923 resultados para Future Scenarios.
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PIP: A delphi study was conducted to identify or envision health scenarios in India by the year 2000. Questionnaires consisting of 48 questions on 5 areas (diagnosis and therapy; family planning; pharmaceuticals and drugs; biochemical and biomedical research; health services) were mailed to 250 experts in India. 36 responded. Results were compiled and mailed back to the respondents for changes and comments. 17 people responded. Results of the delphi study shows that policy decisions with respect to compulsory family planning as well as health education at secondary school level will precede further breakthroughs in birth control technology. Non operation reversible sterilization procedures, immunological birth control, Ayurvedic medicines for contraception and abortion, and selection of baby's sex are all possible by 2000 thereafter. Complete eradication of infectious diseases, malnutrition and associated diseases is considered unlikely before 2000, as are advances in biomedical research. Changes in health services (e.g., significant increases in hospital beds and doctors, cheap bulk drugs), particularly in rural areas, are imminent, leading to prolonging of life expectancy to 70 years. Genetic engineering may provide significant breakthroughs in the prevention of malignancies and cardiac disorders. The India delphi study is patterned after a similar delphi study conducted in the U.S. by Smith, Kline and French (SKF) Laboratories in 1968. The SKF study was able to predict some breakthroughs with basic research which have been realized.
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The QUT Centre for Subtropical Design conducted a design-led interdisciplinary collaborative workshop (charrette) to develop some initial ideas for how innovation in research and practice can be applied to the complex problem of resilient future-focussed urban renewal in Rockhampton’s flood-prone suburbs and core grid. Three creative teams explored a range of scenarios for Rockhampton’s resilience in built form over the longer term. A large number of sketches, drawings and text were produced over two days. This report identifies themes, principles and strategies which emerged from the charrette. Each group proposed multiple guiding principles that fell into three strategic approaches: defend (through construction of a levee); adapt (by designing with flood in mind); retreat (a long term view to relocate populations in flood-prone areas). All three groups identified the importance of design that accommodates art, heritage, recreation, sustainability and tourism, and proposed these as principles to guide future strategies that mediate between Rockhampton’s broader ecological landscape and urban living to accommodate more affordable housing options, demonstrate sustainability and be climate responsive to predicted increased extreme weather events including flooding. The charrette outcomes pave the way to investigate wider issues and solutions to Rockhampton’s resilient future, beyond a levee as an isolated structure.
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West Africa is highly vulnerable to climate hazards and better quantification and understanding of the impact of climate change on crop yields are urgently needed. Here we provide an assessment of near-term climate change impacts on sorghum yields in West Africa and account for uncertainties both in future climate scenarios and in crop models. Towards this goal, we use simulations of nine bias-corrected CMIP5 climate models and two crop models (SARRA-H and APSIM) to evaluate the robustness of projected crop yield impacts in this area. In broad agreement with the full CMIP5 ensemble, our subset of bias-corrected climate models projects a mean warming of +2.8 °C in the decades of 2031–2060 compared to a baseline of 1961–1990 and a robust change in rainfall in West Africa with less rain in the Western part of the Sahel (Senegal, South-West Mali) and more rain in Central Sahel (Burkina Faso, South-West Niger). Projected rainfall deficits are concentrated in early monsoon season in the Western part of the Sahel while positive rainfall changes are found in late monsoon season all over the Sahel, suggesting a shift in the seasonality of the monsoon. In response to such climate change, but without accounting for direct crop responses to CO2, mean crop yield decreases by about 16–20% and year-to-year variability increases in the Western part of the Sahel, while the eastern domain sees much milder impacts. Such differences in climate and impacts projections between the Western and Eastern parts of the Sahel are highly consistent across the climate and crop models used in this study. We investigate the robustness of impacts for different choices of cultivars, nutrient treatments, and crop responses to CO2. Adverse impacts on mean yield and yield variability are lowest for modern cultivars, as their short and nearly fixed growth cycle appears to be more resilient to the seasonality shift of the monsoon, thus suggesting shorter season varieties could be considered a potential adaptation to ongoing climate changes. Easing nitrogen stress via increasing fertilizer inputs would increase absolute yields, but also make the crops more responsive to climate stresses, thus enhancing the negative impacts of climate change in a relative sense. Finally, CO2 fertilization would significantly offset the negative climate
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Modeling the distributions of species, especially of invasive species in non-native ranges, involves multiple challenges. Here, we developed some novel approaches to species distribution modeling aimed at reducing the influences of such challenges and improving the realism of projections. We estimated species-environment relationships with four modeling methods run with multiple scenarios of (1) sources of occurrences and geographically isolated background ranges for absences, (2) approaches to drawing background (absence) points, and (3) alternate sets of predictor variables. We further tested various quantitative metrics of model evaluation against biological insight. Model projections were very sensitive to the choice of training dataset. Model accuracy was much improved by using a global dataset for model training, rather than restricting data input to the species’ native range. AUC score was a poor metric for model evaluation and, if used alone, was not a useful criterion for assessing model performance. Projections away from the sampled space (i.e. into areas of potential future invasion) were very different depending on the modeling methods used, raising questions about the reliability of ensemble projections. Generalized linear models gave very unrealistic projections far away from the training region. Models that efficiently fit the dominant pattern, but exclude highly local patterns in the dataset and capture interactions as they appear in data (e.g. boosted regression trees), improved generalization of the models. Biological knowledge of the species and its distribution was important in refining choices about the best set of projections. A post-hoc test conducted on a new Partenium dataset from Nepal validated excellent predictive performance of our “best” model. We showed that vast stretches of currently uninvaded geographic areas on multiple continents harbor highly suitable habitats for Parthenium hysterophorus L. (Asteraceae; parthenium). However, discrepancies between model predictions and parthenium invasion in Australia indicate successful management for this globally significant weed. This article is protected by copyright. All rights reserved.
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Modeling the distributions of species, especially of invasive species in non-native ranges, involves multiple challenges. Here, we developed some novel approaches to species distribution modeling aimed at reducing the influences of such challenges and improving the realism of projections. We estimated species-environment relationships with four modeling methods run with multiple scenarios of (1) sources of occurrences and geographically isolated background ranges for absences, (2) approaches to drawing background (absence) points, and (3) alternate sets of predictor variables. We further tested various quantitative metrics of model evaluation against biological insight. Model projections were very sensitive to the choice of training dataset. Model accuracy was much improved by using a global dataset for model training, rather than restricting data input to the species’ native range. AUC score was a poor metric for model evaluation and, if used alone, was not a useful criterion for assessing model performance. Projections away from the sampled space (i.e. into areas of potential future invasion) were very different depending on the modeling methods used, raising questions about the reliability of ensemble projections. Generalized linear models gave very unrealistic projections far away from the training region. Models that efficiently fit the dominant pattern, but exclude highly local patterns in the dataset and capture interactions as they appear in data (e.g. boosted regression trees), improved generalization of the models. Biological knowledge of the species and its distribution was important in refining choices about the best set of projections. A post-hoc test conducted on a new Partenium dataset from Nepal validated excellent predictive performance of our “best” model. We showed that vast stretches of currently uninvaded geographic areas on multiple continents harbor highly suitable habitats for Parthenium hysterophorus L. (Asteraceae; parthenium). However, discrepancies between model predictions and parthenium invasion in Australia indicate successful management for this globally significant weed. This article is protected by copyright. All rights reserved.
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Wind power has grown fast internationally. It can reduce the environmental impact of energy production and increase energy security. Finland has turbine industry but wind electricity production has been slow, and nationally set capacity targets have not been met. I explored social factors that have affected the slow development of wind power in Finland by studying the perceptions of Finnish national level wind power actors. By that I refer to people who affect the development of wind power sector, such as officials, politicians, and representatives of wind industries and various organisations. The material consisted of interviews, a questionnaire, and written sources. The perceptions of wind power, its future, and methods to promote it were divided. They were studied through discourse analysis, content analysis, and scenario construction. Definition struggles affect views of the significance and potential of wind power in Finland, and also affect investments in wind power and wind power policy choices. Views of the future were demonstrated through scenarios. The views included scenarios of fast growth, but in the most pessimistic views, wind power was not thought to be competitive without support measures even in 2025, and the wind power capacity was correspondingly low. In such a scenario, policy tool choices were expected to remain similar to ones in use at the time of the interviews. So far, the development in Finland has followed closely this pessimistic scenario. Despite the scepticism about wind electricity production, wind turbine industry was seen as a credible industry. For many wind power actors as well as for the Finnish wind power policy, the turbine industry is a significant motive to promote wind power. Domestic electricity production and the export turbine industry are linked in discourse through so-called home market argumentation. Finnish policy tools have included subsidies, research and development funding, and information policies. The criteria used to evaluate policy measures were both process-oriented and value-based. Feed-in tariffs and green certificates that are common elsewhere have not been taken to use in Finland. Some interviewees considered such tools unsuitable for free electricity markets and for the Finnish policy style, dictatorial, and being against western values. Other interviewees supported their use because of their effectiveness. The current Finnish policy tools are not sufficiently effective to increase wind power production significantly. Marginalisation of wind power in discourses, pessimistic views of the future, and the view that the small consumer demand for wind electricity represents the political views of citizens towards promoting wind power, make it more difficult to take stronger policy measures to use. Wind power has not yet significantly contributed to the ecological modernisation of the energy sector in Finland, but the situation may change as the need to reduce emissions from energy production continues.
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Discoveries at the LHC will soon set the physics agenda for future colliders. This report of a CERN Theory Institute includes the summaries of Working Groups that reviewed the physics goals and prospects of LHC running with 10 to 300 fb(-1) of integrated luminosity, of the proposed sLHC luminosity upgrade, of the ILC, of CLIC, of the LHeC and of a muon collider. The four Working Groups considered possible scenarios for the first 10 fb(-1) of data at the LHC in which (i) a state with properties that are compatible with a Higgs boson is discovered, (ii) no such state is discovered either because the Higgs properties are such that it is difficult to detect or because no Higgs boson exists, (iii) a missing-energy signal beyond the Standard Model is discovered as in some supersymmetric models, and (iv) some other exotic signature of new physics is discovered. In the contexts of these scenarios, the Working Groups reviewed the capabilities of the future colliders to study in more detail whatever new physics may be discovered by the LHC. Their reports provide the particle physics community with some tools for reviewing the scientific priorities for future colliders after the LHC produces its first harvest of new physics from multi-TeV collisions.
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There is huge knowledge gap in our understanding of many terrestrial carbon cycle processes. In this paper, we investigate the bounds on terrestrial carbon uptake over India that arises solely due to CO (2) -fertilization. For this purpose, we use a terrestrial carbon cycle model and consider two extreme scenarios: unlimited CO2-fertilization is allowed for the terrestrial vegetation with CO2 concentration level at 735 ppm in one case, and CO2-fertilization is capped at year 1975 levels for another simulation. Our simulations show that, under equilibrium conditions, modeled carbon stocks in natural potential vegetation increase by 17 Gt-C with unlimited fertilization for CO2 levels and climate change corresponding to the end of 21st century but they decline by 5.5 Gt-C if fertilization is limited at 1975 levels of CO2 concentration. The carbon stock changes are dominated by forests. The area covered by natural potential forests increases by about 36% in the unlimited fertilization case but decreases by 15% in the fertilization-capped case. Thus, the assumption regarding CO2-fertilization has the potential to alter the sign of terrestrial carbon uptake over India. Our model simulations also imply that the maximum potential terrestrial sequestration over India, under equilibrium conditions and best case scenario of unlimited CO2-fertilization, is only 18% of the 21st century SRES A2 scenarios emissions from India. The limited uptake potential of the natural potential vegetation suggests that reduction of CO2 emissions and afforestation programs should be top priorities.
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Concern over changes in global climate has increased in recent years with improvement in understanding of atmospheric dynamics and growth in evidence of climate link to long‐term variability in hydrologic records. Climate impact studies rely on climate change information at fine spatial resolution. Towards this, the past decade has witnessed significant progress in development of downscaling models to cascade the climate information provided by General Circulation Models (GCMs) at coarse spatial resolution to the scale relevant for hydrologic studies. While a plethora of downscaling models have been applied successfully to mid‐latitude regions, a few studies are available on tropical regions where the atmosphere is known to have more complex behavior. In this paper, a support vector machine (SVM) approach is proposed for statistical downscaling to interpret climate change signals provided by GCMs over tropical regions of India. Climate variables affecting spatio‐temporal variation of precipitation at each meteorological sub‐division of India are identified. Following this, cluster analysis is applied on climate data to identify the wet and dry seasons in each year. The data pertaining to climate variables and precipitation of each meteorological sub‐division is then used to develop SVM based downscaling model for each season. Subsequently, the SVM based downscaling model is applied to future climate predictions from the second generation Coupled Global Climate Model (CGCM2) to assess the impact of climate change on hydrological inputs to the meteorological sub‐divisions. The results obtained from the SVM downscaling model are then analyzed to assess the impact of climate change on precipitation over India.
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A two-stage methodology is developed to obtain future projections of daily relative humidity in a river basin for climate change scenarios. In the first stage, Support Vector Machine (SVM) models are developed to downscale nine sets of predictor variables (large-scale atmospheric variables) for Intergovernmental Panel on Climate Change Special Report on Emissions Scenarios (SRES) (A1B, A2, B1, and COMMIT) to R (H) in a river basin at monthly scale. Uncertainty in the future projections of R (H) is studied for combinations of SRES scenarios, and predictors selected. Subsequently, in the second stage, the monthly sequences of R (H) are disaggregated to daily scale using k-nearest neighbor method. The effectiveness of the developed methodology is demonstrated through application to the catchment of Malaprabha reservoir in India. For downscaling, the probable predictor variables are extracted from the (1) National Centers for Environmental Prediction reanalysis data set for the period 1978-2000 and (2) simulations of the third-generation Canadian Coupled Global Climate Model for the period 1978-2100. The performance of the downscaling and disaggregation models is evaluated by split sample validation. Results show that among the SVM models, the model developed using predictors pertaining to only land location performed better. The R (H) is projected to increase in the future for A1B and A2 scenarios, while no trend is discerned for B1 and COMMIT.
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Impact of global warming on daily rainfall is examined using atmospheric variables from five General Circulation Models (GCMs) and a stochastic downscaling model. Daily rainfall at eleven raingauges over Malaprabha catchment of India and National Center for Environmental Prediction (NCEP) reanalysis data at grid points over the catchment for a continuous time period 1971-2000 (current climate) are used to calibrate the downscaling model. The downscaled rainfall simulations obtained using GCM atmospheric variables corresponding to the IPCC-SRES (Intergovernmental Panel for Climate Change - Special Report on Emission Scenarios) A2 emission scenario for the same period are used to validate the results. Following this, future downscaled rainfall projections are constructed and examined for two 20 year time slices viz. 2055 (i.e. 2046-2065) and 2090 (i.e. 2081-2100). The model results show reasonable skill in simulating the rainfall over the study region for the current climate. The downscaled rainfall projections indicate no significant changes in the rainfall regime in this catchment in the future. More specifically, 2% decrease by 2055 and 5% decrease by 2090 in monsoon (HAS) rainfall compared to the current climate (1971-2000) under global warming conditions are noticed. Also, pre-monsoon (JFMAM) and post-monsoon (OND) rainfall is projected to increase respectively, by 2% in 2055 and 6% in 2090 and, 2% in 2055 and 12% in 2090, over the region. On annual basis slight decreases of 1% and 2% are noted for 2055 and 2090, respectively.
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Climate change impact on a groundwater-dependent small urban town has been investigated in the semiarid hard rock aquifer in southern India. A distributed groundwater model was used to simulate the groundwater levels in the study region for the projected future rainfall (2012-32) obtained from a general circulation model (GCM) to estimate the impacts of climate change and management practices on groundwater system. Management practices were based on the human-induced changes on the urban infrastructure such as reduced recharge from the lakes, reduced recharge from water and wastewater utility due to an operational and functioning underground drainage system, and additional water extracted by the water utility for domestic purposes. An assessment of impacts on the groundwater levels was carried out by calibrating a groundwater model using comprehensive data gathered during the period 2008-11 and then simulating the future groundwater level changes using rainfall from six GCMs Institute of Numerical Mathematics Coupled Model, version 3.0 (INM-CM. 3.0); L'Institut Pierre-Simon Laplace Coupled Model, version 4 (IPSL-CM4); Model for Interdisciplinary Research on Climate, version 3.2 (MIROC3.2); ECHAM and the global Hamburg Ocean Primitive Equation (ECHO-G); Hadley Centre Coupled Model, version 3 (HadCM3); and Hadley Centre Global Environment Model, version 1 (HadGEM1)] that were found to show good correlation to the historical rainfall in the study area. The model results for the present condition indicate that the annual average discharge (sum of pumping and natural groundwater outflow) was marginally or moderately higher at various locations than the recharge and further the recharge is aided from the recharge from the lakes. Model simulations showed that groundwater levels were vulnerable to the GCM rainfall and a scenario of moderate reduction in recharge from lakes. Hence, it is important to sustain the induced recharge from lakes by ensuring that sufficient runoff water flows to these lakes.
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If the recent indications of a possible state I broken vertical bar with mass similar to 750 GeV decaying into two photons reported by ATLAS and CMS in LHC collisions at 13 TeV were to become confirmed, the prospects for future collider physics at the LHC and beyond would be affected radically, as we explore in this paper. Even minimal scenarios for the I broken vertical bar resonance and its gamma gamma decays require additional particles with masses . We consider here two benchmark scenarios that exemplify the range of possibilities: one in which I broken vertical bar is a singlet scalar or pseudoscalar boson whose production and gamma gamma decays are due to loops of coloured and charged fermions, and another benchmark scenario in which I broken vertical bar is a superposition of (nearly) degenerate CP-even and CP-odd Higgs bosons in a (possibly supersymmetric) two-Higgs doublet model also with additional fermions to account for the gamma gamma decay rate. We explore the implications of these benchmark scenarios for the production of I broken vertical bar and its new partners at colliders in future runs of the LHC and beyond, at higher-energy pp colliders and at e (+) e (-) and gamma gamma colliders, with emphasis on the bosonic partners expected in the doublet scenario and the fermionic partners expected in both scenarios.
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Foreword [pdf, < 0.1 MB] Acknowledgements PHASE 1 [pdf, 0.2 MB] Summary of the PICES/NPRB Workshop on Forecasting Climate Impacts on Future Production of Commercially Exploited Fish and Shellfish (July 19–20, 2007, Seattle, U.S.A.) Background Links to Other Programs Workshop Format Session I. Status of climate change scenarios in the PICES region Session II. What are the expected impacts of climate change on regional oceanography and what are some scenarios for these drivers for the next 10 years? Session III. Recruitment forecasting Session IV. What models are out there? How is climate linked to the model? Session V. Assumptions regarding future fishing scenarios and enhancement activities Session VI Where do we go from here? References Appendix 1.1 List of Participants PHASE 2 [pdf, 0.7 MB] Summary of the PICES/NPRB Workshop on Forecasting Climate Impacts on Future Production of Commercially Exploited Fish and Shellfish (October 30, 2007, Victoria, Canada) Background Workshop Agenda Forecast Feasibility Format of Information Modeling Approaches Coupled bio-physical models Stock assessment projection models Comparative approaches Similarities in Data Requests Opportunities for Coordination with Other PICES Groups and International Efforts BACKGROUND REPORTS PREPARED FOR THE PHASE 2 WORKSHOP Northern California Current (U.S.) groundfish production by Melissa Haltuch Changes in sablefish (Anoplopoma fimbria) recruitment in relation to oceanographic conditions by Michael J. Schirripa Northern California Current (British Columbia) Pacific cod (Gadus macrocephalus) production by Caihong Fu and Richard Beamish Northern California Current (British Columbia) sablefish (Anoplopoma fimbria) production by Richard Beamish Northern California Current (British Columbia) pink (Oncorhynchus gorbuscha) and chum (O. keta) salmon production by Richard Beamish Northern California Current (British Columbia) ocean shrimp (Pandalus jordani) production by Caihong Fu Alaska salmon production by Anne Hollowed U.S. walleye pollock (Theragra chalcogramma) production in the eastern Bering Sea and Gulf of Alaska by Kevin Bailey and Anne Hollowed U.S. groundfish production in the eastern Bering Sea by Tom Wilderbuer U.S. crab production in the eastern Bering Sea by Gordon H. Kruse Forecasting Japanese commercially exploited species by Shin-ichi Ito, Kazuaki Tadokoro and Yasuhiro Yamanka Russian fish production in the Japan/East Sea by Yury Zuenko, Vladimir Nuzhdin and Natalia Dolganova Chum salmon (Oncorhynchus keta) production in Korea by Sukyung Kang, Suam Kim and Hyunju Seo Jack mackerel (Trachurus japonicus) production in Korea by Jae Bong Lee and Chang-Ik Zhang Chub mackerel (Scomber japonicus) production in Korea by Jae Bong Lee, Sukyung Kang, Suam Kim, Chang-Ik Zhang and Jin Yeong Kim References Appendix 2.1 List of Participants PHASE 3 [pdf, < 0.1 MB] Summary of the PICES Workshop on Linking Global Climate Model Output to (a) Trends in Commercial Species Productivity and (b) Changes in Broader Biological Communities in the World’s Oceans (May 18, 2008, Gijón, Spain) Appendix 3.1 List of Participants Appendix 3.2 Workshop Agenda (Document contains 101 pages)
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4 p.