From Dr. Roy Spencer’s Global Warming Blog
by Roy W. Spencer, Ph. D.
The Version 6.1 global average lower tropospheric temperature (LT) anomaly for November, 2025 was +0.43 deg. C departure from the 1991-2020 mean, down from the October, 2025 value of +0.53 deg. C.
The Version 6.1 global area-averaged linear temperature trend (January 1979 through November 2025) remains at +0.16 deg/ C/decade (+0.22 C/decade over land, +0.13 C/decade over oceans).
The following table lists various regional Version 6.1 LT departures from the 30-year (1991-2020) average for the last 23 months (record highs are in red).
| YEAR | MO | GLOBE | NHEM. | SHEM. | TROPIC | USA48 | ARCTIC | AUST |
| 2024 | Jan | +0.80 | +1.02 | +0.58 | +1.20 | -0.19 | +0.40 | +1.12 |
| 2024 | Feb | +0.88 | +0.95 | +0.81 | +1.17 | +1.31 | +0.86 | +1.16 |
| 2024 | Mar | +0.88 | +0.96 | +0.80 | +1.26 | +0.22 | +1.05 | +1.34 |
| 2024 | Apr | +0.94 | +1.12 | +0.76 | +1.15 | +0.86 | +0.88 | +0.54 |
| 2024 | May | +0.78 | +0.77 | +0.78 | +1.20 | +0.05 | +0.20 | +0.53 |
| 2024 | June | +0.69 | +0.78 | +0.60 | +0.85 | +1.37 | +0.64 | +0.91 |
| 2024 | July | +0.74 | +0.86 | +0.61 | +0.97 | +0.44 | +0.56 | -0.07 |
| 2024 | Aug | +0.76 | +0.82 | +0.69 | +0.74 | +0.40 | +0.88 | +1.75 |
| 2024 | Sep | +0.81 | +1.04 | +0.58 | +0.82 | +1.31 | +1.48 | +0.98 |
| 2024 | Oct | +0.75 | +0.89 | +0.60 | +0.63 | +1.90 | +0.81 | +1.09 |
| 2024 | Nov | +0.64 | +0.87 | +0.41 | +0.53 | +1.12 | +0.79 | +1.00 |
| 2024 | Dec | +0.62 | +0.76 | +0.48 | +0.52 | +1.42 | +1.12 | +1.54 |
| 2025 | Jan | +0.45 | +0.70 | +0.21 | +0.24 | -1.06 | +0.74 | +0.48 |
| 2025 | Feb | +0.50 | +0.55 | +0.45 | +0.26 | +1.04 | +2.10 | +0.87 |
| 2025 | Mar | +0.57 | +0.74 | +0.41 | +0.40 | +1.24 | +1.23 | +1.20 |
| 2025 | Apr | +0.61 | +0.77 | +0.46 | +0.37 | +0.82 | +0.85 | +1.21 |
| 2025 | May | +0.50 | +0.45 | +0.55 | +0.30 | +0.15 | +0.75 | +0.99 |
| 2025 | June | +0.48 | +0.48 | +0.47 | +0.30 | +0.81 | +0.05 | +0.39 |
| 2025 | July | +0.36 | +0.49 | +0.23 | +0.45 | +0.32 | +0.40 | +0.53 |
| 2025 | Aug | +0.39 | +0.39 | +0.39 | +0.16 | -0.06 | +0.69 | +0.11 |
| 2025 | Sep | +0.53 | +0.56 | +0.49 | +0.35 | +0.38 | +0.77 | +0.32 |
| 2025 | Oct | +0.53 | +0.52 | +0.55 | +0.24 | +1.12 | +1.42 | +1.67 |
| 2025 | Nov | +0.43 | +0.59 | +0.27 | +0.24 | +1.32 | +0.78 | +0.37 |
The full UAH Global Temperature Report, along with the LT global gridpoint anomaly image for November, 2025, and a more detailed analysis by John Christy, should be available within the next several days here.
The monthly anomalies for various regions for the four deep layers we monitor from satellites will be available in the next several days at the following locations:
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It’s cold outside.
It’s cold inside and I need my slippers.
I will be putting on slippers when I get home. 🙂
Savor it while you can.
Spoken like a stage 4 doomster.
And what level of denier is “it’s cold outside?”
What level of moron asks such a question?
A lot lower than the deniers who look out their window and pronounce that because it is cold, there must be no global warming. That’s a special level of moron.
I mean come on, you really have to want climate change not to be real, to expose that level of stupid to the world… don’t you?
Saying it’s cold outside does not deny warming. High level of stupid to say that.
No, we want temperature measurements to be treated scientifically.
These are just some of the things that are done everyday in certified labs. Climate science should emulate the practices followed in those labs.
I enjoy heat from affordable natural gas when it’s needed. I don’t enjoy being needlessly cold.
Third warmest November in the UAH records.
The warmest Novembers are
So far in 2025, each month has been either 2nd, 3rd or 4th warmest.
It’s now almost certain that 2025 will be the second warmest year. My simplistic projection is for 2025 to finish at 0.48 ± 0.03°C.
Here’s the graph of all November anomalies.
For fans of the pause, there has been a negative trend since March 2023, a pause of 2 years 8 months.
For fans of the idea that a 6 year trend has any meaning, the trend over the last 6 years is 0.78°C / decade.
For fans of the previous pause, the trend since it started in June 2014, is now 0.36°C / decade.
So it is a little warmer almost every year, Bellman.
The question is “What is causing the increase?”
My guess is that it is the ending of the Little Ice Age but I can’t see any great CO2 influence.
So, Bellman, what do you think is causing the slow warming and why is it important?
There is a no evidence of any human caused warming in the whole of the UAH data.
There is , in fact, no measured scientific evidence that human CO2 has any effect whatsoever on the climate.
And the answer is the precession of Earth’s orbit and the Sun’s movement as well as the corresponding solar activity..
The high peaks are a consequence of northern excursion of the Sun and associated solar activity as well as the solar activity associated with southern excursions.
The next peak will be around 2035. The corresponding solar cycle is a big one as well.
As you can see, 1982 was the most southern excursion in this 60 year time period. A good time to start the Global Warming™ scam knowing that the northern hemisphere has 3.3X the thermal response as the Southern Hemisphere.
Rather, that’s the new question.
The old question here at WUWT is ‘can we trust the data’?
Now that every global temperature data set we have shows the same rate of statistically significant warming over the long term (~30-years), within their respective error margins, not to mention the evidence of our own senses, the old question has been answered in the affirmative.
As fake ‘climate skeptics’, we just move from that early step of denial of reality to the next. And we must never, ever admit that we were wrong about the the old question; even though having to ask the new questions confirms that we were.
Show us the warming in UAH that is NOT associated with El Nino events.
You have failed magnificently at all attempts so far.
Seems the only “deniers” of reality here are you and your hysterical AGW comrades.
What has that to do with the fact that, at best, you can’t even make up your mind whether adding CO2 to air makes thermometers hotter?
First you imply it does, then you agree that it doesn’t, then you backtrack and refuse to commit yourself one way or the other.
Willis Eschenbach claims he is smarter than a rat. Do you claim you are more or less cunning than that same rat? I don’t believe you are more cunning than a rat, but feel free to correct me.
You really are a confused little thing aren’t you.
Ummmm . . . would that be for total global surface area, only over land, only over oceans, for NH or for SH, for the tropics, for the USA48, for the “Arctic”, or for Australia?
If not for ALL of the above areas, now what?
Ot a single data point in the table is shown with an associated measurement uncertainty or variance. We are supposed to believe all measurements are 100% accurate.
As always. Your problem is with the UAH data, not with me. If you want uncertainty estimates for UAH, take it up with Spencer and Christie.
But for some reason you always go on about how inaccurate UAH data is when I comment on it, but not when Monckton was using it for his pause.
El Nino events break the zero or cooling trends.
We have just had a major El Nino event.
The trend from 2017 to just before that event was downwards.
Your silly repeated analysis is a total waste of your time and everyone else’s….
It is meaningless because it relies TOTALLY on El Nino events.
This third warmest November on record occurred during weak La Nina conditions, so….?
Third warmest where? Averaging temps is nonsense, no matter who does it.
Thank you for your opinion, which no one in the scientific community shares.
The effects of the El Nino still linger.
What is your point !
Or do you DENY that there has just been a strong El Nino that stands out like *** *** in the UAH data.
A spike that was not caused by anything humans have done.
As always, Spencer releases the headline temperature long before they release the full data. So I can’t tell you where specifically it was warmest.
That’s OK . . . I can wait for your reply.
I’ve examined the UAH tabulated monthly data (it starts in December 1978) closely across each of the various geographical regions that I listed above and know that there is NO consistent agreement for specific annular calendar months in terms of their respective temperature variations, let alone their top-ten warmest-months-by-year.
BTW, for all WUWT comment readers, the full UAH data set for average lower atmospheric temperatures over the various regions I mentioned—currently tabulated by calendar month from Dec 1978 through Aug 2025—is downloadable as a text file as enabled by the red hyperlink Lower Troposphere given near the bottom of the above article.
This data can, in turn, be copied into an Excel spreadsheet (using the space-delimited text-to-columns command under the Excel “Data” pull-down menu) for easy, subsequent use and sorting by various aspects/characteristics, such as max and min, using Excel (or equivalent spreadsheet software).
Maybe the three month delay in tabulating and publishing the range of data by geographical area after releasing the “headline temperature” (your words) is deserving the criticism of being “long” . . . in my world, it is not.
“the full UAH data set for average lower atmospheric temperatures over the various regions I mentioned”
As is mentioned every month. Usually it’s not updated for a few days, and often somewhat longer. But this month you are in luck as it’s already been updated for this month. Hopefully the gridded data will be updated soon as well.
“…there is NO consistent agreement for specific annular calendar months in terms of their respective temperature variations…”
Why would you expect there to be? Every month some parts are warmer than average, some cooler. It would be a very suspect coincidence if the entire globe had the same anomaly.
For land, this was the 3rd warmest November, only 0.06°C of an all time record.
UAH: Land
The oceans were somewhat cooler – only the 7th warmest November
UAH: Ocean
The Northern Hemisphere was also the 3rd warmest
UAH: NH
Whilst the Southern Hemisphere was the 5th warmest
UAH: SH
Here’s a comparison of land and ocean for November anomalies.
It is interesting how much of a discrepancy there is between the two this month. Usually when the oceans cool rapidly there’s a similar drop in land temperatures, but this hasn’t happened so much the last two years.
And here’s a similar comparison of the two hemispheres.
Above you said it was the third warmest Nov.
Here you say – 3rd, 7th, 3rd and 5th.
How do you get 3rd average from that?
Oh, I agree completely . . . which is the reason I’m baffled as to why you claimed in your previous post:
“Third warmest November in the UAH records.
. . .
So far in 2025, each month has been either 2nd, 3rd or 4th warmest.
It’s now almost certain that 2025 will be the second warmest year. My simplistic projection is for 2025 to finish at 0.48 ± 0.03°C.”
“which is the reason I’m baffled as to why you claimed in your previous post”
I always hope it’s obvious from the context that I’m talking about the global monthly average – given it’s the title of this article:
“ three month delay” ??
Data is up for all regions for November.
nsstc.uah.edu/data/msu/v6.1/tlt/uahncdc_lt_6.1.txt
Yes….. sometimes it takes him a week or two, and we have to be wait.. 😉
Right, so we have to wait for Bellman to do the calcs, even though you just posted a link to the data?
Are fake skeptics incapable of downloading data and checking stuff for themselves?
(Rhetorical question.)
“ incapable of downloading data and checking stuff for themselves?”
That’s very introspective of you.
Now THAT’s funny . . . when I access the link you provided the resulting text file has the month of October (“2025 10”) as the line line of compiled data, not the month of November.
Maybe you should check it out.
“It appears, what we have here, is a failure to communicate.”
— famous line in a classic movie
My typo in the first paragraph of my reply above . . . the ending should have read “. . . as the
linelast line of compiled data, not . . .”Or you could even check it for yourself, once it’s out.
Anything else you need done for you?
TFN, give him a break. He’s still trying to figure out whether he thinks that adding CO2 to air makes thermometers hotter!
Not the most decisive ignorant and gullible cultist in the consensus!
What are you trying to imply? That adding CO2 to air makes thermometers hotter?
Or something else?
Obviously, if adding CO2 to air made it hotter, then every November and every other month as well should be the hottest ever.
Now you are just as ignorant and gullible as before – unless you can prove otherwise.
Fair?
Nice data-centric chart-supported view and analysis
of 1,000 years from a possible 4,000,000,000 year data set.
Words like “warmest” and “coldest” don’t apply here, especially when trustworty data
is less than 100/4,000,000,000 the span that would show trends and patterns.
It was a lot warmer when my parents were children.
How do you know?
Real un-corrupted data shows it was warmer during the 1930s and 1940s.
How does this prove CO2 is the causal factor. It shows the Little Ice Age as being very low. One would expect a natural warming from this low.
Global Average Temperature is an unphysical nonsense, especially when it is calculated with little or no data from the Southern Hemisphere, as is the case for GAT before the satellite era.
OK pick a recognised data set that supports your “there has been no warming” case.
Who is saying ”there has been no warming” ?
Simon, unless your parents were born before you were, then this chart isn’t helping your case.
1958 and 1997 were exactly the same temp. Your chart is an abomination.
Deniers love unsourced graphs.
Geophysical Research Letters. ”Radiosonde revisited”.
And denying what? That Simons graph represents reality? I just showed it doesn’t.
Care to post a link?
That’s why I said “in the UAH record”.
Which is FAR below the temperatures of most of the last 10,000 years.
Only the LIA, and the period around 1979 were colder.
The Little Ice Age (LIA) is generally accepted to have occurred from about 1300 to 1850 AD, an interval of only about 550 years.
The Holocene Climate Optimum (HCO) occurred about 6,000 years ago. Today’s best scientific evidence is that the peak then in “average” global temperature was similar to—perhaps only slightly warmer by a few tenths-of-a-degree C than—today’s “average” global temperature.
Therefore, in fact, MOST of the time over the last 10,000 years Earth’s “average” global temperature has been colder than temperatures experienced over the last 200 or so years.
WRONG. There is massive amounts of evidence from all around the world that most places were a few to several degrees warmer than now during the Holocene optimum.
DO NOT fall victim to activist propaganda fabrications and “averaging.”
Here’s a recent one in China..
There is data more recent than that from 2018 (which your featured in you post above) that says you are incorrect
See the article at https://www.rutgers.edu/news/important-climate-change-mystery-solved-scientists , dated February 16, 2021, where you’ll find these statements (my bold emphasis added):
“Scientists have resolved a key climate change mystery, showing that the annual global temperature today is the warmest of the past 10,000 years – contrary to recent research, according to a Rutgers-led study in the journal Nature. . . . The scientists say their findings will challenge long-held views on the temperature history in the Holocene era, which began about 12,000 years ago.”
The abstract of the referenced Nature article (available at https://www.nature.com/articles/s41586-020-03155-x ) goes a bit further with this concluding statement:
“Furthermore, our reconstructions demonstrate that the modern global temperature has exceeded annual levels over the past 12,000 years and probably approaches the warmth of the last interglacial period (128,000 to 115,000 years ago).”
DO NOT fall victim to using outdated data to support an argument.
That’s is: you should have understood my phrase “Today’s best scientific evidence is . . .”
Science made to order. Lol.
This paper refers to the existence of huge quantities of land ice in the northern hemisphere which would have significant effects on the Earth’s albedo and the atmospheric temperature near it while it was melting. That ice melting resulted in a ~60m rise in sea level by 6000BP!
And one on SSTs around Iceland.
And from Antarctica.
I could produce these studies for many dozens of post..
… but I can’t be bothered.
Made up, on the spot, drivel. There is tons of proxy (and actual) evidence that even the MWP and the RWP were warmer than today, let alone the HCO.
OK, please produce just one pound of those asserted “tons of proxy (and actual) evidence” that has been published, say, within the last five years.
Why? But here’s a pretty picture to hang on your wall. And before you say ”that was just local”, wait till I get a bucket.
Ummmm . . . the MWP began around 950 AD, so that would be about 1075 years ago. However, according to the caption under the photo that you posted, the youngest of the trees revealed by the retreating Mendenhall glacier is dated to be 1200 years old . . . so in reality, the photo is irrelevant regarding global temperatures conditions at that specific location during the MWP, other than the fact that the “ancient” (hah!) dead trees there were under glacial ice.
“Only the LIA, and the period around 1979 were colder.”
I really should know better than to reply, but 1979 was at the time one of the warmest years since middle of the 19th century.
We are talking measured temperatures around the globe, not some doctored activist fabrication from sparse and fabricated data.
There is no way they knew the “global” temperature for most of the period shown…. The measurements just DID NOT EXIST.
Basically every continent shows around 1979 as the coldest period since the warmer 1940s
Even Briffa’s tree rings show it.
“There is no way they knew the “global” temperature for most of the period shown”
Yet some how you know the global temperature going back thousands of years. And know that globally 1979 was colder than the test of the 20th century.
Why would you think a few trees are going to give a more accurate measurement of temperature than hundreds of thermometers?
Yeah . . . you really should know better. If you go up-thread you will find that this particular thread started with bnice2000’s post:
So your posted graph showing a peak anomaly in the period of 1850–1979 AD (at the top of the graph) says nothing about temperature swings over the remaining 99% of that time interval.
I was specifically addressing the claim that only the period around 1979 was colder.
Wherefrom the 1,000 years? UAH data tabulation starts December 1978, as do Bellman’s graphs.
Didn’t see any “analysis” of 1,000 years of data.
I’m guessing Antarctica was warmer before it was covered by a few km of ice, but your analysis may convince me otherwise.
Go your hardest.
All hunga Tonga years
The Hunga Tonga–Hunga Haʻapai (HTHH) eruption occurred on January 15, 2022., the Tonga eruption injected an enormous amount of water vapor—about 146 million tons—into the stratosphere. Water vapor is a greenhouse gas, so this extra moisture has contributed to a temporary warming effect that is expected to persist through 2026..
Hah! In rebuttal:
“The water vapor anomaly increases the net downward IR radiative flux whereas the aerosol layer reduces the direct solar forcing. The direct solar flux reduction is larger than the increased IR flux. Thus, the net tropospheric forcing will be negative.“
— “The Estimated Climate Impact of the Hunga Tonga-Hunga Ha’apai Eruption Plume”, Schoeberl et al., Geophysical Research Letters, 26 September 2023 (quote from abstract, my bold emphasis added)
[download available at https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023GL104634 ]
“We use satellite observations of stratospheric aerosols, trace gases and temperatures to compute the tropopause radiative flux changes relative to climatology. Overall, the net downward radiative flux decreased compared to climatology. . . . The Hunga aerosols cause a solar flux reduction that dominates the net flux change over most of the 2 yrs period. Hunga induced temperature changes produce a decrease in downward long-wave flux. Hunga induced ozone reduction increases the short-wave downward flux creating small sub-tropical increase in total flux from mid-2022 to 2023. By the end of 2023, most of the Hunga induced radiative forcing changes have disappeared.”
— “Evolution of the Climate Forcing During the Two Years After the Hunga Tonga-Hunga Ha’apai Eruption”, Schoeberl et al., Journal of Geophysical Research: Atmospheres, Volume 129, Issue 14, July 2024 (quote from abstract, my bold emphasis added)
[abstract available at https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023GL104634 ]
And there is this too:
“When Hunga Tonga–Hunga Haʻapai, an underwater volcano near Tonga in the South Pacific Ocean, erupted in 2022, scientists expected that it would spew enough water vapor into the stratosphere to push global temperatures past the 1.5 C threshold set by the Paris Accords. A new UCLA-led study shows that not only did the eruption not warm the planet, but it actually reduced temperatures over the Southern Hemisphere by 0.1 C.
The reason: The eruption formed smaller sulfate aerosols that had an efficient cooling effect that unexpectedly outweighed the warming effect of the water vapor. Meanwhile, the water vapor interacted with sulfur dioxide and other atmospheric components, including ozone, in ways that did not amplify warming.”
— “Hunga volcano eruption cooled, rather than warmed, the Southern Hemisphere”, Holly Ober, April 2, 2025 (my bold emphasis added), https://newsroom.ucla.edu/releases/hunga-volcano-eruption-cooled-southern-hemisphere , with an embedded hyperlink to the full text of the UCLA-led study publication of March 2025 in Nature: Communications Earth & Environment that is available at https://www.nature.com/articles/s43247-025-02181-9 .
This and previous references I cited go a long way toward explaining the fact that UAH satellite-based measurements of GLAT temperatures only began to rise above the UAH satellite-established trend line some 14-16 months AFTER the HT explosion and injection of water vapor into the stratosphere.
Objectivity oft loses to confirmation bias.
Nice weather. Be happy. Fewer people freezing in Europe due to energy poverty.
Bellman
Isn’t it comical how the WUWT crowd will downvote an informative comment like yours, while upvoting statements like ‘It’s cold outside’?
I guess that’s where they hit their cognitive ceiling. Everything beyond that seems to overload the system.
Well, some of us can comprehend the difference between cold and hot conditions.
Which is very helpful in how to live with
“coupled, non-linear, chaotic weather systems”.
You’ve mastered the difference between hot and cold. That’s a great start. The next step is understanding how individual sensations don’t substitute for climate statistics.
and conversely, climate statistics don’t substitute for real-world observations.
btw – which climate’s statistics are you referring to?
There’s gazillions of climates all around the world, including your “Intermountain West” one which you singled out in your comment below.
Climate is the statistics of weather observations, so you are waffling about the statistics of statistics!
Are you confused or stupid?
yes
I found November pleasant. When is the world going to end?
I don’t know but our unseasonably warm autumn here in the Intermountain West wasn’t pleasant considering the snow deficit, which is a real issue when that’s your reservoir for summer water.
Seems clanger doesn’t know the difference between weather and climate.
Then neither does David, since he was the one who mentioned his pleasant November, and I simply shared my own experience in response.
Ooooh!
A real zinger – no doubt David has been reduced to a blubbering jelly!
The weather around Colorado of late has been pretty consistent with La Nina patterns. Nevertheless, I hear there is good skiing in the mountains, and coincidentally, the Denver area is getting it’s first big snow of the season tomorrow.
speaking of weather.. Snow in summer in Australia.
Snow, bitter cold, on first day of Australian summer
From that article
My state had the coldest spring for 25 years. Pretty unusual I’d say….
Which state is that? According to UAH Australia overall had the second warmest spring, the coldest in 2 years.
Can’t find it but hear it from the BOM a few weeks back. But this from AI..
”November 2025 in Melbourne was unusually cold, with reports of it being the coldest November for 21 years and only one day with a temperature near 30∘C30 (which was an anomaly).”
According to the BOM summary, Spring was above average in all states apart from Tasmania.
But Tasmania was the coldest in over 50 years
And minimum temperatures were cold in some parts.
If you are talking just about Melbourne, and just November, then that does appear to have been cold.
https://www.bom.gov.au/climate/current/month/vic/melbourne.shtml
Funny how warming from CO2 can vary so much. Location to location, day and night, station to station. Enough to make one think the sun may have something to do with it.
Funny how you think the sun’s warming varies from day to day. But nothing else varies. In the real world there are multiple factors that effect the regional daily temperature.
In England last month we saw temperatures drop from near record highs to unusually cold in a matter of a few days. No-one suggested this was because the sun suddenly got colder or there was less CO2 around. It’s much more to do with weather systems, which direction the winds from and where the jet stream is.
Would it be better if it were colder than 1850?
Does it matter?
For the people dying in cold exposure, it could.
And 10 times as many people die from cold as from heat.
So warming is GOOD !
That is why the bulk of human population lives in lower latitudes rather than higher latitudes.
You tell me. You’re berating us for denying something. But there’s no doubt that warmer is better, unless you’re a moron.
Nah, even your average moron prefers being warm, rather tha; freezing to death.<g>
Don’t you know?
Drought in the Intermountain Region:
Scientific knowledge of drought dates back to 800 AD in the Intermountain Region. The longest drought lasted 71 consecutive years, and 28 droughts of 10 years or longer have occurred (Allen et al. 2013, DeRose et al. 2014, 2015). Records show that recent history (1940-present) has been far wetter than the rest of recorded history (DeRose et al. 2015).
USDA:https://share.google/5wuGdnPRLr9VPJpex
The sky is not falling. This is an acorn, hitting you on the head.
Oh! No! The sky is falling.
When is the world going to end?
Ask Greta. Erm. No. Answer is yesterday. Did you miss it? 🙂
When is the world going to end?
****
That is what I have always wanted to know. The climate alarmists never seem to give me a date when the climate crisis is supposed to start killing us all off. Just the year will do.
I really would like to know so I can start preparing for it. Our sun isn’t supposed to go nova for–what–another billion years?
/sarc
Good question… 🙂
“when the climate crisis is supposed to start?”
No sign of any “climate crisis”…. anywhere !
In your dreams.
All observational data points to no crisis. It’s very telling when people like you eschew that for their feelings.
You like trending anomalies which when averaged tell you nothing about temperature. -50F -> -49F I still damn cold. 50F ->51F is ho hum who cares.
Tell us what the standard deviation is for the absolute temperatures used to calculate the anomalies so we can have a clue of what is changing.
You can do this analysis by yourself.
Oh, are you accepting that he has superior mathematical skills to you, or are you purposely being unhelpful?
I can and have done a bunch of analysis on station data. However, you are the one making assertions therefore you are the one that should have the analysis that should be used to support those assertions, not me.
I also note that you are using deflection as a tool for arguing. That is a fallacy. Shame, shame.
Here is something you can address to explain why comparing anomalies is a scientific procedure.
This is a graph of monthly Tmax. Look at the summer values. Have they increased dramatically? Not really.
Now look at winter max values. Have they increased dramatically? You bet. Since ~1980 winter max temps have gone up by a large amount.
What do you think this does to an average of anomalies? Will that average give an accurate view of what is occurring?
Will anomalies of Tavg be any better or more accurate?
The average maximum temperature anomaly for the CONUS shows a warming trend of 0.15°F per decade since 1895, and 0.55°F per decade since 1979.
Temperature anomalies are calculated by subtracting the average values from a fixed baseline. This doesn’t change the value of the original data.
https://www.ncei.noaa.gov/access/monitoring/national-temperature-index/time-series/anom-tmax/1/0
It’s interesting that your graph shows that the 1930’s were exceptionally hot, and clearly hotter than today.
“You like trending anomalies which when averaged tell you nothing about temperature.”
You still never seem to grasp that UAH data is from satellites. It’s estimating the temperature in the lower troposphere. The absolute temperatures are cold all over the globe. They tell you little in isolation, but it is claimed that the change in temperature is related to the change on the surface.
All I needed to read was:
“You like trending anomalies which when averaged tell you nothing about temperature. -50F -> -49F I still damn cold. 50F ->51F is ho hum who cares.”
It’s known that a shift in the mean isn’t trivial. It alters the entire distribution, including the tails where the extreme events occur. The extremes have profound impacts on ecosystems and people.
I get the impression Jim is processing this at the level of experiencing one degree warmer or cooler on his skin while walking to the mailbox.
Wait until you have the conversation with the contrarians that what they think is an instantaneous spot temperature is actually…wait for it…an average since most automated stations today follow the ASOS or similar protocol in which the reported temperature on the METAR report is actually the average of 30 temperature readings taken 10s apart over a 5 minute period. They claim that an average temperature is meaningless and nonsensical, but have no problem using average temperatures in their posts when they are blissfully aware that they are doing so.
Um, the ASOS averages T readings from a single RTD thermometer at a single location, to simulate the response of an LIG thermometer. BIG difference.
Well that was a load of gibberish.
Do you really think surface stations , almost always in expanding urban areas or at airports, in ANY WAY represent the actual global surface temperature.
That is bizarre !!
Way to deflect from the point.
No, they believe that they represent the temperature of the Earth – interior, surface and all. What a pack of clowns!
You should include quotes of what was said when referencing what someone says.
You haven’t learned anything over the years about measurements.
What is a proper measurement? Let’s look at a measurement made under repeatability conditions. From JCGM 100:2008.
So let’s look at an ASOS measurement.
the same measurand ✓
the same measurement procedure ✓
the same observer ✓
the same measuring instrument, used under the same conditions ✓
the same location ✓
repetition over a short period of time ✓
In an uncertainy budget, a catsgory of repeatability can be be a type A evaluation of the observations. See Note 3
Now let’s see what remains when measuring a temperature at another stations.
the same measurand
✓the same measurement procedure ✓
the same observer
✓the same measuring instrument, used under the same conditions
✓the same location
✓repetition over a short period of time ✓
The condions for repeated measurements are not met.
Averaging these two temperatures to obtain an average temperature is meaningless because temperature is an intensive property. Averaging temperatures do not result in another temperature. The average can however be defined as a property.
JCGM 100:2008 gives a method to determine a property by using sampling.
NOAA has provided the uncertainty of a single sample for an ASOS station, ±1.8°F. The variance between the “samples” should also be added to the variance of the single sample.
Note, variance means the standard deviation squared and not the experimental standard deviation of the mean, i.e. divide by √n.
“They claim that an average temperature is meaningless and nonsensical, but have no problem using average temperatures in their posts when they are blissfully aware that they are doing so.”
A GLOBAL average is meaningless. What you’ve done is make a strawman.
I made no such strawman. See Kip Hansen’s article.
https://wattsupwiththat.com/2022/08/09/numbers-tricky-tricky-numbers-part-2/
And paint with a very broad brush.
The mean has just shifted from 5 to 5.00000001.
Seems pretty trivial to me.
You bet I am.
Now answer which is closer to an optimum temperature for the globe. Where did humans evolve and what was the average temperature? Do global averages of temperature or anomalies give you any clue of a good place to live?
Don’t be just a numbers is numbers guy who mines data to find a number that has no physical meaning.
Now address what a changing mean and variance mean in a time series. Here is an article that begins discussing what is necessary.
https://www.numberanalytics.com/blog/advanced-differencing-time-series
Have you done any time series analysis? What model are you using to forecast future values.
It doesn’t matter what the optimal temperature is, because we won’t be able to experience its full benefits if we simply eclipse right past it.
“We don’t know what it is, but we’re going to pass it!”
Now THAT’S climate science.
Exactly how do you know this?
You seem to be saying that no place on earth will be liveable once the optimum temperature is reached. That’s quite a prediction.
I did not say that.
See what I posted to EC.
Here is the graph I posted. Do the UAH temps give you an accurate view of what is occurring? Can you discern what monthly Tmax is doing from UAH?
“Do the UAH temps give you an accurate view of what is occurring?”
That’s a question you would have to ask of those who regard it is an accurate representation. I’ve always been dubious about it’s accuracy, given it’s a bit of an outlier compared with other sets.
“Can you discern what monthly Tmax is doing from UAH?”
No, because it’s satellite data, and satellites don;t collect daily maximum temperatures.
As to your graph, do you think it gives an accurate picture of what is happening to global temperatures?
I don’t see how it’s that useful. Firstly, it’s just for the USA. And secondly, showing highly seasonal temperatures means that much of the change is lost. Better to avoid the seasonal changes, either by using anomalies, comparing the same month or season.
Here’s the graph of TMax summers for the US, which shows a much more detailed picture. the 1930s, now really look much warmer, whereas in your graph it just appears as a slight blip.
“A bit of an outlier” is a good way to put it.
UAH’s ‘best estimate’ trend is consistently lower than that of the surface data sets over the longer term, but they’re all within one another’s respective error margins.
You don’t see that it is useful. Keep in mind, this is just monthly Tmax temperatures only. It does not create a trend so seasonal changes are entirely useful to examine. As I pointed out, Tmax in summer has little growth, yet Tmax in winter is increasing without a doubt. That is something just waiting for better examination.
How many scientific advances have been made because a researcher wanted to dig deeper into what is happening on a smaller and smaller scale? The real deniers are those who are satisfied using averages that hide smaller scale changes. The real deniers are those who use linear regression on time series data with no adjustments whatsoever to make the series stationary.
I think an entire continent with little to no growth in Tmax provides an insight as to what land surface temperatures are doing. If you believe it is not indicative, then you must show other continents that have sufficient Tmax growth to make the global average rise at an ever increasing rate. Others have shown that Australia is experiencing little to no growth. That is two major continents. What about the rest? the notrickszone.com site has hundreds of temperature graphs worldwide that have no warming. Why do you never address how they don’t really give a picture of what is occurring globally.
“As I pointed out, Tmax in summer has little growth, yet Tmax in winter is increasing without a doubt.”
Something you would be able to see much easier if you plotted both separately.
“That is something just waiting for better examination.”
You think everyone is ignoring seasonal differences? What conclusions would you draw from these differences? For instance, one conclusion might be that this is inconsistent with changes in solar forcing, but consistent with changes in greenhouse gasses.
“The real deniers are those who use linear regression on time series data with no adjustments whatsoever to make the series stationary.”
You’ve really got it in for Monckton. But again, what adjustments do you think need to be made to remove non-stationarity? You keep throwing this up, and never seem to understand that if you make the series stationary there will be no trend, by definition of stationarity.
“I think an entire continent with little to no growth in Tmax provides an insight as to what land surface temperatures are doing.”
It may do, but why restrict your self to that when you can be looking at what’s happening on the rest of the world. What it primarily shows, is any unusual features of the US, such as what happened in the 30s to make it so hot.
“If you believe it is not indicative, then you must show other continents that have sufficient Tmax growth to make the global average rise at an ever increasing rate.”
If it helps, here’s my map of UAH trends for Northern Hemisphere summers.
And here’s the same for Southern Hemisphere summers.
“Others have shown that Australia is experiencing little to no growth.”
Australian summer trend, according to UAH is 0.15°C / decade since 1978/79.
If you want longer term continental trends, NOAA’s climate at a glance is quite useful.
Here’s European summers.
The trend is 0.09°C / decade since 1850, but that’s not particularly meaningful given the obvious non-linearity over that period. The trend since 1979 has been 0.54°C / decade.
Of course, this is for mean temperature, the only option NOAA gives. If you want to see maximum temperatures, BEST I think gives some, but their regional data sets are somewhat out of date.
Sorry, wrong map for NH summer, and I can’t delete it.
Here’s the correct map.
“I think an entire continent with little to no growth in Tmax provides an insight as to what land surface temperatures are doing.”
Your graph does not show data from an entire continent it only shows about 40% of the continent, in particular it omits the northern most 40% of the continent!
Trendology don’t do standard deviations.
Bit rude to talk about Monckton like that. Maybe if he’s around for the next pause he will finally consider the uncertainty of his short term flat trends.
And you still can’t grasp CMoB’s methods…
Where back to this point are we? I ask you to explain what you think his methods are, and you come up with some idiotic excuse for why it’s not worth your time.
Try reading his posts, he tells you what they are.
And there is no “we”.
https://www.sourcewatch.org/index.php/Christopher_Monckton
This is the best you got? The equivalent of a rabid leftist wiki page…
Your assessment of Monton’s ability to deal with climate is an argumentative fallacy of ad hominem.
Did Planck and Einstein have degrees in quantum physics? Did Kepler and Copernicus have degrees in astrophysics?
Tell us some “climate scientists” that have degrees or peer reviewed studies in radiative physics. Are the ones who don’t competent to deal with heat radiation?
Monckton’s undergraduate degree is in classics and his postgraduate diploma is in journalism, comparing him to Planck and Einstein is ridiculous!
Bellman acknowledged in the wording in his reply-to-self that 6 years might not be a meaningful period from which to draw a trend. What amount of time does Eclang recommend for establishing a trend in Earth temperature?
100 years.
I agree that a 6-year period is meaningless. Unfortunately, it’s often used as cherry-picked rhetoric to argue that there’s been no warming.
There is no evidence of any human caused warming in the whole of the 46 years of the UAH data.
Current world temperature, whatever that means, is a minor bump above the coldest period in 10,000 years and a long way below the temperature for most of those 10,000 years.
Jeez… Even Spencer says there is!
Even by WUWT standards, bnice2000 consistently displays a stone age level of awareness re climate change attribution.
He’s an intellectual giant.
Agreed, 100 years sounds like a good number.
So what happens if I don’t trust the data from 100 years ago to be better than a few degrees accurate or to cover a meaningful geographical area?
You address your concerns by reading the literature.
In your case, with zero ability to see what is real and what is activist hysteria.
Yes. How could I ever compete with someone who thinks the greenhouse effect is pseudoscience and that a couple of El Niños explain modern global warming?
“that a couple of El Niños explain modern global warming”.
Show us the warming in UAH other than at the spike/step of El Nino events. !
There is no measured scientific evidence that human released CO2 has any affect on the climate whatsoever…
Still waiting !!
You could try some actual scientific evidence.
Doesn’t seem to be in your field of non-expertise though, does it. !
What if I read the literature and I find that the researchers ignore or mismanage the uncerainty?
What if you read the literature and find it full of made-up data and hysterical activist exaggerations ! 😉
Reach out to the authors, and then it might actually count for something. I’d back it if it’s legit.
“Reach out to the authors”
You can’t be serious. If you’re not part of the team, you don’t get a response
How does the literature decrease the combined uncertainty of temperature measurement 100 years ago. The combined uncertainty for LIG field instruments 100 years ago is at least ±2°F.
The literature says “its worse than we thought”.
Obviously, than can only happen if the original thinking was wrong.
Which also means that establishing trends is meaningless.
Then you can make no claims of climate change, perhaps?
And if there are cycles with periods longer than 100 years, is such a trend analysis valid?
Think Nyquist Theorem.
Isn’t it comical that the warmest/alarmist crowd think running the warmest year, month, day, minutes and seconds charts and roll lists always warming is exciting reading when it just another form of propaganda being pushed.
Still waiting for evidence, that the small warming trend is a danger to all humans aside from leftist democrats who see heat doom behind every healthy growing bush.
The threat doesn’t exist to those who are willfully blind.
The “climate” threat only exists to those who have delusional brain-washed minds…
… and an extremely tenuous grasp on reality.
You could have stopped at “The threat doesn’t exist . . . “.
A none-existent threat doesn’t exist by definition.
“The threat doesn’t exist to those who are willfully blind.”
Likewise the truth doesn’t exist to those who are willfully blind.
It goes both ways.
“The threat exists to those who are willfully blind.”
Yet you can’t articulate the “threat” at all thus you offer nothing.
Joe Biden, in a rare moment of clarity articulated the threat publicly.
He said that human caused climate change is an “existential threat” to mankind.
That means mankind will cease to exist because of human caused climate change.
I’m not convinced that this is true. But if it is, then the earth is automatically saved anyway so all environmentalists should be cheering climate change along.
Oh, grow the f**k up!
https://www.tandfonline.com/doi/full/10.1080/17477891.2025.2571708#d1e322
https://retractionwatch.com/2023/08/25/paper-that-found-climate-crisis-to-be-not-evident-yet-retracted-after-re-review/
If you believe that is a relevant reply you have serious issues.
Temperature is *NOT* climate. If it were Las Vegas and Muami would have the same climate. Anomalies don’t help since a 1deg change at 100degF doesn’t affect the climate ad much as 1degF at 0degF.
So exactly what importance *should* be given to this data?
If you’re referring to GAT, its main role is as a measure of the overall energy in the atmosphere.
And its been decreasing since the peak of the El Nino effect last year.
Yes. Just like it ‘cooled’ after the 1998 El Niño… and 2005… and 2010… and 2016… each time the same ritual.
Didn’t warm from 2001-2015.
Actually cooled from 2017 to mid 2023..
3 major El Ninos, 1998, 2016, and 2023/4 + plus a lesser one in 1987…
… have provided all the warming in the UAH data.
A transient followed by a step up as warm water circulates to other basins (as shown by Bob Tisdale, below)
Without them, there is no warming.
Absolutely no evidence of any human caused warming whatsoever.
The trend from 01/17 – 06/23 has a p-value of 0.454.
Your ‘cooling’ is just eyeballing a trend and imagining a downturn.
DENYING the cooling trend from 2017 -2023.4..
That’s funny.
So statistical significance means nothing to you, then.
Can’t say I’m surprised.
Statistics are descriptors of what the statisticians do with data. Statistics are not the actual physical phenomena.
Correct, but statistics can tell you how likely your dataset is to be just random noise superimposed on an upward trend. If your alleged cooling doesn’t reach statistical significance, then it’s questionable.
And this is of the slightest interest to anyone at all because . . . ?
Maybe you don’t realise that about half of the globe is sunlit at any given time, while the other half is not. It balances out overall. You’re not the sharpest knife in the drawer, are you?
Stop messing around on your parent’s computer, Michael. Go make your bed.
Ah, the refuge of the ignorant and gullible cultist who believes that adding CO2 to air makes thermometers hotter. Sorry, eclang, but casting childish aspersions won’t help you sound authoritative – quite possibly the opposite.
If you are merely trying to be gratuitously offensive, you might like to know that I politely decline to take offence from those whom I consider to be mentally afflicted.
Maybe you could waste your time trying to insult, denigrate or annoy me. Alas, I’ll likely decline to feel insulted, denigrated, or annoyed, but feel free to free to try. [laughs at dimwit who believes that adding CO2 to air makes thermometers hotter]
“[laughs at dimwit who believes that adding CO2 to air makes thermometers hotter]”
Yep that’s me!
Oh well, at least you are prepared to admit your ignorance and gullibility. Many of the other similarly deluded nutters simply refuse to confirm or deny that they share your fantasy.
At least other commenters can be sure that your responses are those of a fantasist, disconnected from reality.
Adding CO2 to air does not make thermometers hotter – in the real world, anyway.
In eclangWorld, anything is possible.
I think red votes are considered the best here.
I only skim through WUWT comments until I see down-votes. Then I know someone has posted something worth reading.
No one, not even you could be such a wanker, surely..
I got news for ya.
Science is not a democracy.
Mr. clang: Much more comical are the ones who read here to affirm one’s self-image of “superiority”.
Cogitate that, cracked-bell one.
This is so true! Partisan crowd for sure. I’ve seen more balanced opinions from rabid soccer fans in Glasgow 🤔
Mr. 1966: I observe that the authors here, as well as the vast majority of comments, seek the truth behind the CO2 hoax. What “balance” do you seek?
Really brings out the echo chamber aesthetic. 🙂
Never been to RealClimate have you. They don’t allow contrary posts.
Just be patient….
NOAA SST-Nino3-4 GlobalMonthlyTempSince1979 With37monthRunningAverage.gif (880×475)
NOAA SST-NorthAtlantic GlobalMonthlyTempSince1979 With37monthRunningAverage.gif (880×481)
NOAA SST-SouthAtlantic GlobalMonthlyTempSince1979 With37monthRunningAverage.gif (880×481)
Not a single climate model came close to predicting Nino34 would be flat or falling.
Hmmm . . . let’s see . . . this from NOAA (my bold emphasis added):
” ‘La Niña conditions emerged in September 2025, as indicated by the expansion of below-average sea surface temperatures across the central and eastern equatorial Pacific Ocean,’ NOAA’s Climate Prediction Center said in a press release on Thursday morning. It is likely to continue into the start of 2026.”
— source: https://www.accuweather.com/en/winter-weather/la-nina-is-here-what-it-means-heading-into-winter/1824171 , in an article published October 9, 2025
Meanwhile, according to this most recent tracking of GLAT anomalies from UAH:
— Sept 2025: +0.53 global, +0.35 tropics
— Oct 2025: +0.53 global, +0.24 tropics
— Nov 2025: +0.43 global, +0.24 tropics
(note: personally, I don’t trust UAH monthly-tabulated temperature anomaly data to more than ± 0.1°C, and that’s on just a reporting basis, not an absolute accuracy basis).
It’s a low impact La Niña, apparently.
From https://www.bbc.co.uk/sounds/play/w172zw8g86s28fn
”More than 6,000 Airbus A320-family aircraft were briefly grounded after solar radiation was found to interfere with flight-control computers. Most planes will return to service after quick software updates, but older jets need hardware replacements, causing scattered global disruptions.”
If solar radiation changes are able to interfere with flight control systems then what is the potential effect on the atmosphere?
The sun owns this joint completely.
Always has, always will.
That’s the bottom, and only line.
Mr. Carrington, I presume.
Even the most ardent skeptic with any power of reason must be at least a little surprised that even under moderate La Ninã conditions, UAH is recording a global temperature that is only just beginning to dip down to the peaks of the 3 highest previous El Ninõs! Personally, I do find that quite extraordinary.
That’s because you are ignoring the increase in absorbed solar radiation.
There is no evidence of human causation in these El Nino events which have caused the warming in the UAH data.
So what is your explanation for the decrease in global cloud cover?
It should be colder, but it’s not, because CO2?
Yes.
Lol.
No really! The Earth should be gradually cooling due to orbital influences, but GHGs have turned that into a fast track warming trend. It’s pretty alarming.
I find it extraordinary that people think global average temp is meaningful.
“I find it extraordinary that people think global average temp is meaningful.”
Why wouldn’t it be meaningful? Are you telling me that all attempts to measure global temperature are a complete waste of time? I do understand that there are a lot of unknowns. But let’s be honest, the globe has been colder and warmer in the past. Isn’t it at least worth being able to monitor the temperature, as we would with someone potentially unwell? Monitoring is good science. Maybe the planet is perfectly well, maybe it isn’t but to suggest that global temperature is meaningless, is a bit like saying human body temperature is meaningless.
Reply
The probity and provenance of human temperature readings are peerless, as they should be.
Absolutely fit for purpose.
Surface temperatures are constructs whose probity and provenance are bordering on outright deception.
“Surface temperatures are constructs whose….”
Maybe so, maybe not! However I don’t think this is true of UAH measurements, which I believe rely on satellite measurements rather than surface stations. After all, it’s the UAH data that we’re looking at, isn’t it?
{}[+]
98.6 F
Mine is 92.2 F
So obviously my body has a problem because it does not conform to the standard.
FYI, 98.6 was established with thermometer mis-calibrated and on a very small population sample.
That suggests that you’re suffering from extreme hypothermia, it seems that your thermometer is miscalibrated, I’d suggest you get a new one.
Even more reason to monitor. At least once you know your baseline, you can determine whether you’re unwell or not.
Ok, we don’t know for sure the global baseline temperature but we do know that the world flourished pretty well in conditions that were colder than present. That being said, the warmth doesn’t seem to be impacting too negatively on world health or crop yields. Still, better to be able to monitor, whatever the case.
There are no MEASUREMENTS of global temperature. There are only calculations that attempt to determine a property that is “global”.
Ask yourself this, if you average all the temperatures on the globe, what would the standard deviation be. The range would be from -50F at the poles to 100F in the Tropics.
Accepted measurement uncertainty says if the distribution is Gaussian, the uncertainty is the standard deviation. That means the true value could be anywhere in the interval of ±SD. In other words, it is UNCERTAIN as to where the actual true value is.
Yes. Do you think otherwise?
You’re entitled to your opinion.
Nobody in the scientific community seems to have an issue with the concept of a globally averaged temperature.
Are you sure you know enough about this subject to hold such a view as you do?
The notion of an accurate GAT is complete nonsense. The only value here is observation of movements in the readings done in the same way at the same time each month. But that value is limited with the short time periods we are dealing with.
Enjoy the mild, gentle, beneficial warming while you can.
When global temperatures begin to decline, worry then.
Any scientist worth their salt could’ve predicted a continuation of the slow rise in global temperature as the Earth emerges from the Little Ice Age.
Remember: ice is present at both poles, even in summer, so technically we’re still in a cool period.
It’s not a slow rise.
https://www.carbonbrief.org/factcheck-what-greenland-ice-cores-say-about-past-and-present-climate-change/
Compared to the Younger Dryas warming it is.
Your graph is missing the sharp uptick at the end. 🙂
It can’t be sharper than the vertical warming of the Younger Dryas.
Why not there’s far less ice to melt now than there was then.
You mean it’s missing spliced temps onto proxies. That’s a naughty thing to do.
I don’t think Clanga understand maths or science to that level yet..
.. and probably never will.
Uncalled for remark!
It’s there if one looks closely. The vertical and horizontal scales do not augment the visibility of that noise spike.
Probably because it doesn’t include data from the last 75 years?
It excludes the last 75-years of data.
It shows “before present” data, where ‘present’ is defined by convention as 1950.
It’s a common ploy used on sites like this to disguise or erase modern warming.
CarbonBrief is a rabid activist site that practices anti-science.
They are well practiced at scientific nonsense like splicing short-term small-time-step surface data from urban warming onto the end of proxy data with much longer time steps.
Those bereft of any actual scientific education fall for such anti-science.
Ice cores provide higher resolution than most other temperature proxies. They can be compared directly, so long as the instrumental data are smoothed to the same temporal intervals. This point was addressed in the linked source.
One has to include the hydro physics of ice. While the measurements can certainly be done with precision, what is being measured is of questionable accuracy compared to the measurement precision.
Surface ice melts and sinks taking the air bubbles with it, and refreezes deeper in the ice. The depth is non-deterministic. A subsequent melt-sink-refreeze often merges with a previous cycle.
There is no way to get an individual year from an ice core, which you inferred.
13 degrees C in 2000 years.
I get 30,40,50 degrees F swings across 8 hours.
Interesting definition of not slow.
I run environmental tests with the temperature required to change at 3C to 5C per minute.
How much of that rise is UHI. The USCRN doesn’t show that hockey stick.
USCRN is only a couple of decades old. And has a warming rate far greater than the global average.
Well now, isn’t that an interesting subject?
USCRN starts in 2005 and it concerns the US only, not global. It was supposed to be (and is hailed by this site as being) the antidote to the spurious warming brought about by ‘adjustments’ and ‘homogenisations’, and other such works of the devil!
Here’s the really funny thing though; compared to ClimDiv (the ‘devil’) over their joint period of measurement, USCRN is warming *faster*.
You read that right.
Despite all the bluster it seems that the adjustments made by ClimDiv on the US temperature record are having a cooling effect, not a warming one.
The so-called ‘pristine’ USCRN is warming faster than the adjusted data over the same period of measurement.
What’s up with that?
It’s an EXTREMELY slow ”rise”
Yes, the rise is so slow, it’s set to surpass the peak of the Holocene in just a couple of decades. What a slug!
should be fun to see how usa48 turns out come 1/2/2026. our 10 day forecast averages 15F below normal
Yep, individual regions can show large swings.
Globally the swings will be much less.
USA and Australia are the only countries treated as “regions” in UAH
Take Australia, anomaly 1.67C in October…. 0.37C in November
October had a two week period in the middle where it was “rather warm”.
Without knowing the actual temperatures, I would say that overall, temperature-wise, November was actually slightly cooler than October, where I am.
The ignorant and gullible seem to believe that they can infer the temperature of the Earth (whatever that is supposed to mean), from a handful of thermometers scattered near the semi-exposed surface of around 30% of the Earths crust. These thermometers are at varying distances from the center of the Earth, exposed to all sorts of variable heat sources – the Sun being just one,
Completely worthless, unless you want to know how hot the instrument is. It doesn’t even measure the temperature of the air surrounding it!
Oh, this is measuring the temperature of the Earth from a satellite, is it?
Even more pointless and stupid, as anybody with half a brain and a faint acquaintance with the laws of physics will point out, if they are in the mood to waste time assisting the mentally disabled.
The atmosphere behaves chaotically. So does the sea, and the rest of the Earth itself.
If anybody can show that the graphs presented by Dr Spencer cannot be explained by chaos theory, feel free to do so.
First, the satellites need to measure the full EM spectrum, not just LWIR.
Black body is the total energy emitted when the surface is in energy equilibrium.
There is a bidirectional thermal energy flow between the surface and the thermal mass below ground. The total EM energy must account for convection, conduction, and latent heat energy transfers, which diminish the EM field power density.
EM radiation is not a vector. Field strength varies as 1/R^2. It is spherical. The point being, the earth’s surface is not a perfect, smooth, polished sphere, so at any point in measurement those very fine satellites are not getting 100% of the energy emitted by the surface. So any of those measurements required approximations and guesses. One has to wonder how the satellites capture accurate measurements when transiting a 45 degree terrain slope, just for example.
The CERES covers 99.95% of the spectrum with a 0.5% to 1.0% error. It is a sampling system and the publications do not state if the quantization error is part of the system acquisition error. Then there are linearization tolerances, amplifier effects, etc., all of which are likely part of the stated error range. The angle of acquisition of the CERES sensors is not stated. It is unclear if its field of view covers the full 25 km grids used in the models.
CERES is good, but far from perfect. In addition, a satellite cannot determine from which part of the atmosphere a specific quantum of energy (aka photon) is emitted.
UAH determines the temperature of the oxygen in the atmosphere not the surface, this is determined by measuring the microwave emission spectrum of the oxygen molecules. It does not require the full EM spectrum.
This article is about satellite measurements. See answer from Sparta Nova. Why do you need to be so contemptuous in your responses to those who state a different view to your own? There is no need to label others “ignorant and gullible”.
The earth is warming up. While there are a lot of plausible explanations, nobody knows for sure. So it’s unwise and uncalled for, to label others as ignorant until you can be absolutely sure of your own position. I do realise that there are some on the opposite side, who engage in similar rhetoric but whoever it is, it does nothing to improve the quality of the discussion.
The new Monckton Pause extends to 33 months starting in 2023/03. The average of this pause is 0.60 C. The previous Monckton Pause started in 2014/06. It lasted 107 months and had an average of 0.21 C. That makes this pause 0.39 C higher than the previous one.
+0.156 ± 0.039 C.decade-1 k=2 is the trend from 1979/01 to 2025/11 covering 563 values.
+0.027 ± 0.010 C.decade-2 k=2 is the acceleration of the trend.
My prediction for 2025 from the 2025/03 update was 0.43 ± 0.16 C k=2.
My prediction for 2025 from the 2025/04 update was 0.47 ± 0.14 C k=2.
My prediction for 2025 from the 2025/05 update was 0.46 ± 0.11 C k=2.
My prediction for 2025 from the 2025/06 update was 0.47 ± 0.10 C k=2.
My prediction for 2025 from the 2025/07 update was 0.46 ± 0.08 C k=2.
My prediction for 2025 from the 2025/08 update was 0.46 ± 0.06 C k=2.
My prediction for 2025 from the 2025/09 update was 0.48 ± 0.05 C k=2.
My prediction for 2025 from the 2025/10 update was 0.49 ± 0.03 C k=2.
My prediction for 2025 from the 2025/11 update now 0.48 ± 0.02 C k=2.
BTW…I want to mention an interesting fact that should be so mind numbingly obviously that it would intuitive even for elementary age children. That is the more information you have (or when N is larger) the lower the uncertainty of the average. Notice that as we move from N=3 to N=11 my predictions for the annual average gets lower and lower. The contrarians here vehemently disagree and say that I am incorrectly reporting the uncertainty on my predictions and that I should be reporting a higher value from the November update when N=11 than from the March update when N=3.
LOL, that is a junior high level comment ! If that.
You are basically saying you can get a more accurate answer if you have most of the data.
Nothing to do with the mathematical errors of large samples, if that is what you are trying to imply.
That’s not all, bdgwx. The same people who highlight the high uncertainty in these averages also claim that a small sample size (like just 4 stations in the central United States) is large enough to draw accurate conclusions. Glad to see I’m not imagining these contradictions.
I suppose you could conclude that 4 equals 4.
Apart from that, what pointless conclusion are they trying to draw? If you think they are trying to draw the conclusion that adding CO2 to air makes thermometers hotter, it wouldn’t matter how many “stations” there were in the sample, would it?
Cite?
https://wattsupwiththat.com/2025/11/03/uah-v6-1-global-temperature-update-for-october-2025-0-53-deg-c/#comment-4127868
November 4, 2025 5:20 pm
That’s a link. You just want to waste peoples’ time don’t you?
Can’t you just copy and paste the relevant text? No?
Like you, that might be too simple.
No, I am providing what karlomonte requested.
No, he requested a “cite”. You provided a link, presumably to a comment from some anonymous blogger. Some “cite”!
I am not surprised that you are too embarrassed to support your bizarre assertion. Just like you are too embarrassed to admit that you believe adding CO2 to air makes thermometers hotter!
Even you aren’t stupid enough to make that claim, are you?
You are not quoting what was said accurately! Why am I not surprised?
The correct context is that as CO2 continues to increase and raise the GAT, why are the 4 CRN stations not showing a growth in temperature over the last 20 years.
You never bothered to answer that question.
Better, the entire 114 CRN stations show little to no warming on the CONUS. Is there something wrong with the CRN stations? If so what is the problem?
Is there another continent that has a large increase that makes the GAT large? How about Australia?
You wouldn’t expect uniform warming rates across the globe. Regions near oceans can warm differently than continental areas.
There’s also latitude: the Arctic warms more rapidly due to the ice albedo feedback, a phenomenon that the tropics don’t experience.
But, but . , .
Didn’t Gavin Schmidt (competent juggler) state that CO2 was evenly mixed?
Can they? Do they? Why is that – do the properties of CO2 change with location and time? Are you completely stupid, and assuming everyone is even more stupid than you?
Is that caused by excess CO2 emitted by humans?
Nope. Differences in heat capacity.
Oh, I see. Regions near oceans can warm differently than continental areas, can they? Does this mean they do, or that they don’t?
Are you stupid? Just because something can or might happen, doesn’t that it will or won’t! About as silly as saying that adding CO2 to air can make thermometers hotter, but that it doesn’t!
I’ll point out that regions near oceans (whatever that means) can also cool differently than continental (whatever that means) areas also – or differently to anything that is different!
Are you really dimwitted, or are you just pretending?
That might be a rhetorical question,<g>
Is this comment supposed to support a belief that adding CO2 to air makes thermometers hotter, or haven’t you made up your mind on that matter yet?
Maybe it’s a matter of uncertainty.
The uncertainty of the mean (average) is not the measurement uncertainty. It is only a statistic that provides the interval where the central value (mean) of the measurement uncertainty interval lays.
Measurement uncertainty is determined from the dispersion of the observations qk, that make up the probability distribution for the measurand. It is the standard deviation of that distribution that is the standard uncertainty.
From the GUM.
3.3.5 The estimated variance u² characterizing an uncertainty component obtained from a Type A evaluation is calculated from series of repeated observations and is the familiar statistically estimated variance s² (see 4.2 ). The estimated standard deviation (C.2.12 , C.2.21 , C.3.3 ) u, the positive square root of u², is thus u = s and for convenience is sometimes called a Type A standard uncertainty.
The GUM also defines the mean as only an estimate of the central value of a measurand uncertainty interval.
σ/√n is not not included in this definition of uncertainty.
“σ/√n is not not included in this definition of uncertainty.”
Is your memory really this bad? You keep repeating the same cut and paste from the GUM every time, and then ignore every time I have have to explain that the very next section, 4.2.3, tells you exactly how to determine the uncertainty of the mean of your repeated measurements, which you get by σ/√n.
Read this very, very carefully. s(q̅) quantify how well q̅ estimates the expectation μq of q. HOW WELL q̅ ESTIMATES THE EXPECTATION μq (that is, the mean) OF q.
Nowhere in this section does it mention that s(q̅) is a measure of the dispersion of the observations of the input quantity, nor that it is the standard uncertainty determined by a Type A evaluation.
Now, reread 3.3.5 again. It explicitly says the standard deviation is the standard uncertainty. Do you really believe that the JCGM was approved while it contained a large error of using standard deviation instead of standard deviation of the mean?
Let’s examine the next part of 4.2.3.
Thus, for an input quantity Xᵢ determined from n independent repeated observations Xᵢ,ₖ, the standard uncertainty u(xᵢ) of its estimate xᵢ = Xᵢ is u(xᵢ) = s(Xi ), with s²(Xᵢ) calculated according to Equation (5). For convenience, u²(xi ) = s²(Xᵢ ) and u(xᵢ ) = s(Xᵢ ) are sometimes called a Type A variance and a Type A standard uncertainty, respectively.
What does this actually say? Xᵢ is the measurement of the first input quantity used in the functional relationship describing the measurand. What is Xᵢ,ₖ? Let’s call Xᵢ = X₁, that is the first input quantity in the functional relationship. What is k? k is the number of the observation taken under repeatability conditions. So how many observations does one get when measuring a temperature at a station. How about 1 (one). That results in an input quantity of X₁,₁. Funny how n = 1, results in the standard uncertainty being the standard deviation.
So what does one do when X₁,₁ is all you get for a single temperature measurement? First, you must recognize that the uncertainty can not be calculated using a Type A evaluation. Therefore, a Type B is required for the standard uncertainty.
Remember, this is only one item in the combined uncertainty calculation. One must also take F.1.1.2 into account and add the standard deviation of the Xᵢ values to the standard uncertainty of a single reading.
“Nowhere in this section does it mention that s(q̅) is a measure of the dispersion of the observations of the input quantity,”
Why should it. That is not the definition of measurement uncertainty.
“nor that it is the standard uncertainty determined by a Type A evaluation.”
Yes it is. I gave you the specific example where they illustrate that in the GUM. Measure voltage. or whatever, 5 times. Use the mean of those 5 measurements as the input to a function and use the standard deviation of the mean as the uncertainty if that mean.
“Do you really believe that the JCGM was approved while it contained a large error of using standard deviation instead of standard deviation of the mean?”
It’s obviously not well written, prossibly because they expect some intelligence in the reader. That section specifically refers you to 4.2. 4.2.2 tells you how to calculate the standard deviation, without calling that uncertainty. 4.2.3 follows on from 4.2.2 and tells you how to calculate the standard deviation of the mean and tells you that is the uncertainty of the mean you have just taken. It then tells you that for an input quantity X, the standard uncertainty of it’s estimate x is the standard deviation of the mean of X. (Subscripts omitted).
It concludes that the uncertainty of the mean is sometimes called a Type A standard uncertainty.
Continued.
“What is Xᵢ,ₖ?”
The kth measurement of the ith input quantity.
“What is k? k is the number of the observation taken under repeatability conditions.”
Wrong.
” So how many observations does one get when measuring a temperature at a station. How about 1 (one).”
And there’s the familiar Gorman twist. Please try to concentrate on one thing. You are talking about the measurement uncertainty of a single thing, an input quantity. You start by quoting the GUM taking multiple measurements of that one thing, and claim this proves that the measurement uncertainty is given by the standard deviation of all those measurements. You are wrong, but lets stick with that.
Then you want to apply this to a sample of different things, and claim that the measurement uncertainty should be the standard deviation of the sizes of all those things. In that you are extending the concept of measurement uncertainty to something beyond the concept of repeatable measurements. You are treating all the different values in your sample as if they were repeatable measurements of the same thing, i.e. the mean of the population.
But then when I point out the actual measurement uncertainty would then be the standard deviation of the mean, you say that this is not correct becasue you are not taking repeatable measurements. But that contradicts your first claim.
Really you can do one of two things here. Treat the sample as a sample of repeatable measurements of the population mean, and use the GUM concept of measurement uncertainty. Or you can use standard statistics and treat the SEM as the uncertainty of the mean. What you cannot do is mix these concepts and claim that the measurement uncertainty of the mean is given by the standard deviation of the mean.
It makes no sense to talk of the standard deviation as the measurement uncertainty, because the variation has nothing to do with the uncertainty of the individual measurements. If you want an actual measurement uncertainty of the average of a finite set of values, you can do that using the general equation for combining uncertainties, using the average as the function, but then if you only have one measurement for each input you have to use a Type B uncertainty. The result is that assuming independent uncertainties the combined uncertainty is reduced by the the number of observations. But that is not the uncertainty of a sample mean, rather it’s the uncertainty of the exact mean of the N values you are measuring.
“One must also take F.1.1.2 into account and add the standard deviation of the Xᵢ values to the standard uncertainty of a single reading. ”
And now you are completely lost in the woods. And I can’t bring myself to again explain to you what F1.1.2 is actually saying.
Well, that’s certainly one reason for you believing that adding CO2 to air makes thermometers hotter!
Or were you talking about something quite irrelevant?
Nothing to do with CO2. It’s just explaining to the Gorman’s how uncertainty is meant to be calculated.
So do you think that the “temperature” data presented by Dr Spencer has nothing to do with CO2, or does the “uncertainty” (however calculated) have nothing to do with CO2?
If the answer to either is “yes”, then the whole charade about “uncertainty” is a farce.
You might claim to be an “expert” on calculating uncertainty, but your English could do with improvement. Would you like me to explain why I think this is so? I don’t claim to be an authority on the use of the English language, of course.
“So do you think that the “temperature” data presented by Dr Spencer has nothing to do with CO2, or does the “uncertainty” (however calculated) have nothing to do with CO2?”
The comment thread you jumped into has nothing to do with CO2. This should be obvious if you had actually read it.
“You might claim to be an “expert” on calculating uncertainty”
I don’t.
“but your English could do with improvement.”
Undoubtedly. But if you are going to pick up on every typing error and grammatical mistake I make, you will be wasting your time.
“Would you like me to explain why I think this is so?”
No.
I don’t think so. Consider it a free gift – assisting those less able than myself to better themselves.
Your continual grammatical errors, and typing mistakes, coupled with an implied refusal to accept an offer of help, points to intentional sloppiness on your part.
You could always spend a little time going through my comments, and finding the intentional errors contained therein. In this way, you will become aware of your own deficiencies.
You don’t need to thank me.<g>
He seems very worried about CO2’s ability to cause rapid warming.
Let’s examine what the GUM says.
Hmmmm. A random variable “q”, with n independent observations obtained under the same conditions of measurement.
Do you really think the JCGM just happened to use “k” at random to depict different things? “k” = “n”
And in case you forgot;
“same conditions of measurement” = “repeatability (of results of measurements) ”
Since you can’t even get the basics correct you have no basis for further incorrect assertions.
“Hmmmm. A random variable “q”, with n independent observations obtained under the same conditions of measurement.”
Exactly. n observations, not k observations. You said k was the number of observations, when k is the index of a specific observation. That’s why I said you were wrong.
“Do you really think the JCGM just happened to use “k” at random to depict different things? “k” = “n””
Using k as a second index is common in maths. j is more normal, but there’s the danger it gets confused with i.
n is used to indicate the number of things being indexed because it stands for number.
If the GUM is saying k = n, then they are idiots. Why use two different symbols for the same quantity?
And I addressed the point about repeatability in my comment. You are trying to argue two different things. One. That the values from a sample are repeatable measurements. In order to justify your claim that their standard deviation is measurement uncertainty. And two. That they are not repeatable measurements in order to justify your claim that the standard deviation of the mean cannot be used as measurement uncertainty.
Read this very carefully.
Every Xᵢ has “k” number of observations from 1 to n.
Tell us what this means to single measurements of temperature. What does n equal in that case?
As always you rage against a trivial point in which you are wrong. None of this has anything to do with the point. Except it illustrates how little you understand the subject.
k is not the number of observations. If it were why do you think they right k=1?
Your equation simply describes the average, but the formatting is wonky. The k=1 is below the semmation sign, and no is above it. It means itterate over all values of k from 1 to n. You understand this, but for some reason keep claiming there are k number of observations.
And then you keep asking the same question, which I’ve already explained to you. If you are making a single observation then n is 1 and all the talk of standard deviations is irrelevant. You cannot claim that the single observation’s uncertainty is determined by the sample standard deviation because your sample size is 1. You have to use some prior estimate of uncertainty, I.e. a type B uncertainty.
If on the other hand you have a sample of multiple different things. You can look at the standard deviation of those values and calculate the SEM from it. It’s up to you if you want to shoehorn this into the GUM equations and call it measurement uncertainty, or just use the identical equations from standard statistics.
Your problem, which you still refuse to address is you want to mix and match. Claim the single measurements of multiple different things are repeatable measurements for the purpose of determining the standard deviation, then somehow claim this is the measurement uncertainty of the mean. But then claim you cannot use the standard deviation of the mean, as each value only has one measurement.
I’ve gone through this three times already, yet you just keep ignoring it, and repeat the same meaningless question.
The quoted text is completely meaningless. You display a wanton disregard for the use of clear English, no doubt expecting others to translate your gibberish into something meaningful.
You spurned my offer of help. So be it.
Typical of a fantasist who believes that adding CO2 to air makes thermometers hotter.<g>
“The k=1 is below the summation sign, and n is above”
Was that too hard?
Thanks. You know how to do it, you just can’t be bothered doing it – preferring sloppiness, and then trying to blame others who point out your failings.
Typical of a fantasist who believes that adding CO2 to air makes thermometers hotter.<g>
The summation is of each Xᵢ input quantity with “k=n” number of observations for each Xᵢ.
You end up with:
X̅₁ = X₁,₁ , X₁,₂ , … , X₁,ₙ
X̅₂ = X₂,₁ , X₂,₂ , … , X₂,ₙ
X̅₃ = X₃,₁ , X₃,₂ , … , X₃,ₙ
X̅ᵢ = Xᵢ,₁ , Xᵢ,₂ , … , Xᵢ,ₙ
That is “n” observations for each Xᵢ.
Look at this equation closely.
X̅ᵢ = (1/n) Σ Xᵢ,ₖ |ⁿₖ₌₁
Why don’t you show us your series with “n” observations?
Lastly, if there is only one observation for each Xᵢ, then
X̅ᵢ = Xᵢ
What is the mean, standard deviation, and standard deviation of the mean of an X̅ᵢ with one observation? In other words when k = n = 1.
Why do you have such a hard time accepting such a simple point. k does not equal n. Your own statements illustrate that k is an index not a constant.
k in that sequence is the value after i. It’s 1, 2, …, n.
I really don’t understand why you have to keep denying this, it makes no difference to your main point. It just demonstrates you don’t understand mathematical notation.
“Why don’t you show us your series with “n” observations?”
No need, you did it above.
And I’m not going over your “n = 1” question for a fourth time. It’s pointless when you just ignore my explanation each time.
It is you that refuse to acknowledge that “k” is an index of multiple observations made on a unique input quantity.
For the functional relationship of
“A = L×W×H” where
X₁ is “L”
X₂ is “W”
X₃ is “H”
and
X₁ has k₁ observations
X₂ has k₂ observations
X₃ has k₃ observations
Note that all Xᵢ must be made under the same conditions (4.1.4) (B.2.15)
“It is you that refuse to acknowledge that “k” is an index of multiple observations made on a unique input quantity.”
I’m literally telling you that’s what it is. You still don’t get that if something is an index it can’t also be the number of observations.
“X₁ has k₁ observations”
k₁ is an index. It can be 1, 2 or any value up to n. It’s meaningless to say there are k₁ observations.
See section 4.1.1 Note 2, if you need it explained again.
“Note that all Xᵢ must be made under the same conditions”
No. Once again you are wrong. Repeatability is referring to the various measurements of each Xᵢ, not to each Xᵢ.
I’ve no idea why you keep referencing 4.1.4. I doubt you understand what it’s saying. Maybe looking at example H.2 would help you.
B.2.15 is just the definition of repeatability, which requires measuring the same measurand. That is not possible with the various Xᵢ, because are describing different measurands. Look at your example – height, length and width are all different things.
The sad thing is that rereading the original comment, Jim might have been right and I misread it. But once I said it was wrong Jim seems to double down on the wrong interpretation. What he actually said was,
“What is k? k is the number of the observation taken under repeatability conditions.”
I misread that as “the number of the observations“, but Jim might just have meant it’s the number of a given observation.
But rather than clarifying what he meant he starts saying k=n.
The “index” you are referring to is an input quantity. It is the “i” in Xᵢ. As I showed you:
“A = L×W×H” where
X₁ is “L”
X₂ is “W”
X₃ is “H”
The “k” is the quantity of observations for each “i” and can have a different number of observations for each input quantity.
It is obvious you are unable to understand a summation sequence that is generalized to “i” input quantities and “k” observations.
I’ll repeat the sequences.
X̅₁ = X₁,₁ , X₁,₂ , … , X₁,ₙ
X̅₂ = X₂,₁ , X₂,₂ , … , X₂,ₙ
X̅₃ = X₃,₁ , X₃,₂ , … , X₃,ₙ
X̅ᵢ = Xᵢ,₁ , Xᵢ,₂ , … , Xᵢ,ₙ
For the example of Area, these would become the following.
X̅ₗ = Xₗ,₁ , Xₗ,₂ , … , Xₗ,ₙ
X̅ᵥᵥ = Xᵥᵥ,₁ , Xᵥᵥ,₂ , … , Xᵥᵥ,ₙ
X̅ₕ = Xₕ,₁ , Xₕ,₂ , … , Xₕ,ₙ
Where l=length, vv=width, and h=height
Show us what your sequences are with “i” input quantities and and each input quantity having “k” observations.
I tried to give you the benefit of the doubt in assuming I’d just misread your original comment – but it seems you are determined to keep displaying your ignorance.
“The “index” you are referring to is an input quantity.“
There are two indices, i and k. i refers to the index of the input quantity, k refers to the index of the observation of that input quantity. Using the notation in 4.1.4, there are N inputs, and n observations.
“I’ll repeat the sequences.
X̅₁ = X₁,₁ , X₁,₂ , … , X₁,ₙ
X̅₂ = X₂,₁ , X₂,₂ , … , X₂,ₙ
X̅₃ = X₃,₁ , X₃,₂ , … , X₃,ₙ
X̅ᵢ = Xᵢ,₁ , Xᵢ,₂ , … , Xᵢ,ₙ”
Where do you think k is in each of those sequences? Your various i values are running from 1 to n, where n is the number of observations and k refers to the number of each individual observation. The full equation for the mean of the ith input quantity is
That’s telling you to sum all the n observations. k is simply a label to show that each value is the kth observation, and that k runs from 1 to n.
Exactly. It what I’ve been saying all along.
Now that you finally agree with me, tell us for a single measurement, X₁,₁, how do you calculate the mean, standard deviation, and √n. More specifically what value does “n” have with a single measurement?
BTW, let me point out what you said earlier in a post. You have moved from that to now quoting what I have been posting.
https://wattsupwiththat.com/2025/12/02/uah-v6-1-global-temperature-update-for-november-2025-0-43-deg-c/#comment-4137891
I’ll also remind you that I have been discussing n = 1 this thread and for many years prior.
“Exactly. It what I’ve been saying all along.”
Apart from all the times you said that k was the number of observations.
“Now that you finally agree with me”
Pathetic. I’m not sure if you realize what you have been arguing all along.
“tell us for a single measurement, X₁,₁, how do you calculate the mean, standard deviation, and √n. More specifically what value does “n” have with a single measurement?”
And you still won’t acknowledge that I’ve been answering your dumb question all along. If you only have a single measurement then it is your best estimate of the measurand, it is the mean of all your observations. You do not know what the standard deviation is, and you cannot estimate from the sample deviation, because your sample size is 1. Sol you also cannot estimate the measurement uncertainty of the mean, except by using a Type B uncertainty.
“More specifically what value does “n” have with a single measurement?”
Are you really this dense? If there is one measurement then n = 1.
Now, if you had actually read anything I wrote in the past comments, this is irrelevant to the question of the uncertainty of a sample. Because then n is the sample size and the SEM is the standard deviation of the sample divided by √n.
Your problem, which you continue to ignore, is that you can’t decide if you want to treat the sample of different things as multiple measurements of the same thing, which is required if you want to use the standard deviation as the measurement uncertainty, or if you insist each measurement is measuring a single unique measurand, in which case it has to have a type B measurement uncertainty. But that tells you nothing about the measurement uncertainty of the mean of the sample.
Once again the self-described “non-expert” of metrology and uncertainty lectures as if he were an expert, with hand-waving.
Um, a combined standard uncertainty for a given measurement procedure can have a component of Type A uncertainty that was previously assessed. It does not have to redone every time the measurement system is used. Type A and B are not mutually exclusive.
But I forget, they are exclusive if everything is random, Gaussian, and cancels, as per usual for climate trendology.
Formal uncertainty analysis is an exercise in engineering judgement, and not hand-waving.
“Once again the self-described “non-expert” of metrology and uncertainty lectures as if he were an expert, with hand-waving.”
You don’t need to be an expert in metrology to know how subscripts work.
“Um, a combined standard uncertainty for a given measurement procedure can have a component of Type A uncertainty that was previously assessed.”
And how are you supposed to get a previous assessment when Jim is claiming it’s impossible to measure a temperature more than once?
Jim is of course 100% correct, and you’ve been told this many, many time yet refuse to acknowledge reality.
The answer is a calibration lab, where the temperature can be fixed and measured multiple times.
Regardless of the reams and reams of obfuscated verbiage you post about uncertainty, at the bottom line, you don’t care about it and just wish the subject would disappear.
“They just ignore it so I can can too!”
You’ll post anything to keep on claiming the magic of averaging cancels all problems.
“Jim is of course 100% correct”
Jim’s not the one claiming you can get a Type A uncertainty from a single measurement. I’m agreeing with him. That’s why I asked you the question.
“The answer is a calibration lab, where the temperature can be fixed and measured multiple times.”
Wouldn’t that be a type B uncertainty? Regardless it makes no difference to the question. You know what the estimated measurement uncertainty of your single measurement is.
“They just ignore it so I can can too!”
Citation required. Who are you quoting and in what context?
More obfuscation noise.
bellman:
https://wattsupwiththat.com/2025/12/02/uah-v6-1-global-temperature-update-for-november-2025-0-43-deg-c/#comment-4137341
All the while the endless bellman curves say exactly zero about measurement uncertainty.
“Numbers is numbers!”
Ignore it and hope it all goes away.
“More obfuscation noise.”
Yes, you ignore all my questions and just link to a joke about Monckton.
No, not necessarily.
Variance from repeated measurements obtained on an earlier occasion can used. It is one reason for using an expanded uncertainty.
I suspect you also don’t understand that repeatability uncertainty from repeated measurements is not the only item in an uncertainy budget. It is only one item of many categories. Things like drift, resolution, reproducibility, hysteresis, etc. must also be considered.
“No, not necessarily.”
That quote is describing a Type B uncertainty. The entire section F.2. is about Type B uncertainties.
But it doesn’t really matter, the uncertainties are treated the same for the purpose of a combined uncertainty, and if you say you can use a calibrated assessment of the instrument uncertainty as the uncertainty of that one measurement, why do you insist that the measurement uncertainty of the mean, is the standard deviation of all values?
That quote is describing a Type B uncertainty.
That quote is describing an uncertainty developed fron a Type A evaluation. I’m not sure what you think variance of repeated measurements means.
I’m not sure what you are trying to prove here. If you think single measurements have a mean and variance, you are mistaken.
X̅₁ = X₁,₁ is a single measurement, and it’s uncertainty can not be supplied by evaluating a probability distribution. That is where we stated and you have not managed to disprove that assertion.
“That quote is describing an uncertainty developed fron a Type A evaluation.”
It may be derived from a type A uncertainty, but when it’s used for a different measurement the GUM implies that’s Type B. That’s how I read it in any case, and if it’s not considered a Type B, why put it in the section on Type B evaluation.
“If you think single measurements have a mean and variance, you are mistaken.”
Their probability distribution has a mean and variance. That comes from a Type A or B uncertainty estimate.
“X̅₁ = X₁,₁ is a single measurement, and it’s uncertainty can not be supplied by evaluating a probability distribution.”
Please just make your mind up. As I said, you cannot get a Type A uncertainty from a single measurement. The you say that if you have previously derived a Type A uncertainty in a calibration laboratory, you can use that as a Type A uncertainty. And now you are back to saying it’s impossible to have a Type A uncertainty from a single measurement.
“That is where we stated and you have not managed to disprove that assertion.”
You still have not explained what your assertion is. You claimed that if you have a mean of a sample of different things then its measurement uncertainty is the standard deviation of all those things. You justify that by pointing to Type A uncertainty using 4.2.2.
Then, in order to justify your claim that you cannot use the standard deviation of the mean as the mean’s uncertainty (4.2.3), you say that each thing has to be treated as a single measurement with no standard deviation
So you simultaneously want to treat the sample of things as repeated measurements under the same condition, to justify using 4.2.2, but as individual measurements to avoid using 4.2.3.
Pure nonsense.
Anything to keep the climate trendology fables alive.
A typically vacuous response.
This is a minor question about how to classify Type A or B uncertainties. It makes no difference to the result, but karlo just asserts it’s part of a conspiracy to promote the climate change.
What you claimed was no different from bigoil’s yarn that if you glom enough different measurements together, “systematic errors” magically transmogrify into “random errors” and disappear.
From the GUM (that you love to abuse) right up front from 0.7:
“The uncertainty in the result of a measurement generally consists of several components which may be grouped into two categories according to the way in which their numerical value is estimated:
A. those which are evaluated by statistical methods,
B. those which are evaluated by other means.
There is not always a simple correspondence between the classification into categories A or B and the previously used classification into “random” and “systematic” uncertainties. The term “systematic uncertainty” can be misleading and should be avoided.”
You will now take the Last Word, as per standard.
“Disappear”, nope. Never said so. Minimize? Given enough repeats to return from the early Bizarro data point, always.
Another content-free word salad.
Climatology has zero understanding of systematic effects (as well as uncertainty in general).
Why repeat what Bellman, bdgwx, FTN, et. al. are saying to try and Snap You Out Of It, better than I could? We actual engineers have a saying “True, by inspection”. That’s why you and your cohort confine your Group Groping to WUWT, and either eschew posting above ground, or have been fact checked away.
Don’t know what kind of engineering you do, but that wasn’t ever something I could do. Legal liabilities and warranties mean you need to have proof of measurements.
He doesn’t understand that true values cannot be known (except in some very specific instances).
You are describing “errors”. That is a paradigm that is no longer in use internationally. That paradigm required the precise knowedge of a “true value”.
Uncertainty is based on probability distributions determined from observations. There is no cancelation of values in the distribution.
“That paradigm required the precise knowedge of a “true value”.”
No it doesn’t. It would be absurd as if you know the true value there is no uncertainty.
“Uncertainty is based on probability distributions determined from observations.”
How is that different to the error paradigm?
“There is no cancelation of values in the distribution.”
Why would you expect there to be. Cancellation occured when you combine different probability distributions.
Not sure how you would calculate an error value if you don’t have true value to subtract.
From the GUM.
You don’t calculate the error. That’s why it’s uncertain.
Maybe I’m misundersting what you think the error paradigm is. Could you quote a reference to the old paradigm that says you need to know the true value and the error in order to work out the uncertainty?
From Bevington 1.1
From Taylor 4.1
Is this a special day for meaningless word salads?
But not to worry, at least bigoil seems to think stuff like this has deep physical significance.
What words did you have a problem understanding?
“What you claimed was no different from bigoil’s yarn that if you glom enough different measurements together, “systematic errors” magically transmogrify into “random errors” and disappear.”
Why do you never engage with the actual discussion. We were not talking about random and systematic errors, just the ambiguous distinction between an A or B uncertainty.
Type A and B are not the same as random and systematic, and as the GUM says there isn”t always a clear distinction between the two.
The ambiguity here is that whilst the GUM says that Type A is determined by statistical means, and Type B by other means, they also say that the other means may include previous measurements and calibration reports. I interpret that as meaning that A requires statistical analysis on the thing you are measuring, as implied in all the sections Jim keeps quoting. Whereas if you use prior statistical analysis to infer the uncertainty, than that’s a type B.
You might have a different and better opinion, but it really doesn’t matter as the combined uncertainty is calculated in the same way, and none of this has anything to do with Jim’s point.
“You will now take the Last Word, as per standard.”
Translation: “If you respond to this comment, I’ll claim victory.”
Show us how how you calculate a mean and variance from a single reading’s probability distribution.?
The mean and variance of a series of non-repeatable measurements is covered in F.1.1.2.
If you want to declare an uncertainty a Type B rather than a Type A, be my guest. It makes no difference.
Here are the pertinent GUM references.
You need to get some things straight in your head.
“If you want to declare an uncertainty a Type B rather than a Type A, be my guest. It makes no difference.”
That’s what I keep telling you.
“Show us how how you calculate a mean and variance from a single reading’s probability distribution.?”
You use your prior estimated standard uncertainty – however you obtained it. If you really want the varience just square it. The mean of the distribution is just your single measurement. So say I measure the height as 123cm and there’s an assumed 0.5cm uncertainty, the the mean of the probability distribution is 123cm, and the varience is 0.25cm².
This is not the probability distribution of the single reading. Because we are not using the error paradigm. It’s the probability distribution of the value of the measurand.
You did not answer my question.
Then I’ve no idea what question you are asking. What calculation do you require other than squaring the standard uncertainty?
You CANNOT calculate a mean and variance from a single, non-repeatable observation/measurement of an input value.
It is why Section F in the GUM is so important.
You mean you can’t calculate it using repeated measurements? Of course not. That’s the difference between Type A and B. But both are ways to calculate the probability distribution.
Maybe at some point, you will get over asking these meaningless questions, and explain what any of this has to do with your claim that the measurement uncertainty of a sample mean is the standard deviation of all the values.
Within 12 hours, the cold snap will move across the Great Lakes.
Warming in the northern hemisphere mainly affects the oceans and is related to the position of the Earth’s axis relative to the Sun. Since the perihelion occurs in January, winter is milder in the northern hemisphere than in the southern hemisphere. Winter circulation is also influenced by solar activity, as the stratosphere interferes with the troposphere in winter.
https://www.cpc.ncep.noaa.gov/products/stratosphere/strat_int/
More waves of Arctic air will sweep across the Great Lakes.
Within five days, the polar vortex in the lower stratosphere will split into two distinct centers corresponding to the two centers of the geomagnetic field in the north. The weakening magnetic center is located over northeastern Canada, while the strengthening center is over central Siberia. The Magnetic North Pole is shifting toward Siberia.
