Optimal signal detection theory has been applied in a search through 100 yr of surface temperature data for the climate response to four specific radiative forcings. The data used comes from 36 boxes on the earth and was restricted to the frequency band 0.06–0.13 cycles yr−1 (16.67–7.69 yr) in the analysis. Estimates were sought of the strengths of the climate response to solar variability, volcanic aerosols, greenhouse gases, and anthropogenic aerosols. The optimal filter was constructed with a signal waveform computed from a two-dimensional energy balance model (EBM). The optimal weights were computed from a 10000-yr control run of a noise-forced EBM and from 1000-yr control runs from coupled ocean–atmosphere models at Geophysical Fluid Dynamics Laboratory (GFDL) and Max-Planck Institute; the authors also used a 1000-yr run using the GFDL mixed layer model. Results are reasonably consistent across these four separate model formulations. It was found that the component of the volcanic response p... Abstract Optimal signal detection theory has been applied in a search through 100 yr of surface temperature data for the climate response to four specific radiative forcings. The data used comes from 36 boxes on the earth and was restricted to the frequency band 0.06–0.13 cycles yr−1 (16.67–7.69 yr) in the analysis. Estimates were sought of the strengths of the climate response to solar variability, volcanic aerosols, greenhouse gases, and anthropogenic aerosols. The optimal filter was constructed with a signal waveform computed from a two-dimensional energy balance model (EBM). The optimal weights were computed from a 10000-yr control run of a noise-forced EBM and from 1000-yr control runs from coupled ocean–atmosphere models at Geophysical Fluid Dynamics Laboratory (GFDL) and Max-Planck Institute; the authors also used a 1000-yr run using the GFDL mixed layer model. Results are reasonably consistent across these four separate model formulations. It was found that the component of the volcanic response p...