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Statistical assessments of anthropogenic and natural global climate forcing. An update

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Abstract:

In actualization of earlier papers we present a statistical analysis of anthropogenic and natural variance or signals, respectively, which can be detected in the observed global mean surface air temperature series 1860–2008 using multiple linear regression (MLR) and non-linear neural networks (NN). The forcing factors considered are greenhouse gases (GHG), tropospheric sulphate aerosols (SUL), solar activity, volcanism and ENSO (El Niño /southern oscillation). Thereby, a maximum total of explained variance of 88 % is reached by NN compared to 80 % by MLR. The related anthropogenic NN signals are 0.9–1.5 K warming due to GHG, 0.2–0.5 K cooling due to SUL and a combined (GHG+SUL) anthropogenic effect of 0.7–0.9 K warming. The natural signals have a magnitude of roughly 0.2 K. Moving MLR analysis shows that within recent decades the solar signal systematically decreased whereas the GHG signal increased to become a dominant factor of climate variability. Some test procedures address the confidence of the results and the sensitivity of the signals.

German
In Aktualisierung früherer Publikationen berichten wir über die Ergebnisse einer statistischen Analyse anthropogener und natürlicher Varianz bzw. Signale, wie sie mittels multipler linearer Regression (MLR) und nicht linearen neuronalen Netzwerken (NN) in den Daten der global gemittelten bodennahen Lufttemperatur 1860–2008 entdeckbar sind. Als Antriebe betrachten wir Treibhausgase (GHG), troposphärische Sulfatpartikel (SUL), Sonnenaktivität, Vulkanismus und ENSO (El Niño / südliche Oszillation). Dabei erreicht NN eine maximale totale erklärte Varianz von 88 % verglichen mit 80 % bei MLR. Die betreffenden anthropogenen NN-Signale zeigen 0,9–1,5 K Erwärmung durch GHG, 0,2–0,5 K Abkühlung durch SUL und einen kombinierten anthropogenen Effekt von 0,7-0,9 K Erwärmung. Die natürlichen Signale liegen in einer Größenordnung von 0,2 K. Eine zeitlich gleitende MLR-Analyse zeigt, dass in den letzten Dekaden das solare Signal systematisch abgenommen hat während das GHG-Signal zu einem dominanten Faktor der Klimavariabilität geworden ist. Einige Testverfahren dienen der Beurteilung der Konfidenz der Ergebnisse und der Sensitivität der Signale.

Document Type: Research Article

DOI: https://doi.org/10.1127/0941-2948/2010/0421

Publication date: 2010-02-01

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  • Meteorologische Zeitschrift (originally founded in 1866) is the joint periodical of the meteorological societies of Austria, Germany and Switzerland. It accepts high-quality peer-reviewed manuscripts on all aspects of observational, theoretical and computational research out of the entire field of meteorology, including climatology. Meteorologische Zeitschrift represents a natural forum for the meteorological community of Central Europe and worldwide.
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