Probabilistic projections of 21st century climate change over Northern Eurasia

We present probabilistic projections of 21st century climate change over Northern Eurasia using the Massachusetts Institute of Technology (MIT) Integrated Global System Model (IGSM), an integrated assessment model that couples an Earth system model of intermediate complexity with a two-dimensional z...

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Bibliographic Details
Main Authors: Monier, Erwan (Contributor), Sokolov, Andrei P. (Contributor), Schlosser, Adam (Contributor), Scott, Jeffery R. (Contributor), Gao, Xiang (Contributor)
Other Authors: Massachusetts Institute of Technology. Joint Program on the Science & Policy of Global Change (Contributor)
Format: Article
Language:English
Published: Institute of Physics Publishing, 2014-04-16T15:33:26Z.
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001 86179
042 |a dc 
100 1 0 |a Monier, Erwan  |e author 
100 1 0 |a Massachusetts Institute of Technology. Joint Program on the Science & Policy of Global Change  |e contributor 
100 1 0 |a Monier, Erwan  |e contributor 
100 1 0 |a Sokolov, Andrei P.  |e contributor 
100 1 0 |a Schlosser, Adam  |e contributor 
100 1 0 |a Scott, Jeffery R.  |e contributor 
100 1 0 |a Gao, Xiang  |e contributor 
700 1 0 |a Sokolov, Andrei P.  |e author 
700 1 0 |a Schlosser, Adam  |e author 
700 1 0 |a Scott, Jeffery R.  |e author 
700 1 0 |a Gao, Xiang  |e author 
245 0 0 |a Probabilistic projections of 21st century climate change over Northern Eurasia 
260 |b Institute of Physics Publishing,   |c 2014-04-16T15:33:26Z. 
856 |z Get fulltext  |u http://hdl.handle.net/1721.1/86179 
520 |a We present probabilistic projections of 21st century climate change over Northern Eurasia using the Massachusetts Institute of Technology (MIT) Integrated Global System Model (IGSM), an integrated assessment model that couples an Earth system model of intermediate complexity with a two-dimensional zonal-mean atmosphere to a human activity model. Regional climate change is obtained by two downscaling methods: a dynamical downscaling, where the IGSM is linked to a three-dimensional atmospheric model, and a statistical downscaling, where a pattern scaling algorithm uses climate change patterns from 17 climate models. This framework allows for four major sources of uncertainty in future projections of regional climate change to be accounted for: emissions projections, climate system parameters (climate sensitivity, strength of aerosol forcing and ocean heat uptake rate), natural variability, and structural uncertainty. The results show that the choice of climate policy and the climate parameters are the largest drivers of uncertainty. We also find that different initial conditions lead to differences in patterns of change as large as when using different climate models. Finally, this analysis reveals the wide range of possible climate change over Northern Eurasia, emphasizing the need to consider these sources of uncertainty when modeling climate impacts over Northern Eurasia. 
520 |a United States. Dept. of Energy (Office of Biological and Environmental Research, grant DE-FG02-94ER61937) 
546 |a en_US 
655 7 |a Article 
773 |t Environmental Research Letters