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gfdl on-line bibliography > 2004 citations
Simple indices of global climate variability and change Part II: attribution of climate change during the twentieth century
| Braganza, K., D. J. Karoly, A. C. Hirst, P. Stott, R. J. Stouffer, and S. F. B. Tett, 2004: Simple indices of global climate variability and change Part II: attribution of climate change during the twentieth century. Climate Dynamics, 22(8), 823-838. |
Abstract: Five
simple indices of surface temperature are used to investigate the influence
of anthropogenic and natural (solar irradiance and volcanic aerosol) forcing
on observed climate change during the twentieth century. These indices are
based on spatial fingerprints of climate change and include the global-mean
surface temperature, the land-ocean temperature contrast, the magnitude of
the annual cycle in surface temperature over land, the Northern Hemisphere
meridional temperature gradient and the hemispheric temperature contrast.
The indices contain information independent of variations in global-mean
temperature for unforced climate variations and hence, considered
collectively, they are more useful in an attribution study than global mean
surface temperature alone. Observed linear trends over 1950–1999 in all the
indices except the hemispheric temperature contrast are significantly larger
than simulated changes due to internal variability or natural (solar and
volcanic aerosol) forcings and are consistent with simulated changes due to
anthropogenic (greenhouse gas and sulfate aerosol) forcing. The combined,
relative influence of these different forcings on observed trends during the
twentieth century is investigated using linear regression of the observed
and simulated responses of the indices. It is found that anthropogenic
forcing accounts for almost all of the observed changes in surface
temperature during 1946–1995. We found that early twentieth century changes
(1896–1945) in global mean temperature can be explained by a combination of
anthropogenic and natural forcing, as well as internal climate variability.
Estimates of
 scaling
factors
that weight the amplitude of model simulated signals to corresponding
observed changes using a combined normalized index are similar to those
calculated using more complex, optimal fingerprint techniques. |