Guest Post by Willis Eschenbach
Well, I decided to take a shot at publishing my views on the cloud feedback response to increases in surface warming. I wrote it up and sent it for peer review to the Journal of Climate.
The reviewers said that it seemed like I was looking at changes in location, not changes over time. So I re-wrote it and sent it back in.
They wrote back and said ok, changes helped, and oh, by the way …
… it’ll cost you $1,546 to get it published.
I can assure you that I harnessed the awesome power that comes from splitting the infinitive. In a far-too-loud voice, I uttered various speculations regarding the ancestry, sexual habits, and personal hygiene of the Owners, Editors, and Reviewers. I fear I went so far as to encourage them to engage in auto-fornication … for all of which I’m truly sorry. It’s just what goes on in 2023, and I’m still not used to it.
So instead, I figured I’d start by publishing it here, and invite people to suggest changes, to point out inconsistencies, and to generally be some combination of Editors and Reviewers of the paper. Please be kind in your comments, I’m just a fool whose intentions are good.
With that as a prologue, here’s the current state of the paper.
Observational and theoretical evidence that cloud feedback opposes global warming
Willis Eschenbach
Independent Climate Researcher, Occidental, California
Corresponding author: Willis Eschenbach
ABSTRACT
Cloud radiative response to a change in surface temperatures is a key component in accurately estimating future temperature changes. Changes in surface temperature lead to different cloud responses in different parts of the planet. However, the overall effect of these changes has been very poorly constrained. (Boucher 2013) Using data from satellite observations, I develop two independent methods to estimate how the clouds in different areas respond to a surface temperature increase. Both methods show a global net surface cloud radiative cooling effect. The size of the cooling obtained in this manner is a minimum value of total cloud cooling, because more cloud-related cooling occurs as a result of a temperature-related increase in thermally-driven tropical and extra-tropical thunderstorms which cool the surface in a variety of non-radiative ways. In addition, using theoretical arguments, I show that it is unlikely that the cloud response amplifies global warming.
1. Introduction
Clouds have a central role in modulating the global energy balance. They have long been recognized as being the major source of uncertainty in climate projections. Although a variety of evidence has been presented, a narrow constraint on how clouds respond to projected warming has remained elusive. Indeed, there is still no widespread agreement even on the sign of the cloud response to warming. Part of the challenge is that net cloud radiative effect involves cloud effects on both solar (shortwave [SW]) and terrestrial (longwave [LW]) radiative fluxes. (Ceppi et al. 2017, Gettleman and Sherwood 2016)
2. Theoretical Arguments
A most unusual yet generally unremarked feature of the climate system is its thermal stability. Here is the trough-to-peak temperature range over a 22-year period for each 1° latitude by 1° longitude gridcell.
Fig. 1. Maximum variations in monthly average temperature (trough to peak) during the period Mar 2000 – Feb 2022.
Here, we see temperature swings of over 30°C in the poles, 29°C over the land, 9°C over the oceans, and 14.8 °C for the globe as a whole. But despite those large intra-annual swings, after 12 months the temperature always returns to nearly the same value. Over the same Mar 2000 – Feb 2022 period, the CERES data reveals annual average global surface temperature changes of only about 0.5°C, which is only three percent of the intra-annual variation.
And as another example, over the entire 20th Century the temperature only increased by 0.8°C, which is a 0.3% temperature rise in 100 years.
Figure 2. Annual temperature ranges for the globe (red line) and monthly temperature ranges for parts of the globe. Red line shows range of 20th Century global average annual temperatures, around 0.3%.
As Figure 2 above shows, this surprising longer-term stability cannot be from thermal inertia, given the far larger monthly intra-annual swings. This overall steady-state condition argues strongly for the existence of natural thermoregulatory phenomena opposing any change in the overall steady-state temperature.
This is supported by Le Chatelier’s Principle. Le Chatelier enunciated a simple principle that governs systems that are in a steady-state condition. Le Chatelier’s principle asserts that a disturbance applied to a system at a steady state may drive the system away from its equilibrium state, but will invoke a countervailing influence that will counteract the effect of the disturbance. (Gorshkov et al. 1990) This principle strongly suggests that if the global average temperature changes, the clouds and other phenomena will act to counteract the temperature change, not to reinforce it.
3. Observational Data Analysis
The net cloud radiative effect (CRE) at the surface is composed of the clouds’ effect on two different types of radiation. The first is solar (shortwave) radiation, which is both reflected and absorbed by clouds. The second is thermal (longwave) radiation, which is both radiated and absorbed by clouds. The net surface CRE, which I’ll call “CRE” for simplicity, is the total of the two effects at the surface where we live. In other words, the CRE is the difference between downwelling radiation in clear-sky and cloudy-sky conditions. If the CRE is negative, it means clouds are cooling the surface.
In general, clouds cool the surface. Figure 3 shows the global variations in the CRE. In Fig. 3 we see that the clouds warm the poles and the deserts, and cool everywhere else.
Fig. 3. Surface cloud radiative effect, on a 1° latitude x 1° longitude basis.
The short-term change in surface CRE with temperature is easily calculated using the CERES data. Figure 4 shows that result.
Figure 4. Short-term trends in surface cloud radiative effect as a function of temperature. Trends are ordinary least squares linear regression slopes.
However, that doesn’t tell us what we need to know, which is how the clouds respond to a long-term change in surface temperature. Despite that, there are two ways that we can use observational data to measure that response.
Both of them depend on a simple idea—as a long-term average for each gridcell, over thousands of years, the temperature and the corresponding cloud radiative effect have reached a steady state condition. All of the various phenomena affecting the CRE, such as relative humidity, boundary-layer inversion strength, CAPE (Convective Available Potential Energy), oceanic subsidence and upwelling, and other factors now oscillate around long-term average values for each given gridcell. Thus, the average relationship between temperature and CRE for each gridcell represents the long-term steady-state relationship.
The first way to see what will happen if the surface temperature warms is a gridcell-based scatterplot of CRE and temperature.
Fig. 5. Scatterplot, 22-year averages of CRE versus surface temperature. Each dot is a 1° latitude by 1° longitude gridcell.
Despite this scatterplot including both land and ocean and covering from the tropics to both poles, there is a clear pattern. Looking from the left to the right in the scatterplot, the slope of the black/white line shows the direction and amount of change in the CRE as the temperature increases. There are four different zones.
The coldest zone encompasses the Antarctic and Greenland ice caps. Where the average monthly gridcell temperature is below -20°C, you are in one of those two locations. There, increasing temperatures lead to increasing cloud warming. This represents less than 4% of the planetary surface.
The next zone is from -20°C to 10-15°C. In this zone, increasing warming results in increasing cloud cooling. The third zone is from 10-15°C to about 25°C. In this zone, increasing temperature leads to increasing cloud warming.
Finally, in the warmest parts, increased surface warming leads to greatly increased cloud cooling. At its greatest, an increase of 1°C leads to up to 40 W/m2 of increased cloud cooling (reduction in downwelling surface radiation).
Now, this shows us the overall pattern of the relationship between temperature and CRE. It is extremely non-linear. But it is a general indication, with lots of scatter around the trend line. It also shows areas from all around the world combined.
What this method doesn’t show is either the detailed spatial pattern or the area-weighted global average response of the CRE to increasing temperature. For this I use a second method.
The second method looks only at the average values of the gridcells in the area immediately around each gridcell. Consider a gridcell in the ocean as an example. Nearby gridcells to the north, south, east, and west of that chosen gridcell will have different long-time average values for temperature and CRE. So we can determine the long-term effect by looking at the local relationship between average temperature and average CRE. For each gridcell, I have used a box that is 9° latitude by 9° longitude, centered on the chosen gridcell. This gives me 81 temperature values and a corresponding 81 CRE values. I do a linear regression of the 81 CRE values as a function of the 81 temperature values. The resulting slope shows the change in CRE corresponding to a 1° change in temperature in the central cell of the range. I’ve analyzed the land and the ocean separately, to avoid mixing different regimes. However, this seems to make little difference. The result is shown in the following Pacific- and Atlantic-centered graphics.
Fig. 6. Changes in surface cloud radiative effect per 1°C change in surface warming. The lower panel is the same as the upper but with an Atlantic-centered view. All values used in the calculation are the average of the full 22 years of the CERES record.
This shows two views, one Pacific and one Atlantic centered, of the detailed location and size of changes in CRE from 1°C surface warming. Globally, there is an area-averaged net cooling of -2 W/m2. The main cooling occurs over the ocean, with an area-averaged cooling of -2.9 W/m2. The land is the only area which is even slightly positive, with an area-averaged warming of +0.3 W/m2
These results are in good agreement with those of Ramanathan and Collins (Ramanathan, V., & Collins, W. (1991)), although the proposed mechanisms are different, and these results are for the planet while Ramanathan and Collins only looked at the Pacific Warm Pool.
4. Stability And Uncertainty
If this metric is indeed a measure of the long-term change in CRE with warming, it should change very little from year to year. The boxplot below shows 22 CRE feedback values for each geographical area listed in Figure 6, one for each year of the CERES record.
Figure 7. Boxplot, change in CRE from 1°C surface warming. Data for each of the 22 years in the CERES record.
As expected, there is very little variation in the results despite the shortness (one year) of each dataset. This indicates that even a 22-year average will give accurate values for the change in surface CRE per 1°C warming. As in Figure 6, the only large area that shows positive feedback is the land, and the feedback is quite small.
5. Data Details
I used monthly gridded Clouds and the Earth’s Radiant Energy System (CERES) Energy Balanced and Filled Edition 4.1 data (Loeb et al. 2018). The CERES record is quite stable (Loeb et al. 2016), which makes it an excellent record for this type of analysis. All of the CERES data used covers the 22-year period from March 2000 to February 2022.
For surface temperature, I have used the CERES surface upwelling longwave dataset, converted to temperature using the Stefan-Boltzmann equation and utilizing the MODIS emissivity dataset. For verification of the calculated CERES surface temperature data, I have compared it with the results using the Berkeley Earth gridded land/ocean data record (Rohde and Hausfather 2020). The area-weighted average difference between the two is only 0.43°C. This difference is not surprising because the Berkeley Earth dataset is a combination of air temperature over land and sea surface temperature. On the other hand, the CERES data is surface temperature everywhere. Below is the same calculation shown in Figure 5 but using the Mar 2000 – Feb 2022 Berkeley Earth Data in place of CERES data for that same period. Note that there is very little difference between this and Figure 5 above which uses CERES data.
Figure 8. As in Figure 5, but using Berkeley Earth surface temperature data in place of CERES data.
6. Final Thoughts
As mentioned above, the cloud radiative effect is only one of the ways that the clouds affect the surface temperature. In addition, thunderstorms cool the surface by means of:
• Increased surface albedo over the ocean due to the white surface foam, spume (foam driven aloft by the wind), and spray. Increased cloud albedo due to the vertical extent of thunderstorm towers.
• A thunderstorm operates on the same refrigeration cycle as a household refrigerator or air conditioner. It evaporates a working fluid (in this case water) in the area to be cooled. It moves the resulting vapor to a separate physical location (the thunderstorm cloud base) where the working fluid is condensed and then returned to the area to be cooled, in the form of cold rain. This natural refrigeration-cycle heat engine greatly cools the surface quite independently of any radiation considerations.
• There is increased evaporative cooling due to the thunderstorm-generated winds at the base, as well as from the provision of dry air to the surface.
• A large thunderstorm typically generates on the order of 20,000 tonnes of rainfall over its existence. This means it is moving on the order of 40 terajoules of energy from the surface to high up in the troposphere. There, because it is above most greenhouse gases, it is much freer to radiate to space.
• Increased evaporative cooling from the increase in surface area due to the creation of millions of spray droplets.
• Increased radiation to space due to the lack of water vapor in the dry descending air between the thunderstorms.
Tropical thermally driven thunderstorms increase with increasing temperatures. As a result, the cloud radiative cooling (CRE) is enhanced by increased thunderstorm production, and the CRE cooling estimates represent a minimum value.
Acknowledgments.
All of this work is my own. However, I owe immense thanks to all of the outstanding scientists who have preceded me. I have no conflicts of interest.
Data Availability Statement.
The underlying CERES EBAF 4.1 data is NASA/LARC/SD/ASDC, 2022. CERES Energy Balanced and Filled (EBAF) TOA and Surface Monthly means data in netCDF Edition 4.1., accessed 11 December 2022, https://ceres.larc.nasa.gov/data/#energy-balanced-and-filled-ebaf.
The underlying Berkeley Earth data is Berkeley Earth, 2022, Monthly Land + Ocean Average Temperature with Air Temperatures at Sea Ice, accessed 17 December 2022, https://berkeley-earth-temperature.s3.us-west-1.amazonaws.com/Global/Gridded/Land_and_Ocean_LatLong1.nc
REFERENCES
Boucher, O. et al., 2013: Clouds and aerosols, Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (Cambridge University Press, Cambridge, UK, 2013), pp. 571–657.
Ceppi, P, F. Brient, M. D. Zelinka, D. L. Hartmann, 2017: Cloud feedback mechanisms and their representation in global climate models. Wiley Interdisc. Rev. : Clim. Change 8, e465.
Gettelman, A., Sherwood, S.C., 2016: Processes Responsible for Cloud Feedback. Curr Clim Change Rep 2, 179–189. https://doi.org/10.1007/s40641-016-0052-8
Gorshkov, V.G., Sherman, S.G. & Kondratyev, K.Y., 1990: The global carbon cycle change: Le Chatelier principle in the response of biota to changing CO2 concentration in the atmosphere. Il Nuovo Cimento C 13, 801–816 https://doi.org/10.1007/BF02511997
Loeb, N. G. et al., 2018: Clouds and the Earth’s Radiant Energy System (CERES) Energy Balanced and Filled (EBAF) Top-of-Atmosphere (TOA) Edition-4.0 data product. J. Clim. 31, 895–918.
Loeb, N., N. Manalo-Smith, W. Su, M. Shankar, S. Thomas, 2016: CERES top-of-atmosphere Earth radiation budget climate data record: Accounting for in-orbit changes in instrument calibration. Rem. Sens. 8, 182.
Ramanathan, V., & Collins, W. (1991). Thermodynamic regulation of ocean warming by cirrus clouds deduced from observations of the 1987 El Niño. Nature, 351(6321), 27–32. doi:10.1038/351027a0 https://sci-hub.se/10.1038/351027a0
Rohde, R. A. and Hausfather, Z., 2020: The Berkeley Earth Land/Ocean Temperature Record, Earth Syst. Sci. Data, 12, 3469–3479, https://doi.org/10.5194/essd-12-3469-2020.
So, there it is. All comments, criticisms, and improvements gladly considered. This site provides one of the best peer-review processes on the planet.
Please remember that when you comment, you need to quote the exact words you are discussing. That way, we can all be clear about your subject.
Finally, a couple of requests.
First, I’d still like to get this sucker published. Does anyone know of a reasonably high-impact-factor journal that does NOT charge $1,546 to publish a paper?
And second, does anyone want to take this paper over and shepherd it through the review process? This method worked out very well for Craig Loehle and me. With some assistance from me, he rewrote parts of my post on extinctions entitled Where are the Corpses?, he arm-wrestled the journals, and we got it published as Historical bird and terrestrial mammal extinction rates and causes, with him as the Lead Author. So far, about 150 citations, with more each month.
Anyone interested? Any “publish or perish” folks out there not interested in perishing? Because I truly hate dealing with the journals …
My very best wishes to all, enjoy this marvelous world where we are given so little time.
w.
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Good paper.
I can’t wait to have time to read this!
On the publish or perish comment though, I am afraid it would be publish AND perish in today’s academia. The slightest heresy against the holy dogma of Climastrology will be punished without mercy.
Willis,
Very Good write-up. I have said before in these pages that (your Fig 5) should be in every modern METEO textbook. Please allow me a comment. Your Molleweide projections of the planet give one a misleading view of the planet (might be just me) with those Pacific equatorial zones looking much smaller than they are in reality. Here is what planet Earth looks like from over the Pacific.
That is definitely the view of a blue planet!
Willis : What a pleasure finding you here again ! It has felt like ages, I’ve missed you a lot. ( you were probably on vacation )
Now, I am going to read your paper two or three times over, so as not to miss anything and understand all.
¡¡¡ Un Abrazo y Gracias !!!
Abrazos at ti tambien, jovencita.
w.
Thanks Willis for another of your interesting and informative analyses of climatic behaviors,
Outside of the actual scientific considerations, do you ever get the impression that mainstream journals, forums, etc have become conditioned to immediate rejection of anything bearing the name Eschenbach?
I raise this because of my observation that “progressives” live in a state of constant anxiety, even fear.
Not anxiety or fear of the imagined existential threats they wring their hands over, but rather fear of saying or doing anything that might put them at odds with the current “progressive” groupthink narratives (which for “progressives” can result in being ‘canceled’)
They are, I believe, even more in fear of any evidence that contradicts their theories. They are examples of the principle that it is difficult for someone to understand a problem when their salary depends on not understanding it..
Willis,
I think there is a typo in the first para of Section 3. Should cite “Fig. 3” instead of “Fig. 2”
I think your paper shows very clearly that clouds are the “control knob” for global temperatures, not CO2 as the climatists like to claim.
On a slightly topic, but somewhat related to cloud cover, do you think the recent underwater explosion in Tonga, which released a jillion tons of water into atmosphere, has had a warming effect on the weather?
https://wattsupwiththat.com/2023/07/31/what-nasa-and-the-european-space-agency-are-admitting-but-the-media-are-failing-to-report-about-our-current-heat-wave/
So why not a cooling effect, like volcano dust?
Thanks, Johanus, fixed the typo.
As to a warming rather than a cooling effect, it’s unclear what the sign of the net result will be.
For “volcano dust” or hydrogen sulfide there’s a cooling effect because the decrease in sunlight from reflections is larger than the increase in downwelling longwave.
Whether this is true for water in the stratosphere is far from clear.
w.
Surely adding water vapour to the stratosphere will raise the effective height at which the Greenhouse gas trapped IR is finally emitted to space, and since the lapse rate is positive in the stratosphere , the higher this level is, the greater the temperature and the greater the emission to space. IE cooling of the whole earth system
Or have I misunderstood the greenhouse effect?
From what I could tell the increase in water vapor stretches from the upper Troposphere all the way into the Mesosphere. In addition, one commenter mentioned a reaction with ozone. This could reduce UV interaction in the Stratosphere allowing more of that energy to reach the surface.
Willis, what about water vapor that condenses miles above the surface. Because it is above much of the CO2 and almost all of the water vapor, this radiation has a much easier path to space than does radiation that is generated near the surface.
Or is this already included in one of your other categories.
The movement of energy to high in the atmosphere is definitely a factor. I have to assume, however, that this is already included in the CRE calculations.
w.
I realised after reading for a while that I wasn’t even sure exactly what CRE is. Going to the NASA pages, their definition left me not a whole lot wiser, only more aware of the multifactorial complexities.
A few words to explain what it is might have been beneficial at the beginning of the article.
Thanks. I’ve added a short explanation. See the start to Section 3.
w.
Willis. You basically show that observations tell us that the feedback on clouds is negative. Since all CMIP6 models assume a positive feedback you show that they are all wrong, not to say rubbish. You implicitly demonstrate that all the IPCC models are wrong and because of that you will not be able to get it into any publication with ‘climate’ in its title. Don’t bother with those; you would enter a revolving door system of reviewers who will regurgitate the same spurious objections ad nauseam (I speak from experience).
However, this a paper dealing with big data. There are a number of publications on that subject who could be very interested in your methods and results. Google on ‘Journal Data Science’ or ibid ‘Big Data’.
Exactly. Also I would suggest a crowdfund campaign for the amount necessary to publish – it would be a worthwhile cause and not a huge amount among people asking for a couple of grand to pay for a honeymoon or somesuch. This paper needs to be published, to reach a wider audience and maybe change a few minds.
I agree that crowd funding would be effective – I would certainly chip in – and from “They wrote back and said ok, changes helped, and oh, by the way … it’ll cost you $1,546 to get it published” I don’t see why Willis should be so negative on the prospects of publication in that journal.
I confess I have yet to read this paper, so that is just an initial thought.
“In a far-too-loud voice, I uttered various speculations regarding the ancestry, sexual habits, and personal hygiene of the Owners, Editors, and Reviewers. I fear I went so far as to encourage them to engage in auto-fornication … for all of which I’m truly sorry.”
A short-fused sailor? Speaking from experience Willis, sometimes we are our own worst enemy.
Back to the science… How did cloud cover fall while the temperature increased? Wouldn’t we expect clouds to increase with increasing temperature?
http://climate4you.com/images/CloudCover_and_MSU%20UAH%20GlobalMonthlyTempSince1979%20With37monthRunningAverage%20With201505Reference.gif
“A short-fused sailor” … is there another type?
Bob Weber:
“How did cloud cover fall when temperatures increased?”
To form a cloud there needs to be moisture nucleation sites. If there are fewer nucleation sites, temperatures can (and will) rise without cloud formation.
This is the mechanism which leads to Atmospheric Rivers, they are always preceded by a drought, where the air is very dry..
I think you’d probably have to factor in Relative Humidity as well – the water vapour would condense around the particulates/nucleation sites which would then lower the RH of the air making it more difficult for clouds to continue to form. I think.
Richard Page:
The problem is fewer moisture nucleation sites. But if there were condensation about a site, it would increase the RH, causing more clouds to form.
There are always nucleation sites in the atmosphere to form clouds. Somewhere before the lapse rate hits -55 at Top of Troposphere, it is cold enough for ice crystals to form whether there is a nucleation site or not. Then, it is impossible to stop ice crystals from high altitudes falling and becoming nucleation sites, which starts a cascade of available nucleation sites by the time you get to cumulus cloud levels.
DMacKenzie.
Your explanation cannot be correct. It implies that there will always be clouds. However, for example, heat domes are characterized as having clear, cloudless skies, and a lack of precipitation.
Wouldn’t we expect clouds to increase with increasing temperature?
Not if it is the absolute humidity that is preserved. The idea of an increased vapour load with increasing temperature assumes that the relative humidity is a conserved atmospheric quantity. There is no observational evidence for that nor any physical principle that suggests such should be the case.
Skies above tropical ocean can be totally devoid of clouds.
How about correlating the Svensmark Cloud Mystery (cosmic ray, solar cycle, atmospheric ionization, global mean cloud cover) hypothesis with all this? Water droplet nucleation is not solely reliant on particlulate matter nor merely saturation level, temperature and pressure. Just a reminder that the entire climate system is essentially electromagnetic and fluid dynamics scales down all the way to the quantum level.
Ptor, I’ve looked hard for evidence supporting Svensmark’s theory and have found none. See inter alia here, here, here, and here.
w.
Thanks for that.
Willis – I can’t help you with your paper, but I’d be willing to chip in a few bucks to help you get it published. Just start a GoFundMe if that’s what it’s called.
I would support that, but I suspect that if the required amount was raised some other impediment would appear.
After posting this, I tried to add under the “edit” link
“but I suspect that if the required amount was raised some other impediment would appear”
This edit was refused and I was rebuked for “posting too fast”. What is that all about?
There has been something wrong with the edit feature for about a week now.
Best guess is that a WordPress update broke it.
Yep, have run into the same thing myself. It resulted in a less-than-coherent comment.
No clue, but I fixed it for you.
w.
Tks.
WE, nice paper. Not much to contribute.
A comment on publication process after having done some quick research. All the open access journals (I checked about 15 climate related majors) have a ‘article publication charge’ (apc). J. Climate is listed as $2400, so they gave you a discount meaning they like the rewritten paper.
Suggestion. Ask AW whether that is something Heartland might fund, since it isn’t big for them unlike for you, and because your paper could be used by Heartland once it appears. For example, all the IPCC climate models have significant positive cloud feedback (albeit with admitted uncertainties since clouds are parameterized), which you show isn’t observationally correct. Which means the other IPCC CMIP model results must somehow be wrong also. Something Heartland could use.
It’s a reasonable suggestion, Rud, if the world were still sometimes reasonable. But you will have to grant me that as soon as that would happen, the paper would be forever-after declared funded by oil interests!
I’ll bet we could raise the fee in about an hour or less. I’m happy to chip in $100.
Thanks, Rud, but I can’t do that or I’ll be “Heartland funded climate denier Willis” … never made a dime off the climate, gotta keep it that way.
w.
I know one paper on which I was a co-author that had a publishing fee of $10K, plus a hard-sell to place a much more expensive corporate advert elsewhere in the associated magazine. Some Journals are just money making tools, with information content being “the best they can get paid for”. So their requested fee doesn’t seem entirely outlandish, in fact, it’s low enough that they must have considered that it would increase their readership….
Story tip?
….
DM,
The ownership of major global scientific journals as broadly described is a concern. Past WUWT articles have touched on it, but an in-depth study is needed. Someone younger and enthusiastic might step up? Geoff S
You describe Fig 1 as
Here is the maximum temperature range over a 22-year period for each 1° latitude by 1° longitude gridcell.
Walk me through that, because although I can sense some degree of correlation with the idea that temperatures vary much more in say Verkhoyansk compared with Singapore, the range in Verkhoyansk is more like over 100K between max and min, and even the range in Singapore is rather more than 2K. The description is too much in shorthand for me to guess what calculations you performed on the data.
Willus,
I think I finally figured it out. A clearer description would be
Here is the range of monthly average temperatures (highest monthly average less lowest monthly average) from 22 years of CERES data (Which data exactly?) refactored to temperatures (How?) for each 1° latitude by 1° longitude gridcell.
You should request the fee to be waived on account of non-institutional publication, preferably at the time of submission. Some journals do that when the authors can’t pay from their grant money. If they say no, you won’t waste much time with that journal. Perhaps you can still try it with the Journal of Climate if you haven’t been too nasty to the editor. It is not like journals can’t afford that.
Thanks for the excellent suggestions, Javier. I wasn’t nasty to anyone, I prefer not to burn bridges if I don’t have to …
w.
I’ll be happy to pay for ya if it helps to get it published Willis. Just let me know. It’s not that I’m loaded, but I fully get your logic and I consider to results very very relevant. This must end up in a journal.
Very interesting.
I think the problem I have, is clouds cause different temperature reactions in different regions for different regions … i.e. its chaotic.
I’m about 100 miles inland from the Pacific Coast, as you were in your youth. Clouds can be generated over the ocean, then blown (transported) inland. On an inland, clear hot summer day, transported marine clouds cause cooling, but if clouds are transported in the early evening, they cause heat retention and prevent overnight cooling.
When looking at the 1910 max surface temperature of 134F in Death Valley, California, I surmise this is what happened. Looking at the data, previous overnight lows were in the 90s, daily highs in the 120s. But The night before the max temperature, the overnight low was 117F … it never cooled down, I surmise because of a transported cloud layer. The next day, it wasn’t a big leap to go from 117F to 134F.
Lil-Mike,
Richard Willoughby is reporting in WUWT and Bomwatch about global energy transport, some functions of water and effects on atmospheric temperatures (with no CO2 promotion). In my reading, the process of evaporated sea water moving over land and raining out is one of the key ways to explain differences in T over land and sea. Willis does not develop this because he is using gross CERES numbers. However, such mechanisms have explanatory power when the Willis observations move into greater detail.
This Willis work has significant importance. It needs to be taken deeper and deeper. Willoughby’s work is about relevant mechanisms that are logical but on different concepts to much Establishment stuff. Recommended. Geoff S
Good stuff, Willis, as we have learned to expect from you. It’s new, it’s important, and its conclusions really need to be published. Even if they’re ignored by alarmists and the modelling community, who might have to add a hundred thousand lines of code to replace cloud parameterization.
I appreciate that your text may have been a bit less lengthy and explicit than usual to keep the size down but there’s a couple of points I couldn’t quite grasp.
One question: “short-term change in surface CRE” — what’s the range of time spans that you refer to as “short term”?
Second question: I may be having a slow-brain day (not unusual in my post-covid state) but I couldn’t quite grasp your methodology for the second approach to long-term relation between CRE and temperature. What I THINK you might have done is use the difference between the average of all 81 gridcells in a 9° × 9° block and the “point” values of the central gridcell. If that was your method, it could be spelled out at slightly greater length than you did in the text. If not, then it could also be spelled out in a bit more detail.
I don’t think I’ve ever seen anyone else use scatterplots the way you use them. They are a great way of presenting vast amounts of data that lead unquestionably to your conclusions. IMHO, that type of presentation should be immortalized and formally referred to as an “Eschenbach Plot”.
Smart Rock September 1, 2023 12:13 pm
The 22-year span of the CERES dataset.
Here’s how I described it:
The second method looks only at the average values of the gridcells in the area immediately around each gridcell. Consider a gridcell in the ocean as an example. Nearby gridcells to the north, south, east, and west of that chosen gridcell will have different long-time average values for temperature and CRE. So we can determine the long-term effect by looking at the local relationship between average temperature and average CRE. For each gridcell, I have used a box that is 9° latitude by 9° longitude, centered on the chosen gridcell, and I’ve used a linear regression of that block of data to determine the value for the center gridcell.
Each gridcell is in the center of a 9°x9° block of gridcells.
This gives me 81 temperature values and a corresponding 81 CRE values. I do a linear regression of the 81 CRE values as a function of the 81 temperature values. The resulting slope shows the change in CRE corresponding to a 1° change in temperature.
I’ve included this in the paper.
Not a chance. I used to think I came up with it, but I found it was used in Ramanathan’s 1991 paper linked to above on the “super greenhouse effect”. My refinements are the use of far more data points, and more importantly, the use of translucent dots to reveal underlying patterns as variations in overall density.
w.
Willis:
I do realize it is common in climate terminology to divide radiation into “short” and “long”, but these are very qualitative terms that don’t do anything to simplify the complexity of solar radiation in the atmosphere. To be unambiguous, my recommendation is to specify the wavelength bands to which you are referring.
Another point that isn’t much appreciated is that clouds can also scatter radiation, just like aerosols and air molecules (Rayleigh scattering). This is especially true of high-altitude cirrus clouds that have lots of ice crystals.
As for a journal, one might be the Journal of Atmospheric and Oceanic Technology.
Actually, ‘long and ‘short’ divide the IR realm very nicely into two parts. The ‘short waves’ (i.e. λ<4μ) describe solar radiation exclusively and ‘long waves’ (λ>4μ) uniquely describe ‘earthshine‘. Can’t get any less complex.
I do realize this, but the average reader might not. And there really is no sharp cutoff of solar radiation, while there is little irradiance by 4um, the decay from the peak at 0.5um is gradual. One could just as easily assign a cutoff ~2-2.4um, which is the window transmittance cutoff of many hemispherical pyranometers used to measure solar irradiance.
And after the extraterrestrial irradiance enters the atmosphere, it becomes very complex.
| “short” and “long”… are very qualitative terms that don’t do anything to simplify
| the complexity of solar radiation in the atmosphere.
Seems like you want this to be complicated. The terms ‘short’ and ‘long’ do simplify the analysis of solar vs terrestrial IR flux in the atmosphere, in the sense that if we pick any IR wavelength less than 4 microns (short) then that flux is virtually all solar. But if we pick IR wavelengths above 4 microns then we are surely looking at terrestrial flux (‘earthshine’). So setting a decision threshold at 4 microns, the roll-off of both distributions is such that it optimally bifurcates the IR problem space into two virtually independent spaces.
I agree. WE says the second is thermal (longwave) radiation. What is his definition of “thermal radiation”?
WE is a word smith and being unambiguous should be his standard.
mkelly, sorry, but you don’t get to tell me what my “standard” should be. Piss off.
And if you and karlomonte don’t know the difference between longwave and shortwave radiation, go back to climate grade school. I’m writing for scientists, not children.
FWIW, in my mind at least “shortwave radiation” is radiation emitted by the sun, and “longwave radiation” is radiation emitted by the earth and the atmosphere … but you knew that, you’re just standing on tiptoe to try to bite my ankles.
And yes, I’m crabby today. Why do you ask?
But heck, since it appears you don’t know, here’s the IPCC Glossary on the subject. Let’s see if my understanding was correct.
Gosh … it’s just what I said. How about “longwave”? Here’s the IPCC glossary:
Gosh … it’s just what I said.
mkelly and karlomonte, this is truly climate grade school stuff. If y’all have any other terms you don’t understand, go to the IPCC glossary, look them up, and don’t bother me.
w.
“Oh Lord, please don’t let me be misunderstood.”
The Animals
When I first read this, I instantly heard that Animals track in my head.
#metoo
right- such an awesome song along many others from the Animals
me, too. 🙂
Me too. It’s a definite trend!
Nice paper Willis.
“Using data from satellite observations, here I develop two independent methods to estimate how the clouds in different areas respond to a surface temperature increase.”
Take out “here”. Not needed.
” In Fig. 3 we see that the clouds warm the poles and the deserts, and cool everywhere else.”
Deserts and the poles don’t have a lot of H2O in their atmospheres. Poles because it is cold. Deserts lack water. I don’t intend to say you are incorrect, but more explanation might be needed.
_____________________
Everything is pretty well explained. It doesn’t have extrapolations that require mathematics to explain. IOW, it only deals with what has happened, not what you think will happen some far off time in the future. The nice thing about that is that people dealing in the future will need to explain what changes to permanently disturb what you have shown.
Bravo.
Jim Gorman September 1, 2023 12:56 pm
Nice paper Willis.
Take out “here”. Not needed.
Thanks. Fixed.
Then, I’d said…
You replied
Deserts and the poles don’t have a lot of H2O in their atmospheres. Poles because it is cold. Deserts lack water. I don’t intend to say you are incorrect, but more explanation might be needed.
True indeed, and worth further investigation. But I think I’ll let it stand. Looking at it from this distance, it’s just a rough description of the Figure, and peripheral to the main argument. I strive for single-focus in my posts. I have to fight my urge to get side-tractored.
Best regards,
w.
Michio Kaku has a new book – Quantum Supremacy – in which he points out that models of complex things like cancer cells and atomic nuclei cannot be modeled using digital computers but quantum computers may do the job. Climate may be too complicated for digital computers too – hence no models really work now.
See my while ago post here ‘The Trouble with Climate Models’. On scales where the physics can be reasonably well modeled (2-4km Tstorm scale grid cells) the CFL constraint on numerical solutions to partial differential equations means such are 6-7 orders of magnitude computationally intractable. Hence tuned parameterization at computationally tractable grid cell sizes to best hindcast, dragging in the attribution problem. (BTW, computationally tractable today means a ~200 x200 km at equator grid cell model that takes about 2 months of continuous supercomputer time to get a single run from now to 2100.)
Kaku is hypothesizing that quantum computing can overcome the CFL constraint. Maybe. Some day. But I doubt it having read up on qubits and quantum computing. Theoretically interesting. Devilishly hard to realize at any meaningful scale.
Sort of like controlled fusion power here on Earth. “A beautiful idea. We put the Sun in a box. The only problem is, we do not know how to make the box.” Neither NIF nor ITER solve the fusion box problem. See essay Going Nuclear in ebook Blowing Smoke for fun illustrated details.
Kaku points out that digital computers only make one calculation at a time….very fast, but still one at a time. Digital computers were vacuum tubed things the size of rooms 80 years ago….if quantum computers only proceed at 1/2 the advancement of digital, the results will still be spectacular. Fusion? Who needs it? Extreme temps are not needed to produce steam for electricity…Thorium Liquid Salts Cooled Reactors can supply the world with cheap safe abundant electricity.
Even with quantum computers, I’d presume much more real, high quality data is needed, no? Data from now and data from the past. Not just data but better understanding of all the variables and their relationships – that is, better models! Even then, much testing will be needed- then decades if not centuries to see what really happens. So I don’t have much confidence that quantum computers will be all that constructive in the climate non debate.
Until a “climate” model can hindcast the MWP AND the LIA, they are crap.
Excellent, Willis!
I expect Figure 5 will be shared widely once published. Very persuasive visually from the data. I suggest adding a note to this graphic that explains your conversion of CERES surface upwelling LW to temperature. Otherwise some might immediately object, “But the CERES data does not give a temperature!”
Interesting theory Willis
I have one comment.
You say: “this amazing longer-term stability cannot be from thermal inertia, given the far larger monthly intra-annual swings. This overall steady-state condition argues strongly for the existence of natural thermoregulatory phenomena opposing any change in the overall steady-state temperature.”
An alternative explanation is that, although the air has low thermal inertia, we know that the ocean and the glaciers have gigantic thermal inertia. That can explain that we have a large short term swing in air temperatures, but the ocean and glaciers hold the average temperature steady over much longer time periods.
This explanation is also compliant with the ice-ages and the occasional heat spikes we have seen in the last 100 millions of year. A strong “natural thermoregulatory phenomena opposing any change” seems not to have been working in those times. That seem to be difficult to explain, as one would expect that such a phenomena would exist forever.
If, on the other hand, if the temperature is held stable in one century by a large thermal inertia, that body of inertia would eventually change if it were forced in one direction over several centuries.
That may have happened in those cold and warm periods.
/Jan
Very insightful. I would add only two thoughts:
Yes, thermal inertia contributes to ‘short term’ stability around a set point, but the set point itself is subject to orbital mechanics (medium term) and plate tectonics (long term).
Thanks, Rud. However, I’m using surface temperature, not atmospheric.
w.
By that, do you mean the ground IR temperatures, as retrieved by satellites, or the 2m weather station temperatures?
Jan Kjetil Andersen September 1, 2023 1:29 pm
Thanks, Jan. I’m not seeing it. The surface monthly temperature swings, even ocean surface, are 9°C or more. Daily it’s even greater. Given that the temperatures are set by things as ephemeral and variable as winds, currents, and clouds, why should it return to where it started year after year?
Bi-stable or multi-stable chaotic regimes are certainly possible in the climate, whether it is thermally regulated or not.
I’m not seeing, however, how a bi-stable thermal inertia would cause ice ages …
You speak as though “thermal inertia” is a force driving a return to the status quo ante regardless of the incoming radiation, cloud amounts and types, and all the other variables. My question remains: why, over the entire 20th century, did the temperature only vary by 0.3%?
I can see, however, that I need to include another theoretical argument, that of the Constructal Law. Thanks for highlighting that lack.
Regards,
w.
Jan, among other evidence for active thermoregulation is the fact that the average albedo of the northern and southern hemispheres is virtually identical. This is despite wildly varying ocean/land ratios. The SH is 82% ocean, while the NH is only 62% ocean. This also means that “thermal inertia” can’t explain the symmetry, as the thermal inertia of the two hemispheres is quite different.
w.
Jan,
In the case of the estimated average temperature of the earth over the last million years or so, the striking feature to me is the hard limit of maximum temperatures in the interglacial periods. This seems best explained by the exponential increase in saturation vapor pressure of water with respect to temperature. A meteorological example is the 26ºC sea surface temperature needed to maintain a hurricane.
Erik,
That 26C hurricane link is troubling because it is too narrow as you express it. Any section of near surface ocean of an area matching hurricane footprints has variable T with mixing, depth, local wind evaporation etc. You can’t average it to better than 1C. Does the 26C really have predictive value, or is it just a handy rule of thumb? Geoff S
JKA,
Willis used ‘phenomena’ which is plural. You seem to be using the word in the singular, so the meaning is confused. It is a common writing error but I mention it because it can have a big effect on what you mean. (Understood that English might not be your first language.). Geoff S
Willis,
Here is my suggestion:
Join a pre-publication website and upload your paper as a pre-print.
I see that Craig Loehle is on Research Gate, as you are a contributing author to Historical bird and terrestrial mammal extinction rates and causes ask Craig to send you an invitation to join Research Gate and publish your pre-print there.
Another possible site is Authorea – the Open Research Collaboration and Publishing
Since being on Authorea I have received offers to publish from the editors of various journals.
Costs and reader impact vary but you can always plead poverty as an unsupported Indepedent Researcher.
Good luck.
Thanks, Philip. I fear I don’t understand the process. I put a pre-print up on Research Gate and what … then I submit it to a journal?
A simplified explanation would be great.
w.
Willis,
I suggest that you use pre-print websites such as Research Gate etc, as a method of gaining traction for your work in academic circles and also as a way of soliciting requests for publication from journal editors.
This strategy has worked for me.
Willis,
Here is an example of the process:
Our latest peer reviewed paper published in Energy and Earth Science Vol. 6, No. 3, 2023 follows on from a direct request for submission from the editor.
Vanity publishing cost $300
“On the other hand, the CERES data is surface temperature everywhere.”
Is this strictly accurate? I thought CERES measured satellite TOA radiation data, thus including other tropospheric points?
Generally, on a first reading, I would also change some of the more personalised language and words like “amazing” and “paltry”.
michael hart September 1, 2023 2:12 pm
From the head post:
You continue.
Done, thanks.
w.
Hmm. You might want to report their fees to Academic-Accelerator, which apparently has no information on them to help other people. academic-accelerator.com/Publication-Fee/Journal-of-Climate
(I’m assuming that you were submitting to the AMS journal of the name.)
Dear Willis,
Your picture of a cumulonimbus tower reaching into the stratosphere tells 99% of the homeostasis (climate feedback) story.
Simply stated, a massive amount of energy transferred from an ocean warm pool as latent heat (potential energy) rises rapidly through the atmosphere, cools due to adiabatic processes, forms vapour and in the process loses that energy radiatively, directly to space. Eventually, the mass of water vapor contained within the tower (effectively a chimney), exceeds the capacity of the up-draft and it collapses upon itself releasing more energy as a result of the phase-change. This process short-circuits, the re-radiation / back-radiation theory which is crudely believed to represent the ‘greenhouse’ effect.
Richard Willoughby wrote a report about this process here: https://www.bomwatch.com.au/bureau-of-meteorology/ocean-surface-temperature-limit/; and also a 4-part series at WUWT (referenced here: https://wattsupwiththat.com/2021/05/29/ocean-temperature-limit-corrections-and-part-4/).
The process operates within about 15 degrees of the Equator, which is the zone where incoming top-of-atmosphere short-wave radiation maxes-out between respective solstices and equinoxes – time-points when the sun is directly over the Tropics of Cancer and Capricorn and when it traverses the Equator. The Monsoon, essentially the heat-pump, lags the sun by 4 to 6 weeks. By now (2 September) the sun is retreating south from the Tropic of Cancer, it will cross the Equator on 23 September and Australia’s tropical rainy season will start probably in early to mid- November.
The only transect study of sea surface temperature is one I published on WUWT in 2021 (https://wattsupwiththat.com/2021/08/26/great-barrier-reef-sea-surface-temperature-no-change-in-150-years/). I subsequently revised the work and submitted it for publication in Frontiers in Marine Science – Coral Reef Research in February 2022 While I was prepared to meet the publication cost of around A$3,000, an email forwarded to me showed a peer-reviewer conspired with the Journal Editor to have the paper rejected. They refused to consider an appeal.
The 250-word abstract of that paper reads:
In November 1871, astronomers from Melbourne and Sydney sailed to Cape Sidmouth near the top of Cape York to observe the total eclipse of the sun. Their observations of sea surface temperature (SST) north from Port Stephens, NSW, and on their return in December, were comparable with SST transects for those times derived from 156 Australian Institute of Marine Science (AIMS) dataloggers south from Bramble Cay in Torres Strait to Groper Island off Woolgoolga, NSW. Multiple linear regression of AIMS data with polynomial terms found average SST was constrained to 29.3oC (±0.73oC95%PI) at Latitude -13.5o between October to March. Cooling of the East Australia Current limits the distribution of Reef ecosystems southward, while cooling of the North Queensland Current maintains favorable conditions toward the equator. As AIMS data for November and December are not different to 1871 expedition data, the body of the Reef is as warm, but no warmer than it was 150-years ago. The UK Met Office Hadley Centre monthly ice and SST dataset (HadISST) was not materially different to 1871 or AIMS data along the length of the Reef in November and December, but specific comparisons found 2020 HadISST was biased-high particularly in the warmest and coolest months of February (by 1.27oC (±0.298CI95)) and August (1.78oC (±0.483)), and increasingly with distance south. As no warming trend is detectable in AIMS data and the HadISST dataset is biased-high, recent occurrences of coral bleaching must be due to factors aside from global warming, including localized warming of individual reefs.
The new study supported Richard Willoughby’s previous work and in addition, showed convincingly that during summer, sea surface temperature declines toward the equator north of Latitude -13.5 deg, and also poleward from that point along the eastern seaboard. The processes involved are different with the Monsoon operating northward and radiation, convection and conduction cooling the southward-flowing East Australian Current.
The point I’m making is that has to be mechanism operating at the surface that controls earth’s temperature and which underpins evidence of that, as shown by satellite maps and gridded datasets. Furthermore, in the process of re-writing and re-analysing the original WUWT post it cannot be ruled out that a ‘warming coefficient’ has found its way into many off-the-shelf datasets, in particular, satellite ’data’ (which is actually modeled), HadISAT SST data and sea-level data.
My experience also shows that despite COPE guidelines (Committee on Publication Ethics of which Frontiers is a member), the peer-review process is rotten to the core.
Yours sincerely,
Dr Bill Johnston
http://www.bomwatch.com.au
Bill,
I see that you are on Research Gate.
As I suggested to Willis, start your publication path there.
Thanks Philip, I’ll look into it.
Cheers,
Bill
A change in downwelling radiation has so small an effect on the earth’s energy imbalance that it is indistinguishable from random noise. This is exactly what a well-controlled system would do. It also indicates the climate sensitivity is very small and much less than one. There’s no amplification of CO2 warming; in fact, the warming is suppressed.
“There’s no amplification of CO2 warming; in fact, the warming is suppressed.”
Climate alarmists are not going to like that.
Climate Alarmists should explain to us again why we are wasting TRILLIONS of dollars trying to control CO2 warming, when Mother Nature is doing it all for us right now for free.