Assessment of the reliability of climate predictions based on comparisons with historical time series by Koutsoyiannis et al. explore: “How well do the models capture the scaling behaviour of the real climate, by assessing standard deviation at different scales.” By their results they specifically throw down the gauntlet of “falsifiability” challenging IPCC to its very foundations. (Is it “scientific” or poltical.) Thought provoking on the role of science and verifiability in the public sphere. (Emphasis added) ———————
Abstract
As falsifiability is an essential element of science (Karl Popper), many have disputed the scientific basis of climatic predictions on the grounds that they are not falsifiable or verifiable at present. This critique arises from the argument that we need to wait several decades before we may know how reliable the predictions will be. However, elements of falsifiability already exist, given that many of the climatic model outputs contain time series for past periods. In particular, the models of the IPCC Third Assessment Report have projected future climate starting from 1990; thus, there is an 18?year period for which comparison of model outputs and reality is possible. In practice, the climatic model outputs are downscaled to finer spatial scales, and conclusions are drawn for the evolution of regional climates and hydrological regimes; thus, it is essential to make such comparisons on regional scales and point basis rather than on global or hemispheric scales. In this study, we have retrieved temperature and precipitation records, at least 100?year long, from a number of stations worldwide. We have also retrieved a number of climatic model outputs, extracted the time series for the grid points closest to each examined station, and produced a time series for the station location based on best linear estimation. Finally, to assess the reliability of model predictions, we have compared the historical with the model time series using several statistical indicators including long?term variability, from monthly to overyear (climatic) time scales. . . .
20. Conclusions
All examined long records demonstrate large overyear variability (long?term fluctuations) with no systematic signatures across the different locations/climates.
• GCMs generally reproduce the broad climatic behaviours at different geographical locations and the sequence of wet/dry or warm/cold periods on a mean monthly scale.
• However, model outputs at annual and climatic (30?year) scales are irrelevant with reality; also, they do not reproduce the natural overyear fluctuation and, generally,
underestimate the variance and the Hurst coefficient of the observed series; none of the models proves to be systematically better than the others.
• The huge negative values of coefficients of efficiency at those scales show that model predictions are much poorer that an elementary prediction based on the time average.
• This makes future climate projections not credible.
• The GCM outputs of AR4, as compared to those of TAR, are a regression in terms of the elements of falsifiability they provide, because most of the AR4 scenarios refer only
to the future, whereas TAR scenarios also included historical periods.
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European Geosciences Union General Assembly 2008
Vienna, Austria, 13?18 April 2008
Session IS23: Climatic and hydrological perspectives on long?term changes
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See also discussion at: ClimateAudit