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 June, 2026 was +0.46 deg. C departure from the 1991-2020 mean, which is down from the May, 2026 value of +0.53 deg. C.
The Version 6.1 global area-averaged linear temperature trend (January 1979 through June 2026) 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 30 months (record highs are in red).
| Year | Mon | Globe | NHem | SHem | Tropic | US48 | Arctic | Aust. | Can. |
| 2024 | Jan | +0.80 | +1.02 | +0.57 | +1.20 | -0.19 | +0.40 | +1.12 | +0.97 |
| 2024 | Feb | +0.88 | +0.94 | +0.81 | +1.16 | +1.31 | +0.85 | +1.16 | +2.45 |
| 2024 | Mar | +0.88 | +0.96 | +0.80 | +1.25 | +0.22 | +1.05 | +1.34 | +1.12 |
| 2024 | Apr | +0.94 | +1.12 | +0.76 | +1.15 | +0.86 | +0.88 | +0.54 | +1.39 |
| 2024 | May | +0.77 | +0.77 | +0.78 | +1.20 | +0.04 | +0.20 | +0.52 | +0.67 |
| 2024 | June | +0.69 | +0.78 | +0.60 | +0.85 | +1.36 | +0.63 | +0.91 | +0.19 |
| 2024 | July | +0.73 | +0.86 | +0.61 | +0.96 | +0.44 | +0.56 | -0.07 | +1.15 |
| 2024 | Aug | +0.75 | +0.81 | +0.69 | +0.74 | +0.40 | +0.88 | +1.75 | +1.36 |
| 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 | +1.89 | +0.81 | +1.09 | +0.89 |
| 2024 | Nov | +0.64 | +0.87 | +0.40 | +0.53 | +1.11 | +0.79 | +1.00 | +1.61 |
| 2024 | Dec | +0.61 | +0.75 | +0.47 | +0.52 | +1.41 | +1.12 | +1.54 | +1.65 |
| 2025 | Jan | +0.45 | +0.70 | +0.21 | +0.24 | -1.07 | +0.74 | +0.48 | +1.04 |
| 2025 | Feb | +0.50 | +0.55 | +0.45 | +0.26 | +1.03 | +2.10 | +0.87 | -0.35 |
| 2025 | Mar | +0.57 | +0.73 | +0.41 | +0.40 | +1.24 | +1.23 | +1.20 | +0.80 |
| 2025 | Apr | +0.61 | +0.76 | +0.46 | +0.36 | +0.81 | +0.85 | +1.21 | +0.45 |
| 2025 | May | +0.50 | +0.45 | +0.55 | +0.30 | +0.15 | +0.75 | +0.98 | +0.81 |
| 2025 | June | +0.48 | +0.48 | +0.47 | +0.30 | +0.80 | +0.05 | +0.39 | -0.22 |
| 2025 | July | +0.36 | +0.49 | +0.23 | +0.45 | +0.32 | +0.40 | +0.53 | -0.23 |
| 2025 | Aug | +0.39 | +0.39 | +0.39 | +0.16 | -0.06 | +0.82 | +0.11 | +0.62 |
| 2025 | Sep | +0.53 | +0.56 | +0.49 | +0.35 | +0.38 | +0.77 | +0.30 | +2.44 |
| 2025 | Oct | +0.53 | +0.52 | +0.55 | +0.24 | +1.12 | +1.42 | +1.67 | +2.59 |
| 2025 | Nov | +0.43 | +0.59 | +0.27 | +0.24 | +1.32 | +0.78 | +0.36 | +1.47 |
| 2025 | Dec | +0.30 | +0.45 | +0.15 | +0.19 | +2.10 | +0.32 | +0.37 | -1.86 |
| 2026 | Jan | +0.35 | +0.51 | +0.19 | +0.09 | +0.30 | +1.40 | +0.95 | +1.17 |
| 2026 | Feb | +0.39 | +0.54 | +0.23 | +0.03 | +1.91 | -0.48 | +0.73 | +0.32 |
| 2026 | Mar | +0.38 | +0.33 | +0.42 | +0.07 | +3.74 | -0.48 | +1.14 | -3.17 |
| 2026 | Apr | +0.39 | +0.43 | +0.34 | +0.23 | +1.20 | +0.30 | +0.70 | -0.89 |
| 2026 | May | +0.53 | +0.46 | +0.60 | +0.58 | +0.21 | +0.34 | +0.10 | +0.21 |
| 2026 | June | +0.46 | +0.54 | +0.38 | +0.57 | +0.64 | +1.01 | +0.38 | +0.99 |
| Year | Mon | Globe | NHem | SHem | Tropic | US48 | Arctic | Aust. | Can. |
Time Series Plots for USA48, Canada, and Australia
The full UAH Global Temperature Report, along with the LT global gridpoint anomaly map for June, 2026 and a more detailed analysis by John Christy, should be available within the next several days here. John officially retired yesterday, July 1, 2026, but will continue working as a part-time employee of UAH.
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:
Here comes the crazies.
Angels, pins, some assembly required.
All that ranting and raving over a small bulge of badly measured warmth over an insignificant island off the coast of Europe.
But the global atmospheric temperature drops. 😉
It was quite a bit larger than that:
“But the global atmospheric temperature drops.”
Will the Gormans challenge this by arguing that the uncertainty is too large to allow for a meaningful detection?
https://www.worldweatherattribution.org/fossil-fuel-emissions-have-rapidly-worsened-european-heatwaves-in-just-a-few-decades/
Roger Pielke identifies three tricks used by WWA in their attribution studies – mathematical sloppiness, assuming the the conclusion the study seeks to prove and ignoring the evidence.
Why should anyone pay attention to them?
Averaging anomalies from multiple locations around the globe is worthless. There are three main problems.
One, if an anomaly is less than the measurement uncertainty, you cannot know if its value is meaningful or not. You have never disputed that adding or subtracting two independent random variable mean values requires adding their variances. Two temperatures each with an uncertainty of ±0.9°C also have a variance of 0.81°C. When you subtract them the combined variance is (0.81°C + 0.81°C = 1.62°C). The uncertainty is the √1.62°C = ±1.27°C. The implication is that any anomaly less than ±1.27°C is in effect unknowable and not statistically significant.
Two, anomalies do not relate actual temperatures. Especially for global values one cannot relate the figure to any specific location(s) which makes it meaningless. The warming could be driven by a change at the poles which remain frozen rather than a point changing in the tropics.
Three, the resolution of anomalies is mathematically driven fantasy. The very best stations in the U.S. have a resolution of 0.1°C. Any calculation that artificially adds further resolution is only pretending that the values are known. Quoting an anomaly to the one-hundredths place signifies that one can estimate to the one-thousandths place. Totally unscientific claptrap.
Nice summation.
I would only add that (temperature ≠ climate)
Temperature anomalies don’t define climate any better than does absolute temperature. As you point out, a change from -22C to -20C doesn’t change the climate. Nether does a change from 12C to 13C.
Diurnal temp changes are greater than this. Seasonal temp changes are greater than this. Neither change the climate definition for any locality or region let alone the globe. The climate of Kansas doesn’t change from Arctic to Equatorial during the year.
bnice2000 doesn’t understand anomalies, episode 1,000 and counting …
You don’t understand anomalies either. They should be weighted according to variance before averaging. But we never even see variance values for anything from climate science. Why should we believe anything from climate science if they can’t even do the simple stuff correctly?
Roy Spencer calculates and publishes these anomalies. Take it up with him if you don’t like his methods.
I don’t need to take anything up with him in order to point out the problems with anomalies. The entire climate science discipline seems to think that temperature determines climate when it is one of the factors with the smallest impact on climate! Who should I take that up with?
You didn’t refute ANYTHING I posted. Just the typical argumentative fallacy of climate supporters known as False Appeal to Authority.
*YOU* are the one using the data and its analysis. *YOU* need to support the use of it. Not Spencer.
Who appointed you the prosecutor, judge and jury for determining who understands what? Show us your bona fides with photos of your degrees. Someone must have seen your resume to have appointed you to this position!
You don’t need to be clever or specially ‘appointed’ to know that an anomaly for June being lower than one for May doesn’t indicate that “the global atmospheric temperature drop[ped]” between May and June, do you?
You would think that anyone with even a scant knowledge of the matter would know that monthly anomalies refer to the temperatures of each month respectively.
A lower anomaly in June than in May does not indicate that absolute temperatures dropped between June and May.
I would suggest that intelligence or degrees are not required for a person acquainted with the concept of anomalies understand this.
It would appear that bnice200 is not a person acquainted with the concept of anomalies, as his comment amply demonstrates.
What insignificant island off the coast of Europe? Jersey? Guernsey? Alderney? Sark? Ireland? Isle of Man? Lundy? The outer Hebrides? The inner Hebrides? The Isle of Wight? The Shetlands? Anglesey? The U.K. is not just one island any more than Hawaii is one island (which, don’t forget has the flag of a foreign “insignificant island” included on its state flag). You do realise that “The star spangled banner” is set to the tune of a drinking song from an insignificant island off the coast of Europe. Happy quarter of a millennium birthday for tomorrow.
No, only UAH’s mathematical calculation of GLAT declined by a reported difference of 0.07 deg C between May and June of 2026.
No scientist worth the name—professional or amateur—really believes that GLAT (emphasis on “global”) can be measured/empirically established to a resolution of 0.01 deg C . . . let alone to an accuracy of even +/- 0.5 deg C.
Even the UAH team admits the absolute calibration accuracy of individual, raw MSU (Microwave Sounding Unit) sensors on the various spacecraft they use for deriving their published monthly “global” and “regional” data is only about 1 deg C.
On top of this, there are all the adjustments needed to convert from instrument radiometric (microwave) data to equivalent temperature, such as:
— the physical equations used to convert EM frequency (energy) to average grey-body temperature considering the range of actual emissivities of the “lower atmosphere” as affected by factors such as cloud coverage, atmospheric TPW content, dust and aerosols and snow and rain particles, variation of “lower atmosphere” depth with latitude, and slant range variation with each MSU scan,
— inter-satellite calibration (bias corrections for unavoidable MSU-to-MSU calibration differences),
— diurnal drift (local time correction),
— orbital decay (altitude correction), and
— instrument body temperature effects.
Why am I not surprised that UAH consistently refuses to state their own calculation for the overall accuracy of their asserted monthly values of GLAT?
“Test all things; hold fast what is good.”
— The Bible, 1 Thessalonians 5:21
Excellent summary:
Yet they record (and report) raw temperature data with a resolution of 10mK…
[Christy et al. 2006]
from the link: “Monthly (annual) standard errors for global mean anomalies of TLT satellite temperatures are estimated at 0.10°C”
The term “standard errors” refers to the SEM, the standard deviation of the sample means. This can be made arbitrarily small by increasing sample size.
The SEM is *NOT* measurement uncertainty, it is SAMPLING uncertainty.
from the link: “Every orbiting instrument utilized in our products has experienced at least some overlapping observations with another, a key feature necessary for merging. Most overlapping periods are 2 yr or longer, allowing precise determination of instrument biases and relative drifts to be assessed.”
How do you precisely determine instrument biases when using two biased instruments?
How do you precisely determine absolute drifts when using two drifting instruments? Relative drifts is *NOT* measurement uncertainty.
This is just one more use of the garbage climate science meme that all measurement uncertainty is random, Gaussian, and cancels.
Need I point out that 2006 was 20 years ago?
Think that nothing has changed since then?
Surely you aren’t trying to say that if something happened 20 years ago it might as well had not happened at all. So I’m not sure what point is being made here. Anyway, of course things have changed. That doesn’t mean that UAH refused to provide an uncertainty analysis.
Duhhhhh . . . I posted “. . . UAH consistently refuses to state their own calculation for the overall accuracy of their asserted monthly values . . .”
See the word “consistently” . . . are you asserting that presenting an analysis of accuracy of an empirical means of measuring a given climate parameter every 20 years or so is proper conduct of science?
Since you seem to discount what I post directly, here is the Q&A exchange I put to Google’s AI bot:
Q: “Has there been any major change in use of MSU’s to derive global lower atmospheric temperature over the last 20 years?”
A: “Yes, the last 20 years have seen major changes in how raw Microwave Sounding Unit (MSU) measurements are translated into global atmospheric temperature records, primarily driven by transitioning to newer instruments, accounting for orbital satellite decay, and correcting for stratospheric interference.”
So, to directly answer you: with regards to establishing GLAT to a resolution of 0.01 deg C, and end-to-end accuracy of the absolute value of GLAT to better than +/- 0.5 deg C using MSUs on currently orbiting spacecraft, I do assert that calibration data from 20 years ago is fundamentally worthless (“might as well had not happened at all”) in terms of today’s needs and data publication.
Of course not. I’ve said repeatedly that they appear apathetic to uncertainty compared to their peers. I’ve asked Dr. Spencer to provide an uncertainty estimate with each monthly value like many of the other datasets do. Nevertheless, they still provide a useable uncertainty analysis already.
“No scientist worth the name—professional or amateur—really believes that GLAT (emphasis on “global”) can be measured/empirically established to a resolution of 0.01 deg C . . . let alone to an accuracy of even +/- 0.5 deg C.”
Well said!
It is all based on the garbage assumption in climate science that all measurement uncertainty is random, Gaussian, and cancels. Thus, increasing sample size can increase the ACCURACY of the average.
Well …. it is hot here in Kansas ….
but it was 20 F hotter in 1936 …
“but it was 20 F hotter in 1936 …”
20 degrees cooler over a 90 year period?
Based on this data, my complex global computer model just indicated that it will be below freezing in Kansas for the high temperatures during July in a mere 360 years.
P.S. Please send me another $10,000,000 so I can keep performing this important research!
For USA reference… max temps per state. Courtesy Chris Martz.
Why do skeptics always highlight summer maximum temperatures? Why not winter minimum temperatures?
https://www.ncei.noaa.gov/access/monitoring/climate-at-a-glance/national/time-series/110/tmin/3/2/1895-2026
No, it’s the climate crazies that call-out every heat wave as the end of the world.
True skeptics cheer the rising winter minimums because extreme cold deaths outweigh extreme heat deaths roughly 10:1 all over the world, even in places known for extreme heat like India. Rising winter minimums save lives.
Can you think of things to complain about with higher minimum temperatures?
The difference, which you will never understand, is that bnice2000 showed actual temperature measurements. And you won’t understand this comment either…
Isn’t if funny how no one here questions the validity of manually-recorded thermometer readings from the 1930s (even though we know for certain that, in many cases, they contain spurious warming caused by ‘time of observation‘ and other biases)?
Yet these same people will fight tooth and nail over the validity of 1/100th of a degree recorded by an electrical sensor at a modern automatic weather station IF it dares to threaten a warm record reported back in the 1930s!
LIG thermometer measurement uncertainty is obviously higher than newer and better measurement devices. Nobody disputes that. The uncertainty ranges from ±2°F to ±4°F.
You use the term “bias” incorrectly. Measurement bias can only be confirmed by calibration because it is a systematic error that is constant on all readings. There is no way to determine measurement bias from decades ago. Measurement bias is dealt with at the time of measurement by including a “correction” determined from calibration. For measurements from 100 years ago, too late, so sad, too bad!
The bias you are describing is that temperatures from long ago do not connect nicely to those measured with newer measurement devices. If you are not familiar with various technological advancements in changing the values being measured, then you don’t understand how entirely accurate and calibrated devices from 100 years ago can have different responses and values than those from newer devices.
The problem with “bias” corrections done because the values differ is that you cannot separate accuracy from simple device differences. Corrections to make data series align and that are done from guesses and assumptions are not scientific. Microclimates change, shelters change, land use changes, devices are moved, trees grow that modify winds.
If the data is not usable in the form it was originally recorded, from a scientific standpoint, it should be declared not fit for purpose and discarded. Not fit for purpose is used when a measurement result fails to meet the accuracy, uncertainty, or performance requirements defined for its intended use. It means the measurement cannot legitimately support the decision, model, or specification it is supposed to inform and should not be used.
I have read the papers that propose to discover the bias corrections needed to make past data equivalent to current measures. They all start with the assumption that modification of recorded information is a fine and dandy procedure in order to create a long data series. They all fail to deal substantially with why the data series are different. They all fail to deal with measurement uncertainty and how it is increased by this process and operate under the assumption that the propagation of uncertainty reduces uncertainty when averaging. Total scientific mumbo jumbo.
“The uncertainty ranges from ±2°F to ±4°F.”
Errrrrr . . . that actually appears to be an uncertainty-of-uncertainty range. 😉
Device and microclimate range in general. Individual stations should fit into that range with some at the low end and some at the high end. It is why averaging stations and assuming, as climate science and the warmists here do, that uncertainty disappears is total ignorance of measurements.
Then you should write a rebuttal to the peer reviewed paper I linked to, since they describe one clearly.
What is questioned is the validity of claims that anything measured now is unprecedented, or that it is in any way a crisis. It is also questioned whether human emissions of CO2 are a major, or more absurdly, the sole cause of the alleged warming.
It is clear that surface measurements were, and remain, unsuitable for the purpose of making the comparisons and inflicting the policies demanded by the alarmist faith.
“It is clear that surface measurements were, and remain, unsuitable for the purpose of making the comparisons and inflicting the policies demanded by the alarmist faith.”
Then how about satellite measurements?
The only measurements that have any meaning are the surface measurements, in the sense that they are what directly affect people on a daily and seasonal basis. It’s the abuse of the surface measurements by the climate hysterics to predict some kind of absurd apocalypse that is being questioned.
The satellite temperatures you are seeing are of the “lower troposphere”. That is a considerably different measurement than surface temperature at 2m.
They are useful for what they are–measurements of tropospheric temperatures. Perhaps in a few decades they will be useful to inform more than interest. They cannot be used to compare to the past, and they are no more valid for informing policy.
Ah, this makes 570 months running for this marvelous product of the era of satellite-based instruments. The UAH-LT record is a monument of terrible beauty, standing out like a volcanic island arising from a sea of confusion.
I agree. It doesn’t appear to be bolstering the skeptic case at the current moment however.
It does bolster the skeptics who have yet to see evidence of the climate-aggeddon that the econazis go on about.
The gentle warming of under 2°C per century experienced so far in the modern instrument era is a boon to civilization. The world is greener and the granaries full. Enjoy it while it lasts because uncontested science research says we’re due for a significant downturn, back to Little Ice Age.
Any fear of a link to this “uncontested” evidence?
Any fear of a link to this “uncontested” evidence?
Asking others to do research to support your question of whether evidence exists is a troll practice to generate hits. Do your own research.
Even NASA recognizes that the earth experiences ice ages. Those consist of glaciation and interglacials. We are currently about 12k years into the current interglacial. CO2 will have to be damned powerful to offset the cooling of the next glaciation.
Yes, and even NASA acknowledges that Earth has had about 10 consecutive glacial/interglacial cycles, all averaging to a cycle period of about 100,000 years, over the last million or so years of Earth’s climate history.
About the first third of each cycle, starting at the low point, is related to warming, while the remaining two-thirds is related to cooling and relatively briefs periods of ~constant temperature transition between the two overall trends.
So, discounting relatively brief up/down excursions that always happen within these major cycles (such as the documented Little Ice Age during the current Holocene warming and documented Dansgaard–Oeschger events), paleoclimatology history indicates that our current interglacial (“warm”) period should last about 33,000 years, yet were are only about 13,000 years into such.
Asking people to back up their assertions with evidence is completely fair. PCman999 claims to have uncontested evidence. If that’s true, it shouldn’t be hard to post a link to this evidence.
The phrase “Do your own research” is often used to mean “Do my research for me” and/or “Believe what I tell you because I said so”
Agreed. But things operate a bit differently here. Being skeptical of the consilience of evidence position is usually met with praise. Being skeptical of the contrarian position is usually met with resistance.
Translation from bdgwxese:
“The IPCC is sacrosanct holy writ and cannot be challenged.”
Hardly. I have no problem challenging the IPCC. I’ve done so regarding their predictions (like that of Arctic sea ice), mistakes (like that of the Himalayan glacier decline), and of their gradualism (like that of the lower bound of climate sensitivity). I also have no problem challenging overly aggressive positions regarding climate change like extreme Arctic sea ice loss, high climate sensitivity estimates, and the like.
Hmmmm . . . my personal observation is that no WUWT commenter has ever “praised”, or even tried to defend, the hypothesis of a flat Earth or the hypothesis that the Sun orbits the Earth .
Lol…well…there is definitely some confusion regarding the geometry of Earth. It even confuses Andy May who told me that S/4 (340 W.m-2) is a flat Earth model and said I was “dense” because I thought otherwise. This is the same article in which the Gorman’s calculate the average insolation as 552 W.m-2. So while I haven’t seen anyone defend an actual flat Earth there are definitely people that cannot recognize flat vs spherical models of Earth.
You have obviously mistaken the fact that intercepted total solar radiation at Earth’s distance from the Sun can be accurately established by considering the ~spherical Earth surface as a flat disk of radius equivalent to Earth’s average radius and being normal to the Sun’s radiation.
This IS NOT the same as saying the Earth is a flat disk, and it is not “confusing” to those that understand basic geometry and basic physics. Andy May certainly understands both apparently much better than you.
However, don’t just believe me. Here is what Wikipedia (https://en.wikipedia.org/wiki/Solar_irradiance ) explains in details:
“The average annual solar radiation arriving at the top of the Earth’s atmosphere is about 1361 W/m2. This represents the power per unit area of solar irradiance across the spherical surface surrounding the Sun with a radius equal to the distance to the Earth (1 AU). This means that the approximately circular disc of the Earth, as viewed from the Sun, receives a roughly stable 1361 W/m2 at all times. The area of this circular disc is πr2, in which r is the radius of the Earth. Because the Earth is approximately spherical, it has total area 4πr2 meaning that the solar radiation arriving at the top of the atmosphere, averaged over the entire surface of the Earth, is simply divided by four to get 340 W/m2. In other words, averaged over the year and the day, the Earth’s atmosphere receives 340 W/m2 from the Sun.”
‘Nuff said.
No. I haven’t. I even derive how the multiplication by 1/4 occurs via calculus and show that the cross sectional area of a sphere is 1/4 its surface area in the link I posted. Do you want to walk through it together?
Andy May (with many defending him) said S/4 is for a flat Earth. He literally does not understand that S is for a flat surface and S/4 for a spherical surface.
There is nothing wrong with the Wikipedia article. S = 1360 W.m-2 and S/4 = 340 W.m-2. Clearly S/4 is spherical geometry. And you seem to have agreed oringally since you stated 340 W.m-2 in another post. So why you are now suddenly defending Andy May (and others) that S/4 is flat geometry is dumbfounding to me. Is this one of those cases where if I say something, even if it is unequivocally and indisputably true, the kneejerk reaction is to take the opposite position even if it is absurdly false?
You did the setup wrong.
Assume
Fact: A point on the equator receives insolation based on a sine from sunrise to sunset. Proof:
I have other sources if you don’t believe my weather station.
At the equator, any point will see (1360 · 0.7 = 952 W/m²
The average of a sine from 0 to π/2 is (1/(b-a)) ∫sin(x)dx = 0.64. Note: this is not the RMS value (under the curve).
Since the equator is directly normal to the insolation the average value absorbed will equal (952 · 0.64 = 610 W/m². Every point on the equator will receive this amount of insolation over a 24 hour period.
Due to the angle of incidence as one moves from the equator to a pole, the absorbed value will vary as the cosine function. In essence, cos(0)=1, so the equator has no effect from an angle of incidence. At the very north/south pole, cos(90) = 0, so no absorption at all.
So what is the average value of a cosine from 0 π/2?
(1/(b-a)) ∫cos(x)dx = 0.64. Lo and behold the same average value.
The average value absorbed between the equator and the pole will be (609 · 0.64 = 390 W/m²). where does this average occur, at cos⁻¹(0.64)=50°N or 50°S
Let’s examine the temperatures that go along with this. At the equator, using the SB.
(610÷5.67×10⁻⁸)⁰.²⁵ = 322K = 50°C = 122°F.
What is the average for a north or south hemisphere.
(390÷5.67×10⁻⁸)⁰.²⁵ = 288K = 15°C = 59°F.
Funny how you get 288K without CO2 adding an extra 33 degrees.
What does 340 give?
(340÷5.67×10⁻⁸)⁰.²⁵ = 278K = 5°C = 41°F
The average solar radiation at 1AU for June 2026 was 1361.2 W/m^2.
The forecast for the average solar radiation at 1AU in July is 1360.5 W/m^2.
This shows decreasing solar radiation.
The intensity of solar radiation is not constant.
Temperature forecast July 2026:
Globe 2026 June +0.46
Forecast Globe 2026 July -0.11
You posted: “At the equator, any point will see (1360 · 0.7 = 952 W/m² . . . Since the equator is directly normal to the insolation . . .”
Sorry, but that assertion is simply not true and leads to big errors in your calculations, even granting an assumed steady state albedo of 0.3 to derive incoming power solar flux a ground level.
The axis of Earth’s rotation is inclined about 23.5 degrees to the plane of the ecliptic. The means that at the equator over the course of a year, the Sun can range from -23.5 degrees to +23.5 degrees from being directly overhead (at “zenith”) at local noon. The only times that the Sun is truly directly overhead along the equator at local noon (meaning the equatorial surface is perpendicular, or “normal”, to the incoming solar radiation vector) are on the day of the vernal equinox and the day of the autumnal equinox . . . otherwise one needs to account for the associated cosine variation of the Sun’s angle in the sky.
The path the Sun traces in the sky at a given location and for the same time each day over the course of a year is called an analemma. For all points along the equator, the analemma at local noon is a symmetric, equal-lobed, “figure 8” centered on the local zenith. (see https://en.wikipedia.org/wiki/Analemma )
You didn’t read my assumptions did you?
Assume
Thank you for quoting what you referred to.
This information from wiki is wrong. Read my response to bdgwx below.
Then by all means please let wikipedia.org (alternatively, the Wikimedia Foundation, Inc.) know your proof of this . . . I’m sure they will give your input all the attention that it deserves.
And perchance if you are referring to my earlier response to bdgwx (posted July 5, 2026 8:11 am) wherein I quoted text extracted from (https://en.wikipedia.org/wiki/Solar_irradiance ), I find that text to be straightforward and accurate, and well as clearly demonstrating that an understanding of basic geometry is all that is needed to derive 340 W/m^2 for the TOA solar insolation value averaged over Earth’s surface . . . there is no need to resort to calculus.
But speaking of information that is wrong, there is this from your previous post of July 5, 2026 6:46 pm:
“Assume . . .
sun rotates around the equator”
Do you think that changes anything if the assumption is changed to the earth rotates while the sun is stationary? Do you think the earth is an ideal sphere?
I was trying to show an equivalent ideal situation as with the earth being a perfect sphere just as using a flat earth with a surface area of π², i.e., a perfect circle instead of the formula for an oblate spheroid.
You completely missed the point: the Sun does not travel along the path of the equator, whether you want to consider that “travel” from the perspective of Earth’s surface or from the perspective of the Sun looking toward the Earth. This is due to the basic fact that the Earth’s axis of rotation is inclined 23.5 degrees to the plane of the ecliptic.
I did not miss the point. If you want to quibble about an ideal system that can help some people understand the earth/sun system then you are free to do so. I just don’t feel like changing my simple system to include more complex math for a simple one day calculation.
Even better, why don’t you discuss the complex trigonometry involved and show everyone the proper mathematical solutions to determine the insolation at every point on an oblate spheroid that is tilted in relation to the sun with an elliptical orbit if that makes you feel better. I look forward to reading it.
In case you missed it, I was asking someone who said they had, “… uncontested science research… ” to say that, “… we’re due for a significant downturn, back to Little Ice Age.”
So I wasn’t asking anyone to do research, I was asking the person making the claim to supply a link to his, “… uncontested science…”. No such link has yet appeared, to no one’s surprise….
“uncontested science research says we’re due for a significant downturn, back to Little Ice Age.”
Ah, guessing that’s Valentina Zharkova ….
Correction: “uncontested” as in here.
A self-fulfilling prophecy.
“RETRACTED ARTICLE: Oscillations of the baseline of solar magnetic field and solar irradiance on a millennial timescale”
https://www.nature.com/articles/s41598-019-45584-3
Can you post a link to several of these “uncontested” research studies saying we are going back to the Little Ice Age? I would like to review them.
What goes up, must come down… simple analogy of the Earth’s climate history.
It doesn’t affect it in any way. The record in question began at the end of a cool period popularly touted at the time as a possible return to the ice age. No one is skeptical that it has warmed a bit since then. The skepticism is directed at the cause(s) and the insistent hype that it constitutes a crisis and a justification for draconian policy.
It’s more than a bit of warming, Mark.
No, it isn’t. By the best data available, it seems to have warmed a degree Celsius or so since the end of the Little Ice Age, the coolest period of the last 10,000 years, and by all accounts a particularly unpleasant climatic episode for much of the Northern Hemisphere.
The video is quaint, but it describes nothing more than changes in heat distribution. The Arctic seems to serve the purpose of a sort of thermostat/heat transfer zone. Ice comes and goes.
None of it constitutes anything particularly alarming, and certainly nothing to call a crisis. Now, if the planet suddenly stopped changing, that might be something to get yer knickers in a bunch over!
You can’t think of even a single person that is skeptical that the Earth has warmed?
No. How much, why, and on what timescale are subjects of debate. I can think of no one who insists the planet has remained the same temperature.
Insisting that has remained at the same temperature and being skeptical that it has warmed are different things. I’m addressing your later statement.
Remember that Dr. Spencer and Dr. Christy once questioned whether it was really warming.
The site occasionally publishes articles like The planet is no Longer warming or UAH – What is Foretold which questions whether the planet is warming.
Even in the comments of this very article you can see posters questioning the temperature record which shows warming. The typical argument is that the global temperature is too unreliable or the uncertainty is too high to know for sure if the planet is warming.
I am unsure what you are getting at. “The planet is no longer warming” implies that it did warm. Do you mean that it is not warming at a constant rate consistent with an alleged CO2 forcing? That I am skeptical of. Is it warming at any point in time? That is hard to say.
That it has warmed and cooled over the course of millennia, centuries, decades, etc. seems uncontestable. The surface temperature record is unsuitable for comparison at the precision level it is subjected to in claiming record heat from year to year, but I think it is useful, along with other evidence like historical accounts and biological proxies, to support the claim that it has warmed in general since the end of the period known as the Little Ice Age.
As for establishing a “global” temperature that can be tracked as some sort of diagnostic tool, I think such a thing, even if possible, is as yet premature. The satellite record is the only truly global record. It tells us much about heat distribution in the troposphere, but is it really a record of the temperature of the planet? I recall the claims in the 1970s about the coming ice age. There was more snow in the winter in the Salt Lake Valley back then. It seems that there has been some warming since then. How much is urbanization responsible?
So, to again answer your vague question, “You can’t think of even a single person that is skeptical that the Earth has warmed?”, I remain unaware of anyone who insists that the planet has not warmed since periods of cooling in the past.
I’m just saying that there are enough people who question warming (whether it is a “has”, “is”, or otherwise) that it shouldn’t be hard to find at least one of them here. Also, the context was that of the UAH satellite temperature record. See Whetten Robert L’s post to which Erdosion was responding.
Find one, in any context. I see much discussion about why and how much, but I have seen none who insist that temperatures are the same as they were in the late 1970s.
I already provided examples.
I see no examples of anyone stating there has been no warming ever, or that there has been none since 1979. Spencer and Christy’s data show a decadal warming of 0.16° C.
To quote Roy Spencer’s latest post:
” The Version 6.1 global area-averaged linear temperature trend (January 1979 through June 2026) remains at +0.16 deg/ C/decade (+0.22 C/decade over land, +0.13 C/decade over oceans).”
In comments for the recent post Closer to the Fire – Increasing Tropical Sunlight – Watts Up With That? we find some arguing that there has been no net warming since 1880 (that temperatures reached levels in the same ballpark as today in the 1880s, cooled, and warmed again in the 1930s, cooled again, etc). Many insist that any warming post 1850 is a rebound from the cooling of the LIA.
I still do not understand what you are attempting to establish.
From the article by David Archibald you cited:
“From this downtrend, can we say that the Modern Warm Period is over, that global warming is definitely over, dead and buried, when the current downtrend regime takes us below the lower bound of the previous uptrend channel?”
He does not say there has been no warming, only that the warming is within a narrow envelope and may have ended.
That it is not hard to identify people who are skeptical that warming has or is occurring. We have people in the comment section of this very article who are skeptical of the temperature record.
He said and I quote “global warming is over, dead and buried”. The problem…global warming is still occurring. It is an unequivocal and indisputable example of someone who is skeptical that the planet is warming.
No, he asked four years ago, in context:
“From this downtrend, can we say that the Modern Warm Period is over, that global warming is definitely over, dead and buried, when the current downtrend regime takes us below the lower bound of the previous uptrend channel?
That question remains unanswered since the downtrend he refers to did not continue.
You can rationalize all you want. It is not hard to find people that are skeptical that the Earth is warming. I’m in a discussion in this very article with at least 3 people who rejects that a global temperature even exists never mind that it is accurate or reliable enough to demonstrate warming. If you can’t hear the cacophony of skepticism in this regard then you are doing the digital equivalent of putting your fingers in your ears and saying “la..la..la” loudly enough to convince yourself it isn’t happening.
Mark,
So what is the “cause” of the alleged T increase since 1979 when these UAH reports started?
What is the mechanism? Is it cloud cover, or change in total precipitatable water, or areas of polar ice change or improvements in instruments, or what else?
Next question: if global average temperature wanders outside the brackets of past temperatures, what triggers feedback type corrections to return it to the fold? Is there a God watching, or is there a known meteorological thermostat, or do we simply not know?
There is a variety of Rumsfeld style unknown unknowns that make it extremely dangerous for political decisions like Control Knob CO2 leading to net zero and subsidies for electric cars and brainwashing of school children.
Future generations will excoriate us for accepting garbage as gospel.
Geoff S
Who knows, to all of the above? I tend to consider the planet, taken as a whole, to be relatively stable by default within a remarkably narrow range of conditions despite some rather remarkable perturbations. If that were not the case, I do not think we would be here to knock the subject about.
One cannot even be certain what future generations will think of the whole thing, if there will be any around to ponder it, or if they will have maintained a level of prosperity to waste time doing so. Humans are definitely far less stable than the planet.
Here are my takes on this.
El Nino doesn’t warm the globe. It is a repositioning of warm water from the west to the east in the Pacific. The water doesn’t get warmer, it just moves. The trade winds control what happens and are probably affected minimally by a warming atmosphere.
The steps in UAH at the time of El Nino’s indicate that the satellites are seeing a larger area of warm water than when it is stacked up in the western Pacific. Is this really global warming affecting.
Steps or temporary shocks that don’t decay in a time series are a problem. They should decay and sometimes it takes special treatment to rapidly decay a step that is not permanent.
The warming and increasing temperature of the Earth is due to increasing solar radiation. The Earth may be heading for another Little Ice Age. There are signs that the Earth’s orbital instability is increasing.
My forecast for the coming month:
The average solar radiation at 1AU for June 2026: 1361.2 W/m^2.
The forecast for the average solar radiation at 1AU in July 2026: 1360.5 W/m^2.
Temperature forecast July 2026:
Globe 2026 June 2026: +0.46
Forecast Globe July 2026: -0.11
The parameter I used for the seasonal delay may have been too small and may have caused too large a temperature decrease. The parameters need to be fine-tuned.
You can only make monthly forecasts if you know the causes of the temperature changes.
Make a forecast for the Earth’s temperature anomaly for July 2026 and see whose parameters match best.
If my parameters for decreasing temperature in July match the outcome, the parameters I am using are correct.
How does decreasing temperature match Earth’s energy budget / imbalance and increasing CO2 levels?
Those who believe in Earth’s energy imbalance and CO2 causing rising temperature cannot explain why Earth’s temperature suddenly starts to decrease.
No it isn’t. The Earth Energy Imbalance is currently around +1.5 W.m-2.
No it isn’t. There is nothing wrong with Earth’s orbit.
Ok. We’ll check back in a month. -0.11 C is pretty bold. I hope it works out for you!
Pretty well actually.
None of us have a problem with the explanation.
Explain the +0.5C and -0.5C oscillations in your graph, where does the stored heat energy go in the atmosphere when the temperature drops by -0.5C?
Is it suddenly the weather that causes the temperature to drop by -0.5C, and when the temperature rises by 0.5C, the cause is the Earth’s energy imbalance?
You do not answer the question of where the heat energy equivalent to 56 million Hiroshima atomic bombs is added to the atmosphere and then disappears from the atmosphere comes from and goes to.
This is because the Earth’s heat imbalance cannot explain this.
Your graph does not explain where the heat comes from and goes to when it disappears.
You do not understand my question and have no answer to my question.
AI calculation for 0.5C temperature change:
Good questions.
Essentially. We don’t know everything going on.
Climate science wants to invoke conservation of energy in radiation while ignoring the fact that there is an intermediate system called ocean/land. These are not black bodies yet that is how they are treated
Meaning heat balance has to be calculated for literally century-long intervals. Not a piddly 30 years or less.
I’m trying to calculate future Earth temperature using TSI data at Earth distance and seasonal lag.
Seasonal lag appears to be different for different climate zones and different for ocean and land. All the data is available. It is just a matter of doing the calculations and making them consistent with future temperatures.
I can’t find daily actual distance measurements to the Sun.
I can see small deviation variations in TSI data at aphelion and perihelion that started in 2021 and seem to be getting larger each year. I suspect that these small deviations may be due to changes in Earth’s orbit and are visible in the TSI data. I can’t figure out the real reason.
TSI data at Earth distance June 30 (aphelion July 6, 2026) was the lowest since the measurement series I use began in 2018. It was these low measurements that I used to estimate the lower TSI in July. The variations only last for a month and then decrease and stop:
20260626.500 1318.4798
20260627.500 1317.8538
20260628.500 1317.1656
20260629.500 1316.6093
20260630.500 1316.3182
20260701.500 1316.3902
20260702.500 1317.2867
20260703.500 1317.6742
I can make a graph of these TSI deviations and make a comment next month.
If you make calculations on the heat balance that your data shows and affects the Earth’s future temperature, we can compare the results and which ones are the most consistent.
It’s impossible to quantify the heat balance because 1. it has to be evaluated over the period of the lowest frequency signal (e.g. centuries at least) and 2. the measurement uncertainty is too large to even determine the sign of the trend let alone the actual difference.
Climate science tries to identify an imbalance of something in the vicinity of 4 W/m^2 using a “global” average temperature. The total measurement uncertainty associated with that average is at least 20-50 W/m^2, a total of instrument Type A accuracy and Type B spatial sampling uncertainty. The uncertainty is even larger for pre-1800 because of poor spatial sampling, poor instrument resolution, and the use of “proxies” that have neither the time/spatial sampling or the measurement accuracy needed. If you think of the variation in a signal from just the measurement uncertainty as a noise signal which is neither random or Gaussian, it just overwhelms the signal being searched for.
Yet climate science totally disregards this. They assume that all measurement uncertainty is random, Gaussian, and cancels leaving only the statistical sampling uncertainty which can be made infinitesimally small with a large enough sample size.
If you’ll notice, none of your TSI data seems to have a measurement uncertainty associated with it. How do you tell whether the differences you are looking at are real or not?
I use data from the TSIS1 instrument mounted on the ISS.
The accuracy of TSIS1:
These uncertainties sound suspiciously like those that climate science push for surface measurement stations – which are not measurement uncertainties but the sensitivity of the sensor itself. The problem is that the measurement uncertainty involves *all* of the systems in the measuring station, things like analog to digital converters, bridge variance with heating, etc.
I cannot find any form of a measurement uncertainty document for these satellites that lists out all possible uncertainties and how they are estimated. One clue is that nothing you list gives any dependence on heat (i.e. electrical current) over time causing components to age and drift. They sound more like initial calibration tolerances – which are *NOT* indicative of measurement uncertainty over time.
In addition, the 1361 +/- 0.5 W/m^2 sounds suspiciously like the sampling uncertainty, not the absolute measurement uncertainty. It’s like the .003% accuracy given for surface temperature average accuracy. The standard deviation of the data divided by the number of samples is not measurement uncertainty, it is sampling uncertainty.
I’m not sure that TSI is an appropriate measurement to use determining atmospheric boundary air temperature. TSI encounters a number of path disruption on its way to the surface. Atmospheric absorption and scattering, clouds, particles, etc.
Once at the surface, on land, the surface reflects a portion of the incoming insolation such as visible green. The part that is left warms the soil and part of the energy is diffused downward and is not immediately radiated.
USCRN stations have two useful databases, one for 5 minute average data and one for hourly average data. I wish the 5 minute data had insolation and surface temperatures but it does not. The hourly data files do have averages for insolation average, max and min and surface temperatures for surface average, max, and min and soil temp averages for 5, 10,20, 50, 100 centimeters. Surface temps are the actual temp value of the “dirt” at the surface. The 2m air temps are separate.
You can find all the information you need at Index of /pub/data/uscrn/products/hourly02/.
There is a readme file that has great information and a headers file that can be used to help create a .csv file.
I have been working with this information trying to decipher what it means and how to display what is occurring in the sun -> earth -> air system. One quickly gets into the need for gradients. How fast does the surface warm, how fast does diffusion put energy to depth, how much does the surface cool when it radiates, how fast does the air warm and cool when it absorbs and radiates. One quickly sees that using average TSI to calculate OLR (outgoing long wave) is only part of the story when t⁴ becomes involved.
I did a climatology 18-20 (1/1/2018-/12/31/2020) of TSI at Earth distance. Then I made a TSI anomaly graph and compared with global/NH/SH temperature anomaly. There is a seasonal lag between the curves of about 24-29 days.
I asked AI if there was any correlation between the curves and got the following answer:
I think the seasonal shift can show future temperature. Is this method something you have tried?
It isn’t something I would try. After seeing the lags in surface temps and atmosphere temps compared to insolation on a daily basis I’m not sure a seasonal change would have a large enough effect to predict temperatures. And, I’m just looking at land. I don’t really know what effect that has atmospheric temperature. We already know that clouds have a large effect on albedo.
I guess I’m just doing one thing at a time. That is insolation and how it affects land temperatures at the surface and deeper in the soil. If we don’t know how much energy is removed by diffusion into the soil there is no way to know what is radiated.
It’s a fool’s errand, but there’s no harm in you confirming that.
What is NOT known scientifically to significant accuracy to support your plan is the variation in Earth’s albedo (due primarily to irregular, global variations in cloud coverage, surface vegetative coverage/”greening”, and snow/ice surface coverage).
According the Google’s AI bot when asked about Earth’s albedo:
“The absolute value is known to an accuracy of ± 1% to ± 2%, meaning the true global mean falls within a narrow band of 0.29 to 0.31.”
I’ll just note that a 1% difference in albedo is equivalent to about a 3.4 W/m^2 difference in solar radiation at ground level. So it’s really absurd that some people perform Trenberth-style “energy budgets” (which are actually power flux budgets) to derive a net EEI asserted to about 1.5 W/m^2, less than one-quarter of the best accuracy of knowing Earth’s albedo . . . and that’s just for the input side of a budget analysis!
Since the power fluxes involved originate at different temperatures over different time periods, trying to equate in and out flux values is a fools errand as well. The albedo variation is all of what you say plus the “heat sink” effect of the ocean and land.
Hah, there are NO credible science-based reports of such . . . I invite you to provide the name & author of, or link to, one . . . just a single one such published credible report will suffice.
Earth’s orbit is tremendously stable over millennia, barring the near-passage or impact of a massive celestial body. Look up “Milankovitch cycles”.
However, I understand that some in the practice of astrology like to foretell of such. /sarc
+0.75 C over 37 years or 0.02 C per year.
Hardly a trend of terror.
Err – 570 months is 47.5 years not 37 surely?
Yeah, so is all this graphing telling our UFO Aliens tourists to now expect 16C on any given spot they may land on Earth instead of the 15C they would have experienced back in 1979?
Maybe this a cunning plan by the UN / WEF to deter the forthcoming Alien invasion?
(if it works, Hollywood will be sooo pissed off. I will too. I loved those B-grade aliens sci-fi movies at the 1950s Saturday afternoon picture shows. 🙂 )
I wonder how much of the 16°C vs 15°C is due to the newer stations added in, and outlier, edge events (like a warm spell near one temperature station representative of all Antarctica, -80 vs -90).
Yet a trend which is the same as that found in all the surface data sets, within statistical margins, and one that this site and others spent years telling people didn’t even exist.
Now that it’s impossible to deny, not least because over the past 20 years UAH, darling dataset of the ‘skeptics’, has been warming slightly faster than NASA_GISS, suddenly the tone changes from, “it’s not happening” to, “yes, it’s happening; but it doesn’t matter!“
I think phase 3 of denialism is, “Ok, it is happening and it does matter; but we can’t do anything about it, so let’s just keep giving fossil fuel companies more money anyway!”
Don’t forget, they’ve still got “UHI” and “Junk stations”. Oh, and it’s SW that is clearing clouds”.
That last thing is true but it is part of the feedback of the GHE.
The satellite datasets start in (January) 1979.
The attached graph shows how the 20-year (/ 240-month) trends have evolved from January 1999 to May 2026 for the main surface (GMST) and satellite (lower-troposphere global average) temperature anomaly datasets.
The situation is “slightly” more nuanced than your summary.
Third warmest June, and mean the last three years have been the three warmest June’s since at least 1979.
Warmest Junes according to UAH are now.
Assuming an uncertainty of 0.1°C, it would be reasonable to assume that 2024 holds the record, but it’s a 3 way fight between 1998, 2025 and 2026, for 2nd place.
A Monte Carlo run, again assuming a monthly standard uncertainty of 0.1 gives the following percentages for each Rank for June 2026 – that is the probability that this June is the warmest June, second warmest June etc.
Rank Percent 1 4.0 2 28.0 3 25.9 4 19.4 5 11.0 6 5.8 7 3.0 8 1.5 9 0.7 10 0.3 11 0.2 12 0.1 13 0.1I’m surprised there’s as much as a 4% chance this could have been the warmest June, but the assumed uncertainties for UAH are quite large.
Here’s the probability of which year had the warmest June. This run increased 2026’s odds slightly.
The El Nino event that started mid 2023 has been a strong and protracted one..
Has it fully decayed yet.. who knows !
Facts are futile with these people.
https://cpc.ncep.noaa.gov/products/analysis_monitoring/enso/roni/
Your ignorance of the difference between an El Nino event…
… and the El Nino phase of ENSO.. highlighted yet again.. Well done.
During bnice’s version of La Nina, cooler sea surface temperatures somehow supply just as much water vapor to the atmosphere, producing the same lower tropospheric warming as El Niño. Fascinating.
Your lack of understanding of what an El Nino event does…
… is quite hilarious. 🙂
Thanks for the laugh. 🙂
As I have often told him – he proposes a 1st LoT busting concept.
IOW: His cognitive dissonance has invented FREE energy!
Bless, what psychology does to protect the mind’s equilibrium.
You have yet to show how water vapor warms the lower troposphere. You do realize that latent heat is not sensible therefore not measurable, right?
That has nothing to do with what I said.
Water vapor does not warm the lower troposphere. Much of the heat contained in water vapor is latent heat that is not sensible. When water vapor evaporates, it does so at the current temperature of the surface and effectively cools the surface.
“Water vapor does not warm the lower troposphere.”
Yes, it does. By condensation.
With respect to the surface, you’re correct though.
From Dr. Spencer:
“A Note on These Tropospheric Temperature Anomalies vs. Surface Temperature Anomalies
It has been a while since I have discussed the main reason why our global monthly satellite-based tropospheric temperature anomalies can sometimes differ by quite a lot from the global monthly surface temperature anomalies. A good example is the last 2 months. In April, our +0.39 deg. C anomaly was statistically identical to the +0.38 deg. C surface temperature anomaly from the NOAA Climate Data Assimilation System (CDAS, which I take from WeatherBell.com maps). But then last month (May) the CDAS anomaly went down slightly (+ 0.34 deg. C), while our UAH anomaly went up considerably (+0.53 deg. C). These month-to-month fluctuations in the relationship between surface and tropospheric temperature changes are almost certainly dominated by fluctuations in moist convective heat transfer from the surface to the free troposphere. When there is a burst of extra convection (usually in the tropics), it cools the surface and warms the free troposphere more than normal, which is probably what happened last month (May).”
https://www.drroyspencer.com/2026/06/uah-v6-1-global-temperature-update-for-may-2026-0-53-deg-c/
Condensation –> latent heat release
Condensation occurs at night when the dew point is reached by the atmosphere. It is not a major driver of temperature over most of the earth.
You don’t even know what this means do you? Where does precipitation take place in the free troposphere? Condensation is at the boundary between surface and atmosphere. Two different processes, two different results.
Thank goodness! 3rd warmest is awesome – would hate it to be the 3rd coldest, as cold kills more people than hot, roughly 7-10 times more over the world. The last few warmish years have meant bumper crops, and global prosperity is proportional to warmth.
“would hate it to be the 3rd coldest”
Clearly some do hate it. The skepticulzzz hoping global temperatures will cool, even though greenhouse gases like CO₂ have produced a massive positive energy imbalance that persists and continues to increase.
Third warmest June.
The Earth’s highest June temperature was in 2024.
The Earth’s June temperature is decreasing after 2024.
It depends on how you express the temperature changes.
Here’s my global map based on the LTL gridded data.
Pretty warm over Western Europe, but the hottest anomaly is over Russia.
Unusually cold over Antarctica.
Here are the countries with the highest anomalies.
1 Fr. S. Antarctic Lands 2.41
2 Switzerland 2.29
3 France 2.16
4 Spain 2.11
5 Luxembourg 2.05
6 Portugal 1.99
7 Austria 1.77
8 Germany 1.76
9 Italy 1.74
10 Slovenia 1.73
11 Falkland Is. 1.72
12 Belgium 1.69
13 Czechia 1.63
14 Netherlands 1.54
15 Croatia 1.54
16 Denmark 1.52
17 New Zealand 1.51
18 Estonia 1.48
19 Finland 1.48
20 Latvia 1.38
Very much dominated by European countries. But the top of the chart is French Southern and Antarctic Lands, which I probably should exclude.
And here are the coldest anomalies.
1 Antarctica -1.30
2 Uruguay -0.99
3 Mongolia -0.92
4 Paraguay -0.92
5 Georgia -0.85
6 Azerbaijan -0.70
7 North Korea -0.68
8 Armenia -0.63
9 Iceland -0.54
10 Libya -0.42
11 Turkmenistan -0.34
12 Cyprus -0.26
13 Japan -0.25
14 Egypt -0.09
15 Uzbekistan -0.09
16 Madagascar -0.05
17 South Korea -0.03
18 Greenland 0.00
19 Bangladesh 0.04
20 Algeria 0.04
According to my mapping the following countries had their warmest June in the UAH dataset.
Spain and Portugal are the most significant in terms of land area. The two island groups are mostly just down to the sea temperature. Panama is interesting, given it was only 0.9°C above average – it shows how much less variability there is in tropical climates.
No country had it’s coldest June.
Here is the rate of warming for the month of June.
Central Europe and parts of Northern Russia are the fastest warming areas in June, and there is a significant cooling in parts of the Antarctic.
The countries that are warming fastest in June are all in Europe
1 Austria +0.61 ± 0.20 °C / decade
2 Slovenia +0.60 ± 0.20 °C / decade
3 Luxembourg +0.59 ± 0.21 °C / decade
4 Switzerland +0.59 ± 0.20 °C / decade
5 Czechia +0.59 ± 0.20 °C / decade
6 Germany +0.56 ± 0.20 °C / decade
7 Croatia +0.56 ± 0.20 °C / decade
8 Slovakia +0.55 ± 0.19 °C / decade
9 Hungary +0.55 ± 0.19 °C / decade
10 Belgium +0.53 ± 0.22 °C / decade
11 Bosnia and Herz. +0.50 ± 0.20 °C / decade
12 Serbia +0.48 ± 0.20 °C / decade
13 Netherlands +0.48 ± 0.22 °C / decade
14 Poland +0.47 ± 0.20 °C / decade
15 Romania +0.47 ± 0.18 °C / decade
16 Moldova +0.46 ± 0.19 °C / decade
17 Montenegro +0.46 ± 0.21 °C / decade
18 Italy +0.46 ± 0.19 °C / decade
19 France +0.44 ± 0.17 °C / decade
20 Ukraine +0.41 ± 0.21 °C / decade
And here are the slowest warming in June. Only Antarctica and Pakistan have a cooling trend, but none of the trends in this group are significant.
1 Antarctica -0.07 ± 0.24 °C / decade
2 Pakistan -0.04 ± 0.15 °C / decade
3 Bahamas +0.02 ± 0.09 °C / decade
4 India +0.02 ± 0.07 °C / decade
5 Iceland +0.04 ± 0.21 °C / decade
6 Afghanistan +0.04 ± 0.22 °C / decade
7 Bangladesh +0.05 ± 0.09 °C / decade
8 Qatar +0.05 ± 0.09 °C / decade
9 Cuba +0.05 ± 0.09 °C / decade
10 Solomon Is. +0.07 ± 0.07 °C / decade
11 Jamaica +0.07 ± 0.08 °C / decade
12 South Korea +0.08 ± 0.15 °C / decade
13 Tunisia +0.08 ± 0.16 °C / decade
14 Taiwan +0.08 ± 0.08 °C / decade
15 Japan +0.08 ± 0.17 °C / decade
16 Fr. S. Antarctic Lands +0.08 ± 0.21 °C / decade
17 Myanmar +0.09 ± 0.06 °C / decade
18 Libya +0.09 ± 0.12 °C / decade
19 North Korea +0.10 ± 0.16 °C / decade
20 Nepal +0.10 ± 0.12 °C / decade
For some years I would add an Australian perspective comment to these monthly WUWT articles. The original Roy Spencer blog has several rusted on sad people.
These perspectives stopped a few months ago because I could not see a feature interesting enough. Today, I would like to suggest that UAH Australia anomalies potentially show a climate change expressed as a cessation of earlier, periodic sharp, symmetric peak excursions in the hot direction. The last 2 1/2 years or so that looks more like a noisy random walk, with several hot excursions that do not look like the classic 1998 peak that first filled some of our minds as typical.
But then, much the same could be said for Canada, in a different hemisphere.Canada had a sharp 2020 hot that Australia did not, so there are differences. Also, Canada has deep cooling excursions in those 2 1/2 years, Australia not. US48, different again. it makes some sense to interpret Nth & Sth hemis separately, because combining them might cancel out some seasonal features.
Overall, there are two many different regional patterns to allow prognostication.
So, Geoff S is hibernating for a few more months before commenting on our regional UAH observations.
Thank you again, Dr Roy, for your brilliant contribution of this technique and for including Canada, US 48 and Australia graphs.
Geoff S
“had a sharp 2020 hot that Australia did not”
It depends on how you define “sharp hot.” Arguably, the entire globe is significantly hotter than it would have been without AGW.
How do you know the warming is anthropogenic? You don’t.
Warming of 5 to 15 degrees c in less than 50 years is quite common:
https://www.britannica.com/science/Dansgaard-Oeschger-event
Among the surprises that have emerged from analyses of oxygen isotopes in ice cores (long cylinders of ice collected by drilling through glaciers and ice sheets) has been the recognition of very sudden, short-lived climate changes. Ice core records in samples extracted from Greenland, Antarctica, Canada’s Arctic Archipelago, and high mountain glaciers in South America show that these climate changes have been large, very rapid, and globally synchronous. Over a period of a few years to a few decades, average temperatures have shifted by up to half of the temperature differences seen between the Pleistocene ice ages and their interglacial periods—that is, as much as 5–15 °C (9–27 °F). Although some scientists note that there may have been up to 25 D-O events during the most recent 120,000 years, detailed analyses of the most accurately dated Greenland ice cores show that 13 D-O events occurred between 11,600 and 45,000 years ago, with an average periodicity of 1,470 years. This regular occurrence has led to the suggestion of a 1,500-year cycle of climate change.
From your link:
“Evidence of Dansgaard-Oeschger events is primarily observed in and around the North Atlantic Ocean, specifically in Greenland ice cores.”
So, Greenland and not the globe.
Polar regions naturally experience much larger climate variability than the global average. Greenland warming by 5–15°C over a few decades is not equivalent to global mean temperature changing by 5–15°C over the same period.
Not to mention these events occurred during the last glacial period, when massive Northern Hemisphere ice sheets and much lower atmospheric CO2 created a climate state very different from today’s.
Well there aren’t any ice cores to drill on the equator are there?
Natural variation is much greater than seen by a couple of human life spans.
There is no climate crisis.
Well there is one on Mt Kilimanjaro which is at 3ºN
You seem to be saying that all proxies are only applicable to the local areas from which they come. That would even cover temperatures too I suspect. Taking an unusual hot spell in Great Britian and averaging with a cooler temperature in Brazil would show global warming, right?
The logic behind your assertion escapes me.
“Taking an unusual hot spell in Great Britian and averaging with a cooler temperature in Brazil would show global warming, right?”
No.
So you agree, averaging temperatures whether from a proxy or a thermometer is meaningless.
No.
I simply disagree that averaging a warm anomaly in Great Britain with a cool anomaly in Brazil would somehow demonstrate global warming.
At most, it would describe the average temperature anomaly of those two locations over whatever time interval you’re referring to.
What color is the sky in your reality? It must be fascinating living in a world where Brazil and Great Britain apparently represent the entire planet.
The entire plant has cooled slightly in June, and a whole lot over the last two years.
Must be CO2. !
I like apples.
Since there is no such thing as a global mean temperature your comment is meaningless.
And thanks for pointing out the glaringly obvious fact that the climate is very different between when continental ice sheets are present and when they’re not. No other commenter on this site could have known that without you pointing it out.
UAH says the global mean TL temperature for June was 264.64 K.
To five significant digits … does this tell you anything?
Write it as -8.51°C, then it’s only three significant figures. Much more acceptable.
The UAH uses absolute temperatures (as they should) — 10 mK out of 264 K requires a precision of 0.004%; that you can’t see how absurd it is to get this level out of microwave radiance measurements is just another indication of your lack of any real metrology experience.
There’s no such thing as “climate” either. You can comment on that if you want.
“There’s no such thing as “climate” either.”
Anthony Watts thinks there is.
In any case temperature is a VERY minor factor in actual climate classification. Precipitation is the most important factor in determining survivability of the flora and fauna that determines climate. Grassland savannah’s in Africa and the Central US are perfect examples, vastly different temperatures and seasonality yet very similar climate class – precipitation!
I looked at the rolling centred 30-year decadal trends in UAH_AUS (Dec 1978-Jun 2026) and found they had an average warming rate of +0.19 (+/- 0.02 1SD) C/dec over the full period. That 30-year trend has never fallen below +0.14 nor exceeded +0.23 C/dec (to two decimal places).
The most recent 30-year period (Jul 1996-Jun 2026) is currently on the high end at +0.23 C/dec; still, this looks like a fairly consistent long-term pattern of warming rather than a series of short-term “random walks”.
“it makes some sense to interpret Nth & Sth hemis separately, because combining them might cancel out some seasonal features.”
What you are describing is a multi-modal distribution when all the data is combined into a global data set. The mean of a multi-modal distribution is usually considered to be useless. The five statistics books I have here all say that with a multi-modal distribution the modes should be analyzed separately. It’s the only way to pinpoint changes that affect the mean.
The differing variances are a clue that different processes are involved in each grouping. Different processes can, many times, indicate different means exist thus making the data multi-modal. You can compensate for differing variances using various weighting techniques. Not so for differing means.
I can’t find where climate science uses weighting by variance groupings to calculate an average. Can anyone point to where this is done for UAH?
(note: different variances imply different measurement uncertainty for the mean. Smaller variances are considered to be more accurate and should be weighted more heavily than larger variance groups.)
The new Monckton Pause extends to 42 months starting in 2023/01. The average of this pause is 0.54 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 0.33 C higher than the previous one.
+0.157 ± 0.037 C.decade-1 k=2 is the trend from 1979/01 to 2026/06 covering 570 values.
+0.026 ± 0.009 C.decade-2 k=2 is the acceleration of the trend.
The IRI ENSO ensemble forecast page is undergoing changes. They removed the data table so I have to eyeball the graph. It looks like they are starting to switch things over to RONI though so I’m hoping they’ll bring back the data table once that is complete.
Anyway, there have been no excursions outside the expectation envelop recently with UAH TLT behaving pretty much inline with expectation. We should continue to expect a general increase in temperature as the El Nino takes hold and UAH TLT starts responding later this year.
You use CO2 , without any proof that CO2 causes warming, and totally neglect the increase in absorbed solar radiation.
You chart is meaningless.
The milli-Kelvin “error bars” return…
They simply will *NOT* understand that how precisely you locate the population average has nothing to do with the measurement uncertainty associated with that average. One is calculated using the stated values of the population data and the other is calculated using the measurement uncertainty values of the population data.
It simply doesn’t matter what the SEM is for the stated values. It doesn’t affect the measurement uncertainty interval.
It truly is WILFULL IGNORANCE at this point. It is based on the garbage meme of climate science and its supporters that all measurement uncertainty is random, Gaussian, and cancels. It doesn’t matter if the measurement distributions are skewed, asymmetric, non-Gaussian, multi-modal, non-iid, etc.
Just ignore it all so you can pretend that increasing sample size somehow reduces measurement uncertainty.
Just so it is clear to everyone…I didn’t use the SEM. I used a heteroscedasticity and autocorrelation consistent covariance matrix to compute the uncertainty. [Andrews 1988]
And yet you still come up with impossibly tiny numbers.
Success!
He says he isn’t using the SEM but that appears to be *exactly* what he is using. UAH doesn’t provide measurement uncertainty intervals for their measurements, only SEM values. So what bdgwx was working with was determining the standard deviation of SEM values, which are *NOT* measurement uncertainties.
Of course, he invoked some fancy esoteric stats in an attempt to paper over what is plain to see.
You are in the same catch22 as bellman. You refuse to say whether the temperature data sets are a single sample or if they are a collection of different samples of size 1.
The SEM is defined as the standard deviation of the sample means. Your formula of SEM = SD/n is only an estimator for that standard deviation.
That standard deviation simply doesn’t exist for one sample no matter how many data entries there are. SEM = SD/n remains undefined is there is not multiple samples to create a distribution.
The standard deviation of the sample means when the sample size is 1 is just the SD of the data entrys. SEM = SD/1 so SEM = SD.
How did you use the heteroscedasticity? Did you weight the data based on its variance to give more accurate data more weight? And exactly what *is* the autocorrelation of the monthly data? Any correlation between June of last year and June of this year is probably due to seasonality. So what partial derivatives did you use?
The Earth Energy Imbalance (EEI) is running close to +1.5 W.m-2. Given the high EEI expect UAH TLT values to generally push higher at a rate faster than the overall trend from 1979. Since the start of Monckton’s previous pause in 2014 the trend has been +0.33 C.decade-1.
Really concerning.
And the Earth still has to equilibrate. It can’t fully do that while atmospheric CO2 concentrations continue to rise. As long as net CO2 emissions remain positive, the climate system is still being pushed away from equilibrium.
It will probably continue warming for a very long time.
Assuming a modest 0.5 C per W.m-2 sensitivity means we have 0.7 C of warming in the pipeline without any additional forcing applied. The consilience of evidence says that the sensitivity is probably higher than 0.5 C per W.m-2.
CO2 makes absolutely no measurable difference to movement of energy in the atmosphere.
Any tiny mythical or theoretical radiative effect is totally dwarfed by energy movement by bulk air movement.
Yes, it does. CO2 absorbs and emits IR, including back toward the surface.
And no. Bulk air movement doesn’t eliminate the role of radiation. Convection and latent heat transfer redistribute energy within the atmosphere, but they require a material medium. Radiation is the only mechanism by which the Earth can exchange heat with space. Ultimately, all the energy the Earth gains from the Sun must leave via infrared radiation.
“Yes, it does. CO2 absorbs and emits IR, including back toward the surface.”
That “back radiation” is reflection of already lost heat. Reflected heat is *NOT* a heat source. It only reduces the cooling rate. It can *NOT* increase temperature that has already dropped from the original loss of heat by the originating source.
Heat transfer is a time function! You have to know what happened in the past in order to determine what is happening in the present.
How many times does Planck’s statement about reflected heat have to be quoted before this becomes clear to those harping on “radiative balance”?
Given that:
a) the surface-averaged solar insolation for Earth (given for TOA) is about 340 W/m^2, and
b) the TOA solar insolation varies by about 6.9% (or 23.5 W/m^2) just due to Earth’s elliptical orbit around the Sun, and
c) our best science today can establish change in total Earth cloud coverage (realized as a change in Earth’s total albedo) at any given time only to an accuracy of about +/- 2%, equivalent to +/- 6.8 W/m^2, and
d) the chart that you presented above, covering less that 30 years of data, shows unexplained, rapid (occurring over four or fewer months) monthly anomaly variations of up to 3.3 W/m^2 ,
it is ridiculous for anyone to claim knowing an actual EEI to a value of 1.5 W/m^2.
Of course, anyone can claim the ability to calculate such a numerical value, but that is something altogether different from reality.
Not only that but attribute the difference in radiation at TOA only to CO2 is a bridge too far. The oceans store much more heat than the atmosphere ever could. Any heat that is stored in the oceans will of course cause less out, than put in. The time spans for storage can far exceed any averages being calculated.
I’m curious…how do you feel about that 340 W.m-2 value? I’m asking because you and your brother said it was 552 W.m-2 and so I expected you to take issue with it.
Oh BTW…insolation is an intensive property. Do you still maintain that being an intensive property any average would be useless and meaningless? If so how do you reconcile your position above?
“ If so how do you reconcile your position above?”
He probably can’t.
“Oh BTW…insolation is an intensive property. Do you still maintain that being an intensive property any average would be useless and meaningless? If so how do you reconcile your position above?”
Your reading comprehension skills are as lacking as in bellman.
You *can* average intensive property observations FOR A SINGLE OBJECT to determine an average value for that intensive property. E.g. you can measure the temperature of an individual water bath ten times and average the ten observations to obtain a “best estimate” of the value of the temperature.
You can *NOT take ten individual water baths, measure each one once, and then average those ten measurements to get an average value for the intensive property of temperature associated with the ten water baths!
Insolation is ONE object. The radiation from the sun. You can average multiple measurements of that one object to get an average value of the intensive property associated with that single object.
You must *STILL* propagate the measurement uncertainty associated with those multiple measurements. If they are taken by the same instrument over a short period of time with the same environment (e.g. orbital components,etc) then the measurement uncertainty becomes the standard deviation of the observations. NOT the SEM, the sampling uncertainty, but the MEASUREMENT uncertainty.
Acknowledging that an average of an intensive property can be meaningful and useful despite Kip Hansen’s claim otherwise is a step in the right direction. And declaring different fluxes at different locations with wildly different values to be the same thing may grossly distort the meaning of “same” it at least leads you down the same road of averaging an intensive property that everyone else goes down. If redefining “same” here is your way of saving face then fine. I don’t care as long as you remain consistent that averaging an intensive property (like flux, temperature, humidity, etc.) is meaningful and useful.
But what about that 340 W.m-2 value? Are you going to try and “teach” ToldYouSo that it is actually 552 W.m-2 like what you did with me?
Kip is correct when it comes to averaging the intensive property of different objects – WHICH IS WHAT THE TEMPERATURE DATA SETS CONSIST OF.
The operative words here are “different fluxes”. This is no different than trying to average the temperatures of ten different water baths to come up with a physically meaningful “average” temperature. The average of the intensive property of different things is physically meaningless.
If defining different things as being the same thing is your way of saving face then fine. But it remains physically meaningless.
You *still* haven’t said how averaging the temperature of ten different water baths gives you a physically meaningful value. Why? My guess is that you *know* that the average would be physically meaningless and you just don’t want to admit it. Averaging the temperature of ten different objects is not any different.
I remind you…again…that NIST average 22 different parcels of air in TN 1900 E2.
Then why go through the exercise of “teaching” me that solar insolation averages 552 W.m-2 if you don’t even think it is meaningful or useful? And why not “teach” ToldYouSo?
I don’t. Just so it is abundantly clear I do NOT think that different parcels of air are the same thing. I do NOT think that different baths of water are the same thing thing. I do NOT think that different fluxes falling on different locations with wildly different values are the same thing.
And yet NIST averaged 22 different parcels of air and found meaning in doing so in TN 1900.
“I remind you…again…that NIST average 22 different parcels of air in TN 1900 E2″
And I remind you POSSOLO MADE THOSE MEASUREMENTS INTO THE SAME OBJECT WITH THE ASSUMPTIONS HE MADE IN THE EXAMPLE.
You have yet, after numerous requests, to list out all of the assumptions Possolo made in TN1900, Ex 2 and DISCUSS THEIR IMPLICATIONS.
There is a reason why you won’t do this. It’s so you can claim you can average the intensive properties of different things.
Do I need to, once again, reprint all of the example here on WUWT so that people can see how you are ignoring the assumptions he made?
Or will you finally accept the challenge to list them out yourself and discuss their implications?
I don’t need to list the assumptions. First…Possolo already does it. Second…I’ve never ignored the assumptions. Third…it is irrelevant. He measured different parcels of air regardless of which or how many assumptions were made or whether I ignored them or not. The topic of assumptions here is your way of deflecting and diverting away from the fact that different parcels of air were measured.
“I don’t need to list the assumptions”
It’s not a matter of you “don’t need to”, it’s a matter of them showing your assertion that you can average intensive values of didferent things to be garbage.
The assumptions are that he *did* measure the same object each time. That environmental conditions did *NOT* change. That the same instrument was used each time.
TN1900,
======================
—————————-
(7a) Observation equations are typically called for when multiple observations of thevalue of the same property are made under conditions of repeatability (VIM 2.20), orwhen multiple measurements are made of the same measurand (for example, in aninterlaboratory study), and the goal is to combine those observations or thesemeasurement results.
EXAMPLES: Examples E2, E20, and E14 involve multiple observations madeunder conditions of repeatability. In Examples E12, E10, and E21, the samemeasurand has been measured by different laboratories or by different methods.
—————-(bolding mine, tpg)
———————-
The daily maximum temperature r in the month of May, 2012, in this Stevenson shelter, maybe defined as the mean of the thirty-one true daily maxima of that month in that shelter.
———————-
——————-
Assuming that the calibration uncertainty is negligible by comparison with the other uncertainty components, and that no other significant sources of uncertainty are in play, then the common end-point of several alternative analyses is a scaled and shifted Student’s t distrbution as full characterization of the uncertainty associated with r.
———————–
========================
Possolo DEFINED the object being measured as Tmax. Tmax does *not* depend on what parcel of air is involved in each measurement. Tmax *is* an independent, common object being measured. The environment consisting of location and measuring device *are* the same and don’t affect the measured value of Tmax on each day. The assumption that “no other significant sources of uncertainty are in play* is an IMPORTANT ASSUMPTION.
This is a teaching example. Assumptions were made in order to not distract from the teaching. Those assumptions simply do not apply to the real world of trying to average intensive properties of different objects.
If Possolo had been including Tmax measurements from two physically different locations, with two different measuring devices, and other significant sources of uncertainty, e.g. station microclimate, then his assumptions would be inapplicable.
For some reason you are simply unable to admit to that fact. It’s obvious that it is because you have an agenda to push = trying to push the idea that averaging intensive properties of different things is scientifically sound.
IT ISN’T.
Different parcels of air on different days with different temperatures, humidity, pressure, etc. are the same thing?
The environmental conditions on different days with different solar insolation, different cloud cover, different humidity, different pressure, different temperature, etc. did not change?
Clearly you misunderstand what conditions of repeatability mean. And no, the GUM does not say that measurements must be on the same object; only that the measurements are of the same measurand. Nor does the GUM say a measurand must be a quantity attributable to only one object.
I have no problem with E2 and all of its assumptions. Remember, I’m the one who brought it to your attention.
That is exactly what I am doing. Scientists do it all of the time including those from NIST and BIPM.
Great excuse. Nothing like an Appeal to Anonymous Authority to bolster your argument.
Here is the real key, that example led to a measurement uncertainty of ±1.8°C. Where does an uncertainty like that disappear to when combined with Tmin? Where does it go when determining the uncertainty in an anomaly for that month? If you look at the standard deviation, it is even worse. If you examine the Wilcoxon reference and use it, it is also worse. Better yet, NIST didn’t pad the resolution to two or three decimal digits. They used one digit, the same as the uncertainty.
“Different parcels of air on different days with different temperatures, humidity, pressure, etc. are the same thing?”
Judas H. Priest!!!! I quoted you what Possolo said in TN1900 and you JUST REFUSED TO READ IT!!!
Again:
Possolo TN1900
1.———————
Exhibit 2 lists and depicts the values of the daily maximum
temperature that were observed on twenty-two (non-consecutive) days of the month of May,
2012,
———————-
2.———————
EXAMPLES: Examples E2, E20, and E14 involve multiple observations mad eunder conditions of repeatability.
—————-
GUM:
3.———————-
B.2.15
repeatability (of results of measurements)
closeness of the agreement between the results of successive measurements of the same measurand carried out under the same conditions of measurement
———————–
GUM:
4.———————–
B.2.9
measurand
particular quantity subject to measurement
———————-
1.Possolo defines the measurand as the daily maximum temperature. (See item 1 above)
2.He then specifies that the measurements are done under conditions of repeatability (See item 2 above
3.Repeatability conditions in the GUM – same measurand, same conditions of measurement
4.GUM defintion of a measurand – PARTICULAR QUANTITY SUBJECT TO MEASUREMENT.
If you want to know *why* Tmax is the value it is then you need to measure humidity, pressure, etc. BUT YOU DON’T NEED THOSE TO DETERMINE Tmax!
READ THE TN1900 FOR MEANING AND CONTEXT.
“The environmental conditions on different days with different solar insolation, different cloud cover, different humidity, different pressure, different temperature, etc. did not change?”
GUM:
———————
B.2.15
repeatability (of results of measurements)
closeness of the agreement between the results of successive measurements of the same measurand carried
out under the same conditions of measurement
NOTE 1 These conditions are called repeatability conditions.
NOTE 2 Repeatability conditions include:
— 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.
—————————
These were all met. Same measurement procedure, same observer, same instrument in the same position, same location, done over as short of a period as possible based on the measurand being measured.
One more time: The measurand is Tmax. You don’t *need* to know all the other components that cause Tmax in order to measure Tmax.
READ THE TN1900 FOR MEANING AND CONTEXT!
“Clearly you misunderstand what conditions of repeatability mean. And no, the GUM does not say that measurements must be on the same object; only that the measurements are of the same measurand.”
The only one that apparently doesn’t understand what conditions of repeatability mean IS YOU.
GUM:
———————-
B.2.9
measurand
particular quantity subject to measurement
——————–
A particular quantity means just that. E.g. Tmax in TN1900. And under repeatability conditions that requires the same LOCATION, same OBSERVER, same INSTRUEMENT, same MEASUREMENT PROCEDURE. Exactly what Possolo says in TN1900!
All of these mean you can’t take the temperature at a different location, by a different observer, with different instruments, and different measurement procedures (e.g. LIG sensor vs PTG vs etc) and say they are measuring the same thing.
You can define anything you want as a measurand. That doesn’t make it physically meaningful. Again, if you can’t say that holding two rocks in your hand, one at 60F and the other at 70F, doesn’t result in you holding a temperature of 130F then how does their average tell you anything physically meaningful? All this does is invoke the “numbers is just numbers” meme.
“I have no problem with E2 and all of its assumptions. Remember, I’m the one who brought it to your attention.”
You *DO* have a problem with its assumptions. Otherwise you would understand what Possolo did. He did *NOT* take Tmax from two different locations, two different instruments, and two different observers and try to find their average with a combined measurement uncertainty and use it as a physically meaningful product.
“That is exactly what I am doing. Scientists do it all of the time including those from NIST and BIPM.”
ROFL!! Others doing it does *NOT* make it correct. That’s called the Bandwagon Fallacy!
And again you steadfastly refuse to acknowledge the assumptions used in your fav NIST paper.
Different calculations. Different assumptions. Why don’t you stop playing gotcha and actually address the subject?
Teaching you all is getting tiresome. The stricture is against average two different values of temperature. In this case, we are determining where on a sine curve is the middle value of insolation occurs, not temperature at two different points or somewhere in between. Two entirely different things.
You just won’t admit that a plane wave from the sun touches every point on the surface. That is 2π². Every point receives 1360 W/m². I do, you do, Anthony does, Santa Claus does. The difference to warming is the angle of incidence.
Look at this page if you don’t believe me.
It’s literally the exact same calculation. There is no difference whatsoever.
I bet it is. You can’t even keep your own arbitrary rules straight.
Patently False. The calculation is to determine the average flux per unit area received from the Sun at TOA over one orbital cycle.
Kudos for unperturbability, command of the facts, and knowing when to let them rant on (Bellman!).
But last week was pretty much looking out onto an uninhabitable South St. Louis humid scape through the dirty windows of my survival pod. So, I’m leaving the rest of this miserable St. Louis area summer to you. Off to Pismo Beach Friday (daily range mid 50’s/mid 70;s, with ocean breeze during daylight). Would have left 3 weeks ago, save for a bad bronchitis picked up on a bike/barge trip from Amsterdam/Bruges – the first real health challenge of my lucky life. Plan is to introduce 14/11 year old g’kids to paragliding, to the extent I can do so legally, or, lawlessly.
“You just won’t admit that a plane wave from the sun touches every point on the surface. That is 2π². Every point receives 1360 W/m².”
‘Every point on the surface’ does not receive 1360 W/m², that is what reaches the top of the atmosphere. That plane wave from the sun has an area of πr², at any instance in time the average that could reach the surface is therefore 1360/2 W/m² without reflection by clouds etc (~25% of incident light).
“That plane wave from the sun has an area of πr²”
Huh? That plane wave has a *much* larger effective area than πr².
The surface area of the earth is 4πr^2. Since half the earth is facing the plane wave at any instant of time it is presenting (4πr^2)/2 = 2πr^2 of its surface area to the plane wave.
The problem with trying to use the area of the earth’s shadow is that it results in that plane wave hitting every point on the earth at 90deg, including at the poles. That’s a non-physical representation; it means the poles would be at the same temperature as the center of the shadow.
If, instead, you do a surface integral from 0 to
π/2 in latitude you wind up with maximum absorption at the equator and none at the pole. Then rotating the earth in longitude will give the absorption associated with the rotation from 0 to
π/2 during the day.
Not exactly correct but a good first approximation and it matches what actually happens physically.
The plane wave has an area of πr² so the total impacting the Earth’s surface at any instant in time is 1360πr² W (in the absence of reflection by clouds etc.). That light is impacting an area of 2πr² therefore the average energy impacting the illuminated surface is 1360πr²/2πr² =1360/2 W/m², if that’s not the value your integration gets you’ve made an error!
Flux is not measured as 1360πr² W. It is measured as 1360 W/m^2. That denominator of m^2 is a unit area = 1 m^2. It’s a dimension.
That means that 1360 joules/sec hits every square meter of the earth. In other words, 1360 joules/sec per square meter. Dimensionally it is joules/sec-m^2.
(sec-m^2) is NOT a product or a difference, it is a concatenated dimension of seconds and m^2.
The amount of that 1360 joules/sec-m^2 that gets absorbed in that square meter can be calculated using the Divergence Theorem.
I.e. P_absorbed = ∯ |S| cos(θ) dA
Lambert’s Law is very similar.
let n be the normal vector to the surface and S the vector toward the source.
E_absorbed = Flux * (n * S)
cos(θ) = n · S
This is your first misunderstanding. A plane EM wave doesn’t have an area. A plane wave has an E component and an M component that make a field in space. Every point on that plane wavy has the same intensity of W/m².
Let’s look at the very 1st square meter that wave intercepts. Is it’s intensity cut in half? If not, why not? Now, look at the surrounding square meter areas. As the wave intercepts them, is the intensity cut in half? If not, why not. Every point on the wave has the same intensity, so something is reducing the intensity at each of the surrounding areas.
You are in essence trying to merge an area of πr² with another area of 2πr². That doesn’t work. It would require stretching the plane wave to match the larger area. How do you stretch a plane EM wave?
Take a basketball whose radius is 4.85 inches with a surface area of 2π4.85² = 147.8 in². Now cut out a circular piece of cloth with a radius of 4.85 in. and a surface area of π4.85² = 73.9 in². Will that smaller piece cover the entire surface area of one side of the basketball? Why not? How does a plane EM wave do it?
I’ve had people try to explain it by saying it “cuts a hole” in the plane wave. But when I point out that means it has touched every point on the earth, they have no answer.
What a load of gobbledygook! You don’t appear to understand the linear propagation of light.
I do know about the propagation of EM waves.
Here are a couple of slides.
Look at the first slide. See that little yellow dot? That is the earth intercepting a plane wave front. Is it a true plane wave? No. But at the distance we are from the sun, the variation in intensity is so far out in the decimal places, it is reasonable to assume that it is.
Similarly, the direction of the EM wave is essentially parallel at all points of intersection for the same reason. The second slide shows this.
An EM wave is a continuous field as shown by the same intensity at all points on the wave front. If you measure the intensity over 1 meter at some point it will be the same if you move 1000 meters away. All points on the earth will be touched by this wave front and all will receive the same intensity.
If satellites measures the intensity of the wave front as 1360 W/m², then that is the intensity at all points. You’ll have to explain how that EM wave doesn’t touch every point on the surface.
The sphere that originates at the sun and intersects the earth has a radius of the distance between the earth and the sun. That sphere is so large that the area of the sphere that the earth presents is essentially flat, that is, a plane wave. EVERY POINT ON THE PLANE WAVE HAS AN INTENSITY OF 1360 – 1370 W/m².
That plane wave, as it travels over the earth, contacts each and every point of the earth surface. Not just πr² but 2πr². Every mm², every um².
Since the sphere is curved each ray intersected the earth will have an angle of incidence. At an angle of 0° (equator) there will be total absorption. At an angle of 90° (pole), there will be zero absorption.
A good reference.
6.007 Lecture 33: Fresnel equations and EM power flow
Jim, if they didn’t build a bridge too far they couldn’t get to the other side of the apocalypse.
CERES uncertainty is between 0.2 and 0.5 W.m-2 depending on the time period. [Loeb et al. 2018] [Loeb et al. 2022] [Loeb et al. 2024] In-situ measurements are closer to 0.1 W.m-2. [Schuckmann et al. 2020]
Well, so you (following Loeb et al.) say.
However, Google’s AI bot, accessing a much larger set of scientific publications on the subject, has this to say . . . and please note my bold emphasis in the pasted-in text below:
“While NASA’s Clouds and the Earth’s Radiant Energy System (CERES) provides a highly stable and valuable record of Earth’s energy budget, the data is subject to known uncertainties and processing limitations.
Specific limitations include:
1. Instrument Degradation and Calibration Drift
Unmonitored degradation:
Solar and thermal sensors naturally degrade in the harsh environment of space. Over time, telescope mirrors and filters suffer from “telescope degradation,” particularly in the shortwave channels.
Drift Corrections:
Although CERES has onboard calibration sources, subtle, long-term degradation is notoriously difficult to detect, requiring complex cross-comparisons and sometimes leading to spurious calibration drifts in the official record.
2. Imager and Cloud Detection Limitations
CERES relies heavily on collocated imagers like MODIS (on Terra and Aqua) and VIIRS (on Suomi NPP and NOAA-20) to retrieve cloud properties. This fusion introduces several errors:
Missed or misclassified clouds:
Passive imagers often struggle to detect optically thin cirrus clouds or small, broken cumulus clouds.
Day vs. Night disparities:
Cloud-phase misclassification and errors in cloud-top height estimates are more frequent during nighttime.
Multilayer clouds:
The detection and retrieval of multilayered clouds remain a persistent challenge, resulting in uncertainties in downwelling surface fluxes.
3. Absolute Bias and Random Noise
Global Mean Uncertainties:
While random noise and short-term variance average out, absolute biases remain. Instrument calibration uncertainties in Top-of-Atmosphere (TOA) filtered and unfiltered radiances can amount to several Watts per square meter (W/m²) for global mean irradiances.
4. Diurnal (Daily) Sampling Challenges
Because CERES flies on sun-synchronous satellites, observing a location at the exact same local time daily means it misses the natural day-night cycle of clouds and radiation. To compensate, scientists incorporate geostationary imager data. However, the quality of this supplemental data varies, resulting in regional discrepancies, especially over oceans.
5. Clear-Sky Radiation Ambiguities
Determining what the radiation budget would look like without clouds (clear-sky fluxes) involves radiative transfer models that require assumptions about atmospheric conditions (aerosols, ozone). When CERES algorithms filter cloudy pixels, it can bias clear-sky datasets if certain clouds (like tiny, sub-pixel clouds) remain undetected.”
Finally, please explain the difference between “in-situ” measurement uncertainty of 0.1 W/m^2 (that you attribute to Schuckmann et al.) versus CERES measurement uncertainty of 0.2 and 0.5 W/m^2 (that you attribute to Loeb et al.), given that CERES is measuring Earth’s radiation in space above Earth’s atmosphere.
“While random noise and short-term variance average out”
Since measurement uncertainty contains both random and systematic effects how does one know exactly what random noise and short-term variance are unless you also know the systematic effects.
Bevington covers in his tome one measurement uncertainty a discussion that basically boils down to “systematic uncertainty is not amenable to statistical analysis”. If that is the case then neither is random noise and short-term variance.
If we use the old error formula of wi = ui – εr = εs where wi is the measured value, ui is the true value, εr is the random error value, and εs is the systematic error value how to you calculate εr?
εr = wi – ui – εs. If you don’t know εs then you can’t know εr. If you don’t know ui then you can’t calculate εr or εs.
This is just the garbage meme of climate science that says: “all measurement uncertainty is random, Gaussian, and cancels”.
Remember, random noise does *NOT* have to be Gaussian. It can have almost any distribution type depending on the generator. Quantization noise . shot noise, and flicker noise are some examples.
In this context in-situ means measuring ΔE directly as opposed to the Ein – Eout method. Though it is important to point out that CERES does utilize an in-situ anchor to improve accuracy. Without the in-situ anchor the uncertainty would be much higher…perhaps exceeding 4 W.m-2. That would obviously make absolute EEI estimates less useful. Anomalies and trend would still exhibit a relatively low uncertainty owing the high correlation.
Hah! What device or instrument, pray tell, measures ΔE directly?
A Google search for a delta-Joule meter does come up with any “hit”.
And no, I didn’t bother to waste my time asking other AI bots for help with this!
[Schuckmann et al. 2020]
I asked for the name of the “device or instrument” that measures ΔE directly, not for a repeat of a reference that you previously cited.
What you did is commonly known as a poor attempt at deflection.
Going forward, I don’t expect better.
Thermometer.
Sorry. I didn’t realize you literally had to be spoon fed the most intuitive and obvious answer possible to your question. I gave you minimum credit here assuming you were asking for the minutia of details because I assumed you already understood ΔE = ΔT / (m*c).
Says the guy who couldn’t figure out that temperature combined with ΔE = ΔT / (m*c) give you ΔE.
Actually, your equation is mixed up for conduction. It should be:
q = (k / s) A dT
= U A dT (1)
where
q = heat transfer (W, J/s, Btu/hr)
k = Thermal Conductivity of material (W/m K or W/moC, Btu/(hr oF ft2/ft))
s = material thickness (m, ft)
A = heat transfer area (m2, ft2)
U = k / s
= Coefficient of Heat Transfer (W/(m2K), Btu/(ft2 h oF)
dT = t1 – t2
= temperature gradient – difference – over the material (oC, oF)
This comes from Conductive Heat Transfer
Actually, a thermometer doesn’t measure the entire energy based on ΔT in the air. Latent heat is not sensible.
No uncertainty limits in graph: D-minus.
Great match to absorbed solar radiation..
Well done. You finally figured it out.
The real cause of this century’s warming is solar radiation.
CO2 has absolutely nothing to do with it.
https://www.pnas.org/doi/10.1073/pnas.1412190111
”The greenhouse effect is well-established. Increased concentrations of greenhouse gases, such as CO2, reduce the amount of outgoing longwave radiation (OLR) to space; thus, energy accumulates in the climate system, and the planet warms. However, climate models forced with CO2 reveal that global energy accumulation is, instead, primarily caused by an increase in absorbed solar radiation (ASR). This study resolves this apparent paradox. The solution is in the climate feedbacks that increase ASR with warming—the moistening of the atmosphere and the reduction of snow and sea ice cover. Observations and model simulations suggest that even though global warming is set into motion by greenhouse gases that reduce OLR, it is ultimately sustained by the climate feedbacks that enhance ASR.”
“The greenhouse effect is well-established. Increased concentrations of greenhouse gases, such as CO2, reduce the amount of outgoing longwave radiation (OLR) to space; thus, energy accumulates in the climate system, and the planet warms.”
Garbage. How exactly is that energy accumulation done? If heat is added to the earth, then the radiation from the earth will INCREASE! Since CO2 can only return a portion of that increased radiation the total outgoing SHOULD GO UP.
The two factors simply don’t go together: accumulated heat and OLR decrease! You can’t have both at the same time!
It’s the entire problem with “radiative balance” in a nutshell.
The climate science meme’s of “co2 blocks heat from escaping” and “radiation goes down as temperature goes up” are JUST MORE GARBAGE.
Hmmm…and average of an average of an average. If you keep going, you could make it a straight line.
Yep. This concept even has a name. It is the Law of Total Expectation.