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 October, 2025 was +0.53 deg. C departure from the 1991-2020 mean, unchanged from the September, 2025 value.
The Version 6.1 global area-averaged linear temperature trend (January 1979 through October 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 22 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 |
The full UAH Global Temperature Report, along with the LT global gridpoint anomaly image for October, 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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Based on regional WX and high sea ice, I thought October might have been cooler.
But downtrend from post-Tongan eruption high 18 months ago continues.
If October has the same GLAT anomaly as that of the preceding September (both +0.53 °C, according to the table in the above article provided by UAH), then how can the “downtrend” be said to be continuing???
Look at the differences NH, SH, Tropics and Australia to September.
So the +0.53 now are not the same as for September.
Please inform UAH/Professors Spencer and Christy of your “analysis” and rather surprising results.
And yes, please check first to confirm that “global” reflects NH and SH—with appropriate relative weightings due to differences in land vs ocean percentages between both hemispheres—and does not also include separate regions (e.g., the Tropics and Australia) if both the NH and SH comprise the “global average”.
YEAR MO GLOBE NHEM. SHEM. TROPIC USA48 ARCTIC AUST
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 +1.6
7
2025 Sept GLOBE +0.53
2025 Oct GLOBE +0.53
As I previous posted, the difference in the +0.53 average values is a rather surprising result. /sarc
Must admit, the WEATHER in my part of Australia was absolutely gorgeous for October.
2nd and 3rd weeks of October’s WEATHER were rather warm for that time of year.
As usual.. very “up and down” in the first week and last week of October.
ie… Basically just “CLIMATE NORMAL”
What’s your best start date for the old “No warming in Australia since…” lark these days, Nicey?
Maybe you’ve stopped checking?
It’s been bloody cold in Southwest WA. It looks like harvesting has been put off another month.
Can you cross check your concerns here.
https://oz4caster.wordpress.com/cfsr/
One sideways month doesn’t cancel the downtrend. Nine months of upturn might.
Only nine?
I’m being generous. Better would be 18. But if the anomalies were warm enough, nine might do the trick.
You need to review how aggregating data, especially in a time series can mislead. One example is Simpson’s Paradox. There are others.
Let’s look at various locations in the USA48. They are CRN stations and the temps are in °C.
COLUMNS – Month/Year, Tmaxavg, Tminavg, Tavg
Manhattan KS 08/25 30.5 18.2 24.4
09/25 27.0 15.1 21.1
10/25 22.9 10.8 16.9
Champaign IL 08/25 28.0 15.3 21.7
09/25 28.2 11.0 19.6
10/25 21.6 7.1 14.4
Dillon MT 08/25 27.0 6.0 16.5
09/25 23.4 2.1 12.8
10/25 12.0 -2.7 7.4
Watkinsville GA 08/25 28.3 19.5 23.9
09/25 29.2 16.4 22.8
10/25 22.7 11.4 17.1
All four locations show falling temperatures month to month, yet anomalies lead one to believe that August and September are cooler than October.
Don’t bother telling me anomalies are monthly based. The issue is that monthly anomalies can not be compared to determine which is warmer than another. All you can say is October is warmer than some average of a number of Octobers in the past.
Read carefully about Simpson’s Paradox and why a group of data can have a positive correlation while subgroups have a negative correlation.
Huh? You didn’t post temperature anomaly data for the months of August, September and October, just absolute temperatures and temperature averages.
Nevertheless, one can only imagine the months of August and September are warmer than the month of October across USA48 if that person is so sophomoric as to believe that just four widely separated geographical temperature measurements (from CRN stations, no less) can fairly represent the average temperature of the contiguous 48 US states for those months.
In reality, all that one can conclude from the data you presented is that all four geographic locations had, in 2025, the month of October that was cooler than the month of September that in turn was cooler than the month of August, all based on Tavg.
I do believe are presenting data that has been “cherry picked”.*
Lastly, and specific to my above points, the UAH table of LAT for “USA48” provided in the above article, which is reporting temperature anomalies (in °C), gives the following values:
8/25: -0.06
9/25: +0.38
10/25: +1.12
From these anomalies, an intelligent person would conclude that August and September were indeed cooler than October across USA48.
*Overall, USCRN (United States Climate Reference Network) temperature trending data is “similar” to trending shown by UAH satellite data specific the the US “lower 48”, with differences primarily due to USCRN monitoring ground station data being more corrupted by UHI (compared to UAH) due to ground station siting problems and absence of properly measuring temperatures in remote areas (necessitating questionable “infilling” adjustments by USCRN). Nevertheless, both datasets show a current warming trend.
Of course I believe that. Even NOAA believes that. That is why the USCRN is considered the reference system for the US land temperatures. Four stations a across a wide geographical area, all having similar characteristics, is a good sized sample from a little more than 100 stations.
From NOAA at:
https://www.ncei.noaa.gov/products/land-based-station/us-climate-reference-network
Your “better than thou” attitude is really unjustified. You are one user I take pleasure in down voting.
TYS is correct here.
Absolute temperatures reflect local climatology, so they don’t tell you much about the overall CONUS mean.
What’s also puzzling is that you’re arguing elsewhere about the uncertainty of satellite datasets, yet you’re treating a four station sample as representative of the entire lower 48.
Absolute temperatures are a very major factor in climate since they are a major component of hardiness zones. Average climate *should* be an average of climate except what does “average climate” mean physically?
The issue is that there is no such thing as average climate over a geographical area of any size. Much of the central US is semi-arid desert. Closer to the Mississippi River basin, e.g. Missouri, the climate is humid sub-tropical or humid sub-continental. What does averaging the climates of the central US with that of the Mississippi River Basin mean physically?
The overall mean CONUS absolute temperature is *NOT* a physical descriptor of “climate”. Neither are any anomalies derived from those absolute temperatures.
Consider some extreme examples. Does a 1F change at a 32F mean have the same climate impact as a 1F change at a 80F mean? It’s the same anomaly, 1F. Does averaging those two anomalies actually tell you anything physically about a phantom average “climate change”?
So much of climate science is physical nonsense . Why do they insist on averaging intensive values? Why don’t they convert their absolute anomalies to relative anomalies in order to weight the contributions appropriately? Why do they continue to use the standard deviation of the sample means as a measure of the accuracy of the mean when it has nothing to do with the accuracy of the mean?
While regional climates differ, they’re still influenced by shared large-scale circulation patterns. If you perform a principal component analysis on temperature records from multiple stations within ~1000 km, you’ll find PC1 explains most of the variance, reflecting those large scale atmospheric drivers. The remaining components capture localized departure.
Then you are disagreeing with Jim Gorman, who claimed that averaging a few absolute temperatures was meaningful.
I don’t think anyone claims it does. Anomalies aren’t about identical impact. They are about relative change from a local baseline. The physical interpretation of the impact is a separate analysis altogether.
Then one must logically ask: Why don’t the operators/managers of USCERN just shut down all the other ground monitoring stations (around 100 or more) and save bundles of money???
ROTFL.
I am surprised you can’t answer this on your own. What other measurements are taken at USCRN stations beyond temperatures. Secondly, you haven’t shown that using a small number of stations doesn’t provide a representative temperature for US48.
A better refutation would examine monthly averages from all 114 stations for the months of August, September, and October and see how many have October showing higher temps than August and September. Then show how the anomalies agree with what the actual temperatures were.
And your conclusion is unjustified. Anomalies are not temperatures. One month with a large anomaly can be cooler than a month with a small anomaly.
Read these two papers that were referenced in another thread and show us the math that refutes them.
https://www.fys.ku.dk/~andresen/BAhome/ownpapers/globalTexist.pdf
https://link.springer.com/epdf/10.1007/978-3-319-58895-7_6?sharing_token=sbXE6WSQRXDxCz1xHaXO8ve4RwlQNchNByi7wbcMAY7cbOnyXPGb_s0RnWaDPsi-fI6K1wgRk6bOL9kC6yYRwi310DH8Ug5PZgVXwXHqv7_haoNpOQmHT_2Goj9ucuRDMapB1PIKXPsRfggA10Dwu7npju2yfdGUpkEBfrbwHRg%3D
And that last sentence indicates that you obviously don’t know what anomalies are. Anomalies can be temperature differences from a referenced constant value. As such if you add an anomaly (stated in °C) to the referenced constant (stated in °C, such as the 1991–2020 temperature average UAH uses for their data graph in the above article, as noted on the y-axis of that graph), one then obtains a temperature value in °C.
And temperature anomalies are referenced to a constant value, not referenced as month-to-month comparitive values.
It’s simple if you understand math and the scientific definition of a temperature “anomaly”.
I don’t disagree. However the constant must be the same for all anomalies. The last time I looked, UAH uses different baseline values for each segment, not one constant value across the board.
Otherwise, simply looking at quoted anomalies as an indicator of temperature, you end up with the Tropics being cooler than the Global value or the Arctic being warmer than the Tropics as the October values indicate.
That’s not a problem for climate science. It’s a problem for people misunderstanding what an anomaly represents.
A region’s anomaly doesn’t describe its absolute temperature, it describes its departure from its own long term average.
So if the tropics show a smaller or even negative anomaly while the global mean is positive, that doesn’t mean the tropics are physically colder than the Arctic. It means they’re closer to their normal baseline while other regions are above theirs.
The problem is that different baseline values are used for each unique temperature and not just one global value for all measurements.
Each land station has a unique baseline value based on its own station history. Each UAH segment has a unique baseline value for each segment. Consequently, anomalies can not be compared to evaluate absolute warmth as indicated by temperature.
And you would be wrong!
The places I posted show October is cooler than August or September.
Here is Watkinsville from 2015
08/2015 30.9 20.2 25.5
09/2015 27.0 17.4 22.2
10/2015 22.7 11.4 17.0
All three show October cooler than August and September. I suspect that this happens in all subgroups of August, September, and October.
As I originally said, anomalies cannot be used to compare temperatures. Anomalies are not temperatures.
Do a units evaluation. An average temperature over a month is “temp/month”. An average temperature over 30 years of a single month is also “temp/month”. When subtracted, you end up with “Δtemp/month”. You lose the absolute temperatures involved.
“Read carefully about Simpson’s Paradox”
What you are describing has nothing to do with Simpson’s Paradox. All you are saying is that whilst absolute temperatures are falling, naturally as you move from summer to winter, anomalies may show warming. That’s becasue anomalies are seasonally adjusted and are showing that October is warmer than August are cooler relative to average for the time of year.
Sure it does. Do sub-groups have different slopes than the complete group? Why do you think individual CRN stations and even state CRN averages have different slopes than the full GHCN graphs?
Averages hide tons of information like the slopes of Tmax and Tmin trends over the days in a month. You can’t just ignore this when making conclusions.
“Sure it does. Do sub-groups have different slopes than the complete group?”
That’s not Simpson’s Paradox. The so called-paradox is when all (or at least most) sub-group trends are opposite to the trend of the aggregate.
(vectors denoted by bold)
If L1 has a smaller slope than B1, and L2 has a smaller slope than B2, then L1+L2 can have a larger slope than B1+B2. All that is required is that one of the L vectors be larger than one of the B vectors, e.g. the slope of L1 > slope of B2.
all vectors have a positive slope.
Simpson’s Paradox *does* apply.
from wikipedia:
“Simpson’s paradox is a phenomenon in probability and statistics in which a trend appears in several groups of data but disappears or reverses when the groups are combined. This result is often encountered in social-science and medical-science statistics,[1][2][3] and is particularly problematic when frequency data are unduly given causal interpretations.[4] The paradox can be resolved when confounding variables and causal relations are appropriately addressed in the statistical modeling” (bolding mine, tpg)
What do you think vector means in that context? Hint, it’s explain ed in t he preceding paragraph.
The vector interpretation is describing success rate: p/q. They are not trends.
Maybe you should actually read the passage you cut and pasted. It’s saying exactly what I said. The trend in sub-groups disappears or reverses in the combined groups.
There is nothing paradoxical about having a trend in the average that is not the same as all subgroups – that’s expected. It appears paradoxical if all groups show a negative trend, but the trend of the average is positive. This might happen with temperature trends if there is missing data or differences in stations over time – but that’s why you don’t simply average all temperatures. It’s why you use anomalies and area weighting.
Or in cases where a particular subset of data is “cherry picked” from the total dataset, as I pointed out above.
No cherry picking. Remarks were being made about October being warmer than the preceding months because they had lower anomalies.
I simply want to point out that anomalies are not temperatures. You can not compare them to determine which is “hotter” or “colder” than another.
For example, in October, is the Arctic warmer than the Tropics?
Maybe you should broaden your sources. Here is one.
https://statisticsbyjim.com/basics/simpsons-paradox/
Every land station temperature record is a subgroup or a vector if you will.
There are many non-UHI global stations that show little to no warming. Yet when all are combined by anomaly, there is considerable warming being shown.
Hmmmm. Sounds like a paradox to me. For some reason the lack of warming doesn’t move around. The converse is that warming stations shouldn’t move around either. Please show us the stations that have sufficient warming to create the global warming being touted.
“Maybe you should broaden your sources.”
It was your brother’s source. I merely pointed out what it said. Statistics by Jim doesn’t really go into the same level of detail as Wikipedia, but is saying the same thing.
You so far have done zero to demonstrate how you think Simpson;s Paradox is occurring in any temperature data, or any indication that you understand what it is.
“There are many non-UHI global stations that show little to no warming. Yet when all are combined by anomaly, there is considerable warming being shown.”
That should tell you something, and it’s nothing to do with Simpson. You expect some places to have negative trends and others positive – it’s natural variability. If the aggregate is positive it means there are more positive than negative trends or that the positive trends are larger than the negatives.
If you want to invoke Simpson’s you need to explain what the confounding variable is between stations. This is tricky given the x variable is time and most stations cover the same overlapping periods. This might happen if you were looking at different stations for different time periods. E.g. start with a cold station for the first 10 years, then switch to a warmer station every decade. Then each station could show a negative trend but the overall trend would be positive.
But that’s not happening with CRN data at least. Here’s a graph a produced showing individual stations and how much they are warming.
Only one station has a strictly negative trend, and that would be rounded to 0.
A couple of stations have a warming trend over 1°C / decade.
The average trend is +0.5°C / decade.
A few footnotes on the trends.
They are based on annual average temperature, calculated from the published monthly data. I ignored any year where there were not 12 months recorded. Only stations with at least 15 complete years were included, but there is not attempt to estimate outside these years – so not all trends are covering exactly the same period of time.
I should also point out this is only the USA48 stations, so ignoring the many Alaskan ones. But it does include a rogue Canadian station.
Yet anomalies that don’t use a constant baseline value can introduce spurious trends that combine into an overall trend that is misleading.
The constant baseline is the entire point of using anomalies lol. It’s clear you don’t have a good grasp on the concept.
You keep complaining about not taking account of seasonal variation, yet then insist that a seasonal adjustment produces a spurious trend.
Uh-oh! Average GLAT for October remaining the same as September 2025 based on UAH data.
Darn the Hunga-Tonga-injected stratospheric water vapor that just refuses to dissipate according to “scientific” predictions. /sarc
Separately, the ENSO meter in the right column of this webpage just shifted to the cooling range associated with La Niñas.
TYS,
I’m still waiting for this to start:
https://wattsupwiththat.com/2016/08/09/solar-physicist-sees-global-cooling-ahead/
He was right. It cooled for more than seven years. Then the Tongan submarine volcano erupted. That effect is wearing off, so it’s cooling again.
The ENSO meter is on the left side of the webpage. When you make such a glaring error, most regulars here will wonder: Does this guy really know what he is talking about?
As the attached screen grab image clearly shows, the ENSO meter is on the right-hand side on my computer screen.
Perhaps your computer’s Web browser displays the WUWT home page and individual article pages differently?
Or do you really know what you’re talking about?
On my Lenovo computer screen, the ENSO meter is on the left and there are no people displayed. I stand by what I posted. Most people won’t have two different webpages displayed on their computer screen.
But the real question is: Do more WUWT readers have the ENSO meter displayed on the left, or the right, side of their computer monitor?
I agree that most people won’t have two different webpages displayed on their computer screen, but that was never an issue.
I stand by what I posted (including the screen grab to document my statement).
Now, having posted the above, can we think of ANYTHING more trivial to discuss???
So does CO2 forcing put the ENSO meter on the left?
Curious minds want to know.
He’s pointing out that despite ENSO recently shifting into its negative phase, global temperatures haven’t started cooling.
I live Burnaby, BC and the local climate is cooling down. Yesterday, in the very far north of Canada the temperature
of the air just broke through the -30°C level. Brrr!
Been cooling since mid 2024 !!
The last few months have been in ENSO neutral. This past week the level did slip into La Nina territory, only barely. Temperatures also trail the current ENSO levels by a few months.
ENSO takes time to propagate through the whole system, so we’ll see. I wouldn’t be surprised if we just hang around the +0.5 anomaly for a while. Nothing striking is happening right now for the land-air-ocean system.
0.5 C is reasonable forecast. My model says we hang around 0.4 C for a while, but it’s also been biased a bit low lately.
Really? The expected drop this year was expected to be in the 0.2 – 0.3 C range. That comes out to about .02 C / month. IOW, well within the ± 0.1 C error range of the UAH number. Did you really intend to point out your lack of simple math skills?
Got any scientific reference that supports your claim of an “expected” drop (i.e., decline) in GLAT for 2025 (“this year”)?
If you were meaning your assertion to be based on the UAH trending itself, you need to redo your math. As stated in the above article, UAH has established a liner trend of increasing of GLAT of +0.16 °C/decade . . . and since they are reporting that trend to two decimal places, the mathematical implication is that the variation in the trend could be from +0.15 °C/decade to +0.17 °C/decade. That works out to being the same as a trend range of 0.015 °C/year to +0.017 °C/year. Both of these are, yeah, positive changes (i.e., increases) in temperature, not declines.
And note that UAH does not make predictions for individual month-to-month variations, instead just providing a linear trend line based on 46+ years of accumulated data.
UAH North Pole logged its warmest October on record, running over +2 SD above the 30 year average.
awesome! 🙂
Uhhhh . . . sorry, but the UAH MSU satellite data does not cover the North and South Poles. The data sets exclude latitudes above +85 degrees North and below -85 degrees South.
“While the satellite data record is shorter than the surface thermometer record, it has
several strengths. It has the greatest global coverage: With 96 percent coverage of the
globe (except for small areas around the north and south poles), the satellite sensors
cover more than twice as much of Earth’s surface as do thermometers.”
— https://www.nsstc.uah.edu/climate/2011/November/Nov2011GTR.pdf (my bold emphasis added)
Is your graphed data really not for the North Pole (as titled) but instead for a North Arctic area, say +65 to +85 N latitudes?
Reanalysis data also show record breaking October warmth and an accelerating trend.
The data in the attached chart indicate a warming rate of 1.7C per decade.
North Pole should be ice free any day now
Maybe we will even see trees growing under Arctic glaciers again 😉
Depends on what ‘any day now’ means. In geologic terms, that could be 4- 5 centuries from now (about when Earth’s equilibrium temperature response to today’s CO2 concentration fully plays out). In that sense, it’s not an unreasonable answer.
Well at least you have the time scales in the right order now. You can see we really need to race to cut emissions 🙂
When the arctic was free was CO2 the cause?
It was most likely a contributing factor.
Be careful here. I get the feeling here that you may harbor a belief that CO2 must explain all past changes in Arctic sea ice (or temperature) for it to be a contributing factor in the changes we see today. This is known as the reduction fallacy.
As I often say CO2 is not the (as in one and only) cause of temperatures changes, but it can be a (as in one among many) cause.
The IPCC does not expect the Arctic to go practically ice free (< 1e6 km2 of extent) until about 2050.
You’ve got that totally right! The IPCC works on expectations, nothing at all to do with actual science, including both paleoclimatology and modeling that matches data.
Heck, the IPCC even goes so far as to assign “likelihood values” to its expectations, such as “virtually certain” (99-100% probability) or “likely” (66-100% probability), and “very unlikely” (0–10% probability) . . . something you’ll never find in any definition of The Scientific Method.
ROTFL.
Is gravity virtually certain?
Only for those persons that have two moons in their virtual pink sky.
If I were to ask what the expected outcome of a 14C atom decaying into nitrogen after say 10,000 years would be would you provide a deterministic or probabilistic answer? Do you think scientists strayed off the scientific method path when learning about beta decay or any quantum mechanical process for that matter?
Note that the topic of carbon decay isn’t central to the intent of my question. I could have picked any of a countless numbers of examples to use. My intent is to get you to think about your own understanding of the scientific method and how far you might go to defend your position on the matter.
My direct answer would be that I can logically deal with scientific predictions, but not with expectations which are subjective.
In this matter, Google’s AI is my friend, stating:
“No, an expectation is not the same as a prediction, though the terms are often used interchangeably. . . . expectations are internal and belief-based, while predictions are often external, data-driven, and more testable.”
In terms of The Scientific Method, nowhere in any proper definition of such does one find the words “expectation”, “expectations”, or “expected outcome”.
Ah…okay. I thought your grievance was related to the IPCC’s use of probabilities. Note that the word “expectation” was my own choosing here; not the IPCC. Understand that I did not mean to imply there was a distinction between “expectation” and “prediction” in this context. I was responding to Derg’s statement that “North Pole should be ice free any day now” and just naturally gravitated toward to the word “expectation” for no particular reason other than “expected” being a synonym for “should” and which would grammatically fit within the flow of my comment.
Regardless, my point is that no one including the IPCC seriously expects or predicts that the Arctic will go practically sea-ice free any day now. If my wording of this point offends you then I’m more than happy to reword it to make it less offensive.
Really? The IPCC? The people who said they could not detect the human warming signal in their first report but now say it is unequivocal that humans are warming the globe – and without one shred of any further evidence than they had in their first report? That IPCC?
Yup, the IPCC that in its first assessment report concluded that, at that time (35-years ago), the observed global warming might just be within the range of natural climate variability.
In the intervening 35-years, with a continued warming rate since the first assessment report of ~+0.2C per decade and no discernible long-term difference in natural variability, their conclusions necessarily followed the evidence.
What did yours do?
AAAAAAAAAAAAHa ha ha ha ha ha ha.
My conclusion is that a mere 35 years of additional “trending” data is insignificant in the context of:
— about 12,000 years since the beginning of the current Holocene interglacial epoch, and
— the prediction that there are another 18,000 years or so of Earth being on the warm side of the current glacial/interglacial cycle that should have a period of about 100,000 years, both values based on the last nine such cycles.
Yes.
You can see the IPCC AR6 WGI report including citations of evidence here. AR1 was published in 1990 so even just a single citation after 1990 would necessarily falsify your statement. There are many such citations.
Anyway…more to the point…the IPCC originally expected the first occurrence of a practically sea-ice free (< 1e6 km2) in the Arctic region around or after 2100. New evidence, including but not limited to the observation of rapid decline of sea-ice significantly beyond expectations, is the basis for the IPCC adjusting their expectation forward in time.
utter and complete garbage. They have no further empirical (and they never did) evidence of human warming. Stop lying.
Your statement was “and without one shred of any further evidence than they had in their first report?” which is patently false.
If you meant to say that they did not consider any further evidence after the first report that you would accept then that’s a different matter. But to just wildly proclaim that they did not consider any further evidence at all is an egregious omission of fact.
Utter drivel. All the IPCC have is speculation. They have no more measurable, observable data than they had at the start. ie; that CO2 is going up along with a slight warming. all other so-called evidence is a re-hash. Stop lying.
A politician rewrote that to change it to have a clear human signature and the scientists were quite upset.
One could speculate that funding = silence.
UAH publishes a table with a column of data for NoPol. Perhaps they shouldn’t, but they do. Take it up with them.
1) Not my job.
2) If you had bothered to look at the very bottom of the UAH table that you provided the link to, you would see that UAH has the following definition for the header in their table: “NoPol 60N-90N”
So, no, not data for the North Pole.
Sloppy, Nick, sloppy!
Eclang simply plotted the data that UAH presented as NoPol. Again, if you don’t like the description, take it up with them.
Incorrect. Even if Eclang plotted UAH data, he went beyond that and labeled his graph at the very top as “North Pole”, not as “60N-90N” which is what UAH tabulates for “NoPol”.
Now beyond sloppy, Nick . . . you’re just not paying attention to details.
P.S. I don’t have any problem with UAH . . . they handle details such as noted above just fine.
UAH says “NoPol” is the region above 60ºN.
The area not capture by the satellites above 85ºN is less than 3% of the area above 60ºN.
Given the moderate accuracy of the data.. this is irrelevant.
Reanalysis fabrications include surface temperatures, usually homogenised to places like Barrow… and numbers made-up by climate models . 😉
They are basically meaningless.
Well, the surface area from 85–90ºN is almost entirely permanent (year-round) floating sea ice.
In contrast, snow and ice covers the surface area from 60–85ºN almost entirely during NH winter, but drops down considerably during NH summer:
— Arctic sea ice extent minimum (in September) is about a third of the winter maximum extent
— only about 30% of the land area between 60 and 85ºN is covered by snow and ice at its minimum (in August), covering an estimated 2 million square kilometers, with about 87% of that being associated with just the Greenland ice cap.
So, even given the moderate accuracy of the data and the differences in areal extent, the seasonal differences between 85-90ºN and 60-85ºN make both highly relevant to Earth’s climate.
Moreover, the northern Polar cell of atmospheric circulation patterns rises at about 60ºN latitude and descends at about 90ºN and basically drives weather and climate by transporting cold polar air at relatively low altitudes toward the equator.
BTW, Just bothered to check out that assertion. Here are the real numbers according to Google’s AI bot:
— Earth’s surface area above 85ºN latitude = about 1.32 million km^2
— Earth’s surface area above 60ºN latitude = about 37 million km^2
So, the proportion is actually 1.32/37 = 0.0357 = 3.6% and therefore NOT “less than 3%” as you posted.
Oh well, to me that difference is irrelevant compared to the overriding facts I’ve posted previously.
It’s interesting viewing the CFS Wetterzentrale winter forecast model. I know it’s beyond any model to forecast with any great accuracy beyond 10 days out. However, it’s currently predicting a very mild NH winter. Hudson Bay area would have a very late freeze, if CFS is to be believed, for example. Moscow also might not have much snow cover until much later into winter than is normal. I wonder if the model is picking up on current warm Arctic, and modelling as a result a slower and less widespread advance of sub-zero conditions. Certainly, NH snow cover has been pretty slow this Autumn, especially over N America. Seems to have stalled over Russia as well. Barents Sea and well into Russian Arctic also showing a very slow advance of sea ice.
Interesting also that my comment on slow winter advance should be down voted, when my post simply presented the current NH conditions. I offered absolutely no opinion on whether this was to do with AGW or CO2. The objectivity from some using this site is about equal to some of the biased media they so often criticise.
Story tip – naughty Auntie
The BBC “doctored” Donald Trump’s January 6 speech to make it appear that the US President was encouraging his supporters to riot in the Capitol, a leaked memo has revealed.
The leaked 19-page dossier, which was shared with The Telegraph by a whistleblower, revealed that a Panorama programme broadcast a week before the 2024 US Presidential Election “completely misled” viewers
https://www.gbnews.com/politics/us/bbc-bias-donald-trumps-january-6-speech-capitol-riot
Now the interesting question may be :
Why is the BBC thousands miles away complicit in doctoring a speech about doctored jan6th.
Especially as an english top level agent(Christopher Steele) was already massively involved in the Russian collusion fakery?
What’s the English interest?
You could ask why do most Western leaders detest Trump?
They’re wimps and don’t like a guy much tougher with more common sense.
Mr Zorzin is 50% right.
He does not appear gay(one of many new trends that started with Obama and are now the norm),
nor demented.
The really interesting thing is that he is actually one of them(as a former democrat), yet they have no problems with any of the other conservative leaders(who always turn out to be leftist).
They only started to be against him about 9.5 years ago.
But all of a sudden everyone was against him.
We later saw the lite-version of that with Biden.
Everyone was on his side until a specific day –
and then they all turned against him like one.
The other 50% are that he does not share their unified opinion(a statistical impossibility) on wokeness,open borders,climate etc.
= he is considered a traitor.
Only really the woke socialists that are dementedly anti-Trump.
.. The rational conservatives like Trump.
Europe loves their globalists. Trump is working to break up globalism.
Trump does not suffer fools gladly, so the fools naturally hate him in return.
Trump getting in would have slaughtered too many of the BBC’s sacred cows. The Climate Crisis. The impossibility to stop illegal immigration. Trans women being women with no advantage in female sports.
Please stop using the word “Trans-women”
There is no such thing. No human male can ever become a human female.
Let’s call them what they are… a “Pretend-woman”
I feel pretty
I feel pretty
I feel pretty and witty and gay
/sarc
Red thumb needs to explain how a human male can become a human female..
Or have they already done it to themselves 😉
The correct term for “Transwomen” is “Transvestites”.
Except those that go through sex change surgery (non-functional, cosmetic physical modifications. Those are trans-sexual.
I have a rude, impolite, and socially unacceptable vision.
Larry Nassar giving Lia Thompson one the Nassar special treatments (pelvic floor massage).
Need I say more? Need I say I agree?
The BBC hates Donald Trump and love Bob Vylan, Hamas, illegal immigrants, Josef Stalin and all left wing politicians. They are the BBC and always right.
Would have been better with the obviously needed /sarc.
Third warmest October since 1979, though someway down from the previous two years.
October 2022 is just below 1998 at 0.23, so the last 7 Octobers are in the top 11.
My projection for 2025 is now 0.48 ± 0.05⁰C. Virtually unchanged from last months, but with more certainty. Now very likely to be the 2nd warmest year in the 46 year UAH data set.
This is also the warmest October for Australia in the UAH history, by some way. Beating the record set last year by 0.58⁰C.
Thanks Bellman. That explains all the cold waves and late snowfall in Victoria.
A weekend in Victoria makes you skeptical of decades of satellite data. Please inform the journals of this brilliant new standard of rigor.
I live in Victoria. October is always variable, but was warmer than usual. Melbourne ave min was 10.7°C, max 20.5°. Each about 1°C above normal.
Absolutely GORGEOUS, by the sounds of it ! 🙂
Not where I am. We are below average and have been for the past 4 springs.
This winter we had 9 frosts. The average here has been 2-3. It is not warming where I am. Not in the least.
No need to thank me – any issues with the accuracy of UAH need to be addressed to Drs Spencer and Christy.
What about 1896?
Still waiting for the carrier pigeons to deliver all the satellite data from 1896.
According to the BEST beta high resolution preliminary data, October 1896 was the 16th Warmest October. 1895 was the 10th. But that’s only going up to 2022.
It is as if history is being erased. For all that we hear about recent record-breaking climate extremes, records that are equally extreme, and sometimes even more so, are ignored.
In January 1896 a savage blast “like a furnace” stretched across Australia from east to west and lasted for weeks. The death toll reached 437 people in the eastern states. Newspaper reports showed that in Bourke the heat approached 120°F (48.9°C) on three days (1)(2)(3). The maximum at or above 102 degrees F (38.9°C) for 24 days straight.
Glad to have satellites over Australia. BOM and ACORN is a litany of dreadfull science.
See
https://www.geoffstuff.com/halfwarm.docx
A detailed, 19 page article showing how official Australian “warming” 1910 to 2024 of 1.51 +/- 0.32 deg C is nearly twice the value obtained by 2 proper methods.
The difference is due to homogenisation, a subjective man made invention that is NOT allowed for GUM uncertainty estimation.
Read and learn. Geoff S
Will be hotter again next year thanks to Northern Western Australia, not like the cause of it isn’t known even our lefty loon media knows why
https://www.abc.net.au/news/2025-09-26/weather-pattern-could-disrupt-australia-for-months/105817572
So push it boys you will have a couple of hot years to try and convince the sheeples.
For those of us who live and work in it well it’s real exciting that extra 0.5 deg on a 40 deg baseline makes all the difference 🙂
Well, what about January, February, March, April, May, June, July, August, September, November and December. You know, the other 92% of the full data set.
Or is it that October is a particularly significant month for monitoring climate/atmospheric temperatures because it has the holidays of US National Cat Day (Oct 29) quickly followed by Halloween (Oct 31)???
Monthly anomalies aren’t statistically independent. There is autocorrelation across months due to ENSO and other factors.
There are “other factors” that break “autocorrelation across months”, such as sub-monthly variations in percentage of hemispherical cloud coverage and the sub-monthly formations and passages of weather fronts, tropical storms and continental-size heat waves.
The largest autocorrelation is due to orbital changes. The seasons occur for a reason. It is what makes time series illustrate incorrect trends. Look into first differences to remove autocorrelation.
The main article is about the UAH October temperature anomaly update, so the comment was about the UAH October temperature anomaly update.
Is that weird?
No, what was weird was Bellman’s post of the ten years of previous anomalies for October, not mentioned or even hinted at in the “main article”.
It was Bellman’s comment to which I commented vis-a-vis leaving the other 11 months of a year unaddressed.
And more correctly, the “main article” (your words) was about the October update to the UAH temperature trending over the last 22 months (the included table of data) to the last 46+ years (the included graph of data).
But rest assured: I don’t find it at all weird that you missed these facts.
If he’d mentioned the ten years of previous anomalies for November, or June, say, then you would have a point.
But I would suggest that using the latest October anomaly, which is the subject of this article after all, to compare against previous October anomalies is a legitimate form of analysis.
For instance, do you think that if this had been the coldest October on record for Australia in UAH, instead of the warmest, that no one here would have even mentioned it?
That they would have just shrugged and said ‘it’s not legitimate to take a single October anomaly and compare it to past October anomalies’.
I doubt it.
You can’t judge warmest or coldest by using anomalies. The reference (baseline) value is an average. An “average” implies that there are values above and below the average. How far above and below no one knows because standard deviations are never quoted for any “average” used in climate science.
What if the standard deviation for the October baseline is ±2 °C? How would you rank the current anomaly?
“You can’t judge warmest or coldest by using anomalies.”
Of course you can – I just did.
As long as you are comparing like with like, same region and time if year. There should be no difference between the rank determined by anomaly or temperature, as anomaly is just temperature minus a constant.
“How far above and below no one knows…”
You keep confusing your own ignorance with a universal truth. You could easily click on the provided links and work it out for yourself.
“What if the standard deviation for the October baseline is ±2 °C? How would you rank the current anomaly?”
If the standard deviation was that large it would be very unlikely that +1.67 would be the warmest. An SD of 2, (not minus 2) would imply there were some Octobers with an anomaly if close to +4. The fact that by virtue if 1.67 being the record should be a pretty big clue that the SD is not that big.
But regardles, it makes no difference, as 1.67 is the warmest October anomaly. That’s determined simply by looking back at all the other October anomalies. No other statistics are required
Just checked, and the October sd for the base period for Australia is 0.60°C. The warmest anomaly during the 1991-2020 base period is +0.76°C.
Except the constant is not constant. Each month and each station has its own “constant”. Therefore you are not making a judgement based on a constant. It is why I proposed sometime back that anomalies should be calculated based on a global optimum temperature.
You won’t agree with that because the variance in temperatures would be apparent and the actual uncertainty would be appear much larger.
“Except the constant is not constant. Each month and each station has its own “constant”.”
Yes. Each point of interest has it’s own constant. That constant is constant. That’s why I talked about comparing lime for like. Specifically I’m talking about Australia in October, that is I’m comparing this October with other Octobers, and I’m comparing Australia in October with Australia in different Octobers, and I’m comparing anomalies based on the same base period – specifically 1991 – 2020.
“You won’t agree with that because the variance in temperatures would be apparent and the actual uncertainty would be appear much larger.”
Yes, becasue you no longer have anomalies – you just have temperatures with a different offset.
“Of course you can – I just did.”
If the anomaly at a point in Alaska is +2F and at a point in Alabama is +1F which one is the warmest?
“As long as you are comparing like with like, same region and time if year. There should be no difference between the rank determined by anomaly or temperature, as anomaly is just temperature minus a constant.”
If the anomaly at a point in Alaska is +2F and at a point in Alabama is +1F which one is the warmest?
“If the standard deviation was that large it would be very unlikely that +1.67 would be the warmest.”
If the anomaly at a point in Alaska is +2F and at a point in Alabama is +1F which one is the warmest?
“anomaly is just temperature minus a constant.”
Which still leaves the anomaly as an intensive property. Did you not bother to read the Essex paper “Does a Global Temperature Exist”?
Why does climate science not divide the anomaly by the mean to get a weighted, dimensionless metric for the actual change in climate and then average those weighted values?
+1F at 32Fis a much larger change in climate than is +1F at 80F. Yet averaging the anomaly directly leads to concluding that the change in climate is the same for both!
“If the anomaly at a point in Alaska is +2F and at a point in Alabama is +1F which one is the warmest?”
Irrelevant. The question is if the average over Australia in one October has an anomaly of +2°C and in a previous October had an anomaly of +1°C, which is warmest.
“If the anomaly at a point in Alaska is +2F and at a point in Alabama is +1F which one is the warmest?”
Same answer.
“If the anomaly at a point in Alaska is +2F and at a point in Alabama is +1F which one is the warmest?”
I refer you to the previous two answers.
Do you think asking the same irrelevant question three times makes it relevant?
“Which still leaves the anomaly as an intensive property. Did you not bother to read the Essex paper “Does a Global Temperature Exist”?”
Why? Has it become less nonsensical over the past 20 years? You can average intensive properties. I’ve explained how you can do it many times. You keep doing it. This monthly report is about an average anomaly. Elsewhere we are discussing the average CRN data over a month.
“Why does climate science not divide the anomaly by the mean to get a weighted, dimensionless metric for the actual change in climate and then average those weighted values?”
You could do that if you wished, though only if you accepted you could have a mean of a temperature. I’m not sure what good it would do you. Absolute temperatures are quite large so the percentage anomaly wouldn’t be much different to the value in degrees. It would bias the global average towards changes at colder parts of the globe.
“+1F at 32F is” a much larger change in climate than is +1F at 80F.”
You keep making this idiotic mistake every time. Degrees F is meaningless for looking at relative changes. You need to use an absolute temperature scale, e.g K. What do you think would happen to your division if the average was 0°F?
We’ve been down this road many times yet you refuse to learn the basics. The answer is that YOU DON’T KNOW. If the measurement uncertainty of each component is +/- 0.5C then the measurement uncertainty of the anomaly will be +/- 0.7C, which means the first anomaly could be as low as 1.3C while the anomaly if the second could be as large as 1.7C. Since they overlap you DON’T know which is warmest.
As usual, you just assume all measurement uncertainty cancels and the stated values are 100% accurate.
Until you can learn how to interpret measurements in the real world you will remain one of thise Essex describes as just seeing “numbers is just numbers”.
“We’ve been down this road many times”
Yes we have. Every time you lose an argument you try to change the subject. You were claiming that it was impossible to know if the reported temperature of Australia was warmer than previous Octobers “because of anomalies”. Now that argument doesn’t work you fall back on your usual idiotic understanding of measurement uncertainty.
“Well, what about January, February, March, April, May, June, July, August, September, November and December.”
Here are the rank for each month of 2025 so far.
You got +/- 0.05C?
I only got +/- 0.0475.
Let’s discuss urgently, before CoP starts.
We all need to be on the same page with this.
Cartoons by Josh “Do you have any money? Where’s my money? I heard there’d be money”
Let’s see . . . with ten years of data for the month of October, each recorded to two decimal places, Bellman is able to state an uncertainty of ± 0.05 °C for a future temperature prediction.
However, Bellman did not go so far as to say the ten—and only ten—data samples could credibly:
— be consistent with a normal distribution (e.g, be absent any significant skewness),
— be consistent with the recommend sample size of at 30 in order to ensure the central limit theorem applies, which is crucial for many statistical inferences,
— result in “± 0.05 °C” being a 1-sigma, 2-sigma, 3-sigma, or other uncertainty level.
So, yeah, why not go with your calculation of +/- 0.0475 °C uncertainty.
The projection is just based on the average so far, compared with previous years. It doesn’t take account of factors such as the trend account of factors such as if the year is cooling or warming. As I try to keep saying it’s just a bit of fun.
At this point I’m inclined to think the 95% prediction interval is too large. November and December will have to average below 0.12°C to reach the lower bound, which will be a remarkable cool down.
This chart shows the basis of my projection. The average temperature for the year up to October, compared with the final temperature for the year. There is very little variation because at this point 5/6 of the year is already fixed.
The grey area shows the 95% prediction interval.
Well to 3 dp my projection is 0.478 ± 0.049°C, but that many digits is triggering to some.
You bet it is. When CRN has an uncertainty of ±0.3 °C, and a resolution of 0.1 °C, how in the world you can increase beyond those values is a mystery to anyone familiar with metrology.
You simply cannot measure something with a ruler graduated in millimeters 1000 times and claim you know the measurement to the nearest micrometer.
Here is a university reference, that explains what is acceptable.
https://pressbooks.nebraska.edu/chem1014/chapter/experiment-2-measurements-and-significant-figures/
Those of us with a physical science or engineering education learned this and apply it to all measurements. Perhaps you can find a reference that rebuts this practice.
This has absolutely nothing to do with CRN. It’s entirely about what the UAH will claim. It’s literally just predicting what the annual average Spencer reports in two months time.
I don’t claim that UAH will be accurate. If we were talking about different data sets the result would be different. This may all be a mystery to you, but that says more about your ability to understand what I’m claiming rather than what I’m saying.
Of course it does. Work backwards in UAH and see what the input uncertainty is on their measuring device. Does that uncertainty support a temperature difference in the hundredths?
If ±4 W/m² uncertainty is what satellite measuring devices have, what is the smallest temperature that can be discerned? (I’ve already done it.)
Show us your calculations. I’ll bet it’s more than the CRN uncertainty.
You are just not getting this. My projections are not predicting what the actual global anomaly is. They are predicting what UAH will give as the 2025 average. UAH data may be wildly inaccurate. I can use the same method with different data sets, and the prediction will be different. But UAH is the only data set reported on this site – and sop that’s the one I’m commenting on.
I could do this with CRN if you want, but it won’t be the same as UAH, not just because of the problems with UAH, partly because CRN is land temperature and not the troposphere, but mostly because it’s only the US and not the 95% of the planet which is not the US.
Based on the data up to August for CRN, my projection for the US anomaly is 0.69 ± 0.47°C. There’s a lot of uncertainty, given the smaller land area, and the limited data.
First, CRN data is given with a resolution of 0.1 °C, even their averages.
How many references do I need to provide you that measurements cannot be reported beyond the resolution that was measured.
Ignoring expanded uncertainty, that would make the proper reporting 0.7 ±0.5 °C. Or, using an I interval, [0.2 to 1.2 °C]
“First, CRN data is given with a resolution of 0.1 °C, even their averages.”
Not the monthly averages this site keeps using.
https://www.ncei.noaa.gov/access/monitoring/national-temperature-index/time-series/anom-tavg/1/0
“How many references do I need to provide you that measurements cannot be reported beyond the resolution that was measured.”
One that made sense would be a start. Preferably one that explains the rational behind such a pointless restriction.
But you still fail to understand the point – which is I am not reporting a measurement. I’m projecting what I think the best estimate of what the data set will report. I can make that estimate have as many decimal places as I deem to be sensible, or enough to annoy you.
“UAH data may be wildly inaccurate.”
And you don’t care, right? Numbers is just numbers. If they don’t accurately describe the real world it’s no skin off your backside.
“And you don’t care, right?”
Why would I care. Nobody takes UAH seriously apart from those trying to play down climate change.
“If they don’t accurately describe the real world it’s no skin off your backside. ”
This entire website is dedicated to supporting UAH data. I go along with the figures rather than obsess over whether they are accurate enough. One of the ways I look into the data is to project what UAH may say is the average for the year. If Spencer, Watts or Monckton don’t care how accurate the data is, why do you think it’s my job to care. Take your issues out on Spencer – not me.
It was warm here in Colorado yesterday. Actually quite nice except for it being windy.
Anyway, I remember the late 70’s as being quite cold. I prefer warmer.
Are you sure 2 decimal places is enough? Maybe 3 or 4 would be more impressive.
[JCGM 100:2008] isn’t as definitive on the subject as many might hope, but based on the examples given if they advocate for any preference it would be to report the uncertainty to 2 significant figures which means the measurement in this case needs to include 3 digits. They do provide an example where the uncertainty is reported with 3 significant figures which means 4 digits for the measurement here would be acceptable as well.
And I’ll remind you that Dr. Spencer reports UAH anomalies with 3 digits.
You need to provide the GUM paragraph reference for this assertion. I know of no such thing in the GUM.
You need to explain what the GUM reference tells you about how to choose a value for the added digit in the measurement.
This would violate everything the GUM is attempting to do in making measurements universal all over the globe.
It defines reason to assert that you can increase resolution of a measured quantity beyond what was measured based simply on an uncertainty calculation.
This arises from you insistence that uncertainy uses the standard error of the mean and not tehe standard deviation. An example.
I have a digital voltmeter that has a resolution of 1 decimal digit. I have a voltage reference that is calibrated to 1.02 volts. I measure the reference 100 times and read 1.0 volts each time with the uncertainty being ±0.05 volts. That gives me an interval of 0.95 to 1.05 volts.
I cannot divide the 0.05 volt uncertainty by the sqrt 100 to achieve an uncertainty of 0.005 volts and also add another digit to the measurement. Doing so would mean reporting a value of 1.0# ±0.005 volts.
And if I provide the paragraph yet again and for the umpteenth time what is going to be different this time? Will you actually read and comprehend it? Or will you dismiss it like you’ve done in the past and instead copy-paste irrelevant sections of the document?
This is why I rarely engage with you. This comment and what follows has nothing to do with the discussion in this subthread. If I address it now you’ll deviate even further away from the original topic all so that you can pretend that sections of the JCGM 100:2008 document that you don’t like don’t exist.
Roy Spencer,
Please be so kind to review this comment for accuracy.
Minimal Temperature Change due to CO2: The climate is not any different, even though, atmosphere CO2 increased from 280 ppm in 1850 to 420 ppm in 2025, 50% in 175 years. During that time, world surface temps increased by at most 1.5 C +/- 0.25 C, of which:
.
1) Urban heat islands account for about 65% (0.65 x 1.5 = 0.975 C) of the warming, such as the UHI of about 700 miles, from north of Portland, Maine, to south of Norfolk, Virginia, forested in 1850, now covered with heat-absorbing human detritus, plus the waste heat of fuel burning.
Japan, China, India, Europe, etc., have similar heat islands
https://wattsupwiththat.com/2025/05/16/live-at-1-p-m-eastern-shock-climate-report-urban-heat-islands-responsible-for-65-of-global-warming/
2) CO2 accounts for less than 0.3 C, with the rest from
3) Long-term, inter-acting cycles, such as coming out of the Little Ice Age,
4) Earth surface volcanic activity, and other changes, such as from increased agriculture, deforestation, especially in the Tropics, etc.
.
BTW, the 1850 surface temp measurements were only in a few locations and mostly inaccurate, +/- 0.5 C.
The 1979-to-present temp measurements (46 years) cover most of the earth surface and are more accurate, +/- 0.25 C, due to NASA satellites.
Any graphs should show accuracy bands.
The wiggles in below image are due to plants rotting late in the year, emitting CO2, plants growing early in the year, consuming CO2, mostly in the Northern Hemisphere. See URL
https://gml.noaa.gov/ccgg/about.html
.
Here are four articles attesting to the small global warming role of CO2 in the atmosphere
.
Eight Taiwanese Engineers Determine Climate Sensitivity to a 300 ppm CO2 Increase Is ‘Negligibly Small’
https://www.windtaskforce.org/profiles/blogs/eight-taiwanese-engineers-determine-climate-sensitivity-to-a-300
By Kenneth Richard
.
The Fairy Tale of The CO2 Paradise Before 1850…A Look at The Real Science
https://www.windtaskforce.org/profiles/blogs/the-fairy-tale-of-the-co2-paradise-before-1850-a-look-at-the-real
By Fred F. Mueller
.
Achieving ‘Net Zero by 2050’ Reduces Temps by 0.28 C Costing Tens of $TRILLIONS
https://www.windtaskforce.org/profiles/blogs/achieving-net-zero-by-2050-reduces-temps-by-0-28-c-costing-tens
By Kenneth Richard
.
German Researcher: Doubling Of Atmospheric CO2 Causes Only 0.24°C Of Warming …Practically Insignificant
https://www.windtaskforce.org/profiles/blogs/german-researcher-doubling-of-atmospheric-co2-causes-only-0-24-c
By P Gosselin on 19. November 2024
Dr. Spencer has published his own urban heat island dataset. You see the effect of the UHI here. UHI accounts for a few hundredths of a degree C on the warming according to his dataset.
Dr. Spencer’s paper says the following.
The map you show doesn’t show the impact on urban and suburban stations being included equally to rural in the land based data.
No one doubts that an urban station might have an anomaly of 0.01 °C, but that occurs at a higher temperature than it would at a rural station. Show a map of urban stations absolute temps as compared to accurate (CRN) stations. Remember, anomalies are not temperatures, they are ΔT’s at various temps.
Please provide a URL of Spencer’s paper
[Spencer et al. 2025]
Hopefully you’ve had a chance to read the paper. If you did you may have noticed that the publication is hyper-focused on the average temperature for the United States and for Jun/Jul/Aug only. It has little relevance to the cumulative effect of UHI on a global scale for all months.
When considering UAH derivations of a hemispherical, or even global, temperature anomalies, it is always useful to know that UHI-corruption does not apply to the 61% of NH surface area associated with oceans nor to the 81% of SH surface area associated with oceans.
Does China getting through 4.5 billion tonnes of coal a year have anything to do with increased temperatures?
Nope.
All to do with absorbed solar radiation, mainly due to cloud changes.
Absolutely nothing to do with CO2 or emissions.
There is an “event” that appears to have happened at the time of the 2016 El Nino.
Downward shortwave radiation (ie solar) has been increasing since then.
Over that period, downward longwave, ie (H2O “back”-radiation), has been decreasing.
Nonsense. It has increased, of course.
Data is NOT your friend… evah !!
What’s your source for that? I linked to a recent peer reviewed study of decades-long global measurements.
Your chart gives no location and covers a two year period.
“Data is NOT your friend… evah !!
Certainly not for someone who doesn’t do due diligence and actually read the paper the pretty pic comes from….
PS: note the inference that data measured by climate scientists always proves that they are wrong.
Now there is a serious psychology Nobel waiting for someone there!
It’s from here ……
https://ceres.larc.nasa.gov/documents/DQ_summaries/CERES_EBAF_Ed4.2_DQS.pdf
And NB:
“Larger difference after 2016 is due to cloud
properties and after November 2019 is caused by the drift of GEOS-5.4.
1 temperature and humidity used for computing Ed4.1 fluxes (Section 2.1 in EBAF Ed4.1 Data Quality Summary). ”
“Loss of the Microwave Humidity Sounder (MHS) has caused a spurious drift in specific
humidity and temperature in the GEOS-5.4.1 reanalysis data used by CERES for data months from
November 2019 onwards. The drift causes the entire troposphere (surface to 100 hPa) to become
too moist, which leads to a drift in TOA LW ∆C”
“The Terra-MODIS water vapor (6.76-µm) and the 8.55-µm channels have degraded since
2008, leading to some artificial trends in cloud properties that are most significant over polar
regions (day and night) and non-polar oceans (nighttime). Corrections were made after the
Terra spacecraft anomaly event (February 18-28, 2016) in an attempt to restore these channels
to pre-degradation levels. As a result, some cloud properties also exhibit a sharp discontinuity
and inconsistency before and after the Terra spacecraft anomaly over Antarctica and the Arctic
Ocean during daytime and nighttime, and over the non-polar oceans during nighttime. The
TOA SW and LW fluxes are not significantly affected.
Well, it’s twenty years. But as Anthony says, it is from CERES, and isn’t even a plot of absolute DWLWIR. Instead it is just the difference between two different measurements. Here is the plot with caption:
And despite that, his comment still got 5 upvotes lol.
Don’t just assert, show factual data.
He didn’t just assert. He posted a reference.
Yes
Are you still using that extra blanket in the winter 🧐
Indoors especially.
The new Monckton Pause extends to 31 months starting in 2023/04. The average of this pause is 0.62 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 0.41 C higher than the previous one.
+0.156 ± 0.040 C.decade-1 k=2 is the trend from 1979/01 to 2025/10 covering 562 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 is 0.49 ± 0.03 C k=2.
Your model seems to have more error since 2016, indicating there is something unaccounted for responsible for the extra warming.
Yes. I agree.
I know you cover this in your narrative, but to put it in perspective for some, when Monckton’s June 2014 ‘pause’ started, the warming rate in UAH, from its December 1978 starting point, was +0.11C per decade; a total warming up to June 2014 of +0.39C.
As of now, which includes the impact of the entire period of Monckton’s so-called 107-month ‘pause’, the warming rate in UAH from its December 1978 starting point is +0.16C per decade; a total warming up to October 2025 of +0.73C.
That’s some impressive ‘pause’, right there.
However, as we know, if Monckton embarks on yet another doomed “No warming since….” campaign at WUWT (that would be the third, at least), there are still those here, old enough to know much, much better, who will swallow it hook, line and sinker.
They’re easy to spot. They call themselves ‘skeptics’.
The next so-called ‘pause’ will likely show up around 2029 or 2030. It’ll stick around for a few years until a new UAH record arrives, probably by the early 2030s.
And while that rinse and repeat cycle plays out, the real world will be edging closer to the 2C threshold.
I like the current climate and have no wish to go back to the LIA, in fact a bit more warming would be good.
I think the Medieval Optimum is a good choice.
You’ll noricenot one warmest on here EVER discusses what the optimum global temperature should be. They just imply that ANY growth means an existential threat to the earth.
I’m not sure if you think I’m one of the warmest people here, but I spent quite some time discussing the optimum global temperature. You just didn’t like it when I said there was no such thing.
Not to mention there’s no point in talking about the ‘optimum global temperature’ if we just eclipse right past it without experiencing its supposedly optimal nature.
Not a answer. Who says we are close to the optimum temperature and on what evidence?
I never claimed we were anywhere near it, nor do I claim to know what the optimal temperature actually is.
If you don’t know the optimum, then how are you sure the current warming is leading to Armageddon?
Maybe we should be burning more fossil fuels!
I might qualify as a “warmest”. I don’t know. Either way I’ve discussed an optimum global temperature before. My position now is no different than it was before. That is I do not think there is a be-all-end-all temperature that is best for Earth and I do not think warming is an existential threat to Earth.
Average, standard deviation, random walk, 1970-2020, fifty years? What about before? Even if you don’t have satellite data, you should use what you have to compare. What we have is insignificant compared to ice core data and geological data. We just haven’t been that sophisticated long enough to draw any conclusions.
According to the WMO, climate trends can only be assessed over a 30 year, or greater, period of time. So it appears that there is not much news here. In fact, the conclusions remain the same: earth is warming at about 0.29C/decade, the fastest rate of warming in thousands of years.
Yes, we are definitely in for a turbulent period ahead.
Beyond greenhouse gas forcing, several positive feedbacks are already in motion. A key one is Earth’s declining albedo. Satellite measurements at the TOA show a notable drop in reflectivity since the early 2000s.
And other real amplifiers may still be ahead of us once large scale permafrost thaw begins to release its stored carbon:
https://web.archive.org/web/20080731114610/tamino.wordpress.com/2008/06/12/the-big-thaw/
Here is a question for you about amplifiers.
I have a amplifier that has a gain of 5 and whose power is limited to 1000 watts. I input 200 W and get 1000 W out. Now I tap the output for 20 W and feed it back, in phase (positive feedback). Do I get 1100 W out?
Where does the extra power originate?
This is just like the atmosphere. Unless there is extra energy being supplied to the earth by the sun, there can be no other “amplifiers”.
The earth receives and emits a given amount of energy over the individual spectrums. The more “carbon” there is, the smaller amount of radiation is absorbed by each CO2 molecule therby resulting in the same total. Look up the term saturation of CO2.
Positive climate feedbacks don’t violate the law of conservation of energy, which is what your amplifier analogy seems to suggest.
Take the ice albedo feedback as an example. The total amount of sunlight reaching Earth doesn’t change. What changes is what happens to that sunlight once it arrives.
When the planet is colder, ice and snow reflect much of that incoming energy back to space. As the planet warms and ice melts, more of the same sunlight is absorbed by the darker ocean surface instead.
The issue is how does additional CO2 (or some other amplification factor) affect temperature with a constant absorption value?
The energy will eventually be radiated away but the planet has to warm to a new thermal equilibrium first.
If the energy was previously being reflected away, then it is amplification.
“The issue is how does additional CO2 (or some other amplification factor) affect temperature with a constant absorption value?”
By reducing the planet’s infrared emissivity.
“Where does the extra power originate?”
From the power supply of your amplifier, that’s why the output voltage is limited to the amplifier supply voltage.
Given there was a claim a few days ago that the South Pole had the coldest October since 1981, it’s interesting to note that according to the recently published UAH area data, the region SoPol, was according to UAH, the warmest October in that region.
Top ten warmest Octobers in the SoPol area, since 1979
Of course this doesn’t measure the actual South Pole, but the area below of -60°
Even more dramatic is the result for SoPol Land, which was the warmest October by over 1°C.
Here’s the UAH map for the month.