Monday, 15 January 2007: 4:00 PM
Detection and Attribution of Regional Climate
Ballroom C2 (Henry B. Gonzalez Convention Center)
Peter Stott, Hadley Centre for Climate Modelling and Analysis, UK Met Office, Exeter, Devon, United Kingdom
There has been widespread warming near the surface of the Earth over the last fifty years and an increasing body of evidence shows that the most important contributor to this warming was human induced greenhouse gas emissions. The global-scale patterns of observed near-surface temperature changes allow a quantitative assessment of the contributions of different forcing agents to past temperature changes, including well-mixed greenhouse gases, tropospheric sulfate aerosols, and natural climate factors such as changing solar irradiance and volcanic aerosols. Distinctive temporal structures in differential warming rates between the hemispheres, between land and ocean, and between mid-and low latitudes show that greenhouse warming has been offset by cooling from aerosols. Knowledge of the contributors to past temperature change in turn provides information about likely future rates of temperature change.
As the signal of climate change strengthens and emerges at smaller scales, evidence is accumulating for a detectable anthropogenic influence on continental and sub-continental scales. As temperatures increase, the risk of extreme events also increases and a methodology has been developed for assessing the fraction of risk of such events attributable to human influence, such as the 2003 European heatwave or the exceptionally hot summer temperatures seen in the US during 2006. Difficulties remain in attributing temperature changes at smaller scales; the signal to noise is less and the credibility of models' ability to simulate small-scale features is lower than for large-scale features. Nevertheless long records in some regions, such as the Central England Temperature record, which stretches back to 1659 and is the longest continuous instrumental surface temperature series available, can help to put recent warming in a long term context and assess the ability of climate models to represent natural climate variability, against which the significance of forced climate changes can be assessed.
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