89th American Meteorological Society Annual Meeting

Monday, 12 January 2009: 4:45 PM
Climate change projections with observation-based interannual variability
Room 129A (Phoenix Convention Center)
David S. Gutzler, University of New Mexico, Albuquerque, NM
Climate change scenarios on a regional scale are developed by superimposing a model-projected 21st Century linear trend in temperature or precipitation to a repetition of observed 20th Century interannual variability. This procedure allows the projected trend to be placed into context with realistic variability, and facilitates assessment of the projected trend in terms of historical climate variability.

To illustrate, we consider the linear trend of temperature or precipitation in various U.S. Climate Divisions for the 21st Century generated from an average of 18 global models forced by the A1B scenario of greenhouse gas concentration changes, as shown in the IPCC Fourth Assessment report. Historical 20th Century anomalies for the same climate divisions are used to generate interannual variability, and superimposed on the 21st Century linear trend to generate the climate change scenario for each Division.

By mid-century, the summer season exhibits a higher average temperature every year than any summer season ever observed in the instrumental record, i.e. summer temperatures quickly rise outside the climatic historical range of variability. Winter temperatures, in contrast, do not fall outside the range of observed 20th Century winters until much later in the 21st Century. This seasonal difference occurs in part because summer trends are larger in magnitude than winter trends. More importantly, however, interannual variability is much larger in in winter than in summer so that "cold winters" in the mid-21st Century are comparable to "average" winter temperatures experienced in the current climate.

Temperature changes associated with projected trends are much greater relative to interannual variability than are the corresponding precipitation changes. The results re-emphasize that temperature presents a much larger and more significant climate change signal in the A1B simulation than precipitation.

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