Correcting and Calculating the Size of Adjustments in the USHCN
By Anthony Watts and Zeke Hausfather
A recent WUWT post included a figure which showed the difference between raw and fully adjusted data in the United States Historical Climatology Network (USHCN). The figure, used in that WUWT post was from from Steven Goddard’s website, and in addition to the delta from adjustments over the last century, included a large spike of over 1 degree F for the first three months of 2014. That spike struck some as unrealistic, but knowing that a lot of adjustment goes into producing the final temperature record, some weren’t surprised at all. This essay is about finding the true reason behind that spike.
One commenter on that WUWT thread, Chip Knappenberger, said he didn’t see anything amiss when plotting the same data in other ways, and wondered in an email to Anthony Watts if the spike was real or not.
Anthony replied to Knappenberger via email that he thought it was related to late data reporting, and later repeated the same comment in an email to Zeke Hausfather, while simultaneously posting it to Nick Stokes blog, who had also been looking into the spike.
This spike at the end may be related to the “late data” problem we see with GHCN/GISS and NCDC’s “state of the climate” reports. They publish the numbers ahead of dataset completeness, and they have warmer values, because I’m betting a lot of the rural stations come in later, by mail, rather than the weathercoder touch tone entries. Lot of older observers in USHCN, and I’ve met dozens. They don’t like the weathercoder touch-tone entry because they say it is easy to make mistakes.
And, having tried it myself a couple of times, and being a young agile whippersnapper, I screw it up too.
The USHCN data seems to show completed data where there is no corresponding raw monthly station data (since it isn’t in yet) which may be generated by infilling/processing….resulting in that spike. Or it could be a bug in Goddard’s coding of some sorts. I just don’t see it since I have the code. I’ve given it to Zeke to see what he makes of it.
Yes the USHCN 1 and USHCN 2.5 have different processes, resulting in different offsets. The one thing common to all of it though is that it cools the past, and many people don’t see that as a justifiable or even an honest adjustment.
It may shrink as monthly values come in.
Watts had asked Goddard for his code to reproduce that plot, and he kindly provided it. It consists of a C++ program to ingest the USHCN raw and finalized data and average it to create annual values, plus an Excel spreadsheet to compare the two resultant data sets. Upon first inspection, Watts couldn’t see anything obviously wrong with it, nor could Knappenberger. Watts also shared the code with Hausfather.
After Watts sent the email to him regarding the late reporting issue, Hausfather investigated that idea, and ran some different tests and created plots which demonstrate how the spike was created due to that late reporting problem. Stokes came to the same conclusion after Watts’ comment on his blog.
Hausfather, in the email exchange with Watts on the reporting issue wrote:
Goddard appears just to average all the stations readings for each year in each dataset, which will cause issues since you aren’t converting things into anomalies or doing any sort of gridding/spatial weighting. I suspect the remaining difference between his results and those of Nick/myself are due to that. Not using anomalies would also explain the spike, as some stations not reporting could significantly skew absolute temps because of baseline differences due to elevation, etc.”
From that discussion came the idea to do this joint essay.
To figure out the best way to estimate the effect of adjustments, we look at four difference methods:
1. The All Absolute Approach – Taking absolute temperatures from all USHCN stations, averaging them for each year for raw and adjusted series, and taking the difference for each year (the method Steven Goddard used).
2. The Common Absolute Approach – Same as the all absolute approach, but discarding any station-months where either raw and adjusted series are missing.
3. The All Gridded Anomaly Approach – Converting absolute temperatures into anomalies relative to a 1961-1990 baseline period, gridding the stations in 2.5×3.5 lat/lon grid cells, applying a land mask, averaging the anomalies for each grid cell for each month, calculating the average temperature for the whole continuous U.S. by a size-weighted average of all gridcells for each month, averaging monthly values by year, and taking the difference each year for resulting raw and adjusted series.
4. The Common Gridded Anomaly Approach – Same as the all-gridded anomaly approach but discarding any station-months where either raw and adjusted series are missing.
The results of each approach are shown in the figure below, note the spike has been reproduced using method #1 “All Absolutes”:
The latter three approaches all find fairly similar results; the third method (The All Gridded Anomaly Approach) probably best reflects the difference in “official” raw and adjusted records, as it replicates the method NCDC uses in generating the official U.S. temperatures (via anomalies and gridding) and includes the effect of infilling.
The All Absolute Approach used by Goddard gives a somewhat biased impression of what is actually happening, as using absolute temperatures when raw and adjusted series don’t have the same stations reporting each month will introduce errors due to differing station temperatures (caused by elevation and similar factors). Using anomalies avoids this issue by looking at the difference from the mean for each station, rather than the absolute temperature. This is the same reason why we use anomalies rather than absolutes in creating regional temperature records, as anomalies deal with changing station composition.
The figure shown above also incorrectly deals with data from 2014. Because it is treating the first four months of 2014 as complete data for the entire year, it gives them more weight than other months, and risks exaggerating the effect of incomplete reporting or any seasonal cycle in the adjustments. We can correct this problem by showing lagging 12-month averages rather than yearly values, as shown in the figure below. When we look at the data this way, the large spike in 2014 shown in the All Absolute Approach is much smaller.
There is still a small spike in the last few months, likely due to incomplete reporting in April 2014, but its much smaller than in the annual chart.
While Goddard’s code and plot produced a mathematically correct result, the procedure he chose (#1 The All Absolute Approach) comparing absolute raw USHCN data and absolute finalized USHCN data, was not, and it allowed non-climatic differences between the two datasets, likely caused by missing data (late reports) to create the spike artifact in the first four months of 2014 and somewhat overstated the difference between adjusted and raw temperatures by using absolute temperatures rather than anomalies.
Discover more from Watts Up With That?
Subscribe to get the latest posts sent to your email.
According to all 4 described methods the temperatures measured in the USA in the year 2014 have to be adjusted 0.1°C or more up!?
A C Osborn says: May 11, 2014 at 2:42 am
“The MMTS thermometers should have been calibrated to the Glass/Mercury ones, not used to thorw a hundred years of readings in the bin.”
The readings are not in the bin. They are online an Steven Goddard posted them. It’s not a calibration issue, the actual readings are not disputed. The question is whether a warm afternoon has been counted twice because of TOB. That is a bias and needs correction. It is wrong not to correct.
Try Mosh’s experiment.
Station move adjustments should be 50% up and 50% down. Not 99% down (in terms of the past record).
MMTS sensor should be a single small adjustment in 1984 to 2000 – not one that seems to new number every month right through the record from 1895 to July 2014 (July’s change is already programmed it seems).
TOBs – I’m tired of hearing about this. The weather bureau was issuing directives regarding proper recording times for TOBs in 1871 already. You think the observers in 1870 or 1934 or 2014 do not know that the time of day affects the reading.
BEST station chopping – there should be just as many station cuts when there is a increase in temperatures as there are when then there is a drop. BEST adjusts out all the drops but leaves all the increases in. Prove me wrong Mosher. I’ve asked for this info going on a dozen times now and it is not reported anywhere.
These are merely “justifications” to adjust the temperature record. It does not mean that the adjustments were implemented properly.
In fact, the systematic nature of the adjustment through time is all the proof one needs that this is done to merely increase the trend.
Why is there a systematic adjustment over the whole record? There was a smooth systematic impact from all these changes – bollocks, it should be variable over the record.
Why does it change every month? [I get an email of the changes every month in GISS temperatures (from the changes at the NCDC) – literally half the monthly record changes every month, sometimes 3 or 4 times every month).
Here is a ScreenCap of what got changed in advance of the April temperature report. Yellow and strikeout are the changes.
http://s15.postimg.org/lc6oo9gl7/GISS_adjustment_april14.png
It is interesting to see that the discussion keeps referring to calibration of sensors.
I note from a link earlier in this thread http://wattsupwiththat.com/2010/01/12/how-the-uah-global-temperatures-are-produced/ about satellite sensors.
It seems strange that satellites are orbiting without any external calibration standards or methods.
It seems as though they rely upon PT100s being averaged to determine the ‘hot’ body temperature.
All well and good, but how are the PT100s calibrated and how often?
It appears as though each satellite is ‘adjusted’ by using the results of a previous satellite.
By ‘flying’ over a certain spot within a few minutes of each other, the drift in one is ‘adjusted’ to match that of the other.
That seems to be a bit incestuous to me.
I know of no use of PT100s where you can allow operation without regular calibration to a traceable, higher standard.
The email between Wrigley and Jones explains the scientific methods used to deal with unsavory blips:
Phil,
Here are some speculations on correcting SSTs to partly explain the 1940s warming blip.
If you look at the attached plot you will see that the land also shows the 1940s blip (as I’m sure you know). So, if we could reduce the ocean blip by, say, 0.15 degC, then this would be significant for the global mean — but we’d still have to explain the land blip.
I’ve chosen 0.15 here deliberately. This still leaves an ocean blip, and i think one needs to have some form of ocean blip to explain the land blip (via either some common forcing, or ocean forcing land, or vice versa, or all of these). When you look at other blips, the land blips are 1.5 to 2 times (roughly) the ocean blips — higher sensitivity plus thermal inertia effects. My 0.15 adjustment leaves things consistent with this, so you can see where I am coming from.
Removing ENSO does not affect this. It would be good to remove at least part of the 1940s blip,
but we are still left with “why the blip”.
Let me go further. If you look at NH vs SH and the aerosol effect (qualitatively or with MAGICC) then with a reduced ocean blip we get continuous warming in the SH, and a cooling in the NH — just as one would expect with mainly NH aerosols.
The other interesting thing is (as Foukal et al. note — from MAGICC) that the 1910-40 warming cannot be solar. The Sun can get at most 10% of this with Wang et al solar, less with Foukal solar. So this may well be NADW, as Sarah and I noted in 1987 (and also Schlesinger later). A reduced SST blip in the 1940s makes the 1910-40 warming larger than the SH (which it currently is not) — but not really enough. So … why was the SH so cold around 1910? Another SST problem? (SH/NH data also attached.)
This stuff is in a report I am writing for EPRI, so I’d appreciate any comments you (and Ben) might have.
Tom
Well nick,
Point taken about us vs global, I would like to debate the 2012 vs 1930’s with you but unfortunately NCDC has been taken off line for the last few days… not sure if its coming back. One easy way to hide the adjustments is to take the data away from the citizenry. You can get annual info for the globe from cimate.gov but not us raw or even adjusted data right now. I do find this somewhat disturbing that a government server would be offline for this long. Anyone have any insight into this?
v/r,
David Riser
David Riser says” One easy way to hide the adjustments is to take the data away from the citizenry. You can get annual info for the globe from cimate.gov but not us raw or even adjusted data right now.”
I agree that is a problem that seems to be politically driven. Give USHCN credit for making both raw and adjusted data accessible as well as maximum and minimums. If NOAA truly wanted the public to be able to examine the data they would provide easy links to max, min, raw, quality controlled but not homogenized, and homogenized. The data is available for those who tenaciously hunt for it. It should be readily available.
jim Steele (May 11, 2014 at 7:38 am) “If NOAA truly wanted the public to be able to examine the data they would provide easy links to max, min, raw, quality controlled but not homogenized, and homogenized.”
If they truly wanted the public to examine their data *and methods*, they would allow the public to run their code after filtering out obvious crap stations like Norfolk Virginia. But if they really cared about a quality product they would have filtered them out themselves a long time ago. I for one am not interested in developing and running GIGO algorithms.
Does it strike anyone else as ironic that “the science is settled” but the temperature record on which “the science” is based, is constantly adjusted?
Perhaps ironic is the wrong word…Moronic is much better.
James Hall (NM) says:
May 10, 2014 at 6:32 pm
+1 James Hall. Thank you. Informative.
So to summarize, irrespective of which method do we use, Goddard’s, or Watts’, the magnitude of the upward adjustment from 1960 onwards is roughly equal to the “trend” reported?
And Antony finds appropriate to obsess over Goddard’s completely insignificant and irrelevant “mistake”, instead over ‘upjustments’ equal to the trend…
Historical temperature data base has not been shown to be credible, given the magnitude of data adjustments and the potential for these to include biased or selective assumptions that yield incorrect data for comparative purposes.
The climate science profession needs to understand and acknowledge that they have major credibility issues on their hands. “Just trust us, we are scientists” is NOT going to work. They have tried this for a decade now and the public is understandably in my opinion either skeptical as to the reliability of trustworthiness of the data upon which the climate models have been based or apathetic to the entire matter; Particularly in light of the 17+ recent years of relatively little change.
If climate change is as real of a threat and if the magnitude of change is as significant as they project, then they had better reassess their approach, open up the data, invite scientific criticism, accept whatever short-term blows to credibility that might occur for past mistakes and cover ups. Stop treating their profession as if it were some subset of political social science and restore faith and credibility in its legitimacy as a hard science; something that at the moment, fewer and fewer believe to be the case.
As just as example, yesterday on Reddit, there were 2 “ask me anything” posts from climate change experts. First of all, many of the questions asked had the appearance of having been prepared in advance by the climate scientists or their associates (they were simply too packaged, well-written and focused on their narrative to have been asked randomly by members of the general public. But more telling, the level of interest by the public (and Reddit is global btw) was extremely limited. Their posts left the front pages quickly and faded into obscurity in just a few short hours.
They have been fighting battles, public relations battles, using politically-based strategies, and they are losing. They not understand that the general public can smell when it’s political from miles away and have demonstrated a considerable distaste when it is force fed upon them.
They need to understand that they are scientists, and as such, they make for really inept politicians. The subject at hand is not one that lends itself to politically-based solutions, except with the progressive left who will always be 100% supportive since they view the entire climate change matter as one of their justifications for a much broader social agenda. But less than 1 in 5 people consider themselves to be progressive liberals.
The far larger body of moderates and independents need to be convinced if there is to be any hope of taking action on climate change and they are not going to buy off on the “trust us” approaches that have been employed to date.
They especially are not going to buy off once they understand that the historical record has been significantly manipulated (corrected, adjusted, whatever) because of “faulty thermometers?”, TOBS, gradient infills, etc etc etc. The cat is out of the bag on this, thanks to Anthony Watts, Steven Goddard et al and eventually, someone in the MSM – most likely beginning with a couple of the British newspapers, will eventually begin to question why this is so.
Once they have to start explaining in the defense, they have lost the argument. In my opinion, the climate science community has a major FUBAR on their hands, they have an lot of explaining to do and they had better lead in this matter. They have dug themselves into a deep hole, yet they keep on digging and they will likely continue to do so until they are called out, as the alternatives will be seen as just too painful.
I have personally been trying for years to understand if global warming is going to be as severe and if the ramifications are going to be as disruptive as are being forecast. I honestly want to know the truth. I know no more what the truth is today than I did say 5 years ago and I have less confidence in the science today than I did back then. What you guys are doing isn’t working. You had better work very hard in building credibility because you are not going to succeed politically. Look at the political change in Australia. This is going to happen elsewhere unless you change your approach.
Ima, absolutely spot on! I am not a scientist, just a retired “pleb” tax-payer. I have been following this “story” for a number of years now wanting to know the truth (I know, I know!). All that has happened is my long-standing respect for the scientific community has taken a very large nosedive. (I would also mention I have been interested in the nutrition and dietary science as well and the similarities are quite remarkable). I’m afraid if a “climate scientist” told me today is Sunday I’d spend an awful long time checking if that was so – and that really is the sad aspect of all this shenanigans.
Wow I just saw Kutsoyanis’s analysis of RAW vs Adjusted globally. He used 163 stations worldwide and found that the RAW trend is 0.42 C instead of 0.76 C adjusted!!!
http://itia.ntua.gr/getfile/1212/1/documents/2012EGU_homogenization_1.pdf
Essentially, what Zeke Hausfather is saying is that Prof Richard Lindzen is wrong when he writes:
Inevitably in climate science, when data conflicts with models, a small coterie of scientists can be counted upon to modify the data. Thus, Santer, et al (2008), argue that stretching uncertainties in observations and models might marginally eliminate the inconsistency. That the data should always need correcting to agree with models is totally implausible and indicative of a certain corruption within the climate science community.
The entire discussion is preposterous when viewed with a rational perspective. Every wild-eyed prediction by the promoters of the global warming scare has been flat wrong. So now, it has devolved into nitpicking over tenths and hundreths of a degree, with those sounding the false alarm insisting that their bogus methodology must be accepted. As Lindzen says:
“Future generations will wonder in bemused amazement that the early 21st century’s developed world went into hysterical panic over a globally averaged temperature increase of a few tenths of a degree, and, on the basis of gross exaggerations of highly uncertain computer projections combined into implausible chains of inference, proceeded to contemplate a roll-back of the industrial age”
A few tenths of a degree fluctuation is well within normal parameters; in the past, global temperatures have changed by tens of degrees, within decades. But the current drum-beating is over a minuscule ≈0.6º change — over a century and a half! Those promoting the carbon scare should be ashamed of their ridiculous, unscientific and emotional scaremongering. It is self-serving nonsense.
I call on Zeke Hausfather to admit that the climate Null Hypothesis has never been falsified, and thus, that nothing either unusual or unprecedented is happening viz-a-viz “global warming”.
Admit it, Zeke. Because that is a fact. Isn’t it?
At the closed door meeting: “Dammit, we have to show what we WANT and BELIEVE the data should be…”
johnbuk – Thanks for the comments. I agree with you observations. In the past few years I have become increasingly jaded with respect to the lack of honesty and integrity in nearly every institution. I spent 30 years around politics and worked for 2 governors. I noticed attitudes and values beginning to change in the early 2000s and they seem to have gotten progressively (pun?) worse. Don’t know if it’s because I am getting older, the internet is exposing us to more of what has happened behind the scenes in the past, or if it is truly getting worse. Sadly I believe it is the latter.
dbstealey, as long as we’re quoting Richard Lindzen about this issue, it might be worthwhile to hear what he had to say to the British House of Commons Energy and Climate Change Committee in January when they were holding hearings about the IPCC AR5 report. Lindzen confirmed what a lot of us have suspected for a long time (at least since November 2009) about many of those who have gone into the “climate science” field (his comments justify the scare quotes, IMO). The video should start playing at the 2:49:14 mark (if it doesn’t, drag the playhead to that point). Watch for about 3 minutes:
Watch the whole thing (3 hours 8 minutes) starting from the beginning if you have a strong stomach.
Lynn,
Brilliant!
v/r,
David Riser
Nick writes “The question is whether a warm afternoon has been counted twice because of TOB.”
Or indeed a cold morning counted twice for the same reason. The need for TOBs is justifiable but the fact its a large positive adjustment spread over such a long time has always made me more than a little sceptical.
Do we make the adjustments based on individual readings? Afterall if consecutive min/max readings are different then there is no need for the adjustment as they cant be effected.
Also I can see policy changes may change when readings are taken (ie 7am vs 9pm for example) but are the adjustments always based on actual reading time data? Or on what policy says should have been the reading time in the absense of reading time data?
And human nature would have some readings at “not the right time” for whatever reason (habit, sort the mail first, whatever) but not necessarily written down accurately because there is an expectation they should follow procedure but why give anyone reason to question them? What is the harm if they read at 11am rather than 7am like they were meant to?
TOBs is always going to be somewhat hit or miss and errors will definitely be introduced against the adjusted readings as a result.
TimTheToolMan says: May 11, 2014 at 9:04 pm
“Do we make the adjustments based on individual readings? After all if consecutive min/max readings are different then there is no need for the adjustment as they cant be effected.”
No, you can’t tell that way. Suppose a warm Monday afternoon, peaks at 4pm. The 5pm reading will say that 4pm is max for Monday, but the 5pm will be max for Tuesday.
“are the adjustments always based on actual reading time data?”
They are based on the agreed reading time. The observer can request a change; that’s what triggers the adjustment. But they have another check. The observer reports the temperature at the time of reading (not the time). That’s usually alrady good enough to tell am from pm. But with thousands of readings, there’s a very good estimate of compliance.
“What is the harm if they read at 11am rather than 7am like they were meant to?”
Suppose it’s a very cold morning, min 6am, so 7am will be recorded as the min for the next day. The later he reads, the higher will be that min, with no balancing effect.
Nick writes “No, you can’t tell that way. Suppose a warm Monday afternoon, peaks at 4pm. The 5pm reading will say that 4pm is max for Monday, but the 5pm will be max for Tuesday.”
True. A lower temperature at the time of reading can still be greater than the next day’s temperature. So we would have had to record min, max and current to overcome that.
But Nick writes “They are based on the agreed reading time.”
I have a big problem with that. Suppose someone took the reading at the right time on weekdays but later (or earlier) on the weekends. Or they were pretty random about it. Then that would throw the adjustment out considerably.
Nick answers ““What is the harm if they read at 11am rather than 7am like they were meant to?””
That was probably written badly since you misunderstood. I was writing that from the point of view of a person who was meant to read the temperature at a certain time and rather than having to explain to their boss why they were late reading the temperature they could easily write down the agreed time as a bit of a “white lie”.
TimTheToolMan says: May 12, 2014 at 12:49 am
“So we would have had to record min, max and current to overcome that.”
In fact they did. But it still doesn’t pin it down. If the max next day is a bit higher than that current, it doesn’t mean it didn’t happen a few minutes later.
“Or they were pretty random about it.”
They could write down random temperatures too. But these are Coop volunteers. They go to a lot of trouble to contribute. There’s no point in doing that haphazardly.
Bill Illis says:
May 11, 2014 at 5:29 am
TOBs – I’m tired of hearing about this. The weather bureau was issuing directives regarding proper recording times for TOBs in 1871 already. You think the observers in 1870 or 1934 or 2014 do not know that the time of day affects the reading.
And I’m tired of reading nonsense such as this! We know when the coop stations recorded their data from their records! So despite the directives we know the coop stations didn’t follow them, and that the TOBS changed over time, the effect of it was analyzed and a correction formula determined from that analysis so that the changes in practice over time could be corrected for. Whether the observers in 1934 knew that time of day effected the readings doesn’t matter because the fact is that they mostly weren’t going out to read the thermometers at midnight!
Nick writes “If the max next day is a bit higher than that current, it doesn’t mean it didn’t happen a few minutes later.”
Also true but then it becomes a bias in the other direction because you throw away the higher temperature on the first day in favour of making the temperature on the second day more “realistically” lower. You cant win.
Nick writes “They could write down random temperatures too. But these are Coop volunteers. They go to a lot of trouble to contribute. There’s no point in doing that haphazardly.”
Human nature is what it is. I’m sure more than a few “readings” were guessed from missed days for various reasons. A couple of days a week of readings at a convenient time rather than the agreed time would have significant impact too.