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Libros sobre el tema "Climate change model"

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Publicado: 18 de mayo de 2024

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1

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.

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2

Wendy, Howe, Henderson-Sellers A y Model Evaluation Consortium for Climate Assessment., eds. Assessing climate change: Results from the Model Evaluation Consortium for Climate Assessment. Amsterdam: Gordon and Breach Science Publishers, 1997.

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3

Ann-Maree, Hansen, ed. Climate change atlas: Greenhouse simulations from the Model Evaluation Consortium for Climate Assessment. Dordrecht: Kluwer Academic Publishers, 1995.

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4

Shrestha, Arun Bhakta. Climate change in the eastern Himalayas: Observed trends and model projections. Kathmandu: International Centre for Integrated Mountain Development, 2010.

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5

Sensitivity of a global climate model to the urban land unit. Middletown, Delaware: Legates Consulting Llc, 2013.

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6

Nozawa, 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.

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7

Hulme, 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.

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8

Grotch, 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.

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9

Nuttal, Pat, ed. Climate, ticks and disease. Wallingford: CABI, 2021. http://dx.doi.org/10.1079/9781789249637.0000.

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Abstract This book is a collection of 77 expert opinions arranged in three sections. Section 1 on "Climate" sets the scene, including predictions of future climate change, how climate change affects ecosystems, and how to model projections of the spatial distribution of ticks and tick-borne infections under different climate change scenarios. Section 2 on "Ticks" focuses on ticks (although tick-borne pathogens creep in) and whether or not changes in climate affect the tick biosphere, from physiology to ecology. Section 3 on "Disease" focuses on the tick-host-pathogen biosphere, ranging from the triangle of tick-host-pathogen molecular interactions to disease ecology in various regions and ecosystems of the world. Each of these three sections ends with a synopsis that aims to give a brief overview of all the expert opinions within the section. The book concludes with Section 4 (Final Synopsis and Future Predictions). This synopsis attempts to summarize evidence provided by the experts of tangible impacts of climate change on ticks and tick-borne infections. In constructing their expert opinions, contributors give their views on what the future might hold. The final synopsis provides a snapshot of their expert thoughts on the future.
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10

Jay, Hannah Lee, Conservation International y California Energy Commission. Public Interest Energy Research., eds. 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.

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11

Jay, Hannah Lee, Conservation International y California Energy Commission. Public Interest Energy Research., eds. 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.

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12

Peterson, David W. Climate change effects on vegetation in the Pacific Northwest: A review and synthesis of the scientific literature and simulation model projections. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station, 2014.

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13

C, Hughes Trevor, Wang Yi-Min y United States. Bureau of Reclamation. Provo Projects Office., eds. Impacts of projected climate change on urban water use: An application using the Wasatch Front water demand and supply model. Provo, Utah: U.S. Dept. of the Interior, Bureau of Reclamation, Provo Projects Office, 1994.

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14

Hansen, Roger. Impacts of projected climate change on urban water use: An application using the Wasatch Front water demand and supply model. Provo, Utah: U.S. Dept. of the Interior, Bureau of Reclamation, Provo Projects Office, 1994.

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15

Ashenfelter, Orley. Using a hedonic model of solar radiation to assess the economic effect of climate change: The case of Mosel Valley Vineyards. Cambridge, Mass: National Bureau of Economic Research, 2006.

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16

Conway, Declan. The development of a grid-based hydrologic model of the Blue Nile and the sensitivity of Nile River discharge to climate change. Norwich: University of East Anglia, 1993.

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17

A, Schiffer R., United States. National Aeronautics and Space Administration., United Nations. Office for Outer Space Affairs. y United Nations Conference on the Exploration and Peaceful Uses of Outer Space (3rd : 1999 : Vienna, Austria), eds. NASA Scientific Forum on Climate Variability and Global Change: 20 July 1999 : UNISPACE III : third United Nations Conference on the Exploration and Peaceful Uses of Outer Space, 19-30 July 1999. [Washington, DC]: Published by National Aeronautics and Space Administration as a contribution to United Nations Office of Outer Space Affairs for UNISPACE III, 1999.

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18

A, Schiffer R., United States. National Aeronautics and Space Administration., United Nations. Office for Outer Space Affairs. y United Nations Conference on the Exploration and Peaceful Uses of Outer Space (3rd : 1999 : Vienna, Austria), eds. NASA Scientific Forum on Climate Variability and Global Change: 20 July 1999 : UNISPACE III : third United Nations Conference on the Exploration and Peaceful Uses of Outer Space, 19-30 July 1999. [Washington, DC]: Published by National Aeronautics and Space Administration as a contribution to United Nations Office of Outer Space Affairs for UNISPACE III, 1999.

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19

NASA Scientific Forum on Climate Variability and Global Change (1999 Vienna, Austria). NASA Scientific Forum on Climate Variability and Global Change: 20 July 1999 : UNISPACE III. [Washington, DC]: Published by National Aeronautics and Space Administration as a contribution to United Nations Office of Outer Space Affairs for UNISPACE III, 1999.

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20

Aragón, Carlos A. Development and testing of a semi-distributed watershed model: Case studies exploring the impact of climate variability and change in the Rio Salado. Las Cruces, N.M: New Mexico Water Resources Research Institute, New Mexico State University, 2008.

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21

DeCanio, Stephen J. Economic Models of Climate Change. London: Palgrave Macmillan UK, 2003. http://dx.doi.org/10.1057/9780230509467.

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22

Felix, Chami, Pwiti Gilbert y Radimilahy Marie de Chantal, eds. Climate change, trade, and modes of production in sub-Saharan Africa. Dar es Salaam, Tanzania: Dar es Salaam University Press, 2003.

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23

Ji yu CGE de ji shu bian hua mo ni ji qi zai qi hou zheng ce fen xi zhong de ying yong: Technological change simulation and its application in climate change policy analysis based on a CGE model. Beijing: Zhongguo huan jing ke xue chu ban she, 2011.

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24

Hengeveld, Henry. Projections for Canada's climate future: A discussion of recent simulations with the Canadian global climate model. [Ottawa]: Environment Canada, 2000.

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25

United States. National Aeronautics and Space Administration., ed. Modeling climate change in the absence of climate change data: Editorial comment. [Washington, D.C: National Aeronautics and Space Administration, 1995.

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26

E, Schlesinger M., ed. Physically-based modelling and simulation of climate and climatic change. Dordrecht: Kluwer Academic Publishers, 1988.

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27

Wang, Zheng, Jing Wu, Changxin Liu y Gaoxiang Gu. Integrated Assessment Models of Climate Change Economics. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-3945-4.

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28

Ward, George H. Hydrological predictands for climate-change modeling. Denver, Colo: U.S. Dept. of the Interior, Bureau of Reclamation, Denver Office, 1996.

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29

Ward, George H. Hydrological predictands for climate-change modeling. Denver, Colo: U.S. Dept. of the Interior, Bureau of Reclamation, Denver Office, 1996.

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30

Cook, Kerry H. Climate Change Scenarios and African Climate Change. Oxford University Press, 2018. http://dx.doi.org/10.1093/acrefore/9780190228620.013.545.

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Accurate projections of climate change under increasing atmospheric greenhouse gas levels are needed to evaluate the environmental cost of anthropogenic emissions, and to guide mitigation efforts. These projections are nowhere more important than Africa, with its high dependence on rain-fed agriculture and, in many regions, limited resources for adaptation. Climate models provide our best method for climate prediction but there are uncertainties in projections, especially on regional space scale. In Africa, limitations of observational networks add to this uncertainty since a crucial step in improving model projections is comparisons with observations. Exceeding uncertainties associated with climate model simulation are uncertainties due to projections of future emissions of CO2 and other greenhouse gases. Humanity’s choices in emissions pathways will have profound effects on climate, especially after the mid-century.The African Sahel is a transition zone characterized by strong meridional precipitation and temperature gradients. Over West Africa, the Sahel marks the northernmost extent of the West African monsoon system. The region’s climate is known to be sensitive to sea surface temperatures, both regional and global, as well as to land surface conditions. Increasing atmospheric greenhouse gases are already causing amplified warming over the Sahara Desert and, consequently, increased rainfall in parts of the Sahel. Climate model projections indicate that much of this increased rainfall will be delivered in the form of more intense storm systems.The complicated and highly regional precipitation regimes of East Africa present a challenge for climate modeling. Within roughly 5º of latitude of the equator, rainfall is delivered in two seasons—the long rains in the spring, and the short rains in the fall. Regional climate model projections suggest that the long rains will weaken under greenhouse gas forcing, and the short rains season will extend farther into the winter months. Observations indicate that the long rains are already weakening.Changes in seasonal rainfall over parts of subtropical southern Africa are observed, with repercussions and challenges for agriculture and water availability. Some elements of these observed changes are captured in model simulations of greenhouse gas-induced climate change, especially an early demise of the rainy season. The projected changes are quite regional, however, and more high-resolution study is needed. In addition, there has been very limited study of climate change in the Congo Basin and across northern Africa. Continued efforts to understand and predict climate using higher-resolution simulation must be sustained to better understand observed and projected changes in the physical processes that support African precipitation systems as well as the teleconnections that communicate remote forcings into the continent.
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31

Hillel, Daniel, Cynthia Rosenzweig, American Society of Agronomy Staff, Crop Science Society of America Staff y Soil Science Society of America Staff. Handbook of Climate Change and Agroecosystems: The Agricultural Model Intercomparison and Improvement Project Integrated Crop and Economic Assessments. Imperial College Press, 2015.

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32

Henderson-Sellers, Ann y Wendy Howe. Assessing Climate Change: Results from the Model Evaluation Consortium for Climate Assessment. CRC, 1997.

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33

General circulation model output for forest climate change research and applications. Asheville, N.C. (P.O. Box 2680, Asheville 28802): U.S. Dept. of Agriculture, Forest Service, Southeastern Forest Experiment Station, 1993.

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34

General circulation model output for forest climate change research and applications. Asheville, N.C: U.S. Dept. of Agriculture, Forest Service, Southeastern Forest Experiment Station, 1993.

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35

Santha, Sunil D. Climate Change and Adaptive Innovation: A Model for Social Work Practice. Taylor & Francis Group, 2020.

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36

Bonen, Anthony, Sebastian Koch, Prakash Loungani y Willi Semmler. Investing to Mitigate and Adapt to Climate Change: A Framework Model. International Monetary Fund, 2016.

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37

Santha, Sunil D. Climate Change and Adaptive Innovation: A Model for Social Work Practice. Taylor & Francis Group, 2020.

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38

Santha, Sunil D. Climate Change and Adaptive Innovation: A Model for Social Work Practice. Taylor & Francis Group, 2020.

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39

Santha, Sunil D. Climate Change and Adaptive Innovation: A Model for Social Work Practice. Taylor & Francis Group, 2022.

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40

Santha, Sunil D. Climate Change and Adaptive Innovation: A Model for Social Work Practice. Taylor & Francis Group, 2020.

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41

Bonen, Anthony, Sebastian Koch, Prakash Loungani y Willi Semmler. Investing to Mitigate and Adapt to Climate Change: A Framework Model. International Monetary Fund, 2016.

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42

Bonen, Anthony, Sebastian Koch, Prakash Loungani y Willi Semmler. Investing to Mitigate and Adapt to Climate Change: A Framework Model. International Monetary Fund, 2016.

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43

Delina, Laurence L. Strategies for Rapid Climate Mitigation: Wartime Mobilisation As a Model for Action? Taylor & Francis Group, 2016.

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44

Delina, Laurence L. Strategies for Rapid Climate Mitigation: Wartime Mobilisation As a Model for Action? Taylor & Francis Group, 2016.

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45

Strategies for Rapid Climate Mitigation: Wartime Mobilisation As a Model for Action? Taylor & Francis Group, 2016.

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46

Keskitalo, E. C. H. Social Aspects of Environmental and Climate Change: Institutional Dynamics Beyond a Linear Model. Taylor & Francis Group, 2021.

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47

Social Aspects of Environmental and Climate Change: Institutional Dynamics Beyond a Linear Model. Taylor & Francis Group, 2021.

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48

Keskitalo, E. C. H. Social Aspects of Environmental and Climate Change: Institutional Dynamics Beyond a Linear Model. Routledge, 2022.

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49

Keskitalo, E. C. H. Social Aspects of Environmental and Climate Change: Institutional Dynamics Beyond a Linear Model. Routledge, 2022.

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50

Atolia, Manoj, Helmut Maurer, Prakash Loungani y Willi Semmler. Optimal Control of a Global Model of Climate Change with Adaptation and Mitigation. International Monetary Fund, 2018.

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