losses of soil C (,1 kg C m,2) would have been modelled after 100 years, including additional emissions of CH4. [source]

Why is the choice of future climate scenarios for species distribution modelling important?

ECOLOGY LETTERS, Issue 11 2008
Linda J. Beaumont
Abstract Species distribution models (SDMs) are common tools for assessing the potential impact of climate change on species ranges. Uncertainty in SDM output occurs due to differences among alternate models, species characteristics and scenarios of future climate. While considerable effort is being devoted to identifying and quantifying the first two sources of variation, a greater understanding of climate scenarios and how they affect SDM output is also needed. Climate models are complex tools: variability occurs among alternate simulations, and no single ,best' model exists. The selection of climate scenarios for impacts assessments should not be undertaken arbitrarily - strengths and weakness of different climate models should be considered. In this paper, we provide bioclimatic modellers with an overview of emissions scenarios and climate models, discuss uncertainty surrounding projections of future climate and suggest steps that can be taken to reduce and communicate climate scenario-related uncertainty in assessments of future species responses to climate change. [source]

A multimodel assessment of future climatological droughts in the United Kingdom,

INTERNATIONAL JOURNAL OF CLIMATOLOGY, Issue 14 2009
Jean-Philippe Vidal
Abstract This paper presents a detailed assessment of future rainfall drought patterns over the United Kingdom. Previously developed bias-corrected high-resolution gridded precipitation time series are aggregated to the scale relevant for water resources management, in order to provide 21st-century time series for 183 hydrologic areas, as computed by six General Circulation Models (GCMs) under two emissions scenarios. The control run data are used as a ,learning time series' to compute the Standardized Precipitation Index (SPI) at four different time scales. SPI values for three 30-year future time slices are computed with respect to these learning time series in order to assess the changes in drought frequency. Multimodel results under the A2 scenario show a dramatic increase in the frequency of short-term extreme drought class for most of the country. A decrease of long-term droughts is expected in Scotland, due to the projected increase in winter precipitation. The analysis for two catchment case studies also showed that changes under the B2 scenario are generally consistent with those of the A2 scenario, with a reduced magnitude in changes. The overall increase with time in the spread of individual GCM results demonstrates the utility of multimodel statistics when assessing the uncertainty in future drought indices to be used in long-term water resources planning. Copyright © 2009 Royal Meteorological Society [source]

A framework for developing high-resolution multi-model climate projections: 21st century scenarios for the UK

INTERNATIONAL JOURNAL OF CLIMATOLOGY, Issue 7 2008
Jean-Philippe Vidal
Abstract This article proposes a framework for building climate projections from an ensemble of global circulation models (GCMs) at the local scale required for impact studies. The proposed method relies on a fine-scale gridded baseline climatology and consists of the following steps: (1) building appropriate precipitation and temperature time series from land areas covered by GCM sea cells; (2) correction of GCM outputs inherent biases through ,quantile-based mapping'; and (3) disaggregation of bias-corrected outputs with monthly spatial anomalies between GCM-specific and observed spatial scales. The overall framework is applied to derive 21st century seasonal climate projections and inter-annual variability for the UK based on an ensemble of six GCMs run under two different emissions scenarios. Results show a large dispersion of changes within the multi-GCM ensemble, along with a good comparison between scenarios from individual ensemble members and from previous UK and European studies using dynamically downscaled outputs from corresponding GCMs. The framework presented in this article provides appropriate outputs to take account of the uncertainty in global model configuration within impacts studies that are influencing current decisions on major investments in flood risk management and water resources. Copyright © 2007 Royal Meteorological Society [source]

Downscaling simulations of future global climate with application to hydrologic modelling

INTERNATIONAL JOURNAL OF CLIMATOLOGY, Issue 4 2005
Eric P. Salathé Jr
Abstract This study approaches the problem of downscaling global climate model simulations with an emphasis on validating and selecting global models. The downscaling method makes minimal, physically based corrections to the global simulation while preserving much of the statistics of interannual variability in the climate model. Differences among the downscaled results for simulations of present-day climate form a basis for model evaluation. The downscaled results are used to simulate streamflow in the Yakima River, a mountainous basin in Washington, USA, to illustrate how model differences affect streamflow simulations. The downscaling is applied to the output of three models (ECHAM4, HADCM3, and NCAR-PCM) for simulations of historic conditions (1900,2000) and two future emissions scenarios (A2 and B2 for 2000,2100) from the IPCC assessment. The ECHAM4 simulation closely reproduces the observed statistics of temperature and precipitation for the 42 year period 1949,90. Streamflow computed from this climate simulation likewise produces similar statistics to streamflow computed from the observed data. Downscaled climate-change scenarios from these models are examined in light of the differences in the present-day simulations. Streamflows simulated from the ECHAM4 results show the greatest sensitivity to climate change, with the peak in summertime flow occurring 2 months earlier by the end of the 21st century. Copyright © 2005 Royal Meteorological Society. [source]

Conditional Probabilistic Population Projections: An Application to Climate Change

INTERNATIONAL STATISTICAL REVIEW, Issue 2 2004
Brian C. O'Neill
Summary Future changes in population size, composition, and spatial distribution are key factors in the analysis of climate change, and their future evolution is highly uncertain. In climate change analyses, population uncertainty has traditionally been accounted for by using alternative scenarios spanning a range of outcomes. This paper illustrates how conditional probabilistic projections offer a means of combining probabilistic approaches with the scenario-based approach typically employed in the development of greenhouse gas emissions projections. The illustration combines a set of emissions scenarios developed by the Intergovernmental Panel on Climate Change (IPCC) with existing probabilistic population projections from IIASA. Results demonstrate that conditional probabilistic projections have the potential to account more fully for uncertainty in emissions within conditional storylines about future development patterns, to provide a context for judging the consistency of individual scenarios with a given storyline, and to provide insight into relative likelihoods across storylines, at least from a demographic perspective. They may also serve as a step toward more comprehensive quantification of uncertainty in emissions projections. Résumé Les changements futurs dans la taille, la composition et la distribution spatiale de la population sont des facteurs cels dans l'analyse du changement climatique, et leur évolution future est très incertaine. Dans les analyses du changement climatique, on tient traditionnellement compte de l'incertitude sur la population en utilisant des sénarios alternatifs couvrant un éventail de résultats. Cet article illustre comment des projections à probabilité conditionnelle permettent de combiner les approches probabilistes avec l'approche basée sur des scénarios, typiquement employée dans les travaux de projections d'émissions de gaz à effet de serre. La présentation combine un ensemble de scénarios d'émissions développé par le Panel Intergouvernemental sur le changement climatique (IPCC) avec des projections de population probabilistes existantes de l'IIASA. Les résultats démontrent que les projections à probabilité conditionnelle peuvent expliquer plus complètement l'incertitude sur les émissions dans le cadre de scénarios conditionnels des modèles de développement futurs, qu'elles peuvent permettre de juger de la cohérence de scénarios individuels avec un scénario donné, et de fournir une idée des vraisemblances relatives dans les scénarios, au moins d'un point de vue démographique. Ils peuvent aussi servir d'étape vers une quantification plus précise de l'incertitude dans les projections d'émissions. [source]