Planet Gore

More Model Mania

Paul Krugman has a strange, very angry and even borderline incoherent piece today, saying things like this:

“Most criticism of John McCain’s decision to follow the Bush administration’s lead and embrace offshore drilling as the answer to high gas prices has focused on the accusation that it’s junk economics — which it is.

A McCain campaign ad says that gas prices are high right now because ‘some in Washington are still saying no to drilling in America.’ That’s just plain dishonest: the U.S. government’s own Energy Information Administration says that removing restrictions on offshore drilling wouldn’t lead to any additional domestic oil production until 2017, and that even at its peak the extra production would have an ‘insignificant’ impact on oil prices.”

Oddly, Krugman then touts the wisdom of promising to adopt cap-and-trade schemes — without mentioning that these policies’ impact wouldn’t even rise to the level of “insignificant.” This should not be surprising from a guy who ceaselessly promotes Kyoto, which also wouldn’t do a thing (look at how well the ETS is working in Europe) but would impose staggering costs, according to none other than his preferred authority, EIA. Who’s being dishonest here?

 

Krugman then turns to an economist to say that climate models make it pretty clear we’re all doomed. This comes as new research pours forth destroying any pretense that climate models have the slightest predictive value or policy relevance.

For example, don’t miss this important paper, published just as Krugman was putting his screed to bed, by Koutsoyiannis et al in the Hydrological Sciences Journal on the credibility of climate predictions. It demonstrates climate models’ lack of any predictive value, particularly at the level at which the National Assessment document I discussed yesterday purports to project future climate. Eighteen years of climate model predictions for temperature and precipitation at eight locations worldwide were evaluated.
The Abstract states:

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.

An extract from the conclusions tells the damning tale rather neatly:

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.” (emphasis added)

As climate scientist Roger Pielke Sr. notes, “A fundamental and societally relevant conclusion from this study is that the use of the IPCC model predictions as a basis for policy making is invalid and seriously misleading.”

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