In honor of Google’s latest diversity kerfuffle, I continue with my diversity initiative on WUWT with a guest post by Nick Stokes.~ctm
By Nick Stokes,
There is an often expressed belief at WUWT that temperature data is manipulated or fabricated by the providers. This persists despite the fact that, for example, the 2015 GWPF investigation went nowhere, and the earlier BEST investigation ended up complementing the main data sources. In this post, I would like to walk through the process whereby, in Australia, the raw station data is immediately posted on line, then aggregated by month, submitted via CLIMAT forms to WMO, then transferred to the GHCN monthly unadjusted global dataset. This can then be used directly in computing a global anomaly average. The main providers insert a homogenization step, the merits of which I don’t propose to canvass here. The essential points that you can compute the average without that step, and the results are little different.
The accusations of data corruption got a workout with the recent kerfuffle over a low temperature reading on a very cold morning at Goulburn, NSW in July, so I’ll start with the Bureau of Meteorology online automatic weather station data. I counted recently a total of 712 such stations, for which data is posted online every half hour, within ten minutes of being measured. You can find the data by states – here is NSW. You can find other states from the bar at the top, under “latest observations”. Here is a map of the stations in NSW in this table:
For context, I have marked with green the stations of Goulburn and Thredbo top which had temperatures of below -10C flagged on that very cold morning in July. On that BoM table, you can see stations listed like this (switching now to Victoria):
I switched because I am now following a post from Moyhu here, and I want a GHCN station which I could follow through. But it is the same format for all stations. This data is from 4 December 2016, and I have highlighted in green the min/max data that will flow through (unchanged except for possible quality control flagging) to GHCN unadjusted. It shows for Melbourne Airport, the most recent temperature (22.4) at 7pm, various other data, and then the min and max, along with time recorded. The min is incomplete; it showed the latest 7pm temperature, but would no doubt be lower by 9am the next day, which is the cut-off. The max probably wouldn’t change. You can see the headings by linking to the page here.
If you click on the station name, it brings up a full table of the half-hourly readings for the last three days, in this style:
Apologies for jumping forward to now (7 Aug), but I didn’t record this back in December. It shows the headings relevant to the above too; the top line is present (a few minutes ago), going back. Now you can see that this has to be automated; no-one is hovering over this stream of data with an eraser. If you click on the “Recent months”, it brings up the following table (an extract here, and we’re back in Dec 2016):
That was taken at the same time (just after 7pm, 4 Dec), and you’ll see that it shows the minimum attributed to Sunday 4th (before 9am), at 9.1, but not yet the max. If you look below that table you’ll see a list of the last 13 months linked, for which you can bring up the complete table. Here is what that Dec 2016 table now looks like:
…
The max of 31.7 is there; the min went down to 15.7. The other data hasn’t changed. Further down on that page, as it appears now, are the summary statistics for the month:
At the end of Dec 2016, that was transmitted to the WMO as a CLIMAT form, which you can see summarized at the Ogimet site
…
You can see that the min and max are transmitted unchanged. The mean of the two has also been calculated and is marked in brown. If you want further authenticity, that site will show you the code that the met office transmitted.
Finally, the CLIMAT form is transcribed into the GHCN unadjusted file, which you can see here. It’s a big file, and you have to gunzip and untar. You can also get a file for max and min. Then you have a text file, which, if you search for 501948660002016TAVG (which includes the Melb code) you see this line:
There is the 19.5 (multiplied by 100, as GHCN does). The other numbers will appear in the GHCN TMAX and TMIN files.
You can even go through to the adjusted file, and, guess, what, it is still unchanged. That is because homogenization rarely modifies recent data. But older data may be. GHCN unadjusted does not change, except if the source notifies an error. There are quality controls, which don’t change numbers, but may flag them.
There have been endless articles at WUWT about individual site adjustments, but no-one has tried to calculate the whole picture of the effect of adjustment. With the unadjusted vs adjusted files, it is possible to do that. I have been calculating a global anomaly every month, using the unadjusted GHCN data with ERSST. The June result is here; there is an overview page here, with links to the methods and code. This post compares the result of unadjusted vs adjusted GHCN; the difference is small. Here from it is a plot from 1900 to start 2015 showing TempLS (my program) unadjusted (blue) vs adjusted (green) and GISS (brown), 12 month running man. It’s an active plot, so you can see more details at the linked site.
If you want more convenient access to the station data, I have a portal page here. The heading line looks like this:
The BoM AWS link takes you to this page, listing all station names with links to their current month data page. BoM also posts the metadata for all their stations, and that link takes you to this page, which lists all stations (not just AWS, and including closed stations) with links to metadata. The GHCN Stations button links to this page, which links to the NOAA summary page for each GHCN station by name, or if you click the radio buttons, to station annual data in various formats.
Summary
I have shown, for Australia (BoM) at least, that you can follow the unadjusted temperature data right through from within a few minutes of measurement to its incorporation into the global unadjusted GHCN, which is then homogenized for global averages. Of course, I can only show one example of how it goes through without change, but the path is there, and transparent. Those who are inclined to doubt should try to find cases where it is modified.
Nick, with respect, I do not think you have addressed the main argument here.
It is interested to see the data flow and the apparent ‘transparency’ however,
According to jo novas site, which has documented the BOM fiddlings;
The AWS screen shots showed -10, it then went to 0, it was then corrected to -10.4 which everyone agrees it should remain at -10.4 degrees C.
The big question is, who had write or edit access to the government database holding the real time data streamed in from the 712 stations?
Who was sat at a computer terminal, with the database query window open, so that they were in a position to perform an immediate edit?
Can any BOM data be considered safe or reliable, if ‘anyone’ ( and who did it is a big question) can edit any data they wish for any reason?
Is there an audit trail?
Is the original retained or lost in these multiple edits?
How often has someone had the edit/update screen open and what edits have been performed?
What other records have been edited over the years, why and how was it documented and justified?
Who ordered this edit?
Or was it a standing order – with a list of stations to watch, just do a quick hand edit, no scripts, no evidence left to incriminate?
Nick, what you have documented above is interesting and good, but does not address the issue of who did it, why, how often and under whose orders.
BOM data can not now be formally trusted, therefore datasets that incorporate BOM data can not be trusted.
What other countries do this ‘under the counter’ editing I wonder?
Exactly, this isn’t the first time the BOM has been caught with their thumb on the scale.
From August 2014:
How accurate are our national climate datasets when some adjustments turn entire long stable records from cooling trends to warming ones (or visa versa)? Do the headlines of “hottest ever record” (reported to a tenth of a degree) mean much if thermometer data sometimes needs to be dramatically changed 60 years after being recorded?
One of the most extreme examples is a thermometer station in Amberley, Queensland where a cooling trend in minima of 1C per century has been homogenized and become a warming trend of 2.5C per century. This is a station at an airforce base that has no recorded move since 1941, nor had a change in instrumentation. It is a well-maintained site near a perimeter fence, yet the homogenisation process produces a remarkable transformation of the original records, and rather begs the question of how accurately we know Australian trends at all when the thermometers are seemingly so bad at recording the real temperature of an area. Ken Stewart was the first to notice this anomaly and many others when he compared the raw data to the new, adjusted ACORN data set. Jennifer Marohasy picked it up, and investigated it and 30 or so other stations. In Rutherglen in Victoria, a cooling trend of -0.35C became a warming trend of +1.73C. She raised her concerns (repeatedly) with Minister Greg Hunt.
—–
Why would anyone trust anything from the BOM? How many other changes have been made that have gone unnoticed?
Fool me once, shame on you. Fool me twice, shame on me.
“One of the most extreme examples is a thermometer station in Amberley, “
I showed here, by looking at nearby stations, how the adjustment at Amberley was absolutely required. You can pinpoint even the month of the discrepancy (August 1980) and the amount (-1.4C). I’ve never understood the beef with Rutherglen. The fact is that ACORN temperatures are adjusted. They make a big point of the fact. That means numbers change. It means trends change. And if you look through enough, you’ll find trends that change from negative to positive, possibly by quite a lot.
Nick, that’s a very interesting analysis and discussion you link to. The comments below your post by Dr Bill Johnston, posting as ‘Anonymous’, explain his very thorough analysis of the station data over a longer timescale and he comes to a different conclusion that is summarised in this comment (bold mine):
@ur momisugly Nick “I showed here, by looking at nearby stations, how the adjustment at Amberley was absolutely required.”
Joanne Nova’s BOM graph is from 1941 (when the Amberley station opened) to present (2014):
http://joannenova.com.au/2014/08/the-heat-is-on-bureau-of-meteorology-altering-climate-figures-the-australian/
Your analysis covers only 1975-85. You’re not comparing the same thing, so it’s not surprising you come up a different result, one that is deliberately misleading.
The latest temperature from the Amberley station was 0.4 C, at Brisbane (which you use in your analysis) it was 10.2 C. Clearly the climate of Brisbane, which is near the coast, is different than Amberley 50 kms away.
On top of that, Amberley is RAAF air force base. One would think that their measuring equipment would be fairly accurate.
Nick,
The problem is that you adjusted the data while sitting looking at trends but without knowing anything about what might have caused it. It other words, you assume something bad happened and that the data should be adjusted and how. As mentioned elsewhere, from a scientific standpoint, if the data is bad, you throw the data away, you don’t adjust it unless you can physically investigate and determine the real physical reason and how that reason affected readings.
Your adjustments leave one to wonder what happened and are the adjustments being made correct. Do you know what happened and how it was corrected?
Reg
JoNova’s plot is here
http://jonova.s3.amazonaws.com/graphs/australia/amberley-adjustments.jpg
It’s very clear that the curves track each other except for some event in 1980. The trendlines express the data as a gradual change, but the actual change is abrupt, and best analysed by looking at the surrounding years. GHCN independently homogenised the same data, with the same result. Their data sheet is here. Their adjustments are shown thus:
It’s clear that the only important adjustment was in 1980.
@Nick “It’s very clear that the curves track each other except for some event in 1980”
But the adjustments go back to 1941. If something changed in 1980 it would only affect data from that date going forward. They cooled the past to warm the overall trend based on something that changed in 1980.
I’m missing your point.
Verity,
“When step-changes due to suspected station re-locations are deducted (call them station effects), there is no residual trend. No amount of mushing about with the data will change that.”
I agree with most of what Bill says. I don’t know how I missed that last bit at the time; it just isn’t true, as a matter of simple arithmetic. If you shift one side of a data point relative to the other the trend has to change. That was the whole point of the arithmetic I did, to use the short-term trend to quantify and hence locate the break point.
Nick,
you identified the break point and corrected for it. For that I applaud you. The point Bill made that I was asserting is that you worked over a short timescale, found a break point and corrected for it, resulting in a different trend over that time scale. Bill on the other hand, over the complete station record, found two breakpoints. He said that correcting for both break points cancelled out the change of trend you are stating is necessary.
“Who was sat at a computer terminal, with the database query window open, so that they were in a position to perform an immediate edit?”
I doubt if anyone was. I’m sure BoM folk are very dedicated, but I doubt they are hunched over their monitors on a Sunday morning, editing data. It looks to me like a flag kicked in at -10°C, and a computer system responded, replacing the suspect value with an estimate from other data. Remember, they also have at least the continuous 30 minute readings at that site. I would expect that the flagged value would have been examined later, probably by a human. They want to know why a malfunction was flagged.
“What other records have been edited over the years, why and how was it documented and justified?”
My point here is that it is out in the open – which is where Walter Pidgeon spotted it. If you think this is common practice, you should be able to find instances.
Three years ago, there was a somewhat similar kerfuffle over Luling Texas, although that was a real GHCN station, and the issue involved several months. But it turned out that the issue was actually an automatic response to what was found to be a faulty cable. The system had detected the discrepancy, and replaced the data with an estimate based on nearby stations, which from a regional average point of view, was the right thing to do. But Goulburn isn’t part of any regional average that is normally published.
“The system had detected the discrepancy, and replaced the data with an estimate based on nearby stations, which from a regional average point of view, was the right thing to do.”
The reason for having multiple measuring and recording stations is because we KNOW temperature and precipitation vary geographically and temporally. If all stations were outputing identical data, there would be no reason to compute an average. It is the differences between stations that matter. After all, aren’t warmists claiming CAGW is confirmed by independent measurements?
Tracking each station’s variance from it’s peer stations is useful for detecting malfunctions, but when a station is discovered to be malfunctioning, the proper thing to do is to throw out the bad data. Replacing bad data with estimates gives those estimates the weight of raw data.
SR
I’m a frequent reader and enjoy the comments as much as the articles, mainly because you get different points of view, something that is, almost without exception, missing on warmest sites. This is one of the big arguments I make to people when debating climate change. Why are there no other points of view in the comments, much less the articles? Nick is consistently one of the big dissenters on this site and I really appreciate the fact that he was a provided the opportunity to guest post.
Can we conclude from this that the data we saw in 1995 showing a substantial cooling from 1940 to 1980 were in error because the modern data don’t display any cooling then? Will the data for 2000 to 2014 change in 2045? If these data are subject to such adjustment it follows that they were not trustworthy before they were adjusted. This brings up the reason I got involved in this study. As a land surveyor I make my living measuring things. In about 2008 I tried to imagine how to “measure” the earths temperature or even how to define it so it could be calculated consistently for comparison over time. My quandary was central to Ivar Giever’s(Nobel physicist) statement that climate science is a pseudoscience and his resignation from the American Physical Society. After all these years I remain unconvinced that the system of using ground measurements is a reliable way to estimate global temperature which Is accepted to be an average of averaged measurements at differing times in changing locations with various instruments and methods of adjustment.
DMA – “After all these years I remain unconvinced that the system of using ground measurements is a reliable way to estimate global temperature which Is accepted to be an average of averaged measurements at differing times in changing locations with various instruments and methods of adjustment.”
I am likewise unconvinced. A better global average temperature would be to capture all thermometer readings at the same point in time and then average them. Some readings will be at night, some will be at day. If these same calculations were performed each hour for a day, we would have 24 values that may differ since differing portions of the Earth would be facing the sun. Instead we are left with polling moving air masses with land based thermometers over some period of time such that one air mass can influence several readings, and the average of averages is published.
How do forest fires impact readings and how are those values ‘corrected’?
Thomas, the problem with trying to calculate a global average temperature is that it is the wrong variable to study if you are trying to study how the climate works. Local temperatures are the result of the climate, they don’t drive the climate. The climate is driven by energy differences that flow from one location to another making changes. The sun warms the top layer of the ocean and evaporates water either directly from radiative absorption or by molecular movement. The evaporated water carries heat energy and changes the characteristics of the air by reducing its density causing it to rise and change its volume. The enthalpy of water, some 40.65 kJ/mol is one of the main drivers of climate.
Unfortunately, the global average temperature tells us virtually nothing about how the climate system is behaving.
The same Nick Stokes who has repeatedly bashed WUWT on other sites, has made claims that Anthony censors and deletes, and who told people he’ll never visit WUWT again…not only freely posts comments here, but is given a forum to making full posts. That’s the best lesson to be learned here. Somehow I doubt the message will get across to those who need it.
Nick has posted here before with Zeke and me.
So MJ’s point goes triple then, huh Mosh?
Thank you for pointing that out.
Well done Nick.
The post traces raw data flow. That is almost beside the point as is not the main problem. The problem is final after homogenization adjustment. This is easily seen in Iceland, a number of ‘pristine’ GHCN stations in Europe, and even in pristine non-GHCN stations such as Rutherglen in Australia using the BoM homogenization. Some time ago I posted here an analysis of 14 USHCN stations judged CRN1 (best) by the surface stations project. Conclusion, homogenizarion did remove at least some UHI from urban stations, but added varying degrees of warming to all the suburban and rural stations, with only one exception.
The core logical problem is simple. Homogenizarion spreads bad data into good. Bad coming from UHI or microsite issues affecting the majority of all stations, as the surface stations project showed. And Kotsoyannis analysis of all long record, reasonably conplete GHCN showed a clear overall warming homogenizarion bias that was highly statistically significant. See footnote 14 to essay When Data Isnt for links to that 2012 paper.
+100 – People need to start looking at the forest and not the individual tree leaves. (SteveRichards 1984 also nailed it very well, the proverbial 5 W’s.)
Yes. Nick Stokes starts the article with “There is an often expressed belief at WUWT that temperature data is manipulated or fabricated by the providers” and then proceeds to show how a recently reported temperature at a site gets ostensibly accurately reported. So what? In other words a straw man is addressed by trying to show a recent instance of non-corruption somehow invalidates the lack of trust in the people and processes generally.
It is too late for that. Climategate exploded the scientific trust that previously supported the warmunist program. They have a desire and intent to change the data to suit their beliefs. Now they are stuck with the lawyer’s defence that their opponents can’t prove individual malfeasance in most individual cases. Stokes is not a fool with words, and employs them carefully in defence of the agenda.
“This is easily seen in Iceland, a number of ‘pristine’ GHCN stations in Europe,”
I’ve had a look at the GHCN v1 data – dated around 1990 – vs the original, already corrected/homogenized data from the Iceland Met Office (IMO) itself, not on a yearly, but on a month per month basis … because as such were the IMO data …
particularly for Stykkisholmur it was not a pretty picture … the blogpost about it is at http://euanmearns.com/stykkisholmur-iceland-temperatures-from-reality-to-ghcn-v1/ …
maybe Nick Stokes can explain the algorithms Russel Vose et al. were using then ?
> There is an often expressed belief at WUWT that temperature data is manipulated or fabricated by the providers. This persists despite the fact that…
Oh please. Everyone knows the data are not manipulated nor fabricated. Rather, they are adjusted and homogenized.
Go ahead Nick. I double dawg dare you. Say with a straight face that the data are not adjusted and/or homogenized.
As I said in the article:
‘This can then be used directly in computing a global anomaly average. The main providers insert a homogenization step, the merits of which I don’t propose to canvass here. The essential point is that you can compute the average without that step, and the results are little different.”
If the results are “little different”, why do it at all?
“So Nick, the BoM has NEVER EVER amended the temperature record in any way?
A simple yes or no will suffice.”
Good grief, how on earth would Nick know the answer to that question?
Has anyone conducted a detailed examination of sites that are NOT contaminated by Urban Heat Island (e.g. South Pole, Alert Bay Canada, etc.) with the use of unadjusted (homogenized) data only? If so, it would be helpful to compare it to Nick’s graph above. I remember a fellow by the name of John Daly who used to do this. His arguments were very persuasive. I remember a tidal gauge (New Zealand???) that had been put in place a few hundred years ago by Capt. Cook? that showed very little change over that time time period..
Yes. Essay When Data Isnt specifically examined De Bilt, Netherlands and Sulina, Rumania (both GHCN), Rutherglen Ag in Australia (BoM), and BEST station 166900 at the South Pole. All diddled into warming from raw cooling or no change.
And through 2015 (the last analysis I saw) the USCRN — the gold standard of US land based temperature measurement — show no warming. Granted the recent El Nino might have changed that a bit IDK.
Nick,
You are a devotee of maintaining the status quo of climate science. Do you think the status quo of climate science is adequate scientifically for determining and declaring there is a climate crisis?
Andrew
My dad was an amateur weather watcher and he wrote the temperature on my birth certificate of the day I was born. Boy, was that old buffer wrong. In fact he has been wrong at least five times at the true temperatures for that day keep rolling in.
Mr. Stokes,
First, let me congratulate you for agreeing to post an article on WUWT – and also to congratulate whoever invited you so to do. The only way in which a true consensus on CAGW is ever going to develop is if both sides are able and willing to post and debate on each other’s sites.
Then I have a question for you. You have written:
“I counted recently a total of 712 such stations, for which data is posted online every half hour, within ten minutes of being measured,” and “This data is from 4 December 2016, and I have highlighted in green the min/max data that will flow through …”
But if we have 48 temperature readings for each station why do we concentrate on only two for each? Surely the mean of all 48 is more accurate than the mean of just 2?
You do such stalwart work already but have you taken some sample stations over a single month and compared the mean of the 1440 (or so) half-hourly temperature readings with the mean of Tmax and Tmin? And if so how do they compare?
Solomon Green,
“But if we have 48 temperature readings for each station why do we concentrate on only two for each?”
I’ve tracked the min/max because it is what is sent via CLIMAT forms to GHCN. They use it because they are a historical database, and most pre-1990 data is available as daily min/max only. BoM highlights it in their summary data, because it is what people often want to know.
I have done a comparison of Boulder, Colorado, here. It was mainly to show the effect of different times of reading (notionally) the min/max. Changing that time (TOBS) has a much bigger effect than the difference between min/max (colors) and continuous (black). The plot is below – it shows a running annual mean (to avoid seasonal contrast) over three years of data.
This is what a serious blog about climate science should be! Congratulations for giving voice to different views, even if we do not agree with them. I do not agree with most Nick Stokes views in commentaries but I read them carefully and he’s clearly an informed, very polite guy, that tries to balance discussion. Sometimes he has a point. That’s what science is about – measuring, discuss and conclude. I’m an AGW skeptic but I also do not agree with lots of, sometimes, “too” biased articles that are often written here or, worst, with the common “left” and “right” political bash that as nothing to do with science.
Maybe you can convince Mann to write here someday 😉
Cheers
Agreed. It takes courage to speak an opposing view and character to invite that opposing view to speak.
CYM
Well done for getting nick to post an article here. He gets a lot of stick but has always come over to me as polite and well informed.
It is essential that the site does not become an echo chamber so how about offering a spot to victor venema?
I seem to remember that Richard Betts also wrote an article here a few years ago for which he received a lot of stick ( mostly from his peers and actvisys, in particular Sou.)
. Perhaps he can be persuaded to contribute another article? Also Sou writes good articles although she has been very quiet recently so perhaps is winding down her climate efforts.
Tonyb
Ctm
Quite why my iPad continually changes your initials to CYM I don’t know. Sorry. Perhaps it stands for ‘Charles, young moderator?’
Tonyb
Cyan, Yellow, Magenta — basic subtractive colors.
Without wishing to damp the conversation at all, I would like to say thanks to all for the discussion, to WUWT for hosting, and to CtM for encouraging.
NIck Stokes, thank you for the essay.
HADCrut4 was introduced to make 1998 colder than 2010.
HADCrut3 shows that 1998 was the warmest year on record and 2010 the second one. HADCrut4 shows that 2010 is warmer then 1998.
“HADCrut3 shows that 1998 was the warmest year on record and 2010 the second one. HADCrut4 shows that 2010 is warmer then 1998.”
They had to manipulate the temperature record so they could claim the temperatures were getting “hotter and hotter” They have manipulated the years since 2010 to make them appear to be “hotter and hotter” too, but the satellite charts show the true picture with 1998 being hotter than every year but 2016, where 2016 exceeded 1998 by one-tenth of a degree.
And according to Hansen 1999, the 1930’s was 0.5C hotter than 1998, which also makes the 1930’s hotter than 2016, which means we have been in a temperature downtrend since the 1930’s, not an uptrend, as the CAGW promoters want us to believe.
Thanks Nick
A good article but I don’t get the relevance.
We all know the planet is warming, by how much is almost irrelevant as the IPCC model predictions are way above observed temperatures, irrespective of what source.
So how does your article demonstrate that CO2 has anything to do with AGW?
What I see, is you defending data acquisition and interpretation techniques. You’re not dealing with the fundamental premise that CO2 is the demon of AGW.
So where do we go from here? Debate the data or find the cause of AGW?
My preference would be the latter, but in 40 odd years of the climate debate, there has yet to be, to my knowledge, a credible, empirical study that demonstrates CO2 causes the planet to heat up.
Now, whilst we sceptics are forced to adhere to the alarmist’s contention that 30 years is the minimum term of climate analysis, are we also forced to accept that the period to determine the culpability of CO2 is limitless, 40 years and growing.
When does this period end, when the 30 year climate alarm period has apparently been settled?
But as I say, respect to you for posting this. I can’t imagine anyone doing similar on an alarmist blog without being banned.
Nor am I a scientist, engineer, or even barely educated, so if you do reply, I would appreciate if you would talk my language. After all, that’s an educated man’s obligation, to communicate to the great unwashed.
HotScot August 8, 2017 at 1:37 pm
“So how does your article demonstrate that CO2 has anything to do with AGW?
What I see, is you defending data acquisition and interpretation techniques. You’re not dealing with the fundamental premise that CO2 is the demon of AGW.”
If data is being collected for the purpose of evaluating a premise, and backers of that premise change the data so as to confirm the premise, any who then say the data was not changed ARE dealing with the premise.
SR
Stevan Reddish
“If data is being collected for the purpose of evaluating a premise, and backers of that premise change the data so as to confirm the premise, any who then say the data was not changed ARE dealing with the premise.”
Too deep for me man. I don’t have education. You must speak Janet and John if I’m to understand. And like I said, that’s a scientist’s job, to educate morons like me.
Hotscot,
I think you have conflated the role of educators, the role of journalists, and the role of scientists.
Scientists have the job of discerning objective reality.
Educators and journalists have the job of informing the public.
None of them are supposed to be advocates for a particular point of view…that is the realm of pundits and politicians.
When we blur those lines, objectivity is lost, and trust becomes increasingly impossible.
When we have scientists stating openly that they have the duty to push an opinion, they are no longer scientists. They have disqualified themselves from that description.
When we have researchers who get the result they are paid to get, and only that result, they are not researchers at all…they are whores.
Words matter.
Steven
?w=400
Exactly they have all gone on a wild goose chase – sadly in his own country Nick will now witness the danger of doing this. Sure there seems to be some warming – we are recovering from colder times – but co2 as the driver – NBL. But as they say follow the money – trouble is it is always OPM.
I should note that I am not saying the data Nick is presenting has been changed, but that pointing out that certain temperature data was not changed does not negate other times when changes were made.
SR
Stevan Reddish
“I should note that I am not saying the data Nick is presenting has been changed, but that pointing out that certain temperature data was not changed does not negate other times when changes were made.”
Sorry mate, but to a thicko like me, that makes even less sense than your last post.
I will simple it up for you Hotscot.
A thief cannot prove he is an honest man by demonstrating a few times that he did not steal anything.
Understand now?
I suppose there are people who have never known any thieves, so lets look at another example.
A person is called a lair if he or she tells or has told lies.
If every word they speak is not a lie, they are still liars.
Telling the truth some of the time, or even most of the time, does not erase or undo the lies.
Even admitting one has lied, and confessing to every lie one has ever told, does not erase the lies and make one an honest person with an honest past.
All it does to confess is to make one an admitted liar.
All that got a little wordy and may be too complicated I suppose, so here it is in a nutshell:
Even the biggest liars on the world tell the truth some of the time.
BTW, the climate liars have admitted nothing…they just keep telling bigger and better and more complicated lies.
And the people who defend them are just as bad as the lying liars who are telling the lies.
For some reason my previous post wouldn’t animate – better luck this time.
?w=640
Where can I find historical time of observation metatdata for stations in the US and around the world? What data is being used to make the TOB adjustments? In the US there is the HOMR site (https://www.ncdc.noaa.gov/homr/), but it is not complete (or maybe it is and there are lots of missing values?) and appears to only go back to 1948. Am I missing something?
US station metadata is at HOMR. It is not perfect, but extensive. You can view the original B-19 forms submitted by observers here. I think that would be a primary source for TOBS data, although each change was supposed to be by permission from NOAA, which probably left a paper trail.
BoM has extensive metadata, but it isn’t easy to access. There is a post about it here, and a gadget that facilitates access.
I certainly understand the importance of TOB adjustments. I have used hourly data to construct correction factors for Pittsburgh, but you need to have a file of the actual times of observations.
I don’t understand how systematic, transparent, reviewable, verifiable TOB adjustments can be made if there is no digital record of the actual time of observation. I have been trying to take one station (Uniontown, PA) that is close to Pittsburgh and has a long record. The HOMR data doesn’t start until 1948. I followed the link to the original B-19 forms, but the forms are essentially illegible. They have never been transcribed? Are we suppose to believe that all of the adjustments have been done correctly when there are no downloadable records of the observation times? How were they done?
To quell discussions of data manipulation, this information should be front and center on the NOAA web site. The fact that it is not makes me concerned.
Kudos to WUWT for presenting a dissenting opinion. Stokes’ defense of corrupted data is lamentable, but he was given a chance to make his case. This would never be permitted at sites such as SkepticalScience where contrary views are deleted and dismissed as “sloganeering” – a Communist phrase from the 50’s.
Kudos to Nick for posting this.
I always welcome Nick’s comments, and always read these carefully and consider what he has to say. I always want to see all sides of a debate, and Nick’s comments are usually intelligent and well argued, and rarely does he engage in drive bys.
I find Nick to be one of the most thoughtful commentators on this blog (whether you agree with him or not), although occasionally I consider that he seeks to defend the indefensible, and sometimes obfuscates, as he did when dealing with Forest Gardener’s straightforward question:
You should have read the letters after the article on BoM in the Australian newspaper. Then you would question what is going on at BOM. In Aus every year is the hottest one yet, that is what they say where I live.
Above a question is asked that is not answered: how do we know the temperature of the Pacific Ocean in 1900? I’m a layperson, and don’t claim otherwise, but I find that an interesting question. How is it possible that we have a firm grasp on the temperature of the Pacific Ocean’s surface (and the Arctic’s, and the Antarctic’s, and that of remote swaths of Africa . . . ), in 1850, 1860, 1870, 1880, 1890, 1900, etc.? If we do not have a firm grasp on those things, how can know the temperature of the entire globe in those days, such that we can say with meaningful confidence how much warmer it is today? (Perhaps estimates are made about portions of the earth’s surface in the old days. If so, how much of the globe is subject to such estimation, what are those assumptions based on, and how are the methodologies for such assumptions tested.) I am not making an argument here; I am just inquiring.
Thanks very much.
Consider this: We have very good data for a large part of the world, a representative sample if there ever was one.
It is contiguous (all touching itself).
It is large in extent from north to south, and from east to west.
It has vast and tall mountains, and vast and not so tall mountains.
It has valleys…big ones and small ones and lots of in between sized ones.
It has vast plains, it has large coastal zones, and these coastal zones abut the two largest oceans on Earth, and the Gulf of Mexico.
It has huge lakes and small ones, and every sized ones in between, and a large number of each.
It has small streams, creeks, and rivers of every sort.
It has deserts.
It has rainforests.
And for well over one hundred years it has had excellent coverage of collected meteorological data.
And for this one place, we can see one thing very clearly…it has had several separate multi decade trends in average temperature, both up and down.
And we can also see that the recent decades have not been the warmest time period over the past hundred plus years. Not even close to the warmest.
There was a decade nearly a century ago that was so hot it changed the course of history.
This hot period can be found to have been roughly coincidental with a hot period in locations all over the world with records from that same period.
That period was roughly the 1930s.
The recent years are not the most extreme in any category of weather statistic in this place.
Other time periods many decades ago had more and worse hurricanes, more and worse tornadoes, more and worse floods, more and worse droughts, more and worse blizzards, and also times that were about just like it is now.
In fact, this place with excellent records over a wide area and for a long extent of time shows that nothing unusual is happening at the present time at all, except that crops are growing ever more bountiful, trees and plants are spreading into areas that were once marginal for their growth, and everything is growing faster and better than ever before.
This area is the United States or course.
And it proves that everything that the warmistas claim to be true is in fact false.
The opposite of what they say is true.
I challenge anyone to give any plausible, or even possible, reason or logical explanation for how a large continent sized area of the planet is doing the opposite of what is claimed to be the case for the planet as a whole.
D Clancy, ask yourself…if you have very good pictures of one area of the world over a long time, and this one place is the only place that has such pictures over such a period of time, and it does not show what some people are claiming is the case by using bad pictures, or using no pictures but only what they think the pictures should look like…what are the chances that they say they can see in their imagination is more accurate and more true than what you can see in the one place that has actual pictures?
That is what is being claimed by the warmistas.
They claim to be better at knowing the past that people who lived in the past knew it.
They claim their imagination is a more accurate representation of reality than actual pictures.
They get a lot of money for believing this and saying it, and any who refuse to say this and believe it get not a lot of money but get fired from their jobs.
They never look out the window, but claim to know what is going on outside, better than people who live outside.
Year after year, for more than thirty years, they have made predictions regarding a huge number of events, and have literally never been correct even once.
They rewrite history to agree with things they claim are true, and then claim that history proves them to be correct.
And they want everyone to believe them so confidently that we should do everything they say to do.
In short, they make stuff up and change their own story constantly.
Is there any reason to believe people who tell you to disregard your eyes and trust their eyes?
Is there instance in any person’s experience that leads one to believe people that do that are telling the truth?
Is there any experience in our lives that dictates that people who are always guessing wrong, should be relied on for guidance about what is going to happen in the future?
There is no need for someone “hovering over this stream of data with an eraser.” That is pure hyperbole, Nick.
I expect AWS stations are designed to promptly notify HQ about abnormal occurrences. Maybe sound a klaxon in the break room? 🙂
Evidently the person handling such situations wasn’t quick enough to use the manual over-ride to adjust the
temperature to the preferred value before it was noticed. Sounds like it might be a policy to not allow new records to publicly be shown without approval from higher up the food chain.
By the way, as of today GHCND shows the ‘adjusted’ -10C rather than the temporarily shown -10.4C for Tmin on July 2nd at Goulburn. It will be interesting to see if it changes when GHCND updates that station again. They currently only have data up to July 3rd. Here is a link to the GHCND file.
ftp://ftp.ncdc.noaa.gov/pub/data/ghcn/daily/all/ASN00070330.dly
Bob
“Evidently the person handling such situations wasn’t quick enough to use the manual over-ride”
There is no person handling such situations on duty early Sunday morning. Or probably any time. Remember, there are about 720 stations posting data every 30 mins. That has to be done automatically.
That portion could also be automated even if no one is around.
Those temperatures are sent to HQ. I doubt they are stored on station. HQ probably immediately posts the value when it is received. Their problem might be a coding problem where HQ looks up the current record after posting, but doesn’t adjust the new record to within that range until the next posting cycle for that station
Since it is unlikely an outsider would observe that reading in the second it would take to update the temperature automatically, there must be some time lag for an outsider to observe the lower reading. Likely a posting cycle.
“Have you read the advice from the BoM to the minister?”
No. But I will if you link to it.
Hi Nick.
Over on realclimatescience, right now there is a GIF which flashes between a NASA ‘global temperature’ graph from 1999 and a NASA ‘global temperature’ graph from 2017.
Logic and science would state that the common part of the two graphs would be perfectly super imposed…they are not. The data has been manipulated to produce a more consistent warming.
Unless of course, you’re ‘denying’ that these are real graphs from NASA?
If so why don’t you pop over there and leave a message for Mr Heller, I’m sure he would be glad to defend himself.
“a GIF which flashes between a NASA ‘global temperature’ graph from 1999”
I looked through the page, and only saw a GIF for USHCN (lower 48 US). It’s frustrating when people can’t make that distinction. It is the animated gif shown upthread.
The reason for that discrepancy is a peculiarly US one. Volunteer observers were given a lot of latitude in TOBS (time when they reset). As I showed in the Boulder plot upthread, it matters when that changes (more in the link there). It has a big warming effect, because the NWS preference had been evening reading, but people drifted toward morning. USHCN introduced the adjustment for TOBS soon after 1999. It’s not optional. Once you have a record of a change, and a clear basis for calculating the effect, you have to allow for it in calculating an average.
My mistake…I guess you’re saying that temperatures in some parts of the ‘globe’ (namely the US which is probably the closest and most consistently observed part of the ‘globe’) are behaving differently to temperatures in other parts?
Also if the measurements in the US are so unreliable, how sure can we be about the temperatures in say, the Arctic, the Antarctic, the Southern Ocean, Africa or even Asia in say….1900?
You know before anyone was actually observing them at all?
The author of the RealClimateScience blog has demonstrated statistically that the Time Of Observation Bias adjustments are and were unjustified and therefore bogus.
If warm days were double counted, so too were cold nights, or cold days, or warm nights.
Just as cooling the past is somehow justified by a UHI adjustment, the claim of TOB adjustments being justified is an assertion. A very convenient one. And one that just happens to smooth out all the bumps and trend reversals in just the way that makes some inconvenient anomalies vanish. Just exactly as the Climategate emails describe doing.
And the sum total of all of the alterations just happens to produce a straight line when plotted against the climate McGuffin, CO2.
If it was a movie script no one would make the movie, because it is to laughably predictable.
Might as well make a mystery thriller in which the opening scene has someone describing the entire plot of the movie, right down to the surprise ending.
Every aspect of the entire CAGW meme is so hackneyed and telegraphed that the only real mystery is how anyone can claim to believe it with a straight face.
Tony Heller and others have shown conclusively that the adjustments are a contrivance of such obvious motive it is stunning anyone can defend them even after they have been outed for what they are.
It was obvious from the start to some of us, even if we lacked the means to prove such.
You should be ashamed of yourself.
“The author of the RealClimateScience blog has demonstrated statistically”
That author is incapable of demonstrating anything statistically. But If you think it can be done, please explain.
“That author is incapable of demonstrating anything statistically. But If you think it can be done, please explain.”
Not nice.
But beyond that, are you saying it cannot be done?
It is not in my skill set to do this sort of thing, but it is in yours, and in Tony’s.
It is unseemly of you to make such a remark of him.
But since you asked nicely, I will be happy to give you as many examples of how he has done so as you want.
He has not given me permission or anything, but I think fair usage applies. Or so I hope. I could be wrong.
Let’s start with one and go from there.
I will copy some of his text, and accompanying graphs, and then a link to the post.
Of which there are many.
Maybe you could respond with a refutation of his reasoning and a synopsis of the original justification for doing it. I can only imagine that, prior to adjusting the entire historical database of temperature records, that a very rigorous vetting procedure was performed, pros and cons weighed, peer review of the proposed methods done, objections noted analyzed and dispensed with in an agreed upon manner, etc.
I simply missed any of it.
I will have to break it up, or it will go into moderation…and it may anyway.
And I may not get back here until tomorrow afternoon, EDT.
I do not think the GIF files graphs will post as graphs, so anyone who wants to will likely have to click on them.
BTW, this one is random…it is very late here, I just pulled the top one from a search of his blog using the three letters, TOB:
“NOAA massively tampers with US temperature data, to turn a 90 year cooling trend into a warming trend.”
“NOAA says that station operators in the past used to reset their min/max thermometers in the afternoon, and now they reset them in the morning. The theory being that resetting thermometers in the afternoon causes double counting of hot days, and resetting thermometers in the morning causes double counting of cold days. So NOAA cools the past and warms the present to compensate.
This is easy to test. I split the stations up into two groups – those that took readings in the morning during July, 1936 and those that took readings in the afternoon during July, 1936. I chose July 1936 because, it was an extremely hot month, which NOAA’s adjustments massively cool.
NOAA is correct that most stations took their readings in the afternoon during that month: 937 currently active USHCN stations were afternoon stations in 1936, and only 140 were morning stations. So lets see how the trends compare.
The two groups of stations show identical trends in temperature anomaly. The TOBS adjustment is fake. There is no indication of double counting.”
“Additionally, the trends in the frequency of hot days are also identical for the two groups, but the morning stations tend to have more hot days. This is because people in warm climates tend to work earlier in the morning.”
“This is confirmed by looking at the latitude of the stations. Morning stations average about one degree further south than afternoon stations.”
“Station history was obtained from this archived NOAA link : USHCN ORNL/CDIAC-87 NDP-019
In order to test out double counting of hot days, I selected two adjacent stations in Missouri. Mexico, Missouri took their readings in the morning during July, 1936 and Warrenton, Missouri took their readings in the afternoon that month.”
“According to TOBS theory, we should see more 100 degree days in Warrenton than in Mexico, but we see the opposite. Mexico, Missouri consistently shows more 100 degree days than Warrenton, though the patterns are nearly identical. There is no indication that TOBS theory has any basis in reality.”
https://youtu.be/-oxKF6rW-W0
https://realclimatescience.com/2017/05/the-wildly-fraudulent-tobs-temperature-adjustment/
Morning station list :
FAIRHOPE 2 NE AL USC00012813
CHILDS AZ USC00021614
GRAND CANYON NP 2 AZ USC00023596
LEES FERRY AZ USC00024849
MIAMI AZ USC00025512
SACATON AZ USC00027370
SAFFORD AGRICULTRL C AZ USC00027390
YUMA CITRUS STN AZ USC00029652
GRAVETTE AR USC00032930
FAIRMONT CA USC00042941
HANFORD 1 S CA USC00043747
HEALDSBURG CA USC00043875
QUINCY CA USC00047195
SUSANVILLE 2SW CA USC00048702
TEJON RANCHO CA USC00048839
TUSTIN IRVINE RCH CA USC00049087
APALACHICOLA AIRPOR FL USC00080211
BARTOW 1SE FL USC00080478
BELLE GLADE FL USC00080611
FT LAUDERDALE FL USC00083163
MADISON FL USC00085275
PERRINE 4W FL USC00087020
TITUSVILLE FL USC00088942
HAWKINSVILLE GA USC00094170
QUITMAN 2 NW GA USC00097276
TIFTON GA USC00098703
ARROWROCK DAM ID USC00100448
CAMBRIDGE ID USC00101408
FENN RS ID USC00103143
HOLLISTER ID USC00104295
SALMON-KSRA ID USC00108080
CHARLES CITY IA USC00131402
FRANKFORT DOWNTOWN KY USC00153028
ALEXANDRIA LA USC00160098
PLAIN DEALING LA USC00167344
EASTPORT ME USC00172426
LEWISTON ME USC00174566
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GREENVILLE MS USC00223605
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FARMINGTON MO USC00232809
MEXICO MO USC00235541
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LANGDON EXP FARM ND USC00324958
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FINDLAY WPCC OH USC00332791
GREENVILLE WTP OH USC00333375
PORTSMOUTH-SCIOTOVIL OH USC00336781
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BEND OR USC00350694
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JOHNSTOWN PA USC00364385
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KINGSTREE SC USC00384753
ORANGEBURG 2 SC USC00386527
YEMASSEE 1 N SC USC00389469
RAPID CITY 4NW SD USC00396947
UNION CITY TN USC00409219
ALICE TX USC00410144
BALLINGER 2 NW TX USC00410493
BRENHAM TX USC00411048
CORSICANA TX USC00412019
DUBLIN 2SE TX USC00412598
EAGLE PASS 3N TX USC00412679
FLATONIA 4SE TX USC00413183
HASKELL TX USC00413992
LAMPASAS TX USC00415018
LLANO TX USC00415272
MCCAMEY TX USC00415707
MEXIA TX USC00415869
PECOS TX USC00416892
RIO GRANDE CITY TX USC00417622
TEMPLE TX USC00418910
LOGAN UTAH ST UNIV UT USC00425186
LEXINGTON VA USC00444876
ROCKY MT VA USC00447338
STAUNTON WTP VA USC00448062
ABERDEEN WA USC00450008
BLAINE WA USC00450729
CLEARBROOK WA USC00451484
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Afternoon station list :
BREWTON 3 SSE AL USC00011084
GAINESVILLE LOCK AL USC00013160
GREENSBORO AL USC00013511
HIGHLAND HOME AL USC00013816
SAINT BERNARD AL USC00017157
SCOTTSBORO AL USC00017304
SELMA AL USC00017366
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THOMASVILLE AL USC00018178
TROY AL USC00018323
UNION SPRINGS 9 S AL USC00018438
VALLEY HEAD AL USC00018469
AJO AZ USC00020080
BUCKEYE AZ USC00021026
CANYON DE CHELLY AZ USC00021248
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HOLBROOK AZ USC00024089
KINGMAN #2 AZ USC00024645
PARKER AZ USC00026250
PRESCOTT AZ USC00026796
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TUCSON WFO AZ USC00028815
WICKENBURG AZ USC00029287
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PRESCOTT 2 NNW AR USC00035908
ROHWER 2 NNE AR USC00036253
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MADISON SEWAGE PLT IN USC00125237
MARION 2 N IN USC00125337
MT VERNON IN USC00126001
OOLITIC PURDUE EX FM IN USC00126580
PAOLI IN USC00126705
PRINCETON 1 W IN USC00127125
RENSSELAER IN USC00127298
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The link to the whole post went into moderation.
Here it is with some spaces inserted.
httrealclimatescience. com/2017/05/the-wildly-fraudulent-tobs-temperature-adjustment/
The reason I said that Steven Goddard is not capable of producing a statistical proof is that he can’t get his head around a basic step. If you are going to argue by difference in some results, you have to ensure that either it is the same population that is concerned, or you can rule out the difference being due to some other difference in the populations. And that is very relevant here. He divides the stations into two groups according to TOBS in July 1936. But they vary clearly have a relevant other difference, of 1 degree latitude on average. So you don’t know how the more southern location effect interacts with the TOBS effect. Maybe the evening TOBS were cooled by changing to morning, but the morning TOBS cooled faster because the SouthEast did.
Or even what the TOBS effect should be. What counts for trend is the changes in TOBS, and there is no data shown on that. It’s true that many in the rather large number of stations reading in the evening are likely to change at some stage to morning reading. But you don’t know how many, or when, both very relevant to trend.
One thing also not stated is whether the data plotted is raw or adjusted. The link doesn’t help at all. It goes to a WayBack file, where is just shows the front page of a paper. The links to data, or even description of data, don’t seem to work.
The Missouri test is completely useless, because there is no control over whether the stations might have had different numbers without different TOBS. There are many things that could influence the number of 100 degree days. There is also no information on whether the stations even had different TOBS in the range of the plot. The only test is whether they were different in July 1936. Finally, the 100 degree test is one that SG seems to have set up and uses for all purposes. It isn’t the right one here. If you have 5pm reading say (which was once recommended), then double counting means that on a hot after noon, the residual warmth at 5pm is counted to the next day. It may be that it is infrequently still 100F at 5pm, but still biased warm.
One last thing – the 140 morning stations is a fairly small sample. Standard error on means and trends will be quite high.
Welcome to NOAA’s cool magic show! We make the cooling disappear! Now you see it, now you don’t (applause)
Nick, you did not refute what he showed at all.
What he did is very simple, is explained in one sentence, and shows a very clear result.
Maybe of someone could show all the other places and times that the afternoon stations graph looks different, specifically looks much hotter, than the morning stations graph, that would be at least some evidence that the TOBS is justified.
You did not give any reason to think that the past should be cooled massively because some stations reported in the afternoons.
Any Tony Heller has given many very simple and very specific and very clear reasons to doubt it was ever justified.
I am wondering why you did not take the time to refer us to the research that proved that the TOBS alterations were valid and well reasoned and necessary.
The logic is so thin I can not even see that it exists at all.
And has anyone got any documentation to show that people were so careless and stupid back then that they would reset a high/low thermometer in the middle of the hottest part of the day?
They are two separate operations…recording and reporting, and resetting the high/low thermometer.
People did not suddenly grow brains in 1988.
Okay, I get to add my own two cents in, here. I do not believe there is any actual fraud involved on the part of NOAA or BEST. Furthermore, I agree that raw data (writ large) won’t do. There are a number of systematic biases which make raw data misleading.
One must either adjust the raw data or throw out all the known compromised data. Well our team has done the latter to the greatest extent possible. But, even so, we are still left with equipment issues. When they switched equipment, they were perfectly happy to get it to within a degree or so. But when you are trying to measure hundredths of a degree trends per decade, it can be a highly disruptive random element. Besides, if we dropped everything possible, we’d have nothing left. So we have to run some pairwise. (So, okay, step one on the road to hell.)
But homogenization. Now there’s a tool. A powerful one. Finally, a statistical basis for roping the ol’ maverick. Just what the doctor ordered. my friend, Kindly Uncle H.
The only (very well known) problem being that homogenization only works on basically good data, or at least on known biased data with the bias accounted for. And when there exists one or more systematic biases in the dataset (either abrupt or gradual), well, that’s when homogenization bombs. Kindly Uncle H has become Wicked Uncle H. You are actually worse off than when you started.
Follow the pea. The pea is the correct data signal.
So, instead of correcting the incorrect majority to conform with the correct minority, homogenization now “corrects” the correct minority to conform with the incorrect majority. Leaving no trace that the correct signal ever existed. As for your data signal, that pea you were following isn’t even pea soup. It is meaningless pap. Peas are not even on the ingredient list.
Kind of puts one in mind of that old movie Gremlins.
Well, that’s what’s happened here. Both to NOAA and to BEST. Our team has identified two unaccounted-for major systematic biases that fatally infect all pairwise computations. Once those biases are compensated for (by weighting, dropping, adjusting, whatever), then homogenization will be applicable. And not until.
But even then, there may be other undetected biases lurking in the data. If our merry band can drag out two, then who knows how many there actually are. It’s an ongoing process.
Nick, all you need to do to KNOW that NOAA& NSA introduced “adjustments” to historical data is to look at James Hansen’s 1999 and 2000 US temperature graphs. He cooled the 1900-1950 data and warmed the 1970-2000 data! That climate fraud for everyone to see!