Where Did the IPCC Get its Numbers From?

I was recently reminded of an issue I discovered several months ago. It seems worth revisiting. The Summary for Policymakers of the latest IPCC report (Working Group II) says:

Global economic impacts from climate change are difficult to estimate. Economic impact estimates completed over the past 20 years vary in their coverage of subsets of economic sectors and depend on a large number of assumptions, many of which are disputable, and many estimates do not account for catastrophic changes, tipping points, and many other factors. With these recognized limitations, the incomplete estimates of global annual economic losses for additional temperature increases of ~2°C are between 0.2 and 2.0% of income (±1 standard deviation around the mean) (medium evidence, medium agreement).

The reference given for this text is Chapter 10, Section 9. When we look at that chapter, we find the same text in its Executive Summary. Like in the SPM, it cites 10.9. However, nothing in the text of 10.9 gives those numbers. They seem to have been pulled out of thin air.

Another troubling issue is the text in Chapter 10’s Executive Summary was changed to match that in the SPM. In the “Final Draft” of Chapter 10, the text originally said:

Globally aggregated economic impacts of global warming are a small fraction of income up until 3°C [10.9.2, medium evidence, high agreement]. A global mean average temperature rise of 2.5C may lead to global aggregated economic losses between 0.2 and 2.0% of income (medium evidence, medium agreement) and losses increase with greater warming. Little is known about aggregate economics impacts above 3°C. Impact estimates are incomplete and depend on a large number of assumptions, many of which are disputable.

General differences aside, the thing which stands out is the previous version of the text said a rise of 2.5C may cause 0.2 – 2.0% economic losses. The new version says “economic losses for additional temperature increases of ~2°C are between 0.2 and 2.0%.” They’ve shifted the amount of warming necessary for these damages up by half a degree, and they’ve done so without any explanation.

A clue might be present in a previous version of the SPM. It said:

Global mean temperature increase of 2.5C above preindustrial levels may lead to global aggregate economic losses between 0.2 and 2.0%

Notice it says a rise above preindustrial levels. We could perhaps assume the 2.5C figure is in relation to preindustrial levels while the 2C figure is in relation to modern levels even though there has been a greater amount of warming than .5C. This assumption requires assuming the “Final Draft” of Chapter 10’s text was wrong to refer to a “rise of 2.5C” as ~20% of that rise had already happened.

Even with that assumption though, nothing much is explained. Even if we know exactly what value the IPCC intends, we have no explanation for where the values came from. It seems they were pulled out of thin air. However, if they were somehow based upon Section 10.9, then they would be affected by the changes I highlighted in my recent post. It’s difficult to see how they could get the exact same results for these two sets of data:


So where did the IPCC get its numbers from? Did it just make them up? Did somebody, somewhere, perform some secret calculations we’re not allowed to see?

It’s impossible to read Section 10.9 and think the numbers came from it. Does that mean the IPCC lied about where it got those numbers from?

Knowingly Promoting False Conclusions(?)

Richard Tol has a blog post responding to an article in the Guardian discussing one of the undisclosed changes to IPCC report I mentioned in my last post. There are a variety of things worth commenting on in it, but one stands out to me more than the rest. The Guardian article focused on the fact this sentence had been removed from the IPCC report:

Climate change may be beneficial for moderate climate change but turn negative for greater warming.

Tol’s post explains:

Here is the story. The old data (the blue circles) roughly fit a parabola: first up, then down, and ever faster down.

The new data do not fit a parabola: The initial impacts are positive, but the progression to negative impacts is linear rather than quadratic.

If you fit a parabola to this data, you will find that the mildly negative estimate at 5.5K dominates the positive estimate at 1.0K and the sharply negative estimate at 3.2K. The parabola become essentially a straight line through the origin and the right-most observation.

I think the appropriate conclusion from this is to fit a bi-linear relationship to the data, rather than stick with a parabolic one. This was not yet in the peer-reviewed literature when the window for AR5 closed, so we decided to just show the data.

To better understand what Tol is saying, we can look at the old and new curves he refers to. Here’s the image he tweeted of them:

As we can see, the old curve says some amounts of global warming will have (net) benefits. The new curve says no amount of global warming will have (net) benefits. That’s a significant change.

Tol’s post explains that change is not due to the multitude of data errors in his earlier work as claimed by some. We can verify that by looking at the effect of the corrections:


The corrections clearly are not the cause of the change in his conclusions. That means, as he says, the change is due entirely to the newer, more up-to-date, data. That would be the data he showed as diamonds in this figure he added to the IPCC report:


But think about that. The figure he added has the new data, meaning the curve for it would show no benefits. Tol says that means a different regression should be used to generate the curve, but that hadn’t been done at the time. The only regression which had been published would show no benefits. Given that, why would Tol try to make the IPCC say:

Climate change may be beneficial for moderate climate change but turn negative for greater warming.

When he knew there was no published work to support that conclusion for the data he was showing? Doesn’t that mean he knowingly added a conclusion to the IPCC report which couldn’t be supported by any published literature? And doesn’t that mean the IPCC lets authors add conclusions to its report not supported by the data shown in the report, much less any published literature?

Or am I missing something?

Side note, Tol’s claim to have fit a parabola to the data is false. He actually used a linear + parabolic fit. That’s why the new curve was so linear – he used a model with a linear component.

Undisclosed Changes in the IPCC AR5 Report

I’ve previously documented changes in the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) which were made absent any external review. This happened despite the IPCC principles stating:

Three principles governing the review should be borne in mind. First, the best possible scientific and technical advice should be included so that the IPCC Reports represent the latest scientific, technical and socio-economic findings and are as comprehensive as possible. Secondly, a wide circulation process, ensuring representation of independent experts (i.e. experts not involved in the preparation of that particular chapter) from developing and developed countries and countries with economies in transition should aim to involve as many experts as possible in the IPCC process. Thirdly, the review process should be objective, open and transparent.

Working Group/TFI Co-chairs should arrange a comprehensive review of reports in each review phase, seeking to ensure complete coverage of all content.

It is difficult to see how a review process can be “open and transparent” if significant changes are made absent any review. It is difficult to see how a review process can “ensure complete coverage of all content” when entire sections are (re)written absent any review.

I’m not going to dwell on that today though. The changes I discussed before were between various drafts of the IPCC report. Today, I’m going to discuss changes made between the “Final Draft” and “final version” of the IPCC WGII report. The Final Draft was released to the public on March 31st with this word of caution:

The Final Draft Report has to be read in conjunction with the document entitled “Climate Change 2014: Impacts, Adaptation, and Vulnerability. Working Group II Contribution to the IPCC 5th Assessment Report — Changes to the Underlying Scientific/Technical Assessment” to ensure consistency with the approved Summary for Policymakers (IPCC-XXXVIII/DOC.3) presented to the Panel at its 38th Session. This document lists the changes necessary to ensure consistency between the full Report and the Summary for Policymakers, which was approved line-by-line by Working Group II and accepted by the Panel at the above-mentioned Sessions. A listing of substantive edits additionally indicates corrections of errors for the Final Draft Report.

But has been widely treated as being the “IPCC Report.” The actual final version was only published two days ago, on October 15th. It has changes as indicated would be made in that disclaimer. The list of “substantive edits” is available here. An errata listing several minor changes is available here. A list of changes necessary for consistency with the Summary for Policymakers (SPM) is available here. That these documents are made publicly available suggests a genuine interest in transparency. That suggestions is completely undermined, however, by the multitude of changes the documents don’t mention.

Denying the Obvious

Sometimes people deny something that seems so obvious I don’t know how to respond. Today on Twitter, several people have been discussing issues related to paleoclimate reconstructions. The details aren’t important for this post. What is important is one participant, Jim Bouldin, claimed people have falsely accused others of cherry-picking. He specifically mentioned Steve McIntyre, so I tried to elicit more information, asking:

The second tweet pointed out one person even used the phrase cherry-picking to describe what they had done, including a link to this post to support that claim:

I don’t have the exact words here. (I’ll edit it if I get better notes.) But, for certain, D’Arrigo put up a slide about “cherry picking” and then she explained to the panel that that’s what you have to do if you want to make cherry pie.


56% of Americans are in the Top 10%

Today I saw a tweet about income inequality in the United States. I responded with a factoid I came across a few weeks ago:

I thought it was interesting. We’re told it’s bad half of all American income goes to the “top 10%.” However, the roster which makes up the “top 10%” is different each year. If you look at everybody in it, not just the people for one year, you find the “top 10%” actually includes 56% of Americans.

More Ballin’

I took a peek over at blogger Anders’s place, and I found another great example of how to be a Climateballer. Now, I was banned from that site some time back, so I can’t comment on this there. Or at least, that’s what I thought. For my own gratification I tried submitting a comment there. I expected it to vanish without a trace like they usually do. It didn’t. It went through. It didn’t even land in moderation.

I don’t know if it will be allowed to stay, but since it showed up, I’m just going to post a screenshot of it. Read it, and you can learn more about how to be a Climateballer:


Kudos to miker613 for his attempts there. I hope he’s seen this link in my last post. It’s by Steve McIntyre, and it specifically lays out the point the people at Anders’s blog aren’t seeing:

First, there is no mention in MBH98 or the MBH98 SI that Preisendorfer’s Rule N was used to determine the number of retained PC series for tree ring networks. The only pertinent reference in MBH98 was as follows:

“Certain densely sampled regional dendroclimatic data sets have been represented in the network by a smaller number of leading principal components (typically 3–11 depending on the spatial extent and size of the data set). This form of representation ensures a reasonably homogeneous spatial sampling in the multiproxy network (112 indicators back to 1820). [our bolds]“

This statement contains no reference to the use of Preisendorfer’s Rule N.

In connection with the calculation of temperature principal component series, a different calculation, MBH98 does refer to the use of Preisendorfer’s Rule N as follows:

“a conventional Principal Component Analysis (PCA) is performed… An objective criterion was used to determine the particular set of eigenvectors which should be used in the calibration as follows. Preisendorfer’s selection rule ‘rule N’ was applied to the multiproxy network to determine the approximate number Neofs of significant independent climate patterns that are resolved by the network, taking into account the spatial correlation within the multiproxy data set.”

They say its hard to see the forest for the trees. I feel like there’s a joke in there about not being able to see the trees for the instrumental temperature record.