Gotowa bibliografia na temat „Climate change model”
Utwórz poprawne odniesienie w stylach APA, MLA, Chicago, Harvard i wielu innych
Spis treści
Zobacz listy aktualnych artykułów, książek, rozpraw, streszczeń i innych źródeł naukowych na temat „Climate change model”.
Przycisk „Dodaj do bibliografii” jest dostępny obok każdej pracy w bibliografii. Użyj go – a my automatycznie utworzymy odniesienie bibliograficzne do wybranej pracy w stylu cytowania, którego potrzebujesz: APA, MLA, Harvard, Chicago, Vancouver itp.
Możesz również pobrać pełny tekst publikacji naukowej w formacie „.pdf” i przeczytać adnotację do pracy online, jeśli odpowiednie parametry są dostępne w metadanych.
Artykuły w czasopismach na temat "Climate change model"
Hanf, Franziska, Janina Körper, Thomas Spangehl i Ulrich Cubasch. "Shifts of climate zones in multi-model climate change experiments using the Köppen climate classification". Meteorologische Zeitschrift 21, nr 2 (1.04.2012): 111–23. http://dx.doi.org/10.1127/0941-2948/2012/0344.
Pełny tekst źródłaA 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, nr 4 (5.04.2024): 1373–76. http://dx.doi.org/10.21275/sr24416172526.
Pełny tekst źródłaElía, Ramón Côté. "Climate and climate change sensitivity to model configuration in the Canadian RCM over North America". Meteorologische Zeitschrift 19, nr 4 (1.08.2010): 325–39. http://dx.doi.org/10.1127/0941-2948/2010/0469.
Pełny tekst źródłaFan, Fangxing, Raymond S. Bradley i Michael A. Rawlins. "Climate change in the northeastern US: regional climate model validation and climate change projections". Climate Dynamics 43, nr 1-2 (1.06.2014): 145–61. http://dx.doi.org/10.1007/s00382-014-2198-1.
Pełny tekst źródłaNobre, Paulo, Leo S. P. Siqueira, Roberto A. F. de Almeida, Marta Malagutti, Emanuel Giarolla, Guilherme P. Castelão, Marcus J. Bottino i in. "Climate Simulation and Change in the Brazilian Climate Model". Journal of Climate 26, nr 17 (23.08.2013): 6716–32. http://dx.doi.org/10.1175/jcli-d-12-00580.1.
Pełny tekst źródłaKarmalkar, Ambarish V., Raymond S. Bradley i Henry F. Diaz. "Climate change in Central America and Mexico: regional climate model validation and climate change projections". Climate Dynamics 37, nr 3-4 (29.05.2011): 605–29. http://dx.doi.org/10.1007/s00382-011-1099-9.
Pełny tekst źródłavan Eck, Christel W., Bob C. Mulder i Sander van der Linden. "Climate Change Risk Perceptions of Audiences in the Climate Change Blogosphere". Sustainability 12, nr 19 (27.09.2020): 7990. http://dx.doi.org/10.3390/su12197990.
Pełny tekst źródłaM, Navaneetha Krishnan, Ranjith R i Lavanya B. "Climate Change Prediction Using ARIMA Model". International Journal for Research in Applied Science and Engineering Technology 10, nr 6 (30.06.2022): 621–25. http://dx.doi.org/10.22214/ijraset.2022.43777.
Pełny tekst źródłaScaife, Adam, Chris Folland i John Mitchell. "A model approach to climate change". Physics World 20, nr 2 (luty 2007): 20–25. http://dx.doi.org/10.1088/2058-7058/20/2/29.
Pełny tekst źródłaKhokhlov, V., E. Serga i L. Neodstrelova. "Objective selection of model run from regional climate models ensemble". Ukrainian hydrometeorological journal, nr 28 (14.12.2021): 29–36. http://dx.doi.org/10.31481/uhmj.28.2021.03.
Pełny tekst źródłaRozprawy doktorskie na temat "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.
Pełny tekst źródłaThe 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.
Pełny tekst źródłaCette 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.
Pełny tekst źródłaAlberth, 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.
Pełny tekst źródłaOtto, Vincent M., Andreas Loeschel i 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.
Pełny tekst źródłaAbstract 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.
Pełny tekst źródłaBetts, 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.
Pełny tekst źródłaConradie, 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.
Pełny tekst źródłaUncertainty 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.
Pełny tekst źródłaUnforced 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.
Pełny tekst źródłaKsiążki na temat "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.
Znajdź pełny tekst źródłaWendy, Howe, Henderson-Sellers A i Model Evaluation Consortium for Climate Assessment., red. Assessing climate change: Results from the Model Evaluation Consortium for Climate Assessment. Amsterdam: Gordon and Breach Science Publishers, 1997.
Znajdź pełny tekst źródłaAnn-Maree, Hansen, red. Climate change atlas: Greenhouse simulations from the Model Evaluation Consortium for Climate Assessment. Dordrecht: Kluwer Academic Publishers, 1995.
Znajdź pełny tekst źródłaShrestha, Arun Bhakta. Climate change in the eastern Himalayas: Observed trends and model projections. Kathmandu: International Centre for Integrated Mountain Development, 2010.
Znajdź pełny tekst źródłaSensitivity of a global climate model to the urban land unit. Middletown, Delaware: Legates Consulting Llc, 2013.
Znajdź pełny tekst źródłaNozawa, 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.
Znajdź pełny tekst źródłaHulme, 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.
Znajdź pełny tekst źródłaGrotch, 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.
Znajdź pełny tekst źródłaNuttal, Pat, red. Climate, ticks and disease. Wallingford: CABI, 2021. http://dx.doi.org/10.1079/9781789249637.0000.
Pełny tekst źródłaJay, Hannah Lee, Conservation International i California Energy Commission. Public Interest Energy Research., red. 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.
Znajdź pełny tekst źródłaCzęści książek na temat "Climate change model"
Bahman, Zohuri, i Mossavar-Rahmani Farhang. "Climate Change". W 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.
Pełny tekst źródłaDe Larminat, Philippe. "Formulating an Energy Balance Model". W Climate Change, 41–53. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2014. http://dx.doi.org/10.1002/9781119053989.ch4.
Pełny tekst źródłaBrewer, Thomas. "Climate Model Projections and Potential Action Paths". W Climate Change, 199–222. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-42906-4_12.
Pełny tekst źródłaGanopolski, Andrey, i Reinhard Calov. "Simulation of Glacial Cycles with an Earth System Model". W Climate Change, 49–55. Vienna: Springer Vienna, 2012. http://dx.doi.org/10.1007/978-3-7091-0973-1_3.
Pełny tekst źródłaYe, Duzheng. "Sensitivity of Climate Model to Hydrology". W Understanding Climate Change, 101–8. Washington, D. C.: American Geophysical Union, 2013. http://dx.doi.org/10.1029/gm052p0101.
Pełny tekst źródłaEstrada, Mario Arturo Ruiz, Ibrahim Ndoma i Donghyun Park. "The Application of the Macroeconomics Analysis of Climate Changes Model (MACC-Model) in China: Floods". W Climate Change Management, 33–48. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-14938-7_3.
Pełny tekst źródłaHelmke, Hannah, Hans-Peter Hafner, Fabian Gebert i Ari Pankiewicz. "Provision of Climate Services—The XDC Model". W Climate Change Management, 223–49. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-36875-3_12.
Pełny tekst źródłaMoernaut, Renée, Jelle Mast i Luc Pauwels. "Framing Climate Change: A Multi-level Model". W Climate Change Management, 215–71. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-69838-0_14.
Pełny tekst źródłaRoche, Didier M., Hans Renssen i Didier Paillard. "A Spatial View on Temperature Change and Variability During the Last Deglaciation: A Model Analysis". W Climate Change, 79–91. Vienna: Springer Vienna, 2012. http://dx.doi.org/10.1007/978-3-7091-0973-1_6.
Pełny tekst źródłaSchlesinger, Michael E. "Quantitative Analysis of Feedbacks in Climate Model Simulations". W Understanding Climate Change, 177–87. Washington, D. C.: American Geophysical Union, 2013. http://dx.doi.org/10.1029/gm052p0177.
Pełny tekst źródłaStreszczenia konferencji na temat "Climate change model"
Arenson, Lukas, David Sego i Greg Newman. "The use of a convective heat flow model in road designs for Northern regions". W 2006 IEEE EIC Climate Change Conference. IEEE, 2006. http://dx.doi.org/10.1109/eicccc.2006.277276.
Pełny tekst źródłaHoltanová, Eva, i Tomáš Halenka. "Climate change scenarios". W První konference PERUN. Český hydrometeorologický ústav, 2023. http://dx.doi.org/10.59984/978-80-7653-063-8.03.
Pełny tekst źródła"The AgMIP Global Gridded Model Intercomparison". W ASABE 1st Climate Change Symposium: Adaptation and Mitigation. American Society of Agricultural and Biological Engineers, 2015. http://dx.doi.org/10.13031/cc.20152124282.
Pełny tekst źródłaCroce, Pietro, Paolo Formichi i Filippo Landi. "A BAYESIAN HIERARCHICAL MODEL FOR CLIMATIC LOADS UNDER CLIMATE CHANGE". W 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.
Pełny tekst źródła"New model for capturing heterogeneity of fertilizer-induced N2O emission factors". W ASABE 1st Climate Change Symposium: Adaptation and Mitigation. American Society of Agricultural and Biological Engineers, 2015. http://dx.doi.org/10.13031/cc.20152144930.
Pełny tekst źródła"Exploring Water Management Options with COWA: A Coupled Human-Climate-Water Model". W ASABE 1st Climate Change Symposium: Adaptation and Mitigation. American Society of Agricultural and Biological Engineers, 2015. http://dx.doi.org/10.13031/cc.20152144305.
Pełny tekst źródła"A computational fluid dynamics model of methane and ammonia emissions from tie-stall dairy barns". W ASABE 1st Climate Change Symposium: Adaptation and Mitigation. American Society of Agricultural and Biological Engineers, 2015. http://dx.doi.org/10.13031/cc.20152124152.
Pełny tekst źródłaMiller, Sara, Terrance Quinn i James Ianelli. "Estimation of Age-Specific Migration in an Age-Structured Model". W Resiliency of Gadid Stocks to Fishing and Climate Change. Alaska Sea Grant College Program, 2008. http://dx.doi.org/10.4027/rgsfcc.2008.09.
Pełny tekst źródła"Application of the CERES-Maize Model for Climate Change Impact Assessment in Rainfed Corn Production in Isabela, Philippines". W ASABE 1st Climate Change Symposium: Adaptation and Mitigation. American Society of Agricultural and Biological Engineers, 2015. http://dx.doi.org/10.13031/cc.20152088440.
Pełny tekst źródłaNissan, Hannah, Jim Clarke, Shirley Oliveira i Ralf Toumi. "Adapting to Climate Change: A Regional Climate Model Study of the Caucasus". W 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.
Pełny tekst źródłaRaporty organizacyjne na temat "Climate change model"
Dewart, Jean Marie. Conceptual Model of Climate Change Impacts at LANL. Office of Scientific and Technical Information (OSTI), maj 2016. http://dx.doi.org/10.2172/1253547.
Pełny tekst źródłaKocarev, Ljupco. An Interactive Multi-Model for Consensus on Climate Change. Office of Scientific and Technical Information (OSTI), lipiec 2014. http://dx.doi.org/10.2172/1136784.
Pełny tekst źródłaGillingham, Kenneth, William Nordhaus, David Anthoff, Geoffrey Blanford, Valentina Bosetti, Peter Christensen, Haewon McJeon, John Reilly i Paul Sztorc. Modeling Uncertainty in Climate Change: A Multi-Model Comparison. Cambridge, MA: National Bureau of Economic Research, październik 2015. http://dx.doi.org/10.3386/w21637.
Pełny tekst źródłaAuffhammer, Maximilian, Solomon Hsiang, Wolfram Schlenker i Adam Sobel. Using Weather Data and Climate Model Output in Economic Analyses of Climate Change. Cambridge, MA: National Bureau of Economic Research, maj 2013. http://dx.doi.org/10.3386/w19087.
Pełny tekst źródłaPolicy 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.
Pełny tekst źródłaKukla, G., i J. Gavin. Global climate change model natural climate variation: Paleoclimate data base, probabilities and astronomic predictors. Office of Scientific and Technical Information (OSTI), maj 1994. http://dx.doi.org/10.2172/145219.
Pełny tekst źródłaRussell, H. A. J., i 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.
Pełny tekst źródłaEdmonds, J. A., M. A. Wise i 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), maj 1994. http://dx.doi.org/10.2172/1127203.
Pełny tekst źródłaCooter, Ellen J., Brian K. Eder, Sharon K. LeDuc i 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.
Pełny tekst źródłaCooter, Ellen J., Brian K. Eder, Sharon K. LeDuc i 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.
Pełny tekst źródła