Littérature scientifique sur le sujet « Climate change model »
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Articles de revues sur le sujet "Climate change model"
Hanf, Franziska, Janina Körper, Thomas Spangehl et Ulrich Cubasch. « Shifts of climate zones in multi-model climate change experiments using the Köppen climate classification ». Meteorologische Zeitschrift 21, no 2 (1 avril 2012) : 111–23. http://dx.doi.org/10.1127/0941-2948/2012/0344.
Texte intégralA Shinde Waman, Sneha. « Replicable Model for Climate Proofing and Reducing Vulnerabilities due to Climate Change in different Agro Climatic Zones of Maharashtra ». International Journal of Science and Research (IJSR) 13, no 4 (5 avril 2024) : 1373–76. http://dx.doi.org/10.21275/sr24416172526.
Texte intégralElía, Ramón Côté. « Climate and climate change sensitivity to model configuration in the Canadian RCM over North America ». Meteorologische Zeitschrift 19, no 4 (1 août 2010) : 325–39. http://dx.doi.org/10.1127/0941-2948/2010/0469.
Texte intégralFan, Fangxing, Raymond S. Bradley et Michael A. Rawlins. « Climate change in the northeastern US : regional climate model validation and climate change projections ». Climate Dynamics 43, no 1-2 (1 juin 2014) : 145–61. http://dx.doi.org/10.1007/s00382-014-2198-1.
Texte intégralNobre, Paulo, Leo S. P. Siqueira, Roberto A. F. de Almeida, Marta Malagutti, Emanuel Giarolla, Guilherme P. Castelão, Marcus J. Bottino et al. « Climate Simulation and Change in the Brazilian Climate Model ». Journal of Climate 26, no 17 (23 août 2013) : 6716–32. http://dx.doi.org/10.1175/jcli-d-12-00580.1.
Texte intégralKarmalkar, Ambarish V., Raymond S. Bradley et Henry F. Diaz. « Climate change in Central America and Mexico : regional climate model validation and climate change projections ». Climate Dynamics 37, no 3-4 (29 mai 2011) : 605–29. http://dx.doi.org/10.1007/s00382-011-1099-9.
Texte intégralvan Eck, Christel W., Bob C. Mulder et Sander van der Linden. « Climate Change Risk Perceptions of Audiences in the Climate Change Blogosphere ». Sustainability 12, no 19 (27 septembre 2020) : 7990. http://dx.doi.org/10.3390/su12197990.
Texte intégralM, Navaneetha Krishnan, Ranjith R et Lavanya B. « Climate Change Prediction Using ARIMA Model ». International Journal for Research in Applied Science and Engineering Technology 10, no 6 (30 juin 2022) : 621–25. http://dx.doi.org/10.22214/ijraset.2022.43777.
Texte intégralScaife, Adam, Chris Folland et John Mitchell. « A model approach to climate change ». Physics World 20, no 2 (février 2007) : 20–25. http://dx.doi.org/10.1088/2058-7058/20/2/29.
Texte intégralKhokhlov, V., E. Serga et L. Neodstrelova. « Objective selection of model run from regional climate models ensemble ». Ukrainian hydrometeorological journal, no 28 (14 décembre 2021) : 29–36. http://dx.doi.org/10.31481/uhmj.28.2021.03.
Texte intégralThèses sur le sujet "Climate change model"
Ogutu, Benjamin Keroboto Za'Ngoti. « Energy balance mathematical model on climate change ». Thesis, Paris 6, 2015. http://www.theses.fr/2015PA066224/document.
Texte intégralThe goal of this study is to build a global reduced-complexity model of coupled climate-economy-biosphere interactions, which uses the minimum number of variables and equations needed to capture the fundamental mechanisms involved and can thus help clarify the role of the different mechanisms and parameters. The Coupled Climate-Economy-Biosphere (CoCEB) model takes an integrated assessment approach to simulating global change. While many integrated assessment models treat abatement costs merely as an unproductive loss of income, the study considered abatement activities also as an investment in overall energy efficiency of the economy and decrease of overall carbon intensity of the energy system. The study shows that these efforts help to abate climate change and lead to positive effects in economic growth. Due to the fact that integrated assessment models in the literature mainly focus on mitigation in the energy sector and consider emissions from land-use as exogenous, the global climate-economy-biosphere (CoCEB) model was extended by adding a biomass equation and the related exchanges of CO2 and used to investigate the relationship between the effects of using carbon capture and storage (CCS) and deforestation control, and the economy growth rate. These measures are found to reduce the impacts of climate change and positively affect the economy growth. These results remain nevertheless sensitive to the formulation of CCS costs while those for deforestation control were less sensitive. The model developed brings together and summarizes information from diverse estimates of climate change mitigation measures and their associated costs, and allows comparing them in a coherent way
Zhou, Jian. « Integrating geospatial web 2.0 and global climate model for communicating climate change ». Thesis, McGill University, 2013. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=114508.
Texte intégralCette étude porte sur l'utilisation de Géospatiales Web 2.0 et Modèle Climatique Global pour le communication du changement climatique. Le but de cette recherche a été d'intégrer les données, les modèles et les outils de la science du climat avec Geoweb pour faire progresser la communication du changement climatique. Plusieurs applications de GeoWeb ont été développés pour démontrer les solutions de cette intégration et de remplir deux objectifs de recherche: (1) développer une méthode d' utiliser les technologies GeoWeb pour communiquer du changement climatique, (2) améliorer l'accessibilité de Modèle Climatique Global en fournissant des outils pour engager personnes dans la pratique de la science du climat, ainsi que les procédures fondamentales liées à la modélisation du climat mondial. Ma méthode de recherche est d'étendre les fonctionnalités de Geoweb à des outils existants des sciences du climat, dans le but d'alléger l'interface et en augmentant l'interactivité de ces outils pour élaborer le processus scientifique de la modélisation du climat. Geoweb a le pouvoir de manipuler des ensembles de données du changement climatique provenant de diverses sources pour créer une visualisation interactive du changement climatique. Ce pouvoir peut être encore améliorée si l'on intègre Geoweb avec analyse scientifique des données climatiques et des systèmes de visualisation. Néanmoins, les technologies GeoWeb qui fournissent une visualisation 2D sont plus stables, plus rapide et couramment utilisée que la visualisation 3D. Il est plus robuste à utiliser Geoweb pour la sortie des modèles climatiques. Au lieu de cela, en utilisant Geoweb pour d'autres aspects du modèle climatique global nécessite des coopérations étroites entre les scientifiques de modélisation du climat et des experts en technologie de GeoWeb en raison de sa complexité. Il est essentiel d'équilibrer un outil facile à utiliser l'interface utilisateur et la complexité des informations transférées. Suite à cette étude, il est à espérer que beaucoup plus d'efforts de groupes mondiaux de modélisation du climat et des chercheurs en sciences GeoWeb peuvent être réunis pour faciliter la communication pour le changement climatique.
Wi, Sungwook. « Impact of Climate Change on Hydroclimatic Variables ». Diss., The University of Arizona, 2012. http://hdl.handle.net/10150/265344.
Texte intégralAlberth, Stephan Eric. « Valuing technical change information in an integrated assessment model of climate change ». Thesis, University of Cambridge, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.613302.
Texte intégralOtto, Vincent M., Andreas Loeschel et John M. Reilly. « Directed Technical Change and Climate Policy ». MIT Joint Program on the Science and Policy of Global Change, 2006. http://hdl.handle.net/1721.1/32541.
Texte intégralAbstract in HTML and technical report in PDF available on the Massachusetts Institute of Technology Joint Program on the Science and Policy of Global Change website (http://mit.edu/globalchange/www/).
Gars, Johan. « Essays on the Macroeconomics of Climate Change ». Doctoral thesis, Stockholms universitet, Nationalekonomiska institutionen, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-74555.
Texte intégralBetts, Richard Arthur. « Modelling the influence of the vegetated land surface on climate and climate change ». Thesis, University of Reading, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.312335.
Texte intégralConradie, Willem Stefaan. « Conceptualising and quantifying the nonlinear, chaotic climate : implications for climate model experimental design ». Master's thesis, University of Cape Town, 2015. http://hdl.handle.net/11427/16527.
Texte intégralUncertainty in climate system initial conditions (ICs) is known to limit the predictability of future atmospheric states. On weather time scales (i.e. hours to days), the separation between two atmospheric model trajectories, initially "indistinguishable" (compared to unavoidable uncertainties) from one another, diverges exponentially-on-average over time, so that the "memory" of model ICs is eventually lost. In other words, there is a theoretical limit in the lead time for skilful weather forecasts. However, the influence of perturbations to climate system model ICs - particularly in more slowly evolving climate system components (e.g., the oceans and ice sheets) - on the evolution of model "climates" on longer time scales is less well understood. Hence, in order to better understand the role of IC uncertainty in climate predictability, particularly in the context of climate change, it is necessary to develop approaches for investigating and quantifying - at various spatial and temporal scales - the nature of the influence of ICs on the evolution of climate system trajectories. To this end, this study explores different conceptualisations and competing definitions of climate and the climate system, focussing on the role of ICs. The influence of ICs on climate quantifications, using probability distributions, is subsequently investigated in a climate model experiments using a low-resolution version of the Community Climate System Model version 4 (CCSM4). The model experiment consists of 11 different 50-member ensemble simulations with constant forcing, and three 50-member ensemble simulations under a climate change scenario with transient forcing. By analysing the output at global and regional scales, at least three distinct levels of IC influence are detected: (a) microscopic influence; (b) interannual-scale influence; and (c) intercentennial-scale influence. Distinct patterns of interannual-scale IC influence appear to be attributable to aperiodic and quasi-periodic variability in the model. It is found that, over some spatial domains, significant (p < 0.01) differences in atmospheric variable "climatologies", taken from 60-year distributions of model trajectories, occur due to IC differences of a similar order to round-off error. In addition, climate distributions constructed using different approaches are found to differ significantly. There is some evidence that ensemble distributions of multidecadal temperature response to transient forcing conditions can be influenced by ICs. The implications for quantifying and conceptualising climate are considered in the context of the experimental results. It is concluded that IC ensemble experiments can play a valuable role in better understanding climate variability and change, as well as allowing for superior quantification of model climates.
Yettella, Vineel. « The Role of Internal Variability in Climate Change Projections within an Initial Condition Climate Model Ensemble ». Thesis, University of Colorado at Boulder, 2019. http://pqdtopen.proquest.com/#viewpdf?dispub=10981737.
Texte intégralUnforced internal variability abounds in the climate system and often confounds the identification of climate change due to external forcings. Given that greenhouse gas concentrations are projected to increase for the foreseeable future, separating forced climate change from internal variability is a key concern with important implications. Here, we leverage a 40-member ensemble, the Community Earth System Model Large Ensemble (CESM-LE) to investigate the influence of internal variability on the detection of forced changes in two climate phenomena. First, using cyclone identification and compositing techniques within the CESM-LE, we investigate precipitation changes in extratropical cyclones under greenhouse gas forcing and the effect of internal variability on the detection of these changes. We find that the ensemble projects increased cyclone precipitation under twenty-first century business-as-usual greenhouse gas forcing and this response exceeds internal variability in both near- and far- futures. Further, we find that these changes are almost entirely driven by increases in cyclone moisture. Next, we explore the role of internal variability in projections of the annual cycle of surface temperature over Northern Hemisphere land. Internal variability strongly confounds forced changes in the annual cycle over many regions of the Northern Hemisphere. Changes over Europe, North Africa and Siberia, however, are large and easily detectable and further, are remarkably robust across model ensembles from the Coupled Model Intercomparison Project Phase 5 (CMIP5) archive. Using a simple energy balance model, we find that changes in the annual cycle over the three regions are mostly driven by changes in surface heat fluxes.
The thesis also presents a novel ensemble-based framework for diagnosing forced changes in regional climate variability. Changes in climate variability are commonly assessed in terms of changes in the variances of climate variables. The covariance response has received much less attention, despite the existence of large-scale modes of variability that induce covariations in climate variables over a wide range of spatial scales. Addressing this, the framework facilitiates a unified assessment of forced changes in the regional variances and covariances of climate variables.
Clark, Logan N. « Southern Hemisphere Pressure Relationships during the 20th Century - Implications for Climate Reconstructions and Model Evaluation ». Ohio University / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1586778291377432.
Texte intégralLivres sur le sujet "Climate change model"
Agoramoorthy, Govindasamy. Sadguru model of rural development mitigates climate change in India's drylands. New Delhi : Daya Publishing House, a division of Astral International Pvt. Ltd., 2015.
Trouver le texte intégralWendy, Howe, Henderson-Sellers A et Model Evaluation Consortium for Climate Assessment., dir. Assessing climate change : Results from the Model Evaluation Consortium for Climate Assessment. Amsterdam : Gordon and Breach Science Publishers, 1997.
Trouver le texte intégralAnn-Maree, Hansen, dir. Climate change atlas : Greenhouse simulations from the Model Evaluation Consortium for Climate Assessment. Dordrecht : Kluwer Academic Publishers, 1995.
Trouver le texte intégralShrestha, Arun Bhakta. Climate change in the eastern Himalayas : Observed trends and model projections. Kathmandu : International Centre for Integrated Mountain Development, 2010.
Trouver le texte intégralSensitivity of a global climate model to the urban land unit. Middletown, Delaware : Legates Consulting Llc, 2013.
Trouver le texte intégralNozawa, Tōru. Climate change simulations with a coupled ocean-atmosphere GCM called the model for interdisciplinary research on climate : MIROC. Tsukuba, Japan : Center for Global Environmental Research, National Institute for Environmental Studies, 2007.
Trouver le texte intégralHulme, Mike. Observational data sets, climate model validation and climate change detection : Final report to the Department of the Environment, April 1995 to March 1997. Norwich : Climatic Research Unit, University of East Anglia, 1997.
Trouver le texte intégralGrotch, Stanley L. An intercomparison of general circulation model predictions of regional climate change : Presented at the International Conference on "Modelling of Global Climate Change and Variability," Hamburg, Federal Republic of Germany, September 1989. [Springfield, Va : Available from National Technical Information Service, 1990.
Trouver le texte intégralNuttal, Pat, dir. Climate, ticks and disease. Wallingford : CABI, 2021. http://dx.doi.org/10.1079/9781789249637.0000.
Texte intégralJay, Hannah Lee, Conservation International et California Energy Commission. Public Interest Energy Research., dir. BioMove : Creation of a complex and dynamic model for assessing the impacts of climate change on California vegetation : PIER final project report. [Sacramento, Calif : California Energy Commission, 2008.
Trouver le texte intégralChapitres de livres sur le sujet "Climate change model"
Bahman, Zohuri, et Mossavar-Rahmani Farhang. « Climate Change ». Dans A Model to Forecast Future Paradigms, 281–317. Includes bibliographical references and index. | Contents : Volume 1. Introduction to knowledge is power in four dimensions : Apple Academic Press, 2019. http://dx.doi.org/10.1201/9781003000662-7.
Texte intégralDe Larminat, Philippe. « Formulating an Energy Balance Model ». Dans Climate Change, 41–53. Hoboken, NJ, USA : John Wiley & Sons, Inc., 2014. http://dx.doi.org/10.1002/9781119053989.ch4.
Texte intégralBrewer, Thomas. « Climate Model Projections and Potential Action Paths ». Dans Climate Change, 199–222. Cham : Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-42906-4_12.
Texte intégralGanopolski, Andrey, et Reinhard Calov. « Simulation of Glacial Cycles with an Earth System Model ». Dans Climate Change, 49–55. Vienna : Springer Vienna, 2012. http://dx.doi.org/10.1007/978-3-7091-0973-1_3.
Texte intégralYe, Duzheng. « Sensitivity of Climate Model to Hydrology ». Dans Understanding Climate Change, 101–8. Washington, D. C. : American Geophysical Union, 2013. http://dx.doi.org/10.1029/gm052p0101.
Texte intégralEstrada, Mario Arturo Ruiz, Ibrahim Ndoma et Donghyun Park. « The Application of the Macroeconomics Analysis of Climate Changes Model (MACC-Model) in China : Floods ». Dans Climate Change Management, 33–48. Cham : Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-14938-7_3.
Texte intégralHelmke, Hannah, Hans-Peter Hafner, Fabian Gebert et Ari Pankiewicz. « Provision of Climate Services—The XDC Model ». Dans Climate Change Management, 223–49. Cham : Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-36875-3_12.
Texte intégralMoernaut, Renée, Jelle Mast et Luc Pauwels. « Framing Climate Change : A Multi-level Model ». Dans Climate Change Management, 215–71. Cham : Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-69838-0_14.
Texte intégralRoche, Didier M., Hans Renssen et Didier Paillard. « A Spatial View on Temperature Change and Variability During the Last Deglaciation : A Model Analysis ». Dans Climate Change, 79–91. Vienna : Springer Vienna, 2012. http://dx.doi.org/10.1007/978-3-7091-0973-1_6.
Texte intégralSchlesinger, Michael E. « Quantitative Analysis of Feedbacks in Climate Model Simulations ». Dans Understanding Climate Change, 177–87. Washington, D. C. : American Geophysical Union, 2013. http://dx.doi.org/10.1029/gm052p0177.
Texte intégralActes de conférences sur le sujet "Climate change model"
Arenson, Lukas, David Sego et Greg Newman. « The use of a convective heat flow model in road designs for Northern regions ». Dans 2006 IEEE EIC Climate Change Conference. IEEE, 2006. http://dx.doi.org/10.1109/eicccc.2006.277276.
Texte intégralHoltanová, Eva, et Tomáš Halenka. « Climate change scenarios ». Dans První konference PERUN. Český hydrometeorologický ústav, 2023. http://dx.doi.org/10.59984/978-80-7653-063-8.03.
Texte intégral« The AgMIP Global Gridded Model Intercomparison ». Dans ASABE 1st Climate Change Symposium : Adaptation and Mitigation. American Society of Agricultural and Biological Engineers, 2015. http://dx.doi.org/10.13031/cc.20152124282.
Texte intégralCroce, Pietro, Paolo Formichi et Filippo Landi. « A BAYESIAN HIERARCHICAL MODEL FOR CLIMATIC LOADS UNDER CLIMATE CHANGE ». Dans 2nd International Conference on Uncertainty Quantification in Computational Sciences and Engineering. Athens : Institute of Structural Analysis and Antiseismic Research School of Civil Engineering National Technical University of Athens (NTUA) Greece, 2019. http://dx.doi.org/10.7712/120219.6342.18579.
Texte intégral« New model for capturing heterogeneity of fertilizer-induced N2O emission factors ». Dans ASABE 1st Climate Change Symposium : Adaptation and Mitigation. American Society of Agricultural and Biological Engineers, 2015. http://dx.doi.org/10.13031/cc.20152144930.
Texte intégral« Exploring Water Management Options with COWA : A Coupled Human-Climate-Water Model ». Dans ASABE 1st Climate Change Symposium : Adaptation and Mitigation. American Society of Agricultural and Biological Engineers, 2015. http://dx.doi.org/10.13031/cc.20152144305.
Texte intégral« A computational fluid dynamics model of methane and ammonia emissions from tie-stall dairy barns ». Dans ASABE 1st Climate Change Symposium : Adaptation and Mitigation. American Society of Agricultural and Biological Engineers, 2015. http://dx.doi.org/10.13031/cc.20152124152.
Texte intégralMiller, Sara, Terrance Quinn et James Ianelli. « Estimation of Age-Specific Migration in an Age-Structured Model ». Dans Resiliency of Gadid Stocks to Fishing and Climate Change. Alaska Sea Grant College Program, 2008. http://dx.doi.org/10.4027/rgsfcc.2008.09.
Texte intégral« Application of the CERES-Maize Model for Climate Change Impact Assessment in Rainfed Corn Production in Isabela, Philippines ». Dans ASABE 1st Climate Change Symposium : Adaptation and Mitigation. American Society of Agricultural and Biological Engineers, 2015. http://dx.doi.org/10.13031/cc.20152088440.
Texte intégralNissan, Hannah, Jim Clarke, Shirley Oliveira et Ralf Toumi. « Adapting to Climate Change : A Regional Climate Model Study of the Caucasus ». Dans International Conference on Health, Safety and Environment in Oil and Gas Exploration and Production. Society of Petroleum Engineers, 2012. http://dx.doi.org/10.2118/157430-ms.
Texte intégralRapports d'organisations sur le sujet "Climate change model"
Dewart, Jean Marie. Conceptual Model of Climate Change Impacts at LANL. Office of Scientific and Technical Information (OSTI), mai 2016. http://dx.doi.org/10.2172/1253547.
Texte intégralKocarev, Ljupco. An Interactive Multi-Model for Consensus on Climate Change. Office of Scientific and Technical Information (OSTI), juillet 2014. http://dx.doi.org/10.2172/1136784.
Texte intégralGillingham, Kenneth, William Nordhaus, David Anthoff, Geoffrey Blanford, Valentina Bosetti, Peter Christensen, Haewon McJeon, John Reilly et Paul Sztorc. Modeling Uncertainty in Climate Change : A Multi-Model Comparison. Cambridge, MA : National Bureau of Economic Research, octobre 2015. http://dx.doi.org/10.3386/w21637.
Texte intégralAuffhammer, Maximilian, Solomon Hsiang, Wolfram Schlenker et Adam Sobel. Using Weather Data and Climate Model Output in Economic Analyses of Climate Change. Cambridge, MA : National Bureau of Economic Research, mai 2013. http://dx.doi.org/10.3386/w19087.
Texte intégralPolicy Institute, International Food. Projections from IFPRI's IMPACT model : Climate change and food systems. Washington, DC : International Food Policy Research Institute, 2022. http://dx.doi.org/10.2499/9780896294257_14.
Texte intégralKukla, G., et J. Gavin. Global climate change model natural climate variation : Paleoclimate data base, probabilities and astronomic predictors. Office of Scientific and Technical Information (OSTI), mai 1994. http://dx.doi.org/10.2172/145219.
Texte intégralRussell, H. A. J., et S. K. Frey. Canada One Water : integrated groundwater-surface-water-climate modelling for climate change adaptation. Natural Resources Canada/CMSS/Information Management, 2021. http://dx.doi.org/10.4095/329092.
Texte intégralEdmonds, J. A., M. A. Wise et C. N. MacCracken. ADVANCED ENERGY TECHNOLOGIES AND CLIMATE CHANGE : AN ANALYSIS USING THE GLOBAL CHANGE ASSESSMENT MODEL (GCAM). Office of Scientific and Technical Information (OSTI), mai 1994. http://dx.doi.org/10.2172/1127203.
Texte intégralCooter, Ellen J., Brian K. Eder, Sharon K. LeDuc et Lawrence Truppi. General Circulation Model Output for Forest Climate Change Research and Applications. Asheville, NC : U.S. Department of Agriculture, Forest Service, Southeastern Forest Experiment Station, 1993. http://dx.doi.org/10.2737/se-gtr-085.
Texte intégralCooter, Ellen J., Brian K. Eder, Sharon K. LeDuc et Lawrence Truppi. General Circulation Model Output for Forest Climate Change Research and Applications. Asheville, NC : U.S. Department of Agriculture, Forest Service, Southeastern Forest Experiment Station, 1993. http://dx.doi.org/10.2737/se-gtr-85.
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