Analysis and prediction of global climate temperature change based on multiforced observational statistics.
The response of the climate system to increasing greenhouse gases was simulated by a number of climate model projections. There is an urgent need to verify or falsify these projections against observational climate data. Therefore, in this contribution, surface air temperature data are considered covering on a global average the period 1861-1990 and on a northern hemisphere average 1670-1990 (including proxy data). Based on a multiple correlation and coherence analysis a regression model is evaluated which is simultaneously forced by the observed or reconstructed atmospheric CO(2) or equivalent CO(2) concentration increase, volcanic activity, solar variations, and the ENSO (El Niño/southern oscillation) mechanism including phase shifts between cause and effect. This model reveals a greenhouse-gas-induced mean global temperature rise of 0.6-0.8 K since preindustrial time (c. 1800-1990). Following the IPCC business-as-usual scenario (trend extrapolation) this would lead to a hypothetical 3.8 K temperature rise in 2100 (best estimate, uncertainty + 0.7/-0.4 K compared to the 1985 value.
Schönwiese
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Institute for Meteorology and Geophysics, J.W. Goethe University, Praunheimer Landstr. 70, D-60488 Frankfurt, Germany.