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Modeling the climate and carbon systems to estimate the social cost of carbon

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  • Tammy M. Thompson

Abstract

This study compares 10 models of the global carbon and climate systems, that represent model sophistication ranging from very simple parameterizations to Earth System Models of Intermediate complexity (EMICS): DICE, PAGE, FUND, FAIR, Hector, OSCAR, ACC2, MAGICC, MESM, and UVic. The focus of this analysis is on how these models meet scientific design and transparency criteria recommended by a recent Committee of the National Academy of Sciences, Engineering and Medicine, for developing a monetized estimate of the future damages from an incremental increase in carbon dioxide emissions in a given year (i.e., the social cost of carbon dioxide [SC‐CO2]). The National Academies report directly addresses methods for estimating the SC‐CO2, including a chapter outlining specific recommendations for a carbon/climate module. The carbon/climate piece of the model platform will capture the dispersion of carbon and energy through the earth system, and estimate the resulting change in several globally averaged metrics: temperature change, sea level, and ocean acidity. A number of model characteristics are evaluated and the findings identify models that meet the recommendations associated with each characteristic. Based on these findings, there are several publically available carbon/climate models that would meet the recommendations presented by the National Academies. This article is categorized under: Climate Economics > Economics and Climate Change

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  • Tammy M. Thompson, 2018. "Modeling the climate and carbon systems to estimate the social cost of carbon," Wiley Interdisciplinary Reviews: Climate Change, John Wiley & Sons, vol. 9(5), September.
  • Handle: RePEc:wly:wirecc:v:9:y:2018:i:5:n:e532
    DOI: 10.1002/wcc.532
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    Cited by:

    1. Furui Xi & Gang Lin & Yanan Zhao & Xiang Li & Zhiyu Chen & Chenglong Cao, 2023. "Land Use Optimization and Carbon Storage Estimation in the Yellow River Basin, China," Sustainability, MDPI, vol. 15(14), pages 1-17, July.
    2. Qing Liu & Dongdong Yang & Lei Cao & Bruce Anderson, 2022. "Assessment and Prediction of Carbon Storage Based on Land Use/Land Cover Dynamics in the Tropics: A Case Study of Hainan Island, China," Land, MDPI, vol. 11(2), pages 1-24, February.

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