How to trust GCMs (Global Climate Models)?

Biggest problem with GCMs is their treatment of clouds. A related problem is albedo. If you cannot model clouds, how do you estimate albedo? The GCMs parameterize clouds and thus albedo is parameterized, at least in part.

When you look at the fan-shaped spread of the 100 or so GCMs, or the 35 or so leading models, consider how they have not converged for decades. The reason is that the modeling groups do not agree on the role of water-vapour and clouds. This is critically important because water vapour condenses to form clouds and clouds are the dominant control for changes in albedo. On average, about 50% of the surface of the Earth is cloudy.

A commonly used nominal value for albedo is 0,30, signifying that 30% of visible light is reflected back into space, mainly by clouds, ice/snow, desert.

About 5% variation in albedo would account for the change in global temperature that has been estimated since about 1750. A 5% variation would mean that nominal albedo varies plus or minus 1.5% from a minimum of 28.5% to 31.5%. High albedo would lead to cooling and low albedo to warming. (Numbers for illustration only as measurements of albedo have varied by the amounts indicated.)

Albedo is also estimated by observation. How can the estimated / inferred albedo of GCM's be validated by the observations?

Two more questions / reservations.

1. Have the GCMs been validated to with error bars within 5%? So far as I know, the answer is no.

2. Apart from GCMs is there another model that would account for climate change? Svensmark and others have proposed a cosmo-climatological theory of climate change based on variations in cloudiness and albedo driven by galactic cosmic rays (actually particles, muons). To what extent has the cosmo-climate model been validated in respect of variation in albedo?

My comment on all of this: The history of science has instances in which two different theories both explain the observations. The prime example is the wave theory of electro-magnetic radiation versus the corpuscular theory (now the quantum theory.)

Do we have here two theories that could both explain climate change during the last 70 years? The last 5,000 years? The last 500 million years?

If people are interested, I will look through my papers to locate relevant references.

Predicting precipitation in the mountainous regions, such as you have around Tabriz, is very difficult, not just in the climate models, but also in the dedicated weather prediction models. The reasons for this situation are related to the vertical coordinates used to represent terrain, cloud schemes and the well known chaotic nature of the atmospheric circulation.

The recent study by Fallah et al. (2017): Towards modeling the regional rainfall changes over Iran due to the climate forcing of the past 6000 years

https://www.sciencedirect.com/science/article/pii/S1040618215009556

shows that winter precipitation over Iran exhibits rather complex pattern, with often erratic increases and decreases, although the trend over the past 6000 years was definitely increasing (please consult Fig. 4 in the above paper).

Based on the general behavior depicted in this figure, I will not discard the predictions described in your question. It will be most useful, however, if we can see the averaged position of the jet stream, as simulated by the models, for the time period indicated in your question.

Adam A. Scaife

Hi Amin,

while climate models inevitably give imperfect reproduction of the climate as pointed out in other posts to your question, it is very important to acknowledge that there are predictable and unpredictable parts to the variability of the climate in any region.

The predictable climate change signal in your region may well be a trend towards wetter climate as suggested by the model. However, the presence of unpredictable variability could create a temporary decrease in rainfall that may hide this trend for years or perhaps even decades before the climate change signal 'emerges' . So the apparent discrepancy between observed records and model projections may not necessarily indicate an error at all. See this paper for a description of time of emergence: Article Time of emergence of climate signals

I would suggest first looking at segments of individual model simulations that are the same length as your observed drying trend to see if they show fluctuations up and down that could explain the observed drying in recent years simply as internal unpredictable variability. There is a schematic in this paper that might help with the analysis: https://link.springer.com/article/10.1007%2Fs00382-008-0451-1

Best regards

Adam Scaife

Amin, when you projected precipitation for iran, did you consider modulation by the Julian-Madden Oscillation?

GCMs are therefore unlikely to take adequate account of natural fluctuations on any time scale. The GCMs are dominated by the Greenhouse-Gas paradigm. The projections are scenarios and not predictions.

Since the world's oceans control the regional climates.we need to take account of oceanic oscillations, including ENSO, AMO, and PDO.

I used the World Bank climate portal to download 100+ years of rainfall data for Cambodia and found no trend. I did find that the ENSO and PDO modulated rainfall quite significantly.

There are several author on Researchgate who have published chaotic models for monsoons. I like one by Peter Carl

Chapter A General Circulation Model en Route to Intraseasonal Monsoon Chaos

Ken

In every entry in Global Warming you appear with your own unfounded idea about GCMs

You have been taught here at ResearchGate over and over again that GCMs are to be used as a "guidance" for the future

Weather models nor climate models are "predictive"; nobody claims this except you

Please use some time to read about what climate models do: for instance they cannot even describe absolute temperatures and are tuned to observations. This is similar to a weather model for the coming days: observations are the starting point OF COURSE

Bottom line,

GCMs are helpful in relating passed records for neighbouring stations in case of a change in measuring sites over the years As with weather and all other areas in natural science without Models there is no way to project coming situations

Hsrry, I agree that GCMs do not predict anything. They present scenarios based on the inputs. Some of the inputs are parameters whose values are not well settled, water vapour and clouds having the most impact on creating the spread between models, mainly because of their impact on albedo.

While the models do not purport to be predictions, they do include "projections" that present hypothetical future states of the various scenarios.

In my opinion, when the GCMs are presented to the public, the line between "projection" and "prediction" often blurred for political reasons.

Criticism of the GCMs may be misplaced, but criticism of modelers is not misplaced when they refer to the "model world" as if it were the "real world", especially when at the same time they deny that they are doing so.

And since, public policy-makers rely on conclusions drawn from GCMs as the basis for radical policies and legislation, plus climate mitigation and adaptation budgets amounting to billions on a national basis and trillions worldwide, I am prepared to support Kenneth in his critique GCMs even though he may mis-attribute the fault to the models and not to those who peddle their "projections" as "predictions" for what appears to him and to me as nefarious purposes.

Ken

You keep on coming with the 1998:

1. A single year this is NOT a climate parameter

A GCM thus does not model single specific years and also does not, cannot and should not account for natural variations within a climate period of 30 years

2. As with the weather models models are incomparably better than 40 years ago: actually climate models did not exist then; your claim of a model that projected a new Ice Age is thus your own fantasy

James C. Trask

I'm a hydrologist who is not involved with climate modeling, but as many of the above posters have touched on, it seems that both the scientific community and the non-specialist news media have not communicated adequately the uncertainties inherent in climate modeling projections, and distinguishing between projections and predictions. Unfortunately a few scientists have been perhaps a bit over-zealous in communicating the latest modeling projections to the press along with dire warnings, without adequately explaining the uncertainties in their modeling--communicating such uncertainty might be viewed as 'hedging' by many reporters and the general public; but really it is not. In turn, too few reporters have any depth of knowledge of science or any of the basics of atmospheric energy exchanges or of statistics--things like confidence intervals, bias checking, hindcasting, etc. I think most climate researchers do have a degree of humility with regard the limitations of their projections, however there may be a few that are a bit over-zealous and tend to exaggerrate their findings and be loud about it, unfortunately the dramatic personas tend to get the attention of the press, and perhaps skew the public perception of the state of climate forecasting, leading to public confusion. Also, it seems to me that PIs in climate research need to be careful that they have no (real or perceived) conflict of interest with regard to the political ramifications of their reported results.

James (Trask): Yes, doomsayers are popular with the press.

But how much have the various climates of the Earth really changed?

Where have the changes taken place and when did the biggest changes occur?

The paper by Belda et Al (2014) is probably the best to date in addressing these issues. Of course they did not draw optimistic conclusions. But you can read the paper and do a few calculations and see for yourself what the data says.

Belda's team reconstructed the Koppen-Trewartha climate classification map from modern datasets. The Belda maps show the climate regions of the world (except Antarctica) for two periods, 1901-1931 and 1975-2005, based on a 30 minute grid, average area about 2500 km2, (About 50,000 grid cells cover 135 million km2, the land area of the Earth except Antarctica.) The data used was published by the Climate Research Unit located at the University of East Anglia in the UK, a depository of global climate data used by contributors to the IPCC reports.

Between the two periods separated by 75 years, 8% of the cells changed climate type. A scatter diagram comparing the two periods shows little divergence from the straight line passing through the origin with slope unity. (R-squared = 99.5). The paper does not discuss error bars.

The Climate Research Unit (UK) later revised the climate data to remove wet bias, an adjustment that would increase R2, indicating even less change than the Belda maps show.

Reference: Climate classification revisited: from Köppen to Trewartha, M Belda, E Holtanová, T Halenka, J Kalvová - Climate research, 2014 Paper download ().

The Belda research suggests that most of the climate change since the Maunder Minimum (ending 300 years ago) took place before 1950 when CO2 began its rapid rise. About 85% of all CO2 emitted has been emitted after 1980 during 25 years of the 30 years of the second period in the Belda study. If mankind's emission of CO2 really did have the effect claimed for it, the contrast between the two periods studied by Belda should have been much greater than it was.

We see elegant climate theory that is not supported by the evidence. And as Richard Feynman used to tell his students, it doesn't matter who you are or how good your theory is, if your theory is not supported by the evidence, then it is wrong.

As we know from history, settled science is often wrong and new discoveries often overturn settled science. I agree with Hubert Lamb founder of the Climate Research Unit in the UK, "In fact, from about the beginning of this century up to 1940 a substantial climatic change was in progress, but it was in a direction which tended to make life easier and to reduce stresses for most activities and most people in most parts of the world. Reference: H. H. Lamb, History and the Modern World Edition 2, Routledge, 1995.

Since climates worldwide at present are not much different from the 1901-1930 period, what Hubert Lamb claimed is still valid.

I go further than Lamb and assert the same is true about environmental problems in both rural and urban areas. Both urban and rural life worldwide have improved since the 19th century. Even in places where there are great environmental problems, people are better fed, healthier, and live longer than at any time in the past. Expectations of doom are subjective. There is no objective basis for pessimism.

Ken

1. What do you want me to read?

2. As for aerosols: these are chemically formed in the atmosphere and it needs MODELLING to describe and project their levels

3. I have replied to you over my "opinion" over and over again but YOU do not want to read it: Vaughan Pratt's analysis and projections

I refer you to the site where you find all experts in the field participating

By the way it is at the site of Judith Curry, and is that does not ring a bell than abstain from further entries here

https://judithcurry.com/2015/11/03/natural-climate-variability-during-1880-1950-a-response-to-shaun-lovejoy/

What do you mean a nut's shell?

Judith Curry? When you are in the field you know she the most famous / notorious skepticist

Ken you should first read the not so long entry of Pratt and then ask what you don't understand: NO CLIPPINGS anymore from my side. I posted already his most famous figure on the correlation between CO2 and 59-yr averaged temperature giving a 1.6 C/ doubling of climate sensitivity as is

Discussed there by the experts:

e.e., Lovejoy, Nick Stokes, Mosher

Timmo Gaasbeek

Amin, I have the same issue with rainfall in the Sahel. Have you looked into moisture recycling? I have a hunch that that may influence things, and i'm not sure how well that has been incorporated in the debate. Basically, moisture originates from the sea, and reaches inland areas through sub-cycles of rainfall and re-evaporation. Now if land use changes (for example through deforestation), the runoff coefficient of areas changes, and the percentage of moisture that re-evaporates and gets transported further inland reduces. Particularly if areas are far inland, there may be more than one sub-cycle between the sea and the area of interest. My hunch is that even if atmospheric and oceanic conditions for rainfall improve, rainfall may still reduce if the hydrological cycle is cut short. Look at stuff written by Van den Ent and Savenije for example.

On top of this, there may be long-term climate variability. No idea how this works in Iran, but it may be that the long-term fluctuations in Eastern Mediterranean SSTs causes a long-term fluctuation in rainfall. When i started looking at this for the (eastern) Sahel, I noticed that the IPCC graphs filter out these long-term fluctuations and only look at trends. A new drought cycle will come to the Sahel sooner or later due to this long-term variability, but it's completely absent from the IPCC graphs. Do you know climexp.knmi.nl? This site enables you to correlate rainfall to SST and a huge number of other factors, and may help you to identify patterns that explain the deviation from the model predictions.

@ Frederick

I mentioned as participating in the discussion and author of the publication that Vaughan Pratt used as starting point

What about reversal of his position? Please provide more info and / or reference

Ken

You never learn or study

The increase is over the last 50 years not 200 years

15 ppm increase since 2008?

Why should I answer to such fallacy?

And secondly why do you always clip from what serves you best?

Why are you nagging me about the policy; I can comment on the science of Global Warming but are no expert at all on countermeasures, apart from cloud seeding at the arctic (a subject I can scientifically follow) whihc could serve as a rough remedy for the first decades

I answered before: re other measures my opinion is worth as much as the guy sitting next to me on the bus

It is true that climate models are not intended as prognostic tools. Their main use is to simulate a possible range of climatic states, depending on the prescribed "scenarios" for the parameters characterizing the Earth system. The most known examples of such "distributed parameters" are the chemical and aerosol field concentrations, as well as surface properties.

All our conclusions about the anthropogenic impact on climate are obtained with the help of several “forward runs” of the climate model. Despite the fact that it is the most natural, this method, unfortunately, is not the most effective. Much better results can be obtained using an adjoint model that can directly lead to an assessment of the sensitivity of the climate to different parameters. Of course, the use of this technique is subject to the usual limitations connected with the existence and uniqueness of the solution of the inverse problem.

Ken

I complain about your stubborn unwillingness to first acquire some basic knowledge by studying climatology; instead you sell the same outdated clippings every fortnight here.

I even provided some introductory sites but you refuse even to know who are the prominent players in the field

Basta

Kenneth, thanks for your comment. My idea is to use a rational methodology to assess the most important parameters of the system. The best example of such an approach is discussed in the paper:

Adjoint‐Based Climate Model Tuning: Application to the Planet Simulator

https://agupubs.onlinelibrary.wiley.com/doi/full/10.1002/2017MS001194

This approach is quite common while working with complex models.

In addition, irrespective of the problems with the estimation of parameters, we are still work to include missing processes and to improve numerical aspects of our models.

Building the model in such an approach is an iterative process; the evaluation of parameters and sensitivities is based on the sequence of model pairs (forward model and its adjoint) with the increasing complexity. Ultimately, at the limit, we will converge to an acceptable model.

Kenneth, we had a similar situation to do with duodenal ulcers. The ailment was believed to be caused by x, y and z. Then it was discovered that duodenal ulcers are caused by an infection.

For decades in the 20th century it was believed that humans have 48 chromosomes, until somebody double checked and counted 46. All the textbooks had to be corrected because they all parroted the same error,

Feynman taught that the test of a scientific theory is that it can predict the outcome of a scientific experiment. But sometimes two or more incompatible theories can correctly predict an outcome (wave theory and corpuscular theory).

In climate theory, I focus on Bond albedo, because about 30% of sunlight is reflected back into space without transmitting energy to the Earth.

Clouds are responsible for most of Bond albedo because clouds cover about 50% of the Earth´s disk that presents to the Sun.

Bond albedo is not constant in time. There exists a theory that claims to explain climate change by changes in Bond albedo related to changes in cloud cover over time.

I offer three thought-provoking papers:

Shaviv and Veizer, Celestial driver of Phanerozoic climate?

https://courses.seas.harvard.edu/climate/pdf/shaviv-2003.pdf

Shaviv, N. J. The spiral structure of the Milky Way, cosmic rays, and ice age epochs on Earth. New Astron. 8, 39–77 (2003).

https://arxiv.org/pdf/astro-ph/0209252.pdf

Svensmark, H., Enghoff, M. B., Shaviv, N. J., & Svensmark, J. (2017). Increased ionization supports growth of aerosols into cloud condensation nuclei. Nature Communications.

http://orbit.dtu.dk/ws/files/140924453/Svensmark_et_al_2017_Nature_Communications.pdf

We recall that there are already astronomical theories of climate change, one of which is the theory of James Croll and Milutin Milankovitch. This Wikipedia article is an excellent overview. I particularly like the reference to Croll´s 1885 work on Climate and Cosmology, which anticipates the modern term cosmoclimatology.

Milankovitch.https://en.wikipedia.org/wiki/James_Croll

Another by one of James Aber´s students is quite good.

http://academic.emporia.edu/aberjame/student/howard2/theory.htm

I am too old to be around to witness the overturning of the scientific blunder we call anthropogenic global warming. You are too. But some of the younger folks engaging in this discussion will look back and maybe laugh. I cannot laugh because I see how much harm is being done to the poor by misguided energy policies and how much future harm is already in the pipeline.

And as a traditional environmentalist since childhood, I am saddened by the gross negligence of real environmental issues caused by this quasi-religious belief that mankind is responsible for disastrous climate change.

We were once taught that the hypsithermal, about 6,000 years ago, was warmer than now and that it was called the Holocene Climate Optimum. We know that the Eemian Interglacial, nominally 100,000 years ago, was substantially warmer than now. Nobody knows what is the optimum average global temperature.

We know that during the last glacial maximum, atmospheric CO2 dropped to 180 to 190 ppm, a low for plant life. Nobody knows what is the optimum level of atmospheric CO2 for the planet. Possibly it is four times what it is at present.

What is the practical minimum level of CO2 for life on Earth? Biology stack reports, "For a C3 plant, carbon dioxide compensation point is around 50ppm (Tolbert, Benker and Beck, 1995). Thus, we can say that, as a rough estimate, the value you want lies between 50ppm and 170ppm (probably closer to 170ppm than to 50ppm)." I have read that a good rule of thumb is 150ppm.

So pre-industrial CO2 at 280ppm was still too near the practical minimum for plant life. The present 400 ppm is still too low for optimum plant life, taking account that commercial greenhouse operators like to maintain CO2 around 1500 ppm, about four times the present level.

In my opinion, we are witnessing in climate alarmism the greatest scientific blunder in history. One of the worst aspects is the adjustment of the data to fit the theory. While I do not object to the time-of-day adjustment and similar corrections as one-off events, the continual adjustment of historical data seems bizarre and the destruction of the originally recorded historical climate data borders on the criminal.

The BOM in Australia was recently exposed for setting a lower cut-off point below which their automatic instruments did not record temperature, which automatically biased upwards daily average temperatures. This is a new low point in climate science malpractice. And a significant bias, because it has been shown that rising daily minimums influence the upward trend in average temperature more than daily maximums. (The urban heat-island-effect is one cause of this phenomenon.)

In my opinion, the "climatism" blunder has become institutionalized in other ways than adjusting the data. "Climatism" has corrupted environmental science, so we now have a quasi-religion, "Environmentalism". So much so, that when I read "environmental education", I think of the words "Green propaganda" and again, as a traditional environmentalist, I am horrified by this word-association.

Sources:

Last Glacial Maximum CO2 and δ13C successfully reconciled

N. Bouttes et al, 2011.

Biology Stack: https://biology.stackexchange.com/questions/29943/whats-the-or-some-of-the-minimums-amount-of-atmospheric-carbon-dioxide-need

Ken

Now you resort to ad hominem of which you always accuse others

Yet: to think that you know better, without any study, climatology (as written down in the IPCC report the Science of Climate Change) better than a thousand experts shows you are fully out of phase with science to put it mildly

Kenneth, thank you for your comment. I have some answers based on my historical reflections. I will arrange them as the answers to your comments:

“I don't understand how any climate model can become acceptable, reliable when nobody can factor in confidently the paths that will be taken by the unpredictable natural variations... as previously mentioned.”

We can consider an ensemble of model runs with various scenarios accounting for unpredictable events. If we accept the notion, that climate is characterized by an attractor in the phase space, we can determine whether or not the random forcing moves the system away from its current attractor.

“This can be done retroactively...so-called "hind-cast" models. Continual "tweaking" to get the "right" result is fooling one's self. Nobody can predict which way the climate will decide to go. History shows us that it often reverses itself.”

Nature is obeying certain least action principles. This idea is due to Leibniz, Fermat, Maupertuis, and Lagrange. While evolving, the Earth system is also “tweaking” its responses in order to stay on a trajectory consistent with the least action principles. Looking at the Earth atmosphere from this point of view, indicates how important are the variational and optimization approaches. I can envision the emergence of new tools, such as optimum transportation theory, in the next decade. They could resolve some of our doubts concerning the predictability of the Earth system.

“We almost made a mistake when the climate cooled after the late 1930s. We may be doing it again? "Damn the torpedos, full speed ahead"?”

Human actions are also determined by solutions of the constrained optimization problems. Examples shown in your diagram are evidently wrong; they were rejected by solving formally the mathematical models (in the past these models were analytical). The main issue here is, of course, how to define the cost functional.

Kenneth... Thanks again for this information. The newspaper clip is not sufficient to describe this impressive new model; for complete description please see

https://www.llnl.gov/news/new-exascale-system-earth-simulation

Kenneth, you mentioned $80 million for the new GCM (model) and express scepticism about whether or not the DOE got value for money.

All college level atmospheric physics textbooks show how to calculate future global average temperature for any level of atmospheric carbon dioxide. The textbooks use one-dimensional models and the calculations can be done on the back of an envelop with a hand calculator.

With the same assumptions for greenhouse gases, water vapour and clouds, the global average result is the same as for GCMs.

What the one-dimensional models cannot do is project temperature by region. For that, you need a global grid of at least 50,000 cells. So a simple test would be whether or not the new model when back-cast will do a better job for regions than earlier models. The real test will be to see if the projection for the year 2033 fits the regional observations in 2033.

Bridge engineers should be bidding for these contracts instead of risky bridge contracts. Because in ten years nobody will remember what happened to the GCM software. But if a bridge built today collapses in ten there will be hell to pay.

GCM development sounds like a great business.

Aleš,

In 2013 the IPCC set out what it consider were the main objectives of the physical science group. The following outline of the methodology has stuck in my mind:

" Improve methods to quantify uncertainties of climate projections and scenarios, including development and exploration of long-term ensemble simulations using complex models. The climate system is a coupled non-linear chaotic system, and therefore the long-term prediction of future climate states is not possible. Rather the focus must be upon the prediction of the probability distribution of the systems future possible states by the generation of ensembles of model solutions. Addressing adequately the statistical nature of climate is computationally intensive and requires the application of new methods of model diagnosis, but such statistical information is essential. "

IPCC, Fifth Assessment Report(2013) Working Group I: The Scientific Basis, Executive Summary, first page, bullet point 6.

https://www.ipcc.ch/ipccreports/tar/wg1/501.htm

In your view, if (1)

"The climate system is a coupled non-linear chaotic system, and therefore the long-term prediction of future climate states is not possible."

then is it feasible to predict according to the methodology set out in this report? (2)

"Rather the focus must be upon the prediction of the probability distribution of the systems future possible states by the generation of ensembles of model solutions."

Can an ensemble of results from 35 or 100 groups worldwide using different approaches to parameterization of water vapour and clouds resolve the prediction problem set out in (1) above?

Aleš, thanks for the response.

I will not be participating here for a while because I have just started a little research project.

Drlatief Ahmad

Trust? I suggest to correlate the GCM data with your observed station data, then only you can come to the conclusion

Aleš,

The role of long-term evolutionary change is indeed neglected in many studies, but it is also obvious that even on a smaller time scale, we can observe the amazing ability of the Earth system to form waves and patterns according to a paradigm of order. emerging from chaos. Moreover, the seemingly chaotic atmospheric system has a property described as the persistence of order. In the high Reynolds flow regime, as in the Earth's atmosphere, we can regularly observe coherent structures such as depressions, persistent blocking systems and jet streams. These structures emerge from the chaotic background flow. For the excellent discussion of this topic please see

http://chaos.utexas.edu/manuscripts/1067543693.pdf

Maybe one day we can write the "climate equations" in the form of the Turing reaction-diffusion system. We still do not know how to deduce such equations and how to define generalized diffusivities and kinetic coefficients.

Kenneth... Maybe it’s just a dream to control the natural system, but we do know some examples from the past when the impossible has become a part of everyday activities.

Considering the "cost" of such a dream, it is true that we can not predict all the effects. According to the US National Academies of Science, Engineering and Medicine, climate intervention technologies "pose considerable risks and should not be deployed at this time." They suggest more research before making the decisions.

https://nas-sites.org/americasclimatechoices/other-reports-on-climate-change/climate-intervention-reports/

The story of Icarus is instructive, not only as an example of human behavior, but also as a guide for our actions. Before the flight, Daedalus instructed his son:

“My son, I caution you to keep

the middle way, for if your pinions dip

too low the waters may impede your flight;

and if they soar too high the sun may scorch them.

Fly midway. Gaze not at the boundless sky,

far Ursa Major and Bootes next.

Nor on Orion with his flashing brand,

but follow my safe guidance.”

Source:

P. Ovidius Naso, Metamorphoses

http://www.perseus.tufts.edu/hopper/text?doc=Perseus%3Atext%3A1999.02.0028%3Abook%3D8%3Acard%3D183

I wonder if this is still applicable in the context of our debate?

In the mean time the future of climate models looks quite interesting as discussed in the recent paper by Palmer

http://rspa.royalsocietypublishing.org/content/472/2188/20150772

Ken

Shows your complete ignorance

El Nino and Nina are part of climate VARIABILITY, averaging out over the long run

This why climate is defined over a period for whihc such variations average out

Read for once Vaughan Pratt's analysis I will provide you again here

Then my question:

why didn't you read it yet? in the blog of a "fellow-denier" of yours, Judith Curry

https://judithcurry.com/2015/11/03/natural-climate-variability-during-1880-1950-a-response-to-shaun-lovejoy/

Drlatief Ahmad

GCM are ensemble models from different sources like UKMO, JMA, NCMRWF, ECMRWF etc. If they are matching with your station data, then only we can trust upon them. You have to correlate it with your station data then use SDSM technique

Kenneth

And also less than 15 days ago you were asked over and over again to present YOUR credentials versus those of the hundreds of meteorologists who contribute to the IPCC scientific report on Global Warming using the re-evaluated data

Ken

I make it easy for you to respond by writing numbering the remarks

1. Answer the question: what are YOUR scientific CREDENTIALS??

2. Credentials of the HUNDREDS of scientists who contributed to the scientific IPCC report of WG1

"Climate Change the scientific basis"

you can easily find yourself when you took an effort to READ it once

Ken

Your credentials please in THIS area of CLIMATOLOGY

versus that of the hundreds of climatologists writing and contributing to the Report of the Climatology Report of IPCC known as WG1

The report is based on thousands of publications

FYI you can easily download and check via GoogleScholar the credentials of all authors, contributors and reviewers

Ken

You are now posting completely insane info

I refer you to the thousands of climatologists who contribute(d) to the scientific IPCC reports(s) and you mention literally that

"Harry is quite happy with what Al Gore ...can assert"

Show me where I even EVER mentioned those names?

Your credentials at ResearchGate show that you are by no means a climatologist or atmospheric scientist

Ken is now blatant lies re my person

Ken a self claimed expert in atmospheric science? Show us

Did Ken check what I did in climatology the last three decades: NO he did not; else he had noticed I headed cluster projects for twenty years in the national climate research programme including a project developing a regional climate model

Ken

Do we still live in 1977???

Do you BTW know in which area I did my PhD work? and how it relates to meteorology

You think that in the say 30-odd active years I did not develop?

For once: read my publications and notice that the majority of those 300-odd contributions are in Atmospheric Science and Meteorology; not to mention the theses done under my supervision

What about YOUR credentials as atmospheric physicist?

Ken

My PhD was on the rate of vibrational energy dissipation in small molecules as occurring in the atmosphere.

In addition I was trained as a spectroscopist (necessary in understanding the propagation and absorption of light and IR in the atmosphere)

You can find my credentials in that area at ResearchGate in the questions

https://www.researchgate.net/post/Whats_the_difference_between_an_excitation_spectrum_and_an_absorption_spectrum_for_the_same_molecule

And give us YOUR credentials by which you claim your authority to judge mine

And why can't you even find the data yourself for the increase in global temperatures even at the best known denier site

https://wattsupwiththat.com/2018/05/global-temperature-update-for-april-2018/

and these are for satellite data that are of lower quality than station data; here for instance

And YES only for the US there is a dip in April temperature but the US is only part of this world

https://climate.copernicus.eu/resources/data-analysis/average-surface-air-temperature-analysis/monthly-maps/surface-air-8

Ken

You now even reside to unquoted sentences without clipping?

How the hell can we know what this means. This is not science

And after first bashing my credentials you now say it is not so important?

Remains my question to you since you started it what are your credentials during your scientific career with respect to climate/atmospheric science/meteorology or related areas; I only saw letters sent about ozone hole.

Ken

Instead of your slander that you accuse others of you should once state YOUR credentials. why do you bring up the credentials of the questioner? He is the one asking. It is the replier who should have expertise and the proper credentials.

So why are YOUR credentials not an issue? because they are not there?

Ken

You obviously do not understand basic climatology

a 0.8 C increase in global Temp, in just half a century is HUGE; and this is with a 40% increase in CO2. So what about an additional 60% increase in "CO2"?