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HERO ID
2009392
Reference Type
Journal Article
Title
Prediction of decadal variability of sea surface temperature by a coupled global climate model FGOALS_gl developed in LASG/IAP
Author(s)
Wu Bo; Zhou TianJun
Year
2012
Is Peer Reviewed?
Yes
Journal
Chinese Science Bulletin
ISSN:
1001-6538
EISSN:
1861-9541
Volume
57
Issue
19
Page Numbers
2453-2459
DOI
10.1007/s11434-012-5134-y
Web of Science Id
WOS:000305564000017
Abstract
A decadal climate prediction was performed by a coupled global climate model FGOALS_gl developed by the State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics (LASG) within the Institute of Atmospheric Physics (IAP), Chinese Academy of Sciences. First, an Incremental Analysis Updates (IAU) scheme was applied to assimilate surface and subsurface ocean temperature and salinity fields derived from oceanic objective analysis data, for the initialization of the ocean component of the model. Starting from the initialized states, hindcast integrations were performed with the specified historical solar cycle variations, concentrations of greenhouse gasses and sulfate aerosol, following the standard 20C3M scenario used in phase three of the Coupled Model Intercomparison Project (CMIP3). Based on the hindcast integrations, we performed forecast integrations under the radiative forcing of the A1B scenario in the CMIP3. Compared with the 20C3M run, the hindcast integrations have a much higher ability to simulate the decadal variability of SST (Sea Surface Temperature) in the tropical central-eastern Pacific and mid-latitude northeastern Pacific. This suggests that the ocean initialization is able to enhance the model skill in the regions with large decadal variability. The forecast integrations suggest that the SST in the tropical central-eastern Pacific has reached its trough phase, and will gradually increase in the following 10-15 years. Meanwhile, the global mean surface temperature predicted by the forecast integrations increases slower than that projected by the A1B scenario run over 2000-2010, but faster than the latter after that.
Keywords
decadal prediction; CGCM; IPCC AR5
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