Notes: Abstract Based on univariate correlation and coherence analyses and considering the physical basis of the relationships, a simple multiforced (multiple) statistical concept is used which correlates observational climatic time series simultaneously with volcanic, solar, ENSO, and the anthropogenic greenhouse gases forcing. This is appropriate to remove some natural climate noise in the observed data and to evaluate the components (signals) possibly due to the anthropogenic greenhouse gas forcing (CO2, or “equivalent” CO2 implying additional gases) during industrial time. In this paper, we apply this technique to 100 global “box” data time series 1890–1985, of the surface air temperature, using observed data from Hansen and Lebedeff. The results are presented in terms of latitudinal-seasonal and regional trends, where the observed trend patterns are compared with the hypothetical signals (statistical assessments) possibly due to anthropogenic greenhouse forcing. These latter signals can be amplified to enable a comparison with corresponding results from general circulation model (GCM) CO2 doubling experiments. These observed-statistical assessments lead to results which are, at least qualitatively and in respect to the zonal mean temperatures, very similar to some GCM experiments indicating the maximum CO2 doubling signals (statistical assessment 〉 12 K) in the arctic winter. However, these signals are moderate in the tropics and in the Southern Hemisphere (global average 2.8–4.4 K). As far as the “industrial” signals are concerned (observed period) these signals are somewhat larger (maximum 7 K, global average 0.5–0.9 K) than the observed trends (maximum 5 K, global average 0.5 K). Phase shifts of cause and effect may amplify these signals but are very uncertain.

Notes: Abstract Analyses indicate that the Atlantic Ocean seasurface temperature (SST) was considerably colder at the beginning than in the middle of the century. In parallel, a systematic change in the North Atlantic sea-level pressure (SLP) pattern was observed. To find out whether the SST and SLP changes analyzed are consistent, which would indicate that the SST change was real and not an instrumental artifact, a response experiment with a low-resolution (T21) atmospheric GCM was performed. Two perpetual January simulations were conducted, which differ solely in the Atlantic Ocean (40° S-60° N) SST: the “cold” simulation utilizes the SSTs for the period 1904–1913; the “warm” simulation uses the SSTs for the period 1951–1960. Also, a “control” run with the model's standard SST somewhat between the “cold” and “warm” SST was made. For the response analysis, a rigorous statistical approach was taken. First, the null hypothesis of identical horizontal distributions was subjected to a multivariate significance test. Second, the level of recurrence was estimated. The multivariate statistical approaches are based on hierarchies of test models. We examined three different hierarchies: a scale-dependent hierarchy based on spherical harmonics (S), and two physically motivated ones, one based on the barotropic normal modes of the mean 300 hPa flow (B) and one based on the eigenmodes of the advection diffusion operator at 1000 hPa (A). The intercomparison of the “cold” and “warm” experiments indicates a signal in the geostrophic stream function that in the S-hierarchy is significantly nonzero and highly recurrent. In the A-hierarchy, the low level temperature field is identified as being significantly and recurrently affected by the altered SST distribution. The SLP signal is reasonably similar to the SLP change observed. Unexpectedly, the upper level stream-function signal does not appear to be significantly nonzero in the B-hierarchy. If, however, the pairs of experiments “warm versus control” and “cold versus control” are examined in the B-hierarchy, a highly significant and recurrent signal emerges. We conclude that the “cold versus warm” response is not a “small disturbance” that would allow the signal to be described by eigenmodes of the linear system. An analysis of the three-dimensional structure of the signal leads to the hypothesis that two different mechanisms are acting to modify the model's mean state. At low levels, local heating and advection are dominant, but at upper levels the extratropical signal is a remote responce to modifications of the tropical convection.