Regions of significant influence on unforced global mean surface air temperature variability in climate models
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2015
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We document the geographic regions where local variability is most associated with unforced global mean surface air temperature (GMT) variability in Coupled Model Intercomparison Project Phase 5 coupled global climate models (GCMs) at both the subdecadal and interdecadal timescales. For this purpose, Regions of Significant Influence on GMT are defined as locations that have a statistically significant correlation between local surface air temperature (SAT) and GMT (with a regression slope greater than 1), and where local SAT variation leads GMT variation in time. In both GCMs and observations, subdecadal timescale GMT variability is most associated with SAT variation over the eastern equatorial Pacific. At the interdecadal timescale, GMT variability is also linked with SAT variation over the Pacific in many GCMs, but the particular spatial patterns are GCM dependent, and several GCMs indicate a primary association between GMT and SAT over the Southern Ocean. We find that it is difficult to validate GCM behavior at the interdecadal timescale because the pattern derived from observations is highly depended on the method used to remove the forced variability from the record. The magnitude of observed GMT variability is near the ensemble median at the subdecadal timescale but well above the median at the interdecadal timescale. GCMs with a stronger subdecadal relationship between GMT and SAT over the Pacific tend to have more variable subdecadal GMT while GCMs with a stronger interdecadal relationship between GMT and SAT over parts of the Southern Ocean tend to have more variable GMT.
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Brown, PT, W. Li, S Xie (2015). Regions of significant influence on unforced global mean surface air temperature variability in climate models. Journal of Geophysical Research D: Atmospheres. 10.1002/2014JD022576 Retrieved from https://hdl.handle.net/10161/9564.
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Wenhong Li
Dr. Li's research interests focus primarily on climate dynamics, land-atmosphere interaction, hydroclimatology, and climate modeling. Her current research is to understand how the hydrological cycle changes in the current and future climate and their impacts on the ecosystems, subtropical high variability and change, unforced global temperature variability, and climate and health issues.
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