The globe may have only warmed by 0.41 to 0.83°C in the last 140 years.
According to a new study, weather station data has been shown to non-climatically and erroneously record warmer-than-actual temperatures due to the steady and perpetual aging process almost universally observed in temperature gauges.
When a weather station temperature gauge’s white paint or white plastic ages and darkens, this allows more solar radiation to be absorbed by the gauge than when the gauge is bright white and new. Within a span of just 2 to 5 years, a gauge has been observed to record maximum temperatures 0.46°C to 0.49°C warmer than in gauges that have not undergone an aging process. This artificial warming is not corrected in modern data sets, and it builds up over time – even when the gauges are cleaned or resurfaced every few years.
If these systematic artificial warming errors were to be corrected rather than ignored, the 140-year (1880-’90 to 2010-’20) GISTEMP global warming trend plummets from the current estimate of +1.43°C down to +0.83°C, a 42% differential. The temperature reduction can be even more pronounced – from +1.43°C down to +0.41°C – if a set of conservative assumptions (described in detail in the paper) are removed.
Image Source: Büsing, 2024
Interestingly, when the systematically erroneous temperature data are removed, or homogenized, at different intervals of time (2 years vs. 12 to 30 years, etc.), the global temperature trend – indeed, the long-term global warming trend – can be shown to effectively disappear, depending on the time interval. This can be observed below, in Figure 7.
As this chart illustrates, temperature data can homogenized, or adjusted, to exhibit just about any trend or non-trend the creator of the chart intends to. Data can be bent and manipulated to show strong warming, weak warming, or even no warming over the last 140 years.
Perhaps the modern version of global warming is not nearly as unprecedented or even unusual as it is purported to be.
Image Source: Büsing, 2024
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And NOAA continues to tamper with temperature data … https://www.youtube.com/watch?v=cF16lDtSVrU
No surprise.
Exactly.
It is not systematic error, it is on purpose.
Bingo — it’s a systematic bias — and its obvious to those who dare to look.
Ah yes, Heller again. How do I know? It describes USHCN data to 2024. Now USHCN was discontinued over 10 years ago. NOAA has not published a USHCN average since that time. The only one who does calculate those averages now is Tony Heller.
LIAR.. USCRN 2.5 still exists.
USCRN isn’t USHCN.
Sorry, typo. USHCN 2.5 still exists. !
They sure fooled you with their shell game. They use the same data, but under a different named dataset. Not only does NOAA do, but all the other nations who are part of the climate-change mob do it.
“NOAA has not published a USHCN average since that time.”
But USCHN 2.5 still exists. You know that because Tony Heller gave you the link to it…
Of course they couldn’t continue using the same fake methodology as they used to, because it would diverged wildly upwards from the pristine USCRN data, showing just how corrupted the data and methodology was.
So they created a homogenised set called ClimDiv, using USCRN as a reference to get rid of the massive urban bias, so they would come out approximately the same.
And the rabid warming adjustments came to a screeching halt.
Since 2005, there is no signature of any human warming, urban or maladjustments, in the US data.
The ruler monkeys won’t like this one.
The “ruler monkeys” in the UK are all over the place [do bear in mind one cannot make this up]
“”Labour’s vaunted International Investment Summit is losing steam before it even starts. Rayner and Haigh have put their foot in it…
Dubai-based DP World, which owns P&O Ferries, has paused plans to invest a whopping £1 billion in its London Gateway container port after getting heated criticism from Labour cabinet ministers. Haigh and Rayner have called P&O a “rogue operator” in a press release which accused its hiring of foreign workers as a “national scandal.” Released right before the big summit’s kick off on Sunday – no wonder Rayner has been snubbed from hosting it…
Downing Street says the summit will act as a “reset” after a disastrous first 100 days. DP World’s chairman Ahmed bin Sulayem will now miss the event and pull the £1 billion. How’s “letting the cabinet ministers do their own thing” going then, Keir?””
https://order-order.com/2024/10/11/rayner-and-haigh-wreck-1-billion-of-investment-ahead-of-international-summit/
6th form identity politics is the gift that will keep on giving – until the proles wake up.
Wow! The truth really hurt some plank who had nothing of value to add on the subject
-1
Isn’t that just about as sad as they get?
It is sad, but it is really all they have.
Given the importance attached to the knowledge that our planet is warming one would have anticipated meteorological professionals to be falling over themselves to get everything one hundred percent correct. The truth about these charlatans is they have never given a damn about accuracy and quite happily exaggerate the amount of warming to suit their point of view.. After all that was the lead Mann set for his so called profession wasn’t it?
Professional scientific activity stopped happening in the mainstream meteorology profession a very long time ago.
The British Labour Party couldn’t run a sweetshop, let alone a country.
Bdgwx will adamantly insist that averaging anomaly time series across multiple weather stations reduces systematic error.
Brilliant! Someone should tell the NIST they’ve been wasting their time calibrating thermometers!
The above article is off-base and confuses most people by referring to instrumentation enclosures as “weather station temperature gauges”.
In comparison, the extract of the referenced paper by Büsing has it correct:
“The white paint or white plastic housings of weather stations ages, which leads to increased absorption of solar radiation and increased temperature measurements.”
AFAIK, NIST does not calibrate weather station enclosures, nor recommend doing such.
Why negative votes?
“Hit and run.”
Actually, I take such as being an indication that I’ve hit my mark of upsetting those with confirmation bias, whether they realize it or not.
Then again, maybe all the down-voters do indeed work for NIST 😳.
Kudos to the authors for revealing a non-random effect that cannot be averaged away or treated with standard statistics. But, without having read the paper, it should be noted that not every screen can be expected to degrade at the same rate, especially considering their use in local environments across the globe. It is futile to imagine it can be removed with corrections, as the air temperature trendology types believe.
Also, this is only one non-random effect, there are others!
I agree! I think this study does a good job of raising awareness. The issue is what you’ve pointed out for years now: uncertainty is not error. Air temperature measurements are not abstract numbers.
Imagine this kind of nonsense being employed in any other field of science. You would be laughed at.
…or your cell phone wouldn’t work, or your computers wouldn’t work, or the internet wouldn’t work, or your microwave wouldn’t work, or…
“”Systematic Error In 1880-2020 Global Temperature Measurements Inflates Warming By 42%””
From a grey, chilly and damp UK I think it safe to say: “We know“.
Congratulations, strativarius, you win the “First step in weather forecasting is to look out the window” award. Confession: as I age I am not getting hotter.
Re: your last sentence: is that what she told you? 😜
Ooh, you are awful (Dick Emery).
…but I like you!
The number of times I have come within a gnat’s doodah of throwing something at the radio or the TV is very huge. But then, all media seem to follow the BBC lead – with one or two exceptions.
That’s why my wife prohibits me to use those devices.
You could buy a Tesla Cybertruck.
I clearly remember the newspaper and magazine articles in the UK back in the early 90’s when the CAGW Scare really got underway. They all predicted that the South of the country would be enjoying
a Mediterranean climate by now, with farmers cultivating olives and lemons.
The differences should be expressed in degrees Kelvin for a correct comparison.
Absolutely !
There is Kelvin or degree Celsius, no “degrees Kelvin”
Did you work at Rocky Flats?
becomes may have only warmed by 0.41 to 0.83K.
now, take a deep breath, and eat your oatmeal.
++5, IDAU, because no one else got it.
They got it. But…
Note the contrast between Celsius degrees and Degrees Celsius. C° and °C.
Hint; 5°C = 41°F, while 5C° = 9F°. A conversion site on the web returns the ’41’ rather than asking what the question means. All this is somewhat like a score of “Love” in tennis — get used to it.
tamperature instead temperature!
The link to the study goes to an error page.
fixed.
I earlier posted the correct link at NoTrickszone
From the above article:
“Interestingly, when the systematically erroneous temperature data are removed, or homogenized, at different intervals of time (2 years vs. 12 to 30 years, etc.), the global temperature trend – indeed, the long-term global warming trend – can be shown to effectively disappear, depending on the time interval.”
Does that mean that correcting for aging is now an existential threat TO global warming?
/sarc
“”correcting for aging””
“”Labour scraps Winter Fuel Payments for millions of pensioners””
https://moneyweek.com/personal-finance/labour-scraps-winter-fuel-payments-for-millions-of-pensioners
I thought the Labour Party was for the little guy; the poor guy. I guess I was wrong. Who is the Labour Party’s constituency? Who votes for these clowns?
Yep, but someone has to explain this to the Glaciers in the Europe and North America.
Interesting to note that the results vary with the number of years homogenized. Looks like that, then, is merely a vestige of the application of the homogenization algorithm, and note real.
This is effectively dealing with a time series. Climate science has never heard of how time series must be treated to obtain decent conclusions. One of the biggest assumptions is stationarity. If the means and standard deviations are not the same throughout, one must attempt to transform the series to obtain stationarity.
See, this site, 8.1 Stationarity and differencing | Forecasting: Principles and Practice (2nd ed) (otexts.com)
There are lots and lots of web resources. One of the big things climate science pays no attention to is if standard deviations are changing. One must determine why standard deviations will have an effect and why.
How to raise temperature on WUWT without the use of homegenisation (sarc)
How about USCRN temperature series?, which in this discussion by Zeke Hausfather …..
https://www.theclimatebrink.com/p/the-most-accurate-record-of-us-temperatures
He states ….
“To ensure a more stable set of measurements going forward, NOAA began developing a U.S. Climate Reference Network (USCRN) starting in 2001. The USCRN includes 114 stations spaced throughout the U.S. that are well sited and away from cities. They have three temperature sensors that measure every two seconds and automatically send in data via satellite uplink. The reference network is intended to give us a good sense of changes in temperatures going forward, largely free from the issues that plagued the historical network.”
“If the warming we have experienced in the US is in part due to factors like urbanization or other localized biases, the pristine rural USCRN data would show the real, unbiased results.”
Hausfather then states at the end…
“During the period of overlap between the USHCN [ClimDiv’s predecessor] and USCRN networks, we can confidently conclude that the adjustments to the USHCN station records made them more similar to proximate homogenous USCRN station records, both in terms of trends and anomalies. There are no systematic trend biases introduced by adjustments during this period; if anything adjusted USHCN stations still underestimate maximum (and mean) temperature trends relative to USCRN stations.”
Now – cue conspiracy theorists – (you know who you are) to chime in … well hello!
Now, cue some reality. Below average temperatures UK
Where is our global heating? Timbuktu?
You still get chilly days, and weather at cooler times of the year still feels cool even if it is warmer than average.
October is still running warmer than average. It was 13 to 17C north to south in England today. 20C possible next week.
Your constant claims that it is near permanently freezing cold are just silly.
Hint:
Clue is in the word beginning with G
I think you will find that the UK is but a tiny proportion.
+ you are aware of the concept of local variation in the global whole?
Another hint …..
Where do the numbers for the southern Indian Ocean come from?
It’s UAH v6 LT atmospheric temperature series – the map version of Spencer and Christy’s product.
They ultimately come from those two performing an algorithm on data received from satellite.
Which is not data from the southern Indian Ocean.
ROFLMAO.
Using the remnants of the 2023 El Nino energy to try to show something..
DUMB even for Banton.
global whole is a fantasy.
That’s wrong, Anthony.
If every air temperature measurement at a specific weather station were affected by a uniform systematic error, the baseline number would change, but the deviations from that baseline would remain exactly the same. The homogenization algorithm would be unable to differentiate between an authentic record and one that has been offset by systematic error.
Take a look at the attached image of ‘climatological data’ from a randomly selected month at a nearby station. If these numbers were uniformly offset by, say 4°F, in the real world, would it still have snowed 11.5 inches on the 25th? Would the snow depth for the following days be lower? Most likely. Would there have been a trace of snow on the morning of the 16th?
The point is that real numbers correspond to real physical changes—this is what climate change is all about, you know? Not abstract numbers.
“The homogenization algorithm would be unable to differentiate between an authentic record and one that has been offset by systematic error.”
There is no algorithm applied to USCRN stations, as they are kept pristine with multiple sensors employed for cross-checking.
Yet, if anything they are warming more than the USHCN stations which allegedly have a (warming) bias by dint of said algorithm.
Anthony, not long ago, Nick Stokes presented his findings based on raw data from both the CRN and GHCN.
The results align because the temperature data from weather stations in both datasets are converted to anomalies, which serve as measures of correlation.
And the homogenization algorithm aims to improve correlation in a corrupted dataset but does not enhance its accuracy.
If your measurements don’t accurately reflect the real world, then you’re not measuring change.
And USCRN shows NO WARMING from 2005-2015, then a bulge of the 2016 EL Nino, then cooling until the start of the 2023 El Nino.
As you would expect, here is no sign of any human caused warming in the USCRN data.
As for ClimDiv, it is a homogenised series, using “pristine sites” on a regional basis to remove urban warming. It is not real.
The slight difference in monkey-with-a-ruler trend is because that have improved their homogenisation routine over time.
Where are the error bars? I also looked at you graph and see ClimDiv over state the highs by nearly a quarter to a half degree. Funny is that not what the above article stated? The drift on the stations will make the measurements off on the warm side. Seems your graph proves that.
Error bars? Temperature measurements in Stevenson Screens are accurate to 0.000001 degree Celsius. /s.
The issue is not biases introduced by adjustments. The issue is systematic bias due to weathering of the enclosures that is not accounted for.
If climate science would perform due diligence in creating an uncertainty budget for these measurements this issue would not even occur. Systematic bias would already have a correction factor based on years of being in service between replacements or renewing.
Plastic enclosures are not immune by the way. Plastic degrades due to UV and changes it’s surface characteristics.
CRN stations also have their own measurement uncertainty that does not propagated.
Show us an uncertainty budget from a peer reviewed paper that has it uncertainty propagated properly.
“The issue is not biases introduced by adjustments. The issue is systematic bias due to weathering of the enclosures that is not accounted for.”
No, the issue is that the paper alleges that there are algorithms employed in historical climate temperature series that are employed to remove degradation of Stevenson screens and somehow that algorithm introduces a warming bias.
Point Is that the USCRN does not employ those algorithms as they are not required … the network being scrupulously implemented, monitored and maintained.
Yet USCRN, if anything is warming a little faster.
Ergo: there can be no systematic bias introduced into the historical networks, otherwise it would be the opposite. It would warm slower. Or, if the case, cool faster.
Where does it allege this?
OMG you are so dumb.
Climdiv is the homogenised series,.. it is NOT REAL… they actually state that they homogenise to pristine data at a regional level to remove urban bias.
USCRN has no evidence of any human warming, just the El Nino bulge in 2016/17, then a bit of a spike at the 2023 El Nino.
The slight discrepancy in trend between USCRN and ClimDiv comes from improvements to the homogenisation routine for ClimDiv.
Note how Climdiv starts a bit higher, and they are now basically the same trend.
So the USCRN enclosures are cleaned and repainted every quarter, or they don’t use Stevenson Screens?
Show a quote from the paper that concludes this. I have read the paper today and don’t remember seeing a conclusion that homogenization algorithms remove systematic bias of Stevenson screens due to enclosure degradation.
In fact, my reading leads me to the conclusion that not removing the systematic uncertainty during homogenization spreads the bias to other stations.
You should stop relying on Hausfather who is a stridently dishonest in his bogus claims that have been addressed many times to be a pile of statistical BS!
Ad Hom is not, in my book, a reason to dismiss a scientist’s “claims”.
“Bogus” or not.
It is your opinion and not a matter of fact.
My opinion is the opposite and is just as correct (as a pub argument) as yours.
In other words meaningless.
Science requires that you address the data not the person presenting it.
BTW: Just what is so hard to reconcile the pair-wise examination of series where one doesn’t have the systemic bias algorithm applied and one that does …
and low and behold not only does the bias disappear, but actually (may) show a cooling bias (in the historical series).
Try addressing that, otherwise you go into the “conspiracy” theorist camp.
Finally Banton is admitting that any difference between trend in ClimDiv and USCRN…
…. is purely a facet of the homogenisation routine that adjusts ClimDiv to remove urban bias..
ie.. it is NOT REAL
Well done, muppet !!
ps.. the “historic” series did not have a USCRN-style pristine series to homogenise to…
So you are now admitting that the “historic” homogenisations and adjustments are a major cause of the warming.
On that we can agree.
….the issue is that the paper alleges that there are algorithms…
So, where does it allege this?
When I read that Anthony Banton statement, I thought he meant to say that there are not algorithms to make that adjustment, and he just left out the “not”.
But he hasn’t corrected himself, so I’m not sure what he meant now.
In the first paragraph of the abstract …
“. However, many different state-of-the-art homogenization algorithms repeatedly add this small value each time a weather station is renovated, renewed, or replaced, which results in a substantial systematic error. “
Fraudulent Fake Data.
The study goes on to say.
I think you have totally misunderstood what this study emphasizes. Homogenization algorithms DO NOT resolve the systematic uncertainty, they spread it throughout.
Poor Banton still hasn’t figured out that ClimDiv IS AN HOMOGENISED, ie TAMPERED data set.
It is NOT REAL, it us adjusted to try to match USCRN.
They actually state that they homogenise to pristine stations to get rid of urban bias on a regional basis.
Before USCRN existed, there were no “reference sites” so they could not have been “adjusted ” to match the reference sites.
If Horsefather is speaking.. you KNOW you are being conned.
USCRN shows that the ONLY warming in the 2005 -> period came at the 2016 /2017 El Nino, and now from the 2023 El Nino
Before 2015, there was ZERO TREND, and from 2017-2023.4 there was COOLING.
Ah, bless the chief resident conspiracy theorist has joined us.
“ClimDiv IS AN HOMOGENISED, ie TAMPERED data set.
It is NOT REAL, it us adjusted to try to match USCRN.”
You miss the whole point of the paper.
Which is that all global temperature series have an inbuilt warm bias due to algorithms that take account of age deterioration.
The USCRN proves that they dont.
AS – it being free of said algorithm – it does’t show a cool bias in respect of comparison to USHCN.
Ie USHC+warm bias (alleged) >(warmer than) USCRN.
It isn’t (in fact it’s the opposite)
Therefore there is no warm bias evident in the alleged algorithm applied due to aging.
Then of course we have the absurd argument of last resort of the failed skeptic – that a nefarius *someone* has added to the observed temps at source.
If that makes yer world go around then that’s fine with me Oxy.
More fun to be had at your expense.
OMG you really have a ZERO grasp on reality.
The Gistemp data has the urban bias removed, by homogenisation to USCRN
“USHC+warm bias (alleged) >(warmer than) USCRN.
It isn’t (in fact it’s the opposite)”
A moronic statement showing you are absolutely clueless about what is being done with the data.
Any “warm bias” has been removed by the homogenisation process.
What is so difficult for you to comprehend.
Why are you so determined to show yourself up as a complete idiot ??
There is absolutely NO WAY you can make any statement about anything by comparing homogenised Gistemp to real USCRN.
Your logic is completely and utterly twisted and moronic !!
I look at the chart and I can’t see a crisis
Here is what NOAA itself admits regarding USCRN temperature measurement data under “IMPORTANT NOTES”: (ref: https://www.ncei.noaa.gov/pub/data/uscrn/products/monthly01/readme.txt ):
“I. On 2013-01-07 at 1500 UTC, USCRN began reporting corrected surface temperature measurements for some stations. These changes impact previous users of the data because the corrected values differ from uncorrected values. To distinguish between uncorrected (raw) and corrected surface temperature measurements, a surface temperature type field was added to the monthly01 product. The possible values of the this field are “R” to denote raw surface temperature measurements, “C” to denote corrected surface temperature measurements, and “U” for unknown/missing.”
(my bold emphasis added)
Not so “pristine” after all.
I wish, and I am sure many here wish also, that there be just one silver bullet that would put this “global w, climate c. weather weirding to rest, but no. It won’t happen. While I am definitely intrigued by the statements regarding the deterioration of the housings, this isn’t even a start. Just something to be known, and possibly brought out at the right moment in a troll battle.
Does the “harshness” of the environment accelerate matters?
Difficult to see that it wouldn’t. Tropics/poles, countryside/urban, sunshine/UK …
Yes, of course it matters. Different temperature/humidity exposures over time.
That DOI doesn’t seem to work: https://doi.org/10.53234/scc202408/21
Is there a corrected one?
The paper is actually 3 years old, and there was adiscussion here 2 years ago …
https://wattsupwiththat.com/2022/08/30/systemic-error-in-global-temperature/
https://osf.io/preprints/osf/huxge
The screenshot in the post clearly shows: “Vol 4.2(2024)”. No way it can be three years old.
“Climate Scientist” model calulaions imply AB is right 😀
. . . as run on a 1983 Commodore 64 home computer? 😃😃
This is the link given to the paper in the Aug ‘22 WUWT article …
https://osf.io/preprints/osf/huxge
Says (at bottom) “Submitted: October 29, 2021
Last edited: November 01, 2021”
And this is the one given by Busing a month ago on his LinkedIn page (apparently now having “passed peer review”). So taken 3 years for it to pass, presumably, as I see no changes in the paper..
https://www.linkedin.com/posts/moritz-b%C3%BCsing-290326142_moritz-b%C3%BCsing-systematic-error-in-global-activity-7237377285668933632-b_2O
The preprint was in 2022 according to your link. That was two years ago.
The date on the printing of the paper is 2024.
Far from “being old”. That is very much a troll deflection.
Why can’t you address the real issue of ignoring uncertainties in measurements, both random and systematic.
Why would you believe measurements that can’t meet ISO/IEC 17025 Accreditation? The world is spending trillions based on data that the legal system would not accept in a DUI case!
Tell where the ASOS ±1.8°F measurement uncertainty of each measurement disappears in the propagation of uncertainty calculations.
Tell how you compare ASOS measurements with a ±1.8°F with CRN ±0.3°C.
Sorry – no rabbit-hole descents for me.
“The preprint was in 2022 according to your link. That was two years ago.”
See above.
“no rabbit-hole descents for me”
You already live in the equivalent of a mental rabbit hole.
You can’t get much deeper.
Your whole complaint appears to be that the paper is three years old. Maybe you should follow your own hollow complaint and only quote papers that are two years old or less.
Anthony didn’t complain that it was 3 years old, he pointed it out with a couple of links to someone for whom the posted link wasn’t working. He also pointed out that the author posted here about this paper two years ago as he was having difficulty getting it accepted for publication.
https://wattsupwiththat.com/2022/08/30/systemic-error-in-global-temperature/
Thanks for the info, Anthony.
The journal page for the paper is here:
https://scienceofclimatechange.org/moritz-busing-systematic-error-in-global-temperatures-due-to-weather-station-ageing/
With some difficulty I found the DOI:
https://doi.org/10.53234/scc202407/21
The preprint also has a DOI, too:
https://doi.org/10.31219/osf.io/huxge
You’re right, it is nearly 3 years old.
Silly me, the correct doi is in the .pdf, on page 1.
If this is true, then getting from the Little Ice Age to now is due to a tiny increase in global temperature. Almost small enough to be entirely due to small fluctuations in solar irradience.
Most of the warming is at night which is how you move the tree lines and glacier terminuses the most.
So the question is the climate is changing, the only problem is how much and which way has not been answered. That been my position all along. Even worse we have no way to accurately measure the changes. All methods have flaws. Models are worthless since the data is not known to be correct. Climate models GIGO. Yet I betters tell us they know best. We desperately need a new set of elites since the one we got certainly aren’t elite in any measure other than in putting out adult male bovine manure.
Table 12.12 on P.90 of Chapter 12, 2021 UN IPCC AR6 WGI shows no increase in extreme weather in historical records. Tendentious arguments over global temperature measurements doesn’t change the various climates’ physical facts.
The minor temperature increase since the end of the Little Ice age has actually resulted in a more benign climate for both flora and fauna. And Man’s production of CO2 has resulted in a significant increase of the Earth’s green mass (flora).
Eat well, Man and beast!
There was no global average temperature before 1920 — there was only a very rough guess of the Northern Hemisphere average temperature with questionable ocean measurements.
The global cooling from 1940 to 1975m as reported in 1975, was significantly reduced in the 1990s, without a good explanation.
We do have global satellite data since 1979
Earth is getting warmer, mainly in the six colder months of the year.
So what?
That’s good news.
It is ridiculous to claim to know the errors in the claimed global average temperatures since 1880 because no one knew the global average temperature until satellites had near global coverage in 1979.
The GAT construct is crap from start to finish
“There was no global average temperature before 1920″
There isn’t one now, either. Not one that’s meaningful.
Three are many questions to analyze data and the people collecting the data. If the people are not honest the data accuracy does not matter.
Are the raw data accurate and appropriate for the conclusion?
Has raw data been adjusted? After adjustments there is no longer data — just an opinion on what the data would have been if measured correctly in the first place
Are the people collecting the data and compiling the data into statistics honest?
Do the statistics tell us anything important?
Do the statistics obscure important details?
Excellent questions, Richard. First, our betters need at least one college-level course in metrology. Then a college-level course in statistics.
I maintain that there are 3 major faults with all averaged temperatures / anomalies –
The ‘3 Ps’
PROBITY
complete and confirmed integrity
PROVENANCE
history of the ownership of an object
PROSECUTION
style or manner with which something is offered for consideration or display
Basic metrology is not followed at all in climate science. Data is analyzed like using numbers from examples in a high school math class. Find the average, then find another average, and another average. Don’t even think that there are uncertainty involved in the numbers representing measurements. Random variables containing measured observation of a measurand? What does that mean? Only the average is important! Show me a textbook or paper that has completed an uncertainty budget for the measurements being taken.
Look at ASOS uncertainty specified by NOAA, ±1.8°F. Where does this go in an uncertainty budget. This is a Type B uncertainty stated as an uncertainty. The variance associated with this is 3.2 and is what should be used to propagate uncertainty when averaging single measurements using RSS.
How does this result fit with satellite measurement?
They’re measuring different things.
Pretty much identical.
In fact, over the past ~20 years the UAH satellite lower troposphere (TLT) record is warming slightly faster than the NOAA, NASA/GISS and HadCRUT surface data sets.
Maybe the satellites need a paint job?
Nail, you’re wrong. You are just showcasing the statistical correlation between those two datasets.
On the other hand, the accuracy of air temperature measurements can only be validated through field calibration testing.
In respect to UAh it is carried out daily …
https://www.drroyspencer.com/2010/01/how-the-uah-global-temperatures-are-produced/
“Once every Earth scan, the radiometer antenna looks at a “warm calibration target” inside the instrument whose temperature is continuously monitored with several platinum resistance thermometers (PRTs). PRTs work somewhat like a thermistor, but are more accurate and more stable. Each PRT has its own calibration curve based upon laboratory tests.”
It’s a tad difficult to haul it out of orbit every 90 mins to do it on Earth.
That is entirely necessary for a single instrument.
Re: the Global network – there are thousands of separate thermometers in the mix, and it is beyond absurd to imagine there is some systemic bias in the same direction in all of them (or even some) – that isn’t cancelled/negated by others of the opposite bias. All climate related instruents are regularly calibrated to boot.
Just another example of *sceptics* requiring 101% certainty, else we know nothing.
Where is your formal uncertainty analysis of the entire UAH process?
” it is beyond absurd to imagine there is some systemic bias in the same direction in all of them (or even some) – that isn’t cancelled/negated by others of the opposite bias.”
Systematic biases reflect a physical departure from the true state of the world.
You’re mistaken in suggesting that these biases can balance each other out across multiple thermometers. They’re not just abstract numbers that can be adjusted or manipulated.
I tried to emphasize this in my reply to you yesterday (see October 12, 2024, at 9:31 am).
.
Re: the Global network – there are thousands of separate thermometers in the mix, and it is beyond absurd to imagine there is some systemic bias in the same direction in all of them (or even some) – that isn’t cancelled/negated by others of the opposite bias.
What horse hockey. Uncertainties dont work that way unless repeatability conditions are met. That primarily means that THE SAME EXACT MEASURAND be measured. Under repeatable conditions, RANDOM observations of the exact same thing may cancel if the resulting probability distribution is normal.
Systematic uncertainty is unable to be assessed by statistical analysis of a station’s observation. The ‘bias’ is in all observation of a single measurand and presents no probability distribution for analysis. Only a calibration and subsequent correction curve can be used to determine systematic uncertainty of a given device or one must use knowledge and experience to determine the correct value.
You should also know by now that uncertainties are stated as standard deviations. Combined uncertainties are calculated from individual uncertainties of different measurements and the individual uncertainties add, always. Either directly or by RSS. If you have a reference that shows subtracting uncertainties please show us. See GUM 3.3.5, E.4.4, F.2.4.5,
Lastly, tell everyone a component of a weather station that in some cases drift upward and some downward in a random fashion. Do some poorly maintained Stevenson screens cause warmer temps to be read while others read lower temps?
Anthony wrote, “there are thousands of separate thermometers in the mix, and it is beyond absurd to imagine there is some systemic bias in the same direction in all of them (or even some) – that isn’t cancelled/negated by others of the opposite bias.”
If you think it is absurd to imagine systematic biases in the temperature records, which affect the calculated trend, then why have the leading global temperature indexes been corrected for such biases?
Tony Heller resized these three GISS global temperature graphs, of different vintages, so that the vertical (temperature) and horizontal (date) scales match, and them he made them into an animated .gif image to compare them:
In general, the corrections to measured temperatures have tended to increase the general warming trend, and decrease the 1940s-1970s cooling, thus bolstering the “CO2 control knob” narrative. It is suspiciously convenient.
Tony thinks it is due to dishonesty. I suspect that it is not intentional dishonesty, but rather due to the human tendency to find what we’re looking for, and dismiss what we are not looking for.
“A man hears what he wants to hear and disregards the rest.”
– Paul Simon (lyrics, “The Boxer”), 1969
OMG , still using the fact that the atmosphere responds more to El Nino events than the land surface does to to a monkey-with-a-ruler trend comparison.
All that does is continue to make you look like an ignorant moron. !
I don’t need no stinkin’ thermometer to know that winters here in Milwaukee are warmer than they were during the ’60s & ’70s.
I can’t access NOAA info right now, but here is a graph of Michigan state average temperature. As you can see, little change in the high average months (summer) and quite large increase in the average temperature of low months (winter).
The question is if that is related to CO2. It appears to be more related to sunshine and clouds than CO2.
I’ve never seen a more battered Stevenson Screen. The instruments inside must be in an appalling state.
A Stevenson screen that gets dirty over time is one of MANY reasons to not trust surface temperature measurements. Ocean measurements are even less reliable until about 1979 with UAH and 2020, with ARGO.
Let’s think about this Stevenson screen problem that would affect ONLY land temperature stations. But could ONLY affect the daytime high temperature (TMAX), NOT the low temperature at dawn, or up to 1/2 hour after dawn (TMIN), with very little sunlight.
Land surfaces are 29% of the planet
TMAX is 50% of the average surface temperature
That means dirty Stenson screens could only affect 29% x 50%, or 14.5%, of Earth’s surface grid temperatures.
How much extra Stevenson screen warming would there have to be of 14.5% of Earth’s surface area grids to cause the average temperature to be overstated by 42%?
The answer is +2.9 degrees C.
Land TMAX averages would have to be overstated by +2.9 degrees C. to cause the global average temperature to be 42% too high, as claimed in the study. I find that claim impossible to believe.
As usual, Ken Richard writes about studies that are irrelevant for the study of the long term effect of manmade CO2 emissions. Or they are junk science theories.
So what? You are just as ignorant about metrology as the usual climatologist.
As usual RG stuffs up any meaning in his comment by ranting a whole lot of evidence-free gibberish…
.. inserting mindless, dumb opinions that are irrelevant to anything real,
… added to his hated of anyone, like Kenneth, who is a far better person and scientist than RG is ever capable of being.
Richard wrote, “this Stevenson screen problem that… could ONLY affect the daytime high temperature (TMAX), NOT the low temperature at dawn, or up to 1/2 hour after dawn (TMIN), with very little sunlight.”
That is a very excellent point, Richard, and I’m embarrassed that I didn’t think of it. Than you for pointing it out.
Since the observed warming trend is mostly an increase in nighttime lows, especially in winter, rather than an increase in summer daytime highs, it suggests that problems with Stevenson screens could not be responsible for much of that trend.
So, what could cause diurnal and seasonal temperature differences to decrease? An explanation I’ve seen is that in summertime agriculture is increasing humidity. Fast-growing crops pump a lot of moisture into the air via transpiration, even if they aren’t irrigated, the more so if they are irrigated.
Dry places tend to have large diurnal temperature ranges. Moisture reduces daily highs, as evaporation & transpiration cool the surface, and it increases daily lows, as condensation of dew reduces the rate and extent of cooling at night.
GIGO
I read a book decades ago that countered the Inconvenient Truth and was one of the first that did so. Sorry, I can not find the book and do not remember the author’s name.
One of the things noted was the paint on those thermometer boxes was changed from whitewash to latex and the difference amounted to 1 to 1.5 C higher readings.
This seems to be in the same category.
I came across a paper where the difference in the smaller ASOS housings made a significant difference in temperature readings. I can’t find it now, but the point is valid.