首页 | 本学科首页   官方微博 | 高级检索  
     检索      


Integrated Global System Model for Climate Policy Assessment: Feedbacks and Sensitivity Studies
Authors:R Prinn  H Jacoby  A Sokolov  C Wang  X Xiao  Z Yang  R Eckhaus  P Stone  D Ellerman  J Melillo  J Fitzmaurice  D Kicklighter  G Holian  Y Liu
Institution:(1) Joint Program on the Science and Policy of Global Change, MIT, Bldg. E40-271, Cambridge, MA, 02139, U.S.A.;(2) Marine Biological Laboratory, The Ecosystems Center, Woods Hole, MA, 02543, U.S.A.
Abstract:Alternative policies to address global climate change are being debated in many nations and within the United Nations Framework Convention on Climate Change. To help provide objective and comprehensive analyses in support of this process, we have developed a model of the global climate system consisting of coupled sub-models of economic growth and associated emissions, natural fluxes, atmospheric chemistry, climate, and natural terrestrial ecosystems. The framework of this Integrated Global System Model is described and the results of sample runs and a sensitivity analysis are presented. This multi-component model addresses most of the major anthropogenic and natural processes involved in climate change and also is computationally efficient. As such, it can be used effectively to study parametric and structural uncertainty and to analyze the costs and impacts of many policy alternatives. Initial runs of the model have helped to define and quantify a number of feedbacks among the sub-models, and to elucidate the geographical variations in several variables that are relevant to climate science and policy. The effect of changes in climate and atmospheric carbon dioxide levels on the uptake of carbon and emissions of methane and nitrous oxide by land ecosystems is one potentially important feedback which has been identified. The sensitivity analysis has enabled preliminary assessment of the effects of uncertainty in the economic, atmospheric chemistry, and climate sub-models as they influence critical model results such as predictions of temperature, sea level, rainfall, and ecosystem productivity. We conclude that uncertainty regarding economic growth, technological change, deep oceanic circulation, aerosol radiative forcing, and cloud processes are important influences on these outputs.
Keywords:
本文献已被 SpringerLink 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号