One more dot on the graphs for our annual model-observations comparisons updates. Given how extraordinary the last two years have been, there are a few highlights to note.
First, we have updated the versions of a few of the observational datasets: UAH TLT/TMT are now on version 6.1, and the NOAA NCEI surface temperature data are now version 6. We use the same collations of Hansen81/Hansen88/CMIP3/CMIP5/CMIP6 model output as previously. The comparisons cover surface air temperatures, sea surface temperatures, tropospheric atmospheric temperatures (TLT, TMT), stratospheric temperatures, and a few variations on these themes that have been of interest in the past. (It would be nice to have some non-temperature variables in the mix – feel free to suggest some if you can point to (or post) an archive of the models historical+projected results).
With respect to the GMSAT, it’s striking how close the real world is to the Hansen et al. (1988) ‘Scenario B’ (this scenario had ‘business as usual’ concentration rises in CO2, but too much growth in CFCs and CH4. However, the prize for most skillful projection still goes to the CMIP3 ensemble; even after 20 years, it’s still pretty much spot on.


The detailed issues that lead to some angst around the CMIP5 models – mis-specifications of the forcings, the importance of the SST/SAT blend vs. SAT trends have somewhat faded in importance. These are/were real issues, but they are small compared to the ongoing trends. With respect to CMIP6, the observations (across a swath of temperature related diagnostics) are still best matched by the sub-sample of screened models (i.e. discarding those that ‘ran hot’).
The updates with respect to the atmospheric temperature profiles (MSU/AMSU derived diagnostics), have become slightly more favorable to the models, though the structural variation between the RSS data and the UAH/NOAA STAR retrievals is still clear. For the sea surface temperature, the real world seems to warming at the upper end of expectations, but still (just!) within the screened spread.
One of the main reasons to maintain these comparisons is to see where discrepancies arise. To that end, multiple versions of the observational data are obviously useful since they can give an estimate of the structural uncertainty (this has been very important in the MSU/AMSU comparisons for instance). In other instances, we have less concerns about the observational data, but we are concerned that the models are not being given the right inputs. For example, since the internal variability in stratospheric temperatures is much less than in the lower atmosphere, incorrect forced signals can emerge faster. I think we may be seeing some of that in the SSU comparisons…
The match to the models is very good over the historical period (to 2014), but post 2015, there is some mismatch between the model variance and the obs. There are two potential issues – the timing of the solar cycle 25 (a solar max warms the stratosphere) – which happened earlier and bigger than expected by CMIP6, and the presence of the Hunga Tonga volcano (from 2021) which is having complex impacts on the stratospheric temperatures. Nonetheless, the long term trends are still well-modeled.
As always, if someone knows of expanded model diagnostics and relevant observational data sets to compare with, let me know and we can add it to the page.
Thanks as always to the data centers who provide the observational data, the CMIP committees who organised this storage of the outputs, the modeling centers that did the runs, and the authors who produced the derived data sets we are using directly here (full refs on the above listed page).
See you next year!
Not a scientist, just an interest in weather models… However one aspect that is becoming important is the number of high winds we are seeing. Of course this is directly related to the overall temperatures, but it is also becoming the cause of a number of wildfires across the Western US, and the intensity of hurricanes.
I have not run across any models that try to predict how the continued global warming will affect these winds, but it seems like that information would be useful for predicting trends towards future disasters.
This is also affecting the arctic blasts we are seeing so spotlighting the trends towards rapid cooling in areas, especially when those downward spikes are sudden and severe, may be a good indicator of how the climate has shifted. For example, here in Colorado a few years back we had one day where the temperature dropped by 70F overnight, killing off otherwise hardy pines. And on the opposite side, I watched the temperature rise by 50F over a period of less than four hours one morning. What happens to the plant life if these trends get worse or more frequent?
S: I have not run across any models that try to predict how the continued global warming will affect these winds, but it seems like that information would be useful for predicting trends towards future disasters.
BPL: I don’t know of a time series for global average winds, although I have seen some estimates. Perhaps some exist for winds in particular areas. If you can find one, you can then apply time series analysis to see how it might be related to temperatures or other factors.
I’m not sure I’D want to try THAT time series analysis without a lot of time and resources (and a grad student or two!)! Just operationalizing wind fields in some sensible and well defined way kicks the math to a whole new level!
Send a note to Tamino…he could likely do it in a few days!!!
Thank you for all the interesting work. However it would be nice if some high resolution versions of the figures were available, as I like to show some of them to my students in class (Climate change Biology course).
[Response: All of them are 300 dpi png files on the main page. Is that not sufficient? – gavin]
i) Open Image in New Tab and ii) Save As. (or some such).
They are okay but still a bit blurred when projected onto a big screen in a classroom. I might be too picky. Thanks anyway.
I agree – they don’t look good. Bigger PNGs, or maybe SVGs, could be much better.
There are programs that are able to sharpen images, Gimp (which is free, but sometimes seems only a little more user friendly than a rabid dog) or perhaps even your phone’s photo gallery. Perhaps you will have to convert from one image format to another, but as long as you don’t over-sharpen the results should be more in line with what you are looking for.
So maybe I’m looking at the wrong files. The image cmip6_sst-600×414.png is 600×414 pixels at 72 dpi. Resizing it (I went for 300 dpi) and fiddling with unsharp masking helped some as a quick fix.
It looks like there are on-line AI tools that will let you up-sample and enhance images for free. I can’t vouch for any, but maybe worth a try.
Hi, I’m a media person who deals with visual files often. I agree. These are kind of low res for these days. Especially for full screen TV and projection. And my software tools reveal them as 72 DPI.
Thanks for these graphs, BTW. So helpful.
[Response: They are uploaded as 300dpi, so maybe I need to tweak something… Update: I tweaked the settings, they should be full resolution now. – gavin]
“There are two potential issues – the timing of the solar cycle 25 (a solar max warms the stratosphere) – which happened earlier and bigger than expected by CMIP6”
That’s embarrassing to mention sunspots. Attributing solar sunspot cycles to climate variation is the equivalent of prescribing Ivermectin to a medical condition. Perhaps worse because you guys claim to understand the physics.
Not sure I understand your point. You seem to be denying the link between the solar cycle and fluctuations in temperature. I thought it was well established that the 11 year sunspot cycle does give rise to an 11 year cycle in global temperatures, but that is overlaid on whatever other trends are apparent: in this case, a steady warming trend. But perhaps I have missed something. Perhaps you could clarify? And in what sense does the posting misunderstand the physics, as you seem to imply? Thank you.
The key is how much solar cycles influence climate variability. Not very much. Your comparison to Ivermectin is unwarranted.
It’s not clear if the current sunspot cycle had much to do with this particular heat spike, but in general sunspots do increase the temperature in the stratosphere. The effect is very nonlinear.
https://localartist.org/media/StratCooling.png
Paul Pukite: “ That’s embarrassing” , “equivalent of prescribing Ivermectin”, “you guys claim to understand the physics”
Extraordinary claims demand extraordinary evidence. Your seething contempt toward Gavin and other “you guys” is as extreme as they come. Yet your extraordinary evidence is …absent.
So put your money where your mouth is – PROVE beyond ANY doubt (“extraordinary evidence”) that the solar cycle does NOT have any effect on the Earth temperature
Since you described Gavin’s “a solar max warms the stratosphere”, to be “embarrassing” and “equivalent of prescribing Ivermectin” – how hard could this be for you, Mr. Pukite?
Not so.
See, for example, Foster and Rahmstorf, 2011:
https://www.researchgate.net/publication/254496419_Global_temperature_evolution_1979-2010
” When the data are adjusted to remove the estimated impact of known factors on short-term temperature variations (El Nino/southern oscillation, volcanic aerosols and solar variability), the global warming signal becomes even more evident as noise is reduced”
https://www.merriam-webster.com/dictionary/hubris
WHUT I am still willing to read your research on ENSO when it has been published in a non-predatory peer reviewed journal.
Note the quote specifically mentions stratospheric temperatures “(a solar max warms the stratosphere) “. IIRC there is a big increase in UV associated with sunspots and that UV is absorbed by ozone in the stratosphere. So while it has a modest effect on surface temperatures, I can see why it would have a greater impact on the stratosphere. So it seems pretty reasonable to me (especially as there is less internal variability in the stratosphere, so small changes in forcing will be more easily detected there).
in re to Paul Pukite, 28 Jan 2025 at 2:25 AM,
https://www.realclimate.org/index.php/archives/2025/01/comparison-update-2024/#comment-829608
Dear Paul,
The relationship between climate variations and sun activity cycles was the Ph.D. thesis topics of notable Czech astronomer Ladislav Křivský in the year 1948:
https://www.astro.cz/spolecnost/sin-slavy/ladislav-krivsky.html
40 years ago, I read in one of his books an explanation why the power output of Sun is slightly higher at the maximum of sunspot number than in minimum of teh solar cycle (although sunspots are colder than the rest of chromosphere.
It is because the opposite effect of much less remarkable hot solar flares accompanying the sunspots prevails. It appears that respectable information sources like
https://www.weather.gov/fsd/sunspots
https://www.climate.gov/news-features/understanding-climate/climate-change-incoming-sunlight
https://www.landgate.com/news/the-impact-of-sunspots-and-solar-flares-on-solar-energy
https://spaceplace.nasa.gov/solar-activity/en/
still share this view.
I therefore join Rory Allen in asking you for clarification of your assertions.
Best regards
Tomáš
Especially embarrassing in the context of sunspots having zero effect on the ocean’s thermocline, which is clearly sensitive to mechanical forcing, such as from the strong lunar tidal effects operating on the reduced effective gravity environment along the thermocline interface.
That’s the physics. In physics, we learn what has a 1st-order impact on behavior, and what has 2nd-order, 3rd-order, etc influences. So tidal and the annual cycle is likely forcing ENSO to 1st-order, and sunspots 3rd-order. Wind may be a 2nd-order forcing as it has been shown that thermocline changes lead changes in the prevailing wind, see https://www.nature.com/articles/s41598-019-49678-w. The wind would therefore lag as the pressure differential set up by the (up/down)welling thermocline causes the shift in the winds (i.e. wind is caused by a pressure gradient).. That places it at 2nd-order at best.
Tidal forcing as mentioned by Munk & Wunsch for abyssal processes is therefore the only remaining possibility to drive the erratic ENSO behavior. See this paper by Wunsch for applicability to AMOC in the other RC thread http://ocean.mit.edu/~cwunsch/papersonline/wunsch_2000_moon_climate_nature.pdf
Gavin: “a solar max warms the stratosphere ”
Paul Pukite: “That’s embarrassing” , “equivalent of prescribing Ivermectin”, “you guys claim to understand the physics”, “Especially embarrassing in the context of sunspots having zero effect on the ocean’s thermocline”
Not everything revolves around your hobby horse, ENSO. “ Stratosphere” is NOT in “the ocean thermocline“. “Especially embarrassing” it is only for somebody who has just lectured Gavin, who unlike him, publishes in the best scientific journals, about …. HIS ignorance.
P.S. I might have unearthed archival footage from
your Ph.D. defense , Paul. Or was it the latest, not entirely successful, grant application?
Piotr said:
“Not everything revolves around your hobby horse, ENSO. “
I have several hobby horses when it comes to Earth sciences, Piotr. I spend time researching them dependent on how challenging they are to solve, ENSO being one of the most challenging. That’s the way it is in science, the toughest nuts to crack gain the highest notoriety and sink the most time and effort. The geophysical fluid dynamics encompassed in ENSO involves aspects of solving the Navier-Stokes equation, which is listed as one of the 10 Clay Mathematics Institute millennium problems. https://www.claymath.org/millennium/navier-stokes-equation/
My underlying hobby-horse is trying to piece how it all fits together. https://geoenergymath.com/2024/11/10/lunar-torque-controls-all/
ENSO may be the last piece of the puzzle,
“The geophysical fluid dynamics encompassed in ENSO involves aspects of solving the Navier-Stokes equation, which is listed as one of the 10 Clay Mathematics Institute millennium problems. https://www.claymath.org/millennium/navier-stokes-equation/”
The highly specialized and simplified form of the Navier-Stokes equations that you employ, including terms dropped at solution time, are in no ways whatsoever related to the formulation that is explicitly and completely specified in the Clay problems. The Clay problem does not in fact address solving the equations. Instead, the Clay problem addresses mathematical proof of existence and uniqueness of solutions to the complete formulation of the transient, 3-dimensional, incompressible flow equations. The Navier-Stokes formulation explicitly specified in the Clay problem almost never appears when solving of the Navier-Stokes equations are presented. Approximations for the shallow-water form for flows on a rotating body, and in which a term arising from the rotation is dropped, are no different than the thousands of “solutions to the Navier-Stokes equations” that have been developed over the past 170 years by engineers, mathematicians, and scientists.
“Especially embarrassing in the context of sunspots having zero effect on the ocean’s thermocline,”
so tell me, how does that affect STRATOSPHERIC temperatures, which was the subject of discussion in the quote?
Doubling down is not a good approach, especially if you make it clear you haven’t properly read the passage you were criticising.
Paul, I read your “Attributing solar sunspot cycles to climate variation” again, and if I use the dictionary definition of verb “attribute”, it appears that you think that they were claiming climate variation is the cause of solar cycles.
Is that what you think they were saying? Because as others have noted, it would be accurate to attribute a bit of climate variation to solar cycle changes in insolation – and they said “a solar max warms the stratosphere”
Scores of climate change deniers, AGW skeptics, or whatever you want to call them prefer to apply sunspot variation as an alternate theory to the GHG model. They do this (IMO) because:
1. Mainstream climate scientists keep citing solar variations as a contributing factor (however marginal it may in fact be).
2. Sunspots have shown larger variability in the past, i.e. Maunder Minimum.
3. There is no good model for predicting sunspot cycles, so they can claim that climate predictions are equally uncertain.
Think of all the deniers that push sunspots as an alternative model of climate change : Zharakova, Soon, Scafetta, etc. And Svensmark, who gained it more legitimacy by being able to secure time and funds at CERN to do iffy experiments.
It was Gavin himself that posted this RC article (w/MM) “The Trouble with Sunspots” https://www.realclimate.org/index.php/archives/2006/09/the-trouble-with-sunspots/
That was in 2006 and I had been blogging for a couple years already so took note of those kinds of observations by Gavin, Michael, and others as to the marginal impact of sunspots on climate variability.
I’m not going to get involved in subjective prose wars, as people like Piotr always attempt to smear me with. So did I apply the word “attribute” or “attribution” correctly? If you all think that is all that is important, all I can do is sigh.
To Dikran: read my Wiley text “Mathematical Geoenergy”. It was peer-reviewed and a lot of sweat went into that work. I was able to elaborate on topics to a greater length than I could in an ordinary research article. The blog I write now, updates the findings, https://geoenergymath.com/2024/11/10/lunar-torque-controls-all/, and continues my research into solidifying a unifying concept, which the monograph started. There is a possibility that the publisher could even revise as a new edition, which book forms allow. The John Wiley editor made a good call in guiding the book through publication — half is on FF/oil depletion which is standing the test of time, continually updated on the POB blog by my co-author. BTW, we are doing this with no outside funding.
Good luck to all in the Trump generation – we will do OK ;)
Hi Paul. “So did I apply the word “attribute” or “attribution” correctly? If you all think that is all that is important, all I can do is sigh.”
Sorry, I grew up in a family with teachers and lawyers, and words do matter – so you didn’t read things backwards – but you object to mention of a cyclic component of overall temperature fluctuations, seeming because dishonest climate messaging abuses solar cycles. Well, they abuse all the rest of the science while they’re not ignoring it instead, so I don’t see why Gavin and the rest should avoid even pointing out that it’s there. Problem with that approach is when something minor is left out – the deniers pounce again. Not mentioning things isn’t going to improve the quality of what gets out to the public, unfortunately.
Here’s a nice, detailed piece about solar cycles and our temperatures from the NOAA site, published in 2009 – I recommend readers look quickly.
https://www.climate.gov/news-features/understanding-climate/climate-change-incoming-sunlight
And a TSI graph https://www.climate.gov/media/13199
I suggest reading quickly because the NCEI pages at NOAA have a banner message that might be benign, but mischief on federal sites has already begun under the new “management”.
Here’s their warning: “Please note: Due to scheduled maintenance, many NCEI systems will be unavailable February 4th, 12:00 PM ET – February 6th, 8:00 PM ET. We apologize for any inconvenience.”
I’ve been in IT for decades and scheduled maintenance during the business week isn’t what I typically plan for. I’ll certainly spend some time late this week looking for what’s still there.
b fagan said:
Well, they leave out the major annual/seasonal signal from the model without fully appreciating the implications of that decision. Consider this logical assertion born from experience: `For modeling of time-series, it may be important to leave a Fourier component in place during the fitting process since a physical model may require that as a non-linear mixing term. Whereas if that Fourier sinusoidal coefficient is filtered out, there is no remnant of that term, so the amount of mixing can’t be calibrated. Give examples of where that may happen.` I know of some applications where this is an important consideration, but this is what DeepSeek responded with given that prompt: 3. Climate Science: Ocean Tides and Atmospheric Oscillations
Scenario: Ocean tides and atmospheric oscillations (e.g., El Niño-Southern Oscillation, ENSO) exhibit periodic behavior driven by gravitational forces and ocean-atmosphere interactions.
Importance of Fourier Components: The Fourier components of these systems correspond to tidal harmonics or climate modes. Non-linear interactions between these components (e.g., tidal mixing or ENSO teleconnections) are critical for understanding the system’s behavior. Filtering out these components would eliminate the ability to study how these interactions influence climate variability.
It is obvious that the annual and ENSO contributions are at least 100x stronger than the minor impact of sunspot variations, yet they don’t get included in any projections. As I have mentioned before here, this is an important consideration mentioned by others, such as from this NASA JPL proposal by Claire Perigaud where this was deemed critical but the project was not funded, in her words “proposed solutions were not considered because of various factors including economic and scientific pressure to publish and continue the standard agenda” Read the full response in the wayback archive:
https://web.archive.org/web/20201101002715/http://www.moonclimate.org/docs/forenote.pdf
The standard agenda seems to be to pay lip service to inconsequential factors such as sunspot variations while ignoring, albeit perhaps out of limited analytical capabilities, the actual much stronger factors governing the temperature variability.
The topic of the quote was STRATOSPHERIC temperatures, not surface temperatures. Sunspots are more likely to have a stronger effect on STRATOSPHERIC temperatures than surface temperatures (e.g. via changes in UV).
I am not paying $200 for a book that doesn’t even mention ENSO in the blurb or the table of contents. I’ll read a peer review journal paper though. Have you submitted the work on ENSO to a journal where ENSO is squarely within the scope of the journal (and hence can expect an expert peer review)?
Thanks for your interest in the book Mathematical Geoenergy. The modeling of ENSO is clearly described in the online blurbs and table of contents. See, for example, here: https://agupubs.onlinelibrary.wiley.com/doi/10.1002/9781119434351.ch12
Because of the way scientific publishing works, one can always get full access to the book contents through a university or though a student, faculty, or alumni online account. Otherwise the cheapest option is to get temporary access to the chapter PDF for $10, link above.
I note you ignored the part about the discussion being about STRATOSPHERIC warming rather than surface warming, and hence your initial post being unfair and factually incorrect.
Actually, no, I don’t have access to the book via my institution. The book is unlikely to have been reviewed by an expert on ENSO as it is only a subtopic of one chapter.
I notice you didn’t answer my question about whether you had submitted your ENSO work to a peer reviewed journal where ENSO was within the scope.
Can you just admit that you misread the original quote (which was about STRATOSPHERIC temperatures) and that your intemperate response was factually incorrect? I suspect not.
I did submit a paper to Physical Review Letters long ago. This is the response that I had archived in my email:
So I submitted the research to an AGU monograph series published by John Wiley. The editor helped guide it through peer-review. An AGU board of reviewers considered my responses sufficient for it to be published. Sorry if that does not meet to your standards.
I note you still haven’t acknowledged that your original comment was factually incorrect because the quote was about STRATOSPHERIC temperatures rather than surface temperatures. At this point it is difficult not to conclude that the evasion is deliberate.
I see you have been less than complete in your submission history
https://esd.copernicus.org/preprints/esd-2020-74/
Not accepted. First review was pretty excoriating:
“To be blunt, trying to shoehorn ENSO into a periodic tidal framework stretches reality
to fit someone’s preconceived theory. Only the most motivated reasoning can believe
this.”
and also mentions lack of proper validation, which IIRC is an issue I have raised before.
“The best way to see the non-tidal nature of ENSO is to note that its behavior is well-
represented in models of the coupled ocean-atmosphere system ranging from the ide-
alized (e.g. Cane and Zebiak 1987 MWR) to modern GCMs … none of which contain
tides. These models DO have predictive skill, which is regularly tested by issuing de-
tailed public forecasts. ”
As I said, I doubt your book was peer reviewed by someone with expertise on ENSO (unlike the above discussion paper).
The latest “Deep Research” variations of LLMs generate quite detailed reports of findings. This is one submitted for the prompt “Explain tidal forcing behind ENSO using derivations based on reduced effective gravity on equatorial thermocline.”
https://geoenergymath.com/wp-content/uploads/2025/02/tidal-forcing-and-enso-dynamics_.pdf
That used Gemini Advanced 1.5 Pro with Deep Research. It raises the question of how much future LLMs will use knowledge spread across sources of information ranging from blogs to peer-reviewed articles.
Dikran mentions: ” non-tidal nature of ENSO”
This is an eye-opener https://geoenergymath.com/2025/01/31/tidal-gauge-differential/
Barring the very long-term rise, tidal gauges primarily measure effects derived from tidal effects. This raises the idea that ENSO is a behavior derived from non-linear tidal effects, The journal ESD Ideas should be about bringing to the fore ideas that are not comprehensively explored by the earth sciences community — and that’s what their charter says “present innovative and well-founded scientific ideas in a concise way (no more than two pages, including one figure or table) “
Paul Pukite: In stating “,,,embarrassing to mention sunspots. Attributing solar sunspot cycles to climate variation is the equivalent of prescribing Ivermectin to a medical condition”, you appear to characterize human Ivermectin use as the height of folly.
In the interest of accuracy, Ivermectin is proven and noncontroversial treatment for a number of human medical conditions. That Covid is not one of them is perhaps the source of your misunderstanding.
Hi Gavin, is there a site that i can get the maximum and minimum worlds average temperatures on a yearly basis?
Cheers.
Simon,
If you’re after annual averages of daily high temperature and daily low temperature (which would apply only to land SAT), Berkeley Earth have both graphed out and link to the data HERE.
If you’re after the average over the land and oceans, you are presumably after the absolute temperature version of the monthly or perhaps daily global SATs showing the annual cycle with its max & min. The absolute temperatures require the temperature of the anomaly base by month or perhaps day. This will require a bit of data manipulation by you and the absolute anomaly base data can be well tucked away. For GISTEMP this page appears to show it. Berkeley Earth show it in the header to the data HERE. (Note there are two sets of anomaly data.) ERA5’s Climate Pulse site graphs out absolute daily global temperature and below the graph is a download button for the 85 years of daily data.
Thanks MA Rodgers
It would be helpful to provide the conversion from 1979-1983 to 1850-1900 baselines.
It would have been helpful if the antebellum United States had launched weather balloons or satellites so that we’d know the 1850-1900 baseline. As it is, surface temperatures are about the only thing measured well enough to provide a global baseline for 1850-1900, and even then just barely.
Dan Miller,
The 1979-83 anomaly base applies to the SST data. HadSST4 & ERSSTv5 understandably show the warming a little different back in the nineteenth century (see graphic HERE). 1979-83 relative to 1850-1900 come out as HadSST = +0.42ºC & ERSST = +0.32ºC.
I wouldn’t know how to show the combined uncertainties from each observation dataset, but note the wide confidence limits around Berkeley Earth’s rigorously QA’ed 19th century measurements and even through the first half of the 20th, compared to more recently:
berkeleyearth.org/wp-content/uploads/2025/01/2024-Global-Time-Series-1536×846.png
As Dr. N-G says, As it is, surface temperatures are about the only thing measured well enough to provide a global baseline for 1850-1900, and even then just barely.
Gavin briefly discussed the choice of baseline last month (realclimate.org/index.php/archives/2025/01/2024-hindsight). He’d prefer 1880-1899, but:
The people have spoken, and they have collectively agreed that ‘pre-industrial’ can be thought of as the average of 1850 to 1900.
My link to the BEST full time series with error bars isn’t stable. The graphic appears on their most recent global temperature update:
berkeleyearth.org/global-temperature-report-for-2024/
While the globally averaged T anomaly is managed to be kept on track at the surface and stratosphere, how do the screened models compare to the mechanisms of energy accumulation, i.e. the ambiguous forcing and feedbacks observable as TOA all-sky trends of absorbed solar radiation and canonical greenhouse effects? (a la CERESMIP). Thanks
NASA have provided a handy explainer Paul (minus the physics of why more sunspots = more irradiation): https://spacemath.gsfc.nasa.gov/sun/Earth8.pdf
If one takes the NASA GISTemp annual (J-D) anomaly data from 1970 forward and plots the year-over-year rate of change values the strong upward trend becomes substantially lowered…moderated. Perhaps someone can explain that phenomenon.
If one actually shows their work to experts, then experts have a much easier time explaining what you’ve done to you that you didn’t understand.
What specific variables did you construct using what specific level of aggregation” What was the level of significance of your “substantially lowered” value?
Should be only about a 10 line R-script to show your work. Please do said and show the world.
Probably something to do with wishful thinking, unreliable memory, confirmation bias, and looking at it through a mirror while standing on your head and squinting through a tiny gap in your fingers, Ken.
Interesting post. But I’m afraid that the hopeful “see you next year” will demand a whole lot of political activism from all scientists and rightminded citizens against the current administration, ie. the sadopopulist fossil oligarchs who won the last US elections, since they are now engaging in a total war against both science and democracy: https://www.nature.com/articles/d41586-025-00266-1 . “Researchers in the United States are reeling after the administration of new president Donald Trump issued an order on 27 January that froze all federal grants and loans. A federal judge in Washington DC temporarily blocked the order late today, but it had already spurred many US universities to advise faculty members against spending federal grant dollars on travel, new research projects, equipment and more.
The Republican-led administration issued a subsequent memo today attempting to clarify what is and is not covered by the freeze, but it included no information specific to scientific funding, leaving many scientists just as confused as when the order was issued.”
The discussion about whether this is fascism or not is rather irrelevant, since the catastrophic results in the longer run will be the same anyway.
Mostly it will mean that US research will be ignored just like Russian genetics research was ignored during the Lysenko era.
I have started referring to Soviet Science – only that which matches the accepted ideology. Even if short-term funding returns to NIH, the writing is on the wall.
The model data comparison graph of the forecast models run in 2024, the warming trend follows the ensemble mean quite well from 1970 – 2005, then droops below the ensemble mean from about 2005 – 2015 (during the so called pause) and rises above the ensemble mean from 2015 – 2024 by a very roughly similar amount. Has anyone looked at whether whatever caused the drooping period during the so called pause has reversed to cause the recent temperatures to rise above the ensemble mean? I ask as a non expert.
Either way we clearly have a massive anthropogenic warming problem, caused in large part by burning fossil fuels. And I realise there are several possible explanations for the anomalously high temperatures last couple of years.
Gavin wrote: “See you next year!”
I hope so. The way things are going right now, by next year research into climate change may be illegal in the Republic Of Trump (a.k.a. The ROT). Perhaps you’ll be posting from Europe.
Hi Gavin,
Thanks for all these comparisons.
You mention in the CMIP5 post 2005 the RCP4.5 is used, but in CMIP6 you only mention the SSP is used from 2015. Is this all SSPs or only SSP2-4.5? If the latter would it be worth looking at the other scenarios, or would there be little difference over 10 years?
In the CMIP6 plot would it be possible to use a different colour for the “new climate model (CMIP6)” mean , I find it difficult to see on top of the TCR model spread. This non-TCR limited values seems to be spot on for 2024!!
Paul Pukite: “ subjective prose wars, as people like Piotr always attempt to smear me with ?
Huh? “ The stratosphere ” is NOT the same as “ ocean’s thermocline “, Mr. Pukite – ergo the difference between these two is NOT “subjective”.
Quite the contrary – it is as objective as they come, and as such – is central to the logical testing of your “proof” of Gavin’s “embarrassing” ignorance of the Earth’s physics, I quote:
– Gavin: “a solar max warms the stratosphere ”
– Paul Pukite: “ That’s embarrassing” , “equivalent of prescribing Ivermectin”, “you guys claim to understand the physics”, “Especially embarrassing in the context of sunspots having zero effect on the ocean’s thermocline”
And what does it tell about you, Paul Pukite – that my QUOTING you YOUR OWN WORDS – you characterize as an attempt to …. SMEAR YOU? You are what you write, Mr. Pukite.
Re: “(It would be nice to have some non-temperature variables in the mix – feel free to suggest some if you can point to (or post) an archive of the models historical+projected results).”
I’ve cited the IPCC 1990 report before. But I understand if the RealClimate team think it’s best not to add it, if there are plenty of temperature comparisons already:
https://www.realclimate.org/index.php/archives/2025/01/unforced-variations-jan-2025/#comment-829310
In terms of non-temperature variables, they could look at northern hemisphere sea ice extent, as suggested by Roger Pielke Sr:
figure 2 of: https://www.science.org/doi/10.1126/science.286.5446.1934
https://pielkeclimatesci.wordpress.com/2012/04/20/sea-ice-prediction-update-to-2012/
https://pubpeer.com/publications/8AB53E8AC964263F1FD8F80B4B8AC6
He elsewhere also suggested ocean heat content, but his reasoning on that is sketchy:
https://pielkeclimatesci.wordpress.com/2007/04/04/a-litmus-test-for-global-warming-a-much-overdue-requirement/
Or, better yet, skip over the useless analysis by Roger Pielke, and go directly to Tamino’s post(s) showing more up-to-date and more correct information.
https://tamino.wordpress.com/2012/04/23/do-the-math/
DOAK: It’s important to recognize the difference between Pielke Sr. and his son Pielke Jr. Senior is a real climate scientists and is not altogether phony. Junior is a political scientist engaged in denial of earthly and scientific reality for profit and fame. Of course he is loyal to his son, and that is sad.
Oh, I agree that Pielke Sr.’s commentary was unreliable and I’m aware of Tamino’s apt criticism of it. Pielke Sr. didn’t account for basic points like how internal variability biases comparisons over very short periods of time, in which a multidecadal forced response has not had enough time to build up. I mentioned Pielke Sr. because that would undermine other contrarians’ possible complaints about including that projection.
There’s also a PubPeer thread that covers how a ‘models vs. observations’ comparison could be done for that paper:
https://pubpeer.com/publications/8AB53E8AC964263F1FD8F80B4B8AC6
The modeled projections in figure 2 start at different absolute values for sea ice. That could be addressed in a comparison to observations by focusing on quantified trends with CIs, or by showing the sea ice as an anomaly relative to a baseline period.
Gavin, if it’s not a huge hassle, could you also update the figure from this post? https://www.realclimate.org/index.php/archives/2024/04/much-ado-about-acceleration/; especially the one that shows CMIP6, obs, and the Hansen et al 2023 projections? Could come in handy with the new Hansen paper.
[Response: Done! https://www.realclimate.org/images/compare_obs_plus_hansen-1536×1131.png – gavin]