Temperature is such a simple finite thing. It is amazing how complex people can make it.
– commenter and friend of WUWT, ossqss at Judith Curry’s blog
Sometimes, you can believe you are entirely right while simultaneously believing that you’ve done due diligence. That’s what confirmation bias is all about. In this case, a whole bunch of people, including me, got a severe case of it.
I’m talking about the claim made by Steve Goddard that 40% of the USHCN data is “fabricated”. which I and few other people thought was clearly wrong.
Dr. Judith Curry and I have been conversing a lot via email over the past two days, and she has written an illuminating essay that explores the issue raised by Goddard and the sociology going on. See her essay:
http://judithcurry.com/2014/06/28/skeptical-of-skeptics-is-steve-goddard-right/
Steve Goddard aka Tony Heller deserves the credit for the initial finding, Paul Homewood deserves the credit for taking the finding and establishing it in a more comprehensible
way that opened closed eyes, including mine, in this post entitled Massive Temperature Adjustments At Luling, Texas. Along with that is his latest followup, showing the problem isn’t limited to Texas, but also in Kansas. And there’s more about this below.
Goddard early on (June 2) gave me his source code that made his graph, but I
couldn’t get it to compile and run. That’s probably more my fault than his, as I’m not an expert in C++ computer language. Had I been able to, things might have gone differently. Then there was the fact that the problem Goddard noted doesn’t show up in GHCN data and I didn’t see the problem in any of the data we had for our USHCN surface stations analysis.
But, the thing that really put up a wall for me was this moment on June 1st, shortly after getting Goddard’s first email with his finding, which I pointed out in On ‘denying’ Hockey Sticks, USHCN data, and all that – part 1.
Goddard initially claimed 40% of the STATIONS were missing, which I said right away was not possible. It raised my hackles, and prompted my “you need to do better” statement. Then he switched the text in his post from stations to data while I was away for a couple of hours at my daughter’s music recital. When I returned, I noted the change, with no note of the change on his post, and that is what really put up the wall for me. He probably looked at it like he was just fixing a typo, I looked at it like it was sweeping an important distinction under the rug.
Then there was my personal bias over previous episodes where Goddard had made what I considered grievous errors, and refused to admit to them. There was the claim of CO2 freezing out of the air in Antarctica episode, later shown to be impossible by an experiment and the GISStimating 1998 episode, and the comment where when the old data is checked and it is clear Goddard/Heller’s claim doesn’t hold up.
And then just over a month ago there was Goddard’s first hockey stick shape in the USHCN data set, which turned out to be nothing but an artifact.
All of that added up to a big heap of confirmation bias, I was so used to Goddard being wrong, I expected it again, but this time Steve Goddard was right and my confirmation bias prevented me from seeing that there was in fact a real issue in the data and that NCDC has dead stations that are reporting data that isn’t real: mea culpa.
But, that’s the same problem many climate scientists have, they are used to some skeptics being wrong on some issues, so they put up a wall. That is why the careful and exacting analyses we see from Steve McIntyre should be a model for us all. We have to “do better” to make sure that claims we make are credible, documented, phrased in non-inflammatory language, understandable, and most importantly, right.
Otherwise, walls go up, confirmation bias sets in.
Now that the wall is down, NCDC won’t be able to ignore this, even John Nielsen-Gammon, who was critical of Goddard along with me in the Polifact story now says there is a real problem. So does Zeke, and we have all sent or forwarded email to NCDC advising them of it.
I’ve also been on the phone Friday with the assistant director of NCDC and chief scientist (Tom Peterson), and also with the person in charge of USHCN (Matt Menne). Both were quality, professional conversations, and both thanked me for bringing it to their attention. There is lots of email flying back and forth too.
They are taking this seriously, they have to, as final data as currently presented for USHCN is clearly wrong. John Neilsen-Gammon sent me a cursory analysis for Texas USHCN stations, noting he found a number of stations that had “estimated” data in place of actual good data that NCDC has in hand, and appears in the RAW USHCN data file on their FTP site
From:John Nielsen-Gammon Sent: Friday, June 27, 2014 9:27 AM To: Anthony Subject: Re: USHCN station at Luling Texas
Anthony –
I just did a check of all Texas USHCN stations. Thirteen had estimates in place of apparently good data.
410174 Estimated May 2008 thru June 2009
410498 Estimated since Oct 2011
410639 Estimated since July 2012 (exc Feb-Mar 2012, Nov 2012, Mar 2013, and May 2013)
410902 Estimated since Aug 2013
411048 Estimated July 2012 thru Feb 2014
412906 Estimated since Jan 2013
413240 Estimated since March 2013
413280 Estimated since Oct 2012
415018 Estimated since April 2010, defunct since Dec 2012
415429 Estimated since May 2013
416276 Estimated since Nov 2012
417945 Estimated since May 2013
418201Estimated since April 2013 (exc Dec 2013).
What is going on is that the USHCN code is that while the RAW data file has the actual measurements, for some reason the final data they publish doesn’t get the memo that good data is actually present for these stations, so it “infills” it with estimated data using data from surrounding stations. It’s a bug, a big one. And as Zeke did a cursory analysis Thursday night, he discovered it was systemic to the entire record, and up to 10% of stations have “estimated” data spanning over a century:
And here is the real kicker, “Zombie weather stations” exist in the USHCN final data set that are still generating data, even though they have been closed.
Remember Marysville, CA, the poster child for bad station siting? It was the station that gave me my “light bulb moment” on the issue of station siting. Here is a photo I took in May 2007:
![marysville_badsiting[1]](http://wattsupwiththat.files.wordpress.com/2014/06/marysville_badsiting1.jpg?quality=83)
It was closed just a couple of months after I introduced it to the world as the prime example of “How not to measure temperature”. The MMTS sensor was in a parking lot, with hot air from a/c units from the nearby electronics sheds for the cell phone tower:
Guess what? Like Luling, TX, which is still open, but getting estimated data in place of the actual data in the final USHCN data file, even though it was marked closed in 2007 by NOAA’s own metadata, Marysville is still producing estimated monthly data, marked with an “E” flag:
USH00045385 2006 1034E 1156h 1036g 1501h 2166i 2601E 2905E 2494E 2314E 1741E 1298E 848i 0 USH00045385 2007 797c 1151E 1575i 1701E 2159E 2418E 2628E 2620E 2197E 1711E 1408E 846E 0 USH00045385 2008 836E 1064E 1386E 1610E 2146E 2508E 2686E 2658E 2383E 1906E 1427E 750E 0 USH00045385 2009 969E 1092E 1316E 1641E 2238E 2354E 2685E 2583E 2519E 1739E 1272E 809E 0 USH00045385 2010 951E 1190E 1302E 1379E 1746E 2401E 2617E 2427E 2340E 1904E 1255E 1073E 0 USH00045385 2011 831E 991E 1228E 1565E 1792E 2223E 2558E 2536E 2511E 1853E 1161E 867E 0 USH00045385 2012 978E 1161E 1229E 1646E 2147E 2387E 2597E 2660E 2454E 1931E 1383E 928E 0 USH00045385 2013 820E 1062E 1494E 1864E 2199E 2480E 2759E 2568E 2286E 1807E 1396E 844E 0 USH00045385 2014 1188E 1247E 1553E 1777E 2245E 2526E -9999 -9999 -9999 -9999 -9999 -9999
Source: USHCN Final : ushcn.tavg.latest.FLs.52i.tar.gz
Compare to USHCN Raw : ushcn.tavg.latest.raw.tar.gz
In the USHCN V2.5 folder, the readme file describes the “E” flag as:
E = a monthly value could not be computed from daily data. The value is estimated using values from surrounding stations
There are quite a few “zombie weather stations” in the USHCN final dataset, possibly up to 25% out of the 1218 that is the total number of stations. In my conversations with NCDC on Friday, I’m told these were kept in and “reporting” as a policy decision to provide a “continuity” of data for scientific purposes. While there “might” be some justification for that sort of thinking, few people know about it there’s no disclaimer or caveat in the USHCN FTP folder at NCDC or in the readme file that describes this, they “hint” at it saying:
The composition of the network remains unchanged at 1218 stations
But that really isn’t true, as some USHCN stations out of the 1218 have been closed and are no longer reporting real data, but instead are reporting estimated data.
NCDC really should make this clear, and while it “might” be OK to produce a datafile that has estimated data in it, not everyone is going to understand what that means, and that the stations that have been long dead are producing estimated data. NCDC has failed in notifying the public, and even their colleagues of this. Even the Texas State Climatologist John Nielsen-Gammon didn’t know about these “zombie” stations until I showed him. If he had known, his opinion might have been different on the Goddard issue. When even professional people in your sphere of influence don’t know you are doing dead weather station data infills like this, you can be sure that your primary mission to provide useful data is FUBAR.
NCDC needs to step up and fix this along with other problems that have been identified.
And they are, I expect some sort of a statement, and possibly a correction next week. In the meantime, let’s let them do their work and go through their methodology. It will not be helpful to ANYONE if we start beating up the people at NCDC ahead of such a statement and/or correction.
I will be among the first, if not the first to know what they are doing to fix the issues, and as soon as I know, so will all of you. Patience and restraint is what we need at the moment. I believe they are making a good faith effort, but as you all know the government moves slowly, they have to get policy wonks to review documents and all that. So, we’ll likely hear something early next week.
These lapses in quality control and thinking that infilling estimated data for long dead weather stations is the sort of thing happens when the only people that you interact with are inside your sphere of influence. The “yeah that seems like a good idea” approval mumble probably resonated in that NCDC meeting, but it was a case of groupthink. Imagine The Wall Street Journal providing “estimated” stock values for long dead companies to provide “continuity” of their stock quotes page. Such a thing would boggle the mind and the SEC would have a cow, not to mention readers. Scams would erupt trying to sell stocks for these long dead companies; “It’s real, see its reporting value in the WSJ!”.
It often takes people outside of climate science to point out the problems they don’t see, and skeptics have been doing it for years. Today, we are doing it again.
For absolute clarity, I should point out that the RAW USHCN monthly datafile is NOT being infilled with estimated data, only the FINAL USHCN monthly datafile. But that is the one that many other metrics use, including NASA GISS, and it goes into the mix for things like the NCDC monthly State of the Climate Report.
While we won’t know until all of the data is corrected and new numbers run, this may affect some of the absolute temperature claims made on SOTC reports such as “warmest month ever” and 3rd warmest, etc. The magnitude of such shifts, if any, is unknown at this point. Long term trend will probably not be affected.
It may also affect our comparisons between raw and final adjusted USHCN data we have been doing for our paper, such as this one from our draft paper:
The exception is BEST, which starts with the raw daily data, but they might be getting tripped up into creating some “zombie stations” of their own by the NCDC metadata and resolution improvements to lat/lon. The USHCN station at Luling Texas is listed as having 7 station moves by BEST (note the red diamonds):
But there really has only been two, and the station has been just like this since 1995, when it was converted to MMTS from a Stevenson Screen. Here is our survey image from 2009:
Photo by surfacestations volunteer John Warren Slayton.
NCDC’s metadata only lists two station moves:
As you can see below, some improvements in lat/lon accuracy can look like a station move:
http://www.ncdc.noaa.gov/homr/#ncdcstnid=20024457&tab=LOCATIONS
http://www.ncdc.noaa.gov/homr/#ncdcstnid=20024457&tab=MISC
Thanks to Paul Homewood for the two images and links above. I’m sure Mr. Mosher will let us know if this issue affects BEST or not.
And there is yet another issue: The recent change of something called “climate divisions” to calculate the national and state temperatures.
Certified Consulting Meteorologist and Fellow of the AMS Joe D’Aleo writes in with this:
I had downloaded the Maine annual temperature plot from NCDC Climate at a Glance in 2013 for a talk. There was no statistically significant trend since 1895. Note the spike in 1913 following super blocking from Novarupta in Alaska (similar to the high latitude volcanoes in late 2000s which helped with the blocking and maritime influence that spiked 2010 as snow was gone by March with a steady northeast maritime Atlantic flow). 1913 was close to 46F. and the long term mean just over 41F.
Seemingly in a panic change late this frigid winter to NCDC, big changes occurred. I wanted to update the Maine plot for another talk and got this from NCDC CAAG.
Note that 1913 was cooled nearly 5 degrees F and does not stand out. There is a warming of at least 3 degrees F since 1895 (they list 0.23/decade) and the new mean is close to 40F.
Does anybody know what the REAL temperature of Maine is/was/is supposed to be? I sure as hell don’t. I don’t think NCDC really does either.
In closing…
Besides moving toward a more accurate temperature record, the best thing about all this hoopla over the USHCN data set is the Polifact story where we have all these experts lined up (including me as the token skeptic) that stated without a doubt that Goddard was wrong and rated the claim “pants of fire”.
They’ll all be eating some crow, as will I, but now that I have Gavin for dinner company, I don’t really mind at all.
When the scientific method is at work, eventually, everybody eats crow. The trick is to be able to eat it and tell people that you are honestly enjoying it, because crow is so popular, it is on the science menu daily.
omnologos says: June 28, 2014 at 1:54 pm
“Nick Stokes please find a station with a faulty cable causing readings to be transmitted high”
Sometimes Nature just has a warmist bias. I’m not on top of the details here, but it seems cables are supposed to have near zero resistance. Positive resistance will reduce the voltage. Negative will increase it. But they don’t do negative.
Same with TOBS. If you go from afternoon to morning reading, the trend will reduce, and adjustment will increase it. If you go from morning to afternoon, conversely. But, as it happens, the NWS originally had people reading in the afternoon. There’s only one way that can go.
From a lay perspective, comparing the estimated (E) data in Luling, Tx to the temperatures reported by the local weather channel would be interesting.
Even though the local TV weather station equipment isn’t part of the “official” network or approved hardware, the comparison seems just as reasonable as averaging nearby temps from approved hardware in the official network to estimate missing data.
richardscourtney says: June 28, 2014 at 3:08 pm
Thanks.
Mosher: Its over no one believes it anymore please give up. The “modeling” of AGW is a FANTASY! but go ahead if you still belive in it thats what science is about LOL(from a person with 4 higher university degrees, BTW ask Freeman Dyson PLEASEEE)
Anthony, what you said in this post has (as far as anyone has shown) absolutely nothing to do with what was said in the Polifact story. Your comments in regard to the Polifact story are not even wrong. They’re just incoherent. You are misleading people by pretending this bug somehow proves what Goddard said in that story is correct.
The only reason I got sidetracked is you presented this bug as proving Goddard right about what he said in the Polifact story when it doesn’t.
REPLY: If you’ll read the Polifact story, you’ll note they are combining link and comments from two issues. The quote they used from me was about the data error issue, the link the make to Zeke’s post at Lucia’s is from Goddard’s original 40% fabrication claim. I agree they have muddled it somewhat with the animgraph. But the idea discussed has been about “fabricating” (or as I address it “infilling and estimating” temperatures. That has in fact increased since year 2000.
Polifact asked Dr. Curry about the infilling 40% issue, and she referred them to Zeke and I.
No intent was made on my part to confuse people. – Anthony
Goddard’s analysis in this case was shown to be faulty multiple times.
I don’t think so. But if that helps you sleep at night, go with it.
Brandon Shollenberger … Estimating does change trends. Stop denying it.
http://sunshinehours.wordpress.com/2014/06/05/ushcn-2-5-estimated-data-is-warming-data-arizona/
Here’s the thing Anthony, jump in to save face, after you made a fool of yourself, and then claim victory.
It works every time.
(Oh, it’s okay to not publish this. I just wanted the screen shot for my diary.)
REPLY: No problem, frame it if you like, but you see here’s the big difference between you and I. I put my name to my words, take my lumps when deserved, and even write about it. you taunt from behind the safety of a fake name. Color me unimpressed. (Oh, it’s OK not to print out this part for your diary) – Anthony
(y) 🙂
Novarupta 1913: Yet another instance of a major volcanic eruption apparently causing warming rather than cooling.
Should note, high latitude v. tropical.
“PS someone FOI the emails for this data change bet the dog will eat them real quick”
Bet their hard drives will crash first…
Anthony, Thank you for manning up. And thank you for this great blog and this great post. The issue of temperature adjustments has always been one of the reasons I don’t trust climate science.
So, does anybody want to wager that once they get this issue straightened out, that the new results will show even worse warming?
Just like the temperature record adjustments, Nick Stokes comments only go one way. lol
Andrew
If the ultimate idea is to “get it right”, then it would seem that many scientists often don’t but through proper scientific methods and persistence may.
Kudos to all who continue to move toward getting it right.
As someone mentioned earlier in this thread, it is more than a little disconcerting to see how suspect the US’s “world’s best” temperature monitoring system is.
Anthony it is good that you have admitted that you had raised straw man arguments that had no bearing on what Steve/Tim was saying. As an outsider with no skin in this game, I always understood what Steve/Tim was saying as it was quite clear if you had started from the beginning and followed his analysis step by step. You have to admin that you did a lot of initial damage to the raising of what is a massive systematic error (being polite) with your previous pieces and that the you gave the alarmist community a “get out of jail free card” on this issue. You now have to work twice as hard to get this issue the spotlight that it deserves.
REPLY: Who is “Tim”?
“The fact that estimated data from long-dead and missing stations is being produced is news.”
It’s the basis of FILNET, which is a long standing USHCN processing step. You can calculate an average with absolute temperatures, which USHCN does, but it’s more complicated than anomalies (and so, IMO, a bad idea). Each data point is the sum of a climatology component and an anomaly component. If you let the station set vary over time then the climatology component will provide a spurious signal. That was the Goddard spike, for example.
So they keep the station set constant, with a fixed set of climatologies, and interpolate anomalies where needed. When you are doing what is in effect a spatial integration of anomalies, interpolating extra values just affects the weighting. Numerical integration is effectively the integration of an interpolating function.
The existence of zombie stations isn’t new, and isn’t a problem. The result just depends on how many real stations there are. And that is mostly somewhere around 800, which is a lot for the area of CONUS.
REPLY:
Well aware of FILNET for years. John Neilsen-Gammon didn’t know that “zombie” stations were still reporting, it was news to him. It was news to me. It is news to a number of people reading here for the first time.
And no matter what you say Nick, making up data where there is none, especially from long dead weather stations using crappy data from surrounding compromised stations is still wrong. For the record, I don’t give a flying F how you rationalize it.
-Anthony
By Nick Stokes thinking, we could use FILNET to make up for missing ice in the Arctic extent maps by interpolating from nearby ice readings and “infill” where ice is missing. We know there’s supposed to be ice there, so let’s just infill it from surrounding ice data, even if its “rotten ice”.
Arctic problem solved. Polar bears saved!
No, wait, that would be wrong….and equally ridiculous.
Making up data where there is none, especially for years for long dead weather stations, is just wrong. If it were financial data, say companies that went bankrupt and closed, and fell off the Dow-Jones Industrial average, but somebody decided that they could “fill in” that missing company data to keep the “continuity” of the DJIA data set over the years, you can bet that somebody would be hauled off to jail within a day or two by the SEC.
Fixing a few missing datapoints in a month with FILNET to make the record useable is one thing, wholesale reanimation of dead weather stations for years is something else altogether.
Reblogged this on Climatism and commented:
Sceptics “eat crow” ~ Science, discovery, truth, integrity and reason the big winners.
Bravo Mr Watts…and Mr Heller.
Will the Global Warming zealotry; NASA, NOAA, USHCN, Gavin, Mosher et al come to the table, or will the usual dose of denial, obfuscation and pal-reviewed-reasoning win the day?
This episode represents why it is important not to try and placate BEST team members. Anthony, it is really not important that you immediately speak out on these issues. Please stop listening to those who have screwed you over in the past, I cannot repeat this enough. Their only intent is to use your words against you.
Nick, anomalies can’t work. Only 51 USHCN Stations have a full 30 years with on non-Estimated data from 1961-1990 (your preferred baseline).
[“with on non-Estimated” or “with no non-Estimated” data ? .mod]
And Brandon. The Arizona blog post I did was mentioned in one of the threads on the Blackboard. I know you read that blog.
My post was June 5th as was the Blackboard thread.
This Post, plus the corresponding one at CE, are a magnificent example of how the internet has changed everything. For the better, albeit threatening all ivory tower foundations. The academically robed are running scared.
A flawed but interesting proposition put forth, rapidly scrutinized using all sorts of mathematical and data arguments, resulting in a new synthesis now forming that the original hypothesis was flawed but the conclusion may be ‘robust’.
Much faster than ‘peer review’ and much more brutal. And wide open for anyone who cares to go fact check for themselves. (Mosher, your explanation of the BEST conclusion for station 166900 over at CE still does not ring true, since you completely avoided my key argument about the flaw in your methodology illustrated by that station using only the data and words BEST itself posted.)
We are entering a new era, ushered in by the great IPCC/CAGW meme. Could not have happened to more deserving folks than establishment consensus climatologists.. But will spread to medicine, energy, economy–everywhere it matters.
I can’t see the NCDC fixing the database in a meaningful way.
If anything, they will come back and say the trend is even higher after we fixed it (or it was 0.003C in total or something).
They have the data, they have 20 analysts working with it. Tom Peterson leans over someone’s desk twice a week tweaking some assumption. This is just the way large databases are managed when senior people have a stake in the results.
… The existence of zombie stations isn’t new, and isn’t a problem.
Well no. Not if your objective is to cool the past and warm the present. I suppose that you have many ways to fudge the data and are very comfortable with all of them. For outsiders, some of these things come as a real surprise.
I once read about a study of the number of deaths in winter in England attributed to the high cost of heating and many people could not afford it. The number was dramatic. I wonder if the dead would agree that a false warming trend that has caused billions and billions to be wasted and energy bills to rise “isn’t a problem”.
richardscourtney says:
June 28, 2014 at 3:08 pm
Nick Stokes:
I write to congratulate you on your fortitude and to commend you for the honour you display by ‘standing your ground’.
____
Let me second that. There is so much bad blood in the climate discussion that one can hardly blame someone for the occasional eruption of anger or cynicism, but some participants have been able to maintain a professional and helpful tone despite the brickbats thrown their way. Stokes is high on that list as are Judith Curry and the Australians. I’m sure there are others I am not familiar with, but I should not omit Richard Courtney. I don’t always agree with everyone mentioned but I take their professionalism as a standard.
@Nick Stokes at 4:19 pm
It’s the basis of FILNET, which is a long standing USHCN processing step.
It is my experience that the tool constrains the thinking.
The existence of zombie stations isn’t new, and isn’t a problem.
No, it isn’t new. And had it stayed at 5% of the data, it could be accepted as a simplifying assumption and it wouldn’t likely be a problem.
But Goddard may us sit up and notice that the zombie data hoard has been growing to alarming percentages of the total data over the past decade. It is no longer at the scale of a simplifying assumption but a serious concern for integrity of the data, analysis, results, and conclusions.
The tool, under these circumstances, is causing problems.
It is time to Think Different.