Detecting changes in global climate induced by greenhouse gases

A quantitative search for a theoretically predicted CO₂ signal in surface air temperature data extending back to 1899 was marginally successful in a statistical sense. However, the nature of the signal strength time series suggested that this result is an artifact of large-scale decadal variations at the beginning and end of the record. Application of the "fingerprint" strategy to three different global fields of climate variables over the last 25-35 years showed no significant CO₂ signal. The analysis pointed up the need to use: (1) model signal-to-noise ratios in selecting fields for subsequent analysis and (2) multiple fields in the detection process. Most importantly, we found the primary pattern of natural air temperature variability to be very similar to the expected CO₂ signal, thus suggesting that the air temperature field is not the best place to attempt early detection of the CO₂ signal. By contrast, the primary pattern of natural variability and the expected CO₂ signal in the ocean's surface temperature are substantially different; this suggests the oceans as a low-noise environment in which to attempt early detection.