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Maurice Newman knows more about climate models than the BOM’s Dr Rob Vertessy

In the topsy turvy world of modern science, big-government has strangled science to the point where bright outsiders know more than the fully trained “experts”.

Maurice Newman, the chairman of the P.M’s business advisory council, daringly wrote in The Australian:

“It’s a well-kept secret, but 95 per cent of the climate models we are told prove the link between human CO2 emissions and catastrophic global warming have been found, after nearly two decades of temperature stasis, to be in error.”

In Senate estimates, a Greens spokesperson asked Dr Rob Vertessy, Director of the Australian Bureau of Meteorology (BoM) on his view of this. “That is incorrect,” he said, showing how little he knows about climate models, where everyone (even the IPCC) is trying to figure out excuses for their failures. Some even invent time-travelling climate models that can finally “predict” today’s climate correctly a decade after it happened.

If Maurice Newman was wrong, he was far too generous to the climate modelers. Instead of a 95% failure rate, it’s well up over 98%. Hans von Storch et al published a paper nearly two years ago comparing models and observations of a 15 year long pause. Statistically von Storch could find no justification for people saying the models matched the observations — there was a less than 2% chance of that. Last year Ross McKitrick estimated the pause was really 19 years long, so the odds are now less than 0.5%.  Newman was being kind, suggesting that 5% of models might be called “right”.

Some will try to weasel out of it, saying the pause isn’t a pause because the missing heat went into the oceans. Aside from the fact that we can’t possibly measure the ocean heat accurately enough to know, there is the problem that the models are supposed to model the ocean too. They are called “global coupled ocean-atmosphere general circulation models”. Those models predicted the heat would be in the atmosphere, not the ocean, and it isn’t. Does that kind of failure matter? Only if you live on land.

The models not only fail on global decadal scales, but on regional, local, short term, [1] [2], polar[3], and upper tropospheric scales[4] [5] too. They fail on humidity[6], rainfall[7], drought [8] and they fail on clouds [9]. The hot spot is missing, the major feedbacks are not amplifying the effect of CO2 as assumed.

The IPCC’s favourite models were 100% wrong in 1990. The IPCC prediction in 1990, the oldest prediction they cannot weasel out of, was a best estimate of 0.3°C per decade with a  range of 0.2°C – 0.5°C. Even with the most generous overestimate of current trends, the temperature trend has fallen below their lowest estimate, at the same time as CO2 emissions were higher than expected. Prof Matthew England, and the ABC still owe Nick Minchin an apology. Rob Vertessy owes one to Maurice Newman as well now.

Dr Rob Vertessy‘s expertise is in “fluvial geomorphology and physical hydrology“. Water catchment. That doesn’t mean he can’t understand climate models, just that he needs to start reading as widely on the climate as investment bankers do.

The warmists just love a good model,
Not those on the catwalk who waddle,
But the ones that forecast,
That the warming would last,
Being wrong,were 99% twaddle.

— Ruairi


Hans von Storch, Armineh Barkhordarian, Klaus Hasselmann and Eduardo Zorita (2013)  Can climate models explain the recent stagnation in global warming? Academia

McKitrick, R. (2014) HAC-Robust Measurement of the Duration of a Trendless Subsample in a Global Climate Time Series. Open Journal of Statistics, 4, 527-535. doi: 10.4236/ojs.2014.47050. [link] to full manuscript. [Judith Curry’s discussion].


[1^] Anagnostopoulos, G. G., D. Koutsoyiannis, A. Christofides, A. Efstratiadis, and N. Mamassis, (2010). A comparison of local and aggregated climate model outputs with observed data’, Hydrological Sciences Journal, 55: 7, 1094 — 1110 [PDF]

[2^] Koutsoyiannis, D., Efstratiadis, A., Mamassis, N. & Christofides, A.(2008) On the credibility of  climate predictions. Hydrol. Sci. J. 53(4), 671–684. changes [PDF]

[3^] Previdi, M. and Polvani, L. M. (2014), Climate system response to stratospheric ozone depletion and recovery. Q.J.R. Meteorol. Soc.. doi: 10.1002/qj.233

[4^] Christy J.R., Herman, B., Pielke, Sr., R, 3, Klotzbach, P., McNide, R.T., Hnilo J.J., Spencer R.W., Chase, T. and Douglass, D: (2010) What Do Observational Datasets Say about Modeled Tropospheric Temperature Trends since 1979? Remote Sensing 2010, 2, 2148-2169; doi:10.3390/rs2092148 [PDF]

[5^] Fu, Q, Manabe, S., and Johanson, C. (2011) On the warming in the tropical upper troposphere: Models vs observations, Geophysical Research Letters, Vol. 38, L15704, doi:10.1029/2011GL048101, 2011 [PDF] [Discussion]

[6^] Paltridge, G., Arking, A., Pook, M., 2009. Trends in middle- and upper-level tropospheric humidity from NCEP reanalysis data. Theoretical and Applied Climatology, Volume 98, Numbers 3-4, pp. 351-35). [PDF]

[7^] Anagnostopoulos, G. G., D. Koutsoyiannis, A. Christofides, A. Efstratiadis, and N. Mamassis, (2010). A comparison of local and aggregated climate model outputs with observed data’, Hydrological Sciences Journal, 55: 7, 1094 — 1110 [PDF]

[8^] Sheffield, Wood & Roderick (2012) Little change in global drought over the past 60 years, Letter Nature, vol 491, 437

[9^] Miller, M., Ghate, V., Zahn, R., (2012) The Radiation Budget of the West African Sahel 1 and its Controls: A Perspective from 2 Observations and Global Climate Models. in press Journal of Climate [abstract] [PDF]

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