Detecting climate signals using space-time EOFs

Estimates of the amplitudes of the forced responses of the surface temperat ure field over the last century are provided by a signal processing scheme utilizing space-time empirical orthogonal functions for several combination s of station sites and record intervals taken from the last century. These century-long signal fingerprints come mainly from energy balance model calc ulations, which are shown to be very close to smoothed ensemble average run s from a coupled ocean-atmosphere model (Hadley Centre Model). The spacetim e lagged covariance matrices of natural variability come from 100-yr contro l runs from several well-known coupled ocean-atmosphere models as well as a 10000-yr run from the stochastic energy balance climate model (EBCM). Evid ence is found for robust, but weaker than expected signals from the greenho use [amplitude similar to 65% of that expected for a rather insensitive mod el (EBCM: DeltaT(2xCO2) approximate to 2.3 degreesC)], volcanic (also about 65% expected amplitude), and even the 11-yr component of the solar signal (a most probable value of about 2.0 times that expected). In the analysis t he anthropogenic aerosol signal is weak and the null hypothesis for this si gnal can only be rejected in a few sampling configurations involving the la st 50 yr of the record. During the last 50 yr the full strength value (1.0) also lies within the 90% confidence interval. Some amplitude estimation re sults based upon the (temporally smoothed) Hadley fingerprints are included and the results are indistinguishable from those based on the EBCM. In add ition, a geometrical derivation of the multiple regression formula from the filter point of view is provided, which shows how the signals "not of inte rest" are removed from the data stream in the estimation process. The crite ria for truncating the EOF sequence are somewhat different from earlier ana lyses in that the amount of the signal variance accounted for at a given le vel of truncation is explicitly taken into account.