Probabilistic projections of the future climate for the world and the continental USA

In this paper, we study possible impacts of anthropogenic greenhouse gas (GHG) emissions on the 21st century climate on the continental USA using the MIT Integrated Global System Model (IGSM) framework. Climate change simulations use an emissions scenario developed with the IGSM’s Economic Projectio...

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Bibliographic Details
Main Authors: Sokolov, A., Gao, X., Paltsev, S., Monier, E., Chen, H., Kicklighter, D., Prinn, R., Reilly, J., Schlosser, A.
Format: Working Paper
Language:en_US
Published: MIT Joint Program on the Science and Policy of Global Change 2017
Online Access:http://hdl.handle.net/1721.1/111820
Description
Summary:In this paper, we study possible impacts of anthropogenic greenhouse gas (GHG) emissions on the 21st century climate on the continental USA using the MIT Integrated Global System Model (IGSM) framework. Climate change simulations use an emissions scenario developed with the IGSM’s Economic Projection and Policy Analysis (EPPA) Model. The scenario represents a global emission path consistent with the current view on the trajectories of technological and economic development. The estimates of possible changes in climate are based on an ensemble of 400 simulations with the IGSM’s MIT Earth System Model (MESM), a model of intermediate complexity. Regional changes over the USA were obtained using statistical downscaling that incorporates results from the simulations with the CMIP5 Atmosphere-Ocean General Circulation Models (AOGCMs). The results show that under the considered emissions scenario, surface air temperature averaged over the continental USA increases by 2.6 to 4.4K by the last decade of the 21st century (90% probability interval) relative to pre-industrial temperatures, compare to 2.3 to 3.4K for the whole globe. Corresponding changes in precipitation are -0.65 to 0.34 mm/day and 0.13 to 0.22 mm/day, respectively. There is significant variation in the geographical distribution of those changes among the ensemble simulations.