The scientific method is at work on the USHCN temperature data set

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:

Analysis by Zeke Hausfather
Analysis by Zeke Hausfather

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]

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:

MarysvilleCA_USHCN_Site_small

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:

Watts_et_al_2012 Figure20 CONUS Compliant-NonC-NOAA

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):

Luling-TX-BEST

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:

Luling_looking_north

Photo by surfacestations volunteer John Warren Slayton.

NCDC’s metadata only lists two station moves:

image

As you can see below, some improvements in lat/lon accuracy can look like a station move:

image

http://www.ncdc.noaa.gov/homr/#ncdcstnid=20024457&tab=LOCATIONS

image

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.

 CAAG_Maine_before

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. 

CAAG_maine_after

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.

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June 29, 2014 6:14 am

Nick, NOAA grids on a 5km x 5km grid. Infilling is not necessary to grid.
Infilling is necessary to warm.
http://sunshinehours.wordpress.com/2014/06/29/ushcn-2-5-estimated-data-is-warming-data-usa-1980-2014/

June 29, 2014 6:15 am

Reagarding the impossibility of CO2 freezing out of the atmosphere.
The experiment of the refrigerator is not quite fair as refrigerators have an internal fan which will mix any pockets of CO2. But you can imagine circumstances where CO2 could be allowed to settle, any sublimated gas would remain in this pocket and provide a high partial pressure environment.
As an example of some of the complexities involved, see this article on natural isotopic separations in fern: http://www.whoi.edu/cms/files/kcasciotti/2006/9/Craig1988_14129.pdf
I doubt it is a significant effect in atmospheric composition, but it does point to the complexities of what happens in the real world compared to a laboratory.

NikFromNYC
June 29, 2014 6:17 am

ferdberple asserts: “paul homewood appears to confirm that goddard was correct on more issues than the zombie stations. Kansas was adjusted about 1/2 degree upwards in 2013. man made warming indeed.”
But that well known adjustment has little to do with the overextended infilling that has now gotten Watts’ attention as a stations hound. The bulk of the adjustment is time of day adjustment (TOBS), which Goddard separately claims is actually being done now vastly in excess of their stated amount, a claim that has not been hashed out yet by other skeptics, but mostly ignored. Perhaps Goddard is attributing to TOBS some of his own artifacts? If Goddard didn’t willfully isolate himself so badly by being so conspiratorial and political as he harbors crackpots, nice liberal minded scientist types might offer him more consistent feedback before he heads into heart of darkness episodes with little technical feedback at all for months at a time which explains how his spurious data drop out adjustments hockey stick lingered on for two years to the delight of his cheerleading squad. When I properly pointed the potential flaw out to him that team of supporters attacked me for being crazy, and the way Goddard failed to moderate this attack further isolates him. This isolation has now led to a skeptic bashing news cycle.
Please note the silence from software savvy skeptics over whether this newly discovered infilling actually adds a false warming trend as Goddard strongly claims it does, in the face of competent claims that it does not. I make little single glance infographics to present skeptical arguments on news sites. So I’ve been pressuring Goddard for years to present the real details of his various procedures, but I am regularly attacked for doing so, so there’s no meat on the bones there, as far as I can tell. That I was attacked there for also being a vegetarian was kind of laughable for a guy who makes his own hipster beef jerky.
-=NikFromNYC=-, Ph.D. in carbon chemistry (Columbia/Harvard)

Bill Illis
June 29, 2014 6:22 am

Nick Stokes says:
June 29, 2014 at 4:47 am
You need to keep the same climatology from month to month.
—————————————
With all the adjustments, the climatology itself is changing every month. I wonder how many recalc cycles one must run in order to keep that situation accurate.
Kevin K. says:
June 28, 2014 at 6:29 pm above that the climatology is not the same as the simple arithmetic mean of the station data in the baseperiod.
There could be some systematic problems with just the climatology that should be looked at.

angech
June 29, 2014 6:27 am

Nick Stokes supports using altered data as real data and prefers the use of anomalies which as he knows full well hides the temperature adjustments that have been made and continue to be made.
“They are used to calculate averages. That is the purpose of adjustment. And it isn’t an error.”
No it definitely is not an error and it definitely is not science as I know it.

June 29, 2014 6:48 am

NikFromNYC: “The bulk of the adjustment is time of day adjustment (TOBS)”
Wrong.
This is Jan 1895 to 2013 TMAX graphed (no gridding … but gridding doesn’t change much)
The trend is -0.1C/decade raw.
The trend goes to 0.2C with TOBS
The trend goes to 0.5 with the rest of the adjustments.comment image

June 29, 2014 7:03 am

“if you split a station where there is no actual move it has no effect.”
To this statement, Steve Mosher, I have to object!
This trick introduces a warming effect:
The temp sharply drops; there’s a cooling trend forming
But you split it there.
Cooling gone.
Global Warming!
===|==============/ Keith DeHavelle

June 29, 2014 7:04 am

Infilling in USHCN tends to emphasize the trend. If the trend is up, the infilled data makes the trend steeper in the upwards direction. If the trend is down, infilling makes the trend steep in the downwards direction.
But the data is always higher.
Warming trend:
http://sunshinehours.wordpress.com/2014/06/29/ushcn-2-5-estimated-data-is-warming-data-usa-1980-2014/
Cooling trend:
http://sunshinehours.wordpress.com/2014/06/29/ushcn-2-5-estimated-data-is-warming-data-usa-1980-2014/

Dan in Nevada
June 29, 2014 7:04 am

It’s surprising that anybody is surprised that data needs to be adjusted in order to be useful and conform to modern expectations. There are numerous examples of this. In 1936, under the wise leadership of FDR, the National Congressional Decision Commissar (NCDC) was formed specifically to address issues such as incorrect thinking, principles, ethics, or honesty that were causing Congressional gridlock and preventing needed Progressive reforms.
The problem was that the use of “raw” votes would lead to either incorrect legislation or prevent necessary legislation from being passed. Using finely-honed algorithms, the NCDC replaces obviously wrong “raw” votes and instead infills corrected votes using a spatially- and politically-correct gridding system.
One originally unforeseen circumstance was that the Congressional Record could be used against incumbent Congressmen and Senators during the election cycle. Thus, over time, it became necessary to adjust past (possibly already adjusted) votes to ensure proper results in the elections. Thus there are numerous cases, such as socialized health-care or invading faraway third-world countries for no reason at all, where the legislation clearly happened at one point, but a majority of legislators can claim that they themselves did not vote for it.
This is probably alarming to some people, and a knee-jerk reaction might be to suspect fraud or dishonesty, but this is how a modern society must function. Rest assured that your government has only your best interests at heart and is committed to always being able to show in retrospect that they did the right thing.

Greg Goodman
June 29, 2014 7:15 am

“Infilling in USHCN tends to emphasize the trend. If the trend is up, the infilled data makes the trend steeper in the upwards direction. If the trend is down, infilling makes the trend steep in the downwards direction.”
And since the centennial trend is upwards on average… it increase GW.
Nice one , sunshine !

Dan in Nevada
June 29, 2014 7:18 am

Stuck in moderation? Didn’t mean to offend.

REPLY:
Sometimes people get this erroneous idea that we examine every comment, we don’t. The ones that get flagged by the spam filter get held often times due to a complex formula we have no control over. I can tell you that the longer the comment, the greater chance the spam filter will flag it. It is up now. – Anthony

Greg Goodman
June 29, 2014 7:24 am

Bill Illis: “With all the adjustments, the climatology itself is changing every month. I wonder how many recalc cycles one must run in order to keep that situation accurate.”
hey, repeat until it converges, like hadSST do.

Greg Goodman
June 29, 2014 7:34 am

“Infilling in USHCN tends to emphasize the trend. If the trend is up, the infilled data makes the trend steeper in the upwards direction. If the trend is down, infilling makes the trend steep in the downwards direction.”
I think this is probably statistically predictable in data set were 80% are sub-standard installations subject to UHI.
This is a result of what our host refered to as “warm soup”.
It will be interesting to see what NOAA et al come up with “next week”. My guess is they will find they ‘need more time’.
I suspect this will do for data confidence, what Climategate did for trust in climatologists.

Global cooling
June 29, 2014 7:42 am

Conspiracy theories are not plausible in the eyes of media and ordinary people. It is better to tell them that the old temperature record is bad. Data is missing, inconsistent and created for another purpose.
Especially metadata, data of the data is missing. We do not know the history of weather stations accurately enough to reconstruct the information based on the raw data only. A temperature reading is a sum (or actually a complex function) of the climate signal and a number of other factors such as exact time of the reading, UHI and changes in the local environment. Without knowing these accurately we can’t calculate the climate signal.
This is why sceptics follow the satellite data that we have from 1979.

Bill Illis
June 29, 2014 7:48 am

sunshinehours1 says:
June 29, 2014 at 6:48 am
——————–
Sunshinehours1, can you plot just the adjustments over time. Raw-minus-Tobs, Raw minus final. And then plot both with a baseline to end in 2013 at 0.0C. It should reach a maximum negative around 0.5C in 1930-1940.
It is just easier for most people to understand.

PMHinSC
June 29, 2014 7:50 am

Zeke Hausfather says:
June 28, 2014 at 6:04 pm
“If you don’t like infilling, don’t use it. It doesn’t change the result…”
June 28, 2014 at 6:24 pm
“Infilling shouldn’t have any effect on temperatures, because …”
It “doesn’t change the result” or it “shouldn’t” change the result? Anytime you defend something that shouldn’t be done you are losing the argument. Performing unnecessary operations leaves you open to mistakes and criticism. Let the process play its self out and we will know rather than speculate whether is “shouldn’t” or “doesn’t.” Rather than stoking a dying fire, wouldn’t it be better to do something more constructive?

Dalcio Dacol
June 29, 2014 8:12 am

I predict that when USHCN corrects its “methodology” the past will be even cooler and the present even warmer because, you know, it is worse than we thought!

Dan in Nevada
June 29, 2014 8:26 am

@Anthony 7:18 Thanks for the reply. Right after I complained, I re-read and saw at least one known code-word. My bad.

David S
June 29, 2014 8:46 am

Ok so here’s a question I’ve been wondering about for some time: Prior to the computer era, temperature data was written by hand into monthly log sheets. That handwritten data has to be manually copied into computer databases so that graphs can be constructed and long term trends determined. Doing even 1 years worth of data for a single weather station is a huge task requiring many man hours to do. So who did that? And where can someone find the digitized (unadjusted) data?

Richard M
June 29, 2014 8:57 am

Correct me if I’m wrong, but doesn’t this infilling mechanism create yet another problem? When NOAA provides one of their monthly reports it is likely based on incomplete data. Just as we see with elections the latest reporting stations are most likely the rural ones. This means they are being infilled from urban data. While this should eventually get corrected, it will make the most recent months appear warmer than they really were. Since these NOAA reports get highlighted in the press we are constantly being presented a false picture of reality.
This is probably why the July 2012 average is no longer the warmest “evah”. The addition of more and more real data cools the final result. By continuing to make these reports NOAA is presenting propaganda. The politicians then repeat this propaganda. Anyone think this will stop?

Editor
June 29, 2014 9:06 am

David S
And where can someone find the digitized (unadjusted) data?
The original station data can be accessed here.
http://www.ncdc.noaa.gov/IPS/coop/coop.html
This gives the original, hand written monthly reports of daily temps

Editor
June 29, 2014 9:11 am

From some data I saved two years ago for Alabama, it seems that the TOBS adjustment has increased by about 0.6F between the 2012 version and now.
For instance, the TOBS adj temp for Nov 2011 has been increased by 0.3F, while Nov 1934 has dropped by a similar amount.
http://notalotofpeopleknowthat.wordpress.com/2014/06/29/more-news-on-ushcn-temperature-adjustments/
And just to complicate matters further! The latest USHCN update for Luling has changed since I printed it off two days ago. Not by much, but even temps for 1998 have been altered.
Apparently, actual temperature data is no longer important!

bruce ryan
June 29, 2014 9:56 am

the nut of it, you really shouldn’t be using data from instrumentation not intended for the purpose. iow a weather station reflects current weather such as it is including the conditions in which it is situated. Which is what it was designed for. How do you intend to compare data with conditions in a continual evolution of environmental change? And designing software to devolve the conditions just isn’t right.

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