The two main drivers of climate change on sub-Milankovic time scales are re-assessed by means of a multiple regression analysis. Evaluating linear combinations of the logarithm of carbon dioxide concentration and the geomagnetic aa-index as a proxy for solar activity, we reproduce the sea surface temperature (HadSST) since the middle of the 19th century with an adjusted 𝑅2 value of around 87 per cent for a climate sensitivity (of TCR type) in the range of 0.6 K until 1.6 K per doubling of CO2. The solution of the regression is quite sensitive: when including data from the last decade, the simultaneous occurrence of a strong El Niño on one side and low aa-values on the other side lead to a preponderance of solutions with relatively high climate sensitivities around 1.6 K. If those later data are excluded, the regression leads to a significantly higher weight of the aa-index and a correspondingly lower climate sensitivity going down to 0.6 K. The plausibility of such low values is discussed in view of recent experimental and satellite borne measurements. We argue that a further decade of data collection will be needed to allow for a reliable distinction between low and high sensitivity values. Based on recent ideas about a quasi deterministic planetary synchronization of the solar dynamo, we make a first attempt to predict the aa-index and the resulting temperature anomaly for various typical CO2 scenarios. Even for the highest climate sensitivities, and an unabated linear CO2 increase, we predict only a mild additional temperature rise of around 1 K until the end of the century, while for the lower values an imminent temperature drop in the near future, followed by a rather flat temperature curve, is prognosticated.
This Arxiv preprint employs a multiple regression analysis with the time series of the geomagnetic aa-index as a proxy for solar activity (“aa-index”) as an independent variable along with the logarithm of CO2 concentration commonly used in climate models. Stefani shows that the temperature variation since the middle of the 19th century can be repro-
duced with an (adjusted) 𝑅2 value around 87 per cent.
Stefani achieves such a high goodness-of-fit (exceeding IPCC AR5 correlation for a GHG-only model) by employing specific combinations of the weights of the aa-index and of CO2 forming a nearly linear function in their two-dimensional parameter space.
Stefani’s reports climate sensitivity in the range between 0.6 K-1.6 K (per 2× CO2). He interprets this finding as a transient climate response (TCR), rather than an ECS.
Notably, Stefani’s results correspond well with that of Lewis and Curry (2018), 0.8 K-
Lewis, N., Curry, J. (2018). The Impact of Recent Forcing and Ocean Heat Uptake Data on Estimates of Climate Sensitivity. J. Climate 31, 6051-6071.
Stefani, F. (2021). Multiple regression analysis of anthropogenic and heliogenic climate drivers, and some cautious forecasts. Retrieved from http://arxiv.org/abs/2101.05183