DETECTING CLIMATE SIGNALS IN THE SURFACE-TEMPERATURE RECORD

Optimal signal detection theory has been applied in a search through 1 00 yr of surface temperature data for the climate response to four spe cific radiative forcings. The data used comes from 36 boxes on the ear th and was restricted to the frequency band 0.06-0.13 cycles yr(-1) (1 6.67-7.69 yr) in the analysis. Estimates were sought of the strengths of the climate response to solar variability, volcanic aerosols, green house gases, and anthropogenic aerosols. The optimal Biter was constru cted with a signal waveform computed From a two-dimensional energy bal ance model (EBM). The optimal weights were computed from a 10000-yr co ntrol run of a noise-forced EBM and from 1000-yr control runs from cou pled ocean-atmosphere models at Geophysical Fluid Dynamics Laboratory (GFDL) and Max-Planck Institute; the authors also used a 1000-yr run u sing the GFDL mixed layer model. Results are reasonably consistent acr oss these four separate model formulations. It was found that the comp onent of the volcanic response perpendicular to the other signals was very robust and highly significant. Similarly, the component of the gr eenhouse gas response perpendicular to the others was very robust and highly significant. When the sum of all four climate forcings was used , the climate response was more than three standard deviations above t he noise level. These findings are considered to be powerful evidence of anthropogenically induced climate change.