Independent Researcher, Exeter NSW 2579, Australia.
Review Article
World Journal of Advanced Research and Reviews, 2024, 22(01), 1313-1318
Received on 09 March 2024; revised on 19 April 2024; accepted on 22 April 2024
This study draws on Chaos Theory to investigate the ability of a General Circulation Model to predict climate. The conclusion is that a General Circulation Model's grid-level physical processes and parameterisations cannot predict climate beyond maybe a few weeks. If a General Circulation Model is to be used at all, longer term climate features can be analysed externally and fed into the model but they cannot be represented by the model any better than by the external analysis. The external analysis, which is likely to be simpler, has the added advantage that the assumptions that are used, and the uncertainties in the results, are much more likely to be explicitly identified, quantified, and understood. Consequently it would be clear which aspects of the climate are being predicted, and how reliable those predictions are. The longer the timescale is, the less relevant the grid-level physical processes and parameterisations in a General Circulation Model become. Although a General Circulation Model can be made to represent climate over a longer time scale, its grid-level physical processes and parameterisations cannot predict the climate. A General Circulation Model calculates weather at each time step and this is then amalgamated into a final prediction of climate. This process is back to front. A realistic long term climate model would calculate climate and then weather would be deduced from the climate.
Climate Model; General Circulation Model; GCM; Chaos Theory; Prediction horizon; Projection; Stadium-wave network; Weather
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Michael Jonas. General circulation models cannot predict climate. World Journal of Advanced Research and Reviews, 2024, 22(1), 1313-1318. Article DOI: https://doi.org/10.30574/wjarr.2024.22.1.1235