Problem 4. Why has a community of thousands or tens of thousands of climate scientists not managed to improve certainty in core areas in any significant way in more than a decade (eg the climate sensitivity caused by CO2 doubling as evidenced by little change in the IPCC bounds)?

This problem has been the hardest, probably because it takes enormous hubris to claim solution to a problem that defeats thousands of usually intelligent people. One man who does that is — Dr Roy Spencer — claiming a huge ‘blunder’ pervades the whole of climate science regarding the direction and magnitude of ocean-cloud feedback, the subject of his upcoming book and paper.

What I want to demonstrate is one of the issues that is almost totally forgotten in the global warming debate: long-term climate changes can be caused by short-term random cloud variations.

The main reason this counter-intuitive mechanism is possible is that the large heat capacity of the ocean retains a memory of past temperature change, and so it experiences a “random-walk” like behavior. It is not a true random walk because the temperature excursions from the average climate state are somewhat constrained by the temperature-dependent emission of infrared radiation to space.

As showed previously, an AR coefficient of 0.99 is sufficient to change a random walk behavior (AR=1) to the kind of mean-reverting behavior his model shows. This difference is virtually undetectable using the usual tests on the available 150 years of global temperature data. Global temperature cannot be a random walk, but it can be ‘almost a random walk’. It can also respond to random shocks, such as volcanic eruptions, and sudden injections of GHGs, and oscillating solar forcings while still retaining the random walk character.

In his latest post he shows how his model of the climate system produces almost random walk behaviour; the kind of behaviour we have dealt with in the last four parts of this series. He shows that millennial climate cycles CAN be driven by random cloud variations, showing the integrative statistical structure found in the real global temperature data.

The answer to the Problem 4 is, of course, that millennial climate cycles HAVE been driven by random cloud variations, which is not the same thing. To show that, it seems to me we don’t need to exclude CO2 as a substantial forcing factor in recent climate changes. It could be excluded by the dogma of Occam’s razor. It could also be excluded if the effect of injections of GHGs were shown to be fugitive, or if the effect was shown to be relatively minor and limited to the direct radiative effects, which is probably the most likely situation.

If an essentially stochastic trend is FALSELY attributed to a deterministic cause, then one would expect no progress in narrowing the confidence limits. A physical uncertainty is then lodged in an epistemic uncertainty, until the offending false assumption is removed.

The resulting system is not a ‘complex climate system’ but an essentially simple, additive system, the only problem remaining being the estimation of the magnitude of the various forcing effects. It is a SIMPLE system from a mathematical POV, as it is decomposable into independent causes, the only complication being the integrated, under-constrained observable effect.

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