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Climate Change Detection and Attribution: Beyond Mean Temperature Signals


Hegerl, GC and Karl, TR and Allen, M and Bindoff, NL and Gillett, N and Karoly, D and Zhang, X and Zwiers, F, Climate Change Detection and Attribution: Beyond Mean Temperature Signals, Journal of Climate, 19, (20) pp. 5058-5077. ISSN 0894-8755 (2006) [Refereed Article]

DOI: doi:10.1175/JCLI3900.1


A significant influence of anthropogenic forcing has been detected in global- and continental-scale surface temperature, temperature of the free atmosphere, and global ocean heat uptake. This paper reviews outstanding issues in the detection of climate change and attribution to causes. The detection of changes in variables other than temperature, on regional scales and in climate extremes, is important for evaluating model simulations of changes in societally relevant scales and variables. For example, sea level pressure changes are detectable but are significantly stronger in observations than the changes simulated in climate models, raising questions about simulated changes in climate dynamics. Application of detection and attribution methods to ocean data focusing not only on heat storage but also on the penetration of the anthropogenic signal into the ocean interior, and its effect on global water masses, helps to increase confidence in simulated large-scale changes in the ocean. To evaluate climate change signals with smaller spatial and temporal scales, improved and more densely sampled data are needed in both the atmosphere and ocean. Also, the problem of how model-simulated climate extremes can be compared to station-based observations needs to be addressed. © 2006 American Meteorological Society.

Item Details

Item Type:Refereed Article
Research Division:Earth Sciences
Research Group:Oceanography
Research Field:Physical oceanography
Objective Division:Environmental Policy, Climate Change and Natural Hazards
Objective Group:Adaptation to climate change
Objective Field:Social impacts of climate change and variability
UTAS Author:Bindoff, NL (Professor Nathan Bindoff)
ID Code:47902
Year Published:2006
Web of Science® Times Cited:68
Deposited By:IASOS
Deposited On:2007-08-01
Last Modified:2007-09-24

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