by Ross McKitrick
Two new peer-reviewed papers from independent teams confirm that climate models overstate atmospheric warming and the problem has gotten worse over time, not better.
The papers are Mitchell et al. (2020) “The vertical profile of recent tropical temperature trends: Persistent model biases in the context of internal variability” Environmental Research Letters, and McKitrick and Christy (2020) “Pervasive warming bias in CMIP6 tropospheric layers” Earth and Space Science. John and I didn’t know about the Mitchell team’s work until after their paper came out, and they likewise didn’t know about ours.
Mitchell et al. look at the surface, troposphere and stratosphere over the tropics (20N to 20S). John and I look at the tropical and global lower- and mid- troposphere. Both papers test large samples of the latest generation (“Coupled Model Intercomparison Project version 6” or CMIP6) climate models, i.e. the ones being used for the next IPCC report, and compare model outputs to post-1979 observations. John and I were able to examine 38 models while Mitchell et al. looked at 48 models. The sheer number makes one wonder why so many are needed, if the science is settled. Both papers looked at “hindcasts,” which are reconstructions of recent historical temperatures in response to observed greenhouse gas emissions and other changes (e.g. aerosols and solar forcing). Across the two papers it emerges that the models overshoot historical warming from the near-surface through the upper troposphere, in the tropics and globally.
Mitchell et al. 2020
Mitchell et al. had, in an earlier study, examined whether the problem is that the models amplify surface warming too much as you go up in altitude, or whether they get the vertical amplification right but start with too much surface warming. The short answer is both.
In this Figure the box/whiskers are model-predicted warming trends in the tropics (20S to 20N) (horizontal axis) versus altitude (vertical axis). Where the trend magnitudes cross the zero line is about where the stratosphere begins. Red= models that internally simulate both ocean and atmosphere. Blue: models that take observed sea surface warming as given and only simulate the air temperature trends. Black lines: observed trends. The blue boxes are still high compared to the observations, especially in the 100-200hPa level (upper-mid troposphere).
Overall their findings are:
- “we find considerable warming biases in the CMIP6 modeled trends, and we show that these biases are linked to biases in surface temperature (these models simulate an unrealistically large global warming).”
- “we note here for the record that from 1998 to 2014, the CMIP5 models warm, on average 4 to 5 times faster than the observations, and in one model the warming is 10 times larger than the observations.”
- “Throughout the depth of the troposphere, not a single model realization overlaps all the observational estimates. However, there is some overlap between the RICH observations and the lowermost modelled trend, which corresponds to the NorCPM1 model.”
- “Focusing on the CMIP6 models, we have confirmed the original findings of Mitchell et al. (2013): first, the modeled tropospheric trends are biased warm throughout the troposphere (and notably in the upper troposphere, around 200 hPa) and, second, that these biases can be linked to biases in surface warming. As such, we see no improvement between the CMIP5 and the CMIP6 models.” (Mitchell et al. 2020)
A special prize goes to the Canadian model! “We draw attention to the CanESM5 model: it simulates the greatest warming in the troposphere, roughly 7 times larger than the observed trends.” The Canadian government relies on the CanESM models “to provide science-based quantitative information to inform climate change adaptation and mitigation in Canada and internationally.” I would be very surprised if the modelers at UVic ever put warning labels on their briefings to policy makers. The sticker should read: “WARNING! This model predicts atmospheric warming roughly 7 times larger than observed trends. Use of this model for anything other than entertainment purposes is not recommended.”
Although the above diagram looks encouraging in the stratosphere, Mitchell et al. found the models get it wrong too. They predict too little cooling before 1998 and too much after, and the effects cancel in a linear trend. The vertical “fingerprint” of GHG in models is warming in the troposphere and cooling in the stratosphere. Models predict steady stratospheric cooling should have continued after late 1990s but observations show no such cooling this century. The authors suggest the problem is models are not handling ozone depletion effects correctly.
The above diagram focuses on the 1998-2014 span. Compare the red box/whiskers to the black lines. The red lines are climate model outputs after feeding in observed GHG and other forcings over this interval. The predicted trends don’t match the observed trend profile (black line) – there’s basically no overlap at all. They warm too much in the troposphere and cool too much in the stratosphere. Forcing models to use prescribed sea surface temperatures (blue), which in effect hands the “right” answer to the model for most of the surface area, mitigates the problem in the troposphere but not the stratosphere.
McKitrick and Christy 2020
John Christy and I had earlier compared models to observations in the tropical mid-troposphere, finding evidence of a warming bias in all models. This is one of several papers I’ve done on tropical tropospheric warm biases. The IPCC cites my work (and others’) and accepts the findings. Our new paper shows that, rather than the problem being diminished in the newest models, it is getting worse. The bias is observable in the lower- and mid-troposphere in the tropics but also globally.
We examined the first 38 models in the CMIP6 ensemble. Like Mitchell et al. we used the first archived run from each model. Here are the 1979-2014 warming trend coefficients (vertical axis, degrees per decade) and 95% error bars comparing models (red) to observations (blue). LT=lower troposphere, MT=mid-troposphere. Every model overshoots the observed trend (horizontal dashed blue line) in every sample.
Most of the differences are significant at <5%, and the model mean (thick red) versus observed mean difference is very significant, meaning it’s not just noise or randomness. The models as a group warm too much throughout the global atmosphere, even over an interval where modelers can observe both forcings and temperatures.
We used 1979-2014 (as did Mitchell et al. ) because that’s the maximum interval for which all models were run with historically-observed forcings and all observation systems are available. Our results would be the same if we use 1979-2018, which includes scenario forcings in final years. (Mitchell et al. report the same thing.)
John and I found that models with higher Equilibrium Climate Sensitivity (>3.4K) warm faster (not surprisingly), but even the low-ECS group (<3.4K) exhibits warming bias. In the low group the mean ECS is 2.7K, the combined LT/MT model warming trend average is 0.21K/decade and the observed counterpart is 0.15K/decade. This figure (green circle added; see below) shows a more detailed comparison.
The horizontal axis shows the model warming trend and the vertical axis shows the corresponding model ECS. The red squares are in the high ECS group and the blue circles are in the low ECS group. Filled shapes are from the LT layer and open shapes are from the MT layer. The crosses indicate the means of the four groups and the lines connect LT (solid) and MT (dashed) layers. The arrows point to the mean observed MT (open arrow, 0.09C/decade) and LT (closed arrow, 0.15 C/decade) trends.
While the models in the blue cluster (low ECS) do a better job, they still have warming rates in excess of observations. If we were to picture a third cluster of models with mean global tropospheric warming rates overlapping observations it would have to be positioned roughly in the area I’ve outlined in green. The associated ECS would be between 1.0 and 2.0K.
Concluding remarks
I get it that modeling the climate is incredibly difficult, and no one faults the scientific community for finding it a tough problem to solve. But we are all living with the consequences of climate modelers stubbornly using generation after generation of models that exhibit too much surface and tropospheric warming, in addition to running grossly exaggerated forcing scenarios (e.g. RCP8.5). Back in 2005 in the first report of the then-new US Climate Change Science Program, Karl et al. pointed to the exaggerated warming in the tropical troposphere as a “potentially serious inconsistency.” But rather than fixing it since then, modelers have made it worse. Mitchell et al. note that in addition to the wrong warming trends themselves, the biases have broader implications because “atmospheric circulation trends depend on latitudinal temperature gradients.” In other words when the models get the tropical troposphere wrong, it drives potential errors in many other features of the model atmosphere. Even if the original problem was confined to excess warming in the tropical mid-troposphere, it has now expanded into a more pervasive warm bias throughout the global troposphere.
If the discrepancies in the troposphere were evenly split across models between excess warming and cooling we could chalk it up to noise and uncertainty. But that is not the case: it’s all excess warming. CMIP5 models warmed too much over the sea surface and too much in the tropical troposphere. Now the CMIP6 models warm too much throughout the global lower- and mid-troposphere. That’s bias, not uncertainty, and until the modeling community finds a way to fix it, the economics and policy making communities are justified in assuming future warming projections are overstated, potentially by a great deal depending on the model.
References:
Karl, T. R., S. J. Hassol, C. D. Miller, and W. L. Murray (2006). Temperature Trends in the Lower Atmosphere: Steps for Understanding and Reconciling Differences. Synthesis and Assessment Product. Climate Change Science Program and the Subcommittee on Global Change Research
McKitrick and Christy (2020) “Pervasive warming bias in CMIP6 tropospheric layers” Earth and Space Science.
Mitchell et al. (2020) “The vertical profile of recent tropical temperature trends: Persistent model biases in the context of internal variability” Environmental Research Letters.
Reblogged this on Utopia, you are standing in it!.
Very interesting, but…..
Cracked record says, why do we care? While understanding the detail is part of the job, aren’t we having the wrong discussion?
This is the overall lapse rate to space that varies the SST, sure. But it’s NOT the dominant control of climate equilibrium, which is bigger and very responsive.
A lot of any GHE change is reversed by the dominant control of the evaporative oceans, that currently deliver 150W/m^2 of negative feedback that is highly variable with temperature and has contained every exceptional and cyclical ice age interglacial since there were oceans.
This is a knife, as someone said.
So why worry too much about a change in the actually small effect of IR scattering by CO2, a small part of total GHE, which is itself just one part of the overall SST raising effect of our smart atmospheric lagging, and is all very well controlled by ocean evaporative response without difficulty.
It’s still colder than the last three warm cycles of this interglacial. etc.
More GHE brings more evaporation and more clouds. The dominant effect of water vapour is to impose stability. Problem solved. Probably ;-)
Just sayin’
What is wrong with this more joined up system description please? I really think realists miss a trick not pointing out that the oceans have the climate’s back as regards a bit of GHE change within the overall system, and have done since there were oceans. Earth’s climate system is overtly an inherently self stabilising system with massive natural oceanic feedback to any SST perturbation, exponentially increasing with temperature. The dodgy end is near zero during the glacial phase of ice ages, not when the tropics have got to 30 deg daytime SST. See how the interglacial warming is flat lined by this response when the oceans achieve an established tropical status capable of moving that heat back to space big time, while the oceans are still rising and the warming effect continues into the interglacial plateaux which still stays within a couple of degrees up and down every 1Ka. Observational reality.
We care because the hot models are driving draconian government policies.
A link to this article should be sent to Justin Trudeau, who is planning to use the Covid-19 reopening Throne Speech this Fall to introduce new climate policies based on Canadian climate models.
Canada has adopted one of the world’s most perfect global warming policies- ineffective but costly demands for Canadians coupled with an aggressive effort to ship the dirtiest possible fossil fuels to China (the oil sands). All of it followed up with press releases denouncing Trump.
Add their strategy to the global “green” effort to eliminate carbon-free energy sources and Canada could be said to be a principal player in the effort to increase global CO2 emissions- which now appears to have been the goal of the climate concerned over the past 30 years.
Good to see see and read. Great work !
So many models to debunk. Report will be saved in my cloud files and probably printed.
Dave Winterflood.
“Back in 2005 in the first report of the then-new US Climate Change Science Program, Karl et al. pointed to the exaggerated warming in the tropical troposphere as a “potentially serious inconsistency.” But rather than fixing it since then, modelers have made it worse.”
made it worse
Why is that? Group think? Stubbornness? Incompetence? Willful ignorance?
Nice post.
A good question. The CMIP6 models are averaging much hotter than CMIP5, and predecessors, going back 40 years. The reason seems to be that about half the models increased their positive feedback from clouds. There does not seem to be any new physical findings to justify this, so why it has happened is a mystery. They may have done it for political reasons, that is to help the push for more government action on climate change. But I have seen no investigation of this.
Their paychecks depend upon it.
Read back M20’s title, Charlie
After reviewing the original Charney Report that became the basis for much of the modeling that has followed, I became curious as to the predictions about increasing water vapor in the atmosphere as the Charney Report surmised. Being an amateur in this matters I did as much research online as I could to see if later studies confirmed the increasing water vapor portion of the theory. What I found was very inconclusive, with many studies showing no increase matching the theory, and many showing decreases. Ironically, if the water vapor effect is close to negligible, and the increase in temperature is only that attributable to increased CO2 )about 1/3 of the warming predicted by Charney) the correlation improves dramatically.
Is anyone aware of any definite studies on the water vapor concentrations over time? Any other thoughts on this possibility?
You could try going outside on a hot summer’s day and observing things.
Alternatively, maybe this could help you: https://en.wikipedia.org/wiki/Clausius%E2%80%93Clapeyron_relation
“Is anyone aware of any definite studies on the water vapor concentrations over time? Any other thoughts on this possibility?”
drhealy
Demetris Koutsoyiannis
Department of Water Resources and Environmental Engineering, School of Civil Engineering, National Technical University of Athens, Heroon Polytechneiou 5, GR 157 80 Zografou, Greece
Revisiting the global hydrological cycle: is it intensifying?
https://hess.copernicus.org/articles/24/3899/2020/hess-24-3899-2020.html
My understanding is that about half the extra warming is from increased water vapor and the other half from changes in clouds. In any case have you looked in the IPCC WG1 reports to see how they present this argument and what references they cite?
Well, as even NASA know, the NEGATIVE feedback to SST change from water vapour is 100W/m^2 in evaporation and latent heat release, and 50W/m^2 from cloud albedo that the evaporation produces. This can vary by 10% per deg in the tropics. Will that do as a control? Why worry about small changes in the lapse rate sub system when this dominant control stabilises all such tiny effects?
Is the dominant feedback in the “models”? https://www.youtube.com/watch?v=KFq2pU21cNU
More CO2 (and water vapour in the atmosphere causing SST rise) brings cooling evaporation and clouds to reflect the primary heat source. Job done.
Stability rains, usually at about 3pm.
I researched every study I could find without paying, and reviewed ten of the most recent studies. None of the results fully supported the increase in precipital water necessary to support Charney’s original theory and a couple of the authors even indicated that their findings raised major questions with the validity of the theory, but followed up with usual comment that more study was needed.
The earliest and longest term study going back to 1948 or so, showed declining precipital water in the upper troposphere, but it has been claimed the radiosonde instrumentation was not sufficiently accurate. Ironically, the studies I reviewed seemed to approximate the earliest study.
I was just curious if anyone was aware of any “pay walled” research that supports Charney’s theory. Thanks
where’s that research, doc
thanks
Is this not the type of problem that Artificial Intelligent computers should be good at solving?
human intelligence or artificial intelligence needs intelligent efforts to get the best data and understand external factors and internal response. NO ONE IN THE ALARMIST OR LUKE WARM ARENAS ARE CONSIDERING INTERNAL RESPONSE.
It snows more when polar oceans are thawed, polar sequestered ice grows, spreads out and that causes colder. That takes a few hundred years in modern times and thousands of years for major past cycles and none are considering internal factors as being important.
Ah, internal effects. One for you, off topic, slightly. What really drives ice age cycles. Probably.
Not the solar driven cycles of the centennial scale, but here is a probable internal cause of ice age cycle, Driven by gravitational orbital forcing on the visco elastic planet, and the effect its variability has on ocean floor movement . Hypothesised by John Wahr and Michael House, quantified by me, the hard way. Caveat Lector: http://dx.doi.org/10.2139/ssrn.3259379
@ brianrlcatt – or maybe there is an external cause of glacial periods… https://en.wikipedia.org/wiki/Milankovitch_cycles
I think computers are the the problem we currently have. Provable science needs human intelligence and scientific method applied using proven physical laws and relationships.
Numeric curve fitting models are useful cause and effect study tools. They prove no “science”. AI that looks forms own laws rather than inputs data designed to prove a presumed theory.?? Better.
But, better still a return to the hard/real science of being “guided by the (proven) science”?
The other way comes Skynet. When the humans become more stupid than their machines and depend upon them for their science, we are in trouble, as we already are when the politics intentionally leads the science, so political presumptions are used to programme computers run by climate priests to prove their presumptions. Really?
Surely the Most draconian policies are the forcing.of fossil fuel dependency and high material flows through subsidies as well as removing social benefits.and.letting.people be homeless.and starve?
Good job. I’m surprised Google sent me this. I was getting the impression they didn’t promote anything that didn’t support the climate alarmists’ agenda. I am so tired of hearing climate alarmists’ claims that the earth is overheating, ice caps are melting away, and we’re all going to die because of CO2, based entirely on these computer models. This article is a breath of fresh air, demonstrating that the model predictions are off by 5 to 7 times.
Reblogged this on Climate Collections.
maybe 35 years isn’t long enough
Here I show the effect of time span on correlation between CMIP5 forcings and temperature.
https://tambonthongchai.com/2018/08/31/cmip5forcings/
It will be interesting to read any responses by Church of Climatology members (radical progressives) regarding these peer-reviewed papers.
Remember, a warmer, wetter climate feeds more and displaces far fewer people than a colder, drier climate. You can’t build cities atop glaciers. And when the Antarctic opens up, there will be a lot of land for both utilizing and preserving.
Ross,
Is this any surprise given that all climate models are based on the wrong atmospheric dynamical system of equations. They violate the necessary conditions of the mathematical Bounded Derivative Theory for the correct dynamical ( reduced) system and violate the necessary differentiability required by the theory of numerical analysis. In addition there are large continuum errors due to excessive dissipation and parameterization errors. This has all been documented in my peer reviewed manuscript accepted long before yours that has been discussed on this site and on WUWT.
Gerald Browning
Judith,
Why didn’t you publish my results on the news, especially as you reviewed my manuscript. My results are mathematically more rigorous than either
of these two manuscripts.
Gerald Browning
Problem is that no one knows why CMIP models run warm, nor are there incentives to acknowledge the existence of possible problems, let alone to search for causes, and fix them (sunken cost fallacy, locked-in syndrome).
It does not matter why models run warm, they have nothing to do with proper understanding of climate.
climate models overstate atmospheric warming
duh
climate models are based on modeling correlations with immediate forcing factors and internal response.
Internal factors store energy in oceans and ice and have internal responses that have never been studied or considered.
overview of state of the ocean heat knowledge (“Measuring Global Ocean Heat Content to Estimate the Earth Energy Imbalance”
Meyssignac et al. [August 2019] https://www.frontiersin.org/articles/10.3389/fmars.2019.00432/full
The reason we need long time spans is that internal climate variability dominates in short time spans. Pls see
https://tambonthongchai.com/2020/07/16/the-internal-variability-issue/
Reblogged this on Tallbloke's Talkshop and commented:
Quote re. the Canadian climate model…
The sticker should read: “WARNING! This model predicts atmospheric warming roughly 7 times larger than observed trends. Use of this model for anything other than entertainment purposes is not recommended.”
Two papers out of, how many?
There is a substantial difference between the quantity and quality of papers.
How to explain that climate models are based on the wrong atmospheric dynamical system of equations, violate the requirements of numerical analysis, use excessive dissipation, and have unresolved and questionable physical parameterizations? Read the mathematical proof of these facts
In my manuscript in the September issue of the journal Dynamics of Atmospheres and Oceans. Rigorous mathematics trumps hand waving.
Gerald Browning
special k
I recommend that you start with the question as to why climate models dilute insolation and in effect make the sun shine directly onto the surface of the Earth at night.
The basic error in these models is the assumption that water provides a POSITIVE feedback to the GHE.
The Hydro Cycle operates as a Rankine Cycle and is responsible for the transfer of large energies (694Watthrs/sq,m) up through the atmosphere and to space irrespective of CO2 levels. This results in a strong net NEGATIVE feedback which is being ignored or discounted in the models.
At the evaporative phase change of water the Planck coefficient of sensitivity is ZERO as it occurs at CONSTANT temperature. Unless this is incorporated into the models there will be too high a value put on the global Sensitivity parameter.
We ignore the physics of the Rankine Cycle at our peril.
More proof that IPCC encourages (even mandates) the use of climate models which produce climate warming estimates at up to 7x observed data.
And the media constantly publishes the incorrect data and seeks to have governments and industries respond to it by lambasting fossil fuel users.
Politics leading science?????
FWIW, according to the lead author, this “(these models simulate an unrealistically large global warming).” should be “unrealistically large *tropical* warming” not “unrealistically large *global* warming”.
Read better, aTTP.
In 2018 which was the 30th year anniversary of Hansen’s prediction, Several alarmsists websites were touting the accuracy of Hansen’s B model
prediction of .8c of warming which almost precisely matched the actual.
However I recall seeing Hansen’s original A/B/c model predictions and at the 30 year point, the B model was showing 1.0c to 1.2c of warming over the same 30 year period.
Question – does anyone else have any recollection of the original version instead of the revised version of Hansens model ? or a link?
thanks in advance
You can access the paper here. The key thing to bear in mind is that the authors had to choose some future emission scenarios, which then produced a change in forcing, which then led to the change in surface temperature. To properly check their model, you need to compare the projection that had a change in forcing that was closest to what we actually experienced. When you do so, you find that the model was reasonably good.
and Then There’s Physics: The key thing to bear in mind is that the authors had to choose some future emission scenarios, which then produced a change in forcing, which then led to the change in surface temperature. To properly check their model, you need to compare the projection that had a change in forcing that was closest to what we actually experienced. When you do so, you find that the model was reasonably good.
We read this a lot: the forecast temperature trend was too high because the forecast (or “chosen”) CO2 trend was too high, but the model was ok (no a priori criteria of “ok” ever written.) That’s practically as good as making an accurate temperature forecast. You can’t doubt the current forecast without being some sort of bad person (“serial disinformer”, etc.).
I think the key thing to bear in mind is that the forecast was too high.
Matthew,
That’s why they’re called “projections” rather than “predictions”. Climate models are not intended to predict how much we will emit in future. The emission pathways are inputs to the models, not model predictions. Climate models can then tell us how much we will warm *if* we follow that emission pathway.
thanks for the link – my error – I was picking up a start date of 1960 to get the 1.2c increase vs start date of 1988.
and Then There’s Physics: That’s why they’re called “projections” rather than “predictions”.
That’s why we do not base policies on them. Or use pejorative language toward people who point out that they are too unreliable for policy..
The key fact here is that there is no expectation of skill from climate models because the numerical truncation errors are vastly bigger than the changes in energy flows that are being predicted. It continues to amaze me that this simple fact has been obscured for 40 years. There has been a flurry of recent papers that are more honest.
If the TOA radiation imbalance is tuned to reality (as it is) and ocean heat uptake is roughly right (which it seems to be) then global mean temperature might be roughly right. This is not very meaningful since the patterns will be wrong and thus ECS will be wrong too.
That the tropics are wrong is not surprising at all to anyone who has ever tried to solve any turbulent flow problem. Convection is an ill-posed problem and with mesh spacings of 50km, its pretty much hopeless. Everyone knows this too.
“That’s why they’re called “projections” rather than “predictions””
I take your point regarding the emissions pathways, but nonetheless the word ‘forecast’ is contained in the title of Hanson’s 1988 paper, and the word ‘predict’ (or ‘prediction’) is used four times in the abstract and 40 times in total in the paper (‘forecast’ is used 12 times).
Perhaps the most important prediction is the claim that by the 1990’s in any of the scenarios “The temperature changes are sufficiently large to have major impacts on people and other parts of the biosphere”.
This, and other predictions like it, led to the “millions of climate refugees” and other armageddon pictures being painted at the time.
In the conclusion, Hanson wrote that more research is urgently required (what researcher ever says anything different?). However, for this paper to qualify as “reasonable good” (to use your expression), he really should have written, “Although we’ve had tremendous fun, in every sense that actually matters this could easily all amount to a hill of beans.”
The criteria for the use of models in attribution are that they are capable of correctly simulating climate. This is stated in AR5, CCSP Reports, EPA’s TSD on the 2009 GHG Endangerment Finding, NCA 2014, and the National Research Council.
Models do not meet this criteria, and therefore are completely useless for attribution analysis.
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As long as models bake in that Co2 causes warming, they will continue to be wrong. It has been shown over and over that temperature increases first, then Co2 follows. Co2 is a TRACE gas, which cannot affect surface temperature. No model with that reverse logic will ever work.
OK OK, So we need more money to make more models to get it right! :)
Isn’t using a 1998-2014 interval cherry picking? You start right before a major El Nino event and then end right before another major El Nino event. Internal variability alone would cause this period to experience warming in reality than climate models would suggest. That does not demonstrate that climate models are inaccurate.
> Isn’t using a 1998-2014 interval cherry picking?
What did you expect?
Maybe, but it doesn’t matter. One would expect the model “wiskers” to at least overlap the observations and they don’t. Models claim to model “internal variability” even though they are terrible at it.
> One would expect the model “wiskers” to at least overlap the observations
y tho
@ dpy6629 – you don’t necessarily expect it if you cherry pick things.
We used 1979 to 2014, which is the longest interval for which all observational products are available and the models are forced with observed historical inputs. We also ran the results extending the data to 2018 by including some scenario forcings for 2015-2018. The results stayed the same. Mitchell et al also did this and report no change in results. Their analysis of 1998-2014 is for the purpose illustrating the trend change in the stratosphere before and after 1998.
The justification for your intervals seems fine. But for Mitchell et al. it seems like cherry picking.
> the longest interval for which all observational products are available and the models are forced with observed historical inputs
Sometimes you’re just lucky.
Willard: I deliver an algorithm to you if you don’t like a papers outcome and you can’t find any mistakes in it:
1. assume “cherry picking” in the selected timespan of the paper in question
2. If the response of the author is satisfactionary for the rest, declare it as “luck”
3. goto 1.
FrankB,
I deliver to you an audit method:
1. Fine-tune a method to produce either trends or lacks of trends;
2. Correct its most obvious blunders, spanning over decades;
3. Pretend you’re an econometrist that never checks under the hood;
4. Publish op-eds after op-eds, in right-wing rags or Freedom Fighter think tanks;
5. Never test your method.
6. Let amateurs fellows who stretch the lowest bounds of sensitivity justified disingenuousness such as you defend you on blogs;
7. Let them pretend they’re in it for the science.
There is no eight step.
Willard, you wrote: “4. Publish op-eds after op-eds, in right-wing rags or Freedom Fighter think tanks”
Others identify a “leftie” CNN view on other things:
https://judithcurry.com/2020/07/14/cancel-culture-discussion-thread/#comment-921163
I’m on track, I guess.
However, I deliverd a useful algorithm to you and you delivered nothing. Some kind of imbalance? :)
Dear FrankB,
I countered both your point and your meek jabs.
Denying it is more than endearing to me.
Thanks for playing!
“You start right before a major El Nino event and then end right before another major El Nino event.”
And if both El Nino events had been included in the time frame, observed warming would have been more.
Ending it right before another and one believes the warming steps theory like Trenberth. Including both steps is then the cherry pick.
Ending it right before another and one does not believe the warming steps theory like Trenberth. The area of an El Nino, height times width, has an impact, but it’s not overwhelming to the average.
The time frame used, was one where there should be traction. We can excuse the decade of the 70s. But CO2 has been marching upwards for a long time. It has been relentless. We should have a CO2 clock to tell us what year it is?
We keep waiting. We say where is it? Look here, it’s over here, here and here. That’s a polar bear. I don’t care. A polar bear. That’s it?
Polar bear kills invasive human and is immediately murdered by swarm of homo sapiens.
Aug. 28, 2020
https://www.bbc.com/news/world-europe-53945950
“A polar bear has killed a man in Norway’s Arctic Spitsbergen island, local officials say.
The attack occurred at a campsite near Longyearbyen, the main town of the island in the Svalbard archipelago.
People in the area shot the bear, which was found dead at the local airport.
Experts say polar bears’ hunting grounds have diminished as the Arctic ice sheet melts due to climate change, forcing them into populated areas as they try to find food.”
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This is a question borne of ignorance, but how do we know the issue isn’t that models are getting it wrong but that there’s something wrong with the radiosonde data?
Al1816
“but that there’s something wrong with the radiosonde data?”
See this work:-
Connolly, R. and Connolly, M. 2019. Balloons in the Air: Understanding Weather and Climate. Center for Environmental Research and Earth Science. https://blog.friendsofscience.org/wp-content/uploads/2019/08/July-18-2019-Tucson-DDP-Connolly-Connolly-16×9-format.pdf.
Philip, can you help me understand the implications of that slide deck as far as my question goes? I read through it but didn’t see anything I thought directly addressed the question.
aljo1816
I recommend conclusion #4 of the slide deck
Einstein’s 1919 work and our balloon work shows that increasing the concentrations of the so called greenhouse gases does not cause global warming
Philip, that does not address the question of whether there might be an error or bias in the radiosonde data, does it? It seems to assume that the radiosonde data are accurate (which might be true, I do not know and so am asking the question).
You have my answer.
Al1816
Data first Model second – Science
Model first Data Second – Climate Science
Philip,
I agree we need to ensure the observational data are good. Hence, my question.
Al1816,
Radiosonde and ACARS data is the best data there is (see manuscript by Sylvie Gravel et al. ) Unfortunately it is very sparse.
See my comment above (and the associated manuscript) about the serious mathematical flaws in climate models that are swept under the rug by the climate modelers. The mentioned manuscript introduces the correct atmospheric dynamical system and discusses the impacts the mathematical and numerical errors have on climate models.
Gerald Browning
Gerald,
It may well be the best data there is, but that does not mean it is perfect, does it? As I read the blog post, three possibilities jump out:
1. The models are wrong
2. The observations are wrong
3. Both are wrong
The blog post and the two papers (so far as I’ve read) seem to claim that 1. is correct, but without much justification. I’m looking for some evidence that 2. or 3. must be wrong.
Aljo1816,
I did not claim the obs data is perfect. Quite the opposite. Read the manuscript by Sylvie Gravel, et al. to see how what data there is is used to keep forecast models from going off the rails because they are using the wrong atmospheric dynamical system and inaccurate parameterizations.
See my manuscript to determine all of the serious mathematical flaws in climate models to explain why Ross, results are eminently reasonable.
Jerry
“This is a question borne of ignorance, but how do we know the issue isn’t that models are getting it wrong but that there’s something wrong with the radiosonde data?
radiosonde data is notorious crap.
But there is a newly minted attempt to correct the faulty data.
wait and see
Steven Mosher: radiosonde data is notorious crap.
But there is a newly minted attempt to correct the faulty data.
Any references to add detail? “crap” does not follow from “faulty”; there would not likely be an attempt to “correct” crap.
I have no doubt you’re working on it. Are you going to make it better?
i.e., a knowing deception, right?
“That’s bias, not uncertainty, and until the modeling community finds a way to fix it, the economics and policy making communities are justified in assuming future warming projections are overstated, potentially by a great deal depending on the model.” ‘~McKitrick
Wagathon,
A numerical model does not prove anything unless
1. It is based on the correct well posed partial differential system of equations that has no continuum errors
2. The numerical method is accurate and stable and of sufficiently fine resolution to accurately approximate the continuum solution
The climate models are based on the wrong atmospheric dynamical system of partial differential equations and have large continuum errors due to this fact, excessive dissipation, and inaccurate parameterizations.
The numerical methods are approximating a discontinuous solution so
they violate the numerical analysis requirement that the truncation error be small. The mesh size is not sufficiently small to accurately approximate the continuum solution even if the correct dynamical system were being used.
Gerald Browning
My police department overestimated muggings therefore crime doesn’t exist.
My police department, in its expert wisdom, estimated that muggings would increase exactly in line with sales of Clorox wipes. Sales of Clorox wipes then tripled over a 12 month period, whereas muggings during that same period went down slightly. From this, should I reasonably conclude that:
A) Muggings do not exist
or
B) The police are completely deluded with respect to the actual factors that drive muggings
Which do you think?
Or, perhaps, one should instead conclude, as per your comment above, that C) “crime doesn’t exist;” or D) that crime does exist? Would one of those options be a more intelligent conclusion?
Global warming does exist and it has warmed in total. One of the reasons we have the models to say how much it will warm. That is a key variable for economic calculations. If it isn’t going to warm a lot, arguments for change become less convincing.
> If it isn’t going to warm a lot, arguments for change become less convincing.
I haven’t seen ANYONE who can say whetherbit isn’t (or is) going to warm a lot. What if it might warm a lot? That seems to me like the important question – and that a lot of people spend (waste) a lot of time an energy focused on the wrong question (because they’re ideologically motivated and/or stick in a binary mindset).
Predictions are hard. Especially about the future
This should be about decision-making in the face of uncertainty (imo). Seeking certainty is ill-suited to reality.
Look to what the Buddhists say.
You appear to be questioning the use of models which are the subject of this post. I am not the one that said, look at what this model says, now do this. The models attempt to look into the chaos of the future. The models here generally say that order will be destroyed by chaos. Yes it will. But in the chaos of the future, a new order will emerge, and we will find a good future.
And I am predicting that burning money as California has done will not lead to a good future.
Our climate scientist oracles have said chaos is coming and answered with chaos. See California. They have made climate order their highest goal. But that denies the inevitability of the change of chaos. I say, strike a balance between order and change and the transformation will will the best we can make of it. We will find that perfect arc between order and chaos. Opportunities and least energy paths will become apparent.
You suggest that answer is not binary. You are correct. It’s the perfect arc between the two things.
You could tell me what the Buddhists say. If they say Yin and Yang is wrong, that’s a binary statement.
Joshua: Look to what the Buddhists say.
Whyever would you do that? If you must, which Buddhists and which sayings?
Predictions are easy. Everyone can/does do it, specially about the future.
Just like the weather, they never apologize for being wrong.
They are pretty much at the same level of the models used to predict “SARS-CoV-2” deaths!
This post should be titled “The Replication of Consequential Scientific Futility”.
Water vapour in the atmosphere ranges from 8 to 50,000 parts per million .In the tropics it will be in the higher range so the marginal warming effect of a rise in CO2 from 280 to 400 parts will be much less in the tropics. Might this explain the bias?
“The relationship between temperature and CO2,” according to Dr. Timothy Ball, “is like painting a window black to block sunlight. The first coat blocks most of the light. Second and third coats reduce very little more. Current CO2 levels are like the first coat of black paint.”
The atmosphere does not consist of a single thin layer, like a pane of glass, but has a volume with no upper bound. You might be able to darken the lower layers to infrared, but you can never fully darken the upper atmosphere. You just keep raising the effective height of emission.
“You just keep raising the effective height of emission”
And in order to do that the atmospheric mass must be increased.
Inverse Climate Modelling Study of the Planet Venus
http://www.sciencepublishinggroup.com/journal/paperinfo?journalid=298&doi=10.11648/j.ijaos.20200401.13
The origin of the Hot spot hypothesis? But, that hypothesis failed real world testing…
https://wattsupwiththat.com/2016/09/22/study-tropical-hotspot-fingerprint-of-global-warming-doesnt-exist-in-the-real-world-data/
Philip,
I have not had time to read your paper further than its description of the greenhouse effect (section 1.3), but there seems to be an error, at least conceptually, in your description of the process. It is this error that leads you to calculate an expected surface temperature that is much too low. It is not merely the occurrence of ‘back radiation’ that establishes an atmospheric greenhouse effect, but the presence of an atmospheric lapse rate. The effective height of emission must approximate the equilibrium temperature (226 K for Venus). Moving the effective height of emission up or down (by adding or subtracting absorbing gasses) in an atmosphere with a lapse rate will cause the entire temperature profile to shift warmer or colder to maintain radiative equilibrium.
All of which is to say that Venus isn’t simply so hot because it has greenhouse gases in its atmosphere, it’s so hot because it has a LOT of greenhouse gases in its atmosphere.
aljo1816
The purpose of the analysis is to establish the minimum irreducible criteria for a climate model. So I start with a tidally locked planet that has a pure nitrogen atmosphere and build from there. As a point of interest Venus has 4 times the mass of nitrogen in its atmosphere than the Earth does. Saturn’s moon Titan also has an almost pure nitrogen atmosphere, so as a starting point for climate a nitrogen atmosphere seems to be an appropriate assumption.
Wagathon,
The tropical tropospheric hotspot is simply a predicted consequence of surface warming, no matter what the cause.
If you are trying to compare Earth’s atmosphere to Venus, that’s a non-starter – Gore compared the future of Earth to the climate of Venus. What a Big Lie! The percentage of CO2 in Earth’s atmosphere is measured in ppm (parts per million). Gore compared Earth’s future to planets like Mars and Venus and did so while climatologists in Western academia remained mute. The actual facts are that the concentration of atmospheric CO2 of Venus, for example, is 97% (Earth is <0.04%). The surface atmospheric pressure on Venus is 92 times that of Earth. Venus has no ocean whereas the Earth’s surface is mostly water. Moreover, Venus is closer to the sun by a third, and a day on Venus is 243 Earth days long; but, there is no nighttime for the polar caps of Venus as both poles are under constant solar radiation as 53% of the surface of Venus is under constant illumination due to its proximity to the sun.
Philip, can you provide additional justification for the geometric series limits for Noonworld? I do not understand where these numbers come from.Can you provide justification for why you suppose that half of the flux moving convectively to the nighttime side of Noonworld will be lost as radiant heat to space and why half will be returned to the daytime side? Why not 90% lost to radiation and 10% returned convectively?
Genuinely curious to understand the answers.
“Genuinely curious to understand the answers”
aljo1816
Thank you for engaging.
As you may have already appreciated there is a considerable background here. I recommend you look at our analysis of the standard model. See:
An Analysis of the Earth’s Energy Budget
https://www.researchgate.net/publication/334480930_An_Analysis_of_the_Earth's_Energy_Budget
The issue of partition derives from a diabatic (equipartition) distribution of energy at the basal boundary (the surface of the planet). So half out by thermal radiation escape to space (via the transparent atmospheric window) and half retained by the mobile nitrogen atmosphere.
The geometric series infinite limits are therefore mathematically defined by the 50/50 partition ratio for a diabatic scenario. Note the coincidence of this application with the standard radiative model where half of the atmospheric thermal radiation is lost to space and half is returned to the ground.
The next step is then to recognise the role of adiabatic partition of energy at the lit boundary, where atmospheric convection acts to transport energy away from the basal surface,
(There is no ping system on this blog so my apologies for any delay in responding).
Not expecting you’ll get the correct response that it’s water vapor and not CO2 that’s the most powerful among greenhouse gases, contrary to AGW doomsday scenarios painted by Western academia and codified in the mathematics of global warming modeling– its net atmospheric effect is actually negative, not positive.The AGW hypothesis requires that CO2 warms the planet, causing water to evaporate, leading to an increase in this most significant greenhouse gas as follows: the CO2 warming effect, minor though it may be, was said to result in an increase in water vapor that would cause a runaway global warming of the planet, despite the fact this would violate the laws of thermodynamics. It shouldn’t take more than the normal scientific skepticism to know that this is not possible which is why scientific skeptics have come to believe that global warming alarmism is nothing but a hoax and a scare tactic… a Left vs right political debate having much to do with social science and little to do with natural science.
Much like rioting in Portland is described as a peaceful protest by the Left even as the city burns and a secessionist leader assassinates a political adversary in the streets, the global warming establishment of Western academia predicts ever hotter days ahead, even as British senior citizens are forced to burn books to stay warm in cold winters.
“Why not 90% lost to radiation and 10% returned convectively?”
Aljo1816,
Please take some time to explore the utility of the model in the Excel Spreadsheet Noonworld Tables 31May19 https://www.researchgate.net/publication/334491101_Noonworld_Tables_31May19
The key point is that the model is designed respond to the physics of a planetary system as measured by the observed parameters (albedo, insolation etc). On a lit surface a partition bias in favour of the air cases the model to heat. On the nighttime side of the model a bias in favour of radiation loss to space causes the model to cool. Compare this with impact of the surface to space radiative cooling observed over the Antarctic icecap during the austral winter and the generation of katabatic air mass movements off the icecap,
Dome Argus Weather Station Temperature Profiles from 09 May to 17 Dec 2008 https://www.researchgate.net/publication/335313576_Dome_Argus_Weather_Station_Temperature_Profiles_from_09_May_to_17_Dec_2008
Simon Harrison:
“Water vapour in the atmosphere ranges from 8 to 50,000 parts per million .In the tropics it will be in the higher range so the marginal warming effect of a rise in CO2 from 280 to 400 parts will be much less in the tropics. Might this explain the bias?”
Simon Harrison, it is an excellent thought!
At the tropics we have the highest level of the surface IR emission capacity.
The tropics is the zone where the greenhouse forcing is somehow present, because
1. In the tropics there are the highest levels of surface IR emission.
2. And there is the highest range of water vapor in the atmosphere 50,000 parts per million.
The greenhouse warming effect of the CO2 400 parts per million is negligible. It is so weak it cannot be measured.
http://www.cristos-vournas.com
The tropics are cooled by chilled water that is circulated back from polar regions. The chilled water was chilled by thawing ice that contacted warm tropical ocean currents. Any warming, thaws polar sea ice and that promotes evaporation and snowfall that increases the volume of stored ice. The increased volume of stored ice spreads and contacts more warm tropical currents. The climate is self correcting. the temperature that sea ice thaws and turns on the ice machines is not influenced by CO2. These cooling processes adjusted automatically as solar into the northern hemisphere decreased over the most recent ten thousand years as it increased in the southern hemisphere. Just like the cooling system in a house, the cooling is turned on when the temperature gets above the set point.
My reasoning! Do any of these climate models currently take into account the relative warming effect of CO2 in different regions ?
If a volcano can produce more Carbon dioxide than man in a lifetime then why the alarm. Sounds like the more complaining about Global warming the more research dollars are handed out. These research dollars could be better spent on greater causes to benefit humankind.
https://www.climate.gov/news-features/climate-qa/which-emits-more-carbon-dioxide-volcanoes-or-human-activities
If you’re following someone that is arguing volcanoes disprove something about CO2 levels, stop that.
People are coming their senses. The climate research isn’t producing much value. Look at Africa and how their lives have been improved by all this research. We could even ask about morality.
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Atmospheric warming happens due to the Earth’s surface IR emission.
Now, the Earth’s IR emission intensity depends on the absorbed SW solar energy.
To calculate atmospheric warming one should estimate the by Earth’s surface the absorbed SW solar energy.
The solar flux absorbed by the sunlit hemisphere is assumed to be:
Jabs = (1 – a) So πr2
here a – is the average albedo
So W/m2 – is the solar flux at the top of the atmosphere
r – is the planet’s radius
It is a mistaken assumption. It is based on the old believe that planet absorbs as a black body. So according to that mistaken believe the sunlit hemisphere absorbs as the sphere’s cross-section disk.
In reality Earth is a smooth surface planet and absorbs and reflects as a smooth sphere.
So we have:
Jabs = Φ(1 – a) So πr2
Φ – is the dimensionless solar irradiation accepting factor
For smooth surface planets, like Earth, Φ= 0,47
So then we have
Jabs = 0,47(1 – a) So πr2
Conclusion:
In order to calculate atmospheric warming one has to use Φ = 0,47.
Thus the amount of energy involved in calculations is reduced to 0,47 of the old assumption’s amount.
http://www.cristos-vournas.com
Atmospheric warming happens due to the Earth’s surface IR emission.
This leaves out water. Water evaporates and cools the surface, the water vapor is carried by convection up where it condenses into water or forms ice which releases the energy that was removed from the surface. Days get hotter and nights get cooler when water is not part of the cycle. Climate Theory does not properly consider water in all of its states and does not properly consider the changing of states.
Alarmists use a gas that is a little more than 400 parts per million, that is 1 in 2,500. The climate system uses water in all of its abundant states. The climate system can regulate the greenhouse effect on a real time basis and self correcting feedback makes the warming from CO2 not relevant to warming or cooling the system.
–popesclimatetheory | September 1, 2020 at 12:36 pm | Reply
Atmospheric warming happens due to the Earth’s surface IR emission.
This leaves out water. Water evaporates and cools the surface, the water vapor is carried by convection up where it condenses into water or forms ice which releases the energy that was removed from the surface.–
Water also evaporates and warms the planet.
What controls global climate is the tropical ocean. The tropical ocean is heat engine of the planet.
The average tropical ocean surface is about 26 C.
What effect would it have if the average tropical ocean surface temperature was 4 C rather than 26 C?
Keep in mind that humans could, if they wanted to, cause the tropical ocean to have average temperature of 4 C.
Also keep in my nature has never had tropical ocean with average temperature as cool as 4 C.
Humans could do this, because the energy cost of mixing warm tropical water with cold deep tropical warms, is not a lot. Or fairly expensive but certainly within the amount energy we can make.
Natural process isn’t going to do this, but it could be done. So, what happens if tropical ocean surface temperature was about 4 C rather than 26 C?
Obviously one crashes the amount water vapor on planet Earth.
If thought it was just cooling, then you removed the major element evaporational cooling from Earth. Does Earth warm?
First without considering any cooling {or warming] effect. Just in terms of what we call global average surface air temperature- how effect the number of 15 C.
The average global ocean surface temperature is about 17 C.
The average global land surface temperature is about 10 C.
As said tropical ocean is 26, and 60% of rest of ocean is about 11 C
40% tropics 40 times 26 is 1,040 and 4 C, 40 times 4 = 160
60 times 11 = 660
1040 + 660 = 1,700 / 100 = 17 C
1040 + 160 = 1,200 / 100 = 12 C
And 70 times 12 = 840 and 30 times 10 = 300 total: 1,140
So global average surface air temperature is 11.4 C.
What about the effects?
Easy part, Europe doesn’t gulf stream warming effect. It’s 9 C, and cools below 0 C.
What happens to tropical land, they roughly become deserts pretty quickly.
And existing tropical deserts would get cooler.
The more complicated part what happens global circulation.
Just cooled the tropical ocean, and so, would still have fairly warm ocean outside the tropics, they probably some effect upon global circulation, not clear to me what the effect is.
So, human continue to cool the tropical ocean and keep at 4 C for few years. What is result?
In terms of “real” global temperature {the temperature of the entire ocean which currently is about 3.5 C] humans are massively warming Earth- but only doing for a few years.
But in terms of average global surface air temperature, I think gets much colder than 11.4 C. As you have seriously crippled Earth’s heat engine.
gbaikie
Interesting thought experiment.
Here is some confirmation of your idea.
At night the ITCZ is often more active over the Atlantic Ocean off the west coast of Africa, than it is over the land.to the east.
https://www.ventusky.com/?p=12.9;-16.3;4&l=rain-3h&t=20200903/0000
https://www.ventusky.com/?p=12.9;-16.3;4&l=temperature-2m&t=20200903/0000
Here’s a paper that mixes the climate with the coronavirus. It proposes an “intergenerational” contract between young and old.
https://www.cambridge.org/core/journals/global-sustainability/article/corona-and-the-climate-a-comparison-of-two-emergencies/AE382384C616E5707064066B5065DD4E
The contract is essentially this. The young say to the old, “agree to believe and support our climate agenda – we’ll know if you’re pretending – or we’ll give you coronavirus. Change your minds and join our cause or cough spit you’re dead.”
For their common future, both generations should enter a social contract (Wissenschaftlicher Beirat der Bundesregierung Globale Umweltveränderungen, 2011) that is based on mutual solidarity. In such a Climate Corona Contract, the younger generations would agree to protect the elderly and other at-risk groups from COVID-19 by adhering to restrictions, such as physical distancing measures. Conversely, the older generations would vow to rigorously implement measures to keep global warming between 1.5°C to 2.0°C above pre-industrial levels in line with the Paris Agreement signed by most governments.
Trading a man made climate scare against a man made virus scare.
We can hope these two man made viruses get rid of each other.
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Much of science has been turned into a religion.
https://anchor.fm/james-mcginn/episodes/The-religion-that-science-has-become-and-the-realization-of-vortice-plasma-ehrkj3
James McGinn / Genius
https://www.cfact.org/2020/09/02/clintel-challenges-icheme-climate-scaremongering/
CLINTEL challenges IChemE climate scaremongering
By David Wojick
The beginning:
The Institution for Chemical Engineers (IChemE) is a prestigious international group of scientists and professionals with over 35,000 members in about 100 countries. IChemE has been conducting what it calls a consultation on its draft Position Statement on Climate Change. This basically means that the members are invited to submit comments. Given that many engineers are skeptical of the climate scare, it will be interesting to see if all of these comments are made public.
The draft statement itself is pure alarmism. They say the science is settled, per the IPCC, and catastrophe looms. Here is the opening paragraph:
“Climate science is established – global climate change is upon us, exacerbated by human activities. IChemE accepts the veracity of the science and its conclusions published by the Intergovernmental Panel on Climate Change (IPCC). To avoid irreparable social, economic and environmental damage, it is essential that we accelerate our efforts to decarbonize our economic systems and stabilize the levels of greenhouse gases in the earth’s atmosphere, if we are to have any chance of limiting the global average temperature rise to 1.5 degrees C, beyond which catastrophic consequences are more likely. Action needs to be global and fair, recognizing the relative differences between regions, both in terms of historic contributions to emissions and vulnerability to the consequences of a warming planet. Chemical engineers are uniquely placed to take action in the industries that contribute to greenhouse gas emissions to arrest and reverse the damage we humans are doing to the life support systems of our single, shared planet .” (Emphasis added).
Not only do they simply sing the IPCC song, they even get it wrong. Nowhere does the IPCC suggest that 1.5 degrees of warming (with one degree already on their books) is a threshold to catastrophe. In fact the Paris Accord target is still 2.0 degrees. The last sentence may explain IChemE’s fervent catastrophism. Its members are positioned to make huge sums of money doing the engineering to decarbonize the world. After all, CO2 emissions are typically the product of chemical reactions (including combustion).
In fact most of the four page draft position statement is nothing but a strategic plan for cashing in on the unwarranted fear of human caused catastrophic climate change.
The CLINTEL letter challenges IChemE to actually do the scientific and engineering analysis needed to back up a reasonable climate statement. That this analysis has not done so makes the present draft what CLINTEL calls an embarrassing “me-too” position statement.
Here is how CLINTEL puts it: “With all respect, the Institution’s draft statement on climate change is an unquestioning, me-too, statement, political in character and lacking in scientific argument, justification or rationale. The document is unworthy of your prestigious Institution. Uniformed ‘me-too’ climate statements do not bring us closer to thermodynamic reality.”
There is more in the article.
Please share this.
David
I’m a fellow of the IChemE.
I can assure you that sharing this risible piece amongst my peers will cement their view of the lunacy of climate change “sceptics”.
Please do. But what is risible about it? Do you believe we are damaging the life support systems of the planet? That is truly risible.
I’m merely a Member of the IET, and my humble opinion is that David’s article is indeed “risible”.
Here’s an extract from a 2011 press release from the IMechE:
The technology needed to cut the world’s greenhouse gas emissions by 85% by 2050 already exists, according to a joint statement by eleven of the world’s largest engineering organisations. While the world’s politicians have been locked in talks with no output, engineers across the globe have been busy developing technologies that can bring down emissions and help create a more stable future for the planet. We are now overdue for government commitment, with ambitious, concrete emissions targets that give the right signals to industry, so they can be rolled out on a global scale.
That still seems to sum up the current situation quite nicely?
Jim,
And precisely what do they propose to do with all the carbon dioxide that will get sucked out of the world’s oceans? Repeal Henry’s Law perhaps?
Philip:
The Earth’s oceans aren’t sat in a lab. They have great depth and are mixed by winds and currents. So no, Henry’s law remains alive and well, just not the limiting factor in oceanic CO2 uptake.
Tony,
My point is not about ingress, it’s about egress.
Philip:
My reply is relevant to both.
There still seems to be no new “Week in review – Science” thread, and comments on the old one are now closed. This seems the most suitable venue for angech’s biweekly Arctic update:
https://GreatWhiteCon.info/2020/09/facts-about-the-arctic-in-september-2020/
3rd lowest in PIOMAS volume:
https://greatwhitecon.info/wp-content/uploads/2020/09/piomas-anom-20200831.png
but firmly in 2nd place across the assorted extent metrics:
https://greatwhitecon.info/wp-content/uploads/2020/08/JAXA-2020-08-30.png
Which does rather make one wonder if the PIOMAS model might be missing something?
Hi Ross and/or Judith,
Since you’re here, I wonder what you make of the conclusions of this recent learned journal article?
https://www.nature.com/articles/s41558-020-0860-7
We find that warming rates similar to or higher than modern trends have only occurred during past abrupt glacial episodes. We argue that the Arctic is currently experiencing an abrupt climate change event, and that climate models underestimate this ongoing warming.
The relative effect of a rise in CO2 is much greater in regions where the warming effect of water vapour is much lower. Water vapour ranges from 10 to 50,000 parts per million .
The greenhouse warming effect of the CO2 400 parts per million is negligible. It is so weak it cannot be measured.
http://www.cristos-vournas.com
The US National Academy of Sciences (NAS) defined abrupt climate change as a new climate paradigm as long ago as 2002. A paradigm in the scientific sense is a theory that explains observations. A new science paradigm is one that better explains data – in this case climate data – than the old theory. The new theory says that climate change occurs as discrete jumps in the system. Climate is more like a kaleidoscope – shake it up and a new pattern emerges – than a control knob with a linear gain.
https://watertechbyrie.files.wordpress.com/2014/06/unstable-ebm-fig-2-jpg1.jpg
Solutions of an energy-balance model (EBM), showing the global-mean temperature (T) vs. the fractional change of insolation (μ) at the top of the atmosphere. (Source: Ghil, 2013)
The model has two stable states with two points of abrupt climate change – the latter at the transitions from the blue lines to the red from above and below. The two axes are normalized solar energy inputs μ (insolation) to the climate system and a global mean temperature. The current day energy input is μ = 1 with a global mean temperature of 287.7 degrees Kelvin. This is a relatively balmy 58.2 degrees Fahrenheit.
The 1-D climate model uses physically based equations to determine changes in the climate system as a result of changes in solar intensity, ice reflectance and greenhouse gases. With a small decrease in radiation from the Sun – or an increase in ice cover – the system becomes unstable with runaway ice feedbacks. Runaway ice feedbacks drive the transitions between glacial and interglacial states seen repeatedly over the past 2.58 million years. These are warm interludes – such as the present time – of relatively short duration and longer duration cold states. The transition between climate states is characterised by a series of step changes between the limits. It caused a bit of consternation in the 1970’s when it was realized that a very small decrease in solar intensity – or an increase in albedo – is sufficient to cause a rapid transition to an icy planet in this model.
Your source attribution (Ghil, 2013) is a bit cryptic. Professor Ghil is a prolific contributor to science.
https://scholar.google.com/citations?hl=en&user=8KDiiDUAAAAJ&view_op=list_works&sortby=pubdate
Can you be a bit more specific?
Thanks.
https://pdfs.semanticscholar.org/3df8/284c921d0194a443411db7a63772b659a79c.pdf
Cheers!
A Mathematical Theory of Climate Sensitivity
https://pdfs.semanticscholar.org/3df8/284c921d0194a443411db7a63772b659a79c.pdf
Apologies Judith.
Didn’t expect that.
The Arctic sea ice has a warming and not a cooling effect on the Global Energy Balance
It is true that the sea ice has a higher reflecting ability. It happens because ice and snow have higher albedo.
But at very high latitudes, where the sea ice covers the ocean there is a very poor insolation.
Thus the sea ice’s higher reflecting ability doesn’t cool significantly the Earth’s surface.
On the other hand there is a physical phenomenon which has a strong influence in the cooling of Earth’s surface. This phenomenon is the differences in emissivity.
The open sea waters have emissivity ε = 0,95.
The ice has emissivity ε = 0,97.
On the other hand, the snow has a much lower emissivity ε = 0,8.
And the sea ice is a snow covered sea ice with emissivity ε = 0,8.
https://www.thermoworks.com/emissivity-table
Also we should have under consideration the physical phenomenon of the sea waters freezing-melting behavior.
Sea waters freeze at – 2,3 oC.
Sea ice melts at 0 oC.
The difference between the melting and the freezing temperatures creates a seasonal time delay in covering the arctic waters with ice sheets.
When formatting the sea ice gets thicker from the colder water’s side.
When melting the sea ice gets thinner from the warmer atmosphere’s side.
This time delay enhances the arctic waters IR emissivity and heat losses towards the space because of the open waters’ higher emissivity ε = 0,95,
compared with the snow covered ice ε = 0,8.
Needs to be mentioned that Earth’s surface emits IR radiation 24/7 all year around.
And the Arctic region insolation is very poor even in the summer.
That is why Arctic sea ice has a warming and not a cooling effect on the Global Energy Balance.
On the other hand it is the open Arctic sea waters that have the cooling effect on the Global Energy Balance.
Feedback refers to the modification of a process by changes resulting from the process itself. Positive feedbacks accelerate the process, while negative feedbacks slow it down.
The Arctic sea ice has a warming and not a cooling effect on the Global Energy Balance. It is a negative feedback.
The melting Arctic sea ice slows down the Global Warming trend. This process appears to be a negative feedback.
http://www.cristos-vournas.com
“The Arctic region insolation is very poor even in the summer.”
Are you quite sure about that?
http://www.physicalgeography.net/fundamentals/images/insolation_latitude.gif
Good answer, if true.
Can you provide a reference please? I keep acquiring such data and then can’t use it – because it is not referred as to source.
I’d like to know why the insolation is highest at the poles at such obliquity, a minimum of 44 degrees at the polar region boundaries? I know the tropopause is lower, but not why, is there less atmosphere above the Poles, seems unlikely with the same gravity holding it on under the same pressure, give or take.
Thanks for any help.
Brian,
I find your request for an authoritative source for what is in effect basic geometry, which can be produced by a competent use of code using an Excel spreadsheet, to be truly puzzling. Is this what we have come to when no one can work from first principles but we are required to cite an authoritative source for everything?
If you still absolutely insist then I recommend that you cite Euclid of Alexandria.(323-283 BC).
I’d like to know why the insolation is highest at the poles at such obliquity,
Would it be when the sun never sets, daylight all day?
Thank you, Jim Hunt.
The above grapheme is correct. It shows the average 24 h insolation intensity and it is correct.
Since at 90° degrees there is at summer solstice 24 h insolation the average is some 520 W/m².
But it is a small spot on the globe.
Now let’s consider the angle of incidence.
On the top of globe at the summer solstice the angle of incidence is equal to the Earth’s Axial Tilt = 23,439°
When the angle of incidence is very low the incident solar flux is not absorbed, but mostly gets reflected from the surface to the outer space.
There is only a tiny 10% – 15% of the incident energy is absorbed.
Now let’s compare with the 30° degrees latitude. There is some 480 W/m² average 24 h incident solar intensity.
But the angle of incidence is 60° + 23,439° = 83,439°
The sun is almost at Zenith there.
When the solar flux is close to the perpendicular, then almost the 80% – 85% of the incident energy is absorbed.
So i will correct the: “And the Arctic region insolation is very poor even in the summer”.
I should write instead: “And the Arctic region insolation absorption is very poor even in the summer.
http://www.cristos-vournas.com
time for CMIP7?
this was from last year, in case anyone hadn’t read it yet
https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2019GL085782
“This ECS increase is primarily attributable to an increased multimodel mean feedback parameter due to strengthened positive cloud feedbacks, as all
noncloud feedbacks are essentially unchanged on average in CMIP6.
However, it is the unique combination of weak overall negative feedback and moderate radiative forcing that allows several CMIP6 models to achieve high ECS values beyond the CMIP5 range. The increase in cloud feedback arises solely from the strengthened SW low cloud component, while the non-low cloud feedback has slightly decreased. The SW low cloud feedback is larger on average in CMIP6 due to larger reductions in low cloud cover and weaker increases in cloud liquid water path with warming.
Both of these changes are much more dramatic in the extratropics, such that the CMIP6 mean low cloud amount feedback is now stronger in the extratropics than in the tropics, and the fraction of multimodel mean ECS attributable to extratropical cloud feedback has roughly tripled.
The aforementioned increase in CMIP6 mean cloud feedback is related to changes in model representation
of clouds.
…
Establishing more rigorously the reasons for these changes and evaluating them against observations is important future work.”
indeed