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Solar and anthropogenic climate drivers: an updated regression model and refined forecast

In a recent paper attempts were made to quantify the respective solar and anthropogenic influences on the terrestrial climate, and to cautiously predict the global mean temperature over the next 130 years. In a double regression analysis, both the binary logarithm of carbon dioxide concentration and the geomagnetic aa-index were used as predictors of the sea surface temperature (SST) since the mid-19th century. The regression results turned out to be sensitive to end effects, leading to a broad range of the climate sensitivity between 0.6 K and 1.6 K per doubling of CO$_2$ when varying the final year. The aim of this paper is to narrow down this range. To this end, the correlations between the two predictors and the dependent variable (SST) are analysed in detail. It is demonstrated that the SST can be predicted until around 2000 almost perfectly using only the aa-index, whereas for later periods the role of CO$_2$ increases significantly. Hence, the weight of the aa-index is fixed to its robust outcome (around 0.04 K/nT) from the regressions up to 1990. The SST data, reduced by the aa-contribution thus specified, are then used in a single regression with CO$_2$ as the only remaining predictor. This results in a significant reduction in the range of CO$_2$ sensitivity, narrowing it to 1.1-1.4 K. Given the exceptionally high temperatures in recent years, these values are considered a kind of upper limit that could still be subject to downward corrections when future data are incorporated. Based on this estimate, the temperature forecast until 2100 is refined by using more precise predictions of the aa-index and the paths of atmospheric CO$_2$ content which are based on constant emission scenarios combined with a linear sink model. With the exception of the most ``pessimistic'' variant, the temperature is predicted to remain below the extraordinarily high value measured in 2024.

preprint2026arXivOpen access
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