Koutsoyiannis, D., A. Efstratiadis, N. Mamassis, and A. Christofides,
2008:, Hydrological Sciences Journal, 53 (4), 671-684.
Abstract: "Geographically distributed predictions of future climate,
obtained through climate models, are widely used in hydrology and many
other disciplines, typically without assessing their reliability. Here
we compare the output of various models to temperature and precipitation
observations from eight stations with long (over 100 years) records from
around the globe. The results show that models perform poorly, even at a
climatic (30-year) scale. Thus local model projections cannot be
credible, whereas a common argument that models can perform better at
larger spatial scales is unsupported."
Conclusion: "At the annual and the climatic (30-year) scales, GCM
interpolated series are irrelevant to reality. GCMs do not reproduce
natural over-year fluctuations and, generally, underestimate the
variance and the Hurst coefficient of the observed series. Even worse,
when the GCM time series imply a Hurst coefficient greater than 0.5,
this results from a monotonic trend, whereas in historical data the high
values of the Hurst coefficient are a result of large-scale over-year
fluctuations (i.e. successions of upward and downward 'trends'. The huge
negative values of coefficients of efficiency show that model
predictions are much poorer than an elementary prediction based on the
time average. This makes future climate projections at the examined
locations not credible. Whether or not this conclusion extends to other
locations requires expansion of the study, which we have planned.
However, the poor GCM performance in all eight locations examined in
this study allows little hope, if any. An argument that the poor
performance applies merely to the point basis of our comparison, whereas
aggregation at large spatial scales would show that GCM outputs are
credible, is an unproved conjecture and, in our opinion, a false one."