"But, we were led to believe there would be no math."

Posted On: Monday - November 19th 2018 7:16PM MST
In Topics: 
  Global Climate Stupidity

- Global Climate Disruption Science team leader

Been craving for that long-awaited next post on Global Climate Stupidity? Well, fret not, dear reader as the long drought is over, or so our mathematical model has told us. It's possible that there'll now be 40 days and nights of heavy rainfall, but then, our modeling is a work in progress (would that the scientists would be this honest about it, right?)

A Zerohedge article from last week, Climate Scientists Admit To Major Math Error After Global Warming Study Debunked, relates how some of this Global Climate DisruptionTM research has been going down. It's not like this article is an expose of this whole global crapshow, as ZH does tend toward the side of extra hype. However, this article is a very good example to illustrate the trouble any scientific/engineering type should have with anyone's claim to a working mathematical model of the entire world climate.

Peak Stupidity has expounded on the difficulty of mathematical modeling of complex processes near our blog-birth, so please read Part 1, Part 2, Part 3, Part 4, and Part 5, with Summaries - Part 1 and Part 2. Let's look at this example, though.
The co-author of a widely-cited global warming study has owned up to a major math error uncovered six days after its Oct. 31 publication by an independent scientist.

The study used a new method of measuring the ocean's absorption of heat
[SIC - "energy"], and concluded - through incorrect math - that 60% more heat [Dammit! SIC - "energy"] had been absorbed than previously thought.
Hey, this, the energy absorption by the oceans, is just one process, one little part of their whole model, but math modeling of nature is one of those things that require EVERY PART to be right. Even then, it doesn't usually work without a whole lot more effort.
Shortly after the article was published, however, independent UK-based researcher Nicholas Lewis published a comprehensive blog post, claiming he had found a "major problem" with the research.
“So far as I can see, their method vastly underestimates the uncertainty,” Lewis said in an interview Tuesday, “as well as biasing up significantly, nearly 30 percent, the central estimate.”

Lewis added that he tends “to read a large number of papers, and, having a mathematics as well as a physics background, I tend to look at them quite carefully, and see if they make sense. And where they don’t make sense — with this one, it’s fairly obvious it didn’t make sense — I look into them more deeply.”

Lewis has argued in past studies and commentaries that climate scientists are predicting too much warming because of their reliance on computer simulations, and that current data from the planet itself suggests global warming will be less severe than feared. -Washington Post
[not my Bold - either ZH or Wash. Post]
Note that this was an independent British blogger, not really a "peer", per academia, of the original researches whose paper was already published.
When we were confronted with his insight it became immediately clear there was an issue there," said Ralph Keeling, a scientist with the Scripps Institute of Oceanography who co-authored the paper with Princeton University scientist and lead author, Laure Resplandy. "We’re grateful to have it be pointed out quickly so that we could correct it quickly."
Keeling said they have since redone the calculations, finding the ocean is still likely warmer than the estimate used by the IPCC. However, that increase in heat has a larger range of probability than initially thought — between 10 percent and 70 percent, as other studies have already found.

“Our error margins are too big now to really weigh in on the precise amount of warming that’s going on in the ocean,” Keeling said. “We really muffed the error margins.” -San Diego Union-Tribune
[again, not my bolding]
Error margins from the calculations of effects of individual processes in a complicated model will accumulate to make the output complete garbage. Listen, it's not like this blogger here can do better right now (though, it's not my field, of course). However, I don't claim to have a serious model of the Earth's climate either! Part of the problem, as I wrote in Part 2 of the "Politics of GCDTM", is in with the reporters, not necessarily the scientists. Do you think any of these "journalists" can read the whole original paper, or really understand what the blogger's correction was about? We'd be really lucky if one of them can properly read the last few paragraphs, the Conclusion of the paper. I'll write more on that at the end of this post, speaking of Conclusions. OK, here comes the weaseling out of the original author:
Note from co-author Ralph Keeling Nov. 9, 2018: I am working with my co-authors to address two problems that came to our attention since publication. These problems, related to incorrectly treating systematic errors in the O2 measurements and the use of a constant land O2:C exchange ratio of 1.1, do not invalidate the study’s methodology or the new insights into ocean biogeochemistry on which it is based. We expect the combined effect of these two corrections to have a small impact on our calculations of overall heat uptake, but with larger margins of error. We are redoing the calculations and preparing author corrections for submission to Nature. -Scripps.ucsd.edu [MY bolding, this time]
OK, I get it. You have new methods that may help model parts of the climate better. This was just a math mistake. You've got new insights learned from the results WITH the math error ... whoaaa... hold on, partner! You're losing me. Oh, and you still have the number right, but with a much larger margin of error, meaning ... well, you don't that number very well. Yet, energy uptake by the ocean is as important a part of the model as any, is it not. It ain't like the world is covered with only 2/3 ocean, it's like 3/4!

If these scientists would put the word out clearly that all this is a work in progress, I'd have no problem with their work. "We're working on a model. There's a lot more work to be done." "We don't know every process in the energy balance, or at least don't know enough to model all of them, cough, ice ages, cough cough ..." Fine. However, this is not what the public gets to hear, which brings me to the promised conclusion.

Here's my point regarding journalism's role in this scam: At the beginning of the ZH article (of which I've pretty much included the whole thing!) on the ORIGINAL REPORT - The report was covered or referenced by MSM outlets worldwide, including the Washington Post, New York Times, BBC, Reuters and others. Now, as far as the correction goes - The scientists have submitted a correction to the journal Nature, which published the study. It'll be a note in Nature. Hey, I know, that's how science is done. This is how journalism is done though: That note WILL NOT BE COVERED by these MSM outlets worldwide. They don't want corrections, they want fear-spreading red-colored graphs and numbers, scary HOT, HOT, HOT temperatures, hurricanes, lack of snow, and dogs and cats living together! Corrections in Nature don't cut it at all.

PS: About the graphic at the top. No, this does not relate directly to the math mistake discussed here. It's flashy, is one thing, but it reminds me, and possibly will the reader, about the problems with lots of this Global Climate DisruptionTM data. This post was about margins of error in the data. You've probably seen those tall error bars that appear in lots of the observational (not from models) data graphs of temperature. Those error bars are usually pretty large compared to the trend in the data itself. I give kudos to scientists for being honest about this (part of why I don't think the scientists are purposefully misleading most of the time). However, when your tolerances are that big compared to the data itself, you really don't have good results. I'm fine with that - the next thing to do would be to try to narrow the error bars. That's the hard part, for observational data, but more-so, for values obtained from these touted mathematical models.

[Updated 11/20:]
Added discussion of the top graphic and error bars.

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