Summary
The problem of global climate change forced by anthropogenic emissions of greenhouse gases (GHG) and sulfur components (SU) has to be addressed by different methods, including the consideration of concurrent forcing mechanisms and the analysis of observations. This is due to the shortcoming and uncertainties of all methods, even in case of the most sophisticated ones. In respect to the global mean surface air temperature, we compare the results from multiple observational statistical models such as multiple regression (MRM) and neural networks (NNM) with those of energy balance (EBM) and general circulation models (GCM) where, in the latter case, we refer to the recent IPCC Report. Our statistical assessments, based on the 1866–1994 period, lead to a GHG signal of 0.8–1.3 K and a combined GHG-SU signal of 0.5–0.8 K detectable in observations. This is close to GCM simulations and clearly larger than the volcanic, solar and ENSO (El Niño/southern oscillation) signals also considered.
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References
Allan, R. J., Nicholls, N., Jones, P. D., Butterworth, I. J., 1991: A further extension of the Tahiti-Darwin SOI, Early ENSO and Darwin Pressure.J. Climate 4, 743–749.
Bayer, D., Denhard, M., Meyhöfer, S., Rapp, J., Schönwiese, C.-D., 1994: Trend- und multiple Signalanalyse globaler bzw. europäischer Klimavariationen. Frankfurt/M.: Bericht Nr. 98, Inst. Meteorol. Geophys. Univ., 172 pp.
Cubasch, U., Hasselmann, K., Höck, M., Maier-Raimer, E., Miklolajewicz, U., Santer, B. D., Sausen, R., 1992: Timedependant greenhouse warming computations with a coupled ocean-atmosphere model.Climate Dyn. 8, 55–69.
Cubasch, U., Hegerl, G. C., Hellbach, A., Höck, H., Mikolajewicz, U., Santer, B. D., Voss, R., 1995: A climate change simulation starting from 1935.Climate Dyn. 11, 71–84.
Denhard, M., Walter, A., Schönwiese, C.-D., 1996: Simulationen globaler Klimavänderungen mit Hilfe neuronaler Netze.Naturw. Rdsch., (in press).
Foukal, P. V., Lean, J., 1980: An empirical model of total solar irradiance variation between 1874 and 1988.Science 247, 556–558.
Grieser, J., Schönwiese, C.-D., 1995: Ein konzeptionelles Modell zum Studium verschiedener externer Einflüsse.Ann. Meteorol. 31, 78–79.
Hasselmann, K., Sausen, R., Maier-Reimer, E., Voss, R., 1993: On the cold start problem in transient simulations with coupled atmosphere-ocean models.Climate Dyn. 9, 53–61.
Hasselmann, K., Bengtsson, L., Cubasch, U., Hegerl, G. C., Rohde, H., Roeckner, E., von Storch, H., Voss, R., Waszkewitz, J., 1995: Detection of anthropogenic climate change using a fingerprint method. Hamburg: Max-Planck-Inst. f. Meteorologie, Report No. 168, 20S.
IPCC see Houghton et al.
Houghton, J. T., Jenkins, G. J., Ephraums, J. J., (eds.) 1990:Climate Change. The IPCC Scientific Assessment. Cambridge: University Press, 365 pp.
Houghton, J. T., Callander, B. A., Varney, S. K., (eds.) 1992:Climate Change 1992. The Supplementary Report to the IPCC Scientific Assessment. Cambridge: Univ. Press, 200 pp.; 1996: Second Assessment Report, in print.
Jones, P. D., 1988: Hemispheric surface temperature variations: recent trends and an update to 1987.J. Climate 1, 654–660; 1992–1995 priv. comm.
Keeling, C. D., Bacastow, R. B., Bainbridge, A. E., Ekdall, C. A., Guenther, P. R., Waterman, L. S., Chin, J. F. S., 1976: Atmospheric carbon dioxide variations at Manu Loa Observatory, Hawaii.Tellus 28, 538–551; 1985–1992: priv. comm.
Mitchell, J. F. B., Johns, T. C., Gregory, J. M., Tett, S. F. B., 1995: Climate response to increasing levels of greenhouse gases and sulphate aerosols.Nature 376, 501–504.
Ropelewski, C. F., Jones, P. D., 1987: An extension of the Tahiti-Darwin Southern oscillation index.Mon. Wea. Rev. 110, 800–807.
Rumelhart, D. E., Hinton, G. E., Williams, R. J., 1986: Learning representations by backpropagating errors.Nature 323, 533–536.
Schönwiese, C.-D., 1986: The CO2 climate response problem. A statistical approach.Theor. Appl. Climatol. 37, 1–14.
Schönwiese, C.-D., 1994: Analysis and prediction of global climate temperature change based on multiforced observational statistics.Environ. Poll. 83, 149–154.
Schönwiese, C.-D., Bayer, D., 1995: Some statistical aspects of the anthropogenic and natural forced global temperature change.Atmósfera 8, 3–22.
Schönwiese, C.-D., Ullrich, R., Beck, F., Rapp, J., 1994: Solar signals in global climatic change.Climatic Change 27, 259–281.
Siebert, B., 1995:Statistische Analyse von vulkanisch-klimatologischen Zusammenhängen. Frankfurt/M.: Diplomarbeit, Inst. Meteorol. Geophys., 119 S.
Simkin, T., Siebert, L., Mc Clelland, L., Bridge, D., Newhall, C., Latter, J. M., 1981:Volcanoes of the world. (Smithsonian Institution), Strondsburg (USA): Hutchinson, 233 pp.; 1984–1993: updates.
Smith, M., 1993:Neural Networks for Statistical Modeling. New York: Van Nostrand Reinhold, 235 pp.
Walter, A., 1996: Die Anwendungsmöglichkeiten selbstorganisierender neuronaler Netze in der Klimatologie am Beispiel globaler und hemisphärischer Temperaturzeitreihen. Frankfurt/M.: Diplomarbeit, Inst. Meteorol. Geophys., 96 S.
Wigley, T. M. L., Schlesinger, M. E., 1985: Analytic solution for the effect of increasing CO2 on global mean temperature.Nature 315, 649–652.
Wigley, T. M. L., Holt, T., Raper, S. C. B., 1991: Sea level and temperature change under the greenhouse effect (an interactive greenhouse model). User's Manual. Norwich, Climatic Research Unit, Univ. of East Anglia, pp.
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Schönwiese, C.D., Denhard, M., Grieser, J. et al. Assessments of the global anthropogenic greenhouse and sulfate signal using different types of simplified climate models. Theor Appl Climatol 57, 119–124 (1997). https://doi.org/10.1007/BF00867983
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DOI: https://doi.org/10.1007/BF00867983