Home/BlogThe Version 6.1 global average lower tropospheric temperature (LT) anomaly for October, 2025 was +0.53 deg. C departure from the 1991-2020 mean, unchanged from the September, 2025 value.
The Version 6.1 global area-averaged linear temperature trend (January 1979 through October 2025) remains at +0.16 deg/ C/decade (+0.22 C/decade over land, +0.13 C/decade over oceans).
The following table lists various regional Version 6.1 LT departures from the 30-year (1991-2020) average for the last 22 months (record highs are in red).
| YEAR | MO | GLOBE | NHEM. | SHEM. | TROPIC | USA48 | ARCTIC | AUST |
| 2024 | Jan | +0.80 | +1.02 | +0.58 | +1.20 | -0.19 | +0.40 | +1.12 |
| 2024 | Feb | +0.88 | +0.95 | +0.81 | +1.17 | +1.31 | +0.86 | +1.16 |
| 2024 | Mar | +0.88 | +0.96 | +0.80 | +1.26 | +0.22 | +1.05 | +1.34 |
| 2024 | Apr | +0.94 | +1.12 | +0.76 | +1.15 | +0.86 | +0.88 | +0.54 |
| 2024 | May | +0.78 | +0.77 | +0.78 | +1.20 | +0.05 | +0.20 | +0.53 |
| 2024 | June | +0.69 | +0.78 | +0.60 | +0.85 | +1.37 | +0.64 | +0.91 |
| 2024 | July | +0.74 | +0.86 | +0.61 | +0.97 | +0.44 | +0.56 | -0.07 |
| 2024 | Aug | +0.76 | +0.82 | +0.69 | +0.74 | +0.40 | +0.88 | +1.75 |
| 2024 | Sep | +0.81 | +1.04 | +0.58 | +0.82 | +1.31 | +1.48 | +0.98 |
| 2024 | Oct | +0.75 | +0.89 | +0.60 | +0.63 | +1.90 | +0.81 | +1.09 |
| 2024 | Nov | +0.64 | +0.87 | +0.41 | +0.53 | +1.12 | +0.79 | +1.00 |
| 2024 | Dec | +0.62 | +0.76 | +0.48 | +0.52 | +1.42 | +1.12 | +1.54 |
| 2025 | Jan | +0.45 | +0.70 | +0.21 | +0.24 | -1.06 | +0.74 | +0.48 |
| 2025 | Feb | +0.50 | +0.55 | +0.45 | +0.26 | +1.04 | +2.10 | +0.87 |
| 2025 | Mar | +0.57 | +0.74 | +0.41 | +0.40 | +1.24 | +1.23 | +1.20 |
| 2025 | Apr | +0.61 | +0.77 | +0.46 | +0.37 | +0.82 | +0.85 | +1.21 |
| 2025 | May | +0.50 | +0.45 | +0.55 | +0.30 | +0.15 | +0.75 | +0.99 |
| 2025 | June | +0.48 | +0.48 | +0.47 | +0.30 | +0.81 | +0.05 | +0.39 |
| 2025 | July | +0.36 | +0.49 | +0.23 | +0.45 | +0.32 | +0.40 | +0.53 |
| 2025 | Aug | +0.39 | +0.39 | +0.39 | +0.16 | -0.06 | +0.69 | +0.11 |
| 2025 | Sep | +0.53 | +0.56 | +0.49 | +0.35 | +0.38 | +0.77 | +0.32 |
| 2025 | Oct | +0.53 | +0.52 | +0.55 | +0.24 | +1.12 | +1.42 | +1.67 |
The full UAH Global Temperature Report, along with the LT global gridpoint anomaly image for October, 2025, and a more detailed analysis by John Christy, should be available within the next several days here.
The monthly anomalies for various regions for the four deep layers we monitor from satellites will be available in the next several days at the following locations:
Looking at the departures table. If I look at changes month to month for Australia I’d guess that the standard deviation from the mean is greater than any other area on the table. If so, doesn’t that suggest concern about the reliability of the provided readings? I would guess that Roy has the ability to provide that statistic for each region and the globe. We should expect the entire globe to have the smallest standard deviation, correct?
Only if weather fits some kind of randomised statistical distribution and I don’t see why it should be.
This is stratosphere, so it’s not a great analogy, but if you have a large pressure difference leading to extreme weather in one location, the pressure gradients will lead to (the other) extreme weather at the other end of the gradient. The planet is all connected but Australia seems particularly so. When Perth swelters, chances are the Kimberly is well below average and vice versa. Seems to apply along latitudes too. But that’s all hunches, no actual analysis of data.
The big flaw in climate science was to settle on the conclusion that all the significant non-random cycles are known and quantified and having eliminated them, the only thing left was (anthropogenic) CO2.
Weather does fit a statistical distribution. Weather is not random. The average temperature (a statistical distribution) is higher in summer and lower in winter. The greater the deviation from the mean, the less we can rely on the the temperature being near average on any given day. This is a fact. It is science.
So, if the deviations for increases and decreases in average temperature over some stated period are greater than the same statistic for another area, it suggests something is either different about weather/climate in that area or the data should be considered as possibly faulty.
The standard deviation of T in Australia is less than that of USA48. You can look at the data here:
https://www.nsstc.uah.edu/data/msu/v6.1/tlt/uahncdc_lt_6.1.txt
I haven’t done the calculation for these areas, but Australia is the smallest region in the table, hence subject to less area averaging, so the expectation is that its standard deviation would be the largest.
All of this data is available, so virtually any sufficiently motivated person can pull it down and do the calculation.
“If I look at changes month to month for Australia I’d guess that the standard deviation from the mean is greater than any other area on the table.”
Looking at all months, the SD for Australia is 0.65C, for the USA48 region it’s 0.77C.
” If I look at changes month to month for Australia I’d guess that the standard deviation from the mean is greater than any other area on the table. ”
Maybe you mean ‘maximal’ instead of ‘standard’.
If you calculate, for all 27 zones and regions, the lowest resp. the highest anomaly since Dec 1978 and build their difference you obtain this:
SP_Land 5.99 (C)
USA48 5.47
NP_Ocean 4.94
NP_Land 4.62
NoPol 4.45
USA49 4.22
AUST 4.10
SoPol 3.87
SE_Land 3.71
SP_Ocean 3.02
SH_Land 2.99
NE_Land 2.91
NH_Land 2.66
Tr_Land 2.63
Trpcs 2.25
Gl_Land 2.25
Tr_Ocean 2.17
NoExt 2.14
NH 1.96
NE_Ocean 1.78
NH_Ocean 1.76
Globe 1.61
SH 1.52
SH_Ocean 1.45
Gl_Ocean 1.45
SoExt 1.44
SE_Ocean 1.39
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Thus, the South Pole’s land part wins, and USA48 (the contiguous part of the US) is second; the lowest difference you see at the ocean part of the Southern Extratropics.
So, I have not explained very well what standard deviation I meant.
Suppose that I track the change from one month to the next in absolute value. i.e. the net change month to month whether + or – from the previous month. Then suppose that for all regions that net change averages .15 degrees Celsius and that for all net changes for all regions the standard from .15 degrees C is .1 degree C. Now, if one area has net changes that average .5 degree C (more than 2 sd from mean), do we question that? Do we wonder if there is something about the climate there that is very different from the others or do we wonder if data collection is consistent and correct?
Sounds like a stansard st. deviation, which is not larger in Australia, according to the data.
1. I just read your first post again and see that you only consider a tiny portion of the UAH time series. Thus, my very first proposal is to consider the entire series since Dec 1978:
http://vortex.nsstc.uah.edu/data/msu/v6.1/tlt/uahncdc_lt_6.1.txt
Please download that stuff into a spreadsheet calc and repeat your calculation over the whole.
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2. The next point is that when considering Australia since Jan 2024, you induce a bias caused by the fact that Australia probably was more affected by the Hunga Tonga eruption in Jan 2022 than other zones and regions monitored by the UAH team.
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3. ” We should expect the entire globe to have the smallest standard deviation, correct? ”
Yes of course: Australia and the US represent with 6% of the land masses and 2% of the total surface a tiny portion of the Globe.
Thus it can be expected that such small portions experience heavier deviations than the Globe as a whole.
And since the public data consists of zonal/regional averages of a 2.5 degree grid, you can expect even much stronger deviations when considering only the monthly time series of single cells in the grid:
http://vortex.nsstc.uah.edu/data/msu/v6.1/tlt
The increase in global LT temperature is accelerating, based on a second-order polynomial fit to the data series. The instantaneous rate of warming is now 0.28 degrees C per decade.
Are you going to extrapolate that polynomial? 🙂
Doesn’t really look like 98.
Third warmest October since 1979, though someway down from the previous two years.
Year Anomaly
1 2023 0.78
2 2024 0.75
3 2025 0.53
4 2017 0.47
5 2020 0.36
6 2021 0.34
7 2015 0.28
8 2016 0.28
9 2019 0.27
10 1998 0.24
October 2022 is just below 1998 at 0.23, so the last 7 Octobers are in the top 11.
My projection for 2025 is now 0.48 +/- 0.05, virtually unchanged from last months, but with more certainty. Now very likely to finish 2nd warmest. Temperatures will have to drop to around 0.1C for the next two months for 2025 to finish below 2023.
Seems likely global mean temp will drop over the next couple of months. Thats because ENSO began a significant decline over 3 months ago and there is typically a multi-month delay.
That said I wouldn’t at all be surprised that 2025 ends up number 2 but its may be close as the ENSO decline is now about -.6C.
“The monthly anomalies for various regions for the four deep layers we monitor from satellites will be available in the next several days”
These values haven’t been updated for September yet. I’m not sure if this is just an oversight or a problem with the data collection.
2025 Sep +0.53
2025 Oct +0.53
Looks like I called it right, again.
Pretty warm, I’d say. As in close. smiley.
Compared to what?
This is also the warmest October for Australia in the UAH history, by some way. Beating the record set last year by 0.58C.
In fact it’s the second warmest anomaly for any month, just behind August 2024.
Weren’t there some folks on here not long ago spinning a Monckton-style “No warming in Australia since….” line?
Wonder how far back that goes these days?
“Beating the record set last year by 0.58C.”
Since when?
Above, Art Groot, tried fitting a polynomial to UAH data and derived an instantaneous warming trend. Nothing against Art personally, but IMHO, the mathematical approach confirms Mark Twains inference that….
“There are three kinds of lies: lies, damned lies, and statistics”.
I was taught in a 3rd year engineering statistics class that context is everything in statistics. In other words, it’s ingenuous to blindly apply statistical methods to data without understanding the context in which the data was attained.
Here’s the context. From 1979 till 1998, the global anomalies were largely negative, meaning there was a global cooling period between those years. John Christy of UAH has pointed out the reason, volcanic aerosols from two significant volcanoes.
Whereas I will defer to John’s qualifications and experience here, I regard 19 years as a tad too long for aerosols to have such an effect, I think there are variations in global temperatures taking place that no one understands. Tsonis et al concluded such variations are due to phase differences between the major oceanic oscillations.
In a paper, John also pointed out that the first positive anomalies, indicating true warming, came with a major El Nino in 1998 which pushed the global average up by a full degree C. This is what we should be looking at as a source of a warming trend.
The thing to note is this: following each major EN, especially in 2016, in which there were substantial warming, the global average increased by at least 0.2C. The first observation of such an increase was noted in 1977 and some scientists wanted to erase it as a mistake. It was subsequently named the Great Pacific Climate Shift then renamed the Pacific Decadal Oscillation. Around the same time, the Atlantic Multidecadal Oscillation was named.
If we take into account each residual warming effect, we can pretty well account for all global warming since 1976. No AGW theory is required. Explanation follows.
We still know essentially nothing about these oscillations and how they interact with each other. Tsonis et al concluded the oscillations do interact by phase, producing warming and cooling OVER A CENTURY. We may be in the middle of such a warming cycle and mistaking it for anthropogenic warming.
Anyway. following the 1998 EN, after things settled down, albeit some 0.2C warmer on top of the 0.2 C from 1977, the globe experienced 15 years of a flat trend. The flatness is based on an averaging of positive and negative cycles and obviously does not show up in a full range mathematical analysis, which is only concerned with numbers, not context.
BTW, the IPCC has confirmed 12 years of the flat trend from 1998 till 2012, calling it a warming hiatus. UAH confirmed the other three years based on satellite data. Then in 2016, another major EN struck and drove global temps even higher than the 1998 EN. This time, however, temperatures were not so quick to fall back, taking 6 years to do so to the original 15 year flat trend average.
The global average had barely stabilized before a major oceanic volcanic eruption, Hunga Tonga, injected roughly 150 millions tons of water into the stratosphere. That represented about 10% of the stratosphere’s water content which is normally a very dry portion of space.
HT occurred in early 2022 and nearly 4 years later the global temps have dropped significantly. How far they will drop back is unknown.
That’s why it is ingenuous to apply statistical methods to the entire range of UAH data since the meaning is not clear given the explanation of context. The data is simply not acquired from a stable source rather a wildly varying source with considerable flat trends.
There is little doubt that a warming trend has occurred since 1979 but it is highly unlikely it has anything to do with the effect of a trace gas in the atmosphere. Tsonis et al concluded that we should de-emphasize the AGW cause and focus on real, physical effects like the interaction between oceanic oscillations.
Each month, Dr. Spencer fits a linear function to the data and reports the rate of warming. I’m curious if you think that your argument against statistical analyses also applies to linear trends (aka first-order polynomials).
art…yes…I have stated in the past that the linear trend has little meaning other than an indicator that it has warmed since 1979, a fact I do not deny. I am arguing over the cause of the warming. I think the linear trend is a simple fit to the data and does not account for 15 year flat trends.
I want to be clear that I am not taking a shot at your analysis per se I simply don’t think the warming in the atmosphere has anything to do with greenhouse gases. Therefore, analysis of the data via any kind of statistical analysis has no meaning other than as an exercise to the person doing the analysis.
Most people I have read are basing their analysis on the AGW theory. Maybe that’s not the basis for your post.
I’ll try to explain my POV as I go along, if it is of interest to you.
My argument is that anthropogenic warming is insignificant and I have based that on the Ideal Gas Law and the heat diffusion equation. A gas making up a mass percent in the atmosphere of 0.06% simply lacks the ability to warm the majority gases, nitrogen and oxygen, significantly.
BTW…I am supportive of statistical analysis when applied to pertinent data. For example, if a factory is producing light bulbs and wants to know how many per lot are faulty, they can apply sampling techniques and analyze the results. That is far different than blindly applying statistical analyses out of context to temperature data with the presumption it has any meaning. When you have flat trends of 15 years and 6 years in the range, it tends to throw the data analysis for a loop.
May I suggest you break the overall range from 1979 – present into the following sub-ranges, and analyze each statistically, you might get a more meaningful result.
-1979 – 1997
-1998 – 2015
-2016 – 2021
-2022 – present
The AGW theory fails due to its contravention of the 2nd law of thermodynamics. Alarmists are interpreting the 2nd law as a ‘net’ summation of heat in both direction from hot to cold and vice-versa but Clausius wrote the law without any reference to a net flow of heat. He was absolutely clear that heat can only flow hot to cold, ‘by its own means’. In other words, to get heat to flow cold to hot, it requires external power to drive compressors to liquefy refrigerants that absorb heat in a colder environment and transfer it to a hotter environment through compression/expansion of the refrigerant gas.
Some confusion arose in Chapter 9 of one of his (Clausius) manuscripts in which he referred to a two-way transfer of heat via radiation, yet he stated clearly that heat transfer via radiation must respect the 2nd law. It is clear that a confusion by all scientists was in place in his era (circa 1850) due to a misunderstanding of how heat was transferred via radiation. The prevalent view was that heat was transferred via undefined ‘heat rays’, which lead to a general misunderstanding that heat could be transferred in both directions by radiation.
Neils Bohr put a stop to that in 1913 when he hypothesized the action in atoms whereby electrons absorb and generate electromagnetic energy (EM). We know now that heat does not flow through space via radiation but is first converted to EM, representing a loss of heat during that action. That defeats the second part of the AGW theory, that GHGs trap surface heat. Not possible. Any heat associated with radiated EM is lost during the conversion, therefore GHGs must create new heat. The new heat has nothing to do with surface heat, even though it can be related mathematically. That is, it is not trapped.
The very action of electron emission and absorption of EM prevents a transfer of heat from cold to hot. Both emission and absorption take place at discrete frequencies and electrons will only react to higher frequencies of EM generated by hotter masses. EM frequencies from colder masses simply cannot excite the electrons, which in hotter masses, is already orbiting at a frequency too high to be affected by the frequencies of EM generated by colder masses.
No heat flow is possible, by its own means from cold to hot and that was stated clearly in the original definition of the 2nd law by Clausius. In fact, he took time to explain what he meant by ‘by its own means’, a term he later renamed ‘compensation’. It is simply not possibly for heat to be transferred from cooler GHGs in the atmosphere to a warmer surface that produced the heat in the first place in order to raise surface temperature.
A third argument is that GHGs somehow slow down heat dissipation at the surface. However, there is no one to one, direct relationship between a GHG molecule and surface heat. By the time a molecule absorbs surface EM, the surface heat has already been dissipated during the conversion of electron KE, which represents surface heat, hence the rate of heat dissipation has already been determined by other factors. In fact, it is the majority molecules of oxygen and nitrogen, in direct contact with the surface, that largely governs surface heat dissipation via Newton’s Law of Cooling.
Of course, radiation does cool the surface as well but the AGW theory is wrong here in that it has minimized the effect of direct heating of the atmosphere by the surface (direct conduction} and used radiation as the only means of surface heat dissipation. Shula discovered that direct conduction is 260 times more effective at cooling a surface than radiation alone. Besides, only about 10% of surface radiation is absorbed by GHGs, leaving 90% to radiate directly to space.
AGW theory is not only a contravention of the 2nd law but also represents perpetual motion. One simply cannot recycle heat from a surface to a mass and back and cause the mass to warm and that is due to intervening losses in the system.
I have never seen Roy attach a meaning to the trend since I have been here. He has claimed the anthropogenic effect is contributing but he has never stated how much.
I’ll try to dig up some commentaries from John Christy on his view of the meaning of the positive linear trend.
Gordon Robertson, it seems that we agree that a linear fit to the data shows a warming trend. By extension, we must agree that a second order polynomial fit demonstrates an acceleration in the warming trend.
Your arguments that AGW is not involved are unconvincing. Note that Stefan Rahmstorf and Grant Foster, who have deep understanding of climate change and statistical analysis have examined global surface temperature trends through 2024, accounting for El Nino, volcanism and solar variation. Their conclusion is in the title of their paper “Global Warming has Accelerated Significantly”. Further, they note: “The unusually rapid rise of global temperature over the last decade cannot be accounted for by the usual suspects.” The Rahmstorf/Foster analysis demolishes your argument about not understanding the “context”.
Art Groot is of course plain correct, and Robertson’s urging to reply once more with his usual endless, though empty posts won’t change anything.
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Let us demonstrate this with a comparison of linear, 2nd order resp. 3rd order polynomials over UAH’s LT Globe data:
https://drive.google.com/file/d/1ptQ2aZhTJYhr0nqB4RBKXLnszCpskvQz/view
You see that the higher the polynomial order, the more does the result espouse the source; and the source clearly contains an acceleration tendency.
If there was no acceleration, the polynomials would all look like the linear trend, which after all is a simple, first order polynomial :–)
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And when I read somewhat more below
” A polynomial model is probably not useful. However, if you know when the warming ends [sic], the linear trend is somewhat useful. ”
I simply get a big laugh.
“Here’s the context. From 1979 till 1998, the global anomalies were largely negative, meaning there was a global cooling period between those years.”
Not at all.
Anomalies are temperature minus baseline, which is set by the average of the whole series.
Anomalies were negative then because the whole series has had a net warming trend, and thus the early temperatures were below the average.
Thus negative anomalies has nothing whatsoever to do with ‘cooling’, which is a possible TREND in the data.
Nate
Robertson still can’t manage to understand what anomalies really are.
The reason is quite simple, he doesn’t want to grasp it, as he isn’t even able to download any data and to process it using the simplest spreadsheet calculator.
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Despite ranting since years against NOAA’s allegedly ‘fudged’ data (he does because the authorities he appeals to also do), NOAA’s anomaly explanations for uneducated people are exactly what he needs, as he himself is one of them:
https://www.ncei.noaa.gov/access/monitoring/dyk/anomalies-vs-temperature
Though the text contains indeed lots of relevant matter, Robertson is only able to keep the simplest part of it:
” A temperature anomaly is the difference between the observed temperature and a baseline average temperature. ”
…
” A positive anomaly means the observed temperature was warmer than the baseline, while a negative anomaly means the observed temperature was cooler than the baseline. ”
This is at best simpleton level.
It’s not so long time ago that he had the chuzpah to discredit and deny my knowledge of how anomalies are actually constructed – namely by removing the annual cycle out of them, as do all people, beginning with Roy Spencer en personne.
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Now back to his stupid claim:
” From 1979 till 1998, the global anomalies were largely negative, meaning there was a global cooling period between those years. ”
He couldn’t be more wrong. The trend in C / decade for Jan 1979 – Dec 1998 is 0.162 +- 0.02, i.e. the same as for the entire series till now.
Robertson will never understand the difference between cold / warm versus colder than / warmer than.
A polynomial model is probably not useful. However, if you know when the warming ends, the linear trend is somewhat useful.
TLDR: less than 3°C of additional warming before tipping into rapid cooling around 2150-2200AD (not an ice age).
Based on sunspot data, a 20-year cooling trend began in 2016. The sunspot-based model can predict up to 13-years into the future due to delay between sunspot data and surface temperatures. Of course sunspots don’t predict volcanoes.
https://localartist.org/media/TempPredictExpanded.png
With the HT eruption we’re in uncharted waters, pun intended. Stratospheric WV likely explains the surface temperature spike. I don’t expect that ocean heat content has changed significantly, so eventually, if my model is correct, we should return to the original prediction.
This is an animation of the prediction. The model is a 99-year moving average of sunspot data.
https://localartist.org/media/sunspot_temp_animation.gif
The predicted long-term trend is warming. In fact, we appear to be in a variation of the Minoan Warm Period. I base this on a 3500-year cycle I’ve discovered in the orbits of the Sun and Jovian planets. Here’s the 3500-year cycle in the GISP2 ice-core data.
WARNING: This next plot may be distressing to those who strongly believe in anthropogenic warming. Viewer discretion advised.
https://localartist.org/media/temperature_sliding.gif
Based only on Dr. Spencer’s +0.16 deg/°C/decade linear trend, if warming continues until 2150-2200, we might expect an additional 2-2.8°C of warming before tipping into cooling.
I expect less warming as the linear trend is estimated over a 40-year warming period, extended by the HT anomaly.
mark b…”…Australia is the smallest region in the table, hence subject to less area averaging, so the expectation is that its standard deviation would be the largest”.
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Australian temps are a poor metric wrt global average. For one, the entire continent is located in the middle of the worlds largest ocean. For another, it has a tremendous climate variation from tropical in the north, through sub-tropical, mid-latitude, to a Mediterranean climate in southern Oz. The entire central region is mainly a desert-like, arid climate. This is the opposite of what we’d expect in the NH.
Australia’s average temperatures are expected to be higher than the global average. Not really fair to hold their temperatures up as representative of current warming since the place is warmer than the norm to begin with.
It’s not temperatures so much as temperature ‘anomalies’ – differences from the long term average for each region listed.
It doesn’t matter what climate or range of climates any given region has; that doesn’t change over a few decades. What matters is the change relative to the long term average.
Over UAH’s time of measurement, Australia has warmed at a rate of +0.22C per decade; considerably faster than the global equivalent of +0.16C per decade.
finalnail….the location of Oz, surrounded by large expanses of ocean is responsible for much of their temperatures anomalies. I think the southern hemisphere and the Pacific Ocean get a far greater share of solar energy than much the rest of the planet year round.
FinalNail
Once more we look at Robertson’s mix of ignorance and boastful speech.
” Australia’s average temperatures are expected to be higher than the global average. Not really fair to hold their temperatures up as representative of current warming since the place is warmer than the norm to begin with. ”
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He apparently didn’t understand what Mark B wrote – it was just about the simple fact that the smaller an area, the higher the deviations in its temperature time series.
But instead of trying to understand what he read, he suspected behind Mark B’s words an attempt to speak about warming! Oh Noes.
One hardly could behave more dumb.
“Australian temps are a poor metric wrt global average.”
No country or even region is a good proxy for global temps. Almost everywhere has warmed over the last century, but the timing of rises and falls and the total amount of warming varies from region to region.
barry…fair dinkum….I was not taking a shot at Oz. My point is the extreme diversity of climates available in Australia coupled with the fact it is surrounded by a major ocean, the Pacific, and abutting the Antarctic Ocean.
As an island nation you in Oz are subjected to extremes that other nations simply don’t experience.
We in Canada have our share of extremes, even in this province of BC. However, we don’t have any major extremes like moving from a tropical climate in the north to a Mediterranean climate in the south, with the vegetation typical of such extremes.
“I was not taking a shot”
Me neither.
SOLAR MINIMUM UPDATE
Why are troglodytes fighting renewables? This little bit of info explaining reduced consumption of natural gas contains the answer. Drops in gas use are:
“driven by renewable generation increases”
Renewables are destroying nat gas demand in the US (largest consumer of nat gas in the world).
https://bsky.app/profile/did:plc:6ml4nxrk45cy23jay5hc2npp/post/3m3wpvnmp4k2y
Good. That should help with both heating bills and electricity prices.
none of the above is consumer driven,rather a forced transition,
Forced transitions is the hallmark of the current US government. Tariffs, the shift back to manufacturing, threatening p. company outsourcing, none of these are consumer driven either.
1. Statistics isn’t science. It’s a tool of science.
2. If you do have large temperature variations *at a location*, it’s almost certainly because the location has low humidity not because the data is dodgy!
I’d argue Canada’s climate variations are just as extreme as Australia’s – look at the difference in summer and winter temps in the central states. The centers of large land masses always have the extremes. It might not get as steamy hot as Darwin, but that’s just latitude. Aus is much closer to the equator and a lot of it is in the tropics. But because of water vapour and convection, the equator, where energy is maximised, and days relatively short, isn’t usually the hottest place on the surface.
Averages of averages are just masking the true mechanisms of energy transfer and are unlikely to lead to any real insights (science). If we want to understand weather patterns we should be integrating temperature over a fast time constant, not averaging it over ever slower ones and generally assuming normal distributions are at play – because over long timescales, they are distorted by the long time-constant cycles we don’t understand, or perhaps more correctly, have not properly characterised. Hence Dr Spencer using a linear trend – it’s the simplest honest fit to the data series that has predictive value (is it hotter or colder now than at some other point in the series?).
Climate, as invented by geographers, is about heat and energy, not temperature and it was useful to tell whether crop A would grow in location X. Temperature (an energy distribution in matter) is just a consequence of processes that are poorly characterised (mostly ignored) in all models. It frustrates me no end that we have the meterological understanding and computational power to produce extremely accurate short term weather forecasts that could form the basis of saving lives and minimising property damage, but instead we’ve wasted billions of dollars trying to make long range forecasts more accurate and understand the climate boogie man – and all apparently, when we need accurate forecasts more than ever because of all the extra extreme weather events we are going to get in the future.
Modern climate science just isn’t useful! It arguably was when tipping points were plausible, but we are 50 years on now, time to admit warming from anthropogenic CO2 is nothing like as bad as was first feared and disband climate research at scale.
/rant over.
Bravo!
https://i.ibb.co/HfS4BWGF/574951435-1412040014256304-6812226391011095891-n.jpg
Freeman Dyson summed it up,when he said climate only takes up less than 1% of his time,other problems are more important.
You have a really good point about people making speculative claims based on “science”. I am reminded of “The Boy Who Cried Wolf”. As time goes on, and more and more speculative claims are debunked, it is the reputation of the science community that suffers. Use of the term “climate change denier” by left-wing media and politicians makes the problem worse. Skeptical analysis is the bedrock of science, but it is not allowed when it comes to climate.
What if there was a pandemic and science created a very effective vaccine in a short period of time, but people were afraid to take it because they did not trust science? Oh, wait, that happened! How many people died because they thought is was safer to be exposed to a deadly virus than receive a vaccination? This story continues on a smaller scale with measles.
Gordon, please do not pollute my serious comment with your crap about virus science being fake.
BACK AT THE RANCH
SUMNER, NE—The Richard B. Cheney Vice Presidential Library and Museum officially opened to the public on Wednesday, housing a variety of exhibits honoring the legacy of the former vice president on display in a vast, dark, sulfurous cave thousands of feet below the surface of the earth.
https://theonion.com/dick-cheney-vice-presidential-library-opens-in-pitch-da-1819574915/