Does NOAA's National Climatic Data Center (NCDC) keep two separate sets of climate books for the USA?


UPDATE: See the first ever CONUS Tavg value for the year from the NCDC State of the Art Climate Reference Network here and compare its value for July 2012. There’s another surprise.

Glaring inconsistencies found between State of the Climate (SOTC) reports sent to the press and public and the “official” climate database record for the United States. Using NCDC’s own data, July 2012 can no longer be claimed to be the “hottest month on record”. UPDATE: Click graph at right for a WSJ story on the record.

First, I should point out that I didn’t go looking for this problem, it was a serendipitous discovery that came from me looking up the month-to-month average temperature for the CONtiguous United States (CONUS) for another project which you’ll see a report on in a  couple of days. What started as an oddity noted for a single month now seems clearly to be systemic over a two-year period. On the eve of what will likely be a pronouncement from NCDC on 2012 being the “hottest year ever”, and since what I found is systemic and very influential to the press and to the public, I thought I should make my findings widely known now. Everything I’ve found should be replicable independently using the links and examples I provide. I’m writing the article as a timeline of discovery.

At issue is the difference between temperature data claims in the NCDC State of the Climate reports issued monthly and at year-end and the official NCDC climate database made available to the public. Please read on for my full investigation.

You can see the most current SOTC for the USA here:

In that SOTC report they state right at the top:


Highlighted in yellow is the CONUS average temperature, which is the data I was after. I simply worked backwards each month to get the CONUS Tavg value and copy/paste it into a spreadsheet.

In early 2011 and late 2010, I started to encounter problems. The CONUS Tavg wasn’t in the SOTC reports, and I started to look around for an alternate source. Thankfully NCDC provided a link to that alternate source right in one the SOTC reports, specifically the first one where I discovered the CONUS Tavg value was missing, February 2011:


That highlighted in blue “United States” was a link for plotting the 3-month Dec-Feb average using the NCDC climate database. It was a simple matter to switch the plotter to a single month, and get the CONUS Tavg value for Feb 2011, as shown below. Note the CONUS Tavg value at bottom right in yellow:


All well and good, and I set off to continue to populate my spreadsheet by working backwards through time. Where SOTC didn’t have a value, I used the NCDC climate database plotter.

And then I discovered that prior to October 2010, there were no mentions of CONUS Tavg in the NCDC SOTC reports. Since I was recording the URL’s to source each piece of data as well, I realized that it wouldn’t look all that good to have sources from two different URL’s for the same data, and so for the sake of consistency, I decided to use only the CONUS Tavg value from the NCDC climate database plotter, since it seemed to be complete where the SOTC was not.

I set about the task of updating my spreadsheet with only the CONUS Tavg values from the NCDC climate database plotter, and that’s when I started noticing that temperatures between the SOTC and the NCDC climate database plotter didn’t match for the same month.

Compare for yourself:

NCDC’s SOTC July 2012:

Screencap of the claim for CONUS Tavg temperature for July 2012 in the SOTC:


Note the 77.6°F highlighted in blue. That is a link to the NCDC climate database plotter which is:

Screencap of the output from the NCDC climate database, note the value in yellow in the bottom right:


Note the difference. In the July 2012 State of the Climate Report, where NCDC makes the claim of “hottest month ever” and cites July 1936 as then benchmark record that was beaten, they say the CONUS Tavg for July 2012 is: 77.6°F

But in the NCDC climate database plotter output, the value is listed as 76.93°F almost 0.7°F cooler! They don’t match.

I initially thought this was just some simple arithmetic error or reporting error, a one-off event, but then I began to find it in other months when I compared the output from the NCDC climate database plotter. Here is a table of the differences I found for the last two years between claims made in the SOTC report and the NCDC database output.


Table 1 – monthly average temperature differences between SOTC and the official database since October 2010, missing SOTC values are due to the CONUS Tavg not be included in that monthly report.

In almost every instance dating back to the inception of the CONUS Tavg value being reported in the SOTC report, there’s a difference. Some are quite significant. In most cases, the database value is cooler than the claim made in the SOTC report. Clearly, it is a systemic issue that spans over two years of reporting to the press and to the public.

It suggests that claims made by NCDC when they send out these SOTC reports aren’t credible because there are such differences between the data. Clearly, NCDC means for the plotter output they link to, to be an official representation to the public, so there cannot be a claim of me using some “not fit for purpose” method to get that data. Further, the issue reveals itself in the NCDC rankings report which they also link to in SOTC reports:



Note the 76.93°F I highlighted in yellow. Since it appears in two separate web output products, it seems highly unlikely this is a “calculation on demand” error, but more likely simply a database output and that is simply displayed data.

Note the claim made in the NCDC July 2012 SOTC for the July 1936 CONUS Tavg temperature which is:

The previous warmest July for the nation was July 1936, when the average U.S. temperature was 77.4°F.

But now in two places, NCDC is reporting that the CONUS Tavg for July 2012 is 76.93°F about 0.47°F cooler than 77.4°F claimed as the previous monthly record in 1936, meaning that July 2012 by that comparison WAS NOT THE HOTTEST MONTH ON RECORD.

The question for now is: why do we appear to have two different sets of data for the past two years between the official database and the SOTC reports and why have they let this claim they made stand if the data does not support it?

There’s another curiosity.

Curiously, the last two months in my table above, October and November 2012 have identical values between the database and the SOTC report for those months.

What’s going on? Well, the explanation is quite simple, it’s a technology gap.

You see, despite what some people think, the nation’s climate monitoring network used for the SOTC reports is not some state of the art system, but rather the old Cooperative Observer Network which came into being in the 1890’s after Congress formed the original US Weather Bureau. Back then, we didn’t have telephones, fax machines, radio, modems or the Internet. Everything was observed/measured manually and recorded by hand with pen and paper, and mailed into NCDC for transcription every month. That is still the case today for a good portion of the network. Here’s a handwritten B91 official reporting form from the observer at the station the New York Times claims is the “best in the nation”, the USHCN station in Mohonk, New York:



Note that in cases like this station, the observer sends the report in at the end of the month, and then NCDC transcribes it into digital data, runs that data through quality control to fix missing data and incorrectly recorded data, and all that takes time, often a month or two for all the stations to report. Some stations in the climate network, such as airports, report via radio links and the Internet in near real-time. They get there in time for the end of the month report where the old paper forms do not, hence the technology gap tends to favor more of a certain kind of station, such as airports, over other traditional stations.

NCDC knows this, and reported about it. Note my bolding.

NOAA’s National Climatic Data Center (NCDC) is the world’s largest active archive of weather data. Each month, observers that are part of the National Weather Service Cooperative Observer Program (COOP) send their land-based meteorological surface observations of temperature and precipitation to NCDC to be added to the U.S. data archives. The COOP network is the country’s oldest surface weather network and consists of more than 11,000 observers. At the end of each month, the data are transmitted to NCDC via telephone, computer, or mail.

Typically by the 3rd day of the following month, NCDC has received enough data to run processes which are used to calculate divisional averages within each of the 48 contiguous states. These climate divisions represent areas with similar temperature and precipitation characteristics (see Guttman and Quayle, 1996 for additional details). State values are then derived from the area-weighted divisional values. Regions are derived from the statewide values in the same manner. These results are then used in numerous climate applications and publications, such as the monthly U.S. State of the Climate Report.

NCDC is making plans to transition its U.S. operational suite of products from the traditional divisional dataset to the Global Historical Climatological Network (GHCN) dataset during in the summer of 2011. The GHCN dataset is the world’s largest collection of daily climatological data. The GHCN utilizes many of the same surface stations as the current divisional dataset, and the data are delivered to NCDC in the same fashion. Further details on the transition and how it will affect the customer will be made available in the near future.


The State of the Climate reports typically are issued in the first week of the next month. They don’t actually bother to put a release date on those reports, so I can’t give a table of specific dates. The press usually follows suit immediately afterwards, and we see claims like “hottest month ever” or “3rd warmest spring ever” being bandied about worldwide in news reports and blogs by the next day.

So basically, NCDC is making public claims about the average temperature of the United States, its rank compared to other months and years, and its severity, based on incomplete data. As I have demonstrated, that data then tends to change about two months later when all of the B91’s come in and are transcribed and the data set becomes complete.

It typically cools the country when all the data is used.

But, does NCDC go back and correct those early claims based on the new data? No

While I’d like to think “never attribute to malice what can be explained by simple incompetence“, surely they know about this, and the fact that they never go back and correct SOTC claims (which drive all the news stories) suggests some possible malfeasance. If this happens like this in CONUS, it would seem it happens in Global Tavg also, though I don’t have supporting data at the moment.

Finally, here is where it gets really, really, wonky. Remember earlier when I showed that by the claims in the July 2012 SOTC report the new data showed July 2012 was no longer hotter than July 1936? Here’s the SOTC again.


Note the July 1936 words are a link, and they go to the NCDC climate database plotter output again. Note the data for July 1936 I’ve highlighted in yellow:



July 1936 from the NCDC database says 76.43°F Even it doesn’t match the July 2012 SOTC claim of 77.4°F for July 1936. That can’t be explained by some B91 forms late in the mail.

So what IS the correct temperature for July 2012? What is the correct temperature for July 1936? I have absolutely no idea, and it appears that the federal agency charged with knowing the temperature of the USA to a high degree of certainty doesn’t quite know either. Either the SOTC is wrong, or the NCDC database available to the public is wrong. For all I know they both could be wrong. On their web page, NCDC bills themselves as:


How can they be a “trusted authority” when it appears none of their numbers match and they change depending on what part of NCDC you look at?

It is mind-boggling that this national average temperature and ranking is presented to the public and to the press as factual information and claims each month in the SOTC, when in fact the numbers change later. I’m betting we’ll see those identical numbers for October and November 2012 in Table 1 change too, as more B91 forms come in from climate observers around the country.

The law on such reporting:

Wikipedia has an entry on the data quality act, to which NCDC is beholden. Here are parts of it:


The Data Quality Act (DQA) passed through the United States Congress in Section 515 of the Consolidated Appropriations Act, 2001 (Pub.L. 106-554). Because the Act was a two-sentence rider in a spending bill, it had no name given in the actual legislation. The Government Accountability Office calls it the Information Quality Act, while others call it the Data Quality Act.

The DQA directs the Office of Management and Budget (OMB) to issue government-wide guidelines that “provide policy and procedural guidance to Federal agencies for ensuring and maximizing the quality, objectivity, utility, and integrity of information (including statistical information) disseminated by Federal agencies”.

Sec. 515 (a) In General — The Director of the Office of Management and Budget shall, by not later than September 30, 2001, and with public and Federal agency involvement, issue guidelines under sections 3504(d)(1) and 3516 of title 44, United States Code, that provide policy and procedural guidance to Federal agencies for ensuring and maximizing the quality, objectivity, utility, and integrity of information (including statistical information) disseminated by Federal agencies in fulfillment of the purposes and provisions of chapter 35 of title 44, United States Code, commonly referred to as the Paperwork Reduction Act.


Here’s the final text of the DQA as reported in the Federal Register:

Based on my reading of it, with their SOTC reports that are based on preliminary data, and not corrected later, NCDC has violated these four key points:

In the guidelines, OMB defines ‘‘quality’’ as the encompassing term, of which ‘‘utility,’’ ‘‘objectivity,’’ and ‘‘integrity’’ are the constituents. ‘‘Utility’’ refers to the usefulness of the information to the intended users. ‘‘Objectivity’’ focuses on whether the disseminated information is being presented in an accurate, clear, complete, and unbiased manner, and as a matter of substance, is accurate, reliable, and unbiased. ‘‘Integrity’’ refers to security—the protection of information from unauthorized access or revision, to ensure that the information is not compromised through corruption or falsification. OMB modeled the definitions of ‘‘information,’’ ‘‘government information,’’ ‘‘information dissemination product,’’ and ‘‘dissemination’’ on the longstanding definitions of those terms in OMB Circular A–130, but tailored them to fit into the context of these guidelines.

I’ll leave it to Congress and other Federal watchdogs to determine if a DQA violation has in fact occurred on a systemic basis. For now, I’d like to see NCDC explain why two publicly available avenues for “official” temperature data don’t match. I’d also like to see them justify their claims in the next SOTC due out any day.

I’ll have much more in the next couple of days on this issue, be sure to watch for the second part.

UPDATE: 1/7/2013 10AMPST

Jim Sefton writes on 2013/01/07 at 9:51 am

I just went to the Contiguous U.S. Temperature July 1895-2012 link you put up and now none of the temperatures are the same as either of your screen shots. Almost every year is different.

2012 is now 76.92 & 1936 is now 76.41 ?

Just in case it was some rounding / math issue with Javascript, I checked the source code & then checked the page in both IE & Chrome… the data for the comma-delimited data is distinct and matches those of the plot. So, in the 2 days since your post it has changed yet again… for all years apparently?

That’s verified, see screencap below made at the same time as the update:


This begs the question, how can the temperatures of the past be changing?

Here’s comment delimited data for all months of July in the record:
























































































































For now, in case the SOTC reports should suddenly disappear or get changed without notice, I have all of those NCDC reports that form the basis of Table 1 archived below as PDF files.

State of the Climate _ National Overview _ October 2010

State of the Climate _ National Overview _ January 2011

State of the Climate _ National Overview _ February 2011

State of the Climate _ National Overview _ March 2011

State of the Climate _ National Overview _ April 2011

State of the Climate _ National Overview _ May 2011

State of the Climate _ National Overview _ June 2011

State of the Climate _ National Overview _ July 2011

State of the Climate _ National Overview _ August 2011

State of the Climate _ National Overview _ September 2011

State of the Climate _ National Overview _ October 2011

State of the Climate _ National Overview _ November 2011

State of the Climate _ National Overview _ December 2011

State of the Climate _ National Overview _ January 2012

State of the Climate _ National Overview _ February 2012

State of the Climate _ National Overview _ March 2012

State of the Climate _ National Overview _ April 2012

State of the Climate _ National Overview _ May 2012

State of the Climate _ National Overview _ June 2012

State of the Climate _ National Overview _ July 2012

State of the Climate _ National Overview _ August 2012

State of the Climate _ National Overview _ September 2012

State of the Climate _ National Overview _ October 2012

State of the Climate _ National Overview _ November 2012


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john robertson

Why do the math, when you know what answer you need?
Its the old joke about the accountants looking for a job.
And of course the new attitude of our bureaucrats, “what you want me to do my job? thats discrimination.”

Glenn Sliva

Garbage in Garbage out. Answers are worked backwards not by NASA or NCDC but the media.
It appears that the warmest ever turns out to be average. Bummer.
Additionally it appears we’re headed into a prolonged Arctic visit for Europe and North America. It would be nice to have this data updated quickly so that the media has to report it. Fat chance on that.
Thanks Anthony and keep the facts and circumstances coming.


Excellent detective work Anthony … again. How many bureaucrats are required to provide inconsistent information? Clearly a lot more than just the one unfunded person who can find a systematic error in the output they produce.


Anthony, Maybe you found the Janus set, not the Conus..

Alex Avery

Keep their incompetent/and/or/lying feet to the fire, Anthony! Bottom line: they’re playing fast and loose with these data, and our tax dollars!
A Avery

Now how the heck are they going to explain that?

The corruption in CAGW lies not in bad data, incomplete analyses or agenda-driven adjustment biases (I’d call these moral or ethical failures) but in the insistence that reported data, statements about conditions, are unequivocally correct, accurate and precise to a fine level. The corruption lies in the claim of certainty, of being above discussion, internal dissension and external reproach.


Very nice work. I have not run the numbers but the writing and thinking is very linear and easy to interpret. Nice work!
As to the numbers, I hope you have found the thread that will unwind Hansen and the others “data cooks” we have at NOAA, NASA and the NSIDC.

Later reports leading to cooling?
No that can’t be – they have corrected for all that stuff like location, heat islands etc.
Or so they claim.

Excellent work, as a mere humble reporter, Anthony. This is the kind of work the newspapers used to do, before they allowed themselves to become little more than rump swabs.
This sort of chaos in the sets of data seems to be increasing. I fear it is a symptomatic of a growing gap between fact and “policy.”
Once “policy-makers” stray from Truth, it is a bit like having one foot on a row boat and the other foot on the dock. The gap gets larger and larger, and they wind up all wet. If you are kind you can throw them a life line, but be careful not do get dragged down with them as they fall.

Frankly, I’m impressed that you found any information in the morass that is . I wasted much of the morning trying to find the biggest one day snowfalls at NWS sites around New England. I had seen them before and discovered somewhat to my surprise that Concord NH’s big storms area smaller than those in Boston, Worcester, Hartford, and even Providence.
I was trying to find that information again to give to a TV met at and failed. I did find data for 1981-2010 at a NWS site, but that database engine crashed after lunch when I decided to add Portland, Maine.
Grr. While the data I found doesn’t have the major storms from 1978 in southern New England, the pattern still held. Only in March did Concord have a bigger snowfall than the other locations. See . I’ll be adding more stuff to it tonight.
Of course, if that data is wrong, then I’ve wasted even more time!
Apologies for a mostly OT rant, I really hate visiting the NCDC web site.

Myron Mesecke

As Artie Johnson said on Laugh In.
“Very Interesting.”


One of the uncertainties that is neglected, IMHO, in weather data is what I call “database error.” This is distinct from instrumentation error, read error (parallax, electronic drift, dead batteries, etc.), representativeness error (e.g. surface stations dot org and/or UHI), systematic error, and homogenization error (such as time of observation error (TOBS) and station moves). Database error would include transmission error, transcription error (i.e. data input of written reports), wrong station IDs, data lag (this case) and the data version of the game telephone (where data changes as it works its way through transmission from station to country to world databases and archives). In this case, the issue is data lag, as different packets of data move through the various transmission and collation systems at different speeds. I would be surprised if there were any publications specifically regarding U.S. and world weather databases that attempted to calculate the magnitude of this uncertainty. There may be publications regarding this issue that have studied other large database systems.

Michael D Smith

I still think this one is amazing… Look at all the 2012 records compared to 1934!!!

Hmm, in an effort to be charitable, is it possible we’ve two different people calculating the “average” in a different manner?
In a more realistic notion, it think it’s likely this outfit, much like all the other climate tracking outfits I’ve experience with, probably don’t know their azz from a hole in the ground and simply spew their brand of jibberish without bothering to check for accuracy.

John West

Why am I not surprised?
Good catch Anthony, thanks.

Rick K

Anthony, I am always amazed by your ability to find these needles in the haystacks. Great work… and I am looking forward to updates from you as this progresses. Maybe there’s a “reasonable” explanation, but at the moment I’m… “skeptical.”


I do believe they are trying to con us.


From the outside looking in, it is hard for me to know if this is a little thing that can be easily fixed, or the biggest fraud since (enter your favorite scandal here).
It so happens I am about a third into Senator Inhofe’s book “The Greatest Hoax”. In the book, he details numerous instances of “mis-representation” of data. Anthony, if this is a big deal, is it something Inhofe should be made aware of?

Kevin Kilty

Mod: A few typos here that ought to be corrected….
“highlighted in blue. that is a link” –> blue. That
“plotter output, the value is list as” –> the value is listed as
“in cases like this station, the observer send the ” –> observer sends
“though don’t have supporting data at the moment.” –> though I don’t
“that the agency charged with know to ” –> charged with knowing
“I’d alos like to see them” —> also
[working on it. Thanks, mod]

The “Rate This” scale only gave me 5 stars to pick from. Not nearly enough relative to other “top” posts. Great work, A.

John in NZ

Well spotted.
Small error. You have written “alos” instead of “also”
[Fixed, thanks. — mod.]


Anthony: You wrote: “Continental United States (CONUS)”
But CONUS means “contiguous US”–i.e., the lower 48 states, excluding Alaska. “Continental US” includes Alaska. Could it be that NOAA isn’t being clear, or has confused itself, about these two measures?
(I’ve made a couple of comments on this distinction in past years here, in response to other commenters.)

I’ve always heard it the other way. Either description gets the point across – Anthony

old construction worker

Where’s Waldo


PS: I wouldn’t put it past NOAA to use the warmer of the two measures (contiguous US or continental US) to affect public opinion when it issues its press releases.

Great work Sir, thank you very much.

chris y

NOAA Top Ten Excuse List.
These 0.7 degree errors:
1. are small and can be ignored.
2. are small compared with the all-time temperature record being broken by 0.1 F.
3. are expected, as they are within the error bounds of our world-class temperature measurement network.
4. have been caused by some Koch-funded denier hacking into our computers.
5. are irrelevant to the global trend, since the U.S. is only a few percent of the global surface area.
6. will be re-processed and re-adjusted on an annual basis going forward.
7. are worse than we thought.
8. are exactly the sorts of extreme events that result from CO2 emissions.
9. result from a careful balance between being effective and being honest.
10. are specious nonsense from the oil-funded network of climate denier flat-earthers.

bruce ryan

I’m of the opinion that historical temp records were recorded by individuals with better things to do and took the data with a grain of salt. If they needed to be in another county they took the reading when they could and either extrapolated or entered the data as it was.
Today we are still humans prone to diversions and intrigue. After all in the scheme of things how important is a number on a sheet of paper, if a six was a nine I don’t mind.


rogerknights says:
January 6, 2013 at 7:30 pm
Anthony: You wrote: “Continental United States (CONUS)”
But CONUS means “contiguous US”–i.e., the lower 48 states, excluding Alaska. “Continental US” includes Alaska. Could it be that NOAA isn’t being clear, or has confused itself, about these two measures?
(I’ve made a couple of comments on this distinction in past years here, in response to other commenters.)

REPLY: I’ve always heard it the other way.

ell, you heard wrong. “Contiguous” means “adjacent.” Alaska isn’t an adjacent state.

Either description gets the point across – Anthony

Not at all–see above. (“Continental” means “in North America” and thus includes Alaska.)

REPLY: Since NCDC says “contiguous” on their plotter page, I’ve updated the text to reflect that for consistency, thanks – A


I think you miss rogerknights’ point that maybe different parts of NOAA have different meanings for CONUS, thus that may be why the temps are different.
You can see that NOAA does appear to be confused, in their glossary they say: “CONUS – Contnental U.S.”
But this page: “Graphical Forecasts – CONUS Area” shows a map of the contiguous US.

D Böehm Stealey

CONUS can mean either:
When I was in the military, CONUS specifically meant the continental U.S.


Someone must have noticed the flipping down of the figure when the paper records were interpolated (by up to 1.1F which is huge in the light of the decadal trend claims).
What’s more, although I wouldn’t put it past them to copycat the Met Office with their press-scare-statements-that-defy-the-data, it really is questionable to be furnishing the entire economy, agricultural, industrial and commercial with junk data (i.e. to every last person in the land who just wants the right data to help haul us out of a recession. But that’s the consequence of spinning to the press.

Mr. Watts’ find would be incriminating if any accountability would exist in our government.
As there’s none, they will take obamacare of it.
Mr Watts, please see to it that your tea does not contain any transuranic elements.

James Sexton says:
January 6, 2013 at 6:59 pm
Hmm, in an effort to be charitable, is it possible we’ve two different people calculating the “average” in a different manner?

There is only one way to calculate an average. But you may be right and someone has made a simple arithmetic error. Easily done in computer code that isn’t thoroughly tested. And I doubt any of the climate agencies test their code properly, and I am sure the climate models, etc. are riddled with errors.
I’ll put money on NOAA blaming a software problem.
BTW, there are no software problems. Only, failures to test properly.


Looking into it more, it seems that CONUS is usually defined as the “continental US” (e..g DoD and NOAA) and does exclude Alaska. Thus there should be no confusion by NOAA (apart from they can’t spell continental 🙂


A joke comes to mind: Three people are vying for an executive position. An engineer, a marketer and a lawyer. There’s one last interview by the CEO.
One question: “What is 2 plus 2?”
The engineer states that while untrained people would say 4, in real life these numbers would have noise, distributions and ranges, not simple integers, so the answer is 4 plus or minus the range on each number. “Very precise” the CEO says.
The marketer states that mere linear thinkers would say 4, but that more creative types would consider 22 to be just as valid. “Very insightful” says the CEO.
The lawyer enters, closes the door and curtains, unplugs the phone and intercom, turns on a radio loudly, approaches the CEO and says quietly “What do you NEED it to be?”
The marketer and the engineer were not called back.


Lies, damn lies, and climate “science”.
Don’t ask me why this popped into my head, but when I read Anthony’s post, I immediately thought that some NOAA employee playing “Foggy Mountain Breakdown” on a banjo could help deflect attention from this issue… much like Steve Martin suggested that Richard Nixon should have done nearly 40 years ago


January 6, 2013 at 6:31 pm | Glenn Sliva says:
Garbage in Garbage out. Answers are worked backwards not by NASA or NCDC but the media.
This is subject to the well known GIGO forcing, so GI = GO^3

Bill Jamison

I compared charted the 60 month period ending Nov 2012 and was a little surprised to see it listed as the 11th warmest! In other words, not particularly noteworthy last few years.

Heads are going to roll this time Anthony you maniac. Good Job, get some well deserved rest, you deserve it.

Policy Guy

Yet again you deserve a clap on the back for great work.
Im not surprised that you found this data inconsistency. The people who mined this data for their own purposes knew what they were doing, but never expected the ignorant skeptical public to find and understand their manipulation. You did it and Cudos to you!
Unless a particular person of Congress, with considerable standing, picks up on his issue I fear it will die on the vine. However, if someone in the Budget realm, begins a formal inquirey, there could be traction. Particularly if expenditures for wind/solar power etc. are challenged against measured data.


If I didn’t know better I would think James Hansen worked on these reports. Of course we know he doesn’t. Right?


i bet you’re right…contiguous, continental vs. US average as a likely source of confusion. Or different groups using different data, and no one has bothered to check or compare reports, data and graphs….?
Good catch, Anthony. impressive


thisisnotgoodtogo says: January 6, 2013 at 6:40 pm
Anthony, Maybe you found the Janus set, not the Conus..
ha ha – can’t let this one go by unremarked: Janus, the two faced Roman God

Re: Saving NCDC pages as PDFs (good idea) and @Ric Werme comment at 6:50pm regarding NCDC pages: I find the NOAA / NCDC websites very frustrating in terms of links to information constantly disappearing – I find interesting data / information and then soon after it’s gone…. it would be nice if they were more organized (or maybe they are – organized to disappear information that doesn’t meet the consensus AGW view and to prevent a systematic review.)

Doug Hilliard

Very impressive Anthony; thanks so much for all your great work!


LearDog says:
January 6, 2013 at 8:55 pm
i bet you’re right…contiguous, continental vs. US average as a likely source of confusion. Or different groups using different data, and no one has bothered to check or compare reports, data and graphs….?

I think this is the likely source of the mixup, somewhere along the line. (Or maybe only SOME of the mixup?) It would be like the mixup on that Mars mission between metric and Imperial units.

This is a great discovery. Is this related to the systematic ‘adjustment, homogenisation and other adjustments to the climate record? Keeping two sets of books is standard practice in criminal organisations which are intent on defrauding the public, the tax-office and the government. It all begins to make real sense, very slowly.

John F. Hultquist

Well done.
I wonder if the NCDC computer storage devices have something like a HARRY_READ_ME.txt file hidden in a deep mountain vault?
Some might need a ref.:
Reading your investigation that’s what came to mind. Well, the contiguous versus continental aspect made me think of Alaskan statehood (1/3/59) but that shouldn’t involve this recent data.