A friend asked me if a discussion paper published on Statistics Norway’s website, ‘To what extent are temperature levels changing due to greenhouse gas emissions?’, was purposely timed for the next climate summit (COP28). I don’t know the answer to his question.
But this discussion paper is problematic for sure. It was, authored by Dagsvik and Moen, and already in its introduction it claims that it is difficult to explain and predict weather and temperature (giving the false impression that it’s more or less impossible). This claim is both misleading and a distraction – weather forecasting has been one of the most important success stories in science.
Today, the warnings conveyed via YR.no are used all over the world, based on calculations that quantify the effects of physical mechanisms and the way different parts of the atmosphere are connected to each other. In other words, we manage well to forecast the weather and temperature in a good way.
Misunderstood models
A common misconception is that weather forecasts and climate calculations are based on statistical models, such as the kind used by statisticians or in economic forecasts.
Presumably Dagsvik and Moen are used to this kind of model, but they seem to be inexperienced with the models used for weather and climate, which on the other hand are based on the laws of physics.
The physics-based models describe how energy flows through the atmosphere and ocean, as well as how the forces from different air masses push against each other.
The physical interpretation of the global mean temperature
Dagsvik and Moen seem to be sceptical about the merit of estimating the global mean temperature, and their doubt is based on a misunderstood notion that it should have no basis in physics. The irony is that they are no physicists, but many climate researchers, like myself, have a background in physics.
The truth, on the contrary to their claim, is that the simplest physical models for both the greenhouse effect and the earth’s energy balance are precisely based on the earth’s average temperature. See for instance Benestad (2016). In other words, the claim shows a lack of knowledge and is a well-known old argument that I commented on Realclimate.org in 2007.
A common strawman argument
We don’t expect to discern a clear effect of greenhouse gases on local measurements, and mixing up local and global climate is a basis for a common strawman argument. Dagsvik and Moen make this classic mistake when they confuse local temperature measurements with Earth’s global mean temperature.
It is well known within the meteorological and climatological communities that local temperatures are strongly characterised by spontaneous and chaotic fluctuations, and it is also no problem to find examples where temperature correlates with (almost) anything. This is a well-known flaw called “cherry picking“.
The temperatures can nevertheless show ‘artificial’ variations because the thermometers are not evenly distributed over the earth’s surface. We have examined the effect of the geographical distribution of measurements in a study that was cited by New Scientist in 2019, and we found that the uneven distribution of thermometer measurements can give a misleading impression that the perceived warming rate has been slower than the actual global warming.
A small and limited selection is a poor representation of the global state
Dagsvik and Moen write that they only relied on land temperature. In plain language, this means that the data they used represented less than 30% of the Earth’s surface.
It is well known that 30% of Earth’s surface does not provide a good description of global warming, and it is not unexpected that a more limited sample will have a greater impression of random and natural variations, which apparently indicates that random variations play a greater role.
While temperatures provide a measure of the Earth’s climate, it is even better to use the global sea level, which provides a far more reliable measure.
The global sea level acts like the mercury in a thermometer because warmer water expands. Furthermore, the volume of the oceans increases from the melting of land ice.
The rise in global sea level is to a far lesser extent influenced by random variations and reflects a global warming that is not characterised by any natural cycles.
Solar activity provides no alternative explanation for today’s climate change
Dagsvik and Moen claim that recent research indicates that variations in the sun’s magnetic field are of great importance for long-term fluctuations in solar activity. The figure below shows the sunspot number, which is a common proxy for solar activity, and the global mean temperature. The resemblance is striking (not!).
Since the 17th century, the idea that the Earth’s climate is influenced by sunspots has been commonplace, but over time it has proved difficult to explain the variations and the trend observed over the past centuries.
In other words, the debate about the role of the sun is old, and the explanation about the importance of sunspots has not stood the test of time, something I have described in the textbook ‘Solar Activity and Earth’s Climate‘ from 2002.
One would have to massage the sunspot and temperature curves well so that they can even resemble each other (this has been attempted many times, but not in a convincing way).
The most important problem with the sun-climate explanation is that there has been no long-term change in either solar activity or cosmic radiation over the last hundred years that can explain the global warming we are now seeing. In 2013, there was a report in the Guardian about scientific studies that refuted the opinion that solar activity or cosmic radiation should explain climate change.
In 2015, an extensive European research collaboration, COST-TOSCA, produced a handbook that dealt with the question of how solar activity affects the Earth’s climate. None of these studies are mentioned in Dagsvik and Moen’s discussion note, which instead refers to think tanks and well-known climate sceptics.
The gravity of the planets in the solar system creates slow variations
Dagsvik and Moen purports that according to theory and reconstructed temperature data, climate is affected by cyclical variations in the Earth’s orbit, the Earth’s axis and the planetary orbits of Jupiter, Saturn, Neptune and Uranus.
The Earth’s orbit around the Sun is indeed slightly affected by the gravity of the heavy planets in the Solar System, known as the Milankovitch cycles. But the variation in the planet’s gravitational fields lead to very slow changes over many thousands of years, while the global warming we see today takes ten to a hundred years.
One thing we can learn from the previous cycles and the ice ages that they created, is that the Earth’s climate is sensitive to changes in physical conditions. In other words, the extent to which climate is affected by varying physical conditions, whether it is the sun’s radiation, volcanic eruptions, changes in the Earth’s orbit around the sun, changes in the Earth’s landscape or the chemical composition of the atmosphere (which also includes “climate gases”).
Today, the Earth is under constant surveillance from advanced satellites orbiting the Earth (e.g. Copernicus), measurement programs in the ocean (ARGOS floats) and land-based instruments that can measure all physical conditions that can affect our atmosphere. The results from this monitoring show that it is primarily the man-made increased greenhouse effect that is responsible for the observed global warming.
Temperature is not just noise
Dagsvik and Moen try to make the point that it can be difficult to say anything about global warming by comparing the temperature with a so-called ‘fractional Gaussian noise process‘ (FGN), which actually involves a kind of smoothing of a bunch of arbitrary numbers.
When such a framework is applied to local or a limited range of temperature measurements, which are characterised by the chaos laws of the local weather, we also do not expect to see any strong effect of CO2. On the other hand, we expect to see the effect of greenhouse gases when we look at the temperature averaged over the entire globe.
This debate is not new and there was a similar public discussion about long-term memory in the climate system and trends in 2014 on a Dutch website, Climate Dialogue. Although there was no clarification on that at the time, we can say that the discussion is characterised by tunnel vision that does not take into account all our knowledge and how physics plays a role. I also wrote a post on this topic in 2005 (Naturally trendy?), and even if it is a blog, it could provide some clues for Dagsvik and Moen.
One thing we know for sure is that there is always one or more physical mechanisms behind cycles and variations in the Earth’s climate. Even internal variations such as El Niño, which I did my PhD on in 1997, are driven by physical mechanisms such as Kelvin waves, the Earth’s rotation and the interaction between ocean and atmosphere.
Another thing is the totality of the increase in the global sea level, the increased precipitation, snow and ice melting and permafrost thawing. All this can be explained by physical processes and an enhanced greenhouse effect.
In summary, we can say that FGN is a red herring that takes us back to old beliefs that have not proven to be convincing, mostly because those who advocate this idea cannot account for any credible physical mechanisms that can explain how the global warming is a fluctuation in such a stochastic fashion. For the sake of consistency and the lack of a hidden physical mechanisms, it would imply high climate sensitivity – and guess what – there are some physical conditions with a trend that can match the observations: CO2.
We do know that CO2 is a greenhouse gas because we can measure this effect in our laboratories and explain why with the help of quantum physics, which is some of the best knowledge we have in science.
The calibration of the climate models does not affect the simulation of changes
Dagsvik and Moen doubt whether the climate models can be evaluated against historical observations, when the same observations have also been used to calibrate them. It is easy to understand this scepticism, but we must also concentrate in order to keep balance and avoid misunderstandings.
The climate models are adjusted so that they create average temperatures that match the observed average, but are usually not adapted to the observations to reproduce the changes and variations that have occurred. The adjustment is about quantifying the statistical effect of, among other things, cloud formation on climate, within a plausible range.
This calibration (often referred to as “tuning“) is thus misinterpreted in the discussion note as meaning that the models are calibrated against the observations to produce the same variations. There is no blind calibration either, but is based on deeper knowledge of the microphysics of the clouds.
My dilemma as a climate researcher at the Meteorological Institute
There must be great freedom in science to research various things and to communicate the results obtained. With that freedom, there is also a risk that one misses the mark completely and is left with misconceptions.
Since I started working as a climate researcher at the Meteorological Institute in 1998, I have come across a number of erroneous conclusions about climate change which included, among other things, scientific publications. Our job is to be thorough and verify questionable results. It has taken time.
About ten years ago, I became curious if there were any typical common features of scientific results that our verification showed to be erroneous. That led me, together with several colleagues, to do an analysis which we published and which was picked up by Scientific American ‘Why Climate Skeptics Are Wrong‘.
We discovered that erroneous analyses tend to ignore relevant information and are often written by researchers who have experience in fields other than climate. It is also common that they do not evaluate their methods in a sufficiently good way. I also see these traits in the discussion note of Dagsvik and Moen.
The arguments that Dagsvik and Moen present in their note are old and have already been checked out, and it is a little frustrating that this verification has been completely overlooked. It feels like we start from scratch again because of inexperienced and lazy newcomers. The note can also be interpreted as an insult because it suggests that we climate scientists do not know our subject.
The discussion note reveals a lack of knowledge
We assume that people do thorough preparatory work to ensure that the analysis does not completely derail. It is wise to be humble when moving into an unknown professional field, and especially if the results are conceived as being controversial. I hope Dagsvik and Moen are interested in my feedback, especially because they presented their claims through a discussion note.
They show a lack of knowledge and reveal, among other things, that they are not up to speed as they used an old temperature curve (HadCRUT3) which we have long since abandoned. Newer curves (e.g. HadCRUT5, which is also more easily available) are based on a more extensive database and agree better with other data sources (e.g. from satellite measurements and archived weather forecasts).
The lack of knowledge also becomes apparent when Dagsvik and Moen claim that it is difficult to get an overview of the scientific consensus when it comes to climate change. They apparently have not realised that both the UN climate panel and the professional communities in the USA and Europe have written a number of reports to do exactly that (IPCC AR6 2021, NCA 2017, ESOTC2022).
The discussion paper also creates a naïve, superficial perception when it both repeats a number of old well-known climate myths that have been refuted and has a selective reference list with a dominant element of sources that are not scientific and often from climate-sceptic think tanks such as the Heartland Institute and GWPF. Only a small part of their references are from scientific journals that focus on climate research.
If Dagsvik and Moen had better knowledge about their chosen topics, they would have referred to other relevant information, not been so selective and been more critical of their own sources.
Hidden costs with disinformation and various considerations
One challenge is that erroneous research results are costly. We have to spend time and resources to review them and explain why they are wrong. This cost is something we have to reckon with, but it is a waste of time if it is really obvious that the analysis was wrong in the first place.
We generally have limited resources for obtaining and disseminating climate knowledge that will protect lives and values. Thus we should preferably spend our time on more sensible things than debunking frivolous claims that surprisingly come from Statistics Norway.
We know from previous experience that it is likely that such cases will be used uncritically and selectively for political and economic goals. Hence my friend’s question about COP28.
Books have been written about how disinformation is deliberately used to cast doubt on climate change and prevent restrictions on the use of fossil energy sources (e.g. The Heat is On, Climate cover-up, The Merchants of Doubt), and during the UN’s last climate meeting, California’s governor, Gavin Newsom, explained how interests from the fossil fuel industry work hard to prevent emission cuts and undermine climate science.
This issue is therefore not only about academic freedom, because doubt is often used to undermine the climate issue quite deliberately by groups with financial interests.
It’s urgent to fix our climate problem
In August, the global mean temperature was close to 1.5°C above pre-industrial times in August, according to Copernicus. In other words, we are approaching the limits defined in the Paris Agreement, even if it is only a monthly measure, as opposed to a permanent increase.
It is very dramatic because we continue to emit CO2 and other greenhouse gases that intensify the greenhouse effect and create further climate change. We are increasingly receiving shocking reports about how extreme weather creates disasters and tragedies.
In this drama, the Statistics Norway memo creates a misleading impression based on old myths while at the same time dismissing well-established knowledge. In the light of hindsight, we can say that there are many possibilities for publishing a working note and that it is not necessary for Statistics Norway to put its stamp on it.
My experience is that it is depressingly rare that people become wiser from debates about the causes of climate change, but society rather becomes more polarised.
References
- R.E. Benestad, "A mental picture of the greenhouse effect", Theoretical and Applied Climatology, vol. 128, pp. 679-688, 2016. http://dx.doi.org/10.1007/s00704-016-1732-y
Re. “The resemblance is striking (not!).”
These people must have hired Vic to do their stats! Or, they are drinking the same Kool-Aid. The resemblance is absolutely NONstriking and appears nil to me, actually. The actual calculated correlation bears my visual impression out:
r = -0.025
t = -0.33727, df = 171, p-value = 0.7363
Kendall’s tau is even a bit smaller and a bit less significant at:
τ = 0.017
z = 0.32557, p-value = 0.7447
(sunspot data from https://www.sidc.be/SILSO/infosnytot
Hadcrut5 annual data from Met Office)
What exactly are they getting on about except giving an example of how to throw their excrement at the wall?
jgnfld,
Thank you for doing the work. Your illustration is clear, simple, and right to the point.
I should have mentioned I used the annually aggregated data. But going to monthly wouldn’t change much if that us what buddies were using for their “analysis”.
Benestad
I have looked into it in a hurry.
References like Scafetta Yndestad and Svensmark is where I stop reading and discard it exept for folklore and parascientific studies to be orientated there also.
Further cycles cyclings and Jupiter Saturnus Uranus and Neptun.. I have my Pensa on royal and imperial astrology, Tycho Brahe and Keppler were quite much better. taking that art rather for serious the best they could in those days and under those kings and emperors. .
Poor Statistisk sentralbyrå, I say. .That central bureau was also Brahe and Kepplers royal and Imperial departments in their days..
We get very appliciable weather forcasts from Yr.no thank you.
We shall come back to it.
As Fourier–and von Neumann too in essence–showed, given the combination of enough cycles, any trend or wiggle at all can be fully characterized. This doesn’t mean the factors defined in combination have anything at all to do with reality.
Any stats person worth their salt knows this and knows examples of dishonest modeling. Heartland/Tobacco “Institute”/GWPF/etc. come to mind in this regard. Well except in Norway, I guess.
jgnfld
I have a special relation to Fourier- analysis and see that it is very often suggested by irresponsible theoretics. Fourieranalysis is higly appliciable on wind instrument phonetics where I work and on coherent electric and hydraulic and string oscillation, but practically failing as soon as it comes to chaos and rumble “Wolf in Ton”.
I see Fourier methodic discussion on such things. as falsely chosen explainations, methods. and “model conscepts”
Then thanks for GWPF, i did not know of them.
Pollution must be taken and stopped or heavily taxed at its source and the polluter must pay.
I strongly recommend that manifest climate denialism and surrealism is taken that way.
Thank you, rasmus!
“My experience is that it is depressingly rare that people become wiser from debates about the causes of climate change, but society rather becomes more polarised.”
That is because humans are primarily driven by emotion and instinct, not logic. If you give people two assertions, one which is false and stimulates fluffy feelings, and another which is factual and induces anxiety, I would be willing to bet the former would be the most likely to be taken up and the latter rejected. This is not unique to climate change discussions, it happens with different categories of road users in the UK, veganism, any sort of sustainable living advocacy, plus plenty of others.
Thank you, Rasmus! IIRC, this is in line with my more superficial criticisms when D & M was first raised here on RC. The (deliberate?) ignorance of physical mechnisms in favor of purely statistical argumentation, and also of the relevant literature in favor of what I might call “brown” lit instead, is all too characteristic of folks who are, as Dr. Oreskes put it, “Merchants of Doubt.”
Although, to be fair, I don’t think that “merchants” really gives enough credit; doubt is not only their commodity, but also in many cases their construct. So they are often “Contractors of Doubt,” as well–even if, as the late, great Pete Seeger said in another context, the product is “all made of ticky-tacky.”
I agree, except that “all made of ticky-tacky” is properly attributed to Malvina Reynolds as the original singer and writer of “Little Boxes.”
Hi, actually weather, climate and Earth-system models are not entirely based on the laws of physics, as with rising numbers to the later parametrizations become ever more important preventing Earth-system models to simulate the Earth system. Especially with the new trend of emergent constrains making models increasingly useless to simulate the coming warming with all the feedbacks kicking in which have to be simulated on a local level. 120 wrong models are of no use, we need one that is functioning! And parametrizations and emergent constrains are the dead end of models…
Sorry, but humanity needs a working model as climate warming and the collapse of our biosphere is now going out of control with ECS maybe even at current GHG levels becoming a runaway climate warming…
JU: weather, climate and Earth-system models are not entirely based on the laws of physics, as with rising numbers to the later parametrizations become ever more important preventing Earth-system models to simulate the Earth system. Especially with the new trend of emergent constrains making models increasingly useless to simulate the coming warming with all the feedbacks kicking in which have to be simulated on a local level. 120 wrong models are of no use, we need one that is functioning! And parametrizations and emergent constrains are the dead end of models…
BPL: Look again.
https://bartonlevenson.com/ModelsReliable.html
Dear Barton Paul,
in their recent article
https://www.frontiersin.org/articles/10.3389/ffgc.2023.1150191/full
that I have cited elsewhere, Makarieva et al. object that (in my understanding all currently available) climate models suffer from an unjustified simplification that causes insensitivity of their projections to changes in water cycle intensity.
In my opinion, this is a very serious objection that can and should be addressed primarily by professional climate modellers among the moderators of this forum, rather than by amateurs participating in discussions herein.
Interestingly, another article comprising also a quite sharp critique with respect to reliability of model projections and predictions
https://www.pnas.org/doi/10.1073/pnas.1906691116
says
“How can we can reconcile our dissatisfaction with the comprehensive models that we use to predict and project global climate with our confidence in the big picture? The answer to this question is actually not so complicated. All one needs to remember is that confidence in the big picture is not primarily derived from the fidelity of comprehensive climate models of the type used to inform national and international assessments of climate change. Rather, it stems from our ability to link observed changes in climate to changes derived from the application of physical reasoning, often as encoded in much simpler models or in the case of the water cycle, through a rather simple application of the laws of thermodynamics.”
In this case, it was an article written by prominent clime modellers.
My question to the moderators is:
Can the “simple application of the laws of thermodynamics” mentioned by Stevens and Palmer be correctly understood as an oversimplification that does, in fact, represent a serious problem of the present climate models?
So far, it is my understanding to the objections raised by Makarieva et al.
Greetings
Tomáš
Interesting link thanks BPL, It did make me go back and look at the 1896 paper again. I am curious why you think Arrhenius says the arctic will warm faster than the antarctic when his numbers seem to say the opposite, admittedly only by a small amount and he doesn’t really go that far south.
He does say the northern hemisphere will heat more than the southern due to the land/sea ratio difference
Also a reminder that at 420PPM we should be at 3.3 degrees above pre-industrial temperatures
I believe we can run models based on what we know how to model, note what’s been parameterized and what’s been held constant, and use the results as a baseline, from which we can consider what may actually happen given what we didn’t include in the model.
Jan Umsonst: “ Hi, actually weather, climate and Earth-system models are not entirely based on the laws of physics,[…] Sorry, but humanity needs a working model as climate warming</i?"
Climate is not weather Jan. Weather is dominated by short-term chaotic nonlinear interactions – hence it is difficult to explain ALL of them of laws of physics, if these cannot be applied with enough temporal and spatial resolution and cannot account for chaos and non-linearity.
Climate, on the other hand, is a multi-DECADAL average of weather – and the process of averaging, typically over the scale of 30 years – averages out these short-term, often dominated by chaos and nonlinearity, fluctuations – so what is left behind after that year averaging are the laws of physics, inherently more predictable over the scale of decades than exact local weather at your location several weeks from now.
So the issues with improving weather predictions are completely different than those facing climate projections. As a result, you cannot use the former to criticize the validity of the latter.
Dear Dr. Benestad,
Thank you for your article.
Some time ago, I proposed another case for possible critical analysis:
https://www.frontiersin.org/articles/10.3389/ffgc.2023.1150191/full
The authors of this article suggest that convective parametrization (that is allegedly a basic assumption in all current climate models) is in fact inappropriate:
“An exact estimate of what happens when the evapotranspiration and the latent heat flux are suppressed on a certain part of land area requires solving the problem simultaneously for the radiative-convective transfer and the temperature profile. This problem is too complicated for modern global climate models to address, therefore they apply the so-called convective parameterization. Convective parameterization in climate models postulates the (generally unknown) value of a critical temperature lapse rate instead of solving for it. While the numerical simulation is run, “whenever the radiative equilibrium lapse rate is greater than the critical lapse rate, the lapse rate is set equal to the critical lapse rate” (Ramanathan and Coakley, 1978). Therefore, by construction, global climate models cannot provide any independent information about the climatic effect of evapotranspirational cooling—that should be manifested as the change in the global mean lapse rate—besides what was fed into them a priori via convective parameterization.”
Could perhaps the RC crew prepare a similarly thorough analysis of this article?
It is my feeling that the objection raised by authors is more serious than assertions that you analyzed and criticized in your present analysis, and might therefore deserve a comparable or even higher attention from
the side of RC scientists.
Best regards
Tomáš Kalisz
hello Tom,
It’s mentioned in Benestad’s mental picture:
https://link.springer.com/article/10.1007/s00704-016-1732-y
the “entanglement between the greenhouse effect and the hydrological cycle, where reduced energy transfer associated with increased opacity is compensated by tropospheric overturning activity”
to some degree.
Conceptually: The opacity effect minus the overturning effect gives the apparent greenhouse effect intensity. Together these yield the diffuse radiation signature observed from space.
Traditionally, educational emphasis tends to be on the opacity effect, relegating overturning to a secondary consequence controlled solely by temperature and emergent phenomena. This simplification, while effective for pedagogical purposes, overlooks the essential relationship between these components.
The computationalists will submit that the physical limit of overturning in a case with total freedom is set somehow by clausius clapeyron CC relations, vertical mixing, atmospheric heat transport, and the associated remote radiative cooling to space. These, together with opacity, form the non-equilibrium steady state condition of surface air temperature and the diffuse outgoing radiation.
However, practical limitations arise, with the actual constraint being the availability of moisture in space and duration from the surface, rather than the capacity of air derived from surface air temperature. CC associated deficits are only increasing i.e. the relative humidity is going down, with subsequent impacts on the ability of the overturning to erode the greenhouse effect intensity. The atmospheric heat transport-by-product is not keeping pace with the opacity as one might expect. This is causing great discomfort in computing the combined water-vapor-lapse-rate effect + cloud fraction. In a forcing-feedback paradigm, the delta lambda is not straightforward.
Escaping from this virtual reality, it has been said that the wilderness of a healthy soil, too complex for human comprehension, can yet be husbanded, can benefit from human care, and can deliver incalculable benefits in return. Mutuality of interest and reward is a possibility that can reach to any city
backyard, garden, and park, but in any place under human dominance – which is, now, virtually
everyplace – it is a possibility that is both natural and cultural. If balance is the ruling principle and a stable balance the goal, then, for humans, attaining this goal requires a consciously chosen and deliberately made partnership with natural reality.
No conservationist would disagree. Fighting against nature using model parametrization and supercomputer, while interesting and useful, has resulted also in substantial blindspots and collateral damage which should be considered prior to denying the extent of humanity’s influence. I think this is what your reference is getting at.
Is it your concern that models are lacking an interactive land surface or are programmed with perpetually-wet forest canopy or aquaplanet conditions?
PS I think there may be a dynamical reason for reduced RH in response to warming even in the aquaplanet case? – something authored or co-authored by Tapio Schneider? I haven’t dug into it, though.
to concerns:
it\s the total refusal to know role of evapotranspiration in the water budget regime and climates. This is a new condition which hasn’t been the case historically. Local vapor budget controls have become incredibly unfashionable to discuss; although they act in addition-to and feed-back-upon dynamical factors.
It’s old news in climate science, since at least 1982. And it’s much older in terms of common knowledge. Drying out the land makes the soil hotter.
try it.
No need for misguided Norwegian statistics and all that.
Local control was formalized conceptually by Shukla and Mintz 1982 in the extreme and widely accepted
https://www.science.org/doi/10.1126/science.215.4539.1498
Free access is available elsewhere.
“Figure 2 shows the calculated land surface temperature. North of about 20°S, the land-surface temperature is about 15° to 25°C warmer in the dry-soil case. There are two reasons for this: (i) there is no evaporative cooling of the land surface (which, in the wet-soil case, amounts to 125 W/m2 when averaged between 20°S and 60°N) and (ii) there is a large increase in the heating of the ground by solar radiation (an increase from 172 to 258 W/m2 when averaged between 20°S and 60°N). This is because the calculated cloudiness is less when there is no land-surface evapotranspiration. In the dry-soil case the net radiational heating of the land surface is balanced entirely by the conductive-convective transfer of sensible heat to the atmospheric planetary boundary layer, the lowest 1 to 2 km of the atmosphere. (This heat transfer to the atmosphere is 169 W/m2 in the dry-soil case, compared to only 21 W/m2 in the wet-soil case, when averaged for the land surface between 20S and 60°N.)”
Also demonstrated is global pressure gradient effects, and a climate system much more extreme overall under continental moisture restriction.
Shukla and Mintz conclude on the impact to real climates, as it relates to the mechanisms which desiccate the catchments: “they do, if they are of large magnitude and large horizontal extent”.
In summary, the only real dispute can be if humanity has ability to influence such factors in magnitude and extent to be worthy of consideration, and from my perspective it is obvious that we do. In general communication of climates the impact is dismissed altogether. This is unwarranted.
Related factors are conceded indirectly, sometimes, in the current fashion of demonstrating the effects of changes to the overlying atmosphere i.e. CO2 doubling experiments and so on. These impose “dynamical constraints” + feedbacks on land-ocean temperature contrasts and the vapor budgets.
e.g. Byrne and O’Gorman 2013 and later works https://agupubs.onlinelibrary.wiley.com/doi/full/10.1002/grl.50971
I should mention that in land use & surface change models the framing of vegetation as the primary control is misconceived and may partly explain the confusion. Consider the soil first and foremost, which imposes the ET limit. You can convert forest to field, or replenish the trees or whatever, but these observable conduits do not describe the soil moisture bucket.
Some suggest fatal flaws in land surface model interpretation of land-use change which helps to align closer with what’s perceived and measured on the ground for real. “Results showed that all LSMs underestimated ET changes by about 55%–78%” https://iopscience.iop.org/article/10.1088/1748-9326/ac38db
I know at least one or more early models worked that way (parameterizing convection via a constant convective lapse rate) – eg., the Manabe and Strickler work I pointed out, if I recall correctly; however, this did not mean they believed that was an accurate assumption; it was progress made toward a more complex model. The input lapse rate could be changed to see what happens. Anyway, I’m not sure exactly how the newer models handle things, but the fact that they produce opposing changes in lapse rates in different latitude bands (which can be understood in mental models (human minds) based on physics) suggests to me that the criticism may be outdated (???)
@ Thomas Kalisz
I have the impression that you are reading inferiour schoolbooks and followimng less qualified teachers of climate and meteorology here.
In Norway being a global sea faring nation and further hihgly related to the change of oceanic winds in the atlantic antipassat and easterly highpressure continental winds by the arctic and Russian winter, together the western european annual monsune…. and the miniatures of it in the daily shifting sea- breeze with afternoon showers….. I may have got it all from more enlighted sources and teachers.
I was once up in a plane in the north German flatlands. The pilot spoke of up and downgoing summer cumulus winds, that experienced glider- pilots have to know about. and has to judge by ground patterns under the sunshine and shadows, urban meadow and forestlands That flight did sustain what I learnt about air in school physics, and falsifried Thomsa Kalisz`suggestions about the same.
. As my highschool textbook of general physicas was also written by the fameous meteorologist Olaf Devik assistant of Kr. Birkeland. .
I later got the fameous “Atem der Erde” by Theo Löbsack in translation. Who was an experienced glider pilot and especially good on thunderstorms and tropicalo hurricanes , tornadoes, föhnwinds, weatherfronts, and lapserates.
Löbsack became my handbook of meteorology ever since, and in the climate dispute.
Thus better seek up and stick to and try and further the Humboldt and Helmholz, and Birkeland Herz Bjerknes / Devik school of physics geophysics,, on cyclings, and on meteorology.
As I am rather able to disuss and to understand aerodynamics and aeronautics, hot air balloons thunderstorms , cumulus altus scirrus , the halos and the wheaterfronts…..the jetstreams and the tropopause. the isoterm layer.
And take it out from that and not from the experts.
I am able to follow both Benestad & Yr. no & DMI,dk and IPCC the Paris convention that way. I can just throw an eye to the heavens and on my local special eyemarks of weather signals, in nature, , and I get it.
I have even another formula:
Formula:
All responsible weather prophets whoose words can be believed in…., are also looking up the Yr.no weather forecast & weather maps and DMI.dk weather at sea before they dare to predict and even to ask.
I repeat….!
Those fameous reliable, folk weather prophets (such as me for instance) regard the national meteorological institutes more and more as their very best colleagues that have become better and better all the way, ……..
….. and still know how and where and on what to beat them.
And If you cannot beat them, join them.
Take them for serious, and they will also take you for serious. .
The meteorological institute here where I live has for decades been the only daily updated national mass media program about what goes on in real nature.
Thank you for such a thorough and well reasoned explanation.
We don’t expect to discern a clear effect of greenhouse gases on local measurements
============
So what you are saying, that greenhouse gases have no effect on my weather or my climate.
That applies across the world.
Yes it does, but on a lokal smale it’s not si clear and it is masked by regional variations. The global sum though, is very clear.
Have always thought that elevated GHG levels at the surface contribute significantly to the urban heating islands via strong back radiation
“While temperatures provide a measure of the Earth’s climate, it is even better to use the global sea level, which provides a far more reliable measure.
The global sea level acts like the mercury in a thermometer because warmer water expands. Furthermore, the volume of the oceans increases from the melting of land ice.”
Interesting. What Rasmus seems to be saying is that global sea level might very possibly work as a more reliable proxy for global temperatures than thermometer readings. If that is indeed the case, then it’s possible to infer that, unlike thermometer readings, global temperatures have been steadily rising since the 19th century, as have sea levels, with no significant interruptions at all, from then to now. What makes this especially interesting is the very strong apparent correlation with CO2 levels, which have also steadily risen over the same period.
I’ve never run across this idea before, and wonder if anyone other than Rasmus has ever proposed it.
Note for all the people who have spent hours of their lives explaining the niceties of statistical reasoning to Victor:
“What Rasmus seems to be saying is that global sea level might very possibly work as a more reliable proxy for global temperatures than thermometer readings.”
Come on, people. Think about that.
As I’ve said many times now, even the experts have failed to consistently convey, clearly, that GMST is an effect, not a cause, and that it is a proxy for the energy increase caused by CO2.
And that, I think, is because everyone wants to ‘splain about detailed stuff to show their expertise, and so ignore/play-along-with the misunderstandings of basic physics, and what the words actually mean.
And that shows up here with the trolls, and also with the people doing pretend science as in the paper under question, and Soon and the others. Yes, Rasmus is correct, it is a distraction, but that is the intent, and getting sucked in to their framing of the issue means they win.
Before providing a detailed critique of their output, how about requiring them to answer the simple question:
If it’s the Sun, cosmic rays, whatever… what happened to the increased system energy caused by an increase in CO2 molecules in the atmosphere?
That’s how science works. Everyone here knows that, but just lets it slide.
“If it’s the Sun, cosmic rays, whatever… what happened to the increased system energy caused by an increase in CO2 molecules in the atmosphere?”
Excellent question!!
Dear Victor,
Thank you for citing the two sentences from Rasmus’ analysis.
I think that the idea of the sea level as a thermometer for average global temperature is a rare gem and I highly appreciate it, because it must, as you mention, amazingly smooth every insignificant local or temporal temperature fluctuation.
Therefore, I tend to agree with you that it might be the best available parameter for a reliable assessment of long-term global temperature trends and correlations thereof with various factors that may affect global energy balance.
Similarly as you, I am also curious if this idea was already published elsewhere or if Rasmus’ article is perhaps the very first occasion when this crystal clear metaphor was presented to the public. Global ocean like mercury in a thermometer bulb. If Rasmus just dropped it herein in a sudden inspiration – wow.
Greetings
Tomáš
We had most of these here on RC, some even recently:
– arrogance of coming from another discipline and thinking that their expertise automatically transfers to climatology (Robert H Essenhigh, a mechanical engineer, claiming that water vapour does between 97- 99%, of LW absorption)
– in fact, thinking that they are more qualified, since they see things with “fresh eyes”, untainted by previous knowledge and not the part of the derided “consensus”
– thinking that they don’t need physics to distinguish between causation and spurious correlations
– ignoring the existing body of knowledge, either because they can’t be bothered to study it, or because in their hubris, they don’t think they need it (R. Cutler, T. Kalisz, M. Shurly)
– lying with a straight face about it (e.g. Victor claiming there has been no increase in SLR)
– reinventing the (square) wheel – they don’t know that their brilliant new ideas have been “discovered” by other deniers, and disproven, many times before
– cherry-picking the data to fit their thesis
a) by using an outlier as a reference point – e.g. the warmest month in one of the strongest El Nino in 1997/1998 – to count from that the “hiatus”, i. e. “ how many years and months since the end of global warming“, or using the record low Arctic ice in 2007 to claim “continued Arctic sea-ice recovery” in 2008 (Tim Ball)
b) by using only the periods in which trends are what they wanted them to be
– not seeing the difference between mechanisms shaping weather and climate (R. Cutler)
– using data from some part of the Earth as representative to the global average (Trump and RC deniers disproving global warming because somewhere in the world there were a few colder than usual days)
And of course, the steadfast refusal of admitting of being wrong.
Piotr,
Yep. You nailed it. I encounter that every day on ResearchGate (a legitimate venue, but recently infiltrated by AGW deniers).
Pjotr
I tend to see that Thomas Kalisz is able and trying to adapt. He seems hitghly trained and scilled rather on Humaniora from his standpoint in Brno Moravia , That is next to Praha in Bohemia, the High Tatra, and the Wiener school and late empire quite next by, that has been important and delivered Wiener classics both in music and in science. Mozart and Einstein even scored from Praha.
Wiener and Moravian classics is not heavy metal and not country & western. .Think rather of Smjetana and Dvorak. Both very popular and fameous.
In science they have scored by Mendels beans, Sigmund Freud, the Chladni figures Copernicus, and <Keppler, even Tycho de Brahe, as the imperial court astrologists, that means ministers of environmental threat and affairs & destrinies.
In recent time, Moravia has come up with many more. Kurt Gödel, Ernst Mach, Karel Capek and Thomas Masaryk.
Better adress to who i is, and what he delivers. Then you can discuss and tell who you really are and what you believe along with that and due to what.
Turn down our your perverse provincial state religion "Make America great again" and "Bigger and better over there in the states!"
In Re to
https://www.realclimate.org/index.php/archives/2023/11/a-distraction-due-to-errors-misunderstanding-and-misguided-norwegian-statistics/#comment-815683
and
https://www.realclimate.org/index.php/archives/2023/11/a-distraction-due-to-errors-misunderstanding-and-misguided-norwegian-statistics/#comment-815697
Dear Piotr,
If you mention me, please let me add a comment.
I do not think that asking questions is the same as “ignoring the existing body of knowlledge”.
And if you mean by the “existing body of knowledge” your assertion that water cycle intensity must play a negligible role in Earh surface temperature regulation because major part of the latent heat flux returns back to the Earth surface, I cannot remember when you admitted that in parts 1-4 of his analysis,
https://www.realclimate.org/index.php/archives/2023/09/unforced-variations-sep-2023/#comment-814201
Barton Paul showed quite convincingly that you are wrong.
Dear Barton Paul,
A polite reminder that I still await your confirmation that the unfortunate reversal of the outcome of your analysis was purely unintentional, caused by a mistake in part 5 of your analysis
https://www.realclimate.org/index.php/archives/2023/09/unforced-variations-sep-2023/#comment-814205.
It is still my understanding that although you have asserted an opposite, your analysis has in fact showed that even in case that the assumed water cycle intensity increase would have been accompanied by a commensurate absolute humidity increase, the greenhouse effect of the increased water vapour concentration cannot fully compensate the cooling effect of the increased latent heat heat flux.
Thank you in advance and greetings
Tomáš
Well done, thank you Rasmus. They seem to have been suckered by a LOT of the champion climate deniers, with (perhaps) special emphasis on Willie Soon (all that solar stuff) and Nicola Scafetta (and his crack-pot ideas about the orbits of Jupiter and Saturn).
I think, maybe, we’ve reached the point at which this kind of nonsense will no longer work very well.
tamino,
I don’t agree that it will no longer work. Old anti-AGW and anti-greenhouse effect arguments are alive and kicking among the non-scientists. Sadly, the sheer weight of pseudoscience propaganda seems to be strengthening the antis political position. I’m not optimistic.
Another newly published paper, which states that the measurement error in the data for global temperature from 1900 to 2010 is so large that the data is unusable, could also be analyzed here:
LiG Metrology, Correlated Error, and the Integrity of the Global Surface Air-Temperature Record
https://www.mdpi.com/1424-8220/23/13/5976
[Response: Already well critiqued here: https://diagrammonkey.wordpress.com/2023/08/15/at-the-molehills-of-madness/. – gavin]
FWIW 271 comments in pubpeer
https://pubpeer.com/publications/391B1C150212A84C6051D7A2A7F119#5
Thanks for the link, I will read the comments.
The DiagramMonkey post that Gavin points to references a post I made at Skeptical Science.
https://skepticalscience.com/frank_propagation_uncertainty.html
Make sure you read DiagramMonkey’s earlier post (also referenced in the post Gavin links to) on Pat Frank’s earlier work, where DiagramMonkey coins the term “hagfishing”. The description of how Pat Frank responds to criticism is spot-on.
https://diagrammonkey.wordpress.com/2019/10/09/hagfishing/
And last (I wish) but not least, there has been some discussion of the recent paper at PubPeer. Pat Frank goes into weapons-grade hagfish mode, showing rather conclusively that he has no idea what he is talking about, and is more or less completely resistant to reasonable discussion.
https://pubpeer.com/publications/1C5082B870CED35BA227539F138667
Thanks, Bob, for the hagfish thing. I’ve been looking for that differentiation from Gish Gallop, and I keep thinking there is a more formal informal fallacy term but I just can’t remember what it is.
Literary digression: “At The Molehills Of Madness,” IMO, is an absolutely brilliant title.
In terms of timing, this pile of nonsense from Dagsvik, Fortuna & Moen has been bobbing about for some years in that the basis of it appeared back in 2015 in an item in a Norwegian weekly newspaper, the item according to a web translator being titled ‘Misleading and condescending about temperature research’ and it did get a mention in the RealClimare UV of the day.
It galls me that they call this a “discussion paper,” which according to the very first page is supposed to be a *research* paper. I don’t see any research at all; regurgitating somebody else’s ideas isn’t research, and when those ideas are long-refuted it becomes propaganda.
As a non-specialist myself, I have to admit that my impression of climate science had been that it was based on statistical models (but based on physical principals and data, of course). Although I don’t really see why that would be a problem. I assume that the point is that modern methodology includes both modelling of trends in global mean surface temperature as well as weather modelling. I’m not really sure why that would be necessary or even desirable, if so. Weather modelling would, I assume, be essentially computational geophysical fluid dynamics at various length and time scales. But GMST would be simply a slowly varying contribution that could be assumed constant at those scales. On the other hand, weather phenomena simply become higher order noise which would not contribute to temperature trends. I wouldn’t think it would be efficient to include all these phenomena in one model. There may be advantages that I don’t see, however. Assuming that my impression is accurate.
Oh, for pete’s sake, start here: Gavin Schmidt:
The emergent patterns of climate change, [I know it’s out of date, but you have to start somewhere and this is as good as it gets.]
https://www.youtube.com/watch?v=JrJJxn-gCdo
If you want to fiddle with weather data as it reflects warming/climate change, you could do worse than this (Masters & Henson):
https://yaleclimateconnections.org/topic/eye-on-the-storm/
Comment section is a little hyperactive, but when weather meets climate, these guys know what they’re talking about.
JD: my impression of climate science had been that it was based on statistical models (but based on physical principals and data, of course).
BPL: You can do statistical models like that, but the big atmosphere-ocean coupled general circulation models generally run on straight physics–pick an initial state, then apply conservation of mass, momentum, etc. along with radiative transfer and convective physics, etc. I have an oversimplified explanation of simple column models here if you want to get into this stuff:
https://BartonLevenson.com/RCM%20%Tutorial%20%V2.rtf
Thanks, Barton, unfortunately this link doesn’t work. In any case, since it may not be clear exactly what I am asking, I am not interested in a simplified explanation but in the technical details of the derivation and construction of general climate models: For example: how are the governing equations structured? What are they? What physical effects are excluded or included? What assumptions and approximations are made? What are the initial conditions and boundary conditions? What numerical methods are used in the computations? I understand your comment and am very familiar with governing equations such as Navier Stokes. but I am happier to see exactly which governing equations are used and how. Presumably, there are monographs which cover this material? This is for my own personal interest I have no interest in attempting to construct such a model myself. Just interested to see how it all works.
Not sure there is a nice high level description of any model that would answer your questions. The answers are probably somewhere buried in multiple papers. Or, this page might point you to at least info on one GCM: https://www.giss.nasa.gov/tools/modelE/
There’s a book on the development of modeling, called “A Vast Machine.” It’s lengthy, and a bit aside your main line of inquiry, but fascinating IMO, and if you are like me and appreciate a pretty full contextualization, very worthwhile.
And to your point, it would provide multiple entry points into the literature, which is where you would be likely to find the sort of “monograph” you are looking for.
https://www.amazon.com/Vast-Machine-Computer-Politics-Infrastructures/dp/0262518635
Jonathan, you can find information on the University Corporation for Atmospheric Research’s Community Earth System model .
There should have been a “here” in the above linked to https://www.cesm.ucar.edu/
Thanks, Steven, and others responding. These look promising. I’ve also pulled Manabe’s 1969 papers which look to be as good a place to start as any. Although 1969 was in the Stone Age computationally. About 1800 cites in Google Scholar on these so the NASA page will hopefully whittle that down.
Imagine a GCM-type climate model where all transient eddies (turbulence, non-static waves) are inhibited. A steady-state flow could be attained (aside from externally-forced cycles/etc.) which balances flows of energy, mass, and momentum, thus attaining and then maintaining an equilibrium climate (when forcings are not changed).
However, that may n0t be the same equilibrium climate that would be maintained by the real, messy chaotic weather processes. Eg., presumably there would be no eddy-driven jet without any eddies. My **guess** is that without ‘weather’ as such, there might be more cloud cover near the ITCZ and less winter precipitation at high latitudes and the polar regions would be colder – but I’m not sure.
In principle, the effects of transient eddies could be parameterized, as the smaller ones must be given the model resolution limits.
ie…
There is the phrase “Climate is what you expect, weather is what you get.”
But of course, we do expect to get weather. We expect (depending on location, time of day, time of year, phase of ENSO, etc.) to have some downpours, some cloud-free days, some gusty days, some cold fronts, etc., and we expect to not see it all coming well in advance (lead-times vary depending on the specificity and nature of the event).
This post is of the character of “thou doth protest too much”. Yes, it’s clear that sunspot arguments of natural climate change are useless, and that assigning randomness is a dead end. Yet, it’s also evident that the state-of-the-art in climate science is far from being able to model all the variability that is being observed in temperature measurements,. Attacking strawman arguments such as sunspot models doesn’t address the ugly parts of current understanding. This the actual problem statement (from an upcoming workshop called “Confronting Earth System Model Trends with Observations: The Good, the Bad, and the Ugly”):
It’s the easiest thing in the world to beat down incompetent scientific arguments, but much more difficult to address the actual limitations in what are considered the consensus models. There are several other paths of promising research that are coming out of NASA and other groups that deserve much more attention than the brain-dead sunspot argument that keeps popping up. The analogy is akin to drawing attention to the delusion of flat-earthers when addressing an unsolved geophysics problem — don’t lump all them together!
PP: it’s also evident that the state-of-the-art in climate science is far from being able to model all the variability that is being observed in temperature measurements,
BPL: Statistically, CO2 accounts for 85% of the variance of temperature anomalies from 1850 to 2019. That means all other causes, known and unknown, can only account for 15% of it during that period. Adding solar constant, aerosols, etc. I get up to about 87%, which isn’t great, I agree. But we know enough about what’s happening to know that we have to take action yesterday.
Here’s the geophysics that few in climate science take seriously. The equatorial ocean thermocline is the most delineated as a function of latitude and has the characteristic of a less dense warmer upper layer separating a mode dense colder deeper volume, This density difference manifests as a highly reduced effective gravity environment that should be extremely sensitive to external forces. Consider that the surface layer by itself is sensitive to tidal forces capable of shifting the sea-level height by meters — this is a well-accepted phenomenon understood for ages. But now consider that the same tidal forces acting on the subsurface layer should be able to shift the thermocline by 100’s of meters based on just the scaling of the reduced gravity environment across that interface. And this is what is observed by deployed instruments — indeed, subsurface waves that tall do occur (the size of skyscrapers) and have the effect of rearranging the stratified waters with respect to the surface, which is then exposed to the atmosphere thus leading to El Nino & La Nina cycles.
But why is this mechanism never discussed as a cause of climate variability, and instead all we see is beating down the strawman of sunspot cycles? Seriously, this is basic physics we are talking about, and only a few climate modelers are considering tidal effects and the rest are ignoring it.
Tidal acceleration approximately increases in proportion to distance from Earth’s center (as long as it is a small fraction of the distance to the tide-raising mass (Moon, Sun);
the ratio of tidal acceleration to Earth’s gravity…
(Earth’s gravity increases up through the core, then nearly constant to the surface, decreases as 1/r^2 beyond that)
…, * radial distance,
is proportional to the bulge (perturbation) of geopotential surfaces, ie, equilibrium tidal bulge height (high tide – low tide at equator if moon/etc. is in equatorial plane)
This is roughly constant from the sea floor to the stratopause at least.
to be cont…
(I have read that the tides, wind, and plankton contribute similarly to oceanic mixing.)
Patrick,
Unless I misunderstood what you were saying, tides are proportionate to the inverse third power of distance.
Yes, I should clarify:
For two spherically symmetrical masses M0 and M1, with their centers p0 and p1 seperated a distance R (along the x-axis), the tidal acceleration g’ caused by M1, at distance r0 from p0, …
(assuming M1 is contained within a space outside the radius r0, and r0 is much smaller than R)
can be approximated as proportional to r0 / R^3 (and their is an angular dependence relative to the x-axis)
I was refering to r0 above.
also, the description of the tidal bulge height depends on an approximation, applicable for g’ much smaller than go (the gravity caused by M0, or that part of M0 contained within radius r0), so that the vertical gravity g0 – g’vertical is approx = g0, then the slope of the equilibrium bulge is approx. = g’horizontal / g0, and integrating slope over horizontal distance (proportional to r0) gives the equilibrium bulge height. (not including the gravitational effect of the tidal displacement of mass itself)
The other way to think about the physics involved in tidal-related forces is that they modify the angular momentum of the spinning Earth. This is well-characterized by measurements in the differential length-of-day (LOD) where tidal cycles account for 99% of the fastest variations (highest acceleration/ deceleration) in the rate of rotation. What this does to the solid earth is obvious, but to the ocean it’s much more dynamical as it will set sloshing waves in motion, with the subsurface layers much more sensitive than the surface as the heavier deeper waters with their greater inertia will slide underneath the lighter surface waters if the spinning Earth decelerates. There’s really nothing mysterious about this — an earthquake will create a tsunami as the Earth temporarily creates a LOD glitch in its revolution rate, leaving the volume of water thinking it’s still inertially rotating at its average rate and thus generating a huge soliton wave as a response. Likewise, subsurface tsunamis are continuously occurring due to long-period tidal cycles, it’s just that the non-linear dynamics hasn’t been properly decoded. The sloshing back-and-forth that’s the hallmark of ENSO generates standing subsurface waves that have fixed nodes due to the spatial boundaries of the ocean volume, but the period is a non-linear modulation of the input forcing cyclic tempo. I solved this problem in Chapter 12 of Mathematical Geoenergy back in 2018, but it seems that climate scientists would rather beat down hypothetical sunspot strawmen than address the practical geophysical fluid dynamics. It’s really not that challenging mathematically to map measured LOD variations to ENSO cycles if one understands the nonlinear modulation required. And again. it’s not shifts in the wind, which is almost preposterous to consider when the actual mechanism is staring us in the face,
If you scale displacement as 1/(reduced gravity), then the displacement would tend toward infinity within well-mixed layers.
My understanding is that significant energy goes into internal tides via conversion from the energy of surface/whole ocean tides, (??) maybe at continental shelves/slopes and seamounts, etc…(?)
Patrick said:
That’s what makes it difficult to quantify — the amount of gravity reduction achieved is essentially dependent on the density difference. What value to give to the displacement scale? It certainly must be around 100X as that is the size of the subsurface tidal waves as compared to surface tides. As comparison, the Moon’s reduced gravity is 1/6th that of the earth. I think the oil/water effective gravity reduction is between 1o and 20X, which leads to this behavior in a wave machine:
https://youtu.be/Wj2OX1BEYCw
(Note that the equatorial region has the most distinct thermocline delineation, which may be partly responsible why the amplification is most pronounced there)
Now, it seems that there is consensus that these subsurface waves (often referred to as upwelling) are responsible for the transfer of heat to/away from the surface and thus the alternating El Nino and La Nina episodes, but that wind is the driving force. This is part of a belief system, as there is no way to do a controlled experiment on this scale to see if wind can actually force these subsurface waves. And from temporally resolved measurements, there are indications that the shift in the wind is not a leading indicator, but a lagging indicator. So the wind is more of a result of the temperature differences causing an atmospheric pressure gradient to be generated and thereby creating winds as it blows from high pressure to low pressure. That’s why it would closely lag, but giving the impression that changes in wind are creating the El Nino or La Nina episodes.
My point is somewhat tangential to yours; I don’t dispute the size of the internal waves; I’m just arguing that large displacements of internal material surfaces would tend to be a more indirect consequence of the tides, eg., from when tidal flow is forced up over seamounts, etc.
Because ocean is well-approximated as a constant density layer, (constant potential density and incompressible). For a freely-propagating gravity wave, of long wavelength (much larger than ocean depth), the shallow water approx. applies.
surface vertical displacement creates horizontal pressure gradient that is constant with depth, as are horizontal velocities and convergences; thus vertical displacement is proportional to height above seafloor.
Now in the slightly perturbed case, with a small potential density increase at some fraction of total depth from the seafloor, as a passive tracer this will have a wave of that fraction of the surface wave. Because it is smaller in height, it will produce a smaller pressure gradient relative to the increase in density, so the velocities will be slightly smaller below that level; this feeds back by reducing the vertical displacement; thus the wave is somewhat concentrated in the upper level.
Of course the tides are forced (although it is complicated; I imagine in some parts of their cycles they propagate freely or even against the tidal forcing, but on balance they must be forced), but I think the same logic applies.
Note that the case of a dominant internal wave, the surface has a (small) wave 180 deg out-of-phase to drive compensatory motion in the upper layer; this (I believe?), along with the reduced gravity and thinner layer(s), make the free-propagation phase speed much smaller
(at g0 ~= 10 m/s^2 and H ~= 4 km, c ~= 200 m/s. for the surface/bulk ocean wave.)
So the resonance periods will be very different. Perhaps the internal mode could be excited by tidal forcing within certain small sub-sections….???
@ Paul Pukite
I like that youtube reference to the 2 phase hydraulic wave machine..
Se also what happens at the top of the bath that is closed, and with another 2 phase system.
Several partial waves here are obviously out of step with obvious turbulence here and there.
“ as a passive tracer“…
I meant I started the reasoning by treating it as such; then I considered the effect it would have, thus accounting for it’s lack of passivity.
The boundary conditions are already there. The reflecting boundaries are the edges of the Pacific Ocean and that defines the standing-wave modes of the basin — close to a wavelength spanning the width, thus defining a dipole for ENSO. This is fixed and it swamps the impact of isolated ocean floor seamounts. There are also harmonics of the fundamental standing-wave and these are also fixed in wavelength, with one such frequent mode having a wavelength of 1100 km, about 1/15 the width off the fundamental ENSO dipole.
The tidal forces are simply driving these modes, not impacting the spatial structure (which is fixed by the ocean’s “waveguide” basin and boundary conditions), but putting the temporal response through the ringer. Sloshing dynamics math is not intuitive, but it can be done and the results are eye-opening. No sense in trying to hand-wave what is going on, when one can work out the math and fit the resulting model to the data.
BPL: Statistically, CO2 accounts for 85% of the variance of temperature anomalies from 1850 to 2019.
BPL, at what temporal resolution is this variance ? All the short-term T oscillations – seasons, ENSO and decadal oscillations, are driven by factors other than CO2, hence trying to fit the temperature
variations over short-timescale would artificially lower the climatological correlation with CO2, since CO2 has no inherent reason to positively correlate with T over short, weather not climate, time-scales. Only the oscillations that survive averaging over typical timescale of climate, say, 3 decades, are relevant to climatological trends like AGW.
Other problem is where you start – if in 1850 then it means that for ca. 2/3 of your period there is not enough surplus CO2 to have a significant warming, then even if in the last 1/3 the CO2 explained 100% of variability, the explaining power of Co2 over the entire period since 1850 would obviously have to be considerably less. Has somebody said 85% ? ;-)
And for the predictions of AGW – ironically it is the predictions from the last 1/3, when there was enough CO2 to dominate over the non-CO2 factors, that are relevant – nobody is expecting to see the future CO2 to fall below the pre-1950 levels any time soon.
I used annual values.
BPL: “ I used annual values”
I have thought so. Hence I suggested that annual values are inappropriate to judge the climatological relationship between CO2 and T – as in the short term (annual, ENSO, decadal oscillation) factors other than CO2 are dominant, thus not informative on the climatic timescale (annual data averaged over ~ 30 years) forcing of CO2.
Therefore, the number in question – Co2 explaining 85% of variability of T anomaly in the dataset containing both weather and climate – is an underestimation of the ability of CO2 to explain T anomaly over CLIMATOLOGICAL time scale, which it the subject of the climate change research.
Second, the data from the past periods when the increases in Co2 were a too low to be caused noticeable warming, are irrelevant to the periods when the concentration of Co2
is significantly above the pre-industrial baseline (such climate projections until the end of XXI century). Particularly, that the continuous direct instrument record of Co2 is only from 1958 on.
Third, the effect of Co2 on T is more likely to be logarithmic than linear
Fourth, Co2 is the largest, but not the only GHG that causes warming. so Co2 conc. should be replaced with CO2 [eq}.
So if one insists on assessing present and future climate forcing with statistics only (correlations), then at very least, please use
the running mean over 30 years, of T anomaly vs the running mean of log of CO2(eq), and probably only from 1958 on.
Even then the results may be distorted by a myriad of statistical artefacts, too many to be discussed here, and that’s why the proper way to do it, is to run an actual global circulation model, tuned with historic data, with and without a given forcing.
And the best thing – we don’t have to invent a square wheel (correlations) when we already have a round wheel (model based attribution) already available – first Gavin’s post on RC in 2007(?), and then upgraded into Schmidt et al. 2010 (“Attribution of the present‐day total greenhouse effect” JGR (Atm.) 115, D20).
Re Paul Pukite, Nov 12 “This the actual problem statement, from an upcoming workshop called “Confronting Earth System Model Trends with Observations: The Good, the Bad, and the Ugly”:
Naming an upcoming workshop, and typing it in boldface, proves nothing. See my upcoming workshop: “ Paul Pukite Cannot Go Over that His Hobby-Horse, ENSO, Does Not Have Much Relevance for Climate Change Trend, and Consequently His Field of Interest Can’t Get No Respect”
See? The title of the workshop, and even a vague “problem statement” without a single falsifiable claim – would not suffice – I would still have to argue WHY the title is justified, namely, that ENSO being an oscillation around the mean – is merely noise over the AGW multidecadal trend – and as such – inability to predict its exact timing has much less relevance to the future of humanity than the projections of that AGW trend depending on humanities actions (or inactions).
@ Piotr
This can probably clear up a bit if you can resign on partisan political dispute manners against Paul Pukite.
Given a field and then ask or try and predict where will birch or spruce trees will have come up in 15 years. Where nobody knows and only future will show.
The same, give an earth longtime global clime temperature curve, that seems rater predictable,….but where will the El Nino- peaks have come up?
Paul Pukite seems sure that this is somehow predictable and wants to find out, I help him the best I can as he is looking for the laws for where in the future it will come up.
Back to the upcoming trees. They will come up for sure because that is natural law. It is due to varying years of blossoming and seed spreading and,… if tose seeds are luchy to fall on ground with necessary conditions, and not eaten by mice, and even more, genetic diversity in the seeds. Much can be said for sure there, but are we asking the fruitful and realistic scientific questions? or just bragging and using popular, qvasi- scientific idoms to further ourselves? ( which is often the case)
As I have found among surrealists. They try and repeat extrapolate the popular success of Milancevic selling new cycles.where there hardly are anymore.. As in the fameous tree population in the fields .It is decided the natural way by mice, destiny, and fertility…. not in terms of “Cycles” or oscillation and not at allin terms of Saturnus.
If we better can ask for men, mice, destiny, and fertility,… that would be more scientific. And resign on strict even “cyclic” determinism. in details that are irrelevant, even unnatural to the systemj.
The art of solving problems / cracking a RE-BUS is often the art of stating the problems on solveable form, else resign on solutions in your arbitrary convensionally learnt categories.
There I have a poem again:
“Que sera sera whatever will be will be, the future`s not ours to see, que sera sera” …(youtube.)
That is now and then the responsible answer to juvenile questions.
(Our very good teacher in public school from whom I learnt a lot of science, said that he hated that song. We should better do our schoolworks and plan for the future.
That is .not allways fruitful either.)
I have often been in situations looking for something that was not there and found something important that was categorically different, that became quite important. Be ready allways to find something unexpected in nature, that may be more valuable.
The art is rather to pick and use what you actually find. and do not cook or synthetize- trans- form it too much. Rather take it for what it is.
the art of having luck and possibly find or get somethig is to see and take and make use the tiny luch that you have at any time in any case.
Rather tell it that way to Paul Pukite and whish him good luck.
I’m serious about pursuing this angle of applying geophysics to natural climate variations. I have a background in GPS and time-keeping calibration and am tracking all the recent advances in instrumentation for measuring variations in the Earth’s rotation rate. Consider that there’s a recent unveiling of a ring laser gyro in Germany used to measure deviations in LOD via precise interferometry. The article Ring Laser Precision: Unprecedented Daily Measurements Charting Earth’s Rotation presents this as a rationale:
As I said up-thread, tidal forces generate the vast majority of the angular momentum fluctuations, but calibration remains a challenge. I have published models of tidally-driven mechanisms for the Chandler wobble and the QBO over 5 years ago which haven’t been challenged or falsified/debunked yet, as they predict those cycles precisely. It’s a bit more involved to do the same for climate cycles such as ENSO and AMO because more tidal factors are required (Chandler wobble and QBO both are longitudinally invariant so simplify to essentially one tidal factor) but there are more than enough indications that this is the correct path forward.
Except that Paul’s instance isn’t just invented as a sort of reductio, it’s a real event with real support:
https://usclivar.org/meetings/confronting-earth-system-model-trends
At a minimum, this shows that there is significant interest in the topic in the modeling community.
While I agree with your main argument from a policy perspective–i.e., we know more than enough to say confidently that the practical problem for humanity is just seriously getting on with decarbonization, and other modes of emissions mitigation, and stat–it seems to me that the workshop is attempting to address a scientifically valid and interesting question. It might even lead to something useful–say, hypothetically, better regional-scale climate forecasting.
Carbo-“This can probably clear up a bit if you can resign on partisan political dispute manners against Paul Pukite“.
What “partisan political dispute manners” are you blabbering about?
I question the oversized importance Mr. Pukite assigns to his field of interests: implying that better predicting the timing of ENSO would save, I quote: “countless lives“, a claim he failed to prove, and his bitter disappointment that research interests, funding of, and social interest in his ENSO is not on par with that of the research into AGW, even though its is the AGW that may end human civilization, while at the same time can be slowed or stopped by human action,
while ENSO is neither. And ENSO by its nature, being an oscillation around the mean, is merely the noise to the AGW trend.
The fact that despite being refuted again and again, Mr. Pukite still repeats the same argument in new threads may say something about him, but it is not the goal of my posts, his arguments are.
So your stream-of-consciousness “analysis” of Mr. Pukite, my dear Carbo, is neither needed nor helpful.
Streams of consciousness may perhaps be more helpful to you,Hr Piotr. if you are able to tolerate it.
His discussion of deep sea tidal wave morphology shows us that he is after something real and weighty at least, that is not too well known and conscidered.
You see, it is not a machinery in the classical industrial workers sense who never learnt hydraulics aerodynamics and electromagnetics. Neither is it Logics in the same workers racial class political paradigmatic sense after his highly specialized schoolbooks for employed dilettants in the factories..
Meetoo does actually have another paradigm of physics to it with other experimental archetyps thus able to think further in terms of other perhaps more appliciable “model conscepts. that may be both ridiculous alian misconsceived and strange , even “babbel” on your side.
Carl Anton Bjerknes` experimental water bath Gold in Paris 1886, Rather Chr. Huyghens on wave and oscillation morphology, Niels Bohrs and De Broglies conscepts of matter and microchosmos, and the Helmholz school of physics and sensual persception, on mind and matter with very easy experiments..
Piotr is not a good professor of scientific systematics. He wants it his way by his own geographically professionally and historically provincial experimental archetyps.
I have personally found many things and scored high, even science in press, having been able to basically disqualify suggested approaches and device constructions and understandings, . from such experts who were hardly trained to see what it really is and what it is about,…. but
who were rather blind believers in the scriptures.. . .
Benestad
I sent a reply that did not come up.
In the meantime I have found the arguments of Dragsvik & Moen presented also at https://klimareaklistene.no , a fameous group that actually seem to stand in the background and administer Statistisk sentralbyrå by this event . . “Poor Statistisk Sentralbyrå!” I wrote, because of that..
Statistiski sentralbyrå in Norway seems infiltrated and politically taken over by the climate surrealists. who obviously are trying to repeat the successes of both Milancevic on cycles and Steve Mcintyre on political statistics especially where it is not appliciable, along with the republican war on science. Also politically successful.
Todays Hon Editor of “Klimatrealisterne..no ” is Prof. Emeritus Ole Henrik Ellestad former Prof. 2 of Norsk Regnesentral, poor Norsk regnesentral.
I know him personally from the “climate pizza” meetings Oslo downtown.
Authorities and references like Nicola Scafetta, Uranus Neptune Saturnus Jupiter, Cycles and cyklings, Yndestad… and Svensmark,…. is a lltogether a sociolect that gives me the content in a glimpse,
They operate by another paradigm that I connect with the late Arbeiter und Bauernfakultät in Greifswald by patent from The Soviet science academy in Leningrad and with very hardnecked traditional deputees in the remote province, as the Province is conservative. Giving industrialized dilettantism, Dictatorship of the dilettant., and the reason why Cernobyl blew up.
An important effect is that during all the years with the grand old Party with P, industrialized exam. cheating was installed and comitted in Highschool by employed and organized Party comrades and Kadre comittees AD HOC , for all who were privileged and seen worthy of that on the Party Quote.
That explains the characteristic big holes and great craters in rather compulsary, elementary science education & training, where the one and only one technical industrial method namely “statistics” along with dia- lectic materialism has taken over and cowers it all.
. A situation that follows further on University level privileged and cheated Doctor and Professor diploma titles and and positions, giving the Peculiar Professors. The Svensmark Yndestad Scafetta and maybe McIntyre- syndrom.
Dear Carbomontanus,
I would like to learn why you so often mention Greifswald and its university.
It appearst that it might be a quite nice place:
https://www.spiegel.de/start/studieren-in-greifswald-campus-wohnviertel-wg-zimmer-und-kneipen-a-1515204c-4d46-4848-9983-650f3ad12a52?utm_source=pocket-newtab-de-de
Greetings
Tomáš
@ Thomas Kalisz
I do not discuss the University of Greifswald, that is something quite different.
I label people, things, and opinions with the fameous and very ugly KADRE – highschool for the privileged regardless how stupid on individual level, for keye- roles in the fameous dynastic peoples republic east of the late Berlin wall.
If thereis any resemblance to elsewhere, that is intended from my side.
The danger is that some people may feel flattered by being called analphabeic privileged racial bloody hitlerjugend and junge pioniere from behind the iron curtain..
Thanks!
Kalisz
Greifswald is the next university after Universitas Carolinum IV in Praha from 1348, the first one in the north, and by the same Prager patent of 4 faculties Theology Medicin Philosophy and Law. .
They educated the priests and lawyers and timekeepers and geometers for Denmark/ Norway fore some years until we had an own university in København. They are also Patron of Uppsala.
The royal Frederiks of 1811 in Chtistiania/ Oslo where I am matriculated, also relates directly back by the Praha. patent. That I tend to believe comes from Bologna.
The reason why Tycho de Brahe went to Praha after getting unfriendly with King Christian IV was mainly due to this line of origin and learnings.
I have a very important history from Praha also.
The original faculty of philosophy in Oslo 1811 soon broke up into faculty of science and faculty of linguistics & humaniora. A split that I cannot accept, thus I graduatede both places. That showed possible.
Some other similar criticism of the Dagsvik & Moen study, but with a particular focus on their statistical model which generates absurd results:
https://blog.indecol.no/climate-sceptic-talking-point-published-by-statistics-norway/
https://blog.indecol.no/dagsvik-silent-on-the-sensitivity-of-their-method/
Nigelj
Your references were really very fine.
Again I see the shadows and the footprints of the grand old Party with P , now even over Statistisk Sentralbyrå.
Against which I recommend “kvinner vin og sang” women wine and song, Wild strawberries in the season, and the body temperature of the snowman for zero climate reference nowaday and everyday. .
And “Badetemperaturen på vippetangen” at any other season, carefully measured, discussed and explained.
The bathing temperature at Vippetangen Oslo S. is exactly Where Christopher Hansteen first made up his royal chosmological observatory in order for Norway to be taken politically serious. assembling rather with the Paris Convention and The Royal Society.
Hansteen followed up the royal chosmology and astrology of Tycho Brahe and Ole Rømer in Købehhavn and did correspond with H.C.Ørsted.
Edward Munchs fameous “scream” is picturing Vippetangen with 2 sailboats more or less ahed of it and the fameous heavens of the Krakatoa eruption over it.
For muic try “Norges skaal ” national anthem 1814- 1820. youtube.
That is still my favourite. Something for Thomas Kalisz Moravia also.
Quote: “My experience is that it is depressingly rare that people become wiser from debates about the causes of climate change, but society rather becomes more polarised.”
…and apparently more stupid than it ever was.
Central Texas experienced its hottest summer on record in 2023. Austin saw a total of 80 days with 100-degree heat, 40 days with temperatures of 105 degrees or higher, and received less than 1.5 inches of rain from June through August. The National Weather Service issued an Excessive Heat Warning for 38 days.
Google Datum, Sept 27, 2023
I lived through this. At 80 years old it was too hot for me to work outside almost all summer. I built PVC pipe water spray wands I could hang in trees for the birds. We had to temporarily abandon our rain water cistern and divert softened well water to the house.
Texas just voted to increase reliance on natural gas power plants to address the cold spells we’re getting when Arctic loop currents drive Arctic weather down to Mexico. It refused to finance greater reliance on wind and solar to meet these needs due to the iron grip of the fossil fuel industry and the willful ignorance of the state legislature and our bone headed governor on decision making.
Just to see how the fossil fuel industry is even more turning Texas into an intellectual disaster:
“A Republican-controlled Texas State Board of Education on Friday rejected seven of 12 proposed science textbooks for eighth graders that for the first time will require them to include information on climate change.”
THE TEXAS TRIBUNE
Even worse…
“A Republican-controlled Texas State Board of Education on Friday rejected seven of 12 proposed science textbooks for eighth graders that for the first time will require them to include information on climate change.”
THE TEXAS TRIBUNE
Thank you Rasmus for this important article! I think though, that this: “Dagsvik and Moen claim that recent research indicates that variations in the sun’s magnetic field are of great importance for long-term fluctuations in solar activity” ought to be put a little bit more precise, like this: “Dagsvik and Moen claim that recent research indicates that variations in the sun’s magnetic field are of great importance for long-term fluctuations in solar activity, *and that these fluctuations are a major factor behind global temperature changes*” – my adjustment within exclamation marks. I think this is nescessary, because your following figure does not show variations in the sun’s magnetic field and long term fluctuations in solar activity (sunspot numbers), but the latter and global mean temperatures year by year.
“weather forecasting has been one of the most important success stories in science”
Sure, as long as you limit your analysis to 5 days, or 7 if you are willing to redefine what a good forecast is
Improvements have been made within this short term range by better defining the initial state of the system via improved sampling of input data . But a week is as far as we can go. When we can predict weather to within a degree on a day a month ahead, then maybe we can let the models run for 30 years. Or maybe even if we could predict the ENSO state 12 months ahead??? Where I live in Perth is the easiest place in the world to predict the future. Almost all weather comes from the west where there is open ocean for 7000km in an arc of about 140 degrees. The coast is flat with only minor hills about 40km inland. I am sure this is where they train learner forecasters. But still the 7 day forecast is very unreliable.
Models are no better than taking current global average temp and extrapolating using your preferred climate sensitivity selection
Are you trying to say that climate models are weather forecast models allowed to run into the far future? If so, you would be wrong. That not how climate modeling works.
Yes, there are some differences, but the process is essentially the same. Hence the reason Rasmus was keen to extol the virtues of weather forecasts, and also why Dagsvik and Moen equated them.
Differences include the obvious things like time steps, grid size, vertical layers , boundary conditions and sometimes regional scale versus global. Also the training may be different, climate models are typically trained using history matching from last century. Regionally based weather forecasting often used human understanding of the known weather patterns, but that is becoming less common and (in Australia anyway) the same general model is used for weather and climate forecasting (ACCESS). The other difference is that often multiple runs are generated via Monte Carlo’ing a selection of input parameters with the mistaken belief that this will improve accuracy. I’ve said this before on the website and I will say it until the cows come home, averaging reduces noise IFF it is true (white) noise. It does not improve accuracy. If your model does not have the correct understanding of how clouds get created, then no number of runs is going to make it better.
You will often hear it said that climate models do not try and predict what the temperature will be at a point on the surface on the 15th of March 2078….. but they do, they just don’t list that as an output.
You will also hear false claims like Dr Rory Allen’s below “The simplest reply to this is ‘weather is not the same thing as climate. If your logic were correct, you would not be able to predict that it would be warmer next summer than next winter” What a truly bazaar claim.
Climate (by definition) is the low frequency component of the long term weather signal. Weather prediction and climate prediction are the same problem, the difference is only that there are many more factors affecting climate over the next 100 years that we do not fully understand, or have no ability to predict.
” the difference is only that there are many more factors affecting climate over the next 100 years that we do not fully understand, or have no ability to predict.”
– That’s why they’re called projections. Ie., conditional predictions… If we do A and B and C don’t happen, we can expect D…
jgnfld: “Are you trying to say that climate models are weather forecast models allowed to run into the far future?”
Keith Woolard: Nov. 17: “ Yes, there are some differences, but the process is essentially the same ”
Thanks, Mr. Woolard, you for managing to pack more than one classic climate change denier clichés in a single sentence.
Fallacy 1. Making statements about global climate from local weather. Two flavours of this fallacy:
1a) “Disproving” Global Warming because somewhere … there was a week of colder than usual weather. Representatives: RC usual deniers; Donald J. Trump
1b) “if we can’t reliably predict weather in two weeks from now, how on Earth are we going to predict climate in 2010” line. Here falls in our Keith Woolard with his claim above that climate models are “essentially [weather forecast models allowed to run into the far future]”
No, they are not. Even though the output variables of weather (T, humidity, precipitation, wind etc.) and are the same those of climate, the process dominate them are very different:
Weather, in your town, Mr. Woolard, could be different, depending on whether a weather system goes to the left, over, or to the right of your town. We can’t predict its exact path past a couple of weeks, because weather is strongly dominated by chaotic, nonlinear, interactions.
Climate, on the other hand, does not care about these short-term chaotic variabilities -averaging of weather over climatic time scale, say, 30 years averages out the chaos and what is left behind is the climate, which is dominated by simpler and deterministic laws of physics, supplemented with the long-term averages for a proper parametrizations of the processes that are not modelled explicitly. As result, the climate model are NOT AT ALL “essentially weather forecast models allowed to run into the far future” as you proclaim.
Hence, as Rory Allan explained to you a few days before your current post:
“If your logic were correct, you would not be able to predict that it would be warmer next summer than next winter.” It went over your head too?
To make things better – a similar argument goes for spatial averaging – if a given weather system went to the left of your town, then it means that it went over the place that is on your left instead – so when you average all that globally – the particular path of the weather system (over your town or to the left of it) which depends on the chaotic nonlinear interactions, no longer matters – because. again, the local variations are averaged out when you averaged out over global (or even regional) scale.
So no , Mr Woolard, the processes dominating the local weather are not the same as that global climate, and, consequently, we use very different models to study each, and the resulting predictability time-scale is completely different,
2. Second denier fallacy: the assumption that the uncertainty is your friend , i.e., that any uncertainty would be in your favour, and therefore the climate change won’t be as bad as projected. Two fundamental problems with that assumption:
– First, other than a belief in the global conspiracy of scientists, there is no reason to expect a systematic overestimation of climate change by the scientists from various centres all over the world. If anything, most of the models are conservative – do not include some of the positive feedbacks and tipping point, which, if significant, would make the actual climate worse than the projected one.
-Second, human/ecosystem impact of a departure from the predicted climatic values are NOT symmetrical: the additional damage in the world 1C warmer than predicted is more than the reduction in the damage in the world that is 1C less warm than predicted. Or, if we predicted higher frequency of cat. 4 hurricanes, then the additional damage if it turns out that these are in fact cat 5 hurricanes, is much larger than the reduction in damage if instead of cat.4 we got cat 3.
Finally, as pointed out by others – we run climate models of the future for projections, not predictions (since we don’t know -our future GHG or aerosol inputs into these models).
The goal is to say that if you do A then global temp. would increase by Delta T(A), and if we do B then global temp. would increase by Delta T(B). In other words we look for the difference between Delta T(B) and Delta T(A.) So even if, as you argument demand, the climate models systematically overestimated Delta T, they would overestimate both Delta T(A) and DeltaT (B), hence our goal, comparing outcome of A and B, would be either unaffected, or at least smaller that overall overestimation (if Delta (B) was more overestimated than Delta (A)).
Or, if it is too technical for you – if you want to know how much one 100m dash runner is better than the other one, you can tell it quite well EVEN if your stop watch runs a bit too slow for both.
Piotr,
You have really outdone yourself this time. Nowhere in this 800 word rant have you actually addressed anything I have said. Please explain how climate models are different to weather models.
Both take a gridded version of reality at T0 and step through time into some future evaluating the parameters of each cell at each time step with some amount of prediction on changes to external inputs. T(0+1) then becomes the input to the next iteration.
There seems no point discussing any of your statements, just explain why you think climate models are different to weather models.
re Keith Woollard
IMO, the more meaningful difference is not between climate models and weather models; if computer power and speed were unlimited, a high resolution model with ‘all the bells and whistles’ could do a good job with both weather forecasting out to a week or so, and for climate projections out centuries (and for hindcasting and understanding, etc.). But it could not forecast the weather for November 21, 2084 with any accuracy, besides climatology. It makes sense that a climate model will produce resolvable weather events (or parameterize them, eg when not resolvable at grid scale) because weather events are part of the process of how climate works (see https://www.realclimate.org/index.php/archives/2023/11/a-distraction-due-to-errors-misunderstanding-and-misguided-norwegian-statistics/#comment-815796 ).
The meaningful difference is between weather and climate forecasts, reports, histories, and just what weather and climate are.
For practical human purposes, climate may be defined as the statistics (or statistical tendencies) of weather conditions for a period of at least 3+decades, but more generally:
You could think of the weather as being a more specific description of a system’s state, with climate being more general. Eg:
Like computer programming?
climate: defining a class of objects;
individual weather events: instances of that class.
Shakespeare?
weather: what Hamlet told Ophelia in that one scene.
Climate: what happens in Shakespearian tragedies. (Iambic pentameter is coming!)
Lawn care?
weather: describe each individual blade of grass in a particular square dm (decimeter).
climate: what is the texture of the lawn? Ie, is the grass evenly distributed or in clumps? how thick (high) is it? Has it gone to seed? Is it yellow and crunchy?
Notice how the climate of the lawn is predictable based on various forcings, while the weather has limited predictability. Take pictures of wo lawns with the same climate – they look the same, except when you overlay them and can’t match corresponding pairs of individual blades of grass.
You could also think of weather as being potentially sensitive to initial conditions. Given initial conditions for November 14, 2084, a model may do a good job with a weather forecast for November 21, 2084. You could try getting those initial conditions from a forecast based on initial conditions the week prior; however, the errors get compounded, so a forecast for Nov. 21, 1984, based on conditions on October 24, 2084, probably shouldn’t be trusted.
But climate only depends on initial conditions when it is in disequilibrium; the disequilibrium decays as the climate evolves toward an equilibrium, which is determined by the boundary conditions (eg./ie. forcings).
Weather is a specific trajectory (of many possible trajectories, each corresponding to specific conditions at a specific time) of the system in some n-dimensional phase space, which is drawn toward some attractor; equilibrium climate is that attractor (PS see “strange attractor”); climate could be all possible trajectories, or those which come from any disequilibrium climate state. (n is very very large, and due to quantum effects, small unresolved or unpredictable perturbations in forcings (individual cosmic rays, earthquakes), and/or considering a simplified description of the state which occupies a subset of dimensions (wherein the attractor and all possible trajectories appear in projection and thus seem to intersect), the trajectories become or appear probabilistic.)
Consider this extremely simple attractor: T = T0 exp(i*ωt’). For simplicity, let’s say the system is on the attractor. Now weather repeats and climate is just a loop. But suppose we have a 2 % possible error in climate – in the frequency ω. And the process is iterative, where t is continually redefined as relative to the prior moment and T of that moment is the new T0. Now, after some number of cycles, weather can only be predicted to be somewhere along the loop, but the phase at any given time is completely unpredictable. Uncertainty in phase grow over time. Yet the climate is still known to within 2% accuracy.
Weather: Oct 24, 2084, a category 3 hurricane makes landfall 2 mi west of ? in FL, during a moderate El Nino, alleviating drought conditions…
Climate: how many tropical cyclones occur in an average year during 2070-2100; what is their seasonal distribution and strength distribution; how are they affected by ENSO, and how do they correlate with other things…
On other scales:
You don’t need to predict (or project) (or even resolve – or even parameterize – lightning doesn’t feedback much, except for nitrate production?) individual lightning bolts or tornadoes or hail stones in order to predict a severe weather outbreak; the later is like a short-term, localized climate.
You don’t need to predict individual snow crystals and gusts of wind in order to predict a blizzard (a several-hour local ice-age climate).
You don’t need to know the exact location, variety, and age of a particular tree, to project the climax community (equilibrium climate) of some acre.
Given a terrestrial (rocky) planet’s size and composition and a few other things, in principle, one might?/could predict (or project) it’s evolution regarding when or if it will develop plate tectonics or rigid-lid or squishy-lid tectonics… producing granitic crust… with layered or whole mantle convection… with a geodynamo that flips typically every x hundred-thousand years… etc. This might be doable without being able to produce a topographic/geologic/etc. map of the planet’s geography on it’s 3,000,000,000th birthday.
Keith Woollard 19 NOV: “Nowhere in this 800 word rant have you actually addressed anything I have said”
Can you read? Most of “this 800 words” – addressed either what you have said, or the climate change denier clichés you followed in order to say it.
KW: Please explain how climate models are different to weather models
See my 800-word (thanks for counting!) post on which you are commenting.
“Weather, in your town, Mr. Woolard, could be different, depending on whether a weather system goes to the left, over, or to the right of your town. We can’t predict its exact path past a couple of weeks, because weather is strongly dominated by chaotic, nonlinear, interactions.
Climate, on the other hand, does not care about these short-term chaotic variabilities -averaging of weather over climatic time scale, say, 30 years averages out the chaos and what is left behind is the climate, which is dominated by simpler and deterministic laws of physics, supplemented with the long-term averages for a proper parametrizations of the processes that are not modelled explicitly.”
See? The above means that unlike local weather models, the global climate models don’t have to represent all the detailed local chaotic interactions, but instead model “ only simpler and deterministic laws of physics, supplemented with the long-term averages for a proper parametrizations of the processes that are not modelled explicitly
Since you completely missed it, I don’t know how to help you. Any remedial courses in comprehension for “ scientists of 40 years standing” at a nearby university?
No, Keith, weather and climate models are not the same, although the process is similar. Speaking as a weather forecaster, I have seen the massive improvements in weather modeling over the course of my career. When I started, you got one model run to look at every 12 hours, and the last 12 hours of a 48 hour forecast was dubious. Now, 5 to 7 day forecasts are generally good, and we know when there is a lot of uncertainty in part because we get to compare models, and also ensembles of the same model run with slightly different initial conditions. Improvements have included a tighter grid, better incorporation of an expanding set of observations, and better modeling of boundary conditions, to name a few.
Climate models differ in purpose. They are run to ask “what if” and “how does this work” type of questions, over a much longer period. That means you can test different model processes and see how they compare with what happens in the real world – in addition to making projections about what happens if you (for example) double CO2 levels. You can alter cloud or convective parameters, and see what results in the model. There has been a decades-long iterative process of adjusting models to find out where the uncertainties are greatest, and directing research to better measure the processes leading to those uncertainties. That’s where the increased accuracy comes from, the real training of the climate models. by research and human effort. Your assertion that the climate models are trained “using history matching from the last century” is very strange. You seem to be confusing climate modeling with artificial intelligence.
Thanks John (and others that have said similar things)
Most of the arguments I have heard here and elsewhere trying to separate climate and weather models say similar things about what each one is used for, or is trying to achieve. But that doesn’t get away from the similarities of how they actually work. The reason weather forecasts can’t go beyond, say,7 days is the inherent instability of forward modeling. The move from T0 to T1 contains errors that we are all happy to deal with. Going from Tn to Tn+1 when n is large has those same monor errors, but the state of Tn is no longer based on reality. There is nothing to anchor it on. In weather forecasting we only let it run for, say, 7 days, and it is recalculated daily, or 4 times/day or whatever we can afford/need. Climate models can’t do that, but they still rely on the same iterative process and its inherent instability
Keith,
I will try a different type of explanation that will perhaps answer some of your concerns.
You stated that when time stepping the model indefinitely “the state of Tn is no longer based on reality. There is nothing to anchor it on.” In fact, there is. A properly constructed model is a close enough approximation to physical reality that its overall state is bounded.by negative feed-backs. If it gets too hot or cold, it will be out of radiative equilibrium. If the pressure gradient is too great, it will be restored by circulation, etc.
A forecast model can be viewed as time-stepping through this multidimensional weather phase space for a short time period. Since this is a model of a fundamentally chaotic system, the errors grow with each time step, as you have noted. The growing error is accommodated by indicating probabilities and ranges in the forecast parameters. The useful time period can be extended several days by better starting observations, more detailed modeling, and by using an ensemble of models rather than a single realization.
At some time extension, this all breaks down, and you have chaos. You can’t make a specific forecast with any skill beyond the mean. But it isn’t unbounded chaos. That mean is still there, one of the statistical properties of climate. It is a long-term signal. You are exploring a basin of attraction in model space, time stepping through it. A Monte Carlo sampling will give you other properties, such as estimates of the probability of exceeding various conditions in any number of parameters. There can also be a bifurcation between two basins of attraction, often called a “tipping point.” While we can look at the model climate at any point or time, a general circulation model operates on a planetary scale, and would be coupled with oceans, biosphere,etc. These couplings would not be included in a forecast model, because they change too slowly to make a significant difference to a weather forecast. There will usually be multiple runs of a model to provide better Monte Carlo statistics.
Models are related to reality through refinements of measurement and physical representation of the relevant processes. This refinement is the result of ongoing research, and produces model improvements. The fidelity of a model to reality is judged by how well it verifies for various measured states of the system at different times and places. For a forecast model, this verification might be expressed as the mean error. A climate model can be tested by the goodness of fit between the model climate statistics and the observed statistics. This is NOT an explicit day-by-day or year-by-year comparison between worldwide weather for some period in the past and the model output, the way you could do with a forecast model. It is a test of how well the statistics of the climate model match the real world when the boundary conditions (such as CO2 and aerosol levels) are matched. It is a test of how well the basin of attraction in the climate model resembles what was observed. This is training.
Any change to a climate model will change the shape of the basin of attraction in weather parameter space. That will change ALL the climate statistics. There is no simple way to adjust the climate sensitivity to GHGs without changing all of the other climate statistics, too. Rather, the climate sensitivity is the worldwide averaged outcome of the many other adjustments made to a climate model to improve the overall fidelity with reality. A climate model that was simply forced to have the “right” sensitivity would go wrong in many other aspects, because it would actually be a less accurate modeling of physical reality.
KW: Climate models can’t do that, but they still rely on the same iterative process and its inherent instability
BPL: The models are not “iterative.”
re “Climate models can’t do that, but they still rely on the same iterative process and its inherent instability”
We should disentangle different types/sources of error.
***My understanding is *** (PS re John Pollack and others with experience with models – I’d appreciate feedback as I am basing this on my knowledge of the physics, what I’ve read about climate and weather and chaos, and applied reasoning):
I anticipate 3 sources of error:
♦Model physics error (eg. limited spatial-temporal and spectral resolution, missing components)
♦Forcing/boundary condition error (to some extent this may overlap with model physics)
♦Initial condition error
Weather forecasting will be affected by all three, but climate projections will generally not be affected much by the initial condition error, except if that error is sufficiently large or biased so as to create a climate error – in which case, a solution is to just give the model extra time at the beginning so that the model climate can approach the required initial condition for a given purpose.
This is because climate disequilibrium tends to decay over time, and if the model is decent enough, the model climate’s disequilibrium should decay as well. Errors relative to the model climate physics and forcing should then decay as well.
Initialization errors, along with momentary microscopic forcing errors (which should average to 0 effect in climate)…
(eg. the occasional cosmic ray that trips a butterfly’s neurons to change it’s wing flap for a moment – we’re not going to try to predict those)
…impact weather differently. These errors in specific weather conditions grow over time, maybe exponentially (some fraction of them?) at first, until they saturate. They saturate because the weather is bounded. The bounding is fuzzy – extremes (relative to a given climate) happen, but the stronger the extremes, generally, the rarer they are. If the weather fluctuations become climate fluctuations and the climate is stable (sensitivity is finite), then the fluctuations should tend to be reigned-in by negative feedback. If there is a range in which they are not pulled back (along some dimension(s) in phase space), then we’ve found a prominent? mode of internal variability, and the variations are part of the climate.
I was thinking of error as the difference between actual and predicted/modelled weather at a given time, but to some extent it may be measured as error in timing for a given set of weather conditions. Weather repeats – not exactly as in the loop climate example I gave above, but in the sense that there is a texture for a given climate. When will the next moderate heat wave of a given duration, in a given region, occur? One will come eventually.
We can expect 50-year events to happen on average twice every 100 years; climate change can increase or decrease the average frequency of an event.
In this view, weather forecast error is like a phase error.
In terms of climate, this type of initial-condition error is not even an error. The different weather trajectory that results is still in the same climate. We can expect the trajectory will jump because of those microscopic external forcing errors I mentioned (individual cosmic rays, etc.). So it doesn’t really matter.
???The exception is when the climate is at a sensitive point, and/or perhaps at a bifurcation… eg. when on the precipice of entering or leaving a “snowball” state. ???
(PS There are also persistent microscopic details in boundary conditions – eg. the exact shape of a coastline, etc. People tend to want to be able to know things that are only weakly sensitive to that kind of detail; for practical reasons…)
The different weather trajectory that results is still in the same climate.
Having multiple runs with slight perturbations to initial conditions can help fill in the picture of the climate by providing more weather trajectories.
John Pollack,
John, I read through 3 times to be sure I got it, but I have a question from the last couple of paragraphs. As is often the case for me, it is about terminology. You say:
“There is no simple way to adjust the climate sensitivity to GHGs without changing all of the other climate statistics, too. Rather, the climate sensitivity is the worldwide averaged outcome of the many other adjustments made to a climate model to improve the overall fidelity with reality. ”
I’m assuming that when you say “climate sensitivity” you mean sensitivity of GMST to forcings?
And prior to that, you say:
” It is a test of how well the statistics of the climate model match the real world when the boundary conditions (such as CO2 and aerosol levels) are matched. It is a test of how well the basin of attraction in the climate model resembles what was observed. This is training.
Any change to a climate model will change the shape of the basin of attraction in weather parameter space. That will change ALL the climate statistics.”
And here I see the source of ‘misinterpretation'(?) by Keith and others…. if my interpretation is right.
Would it be correct to say that if a change in the model changes the shape of the basin… all the climate statistics… then a change in the forcing (CO2) must have the same effect, as we depart farther from the original equilibrium value? You then say (my bold):
” Rather, the climate sensitivity is the worldwide averaged outcome of the many other adjustments made to a climate model to improve the overall fidelity with reality.”
Which seems to reinforce the point I have tried to make to Keith and the others that GMST is the result of multiple factors in the system, and so his focus on precision/accuracy, whether in the model outcomes, or proxy measurements, or whatever, is not that useful.
I propose that there could be two identical GMST outcomes, with meaningfully different consequences.
Google’s Deep Mind is supposedly beating the standard weather forecasting system.
https://www.wired.com/story/google-deepmind-ai-weather-forecast/
Probably nothing fancy here. The bigger the climate cycles, the less likely they are to be chaotic. Just think of the seasonal cycle driven obviously by the sun’s relative declination in the sky. I am sure that DeepMind is finding these large-scale patterns, weeding them out for other smaller scale patterns, and doing a dead reckoning about a week in advance.
So the algorithm is one of processing all the historical data and finding repeats in the pattern that match current conditions, with very little knowledge about weather physics in general. After all, DeepMind is just a general-purpose neural network learning system.
At this rate of advance in capabilities, might be better to let AI take control of predictions. There are many other deterministic factors in climate that humans are having a hard time figuring out. I ran across an interesting article in TOS’s Oceanography, describing an IMO amazing observational research study mapping massive ocean upwelling events. Conclusion is that the events may be predictable as the research team found a pattern match to longer period tidal cycles interacting with seasonal cycles.
https://tos.org/oceanography/article/extreme-upwelling-events-in-the-seas-of-the-alor-kecil-alor-island-indonesia
This is taking place in the area of the straits of Indonesia so obviously some funneling amplification activity (via the Pacific to Indian ocean flowthrough) is taking place, but upwelling in the ocean is responsible for the largest excursions in climate variability a la El Nino and La Nina events. So if these too can be associated with tidal patterns, and AI helps discover the patterns, then the need for humans is finished and done with ;)
Zebra,
Thanks for having the patience to read through what I wrote several times. I will answer as best I can. I am certainly no modeling expert. (There are others on this who are, so I welcome correction..) I wanted to expand the perspective in a way that might be useful.
“I’m assuming that when you say “climate sensitivity” you mean sensitivity of GMST to forcings?” Yes.
“Would it be correct to say that if a change in the model changes the shape of the basin… all the climate statistics… then a change in the forcing (CO2) must have the same effect, as we depart farther from the original equilibrium value?”
Yes, in general. But as we depart farther from the original equilibrium value, the response may also be nonlinear.
“I propose that there could be two identical GMST outcomes, with meaningfully different consequences.”
Yes, I agree. There could be several different outcomes featuring identical GMST. For example, if the AMOC shuts down, there could be two or more quasi-stable states with the same GMST, but different circulations. GMST is but one parameter for understanding the state of the climate system. It is getting the most attention, because international climate goals are directed toward stabilizing it. It is very useful part of the picture, but only a part.
I think we are both looking for a way to get across to Keith and others that the climate system, and the models of it, are quite complex. There isn’t a simple way to adjust the models to match any particular outcome. If you force it to happen somehow, you’d mess up the rest of the model.
I also note that there are a lot of different ways of adapting models to reality, depending on the time period you wish to examine. Forecast models look at a short time period, so they don’t include longer-term processes, but attempt to explicitly model convection. That’s too much calculation for climate models, which resort to parameterization. However, if they want to go long term, they will need coupled oceans, biosphere, and glaciers, etc., at least to the extent possible.
Patrick,
Your understanding of modeling as you explained it is somewhat different from mine. Again, I should not be confused with an expert. I’ve read research, but never directly used or helped build a model.
P: “…climate projections will generally not be affected much by the initial condition error, except if that error is sufficiently large or biased so as to create a climate error – in which case, a solution is to just give the model extra time at the beginning so that the model climate can approach the required initial condition for a given purpose.”
J: Sort of correct. However, coupled climate models require a long “spin-up” from initial conditions that can run over 1000 years to get the oceans stabilized. It would take even longer to do continental ice sheets. At those time scales, Milankovitch cycles start to become
important. In theory, a model can cycle for an indefinitely long period before actually stabilizing, or jump from one basin of attraction to another depending on where the tipping points are encountered. In practice, you have to start somewhere, and you hope that you get an adequate sample by running ensembles with slightly varying initial conditions.
P: “I was thinking of error as the difference between actual and predicted/modelled weather at a given time, but to some extent it may be measured as error in timing for a given set of weather conditions.”
J: That isn’t really the way I think of it. Mid and high latitude weather does tend to fall into regimes that approximately cycle for a while. However, that’s not guaranteed. I’ve been fooled by thinking a pattern will repeat, when it shifts instead. Often the models will disagree when this is about to occur. However, they commonly disagree on those time periods of around 5-7 days anyway. Over a week, there will also be a difference in the solar angle, affecting insolation. Even around the solstices, when the sun angle is changing slowly, the differential thermal balance between the land and the oceans will be shifting, because the land has a lot less thermal inertia than the oceans (or even large lakes). Those shifts affect the weather patterns.
It may help to consider why Earth’s weather (atmosphere and ocean) is chaotic. (PS chaos is also found farther below, as I understand it (Mantle, Outer Core)).
I am not prepared (with time or knowledge) to give a complete explanation. But I will note:
Various instabilities develop, with available energy building up in thermal and/or momentum gradients:
(conditional) convective instability (vertical heating gradient creates CAPE; feeds cumulus convection/thunderstorms) https://en.wikipedia.org/wiki/Convective_instability,
(conditional) symmetric instability (vertical heating + vertical shear; associated with frontal zones – see “inertial instability”) https://en.wikipedia.org/wiki/Conditional_symmetric_instability,
baroclinic instability (horizontal temperature gradient + associated geostrophic vertical shear; feeds frontal cyclones), see also IPV gradient, surface θ or ρ_θ gradient, “Counterpropagating Rossby Waves”, https://en.wikipedia.org/wiki/Baroclinity#Baroclinic_instability ,
and Kelvin Helmholtz (not to be confused with Kelvin waves) and other shear instabilities, eg. barotropic (how eddies can gain kinetic energy from smooth flows purely due to velocity gradients) https://en.wikipedia.org/wiki/Kelvin%E2%80%93Helmholtz_instability.
The instability and associated energy can be released as a disturbance grows with positive feedback (growth can be exponential for small disturbances, at least for normal-mode baroclinic waves). But eventually the disturbance reaches some limits. And the instability must be replenished (eg/ie directly or indirectly by gradients in net non-convective heating/cooling, eg/ie solar heating) for the disturbances to keep occuring; thus there should be an upper bound on the activity, and if the activity slacks, a buildup of instability tends to occur which should tend to increase the activity again…
(fudge factor: clouds and snowcover, H2O vapor, etc., feedback on the heating gradients, and energy may be redirected from one route to another(?) eg: large-scale overturning by baroclinic waves brings heat upward as well as transporting it horizontally, thus affecting the lapse rate…)
PS cool thing about the baroclinic wave (extratropic cyclones)/ midlatitude storm-track activity – it can pull in momentum (hence the “eddy-driven jet”) and available potential energy (APE, eg: “MAPE”) from elsewhere. But the energy is then drained elsewhere and must be replenished to keep the storm tracks active.
For some conditions, steady state convective motion can occur. I believe I’ve read about arrays of hexagonal convection cells being possible (requires lack of vertical wind shear) – in fact, if I’m not mistaken, (??) these are sometimes observes in the PBL (Planetary Boundary Layer) over the ocean (right?), though perhaps they are not perfect ‘crystals'(??).
I believe a stable steady state solution requires relatively gentle heating/cooling rates….(?)
(growth can be exponential for small disturbances,… I know this for baroclinic normal modes; theoretically this makes sense for convective instability if other things (entrainment and (eddy-)viscosity) don’t get in the way; I’m less familiar with the others…
27 said:
This deference to chaos has got to be re-evaluated at some point. The Earth’s Chandler wobble has been attributed to chaotic motions of the core, but that’s clearly not the case when you consider that the cycle aligns perfectly with a critical lunar cycle.
https://geoenergymath.com/2021/01/07/chandler-wobble-forcing/
This is a great example, as I published this model 5 years ago, yet no one has dared to try to debunk or falsify it yet. There are no controlled experiments one can do, so left with trying to contradict the math, but the math aligns perfectly so the model is still standing,
re John Pollack – Thank you.
Regarding weather (quasi-)repeats (but not exactly) – perhaps I was thinking of trajectories eventually coming near an earlier segment, being nearly parallel for a little time (quasi-repeat time depending on what counts as “near” and “nearly” – perhaps it is true but just trivially so). I believe this would happen with the (system described by the) Lorenz attractor (right?). Of course, the attractor for the whole atmosphere (or that + ocean) would be so unwieldly and dimensionally vast … but maybe in a lower dimensional subspace ie. just in one region, with practical resolution, or just the indices of several prominent modes of internal variability… (although if those modes are empirical orthogonal functions… then there shouldn’t be any structure to that projection of the attractor because there wouldn’t be correlations… (???))
(And of course the attractor (and possible trajectory field) itself shifts around in daily and annual cycles…)
Follow-up from prior comment:
Veritasium: “Chaos: The Science of the Butterfly Effect” https://www.youtube.com/watch?v=fDek6cYijxI (see especially part starting at ~10 min)
Veritasium: “This equation will change how you see the world (the logistic map)” https://www.youtube.com/watch?v=ovJcsL7vyrk (@ ~11 min, experiment on convection)
Hexagonal convection cells (and other patterns): https://psl.noaa.gov/outreach/education/science/convection/Pattern.html : https://psl.noaa.gov/outreach/education/science/convection/RBCells.html , https://visibleearth.nasa.gov/images/59758/hexagonal-cloud-cells-in-south-atlantic-ocean , https://earthobservatory.nasa.gov/images/87456/open-and-closed-cells-over-the-pacific , https://en.wikipedia.org/wiki/Rayleigh%E2%80%93B%C3%A9nard_convection ; https://en.wikipedia.org/wiki/Horizontal_convective_rolls
re Zebra – although the relationship is a bit squishy given the horizontal and temporal temperature, H2O and cloud (and O3) variations and the nonlinearity of the Planck function, temperature is a key variable at least in part because it must change by some amount (given feedbacks, including lapse rate and changes in horizontal… etc.) to restore balance, given a change in radiant forcing. But I agree that changes in the enthalpy of the system are 1. obviously necessary for the temperature to change and 2. helpful for keeping track of what’s happening (and 3. melting ice is among the other important consequences of climate change).
“1. obviously necessary for the temperature to change ” … well techinically no; a redistribution of enthalpy could suffice for GMST changes (eg. ENSO hiding or revealing colder water, melting ice while cooling water etc.)
Keith Woolard: Nov. 17: “ Yes, there are some differences, but the process [of climate models and weather forecast models] is essentially the same ”
Man, you’re just nuts.
iow ignorant and yet haughty and self assured where you have no reason to be.
Being here (and elsewhere) talking about climate for so long leaves you no excuse for such stupid false statements as this.
Jeez. Nothing has improved on this site — the idiocy keeps on coming. :-)
Re: “Yes, there are some differences, but the process [of climate models and weather forecast models] is essentially the same…”
That’s actually one point I would agree with Keith on–although, as it’s a qualitative statement, it suffers from the slipperiness inherent in natural language, so there’s room for reasonable folks to disagree.
Specifically, weather models and climate models share:
–same equations/algorithms describing circulation and radiation
–same (or very similar) schemes of partitioning atmosphere, and dealing with fluxes across grid-boxes
The differences, AFAICT, mostly come in with:
1) parameterizations needed (climate models must parameterize some things that at least some weather models can computationally afford to calculate); and
2) the inclusion (or not) of coupled models (weather models can use static carbon cycle state or ice state boundary conditions, where climate models need to model changes over time.)
But the similarities mentioned are enough for me to have written to doubting Thomases repeatedly over the years that “The radiative physics in climate models is validated with every successful weather forecast you see or read.” And–again AFAICT–that remains a fair statement.
Let me start by saying how frustrating the new’ish system of commenting at RC is. Because you can’t nest comments more than a certain level you end up with people replying all over the place…… which is what I am doing sorry..
This reply is mostly aimed at Kevin McKinney below as well as a number of John Pollack’s well written responses. I will ignore the inane “no, climate models aren’t like that” rubbish from various people who have no clue.
Regarding KMcK’s points, I certainly agree with the similarity and differences list. And you are right, it is a very qualitative statement but I do go on to discuss why the similarities mean that both suffer from the inherent forward modelling issues. The differences you point out only add to the instability problem.
And JohnP clearly knows what he is talking about, but I think (nott 100% sure) that he has misunderstood my reference to anchoring in reality, so I might endeavour to explain this a little better.
Let’s imaging a 7 day weather forecast. As we know, mostly these tend to be acceptable with maybe day 6 and 7 not being ideal, but close enough for week-ahead planning in our lives. Now let’s be clear. the output we depend on is a few numbers for a fairly specific location, but that is a tiny percentage of what modelling generates. It has taken the entire input model and stepped through time calculating all grid cells for the entire modelling run. There is nothing wrong with the model by day 6 for example, no energy in-equilibrium, The problem is that if we where to compare the model state at day 6 with the actual numbers on day 6 there will be (minor) differences in every time/grid node. And as we know, the reason we can do accurate forecasting is we have a good handle on the input data (and a truckload of compute power)
this weekly anchoring in reality is what I am trying to show. In climate models we don’t have that luxury. We could easily take the full output of models run 25 years ago, and compare the state now with what was predicted but I suspect that is likely never going to happen and any discrepancy likely attributed to coarseness, compute power inadequacies or early algorithms. Simply saying that climate models are trying to predict averages and therefore they are more stable has no basis in fact. Averaging only improves accuracy if there is equal chances of over estimation compared with underestimation. This is what true noise is, but the models aren’t inaccurate due to white noise, they are inaccurate because the model does not represent reality exactly. If it were only a noise issue, then all model would produce the same shape temperature projection with only osculations around a central value.. This is not the case.
Models have a useful place in understanding how the future may change, but as mention in my very first comment…..
“Models are no better than taking current global average temp and extrapolating using your preferred climate sensitivity selection”
.
Paragraph
re Keith Woollard https://www.realclimate.org/index.php/archives/2023/11/a-distraction-due-to-errors-misunderstanding-and-misguided-norwegian-statistics/#comment-816492
“Let me start by saying how frustrating the new’ish system of commenting at RC is.” I sympathize!
Now I understand. Okay, so … anyone correct me if I’m wrong here, but I’d think/expect/believe (based on what I’ve seen, read, etc.) that when a model is run to produce a projection based on some future forcing/boundary condition scenario, it would not be initialized at/near present; rather, I expect it is initialized and then run to equilibration for preindustrial or earlier conditions, then run for the historical period up to near present with the historical forcings (as they are understood to have been), then run through one of the scenarios. (And there may be ensemble runs with varied initial conditions to cover weather variability to better illuminate the climate, and there may be runs with different forcing scenarios.) Thus the climate and climate trends produced can be and would be compared to reality up to present.
This may be helpful:
https://www.realclimate.org/index.php/archives/2008/11/faq-on-climate-models/
KW: “Where I live in Perth is the easiest place in the world to predict the future … I am sure this is where they train learner forecasters.”
Really? How sure are you? Forecasting what is coming in from the ocean, with a paucity of observations both at the surface and aloft can be a tricky business. Neither models nor humans make good predictions without good data.
Even if it were the case that the predictions were easy, is that how you train your “learner physicians?” I would think that you’d want your interns to be exposed to a wide variety of cases, both easy and hard, before you turn them loose on patients. The same is true of intern forecasters, at least in the U.S. They get all kinds of weather cases to study and participate in forecasting. I would be surprised if it different i Australia.
One of the commonest fallacies repeated by climate science deniers is that ‘we cannot predict the weather for more than a month ahead but scientists claim to know what will happen by the end of the century, so climate science is rubbish’. The simplest reply to this is ‘weather is not the same thing as climate. If your logic were correct, you would not be able to predict that it would be warmer next summer than next winter.’ It is depressing that papers can be published that perpetuate this confusion, though ‘published on a website’ presumably means it hasn’t been peer reviewed.
I like to counter that flawed argument with an analogy:
If you drop a rubber duck into a river, I couldn’t tell you exactly (to the nearest cm in both dimensions) where the duck will be in one hour’s time because it is impossible for me to perfectly predict all the turbulence in the river. However, if I know the average speed of the near surface water in the river (i.e. flow rate) at different locations downstream and different points across the river, I could give an approximate location of the duck in one hour’s time which would be good enough for someone genuinely interested. If I don’t have direct measurements of the river flow, I could estimate it using a hydrological model and topographic data. The former is analogous to weather prediction, the latter is analogous to climate prediction.
Really good analogy here. I would only add that climate models tend to be run many multiples of times with slightly perturbed inputs. This is analogous to a rubber ducky “race” such as those often run for charities. Most all duckies end up crossing the line. But the routes and times will be quite different across individual duckies. Still, however, probabilities will emerge for various specific routes and times.
Stream flow is essentially an example of dispersion in action — the further one goes downstream, the greater the uncertainty. I discuss the stochastic math behind this in Chap 20 of Mathematical Geoenergy, and specifically how to model what are called breakthrough curves in groundwater flow experiments: https://agupubs.onlinelibrary.wiley.com/doi/10.1002/9781119434351.ch20
Evidence is that climate does NOT behave this way, as it is synchronized to external forcing factors. The most well-known of these are the daily and seasonal cycles. No one argues that seasonal climate does not disperse over time as we can be guaranteed an up-coming winter cold exactly 100 years from now with little uncertainty, due to the deterministic seasonal flow.
But there are less obvious and much more subtle examples of this synchronization in climate. Consider the climate that is governed by tidal forces. Conventional ocean tides are well known to be non-dispersive and deterministic as they are solely synchronized to the moon and sun. Tides are not climate, but the El Nino Southern Oscillation (ENSO) cycle is one such climate behavior that should seriously be considered as a case of tidal synchronization. Not so, you say, as climate scientists assert that El Nino occurrences are unpredictable and possibly chaotic in nature. But the evidence keeps piling up that ENSO follows the long-period tidal cycles interacting with the seasonal cycle, largely as a result of the equatorial thermocline being extremely sensitive to gravitational forcing (that I mentioned elsewhere in this thread).
ENSO is essentially a standing wave sustained by external forces, which may look erratic but can be decoded by inverting the time-series to the tidal forcing that would generate it. The atmospheric pressure at Darwin is close to a maximum excursion in the dipole and so we can use that to cross-validate a tidal model of ENSO. Here’s a typical model result, calibrating the tidal forces to measurements of the Earth’s length-of-day (LOD) variation.
https://user-images.githubusercontent.com/2855758/284008506-e925f6f0-5def-48b6-bb07-9293209a94d5.png
There goes the fallacy that ‘we cannot predict the weather for more than a month ahead but scientists claim to know what will happen by the end of the century, so climate science is rubbish’.
Climate science is not rubbish at all.
Zebra sez: Note for all the people who have spent hours of their lives explaining the niceties of statistical reasoning to Victor:
“What Rasmus seems to be saying is that global sea level might very possibly work as a more reliable proxy for global temperatures than thermometer readings.”
Come on, people. Think about that.
V: Not sure what your problem is, Z. That’s Rasmus’ idea, not mine.
Better make that also your idea, Victor.
It is also mine, being aquainted to design scientific methods for crossexamination by systematically independent empirical methods.
And it has been suggested and discussed and used all the way during the climate dispute..
It is a very “natural”, i would say obvious thought, not worthy of being disputed or denied in any kindv of way. . It is a thing that we can agree to rather by routine.
Whenever measuring or deciding on unknown and vital things, try and keep also 2 other quite different
and systematically independent methods in reserve for contol of systematic errors. When 3 or more such very different ways rather entail roughly the same, you can dare to draw a conclusion and deliver, hoping that it will stand. Never before.
It is how to operate in Microchosmos and in Macrochosmos and in between, Genosse. Never believe in the Party wityh P.
But this is alian to many, I know, betraying their lacks of scientific formation and experience.
Shades of Climategate !—
A very successful climate disinformation hacker has been sentenced to 80 months in prison and forfeiture of the $ 4,800,000 he earned :
https://vvattsupwiththat.blogspot.com/2023/11/remember-climategate.html
“My experience is that it is depressingly rare that people become wiser from debates about the causes of climate change, but society rather becomes more polarised.”
Well, people in the highest Offices of trust and responsibility throwing the climate issue to the shark pool of public opinion where every element can and will be contested was a profound betrayal of their duty of care, especially when accompanied with deliberate undermining of public trust in that expert advice.
Presidents and Prime Ministers have not only had full and unfettered access to the best available science based expert advice (governments commissioned it in order to make informed decisions) but to a variety of means to assess it’s validity and assist their comprehension. I expect up to and including Defense Science boffins on the science and Intelligence agency reports on the political leanings and activities of scientists – since some Presidents and Prime Ministers have been quite taken with the possibility it is some kind of grand globalist/socialist/environmentalist/scientist-ist conspiracy to impose tyranny. And having thought it up themselves, may even believe it.
We wouldn’t be expected to be fighting foreign invaders with our own resources as they roll down our streets to have our calls for a government led, coordinated response taken seriously – like that. They already know. We don’t expect the existence of the invasion to be called into doubt or make it a matter of public opinion whether it actually is an invasion or decide whether governments should take it seriously.
There has never been genuine science based cause to doubt the validity of the expert advice.
Courts too have been letting us down, being unwilling to make lines of responsibility and accountability clear.
And yet….Why are we having any of this hand-waving if it doesn’t really mean anything in the real world? Who the hell cares about 1.5C when nothing is happening? Wasn’t AGW supposed to usher in a catastrophe to humans? Where are the heat related deaths? Where are the increases is malaria deaths, dengue deaths, cholera deaths, west nile deaths, malnutrition deaths, childhood deaths, heatstroke deaths? flooding deaths, fire deaths, tornado and hurricane deaths?
According to IHME (https://vizhub.healthdata.org/gbd-compare/) death by exposure to high ambient temperatures currently ranks as one of the lowest causes of death globally (about 4 in 100K). For comparison, lead exposure causes more than double the amount of deaths than heat related deaths (10 in 100K).
According to ourworldindata.org (https://ourworldindata.org/natural-disasters) death rate from natural disasters is currently about 0.51 per 100K. Compare that to over 26 per 100K in the 1920’s.
For all those here who love to castigate climate “deniers” about “climate is not weather!” Take a look at the data above. Are you going to go after them now? They are carefully recorded longer term trends of health outcomes. Huh. Just like climate trends. It’s trends like these, obvious to anyone who cares to look them up, that make otherwise really smart people start making snickering comments about self-enclosed climate science echo chambers. Kind of embarrassing for those espousing a catastrophe that’s always getting near(er).
And here come the ad hominems. Save your breath folks. Seriously. If all you have are ad hominems, you’re kind of in trouble, don’t you think?. Maybe not today, (you have all the corporate media on your side). But ad hominems do get awfully old, when all you have are anecdotes of this fire and that heatwave. Seriously folks, lets discuss a double standard.
Scott, telling you that your argument is fallacious is not “ad hominem”. Look it up.
So, the statistics you cite don’t tell us anything about climate trends, because there are obvious “confounding factors” (look it up) like improved medical technology, infrastructure (e.g. air conditioning), and even weather forecasting.
I don’t know if the people snickering are “really smart” or not, but they appear to lack education in basic logic and scientific reasoning. (That’s not “ad hominem”, by the way.)
Zebra,
Is it logical and reasonable to pump CO2 into a greenhouse and expect a gentle warming of greenhouse temperatures? Is it logical and reasonable to pump CO2 into a greenhouse and expect to cook a steak?
Is it logical and reasonable to pump CO2 into the atmosphere and expect a gentle warming of temperature? Is it therefore logical and reasonable to pump CO2 into the atmosphere and get “global boiling”, “mass extinction”, or “catastrophe”?
If “confounding factors” always seem to get in the way of our road to endless perdition, then perhaps the mysterious road to hell hasn’t been paved quite yet. A lot of smart people call this “adaptation”. However, even that’s not very descriptive, as climate related deaths have dropped precipitously over the last 5 decades. It’s more like “thriving”. Yep, you see catastrophe, I see thriving. And I have proof to back it up. What proof do you have to show that climate change is overwhelming adaptation and causing the catastrophe you are seeking? Are you surprised that so many doctorate level professionals such as myself doubt the veracity of climate catastrophes?
Scott, it’s obvious that your “doctorate level” is not in the physical sciences, particularly physics… you are just using superficial rhetorical arguments with undefined terms, and making fundamental physical and quantitative errors.
If you want to have a real scientific debate, you have to be able to do more than repeat the same superficial assertions over and over and over, with slight variations in your language.
If you are not willing to define your terms and elaborate on your reasoning, you can’t expect serious people with science backgrounds to answer you.
(Although there are folks here with too much time on their hands, who like to fill up the pages.)
Zebra, what a refreshing response to an otherwise boring Sunday afternoon. Neither you, nor anyone else on this website can lead to one single outcome based study showing increased deaths due to climate change. We have an emergency on our hands, or so were told by NCA, and yet, no real world ,observational increase in heat related deaths, malaria, dengue, cholera, malnutrition, etc. etc. etc.
OK, the way I define my terms is that my theory is that there is no climate emergency. In fact, if we quit talking about this drought or that fire or hurricane and put trend lines to it like Gavin et. al. love to do to show global warming over decades, do the same damn thing for health outcomes. These are easy to find on the resources I have bounteously provided in previous posts on this thread. Those are my terms Zebra. Science. Debate with science. Observations. Outcomes. Gavin can do it with NASA-GISS dataset, why can’t we do the same thing?
I’m going to continue living my life THRIVING–NOT COWERING to a group of inbred scientists who are increasingly are out of touch with reality presented to them by other scientific fields. How may medical doctors are involved with IPCC for health outcomes? That’s a question for you. Are we all so stupid that we don’t know what’s going on? Hey Gavin et al., try on my stethoscope, eh? Come on, you’re an expert in human health, you don’t need medical doctors to tell us that we’re all in an emergency. You’re the expert here. Keep telling yourself that anyway. Doesn’t your appeal to authority get old?
Scott, it sounds like you are saying that the only thing that would create concern for you would be an increase in deaths directly correlated to increased Global Mean Surface Temperature.
You seem not to understand that GMST is an effect, not a cause, so you are making the most basic type of error in thinking there should be such a direct correlation.
But people familiar with the math and physics and the nature of complex, non-linear systems (AKA “chaotic”) are concerned with all the effects of an increase in energy in the climate system. That’s why they look at trends in all kinds of extreme events.
So, increased energy would result in many changes, only some of which would manifest as local temperature extremes, which is what would show up in your statistics about direct heat-related deaths.
Again, you seem to be lacking in education on very, very, basic quantitative reasoning… if you don’t know what an average is, perhaps you should take a refresher course in K-12 math.
S: climate related deaths have dropped precipitously over the last 5 decades.
BPL: [CITATION NEEDED]
Easy:
https://ourworldindata.org/natural-disasters
Re Scott Nov.18.
Have you noticed, Scott, that there is not a single number, nor a falsifiable argument in your post?
And in which professional field can I get a doctorate for _this_ kind of arguments? Even literature seems to have some prohibitions against your kind of scholarship. As in: “It is a tale told by Scott, full of sound and fury, signifying nothing ” . Or something like that.
Scott, are you the same “Scott” that stated on 8 AUG 2023 AT 11:22 AM: – “This will be my final post.?
https://www.realclimate.org/index.php/archives/2023/07/back-to-basics/#comment-813644
Scott: – “Who the hell cares about 1.5C when nothing is happening?”
Where you are isn’t representative of everywhere!
While you’ve apparently been ‘away’, BioScience published on 24 Oct 2023 a journal article by William J Ripple et al. (including Johan Rockström, Timothy M Lenton, Leon Simons & Sir David Anthony King) titled The 2023 state of the climate report: Entering uncharted territory. It begins with:
https://doi.org/10.1093/biosci/biad080
Professor Rockström’s talk on 18 Oct 2023 covers the latest scientific results of the health of the Earth System, including the recent work of the Earth Commission and an update on the “Earth for All” scenario, analysing pathways towards attaining the Sustainable Development Goals within planetary boundaries.
https://www.youtube.com/watch?v=h2VjdyqG-nY
Scott: – “Where are the heat related deaths?”
The Proceedings of the National Academy of Sciences (PNAS) published a paper on 9 Oct 2023 titled Greatly enhanced risk to humans as a consequence of empirically determined lower moist heat stress tolerance, by Daniel J. Vecellio, Qinqin Kong, W. Larry Kenney and Matthew Huber. Figure 1 shows annual hot-hours under (A) 1.5, (B) 2, (C) 3, and (D) 4 °C of warming relative to preindustrial level, (E) population projection in 2050 following the Shared Socioeconomic Pathway 2, and (F) population subject to accumulated duration of 1 week to 3 months of uncompensable heat stress annually under 1–4 °C of global warming (the shaded area corresponds to the 10th to 90th percentiles of CMIP6 model spread). The PNAS paper includes:
https://doi.org/10.1073/pnas.2305427120
New projections presented in the eighth annual global report of the Lancet Countdown on health and climate change reveal soaring health risks of persistent global inaction over the climate emergency.
https://www.thelancet.com/countdown-health-climate
On 17 Nov 2023, the global daily mean 2 m surface temperature reached a new high for year-2023, at 1.98 °C above the IPCC 1850-1900 baseline. Only one other day (since records back to year-1940) has been higher, at 1.99 °C on 28 Feb 2016. Perhaps new temperature records are in the offing very soon?
https://twitter.com/EliotJacobson/status/1725849894941024543
Scott: – “Where are the increases is malaria deaths, dengue deaths, cholera deaths, west nile deaths, malnutrition deaths, childhood deaths, heatstroke deaths? flooding deaths, fire deaths, tornado and hurricane deaths?”
A reminder of global warming I see causing problems at: https://www.realclimate.org/index.php/archives/2023/07/back-to-basics/#comment-813655
I expect self-characterized climate science deniers to willfully misunderstand/misrepresent information that conflicts with their ideological narrative.
Scott, I’m just going to reinforce what Zebra said. You have repeated all this rhetoric at least twice before. Several things have been pointed out to you before by various people:
1) That nobody has claimed that one degree of warming would cause a catastrophe. Your statement is a strawman. And that is not an ad hominem. It is a characterisation of what you are doing.
2) It has been pointed out that the mortality rate from heatwaves has not increased because healthcare has improved, but there is no guarantee that situation will continue indefinitely. There could come a point where high heat high humidity events become widespread and very lethal and overwhelm the health system. I do not want to gamble that things will all work out just fine.
3) Although the mortality rate related to heatwaves has not increased (yet) the system has had to deal with more injuries due to the increasing frequency and intensity of heatwaves, and this diverts resources from other pressing needs. So we are already feeling impacts form climate change if indirectly..
4)It’s not all about the mortality rate. Climate change has already had negative impacts on crop productivity, the increase in heavy rainfall events has cost money, etc,etc.
Your repeating of things does not make the impacts of climate change any less real.
I hope you give this some consideration this time. Maybe other sceptical people will if you don’t.
Scott says
17 NOV 2023 AT 12:32 AM
And yet….Why are we having any of this hand-waving if it doesn’t really mean anything in the real world? Who the hell cares about 1.5C when nothing is happening?
Nothing is happening? I suspect you go from your air conditioned apt. to your air conditioned car to your air conditioned workplace to your air conditioned, restaurants only to rarely visit the “real world.”
On the other hand those of us old enough, I’m 80, living on the land, (I’ve supervised a nature preserve in Central Texas for the last twenty years) have experienced disheartening changes unlike anything in recorded history. The “2000 year flood” on the Blanco River in 2015 wiped out most of the ancient cypress trees along the whole length of the river. It killed people, swept away by rising water.
It followed the disastrous summer of 2011 where two thirds of our cedar elm trees died from the heat and drought.
The ice storm of the winter of 2023 was the worst anyone remembers. Multiple thousands of trees in Central Texas were toppled with the weight of the ice when warm air from the south dropped rain through the arctic blast (caused by the weakening arctic jet stream) reaching down to Mexico.
The summer of 2022 was so hot I stretched hoses out to everywhere there were cedar elm trees so the rest wouldn’t die off.
The summer of 2023 was much worse though spring rains saved the trees. I spoke to this earlier.
Each year out here it seems to be getting worse. The drought has virtually wiped out many of the local. butterflies. I used to post photos on my website groundtruthinvestigations so folks could identify what they see. These last few years I’m sadly not finding them.
I realize these are mere anecdotes but they do reflect what’s happening in the real world, sir.
Don’t believe me? Come out here some summer afternoon next year and let’s see how long you last
out in the sun where our Texas legislators are forcing laborers to go on without a break.
“As Texas sweltered last month under a weeks long, record-breaking heat wave, the state passed a law that will eliminate mandatory water breaks for construction workers in cities where such ordinances had been in place to protect people from extreme heat.” Jul 7, 2023
https://www.texastribune.org/2023/06/16/texas-heat-wave-water-break-construction-workers/
Some people are misleading others so that when the disasters do arrive, and they will, they are unprepared for the magnitude of the event. You have company.
But why do you come HERE to spit in the wind?
NigelJ says that nobody says 1 degree will cause a catastrophe. But I didn’t say that. I said 1.5 degrees. Nobody said that 1.5 degrees isn’t a tipping point for catastrophe? That’s strange. Just look at the first paragraph of this CNN article:
https://www.cnn.com/2023/08/08/world/july-climate-record-paris-agreement/index.html#:~:text=The%201.5%2Ddegree%20threshold%20is,life%20as%20we%20know%20it.
“The 1.5-degree threshold is significant because scientists consider it a key tipping point for the planet, beyond which the chances of extreme heat, flooding, drought, wildfires and food and water shortages will become even more unfavorable for life as we know it.”
Is this still a strawman, Nigelj? Do you not agree with these climate scientists? Oh yeah, and that rhetoric? I keep asking it because you can’t answer it–you know you can’t–so you try to convince yourselves and others here that it’s just “rhetoric”–spouted by some crazy uncle in the basement–thus convincing yourself–wrongly–that you don’t need to use real world data (like the data I used) to prove me wrong. Just more handwaving with exactly zero links to studies.
You cite negative impacts on crop productivity, and yet, according to the UN, “global production of primary crops increased by 52% between 2000 and 2020. See it here:
https://www.fao.org/food-agriculture-statistics/data-release/data-release-detail/en/c/1491961/#:~:text=The%20latest%20statistics%20revealed%20that,%2C%20maize%2C%20rice%20and%20wheat.
Oops.
And you need to get together with Geoff who disagrees with your “we’re ok now due to air conditioners but will get overwhelmed in the future” model with his “no, life on planet earth is under siege right now” that he shares with the 2023 5th US National Climate Assessment. Y’all are both contradicting each other. And it’s not hard to see why. Geoff copies and pastes a statement about earth being “under seige” and yet, neither Geoff nor NCA offer anything at all that this is happening. Again, I ask you, where are the deaths? It’s not a rhetorical question if you can’t answer the the fundamental question that is being asked.
Geoff seems to think by quoting a PNAS article about theoretical humid heat stress boundaries will somehow placate his need to actually provide evidence that climate change is causing more heat deaths. This article says nothing about real world observations. It’s more hand waving. In the meantime, let’s review the scientific literature:
https://www.thelancet.com/journals/lanplh/article/PIIS2542-5196(21)00081-4/fulltext
(cold related deaths 9X greater than heat related deaths, with a DECREASING trend in excess deaths, no catastrophe)
https://iopscience.iop.org/article/10.1088/1748-9326/aab214
(A general decrease in heat sensitivity due to adaption, no catastrophe)
https://journals.ametsoc.org/view/journals/wcas/13/1/wcas-d-20-0083.1.xml#bib22
(Decrease in heat sensitivity, no catastrophe)
https://www.sciencedirect.com/science/article/abs/pii/S0048969721026115
(High temperature accounted for a whopping 0.54% of death globally, wow, no catastrophe)
https://vizhub.healthdata.org/gbd-compare/
(As previous post–no catastrophe)
https://ourworldindata.org/natural-disasters
(As previous post–no catastrophe)
Scott
“You cite negative impacts on crop productivity, and yet, according to the UN, “global production of primary crops increased by 52% between 2000 and 2020. See it here:”
I accept that study, but I gave you links previously at least twice showing climate change has 1)slowed down the rate of crop productivity increase and 2) has already REDUCED the productivity of some specific grain crops some people are very dependent on. Please actually read things and read for comprehension.
“And you need to get together with Geoff who disagrees with your “we’re ok now due to air conditioners but will get overwhelmed in the future” model with his “no, life on planet earth is under siege right now” that he shares with the 2023 5th US National Climate Assessment. Y’all are both contradicting each other. And it’s not hard to see why. Geoff copies and pastes a statement about earth being “under seige” and yet, neither Geoff nor NCA offer anything at all that this is happening.
I do not agree with everything Geoff posts, but he is mostly right and has a far deeper understanding than you. And he quotes good sources in detail.
And the areas of the planet that are most at risk from severe heatwaves are the least able to afford air conditioning, and have a huge proportion of their population involved in farming. Links have already been given to you many times. Have you actually thought any of this through? Remember we are talking quite large areas of the tropics where billions of people live. Or perhaps you just don’t care.
“Again, I ask you, where are the deaths? It’s not a rhetorical question if you can’t answer the the fundamental question that is being asked.”
I have not claimed there were excess deaths from heatwaves, and I already responded to your question as follows: “2) It has (already) been pointed out that the mortality rate from heatwaves has not increased because healthcare has improved, but there is no guarantee that situation will continue indefinitely. There could come a point where high heat high humidity events become widespread and very lethal and overwhelm the health system. I do not want to gamble that things will all work out just fine.”
Please read for comprehension.
Scott: – “Geoff seems to think by quoting a PNAS article about theoretical humid heat stress boundaries will somehow placate his need to actually provide evidence that climate change is causing more heat deaths.”
Scott, it seems to me you have a comprehension problem. The PNAS paper titled Greatly enhanced risk to humans as a consequence of empirically determined lower moist heat stress tolerance I referred to includes (bold text my emphasis):
https://doi.org/10.1073/pnas.2305427120
I’d suggest “laboratory-measured, physiologically based” is NOT as you allege “theoretical humid heat stress boundaries“.
Meanwhile, per CNN Brasil, dated 18 Nov 2023 (translated from Portuguese):
https://www.cnnbrasil.com.br/nacional/sensacao-termica-no-rio-chega-a-597oc-e-bate-recorde-historico/
Extreme heat is already disrupting commerce/business. How’s that for “real world” observations, Scott?
I assume “thermal sensation” is similar to Heat Index?
43.8 °C (110.84 °F) at 41% RH yields a heat index of 139.8 F / 59.9 C.
https://www.wpc.ncep.noaa.gov/html/heatindex.shtml
Lethal heat conditions in Rio de Janeiro are already being experienced even before the summer 2023/24 season has begun! The humidity (&/or temperature) only needs to increase a little bit more and people would drop like flies…
Per Prof Eliot Jacobson’s tweet on Nov 19, on 18 Nov 2023, the Earth System breached the global daily mean 2 m surface air +2.0 °C threshold (relative to the IPCC’s 1850-1900 baseline). This is the first time in the instrumental record.
https://twitter.com/EliotJacobson/status/1726209452729327644
Scott: – “Again, I ask you, where are the deaths? It’s not a rhetorical question if you can’t answer the the fundamental question that is being asked.”
The Lancet published a YouTube video titled The Lancet Countdown on Health and Climate Change: 2023 report, duration 0:03:25. The voiceover included:
“Heat-related deaths of adults over 65 have risen by 85% since the ’90s, over twice the increase expected if temperatures had not changed. The increased frequency of heatwaves and droughts in recent decades was associated with 127 million more people experiencing moderate or severe food insecurity, and new locations are now suitable for the transmission of deadly infectious diseases.
These impacts could be an early sign of the future in store, with new projections this year revealing that people around the world could face devastating increases in all of these health harms in a 2 degree heating scenario.”
https://www.youtube.com/watch?v=pQGlu_ycDbU
Explore the key findings of the 2023 report of the Lancet Countdown: Visual summary at:
https://www.lancetcountdown.org/about-us/interact-with-the-key-findings/
Scott, I keep providing evidence/data that you ask for and you keep ignoring/denying them. But that’s what I expect self-characterized climate science deniers to do.
Geoff,
This would all be so hilarious if it wasn’t so tragically sad. You keep speaking of “risk” as if it were in fact, reality. This is so incredibly sad. OK. In medicine, risk is established ONLY by establishing historical patterns of ACTUAL DISEASE PREVALENCE. In other words, we can only establish if a patient is at risk of developing a disease because of, and based on a pattern of past occurrences of the disease. According to AHA/Framingham, I can only assign risk on your risk of a heart attack based on parameters validated over time, like total cholesterol, LDL, HDL, age, gender, blood pressure and smoking history. Pilots execute checklists that reduce risk based on previous experiences, usually bad ones that killed people in the past, like flairing before touchdown and avoiding bad weather. NONE of the so called risks you state from PNAS article have been validated. If heat related mortality is decreasing over time, how on earth can these heat related risks from the PNAS article be validated at all? It’s like remdesivir for COVID treatment. It made great sense on paper, and logically made sense, and yet, it failed to actually save lives under controlled conditions, despite all the logic in the world, it failed.
Oh yeah, the 2023 Lancet countdown you cite? The one reference you used to show that “heat related deaths over age 65 increased by 85% from 1990″? Get this:
There is only one author, Dr. Zhao Liu (supplementary appendix, page 43)
Liu’s findings were never peer reviewed, and hence never published.
Liu used 2019 population data due to COVID, not 2022.
Liu’s graph doesn’t even have a Y axis! (I kid you not).
Liu even states, ” It does not capture changes in response to heat exposure that might happen over time, as a result of acclimation and adaptation. Not capturing these changes could result in an over-estimation of heat-related deaths in later calendar years. Annual average mortality rates are used, rather than daily mortality rates (0). Given baseline mortality can
be higher in colder months, this may lead to an overestimation of overall mortalities”
Liu uses a counterfactual approach. Any time counterfactuals are used, errors get magnified enormously.
Nobody has been able to replicate Liu’s findings accurately.
It appears that population increases have not been accounted for.
His findings go back to 2000, not 1990.
Liu’s findings are utterly out of line with most other peer reviewed, published OBSERVED, REAL WORLD data on heat related deaths:
https://vizhub.healthdata.org/gbd-compare/ (Heat related deaths age 70+ decreased from 4.95/100K in 1990 to 3.15/100K in 2019)
https://journals.ametsoc.org/view/journals/wcas/13/1/wcas-d-20-0083.1.xml (“The decrease in heat vulnerability continues among those 65 and older across most of the country, which may be associated with improved messaging and increased awareness”)
https://ehjournal.biomedcentral.com/articles/10.1186/s12940-016-0102-7 (“There is evidence that across a number of different settings, population susceptibility to heat and heatwaves has been decreasing. “)
https://bmcpublichealth.biomedcentral.com/articles/10.1186/1471-2458-14-1112 (“Attributing health outcomes to heat adaptation remains a challenge. Recent study designs are less rigorous due to difficulties assigning the counterfactual. While sensitivity to heat is decreasing, the examined studies provide inconclusive evidence on individual planned adaptation measures.”) I love the “study designs are less rigorous due to difficulties assigning the counterfactual”. Hah! I agree!
Lastly, according to 2023 AP/NORC poll, the belief that climate change is caused either entirely or mostly by humans has finally crossed the 50% threshold. Unfortunately for alarmists, the momentum is going down, led by shifts in democrats and independents. It will continue to lower over time as more and more predictions fail to materialize.
Scott: – “This would all be so hilarious if it wasn’t so tragically sad. You keep speaking of “risk” as if it were in fact, reality. This is so incredibly sad.”
Scott, would you play Russian Roulette? Would you ride in a car with a 10% chance or more of the brakes or steering failing? Would you get on a plane that had a 10% chance or more of crashing. Would you cross a bridge that had a 10% chance or more of collapsing? Would you jump out of a plane with a parachute that had a 10% chance or more of fouling? etc…
I’d suggest most people would not willingly/knowingly accept those risks, but perhaps you would, aye Scott? Daredevil Scott?
Scott: – “OK. In medicine, risk is established ONLY by establishing historical patterns of ACTUAL DISEASE PREVALENCE. In other words, we can only establish if a patient is at risk of developing a disease because of, and based on a pattern of past occurrences of the disease.”
Um… I’d suggest that’s what the PNAS paper does with “empirically determined lower moist heat stress tolerance”. Fig. 4 shows the empirically determined heat stress tolerance threshold.
https://www.pnas.org/cms/10.1073/pnas.2305427120/asset/7e1197f1-3196-4a36-a310-937609789b47/assets/images/large/pnas.2305427120fig04.jpg
As that moist heat threshold is approached the heat stress on people increases, per the NWS Heat Index chart:
https://www.weather.gov/images/wrn/social_media/2017/heat_index.jpg
Go beyond the moist heat threshold and people (including the supremely fit & healthy) die like flies with exposure times in as little as 15 minutes to a few hours. Increasing global mean temperatures ‘load the dice’ towards increasing instances of exceeding those lethal thresholds. Ah, but that’s inconvenient for your narrative, aye Scott, so it seems you continue to ignore/deny it.
Scott: – “Oh yeah, the 2023 Lancet countdown you cite? The one reference you used to show that “heat related deaths over age 65 increased by 85% from 1990″?”
You’re apparently a health professional, so, you’ve already communicated with The Lancet then to challenge them, aye Scott? Interesting you’ve not included links/excerpts on this issue. I hope you’ve presented a clearer argument/evidence to The Lancet than what you’ve presented here at this blog.
What’s the VizHub data you link to relate to? US only?
The AMS paper you link to relates to US only. It’s not global and doesn’t include ‘hotter’ regions. In the US, I’d suggest air-con is widely available. Most places in the world don’t have access to air-con.
The Environmental Health paper you link to is dated 8 Mar 2016 (more than 7½ years ago). The majority of studies used data from the US or Europe. I’d suggest it’s hardly representative of the whole world, and more particularly seems to exclude ‘hotter’ regions, aye Scott?
The BMC Public Health paper you link to is dated 28 Oct 2014 (more than 9 years ago). It relies upon 30 studies, including 12 from Europe, 10 from USA with one including a Canadian city, two from “East Asian” countries, one each from Canada & Australia. There were no studies from Africa, Southeast Asia or Central and South America. Again, hardly representative of the whole world, aye Scott? But, hey, that’s convenient for your narrative.
Show me data that includes representative ‘hotter’ regions.
Scott: – “Lastly, according to 2023 AP/NORC poll, the belief that climate change is caused either entirely or mostly by humans has finally crossed the 50% threshold. Unfortunately for alarmists, the momentum is going down, led by shifts in democrats and independents.”
Polls change like the breeze. Beliefs aren’t science or reality.
Scott: – “It will continue to lower over time as more and more predictions fail to materialize.”
We’ll see! I’d suggest breaching the longer-term/multi-year +1.5 °C threshold will reveal a much more hostile climate paradigm. It seems that we don’t have to wait very long…
https://twitter.com/EliotJacobson/status/1726682184914989529
Vizhub is global. (See Settings–Location–Global).
Sorry.
Scott,
What I notice is how careful you are to define the problem and look for data that give you your desired outcome. That is the opposite of science.
For instance, your statement here: ” In medicine, risk is established ONLY by establishing historical patterns of ACTUAL DISEASE PREVALENCE.”
THIS is bullshit. If we were to adopt such a definition, we could not estimate risks for a flu pandemic due to a new bird flu because that “ACTUAL DISEASE” does not exist yet. I have found nothing to suggest that this definition of medical did not originate in your rectum.
Risk is defined by a probability and a consequence. The origin of those two quantities may be empirical or it may be a model. Most likely–since data is meaningless without the context of a model–it originates from a combination.
What is more, while Liu is quite candid about the limits of his study–e.g. that humans can adapt within limits to new conditions–your reasoning assumes that we can simply look at numbers from 1990 and 2019, draw a straight line, and ceteris paribus, if the slope is negative, voila, you can stop thinking. The problem with this line of thinking is that ceteris ain’t paribus. Over 30 increasingly warm years, municipalities have adapted, prevalence of air conditioning has increased, forecasting has improved… So, it appears that you stopped thinking even before you did the analysis.
As to your “doctorate-level” degree, I’m gonna go out on a limb and guess that since you assess the validity of your argument by whether you can deliver it with a straight fact that you are a lawyer.
Geoff,
Can you take the CNN Brazil story and trend it globally for health outcomes over decades? Otherwise, it’s just more hand waving. I can give you anecdotes of cold winters in Brazil too, but you’d be all over me like a wet blanket for cherry picking anecdotes. Same goes for you. Seriously. Not everyone gets their science from CNN. (shocker, I know).
Scott; – “I can give you anecdotes of cold winters in Brazil too, but you’d be all over me like a wet blanket for cherry picking anecdotes. Same goes for you.”
I’d suggest you miss my point (deliberately?). A warming world ‘loads the dice’ to more instances of warmer and extreme heat events, and less cooler and extreme cold events.
James Hansen, Makiko Sato, and Reto Ruedy drew attention to this in their 2012 (more than a decade ago) PNAS paper titled Perception of climate change. The Abstract included:
https://doi.org/10.1073/pnas.1205276109
Scott; – “Seriously. Not everyone gets their science from CNN. (shocker, I know).”
I’d suggest the CNN Brasil article referred to is a contemporaneous report of an event and a consequence from it. Are you denying the event and consequence actually happened, Scott?
Where do you get your contemporaneous information from, or do you ignore everything not so-called “peer-reviewed”, aye Scott?
“Scott says 19 Nov 2023 at 9:32 AM”
All these amateurs so far out of their depth they don’t even realize when they are drowning and about to die in a sea of haughty ignorant arrogance. Poor buggers.
re “The 1.5-degree threshold is significant because scientists consider it a key tipping point for the planet, beyond which the chances of extreme heat, flooding, drought, wildfires and food and water shortages will become even more unfavorable for life as we know it.”
Yes sirree that is what the CNN reporter wrote. So what’s the beef then except that you cannot understand what it means as a news report on prior reporting?
And of course you know that for the global average to be +1.5C that some regions on earth will be experiencing temperature regimes of +4C or higher AVERAGES over summer and maybe even higher over winter. And you know that temperature in regional areas, across oceans and plains has an automatic effect upon extreme heat, flooding, drought, wildfires and food and water shortages …..
Right? You know that Scott don’t you. Because you are really really smart skeptic who can do Maths and stuff, and can read too?
re “…..and yet, according to the UN, “global production of primary crops increased by 52% between 2000 and 2020….”
Yeah that’s right Scott, if te data was collected and analysed correctly you got it.
Now do tell the obvious point which fails to eat it’s way into your brlliant (not) MInd.
Global Average Mean Temperatures were not anywhere near +1.5C or +2C during 2000 to 2020.
So tell us all Scott – what happens when they do and US wheat belt experiences +6C averages over spring or summer and +15C higher maximum daily temps in the food bowl? Or in Russia, India, Canada Australia Brazil as well, at the same time in the middle of their growing seasons?
Yeah Scott, so what happens then? Does the early shoots shrivel and the mature plant get wiped out in the local wild fires blown with 70 mph winds? Or does the growing region next door get wiped out in massive floods? Do tell …. what do your scientific models tell us Scott?
Man you’re so damn smart you could even get a job cooking fries at a Burger King!
Happy Daze Dude!
Seems to me we’re just quibbling over words. A catastrophe for me is a statistic to you.
“2023 becomes deadliest summer in last 5 years for heat-related deaths in Harris, Ford Bend counties. Texas’ heat-related deaths in 2023 reached a new high in Harris, Ford Bend Counties compared to the last five years amid severe weather.” Aug 21, 2023
Google datum
“Emergency room visits surge, Texans die amid dangerous heat wave”
https://www.texastribune.org/2023/06/30/texas-heat-wave-deaths-illness/
“After weeks of extreme heat, health officials have reported numerous deaths, while emergency departments across the state are seeing record numbers of people seeking treatment for heat exhaustion and heat stroke.”
BY ERIN DOUGLAS
JUNE 30, 2023
etc., etc., ad nauseum
Is Scott the new Victor? LOL
Someone needs to relocate the Delete function and use it.
Dumb ignorant and incapable people, especially fanatical climate science deniers, wastes everyone’s time and energy.
Ah, but we know that already.
So ………………………………………………….. ? Kind of begs the question doesn’t it.
It looks like we are having a new , somewhat animated and unclean character here.
I shall try and do my best.
Permit me to take to my fully, facultary orders in that case, different from party or military or commercial orders and FAGIDIOTI. .
The climate dispute and the climate problem has got 2 sides,
that are not IPCC vs. “the sceptics” as the contrarian and surrealists want it and try and define it in order to make it their own dia- lectic materialistic wolleball or football- arena with 2 sides, where the earth is flat as a marxistic factory floor or Peoples Republic within error- bars,..
……….But 2 sides given as science of Nature and science of Humaniora.
Nature behaves but do humans allways behave?.
In Humaniora, there is a lot of pollution dirt, rubbish, disaster, and disease, as in Nature also,
But it shall be mentioned under Health and Hygiene in public school allready.
@Scott 20 NOV 2023 AT 11:49 AM
“OK. In medicine, risk is established ONLY by establishing historical patterns of ACTUAL DISEASE PREVALENCE. In other words, we can only establish if a patient is at risk of developing a disease because of, and based on a pattern of past occurrences of the disease. According to AHA/Framingham, I can only assign risk on your risk of a heart attack based on parameters validated over time, like total cholesterol, LDL, HDL, age, gender, blood pressure and smoking history.”
LOL
So how do you risk assess novel, emerging or re-emerging diseases? How do you risk assess new molecules in pharma studies? How do you risk assess re-purposing existing approved molecules to new treatments of different diseases?
Or are you suggesting that no risk assessments are done to inform public health policy or determine whether a new drug and/or new treatment protocol should be approved?
Please do expand your unique thought process here, I’ll go grab some popcorn…
“Lastly, according to 2023 AP/NORC poll, the belief that climate change is caused either entirely or mostly by humans has finally crossed the 50% threshold. Unfortunately for alarmists, the momentum is going down, led by shifts in democrats and independents. It will continue to lower over time as more and more predictions fail to materialize.”
LOL
So I keep hearing since at least the 1990’s…
Anyway… back to risk assessments, you were dazzling me with ground breaking ideas, concepts… please proceed, I have the popcorn with me now.
Ned Kelly: Is Scott the new Victor?
V: Hear hear!
Professor Rahmstorf,
There is a large proportion of anti-AGW disinformation propaganda in the approximately 100 comments responding to your relevant post in LinkedIn (from one day ago) signposting this article – see this post thread there:
https://www.linkedin.com/posts/stefan-rahmstorf-37049a1b9_science-denial-is-still-an-issue-ahead-of-activity-7135738660133449728-T7dt?utm_source=share&utm_medium=member_desktop
Please provide some moderation in that thread in LinkedIn, to address the risk of not just “false balance” but even a high degree of false consensus among apparent respondents in that LinkedIn thread, with many of those responses claiming that AGW either does not exist or is not a significant problem.
More on false balance here:
https://www.carbonbrief.org/exclusive-bbc-issues-internal-guidance-on-how-to-report-climate-change/
[Response: Sorry but I simply do not have the time. I don’t see view numbers on LinkedIn (and in fact rarely look there at all – my social media app simply crossposts things there), but judging from the view numbers on TwiX, these denialist comments get typically 0.1 % of the views compared to my original post, so they are not worth my time bothering. But others are free to engage in the discussion there of course. Many are easy to refute, like the person claiming I’m showing Mike’s old hockey stick again, while you just have to read the figure caption to see it’s the recent PAGES2k reconstruction. -Stefan]
Benestad
By reading closer I find “Why Climate sceptics are wrong” fom Scientific Ametrican under your headline “My dilemma as a climate researcher at the meteorological institute.”
And under there I find William Whewell mentioned
Which showed higly interesting.
Whewell was totally unknown to me until now. , but I checked up and found that I have learnt wide horizons of his philosophy indeed at the Royal Frederiks, from the faculty of Medicine and of Science.
Namely practical Whewellism in the province rather than Arne Næssianism about scientific theory and method, that has occured a bit more strange to me and hardly thinkable all the time.
That ide a of consilence of inductions from “Philosophy of inductive sciences” seems to have had a quite tremendeous impact on parts of the old Royal Frederiks at least in earlier days when my personal GURUs studied there.
It keeps in it that it must be reality known and shown from several independent crafts and trades and points of wiew, and not the opinions and findeings and production secrets of experts and specialists. under which we have to to pray, to obey., and to pay.