The Bob

Bob Tisdale is rapidly becoming, for me, what Donald Trump is for John Stewart.


No matter how wrong he gets it, he won’t back down — he’ll double down. He even posted again, to say essentially the same thing he’s said so often: that the reason he accused Tom Karl at NOAA of malfeasance, saying he “mixed and matched methods until they found the results you wanted,” is that NMAT shows a different trend from ERSSTv4 since 1998. But maybe reader “Sou” said it best:


Bob has it all wrong in his now umpteenth post about this. HadNMAT2 is used to correct a bias in ship sea surface temps only. For the period he’s looking at (in fact since the early 1980s), they only comprise 10% of the observations. The rest of the data is from buoys, and HadNMAT doesn’t apply to them. They are much more accurate than ship data anyway. So much so that if ship and buoy data are together, the buoy data is given six times the weighting of ship data. So the comparison Bob thinks he’s making is completely and utterly wrong. And not just because the trends is actually quite close. He is not comparing what he thinks he is comparing.

I got sick and tired of Bob’s articles about this. He keeps insisting on making the same huge error over and over and over again. He’s repeating himself twice a day now, with yet another article hot on the heels of one just a few hours earlier. After reading lots of papers on the subject – if Tamino doesn’t mind, I wrote about it:

http://blog.hotwhopper.com/2015/07/biased-bob-tisdale-is-all-at-sea.html

I’ve also done the unthinkable (only if you’re a WUWT denier) and checked it out with one of your colleagues and co-authors of Huang15, one of the main ERSSTv4 papers.

I’d rather discuss something interesting.

Here’s the data that has The Donald The Bob in a tizzy, where I’ve computed the difference between NMAT and ERSSTv4:

fig1

I’ve circled the earliest part, from 1998, where NMAT is higher than ERSSTv4. It’s one of the main reasons that The Bob found a lower trend for NMAT than for ERSSTv4 since 1998. The difference since 1998 shows an estimated trend of -0.0044 deg.C/yr, the same value The Bob found for the difference in their individual trend rates.

What The Bob didn’t bother to do is wonder, why might that be? Just because there are differences between NMAT and sea surface temperature, that doesn’t mean the people estimating SST have rigged the game; why, there might even be an actual, physical reason for it.

What’s so special about 1998? The Bob wants us to believe it’s because of that non-existent “hiatus”. But let’s not forget that 1998 was the year of the big el Niño. Which made me wonder, might that have affected the difference between NMAT and sea surface temperature? What about aerosols from volcanic eruptions? What about changes in solar radiation?

To investigate, I took the difference between NMAT and ERSSTv4, and sought to discover how it might be related to el Niño, aerosols, and solar output. As I’ve done before, I used the multivariate el Niño index to quantify el Niño, aerosol optical depth for volcanic aerosols, and sunspot numbers as a proxy for solar output. I allowed for lagged response to each of those variables. I also allowed for an annual cycle, to account for possible annually cyclic differences between the two variables under consideration.

The available data extend from 1950 through 2010, but I started the regression in 1952 to ensure there was sufficient “prior” data for lagged variables. It turns out that all three variables affect the NMAT-ERSSTv4 difference. Here again is the difference, this time since 1952, compared to the resulting model:

fig2

It turns out that the model explains the NMAT-ERSSTv4 differences rather well, particularly the high value in 1998 as mostly due to the el Niño of that year.

Here are the residuals from the fit:

fig3

If we study only the residuals since 1998, by golly the estimated trend is still negative. But only by -0.0018 deg.C/yr (not -0.0044), a value which is not statistically significant. So much for The Bob’s “much lower.”

Is the (statistically significant) impact of these factors really affecting NMAT-SST difference? Time will tell, but the data seem to indicate so. Right or wrong, it’s a much more plausible explanation than malfeasance by Tom Karl at NOAA, and one which is founded on science, not reprehensible behavior.

Of course the salient point is what was pointed out by Sou, that the comparison Bob thinks he’s making is completely and utterly wrong.

I expect The Bob will post about this again. I expect he’ll repeat himself again. After all, the trend in NMAT is lower than that in ERSSTv4 since 1998, which can’t possibly have anything to do with el Niño or atmospheric aerosols or solar variations because that’s the time of the non-existent “hiatus”.

While you’re at it, Bob, repeat my real name as often as you can, and be sure to ask Anthony Watts to insult me because I post under a pseudonym.

14 responses to “The Bob

  1. Ahhhhhhh, looking through the comments (where you said about posting under an pseudonym, I saw a name I knew well from back a few years ago. I would argue back and forth with him at another forum. He was was a complete fool, doing nothing but repeating things that were shown to be wrong, cherry-picking of his data, and introducing irrelevant data. But, in my search to find support to show how wrong he was, led me to your blog. So, some good came of it. Thanks Tamino, for providing that link, which allowed me to remember his foolishness.

  2. I think this bit might be unfortunately phrased: “Right or wrong, it’s a much more plausible explanation than malfeasance by Tom Karl at NOAA, and one which is founded on science, not reprehensible behavior.”

    Presumably you meant that the latter explanation was founded — to the degree it was founded on anything — on reprehensible behavior on the part of the would-be explainer and not on the behavior of anyone at NOAA?

    [Response: That’s right. Bob Tisdale’s remarks are, in my opinion, reprehensible (specifically, his accusatory comments about Tom Karl).]

  3. Tamino: Tom Karl and Boyin Huang are really interested in getting a better handle on the relation between SSTs and NMATs – I’ve done a little bit of work on it. I think you may have an important piece here – I’d suggest getting in touch with them.

    • And this is how the science in a particular field progresses: over time, the scientists converge on the good ideas, and weed out the bad ones.

    • ETA: I know this is self-evident to rational people. But in the climate change denial blogosphere, anything that isn’t perceived as being substantively correct on the first attempt is automatically labelled as ‘wrong’ or ‘fraudulent’. Actually, that applies to anything they can’t *understand*.

  4. …he accused Tom Karl at NOAA of malfeasance, saying he “mixed and matched methods until they found the results you wanted”…

    Ironic, given the way Bob Tisdale mixes and matches spuriously misapplied “statistics” and egregiously misleading (to the point of lying) statements.

    Even more ironic given that the objectivitity of the expert science is easily demonstrated by its replicability, and that folk of Tisdale’s ideological bent, such as Steve McIntyre and Ross McKitrick, have been proven to have deliberately and non-randomly selected the most extreme results to try to bolster their own cases:

    http://deepclimate.org/2010/11/16/replication-and-due-diligence-wegman-style/

    It takes a particularly extreme of lack of shame and humility to be as incompetently hypocritical as Tisdale.

  5. Horatio Algeranon

    “the buoy data is given six times the weighting of ship data. ”

    Oh buoy, subject for another Bob post.

    “Bobbing Buoys”

    Buoys will be buoys
    And Bobs will be Bobs
    And bobbing buoys
    Will tweak their nobs

    • Martin Smith

      “the buoy data is given six times the weighting of ship data. ”
      Oh buoy, subject for another Bob post.

      That raised another question for me. Isn’t that the same data that was adjusted up by 0.12C? Is it both adjusted up and given a 6x weighting?

      • I hope I’m interpreting this correctly, but I thought it was clear that buoy data are weighted *relative to contemporary ship data in the same grid box*–not all buoy data compared with earlier ship data.

  6. Thanks, Tamino.

    I removed some charts from the HW article before posting it, because it was getting a bit too long. However if anyone’s interested, the charts I took out were from a 2013 paper by Elizabeth Kent et al. Figure 15 had some charts that plotted the difference between sea and air temps (HadSST and HadNMAT2 and some other comparisons).

    http://onlinelibrary.wiley.com/doi/10.1002/jgrd.50152/pdf

    There’s no reason to expect night time air temperature would follow the same trend as the sea surface temperature exactly, though it’s fairly close. I also came across articles which discussed the diurnal variation – some places can have different trends in daytime vs night temps in sea surface temps. That is, other than the obvious where ships exhibit a maritime heat island effect during the day (which is why the night time marine air temps are used, not the day time ones).

  7. Martin Smith

    The people I argue with are “pausemaniacs,” but they are also “rawmaniacs.” They immediately dismiss any new record high for a month or a year or, most recently, the first 6 months, because the data has been adjusted. They invoke rule 5: conspiracy theory by implication. The peer review of adjustments is just pal review; the adjusters have to get a warmer result to ensure their funding continues, and the satellite data, which is pristine, diverges from the adjusted data datasets.

    My standard rebuttals are: If you have any evidence that any adjustment is incorrect or fraudulent, post it (they never do), and Satellite data is not only not pristine, it is probably the most adjusted of datasets, and, in it’s raw form isn’t even temperature data, and, it isn’t surface temperature data anyway.

    Then they switch to attacking Michael Mann, Gavin Schmidt, Tamino, Al Gore, John Cook, RealClimate, and Skeptical Science, not necessarily in that order.

    [Response: If I’m on their list of favorite targets, I must be doing something right.]

    But although they are “rawmaniacs,” they never resort to showing what the historical temperature graph would look like if only the “raw” data were used, whatever that means for each dataset. Does anybody do that? Is the raw data all still kept somewhere?

    [Response: I did that a few years back, so did several others. Result: no meaningful difference in results.]

  8. Horatio! We need you to do “The Bob” to the tune of “The Blob!”

  9. Bobby Tisdale’s most recent piece explaining (in his own words) how ERSSTv4 is oh-so profoundly wrong (Wattsupia July 21) actually make two points.
    The first point can be easily dismissed by the comment from Sou in the post here. But extra to that, it takes only a quick swuint at Figure 6 of Huang et al (2015) to see that whatever the small contribution of the ship data within ERSSTv4 during the interval 1998-2010, the adjustment over that period is pretty flat and so is doubly inconsequential.
    The second point Bobby labours to make is that he wants to examine the “hiatus” years which according to Bobby span the years 1998-2012. Bobby assures us that Karl et al (2015) “used 1998 as the start year for many of their trend comparisons.” Indeed, Karl et al (2015) do rather stress that this 1998-2012 is “the most recent IPCC period” and not one of their devising. And the IPCC say of this period:-

    “Due to natural variability, trends based on short records are very sensitive to the beginning and end dates and do not in general reflect long-term climate trends. As one example, the rate of warming over the past 15 years (1998–2012; 0.05 [–0.05 to 0.15] °C per decade), which begins with a strong El Niño, is smaller than the rate calculated since 1951 (1951–2012; 0.12 [0.08 to 0.14] °C per decade).”

    So, just as Karl et al (2012) talk of a “hiatus” as some apparent phenomenon, a fantasy and not a real event, the IPCC are presenting the period 1998-2012 as an example of cherry-picking.
    And Bobby argues (at some length, so his message is clear) that we should indeed be cherry-picking this fantasy phenomenon for examination.
    I’m not sure myself what methods are best to employ in such circumstances. A Ouija board? Astrology? The entrails of dead sheep? In such a situation as this I’m well out of my depth but that is probably precisely where Bobby is used to operating.