By Ron Barmby
I’ve looked at climate change from both sides now, and I have found common ground between proponents and skeptics of the belief that climate change is largely caused by humans. When it comes to forecasting global temperatures, distinguished experts in both camps agree a dominant variable cannot be simulated in computer models because clouds get in the way.
Among the proponents is Dr. Bjorn Stevens, a contributing author to the Intergovernmental Panel on Climate Change (IPCC) Assessment Report 5 (2014). Dr. Stevens is also director at the Max Planck Institute for Meteorology, Hamburg, Germany, and a cloud expert. In a recent interview he acknowledged the contribution of clouds to global warming is overestimated in the IPCC’s “Climate Change 2021: The Physical Science Basis.”
“Clouds are tricksters,” he said, referring to their complexity. However, he said, many scientists use oversimplified representations of clouds in modeling “as a guide because they are easier to simulate. This makes the climate models less accurate.”
On the skeptic side is Dr. Richard S. Lindzen, a former lead author for IPCC Assessment Report 3 and now a vocal critic of the IPCC. In a recent podcast the interviewer noted that Lindzen had published sufficient research papers to earn 80 PhDs. (Lindzen humbly declined the praise.)
Lindzen, professor emeritus of Atmospheric Sciences at the Massachusetts Institute of Technology, points out that IPCC models rely on the assumption that water vapor and clouds amplify the greenhouse gas effects of CO2 in order to achieve forecasts of catastrophic global warming. The IPCC theory is that a warmer atmosphere will have a higher content of water vapor – itself is a greenhouse gas – that adds to the warming caused by CO2. Without this amplifying “positive feedback” effect, the models are still wrong for many reasons, but they no longer project “catastrophic” warming.
Dr. Stevens, who is on record stating that global warming is a “huge problem,” agrees that increased clouds do not amplify global warming: “Water-rich low clouds over the tropical ocean have the greatest cooling effect and low-water ice clouds at high altitudes have the strongest warming effect. Overall, the cooling effect is greater.” That’s called “negative feedback.”
Dr. Lindzen argues that global average temperature is controlled by the polar regions. The temperature at the tropics remains relatively constant over long periods of time while the polar regions have significant variations. In other words, a small change in global average temperature is the result of a big change in polar temperatures. The stability of tropical temperatures indicates that increased clouds provide negative feedback in times of global warming. Rather than exacerbating the global warming effect of CO2, clouds reduce it.
Lindzen proposes the mechanism by which greater negative feedback is produced: High altitude cirrus clouds (Dr. Stevens’ low-water high altitude ice clouds that cause warming) control heat emissions to space. As the air below these clouds warms, the cirrus clouds dissipate and allow more energy to radiate into space. He calls this the Iris Effect.
Nature is dominated by negative feedbacks, not positive ones. French chemist Henry Louis Le Chatelier expresses this in Le Chatelier’s principle: A system in dynamic equilibrium (in this case the climate) is disturbed by changing the conditions (in this case the concentration of CO2), then the equilibrium moves to counteract the change. Negative feedbacks occur because when a variable changes, other variables react in ways that offset the shift.
We can’t model clouds. The IPCC admits this. Nonetheless, its forecasting models rely on assumptions that clouds amplify CO2 warming, without which its temperature forecasts are benign (that’s strike one).
IPCC forecasts based on cloud models have been called out by eminent cloud experts on both sides—proponents and skeptics of the notion of human-caused climate change. A recognized cloud expert and IPCC author (Dr. Stevens) states that clouds cause cooling overall, not warming (strike two).
And, finally, the observed stability of tropical temperatures argues that increased clouds provide even greater negative feedback to CO2, and a cloud expert who has done enough research for 80 Ph.D.s (Dr. Lindzen) has an idea how that happens (strike three).
Clouds do not amplify global warming; they promote global cooling. That’s enough to convince this climate heretic that IPCC forecasts are no “red light” for humanity and to reject the insane drive to eliminate CO2 from our economies.
IPCC forecasters overstate warming because they still somehow really don’t understand clouds at all.
This commentary was first published at Real Clear Markets, April 7, 2023, and can be accessed here.
Ron Barmby, Professional Engineer with a master’s degree majoring in geosciences, had a 40-year career in the energy industry that covered 40 countries and five continents. He is author of “Sunlight on Climate Change: A Heretic’s Guide to Global Climate Hysteria” and is a proud member of the CO2 Coalition, Arlington, Virginia.
Tags: clouds, Richard Lindzen, IPCC, Ron Barmby, Intergovernmental Panel on Climate Change, Bjorn Stevens, Iris Effect, Ronald Barmby
That old tune by Joni Mitchell comes to mind. We really don’t know clouds at all.
But now they only block the sun
They rain and snow on everyone
So many things I would have done
But clouds got in my way
I’ve looked at clouds from both sides now
From up and down, and still somehow
It’s cloud illusions I recall
I really don’t know clouds at all
https://jonimitchell.com/music/song.cfm?id=83
Smarter than Neil DeGrasse Tyson.
I don’t like him because he’s emphatic that no UFOs have come to Earth from another planet. He may be right but his arguments against UFOs, now called UAPs isn’t very convincing. Having seen one myself I leave open any possibility.
If I were to say NDT is a DEI science spokesman, would you cancel me?
Clouds are just convection made visible.
They really don’t know convection at all.
Yes clouds cause warming and they do it, in conjunction with high-speed electronic thermometers.
Yet it is actually cooling
You’ve seen this picture before – it’s the data-log from an electronic sensor, behind 3 separate solar shields, reading air temperature at 20 second intervals.
In my garden in South Norfolk on the border with Cambridgeshire
Because the sun heats the air directly, what that hedgehog graph shows you is clouds passing overhead.
Temp drops when a cloud comes and rises again when the cloud passes by.
You can almost count them going overhead.
This explain Ma Marohasy’s concern about electronic probes recording unusually high temps vs what mercury thermometers record.
For whatever reason, it seems ‘sensible’ that the more data points you get when recording the temperature of any given day, the better your calculated average will be than what a standard Max-Min thermometer would record.
I certainly thought that BUT – I need pictures so I started taking my own pictures. as seen.
From my dataloggers and from data downloaded off Wunderground it is truly amazing how accurate the Max Min data really is when used as ‘an average temperature’
I’ve checked loads of times in Excel:
And 99 times out of 100, the two numbers will be same distance apart as the resolution of the data loggers = less than 0.1°C
You really do have to go there, do that and buy the T-shirt. It’s amazing
Now we get the the solid state electronic probe and we see its output.
The Computer will see those spikes caused by passing clouds and sure as eggs are eggs, one of them is gonna be recorded as that day’s maximum.
When ‘just eyeballing’ the graph says that the average temp was somewhere where that hedgehog had been given a good haircut.
How many of Climate Science’s sacred cows does that little picture slay..here’s 3
Re : “Temp drops when a cloud comes and rises again when the cloud passes by.
You can almost count them going overhead”
Exactly right.
Some years ago I was burning some cumbungi (https://vro.agriculture.vic.gov.au/dpi/vro/vrosite.nsf/pages/sip_common_cumbungi) that had overtaken the creek running through a lower farm paddock. The cumbungi had dried off and was quite flammable and burnt fiercely when first lit up.
It was generally a warm sunny day but with patches of cloud passing overhead. As each cloud passed overhead the flames died right down, as the first cloud passed I thought my attempt to burn it all had failed, but then as it had passed the flames took off again fiercely as ever. It was an interesting exercise watching the impact the direct sunlight and the clouds each had on the fire being repeated as each cloud passed.
Your temperature profile looks much like mine, a sinusoid during the day and an exponential/polynomial at night.
You don’t find the average of a sinusoid by adding serial data and dividing by the number of data points. You have to integrate the curve, e.g. 0 to pi/2, and divide the total by pi/2. From 0 to pi the average value is .637 * Tmax.
What you have done is calculated a mid-range value – it’s no wonder it comes out the same as (Tmax + Tmin)/2. If the profile was a pure sinusoid and you shift the temps to a zero baseline you would get 0deg as the mid-range. E.g. Tmax = 20 and Tmin = -20.
What is the RMS value of a sine wave for the positive part of the curve?
You realize there are not just days, but also nights???
So why not make us a similar pretty picture? Would be interesting to see what clouds that counts…
“IPCC forecasters overstate warming because they still somehow really don’t understand clouds at all.”
This is purposeful. At least 15 peer reviewed papers have documented a reduction of clouds during the modern warm period. The average increase in solar energy reaching the surface found was more than twice the human forcing. That data destroys the lie that humans are mostly responsible for the modest warming we have seen. This is why they ignore it.
What causes the condensate to form, or to not form?
“What causes the condensate to form, or to not form?”
Are you referring to the ridiculous water vapor would collapse argument?
The sun is the primary cause of water vapor through evaporation. Water vapor can also sublimate from frozen ice.
I have no idea what that is. I’m interested in this data which destroys the notion of human impacts upon cloud condensation.
Sorry, it came off as if you were supporting human caused condensation. I’ve had many discussions over the years with people who claim non-condensing CO2 is responsible for water vapor being present in the atmosphere. The likely source for their misunderstandings here-
What is the greenhouse effect? – Climate Change: Vital Signs of the Planet (nasa.gov)
“Remove carbon dioxide, and the terrestrial greenhouse effect would collapse.”
JCM,
In the “Global Cooling” times of the 50’s through the early 80’s, the additional cloudiness was most likely caused by the sulphur compounds and coal soot put out the smokestacks of every power plant and manufacturing plant. By the early 80s, the scrubbers that were added to the stacks had removed most of that and greatly reduced the number of condensation points in the atmosphere. Thus global cloudiness declined and temperatures increased.
To get clouds, you need water vapor, the right temperature and pressure, and a particle for the water to stick to when it condenses. Without the particles condensation occurs at much lower temperatures than otherwise would get, and would have more of a tendency to revaporize, thus ending the cloud.
Part of the reason they are so hard to model is you have to predict those dust storms in Africa and how much salt a tropical storm shoots out of the ocean into the upper troposphere. Figuring out the density of nucleation sites is one of those wicked problems that the GCMs will never get close to as they happen at the molecule level, not the 10km square level (or more) of the models.
Hope this helps
Additionally, humanity has desiccated 5 billion hectares of the terrestrial landscape, thereby starving the atmosphere of biotic hygroscopic condensation nuclei in the form of microbes and fungi. These have now been replaced with fine clay dusts which only form haze microdrops, not cloud.
15 or more links would be appreciated.
Global average temperature is not a physical quantity and cannot represent “the climate”. But it is all these models can output.
Because the models are successive iterations, small uncertainties accumulate during each iteration step and quickly drive the results to zero quantitative value.
The condensing gas H20, alone, can cause no net warming or cooling. it can only “cool” hot places, and “hotten” cold places.
That’s a bit like saying that refrigerant by itself cannot heat or cool anything. And yet it is a vital part of air conditioning.
Strong sun over oceans creates massive water vapour which convects upwards carrying heat to the upper atmosphere, well above most of the CO2, and where it can happily radiate to space. And turn to ice and come down as cold ice, hail or rain. Meanwhile the condensed clouds shield the sea from the direct sun. It is a natural analogue of an air conditioning unit.
Higher latitudes are far more complex, as they rely on heat transfer from the tropics to warm them and that is very geography affected.
in this way, it has cooled a hot place (surface), and hottened a cold place (at altitude) in the vertical plane.
additionally, it is a transport vessel to higher latitudes, in this way it cools hot equatorial places, and hottens higher latitudes.
In both circumstances, whether at altitude or at latitude, the transmittance of heat to space in the form of radiative flux is optimized.
As Dr. Watson would surely have said at some time to Dr. Stevens –
Here’s a thought experiment. Take a planet that is 75% covered in water, the remainder mixed land, and let it settle to a realistic equilibrium, changing all the time but reverting to the mean.
Now spill enough light oil and/or surfactant on the water to cover 10% of the water surface.
What will happen to the sea surface temperature?
JF
Nothing. There will be a combination of photo-oxidation, emulsifying and dispersion that break down, mix and spread the remnants of the surface oil within a few days.
When CO2 increases you get more IR absorbed at the surface. This leads to increased evaporation which will naturally speed up convection and provide more H2O. This alone is a cooling process. If you also get additional clouds the cooling is even more significant.
From an engineering standpoint, the entire reason for the atmospheric window is to supply more energy to counter this cooling effect from well mixed GHGs. Nature is a phenomenal engineering feat.
Richard, yes to your increased evaporation and additional clouds, but philosophically…..
The atmospheric window shouldn’t be ascribed as having a “reason for being”. It simply IS. The life on the surface has adapted, over millions of years, to it’s characteristics. So yes, nature, being that adaptation, is a phenomenal engineering feat.
Of course, it could be coincidence the window exists exactly where it needs to be to compensate for CO2’s cooling effect. Personally, I’m not a big believer in coincidence when it aligns perfectly with what a good engineer would do.
“Dr. Stevens, who is on record stating that global warming is a “huge problem”
What’s so huge about it? He’s “stating it”???
The “cloud problem” is a lot more profound and it starts with an ill-fated attribution. The cloud radiative effect (CRE, or GHE of clouds) is 30W/m2 net, 75W/m2 gross. Their albedo effect is about 50W/m2. The not so trivial question now is, what is larger? The CRE or the albedo effect???
Obviously that will depend on whether you take the net or the gross CRE. Which one is correct? The answer is, we do not know. Epistemologically there is no way to tell.
https://greenhousedefect.com/the-beast-under-the-bed-part-1
The CRE is a very poor way to conceptualize the processes. That “net downward radiation” effect attributed to clouds is actually the result of the closed radiative window in saturated conditions.
The upward surface radiative flux is diminished by closing the window, and air resembling 100% humidity exhibits no vapor pressure deficit, necessitates that the surface budget is balanced by surplus sensible heat into the boundary layer. There is no other option.
The CRE is not about “downward radiation”, but about the reduction of emissions TOA.
there can be no net reduction of emissions TOA due to condensation.
From Hartmann’s Global Physical Climatology textbook…note that Albedo change of cloud cover to ocean is going to be above .3 and clouds will be low, and negative means cooling at ground level…note it says “real clouds” but is actually “calculated”…..so lots of cooling is associated with the types of cloud routinely visible to us, that is generated every day by evaporation, or blows in on weather fronts.
Finally, someone says the truth. It is not possible to model clouds from first principles. Clouds are a condensation phenomenon, and condensation depends on many factors that are inherently chaotic, and random. So, the models use assumptions and simplification to arrive at their preferred conclusion.
Engineers who have to deal with condensation either do a lot of experimenting at different scales, or build on existing experience and data , and try not to outrun their database. They also add large amounts of margin into their designs to account for the uncertainty.
But climate modelers cannot do any these things, so the results they get from their calculations simply reinforce their intuition going in.
It is ceratinly possible to model these things. Just not with any digital computer we have in human timescales.
I’d replace “intuition” with “preconceived conclusions.”
The biggest thing is oceans to me. Pretty much it all can be explained by oceans. About 12k years ago the oceans changed and brought warmth to the poles through the push pull of cold waters going to the bottom of the ocean pulling in warm waters, anything by the oceans warmed quickly. Since then the planet has cooled in cycles. It took a few thousands of years to melt the giant ice cubes on the continents. Today’s Atlantification of 2 degree warmer ocean temperatures are making the Arctic more saline when more glaciers are melting. We are going to get colder. It was far warmer previously and we are in a cooling cycle.
Antartica: https://www.nature.com/articles/s43017-022-00309-5
Svalbard Arctic: https://journals.sagepub.com/doi/abs/10.1177/0959683617715701
Atlantification of todays warming: https://www.science.org/doi/10.1126/sciadv.abj2946
Last 800 years of sea life changes reflecting changes to the oceans and atmosphere: https://www.science.org/doi/full/10.1126/science.aaa9942
Small changes in the oceans make large changes in the atmosphere.
What’s the evidence clouds cause warming? Everyone knows everything causes warming, don’t it?
Clouds cool you by day and warm you by night.
Go to de-ath valley and see for yourself.
from a climate perspective, warming sometimes and cooling other times sounds like net neutral (i.e. no net warming).
They cool more than they retard cooling. They “warm” nothing.
Water cycles represent enhanced transport of heat from hotter places to colder places. Without such hydrodynamic transport hot places would be hotter and cold places would be colder. Conceptualize it however you wish.
The author does a very good job of contridicting themselves. First they state that it isn’t possible to model clouds and so climate models can’t be trusted. Then they say that Prof. Lindzen has a model for how clouds behave and which predicts that clouds are a negative feedback. The next step is that we should apparently believe Prof. Lindzen’s model despite it being based on the behaviour of clouds that are impossible to model.
The alarmist computer models break the world down into thousands of (relatively) tiny grids in order to attempt to model weather over long periods of time – i.e., climate. Even within those tiny grids the forces producing clouds are impossible to accurately predict, so they paramaterize them – they make rough guesses. Therefore he’s right, they can’t really model clouds.
What you can do is determine whether there is a net positive, net negative, or no effect from clouds, and try to work that into the model overall. The way the alarmists set that up results in a net positive feedback. Dr. Lindzen has explained a theory of why it should be a net negative. That is a different sort of model than the climate models. Treating the climate computer models differently than Dr. Lindzen’s theory is not a contradiction.
Others may explain it better, but I don’t see a problem with the logic of the article
Did you think about this question at all? What clouds *do* is far different that predicting the cloud existence around the globe. I can study what clouds *do*. I can’t predict when a cloud will float overhead! If I can’t do that then how do I model clouds even if I understand what they do when they exist?
Izaak, it was Dr. Bjorn Stevens, a contributing author to the Intergovernmental Panel on Climate Change (IPCC) Assessment Report 5 (2014). Dr. Stevens, also director at the Max Planck Institute for Meteorology, Hamburg, Germany, and a cloud expert, who said that –
“Clouds are tricksters, referring to their complexity. However, many scientists use oversimplified representations of clouds in modeling as a guide because they are easier to simulate. This makes the climate models less accurate.”
On the other hand, –
Lindzen proposes the mechanism by which greater negative feedback is produced: High altitude cirrus clouds (Dr. Stevens’ low-water high altitude ice clouds that cause warming) control heat emissions to space. As the air below these clouds warms, the cirrus clouds dissipate and allow more energy to radiate into space. He calls this the Iris Effect.
So the takeaway is that climate modelers take a guess at what effects clouds have, while Lindzen determines clouds’ effects based on the physics mechanisms (as one would expect a master physicist to do). Geddit?
And a minor nit-pick that I’m surprised Nick didn’t pick –
Ron Barmby, the author, is clearly ONE bloke.
So why are referring to him as “them”?
Surely “he” is the correct grammatical term?
Lindzen: “IPCC models rely on the assumption that water vapor and clouds amplify the greenhouse gas effects of CO2 in order to achieve forecasts of catastrophic global warming. The IPCC theory is that a warmer atmosphere will have a higher content of water vapor – itself is a greenhouse gas – that adds to the warming caused by CO2. Without this amplifying “positive feedback” effect, the models are still wrong for many reasons, but they no longer project “catastrophic” warming.”
There is conflation here. Water vapor as a positive feedback goes back to Arrhenius, and s not in doubt. There is doubt about the effect of clouds, as Stevens says, and it does affect the accuracy of models. But in the models, some cloud types warm and some cool, and it doesn’t have a huge effect on the result. Maybe, as Stevens suggests, the CMIP6 versions overdid the warming. It’s still a small net effect compared, say, to water vapor.
“French chemist Henry Louis Le Chatelier expresses this in Le Chatelier’s principle”
That principle just expresses a stable equilibrium. It doesn’t say there can’t be positive feedbacks. They will tend towards instability, but need not destroy it.
Nonsense. If a positive water vapor feedback exists, you’ll be happy to explain no “runaway greenhouse effect” occurring when the atmospheric level was 7000ppm.
Neglecting the speeding up of the hydrological cycle. The energy absorbed by additional water vapor is likely trivial compared to the movement of latent heat. If the water spends less time in the air, it also absorbs less heat.
Good article.
And if you cannot model clouds, you cannot model precipitation.
In figure 18 of this 2019 paper, notice that the best root-mean-square-error (RMSE) being reported for precipitation is on the order of 1 mm/day. This corresponds to about 29 W/m^2 in terms of latent heat release as water vapor condenses into rain. This figure is very helpful because it also shows how the CMIP5 models compare as a group.
Structure and Performance of GFDL’s CM4.0 Climate Model
https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2019MS001829
This is another reason to conclude that none of these large-grid, discrete-layer, step-iterated, parameter-tuned models have any diagnostic or predictive authority to compute a climate system response to rising concentrations of the non-condensing greenhouse gases.
The inability of open ocean surface to sustain a temperature over 30C is well known. It was identified in scientific literature dating back to the 1970s. You can ask ChatGPT to confirm that.
The really silly notion in the climate belief is that Earth is in some magical energy balance. Reality is that no place on Earth has a surface temperature that reflects the local radiation energy balance. Tropical oceans absorb an enormous amount of heat. The climate system transfers that heat poleward from where it is released to space. Net energy uptake over time in any location and temperature change over the same period are UNCORRELATED across the globe – per attached images and chart.
The common belief that all incoming radiation energy into the Earth system degrades to heat needs much better analysis. We we see the effects of water and ice terraforming; the effect of ocean waves and currents terraforming, coral atolls expanding, biomass additions, ocean floor accretions from dead vertebrae and so on. Humans are even releasing some of that stored energy from long dead fossils.
It takes between 180 and 200W/m^2 of surface sunlight to keep the tropical convection engine running at its maximum output. That is where the surface temperature of tropical oceans reaches 30C and there is no net surface heat flux – the sun just makes up for evaporation and surface cooling from rainfall. The convective instability cycles fast enough to form persistent cloud to regulate the surface sunlight. With a hot end of 303K and cold end averaging 255K, the Carnot efficiency of that engine is 15%. So the mechanical work of the convective engine is of the order of 30W/m^2. That is a lot of energy going into pumping up the tropical atmosphere the 800m to 900m that drives the global circulations. My bet is that some of the 30W/m^2 of “mechanical work” never ends up as heat.
http://www.pmd.gov.pk/rnd/rndweb/rnd_new/hrm/gsm_files/500mbheight.htm
Very nice.
Downing welling long wave (infra-red) radiation has been decreasing during the satellite era, it is escaping to space. (not going into oceans)
Yuanchong Zhang and William B. Rossow published 2023.
Long wave radiation escaping the planet’s atmosphere cooled the planet by as much as 4 watts per squ m. This in comparison to CO2 which had a warming forcing of 0.4 watts per square meter during the same period.
The attached graph from this paper shows the decrease in down welling long wave radiation and increase in short wave radiation.
It cannot be CO2 warming the planet as CO2 warming depends on increasing downwelling longwave radiation.
Who says water-rich low clouds are increasing? I have been hearing they’re decreasing their coverage by becoming less stratiform and more cumuliform. Also, they mostly cover a smaller percentage of the surface as the updrafts in the cumuliform ones carry more heat.
The main reason I see for the CMIP3 and CMIP5 models overpredicting warming is they have the water vapor feedback being greater than it is in reality, although it does exist and is positive. This is why the tropical upper troposphere warming hotspot hardly exists while it was modeled to exist to a great extent. These models were mostly tuned to hindcast a 30 year period that had part of its warming being from upswing of multidecadal oscillations.
As for the CMIP6 models being even worse than the CMIP3 and CMIP5 ones: Maybe there, there is too much positive feedback from clouds as well as excessive amount of water vapor feedback.
They also neglect the speeding up of the hydrological cycle. The energy absorbed by additional water vapor is likely trivial compared to the movement of latent heat. If the water spends less time in the air, it also absorbs less heat.
It’s less clouds getting in the way than it is pre-conceived notions.