Guest essay by Pat Frank
Today’s offering is a morality tale about the clash of honesty with self-interest, of integrity with income, and of arrogance with ignorance.
I’m bringing out the events below for general perusal only because they’re a perfect miniature of the sewer that is consensus climatology.
And also because corrupt practice battens in the dark. With Anthony’s help, we’ll let in some light.
On November third Anthony posted about a new statistical method of evaluating climate models, published in “Geoscientific Model Development” (GMD), a journal then unfamiliar to me.
WUWT readers will remember my recent post about unsuccessful attempts to publish on error propagation and climate model reliability. So I thought, “A new journal to try!”
Copernicus Publications publishes Geoscientific Model Development under the European Geosciences Union.
The Journal advertises itself as, “an international scientific journal dedicated to the publication and public discussion of the description, development, and evaluation of numerical models of the Earth system and its components.”
It welcomes papers that include, “new methods for assessment of models, including work on developing new metrics for assessing model performance and novel ways of comparing model results with observational data.”
GMD is the perfect Journal for the new method of model evaluation by propagation of calibration error.
So I gave it a try, and submitted my manuscript, “Propagation of Error and the Reliability of Global Air Temperature Projections“; samizdat manuscript here (13.5 mb pdf). Copernicus assigned a “topical editor” by reference to manuscript keywords.
My submission didn’t last 24 hours. It was rapidly rejected and deleted from the journal site.
The topical editor was Dr. James Annan, a climate modeler. Here’s what he wrote in full:
“Topical Editor Initial Decision: Reject (07 Nov 2017) by James Annan
“Comments to the Author:
“This manuscript is silly and I’d be embarrassed to waste the time of reputable scientists by sending it out for review. The trivial error of the author is the assumption that the ~4W/m^2 error in cloud forcing is compounded on an annual basis. Nowhere in the manuscript it is explained why the annual time scale is used as opposed to hourly, daily or centennially, which would make a huge difference to the results. The ~4W/m^2 error is in fact essentially time-invariant and thus if one is determined to pursue this approach, the correct time scale is actually infinite. Of course this is what underpins the use of anomalies for estimating change, versus using the absolute temperatures. I am confident that the author has already had this pointed out to them on numerous occasions (see refs below) and repeating this process in GMD will serve no useful purpose.”
Before I parse out the incompetent wonderfulness of Dr. Annan’s views, let’s take a very relevant excursion into GMD’s ethical guidelines about conflict of interest.
But if you’d like to anticipate the competence assessment, consult the 12 standard reviewer mistakes. Dr. Annan managed many ignorant gaffes in that one short paragraph.
But on to ethics: GMD’s ethical guidelines for editors include:
“An editor should give unbiased consideration to all manuscripts offered for publication…”
“Editors should avoid situations of real or perceived conflicts of interest in which the relationship could bias judgement of the manuscript.”
Copernicus Publications goes further and has a specific “Competing interests policy” for editors:
“A conflict of interest takes place when there is any interference with the objective decision making by an editor or objective peer review by the referee. Such secondary interests could be financial, personal, or in relation to any organization. If editors or referees encounter their own conflict of interest, they have to declare so and – if necessary – renounce their role in assessing the respective manuscript.”
In a lovely irony, my cover letter to chief editor Dr. Julia Hargreaves made this observation and request:
“Unfortunately, it is necessary to draw to your attention the very clear professional conflict of interest for any potential reviewer reliant on climate models for research. The same caution applies to a reviewer whose research is invested in the consensus position concerning the climatological impact of CO2 emissions.
“Therefore, it is requested that the choice of reviewers be among scientists who do not suffer such conflicts.
“I do understand that this study presents a severe test of professional integrity. Nevertheless I have confidence in your commitment to the full rigor of science.“
It turns out that Dr. Annan is co-principal of Blue Sky Research, Inc. Ltd., a for-profit company that offers climate modeling for hire, and that has at least one corporate contract.
Is it reasonable to surmise that Dr. Annan might have a financial conflict of interest with a critically negative appraisal of climate model reliability?
Is it another reasonable surmise that he may possibly have a strong negative, even reflexive, rejectionist response to a study that definitively finds climate models to have no predictive value?
In light of his very evident financial conflicts of interest, did editor Dr. Annan recuse himself knowing the actuality, not just the image, of a serious and impending impropriety? Nope.
It gets even better, though.
Dr. Julia Hargreaves is the GMD Chief Executive Editor. I cc’d her on the email correspondence with the Journal (see below). It is her responsibility to administer journal ethics.
Did she remove Dr. Annan? Nope.
I communicated Dr. Annan’s financial and professional conflicts of interest to Copernicus Publications (see the emails below). The Publisher is the ultimate administrator of Journal ethics.
Did the publisher step in to excuse Dr. Annan? Nope.
It also turns out that GMD Chief Executive Editor Dr. Julia Hargreaves is the other co-principal of Blue Sky Research, Inc. Ltd.
She shares the identical financial conflict of interest with Dr. Annan.
Julia Hargreaves and James Annan are also a co-live-in couple, perhaps even married.
One can’t help but wonder if there was a dinner-table conversation.
Is Julia capable of administering James’ obvious financial conflict of interest violation? Apparently no more than is James.
Is Julia capable of administering her own obvious financial conflict of interest? Does James have free rein at GMD, Julia’s Executive Editorship withal? Evidently, the answers are no and yes.
Should financially conflicted Julia and James have any editorial responsibilities at all, at a respectable Journal pretending critical appraisals of climate models?
Both Dr. Annan and Dr. Hargreaves also have a research focus on climate modeling. Any grant monies depend on the perceived efficacy of climate models.
They will have a separate professional conflict of interest with any critical study of climate models that comes to negative conclusions.
So much for conflict of interest.
Let’s proceed to Dr. Annan’s technical comments. This will be brief.
We can note his very unprofessional first sentence and bypass it in compassionate silence.
He wrote, “… ~4W/m^2 error in cloud forcing…” except it is ±4 W/m^2 not Dr. Annan’s positive sign +4 W/m^2. Apparently for Dr. Annan, ± = +.
And ±4 W/m^2 is a calibration error statistic, not an energetic forcing.
That one phrase alone engages mistakes 2, 4, and 6.
How does it happen that a PhD in mathematics does not understand rms (root-mean-square) and cannot distinguish a “±” from a “+”?
How comes a PhD mathematician unable to discern a physically real energy from a statistic?
Next, “the assumption that the [error] is compounded on an annual basis”
That “assumption” is instead a demonstration. Ten pages of the manuscript are dedicated to showing the error arises within the models, is a systematic calibration error, and necessarily propagates stepwise.
Dr. Annan here qualifies for the honor of mistakes 4 and 5.
Next, “Nowhere in the manuscript it is explained why the annual time scale is used as opposed to hourly, daily or centennially,…”
Exactly “why” was fully explained in manuscript Section 2.4.1 (pp. 28-30), and the full derivation was provided in Supporting Information Section 6.2.
Dr. Annan merits a specialty award for extraordinarily careless reading.
On to, “The ~4W/m^2 error is in fact essentially time-invariant…”
Like Mr. andthentheresphysics, Nick Stokes, and Dr. Patrick Brown, Dr. Annan apparently does not understand that a time average is a statistic conveying, ‘mean magnitude per time-unit.’ This concept is evidently not covered in the Ph.D.
And then, “the correct time scale is actually infinite.”
Except it’s not infinite, (see above), but here Dr. Annan has made a self-serving interpretative choice. Dr. Annan actually wrote that his +4 W/m^2 is “time-invariant,” which is also consistent with an infinitely short time. The propagated uncertainty is then also infinite; good job, Dr. Annan.
Penultimately, “this is what underpins the use of anomalies for estimating change…”
Dr. Annan again assumed ±4 W/m^2 statistic is a constant +4 W/m^2 physical offset error, reiterating mistakes 4, 6, 7, and 9.
And it’s always nice to finish up with an irony: “I am confident that the author has already had this pointed out to them on numerous occasions…”
In this, finally, Dr. Annan is correct (except grammatically; referencing a singular noun with a plural pronoun).
I have yet to encounter a single climate modeler who understands:
- that “±” is not “+,”
- that an error statistic is not a physical energy,
- that taking anomalies does not remove physical uncertainty,
- that models can be calibrated at all,
- or that systematic calibration error propagates through subsequent calculations.
Dr. Annan now joins that chorus.
The predominance of mathematicians among climate modelers, like Dr. Annan, explains why climate modeling is in such a shambles.
Dr. Annan’s publication list illustrates the problem. Not one paper concerns incorporating new physical theory into a model. Climate modeling is all about statistics.
It hardly bears mentioning that statistics is not physics. But that absolutely critical distinction is obviously lost on climate modelers, and even on consensus-supporting scientists.
None of these people are scientists. None of them know how to think scientifically.
They have made the whole modeling enterprise a warm little pool of Platonic idealism, untroubled by the cold relentless currents of science and its dreadfully impersonal tests of experiment, observation, and physical error.
In their hands, climate models have become more elaborate but not more accurate.
In fact, apart from Lindzen and Choi’s Iris theory, there doesn’t seem to have been any advance in the physical theory of climate since at least 1990.
Such is the baleful influence on science of unconstrained mathematical idealism.
The whole Journal response reeks of fake ethics and arrogant incompetence.
In my opinion, GMD ethics have proven to be window dressing on a house given over to corruption; a fraud.
Also in my opinion, this one episode is emblematic of all of consensus climate science.
Finally, the email traffic is reproduced below.
My responses to the Journal pointed out Dr. Annan’s conflict of interest and obvious errors. On those grounds, I asked that the manuscript be reinstated. I always cc’d GMD Chief Executive Editor Dr. Julia Hargreaves.
The Journal remained silent, no matter even the clear violations of its own ethical pronouncements; as did Dr. Hargreaves.
1. GMD’s notice of rejection:
From: editorial@xxx.xxx
Subject: gmd-2017-281 (author) – manuscript not accepted
Date: November 7, 2017 at 6:07 AM
To: pfrankxx@xxx.xxx
Dear Patrick Frank,
We regret that your following submission was not accepted for publication in GMD:
Title: Propagation of Error and the Reliability of Global Air Temperature Projections
Author(s): Patrick Frank
MS No.: gmd-2017-281
MS Type: Methods for assessment of models
Iteration: Initial Submission
You can view the reasons for this decision via your MS Overview: http://editor.copernicus.org/GMD/my_manuscript_overview
To log in, please use your Copernicus Office user ID xxxxx.
We thank you very much for your understanding and hope that you will consider GMD again for the publication of your future scientific papers.
In case any questions arise, please contact me.
Kind regards,
Natascha Töpfer
Copernicus Publications
Editorial Support
editorial@xxx.xxx
on behalf of the GMD Editorial Board
+++++++++++++++
2. My first response:
From: Patrick Frank pfrankxx@xxx.xxx
Subject: Re: gmd-2017-281 (author) – manuscript not accepted
Date: November 7, 2017 at 7:46 PM
To: editorial@xxx.xxx
Cc: jules@xxx.xxx.xxx
Dear Ms. Töpfer,
Dr. Annan has a vested economic interest in climate modeling. He does not qualify as editor under the ethical conflict of interest guidelines of the Journal.
Dr. Annan’s posted appraisal is factually, indeed fatally, incorrect.
Dr. Annan wrongly claimed the ±4 W/m^2 annual error is explained “nowhere in the manuscript.” It is explained on page 30, lines 571-584.
The full derivation is provided in Supporting Information Section 6.2.
There is no doubt that the ±4 W/m^2 is an annual calibration uncertainty.
One can only surmise that Dr. Annan did not read the manuscript before coming to his decision.
Dr. Annan also made the naïve error of supposing that the ±4 W/m^2 calibration uncertainty is a constant offset physical error.
Plus/minus cannot be constant positive (or negative). It cannot be subtracted away in an anomaly.
Dr. Annan’s rejection is not only scientifically unjustifiable. It is not even scientific.
I ask that Dr. Annan be excused on ethical grounds, and on the grounds of an obviously careless and truly incompetent initial appraisal.
I further respectfully ask that the manuscript be reinstated and re-assigned to an alternative editor who is capable of non-partisan stewardship.
Thank-you for your consideration,
Pat
Patrick Frank, Ph.D.
Palo Alto, CA 94301
email: pfrankxx@xxx.xxx
++++++++++++++++
3. Journal response #1: silence.
+++++++++++++
4. My second response:
From: Patrick Frank pfrankxx@xxx.xxx
Subject: Re: gmd-2017-281
Date: November 8, 2017 at 8:08 PM
To: editorial@xxx.xxx
Cc: jules@xxx.xxx.xxx
Dear Ms. Töpfer,
One suspects the present situation is difficult for you. So, let me make things plain.
I am a Ph.D. physical methods experimental chemist with emphasis in X-ray spectroscopy. I work at Stanford University.
My email address there is xxx@xxx.edu, if you would like to verify my standing.
I have 30+ years of experience, international collaborators, and an extensive publication record.
My most recent paper is Patrick Frank, et al., (2017) “Spin-Polarization-Induced Pre-edge Transitions in the Sulfur K‑Edge XAS Spectra of Open-Shell Transition-Metal Sulfates: Spectroscopic Validation of σ‑Bond Electron Transfer” Inorganic Chemistry 56, 1080-1093; doi: 10.1021/acs.inorgchem.6b00991.
Physical error analysis is routine for me. Manuscript gmd-2017-281 strictly focuses on physical error analysis.
Dr. Annan is a mathematician. He has no training in the physical sciences. He has no training or experience in assessing systematic physical error and its impacts.
He is unlikely to ever have made a measurement, or worked with an instrument, or to have propagated systematic physical error through a calculation.
A survey of Dr. Annan’s publication titles shows no indication of physical error analysis.
His comments on gmd-2017-281 reveal no understanding of the physical uncertainty deriving from model calibration error.
He evidently does not realize that physical knowledge statements are conditioned by physical uncertainty.
Dr. Annan has no training in physical error analysis. He has no experience with physical error analysis. He has never engaged the systematic error that is the focus of gmd-2017-281.
Dr. Annan is not qualified to evaluate the manuscript. He is not competent to be the manuscript editor. He is not competent to be a reviewer.
Dr. Annan’s comments on gmd-2017-281 are no more than ignorant.
This is all in addition to Dr. Annan’s very serious conflict of financial and professional interest with the content of gmd-2017-281.
Journal ethics demand that he should have immediately recused himself. However, he did not do so.
I ask you to reinstate gmd-2017-281 and assign a competent and ethical editor capable of knowledgeable and impartial review.
Geoscientific Model Development can be a Journal devoted to science.
Or it can play at nonsense.
The choice is yours.
I will not bother you further, of course. Silence will be evidence of your choice for nonsense.
Best wishes,
Pat
Patrick Frank, Ph.D.
Palo Alto, CA 94301
email: pfrankxx@xxx.xxx
++++++++++++++++++
5. Journal response #2: silence.
++++++++++++++++++
The journal has remained silent as of 11 November 2017.
They have chosen to play at nonsense. So chooses all of consensus climate so-called science.
I was interested enough in the origin of the Journals and the EGU (European Geosciences Union) to look a bit further and found that a number of open access journals are published under their aegis . I spent some time (which should have better employed tidying up the garden) browsing through some of the articles , in “Climate of the Past” and “Nonlinear processes in Geophysics ” from which I found that the surface mass balance of ice in the Antarctic has apparently been increasing in recent years (well to 2010) and that hurricane statistics in the Gulf and surrounding ocean are best described as being “on the edge of chaos” . Don’t know what that means but pretty sure it is not the model that Al Gore and the BBC are putting out.
One that rather destroyed the image of climate scientists being motivated by less than honest or altruistic motives is one which describes the cyclical changes in a simple (the authors call it a “toy model”) ocean + vegetated land model. Something like sawtoothed ice ages result . However in their conclusions the authors are refreshingly and rather charmingly self effacing :
“-Our paper is only trying to make a case for the possibility
of vegetation playing a more important role than contemplated
heretofore and does not claim in the least to have
definitively proven that this is so. A similar argument about
local versus global effects has been made with respect to
the oceans’ thermohaline circulation. Recall that the Stommel
(1961) paper – much quoted recently in the context of
multiple equilibria and symmetry breaking in the meridional
overturning of the Atlantic or even global ocean – was originally
written to explain seasonal changes in the overturning
of “large semi-enclosed seas (e.g. Mediterranean and Red
Seas)”; see, for instance, Dijkstra and Ghil (2005).
There is no better way of concluding this broader assessment
of our toy model’s results than by citing Karl Popper:
“Science may be described as the art of systematic oversimplification”
(Popper, 1982). It might be well to remember this
statement, given an increasing tendency in the climate sciences
to rely more and more on GCMs, to the detriment of
simpler models in the hierarchy.”
https://www.nonlin-processes-geophys.net/22/275/2015/
” science as the art of systematic oversimplification ” – another Popper phrase to add to those people here like to quote.
Is a $10 million lawsuit in order?
Pat
I’ll comment here rather than your recent post on your paper. The main contention in it is that the models are effectively mathematically equivalent to a linear sum of forcing that is then iterated. There may be a few noise terms in there but this is the point in general. From here it’s easy to show that the uncertainties will compound i.e. the increasing systematic error envelope.
So the question is: can this equivalence be shown from first principles? As in is it in the design itself rather than just being similar in form? Because as someone who has built models before, and dealt with modellers, there may be a pedantic point to say the models are not linear sums even though they produce behaviour like it.
It’s a nuance point but it’s also a niggling one that means they can easily dismiss what you say.
The design replicates linear sums quite deliberately. As I have said before , replace all variables with the timetables of London buses, leaving the forcing intact and you end up with the same answers ( and errors).
Its numerology, GIGO, call it what you want, its nothing to do with science.
And people like Nick are so proud/bemused by their ‘shiny complicated models’ that they don’t realise it. And those that do, stay dumb because their noses are in the trough.
Jim
I went and searched for “climate model mathematics” and came across :
MATHEMATICAL MODELS OF LIFE SUPPORT SYSTEMS – Vol. I – Mathematical Models for Prediction of Climate – Dymnikov V.P.
Equation (1) in this short article (that is taken from a book) is that most if not all climate models can be reduced to a canonical state:
∂φ/∂t + K(φ)φ = −Sφ + f
where:
So integrating over multiple steps will integrate the uncertainties in f. So the thing that Pat gets wrong is that the time period should actually be the time period of integration, which may be a month.
A sensitivity analysis would should that the models are useless if f is not properly bounded.
The alternative is to theorise a value for f but that just means the models are hypothetical exercises and not fit for anything.
“So integrating over multiple steps will integrate the uncertainties in f.”
No, it doesn’t. That’s a misunderstanding of differential equations, which is somewhat relevant to where Pat goes wrong. Suppose K is zero and f is constant. The solution is f/S+C*exp(-S*t), where C is constant that gives different solutions (fixed by initial conditions). It doesn’t increase linearly with f, as would an integral. In fact, it is a control equation which pulls the solution to a particular trajectory. And if f is something that fluctuates about zero, that will certainly not produce a greater rate of increase.
“It doesn’t increase linearly with f”
sorry, linearly with time t.
Nick
If you iterate the equation then the dt is removed and you move from step to step. If f is an external factor at t = 0 with uncertainty then this will affect the change of state. At time = 1 step then the error in f will affect the next result and so on.
You appear to be conflating continuous solutions with numerical methods. You are solving the equation rather than using the equation iteratively. My question originally was about whether forcing was treated as a linear factor. As it turns out it is canonically. So it should apply to all climate models.
And this equation shows that if you use a real world value you need to be very careful if the uncertainties are large as well as trying to find a suitable time period before it blows up. As others have pointed out, that’s good for weather.
I saw the same thing modelling plasmas compared to erosion caused be plasmas.
“You are solving the equation rather than using the equation iteratively.”
An iterative numerical process isn’t worth much if it doesn’t solve the equation.
An iterative process is a numerical way to model dynamics. You can run it to achieve a solution or just to see what happens. It depends on what you want to achieve. A control algorithm can be written as a differential equation but it doesn’t have a solution, just a range and possible limiting functions. I wrote such a function for ion thruster control.
The point is that if you have uncertainties in the inputs to each step you quickly can diverge from what you expect unless you account for these. That’s a pretty standard check in numerical modelling, Nick. And it’s what Pat is talking about.
“The point is that if you have uncertainties in the inputs to each step you quickly can diverge from what you expect unless you account for these. That’s a pretty standard check in numerical modelling, Nick.”
It’s what I have spent a large part of my professional life dealing with. It is what is illustrated with your equation, with K=0. If S is positive, deviations from the solution are corrected. The solution is stable. If S is negative, the solution is unstable. Errors grow. If it is a system of equations, you need all the eigenvalues of S to be positive. Your text actually specifies that (S is positive definite). People really know about this stuff. They need to.
Nick
They don’t know K, or phi, or S. That’s the point. They use the equation to try and solve for this. What is known is f (with uncertainty). So they iterate with a forcing number. That’s the issue.
Nick,
you example is just irrelevant. As you pointed out, it is an example of fully controlled, exponentially damped, equilibrium bound system, where the pertinent variable isn’t φ, but φ-f/S, and where time basically has exponentialy decreasing importance (so of course the error do not depend on time: nothing does!)
Is Climate this sort of system? No it isn’t…
No one discuss the fact that some systems are able to controlable, and any error will be damped to effectively zero. That the whole point of control theory!
The purpose of the paper was to check what behavior can be expected in the case of climate models. The author says that in this case, the error propagates to infinity, that is, the ratio (φ-φ’)/(f-f’) is NOT bound in any way
(where f’ is the real, unknown, forcing; f-f’ is the error; and φ’ is the real trajectory with the real forcing f’)
Which is just basically a definition of a chaotic system, BTW.
In essence, the reviewer states that climate model are not chaotic. Which is double wrong. They ARE (as evidenced by the spaghetti), and since the climate is chaotic, they have better be chaotic too.
“you example is just irrelevant”
For heaven’s sake, it isn’t my example.
Nick, you have been found out. You don’t really understand the application of those lovely complicated models you run. You ‘believe’, you don’t ‘know’. There is a world of difference.
Oh, and you continue to show basic misunderstanding of statistics. But you continue to lie in vain attempts to cover your shortcomings
‘ People really know about this stuff. They need to.’ Yes they do, otherwise ‘real things’ would break or fall down. You clearly don’t, but it doesn’t matter except for the support people like you give to those who bleed economies around the world financing useless ‘energy projects’. That ultimately will cost lives, millions of them. I hope you sleep well.
“I hope you sleep well.”
I doubt Nick has even the slightest bit of shame or conscience that he is supporting an agenda that, in its own words, is trying to bring down western society.
And he will LIE and squirm and deceive and misrepresent, against all rational maths and science, as long as he can to keep his support for that evil, irksome agenda going,
Micky, I haven’t checked the models themselves. I’ve only emulated their behavior.
However, a repeated criticism of my reviewers has been that the emulation equation is incomplete physics because it does not include a term for ocean heat capacity.
One can infer from that comment, that the models do just incorporate a linear extrapolation of forcing, but that it’s modified by other thermal responses.
Also, in one of my responses, I noted that the IPCC itself states there is a linear relation between forcing and projected air temperature, which they express as ΔTs = λΔF, where λ is model climate sensitivity.
That’s in Pyle, J., et al. (2016), Chapter 1. Ozone and Climate: A Review of Interconnections, in Safeguarding the Ozone Layer and the Global Climate System: Issues Related to Hydrofluorocarbons and Perfluorocarbons” IPCC/TEAP Geneva.
The emulation equation isn’t about physics, of course, which makes irrelevant the criticism that it’s physically incomplete.
I’ve read your paper and based on what I had a look at (the canonical equation above) and your findings with the emulation, the basic idea is that irrespective of what the details of climate models are doing, their behaviour is numerically equivalent to a much more simple linear sum of forcing. So it doesn’t matter what fancy maths is happening or how differential equations are being solved or limited, the effect can easily be replicated by a much more simple equation.
In doing so it highlights the sensitivity of the models to forcing and it appears that if you take for example, the yearly forcing, and include uncertainties in that value, the expansion of the range of possible temperatures makes the models become not very useful.
So the key element is the effect of the numerical wizardry is to produce a much more simple relationship that can be emulated. And this linear relationship is also expressed by the IPCC.
The key is that if you can emulate with a simple relationship and that it shows very good agreement with a whole host of models of different types, then the resultant core of the models is linear i.e higher order terms are being minimised.
It is actually a very nuanced argument Pat. It’s like using a complicated polynomial expansion only to find out your higher terms are all zero over the range of values you use it on!
Just to add: because you use an emulation, effectively like a reverse engineering process, and you don’t necessarily need to know exactly what is going on in the models, I believe this is why you are getting the responses.
Playing Devil’s Advocate: First of all, it’s not a derivation or understanding from first principles. It also does not detail how the forcing values are used to calculate the internal states, run or solve differential relationships and so on. A modeller would look at all the whistles and bells and say, no the model is not run like that.
However, mathematically, what matters is the result and how it behaves within a range of data. It is the reverse argument to many here who look for higher terms in temperature data, only to be told that a linear fit applies.
Whatever higher terms and processes are going on the result can be fit to a linear sum, which then implies that the behaviour of the model produces a result with characteristics similar to a linear sum. One being sensitivity to uncertainties as you have shown.
I don’t know if this is way you describe the argument though Pat. It might be lost in translation a bit. I could be wrong.
micky, I interpret Pat Frank’s work similarly. I haven’t yet seen a single valid rebutal of the core findings 1) a very simple linear finction can emulate complex climate model output. Kind of embarassing if you’re demanding super computers tl run your complex models, and 2) uncertainty in the parameter values that come frome measurement is neither reported nor accounted for in the model output, and the correspondemce suggests that many climate modellers do not care for or understand error propagation, and do not possess a very good grasp of basic statistics.
RW
I also now see where Pat got the yearly error from. RMS error of the year is quoted in the L&H model so I can see why Pat uses the yearly emulation. It’s the highlight the problem using L&H as a candidate example.
“RMS error of the year is quoted in the L&H model”
It isn’t. They just quote rmse error 4 W/m2. . Nothing said about “of the year”. This is crucial to Pat’s numbers.
Pat,
Pardon a layman’s question, but based on micky’s explanation of your paper (which helped put it in context for me), it sounds as though there are two separate issues: 1) climate models are essentially just linear sums of forcing, and 2) error propagation in a model of linear sums should be calculated in such-and-such a way.
If this is accurate, shouldn’t there be two papers then: One arguing and demonstrating the first point, and another the second? This seems especially necessary since the second point is the one that you’re really interested in, and it appears that it’s dependent on the first.
Just a thought.
rip
Apologies to Pat. I read section 2.4.1 and the yearly uncertainty is because even the 20 year value is a sum of yearly calculations. Thats why the uncertainty is per year. The basis is a yearly value.
There has got to be a free market solution to this problem:
1) The Journals are controlled by activists, not interested in the truth. A climate journal needs to be edited by unbiased and disinterested people in the Stats, engineering and Mathematics fields. Rejected Climate Articles should be submitted to statistics or mathematics journals for publication. The existing climate science would never pass the rigor needed for publication in a real science journal.
2) Reproducibility and the Application of the Scientific Method would be a requirement for publication in any new Climate Journal. The very fact that the new journal announces that requirements would put the other journals on the defensive.
3) The new Journal could start by simply doing that happens here on WUWT. Existing published articles could be critiqued, and the flaws in their science and statistics could be exposed and validated by people in the math and science fields.
The first thing communist totalitarians do it take over the media and educational system. They have to control the message and censor all opposition. That is their well-known MO. Real scientists need to break that truth embargo imposed my the slimate climatists. There has to be a market for the truth, an entrepreneur just has to tap it. Aren’t there any scientific journals interested in the truth anymore?
WUWT Site stats
333,102,862 views
There is enough firepower there to generate interest in a new Journal. WUWT could team up with the other Global Warming Blog and start publishing an Alt-Science Journal, a journal clearly intended to challenge the status quo. The Alt-Title might appeal to the rebellious Millennials. Bottom line, there are no real barriers to entry to the Science Journal Industry, and WUWT has a vehicle to bring everyone together.
1) Hit counters are meaningless
2) New Journal? Try this: https://theoas.org/journal-of-the-oas/
These people don’t even demonstrate a solid understanding of statistics, let alone how statistics would connect to physical phenomena.
Errors of measurement seem to be far better understood by physical scientists and engineers than mathematicians which is ironic given the concept’s roots in statistics.
The editor and “reviewer” have definite conflicts of interest that bias them towards the consensus.
Even Ronan Connolly?
What did Ronan Connolly get right, Nick?
More weirdnesses
“How does it happen that a PhD in mathematics does not understand rms (root-mean-square) and cannot distinguish a “±” from a “+”?”
Just about anyone understands that rms is positive. Who talks about their voltage being ±110V?
James Annan says
“Nowhere in the manuscript it is explained why the annual time scale is used as opposed to hourly, daily or centennially, which would make a huge difference to the results.”
He’s right; I made that point at some length. A referee pointed out this weirdness – PF takes a 20 year average of something in W/m2 and says that the result has units W/m2/year. But why /year, just because the time period was described as 20 years? It’s also 240 months; why not W/m2/month? As James Annan says, it would make a huge difference to the result.
Nick,
“Who talks about their voltage being +-110V?” Well, an electrical engineer for one. Put a diode on one side of that +- feed and measure the result. Now reverse the polarity of the diode – get the same result? Now add a capacitor of sufficient size across the circuit and repeat the procedure. Answers the same in all cases? I think not, particularly depending on the type of measuring instrument. So it depends on your perspective and your needs. The consumer relies on the fact that is 110V appliance works when plugged into a 110V AC outlet, but try plugging a transformer-based device into 110DC. Obviously, it matters, so please don’t attack an attempt at clarity with a trivialization of his point.
No, the voltage may be ±, but the RMS measures the magnitude. An engineer would multiply the RMS by a phase term (after converting to peak to peak). It is James Annan who is correctly using magnitude.
Nick now try your answer with an AC voltage on a DC offset the situation Taylor describes with a half wave ripple.
http://www.ka-electronics.com/Images/jpg/Crest_Factor.JPG
The full wave rectified sine and half wave rectified sign whilst they have an RMS value you often put a +- in front of to show the DC offset direction.
I think I got your meaning but be very careful trying to make that absolute.
Nick,
You’re giving away some of your lack of knowledge. RMS is not the magnitude of an alternating waveform. It is merely the value (magnitude) of an equivalent DC voltage that gives the same power. You can not determine the RMS value of an alternating current, especially an asymmetric one by a simple multiplying of a phase term.
As before, this is dealing with a real world item. Simple math doesn’t always apply. By the way what is the RMS value of a sine wave of +- 110vac +- 5v?
RMS means root mean square. It’s as simple as that. There are no ± (or -) signs in LdB’s table. Yes, of course for non-sunusoids you can’t use a simple amplitude and phase characterisation. But RMS still means root mean square. Positive.
So you are saying in your field the RMS of a series of all negative numbers is positive, that would make analysis fun 🙂
I know what you mean but in many field we add the sign in for meaning. You can go thru the process of trying to split hairs the sign isn’t part of the RMS value but that is being vexatious 🙂
“So you are saying in your field the RMS of a series of all negative numbers is positive”
Of course it is.
I should say if you want to play vexatious then I am going to tell you that you can’t do square roots of negative numbers so any offset negative waveform can’t have an RMS 🙂
“you can’t do square roots of negative numbers”
Again, RMS is root mean square. Root. Mean. Square. Before you do anything else, the argument is squared. Everything is then positive. The mean is positive, so has a sqrt. RMS(-V)=RMS(V).
You see where this goes Nick all you can do is add a minus out the front to get all the numbers positive
-X + RMS
Then I am going to tell you that formula shows you specifically that you can’t do the RMS because you had to put a term in front of the RMS and you kicked and own goal.
As I said I would settle for your answer without vexatious extension 🙂
The basic problem is the negative has meaning no electrician or QM person is going to accept a positive RMS value on a negative basis offset because you lose meaning. You may never accept our answer but equally we can’t accept yours.
To give you an example if I had a -20VRMS and +20VRMS waveform I would correctly deduce there is 40Volts RMS between them. In your case I would have 20VRMS and 20VRMS and I would conclude there is 0Volts between them. Do you see the answer is completely miss leading. I i write your it long hand using your offset above I get the right answer -20VDC + 20VRMS and 20VDC + 20VRMS but it’s a lot more complicated, so you can think of it as shorthand.
Nick says..”RMS is a magnitude”
Yes, that means it can be in either direction
WAKE UP NICK !!
“RMS is root mean square.”
Nick, you mathematical IMBECILE.
Root = square root
ALWAYS a “±” answer.
A long time since you did junior high maths, isn’t it Nick.
Go back and RE-LEARN.
You guys do realize you’re wasting all this time and space on the purely semantic distinction between expressing RMS as a magnitude only, whose value must always be positive (and therefore implicitly understanding the +/- as part of the definition of RMS), or expressing RMS with the +/- signs?
Is it just me or does Nick Stokes not understand the difference between a Magnitude and a Vector? RMS is magnitude. He keeps making it a positive vector.
Kurt,
“You guys do realize you’re wasting all this time and space on the purely semantic distinction”
You could say that. My point is that RMS is well defined and is positive. You could make sense of an alternative usage, and getting the semantics messed up is not the worst thing in the world. My point is, well, I’ll repeat PF:
“How does it happen that a PhD in mathematics does not understand rms (root-mean-square) and cannot distinguish a “±” from a “+””
He’s using JA’s perfectly conventional and correct usage to try to discredit him as a scientist.
Gnrnr,
One thing RMS and magnitude of a vector do have in common is that they are both positive.
“One thing RMS and magnitude of a vector do have in common is that they are both positive.” Bzzzttt. You just failed a basic 1st year type engineering exam question. Vector has a direction, could be negative or positive. Magnitude has no direction, it is just a magnitude, not positive or negative.
“Vector has a direction, could be negative or positive.”
Well, it has multiple components. But I have not spoken of sign of a vector. Only its magnitude, which is positive (and scalar).
“He’s using JA’s perfectly conventional and correct usage to try to discredit him as a scientist.”
I should add that the issue to me isn’t the unfairness of that. It’s the ignorance. Undergrads, even school students, are supposed to know how to use RMS. You can possibly justify an alternative usage, with great care for consistency, but to slam Annan for orthodox use just shows ignorance of that undergrad teaching.
You still aren’t understanding it Nick.
“Well, it has multiple components. But I have not spoken of sign of a vector. Only its magnitude, which is positive (and scalar).”
As soon as you assign a positive or negative to it, you change it from a magnitude to a vector i.e. you give it a direction relative to some co-ordinate system. A magnitude is neither positive or negative (but is is scalar). Gravity has a magnitude of 9.81m/s^2, whether is is increasing your velocity or decreasing your velocity, depends on the direction you assign it (+ or -) with respect to the co-ordinate system you are working with. These is very basic concepts on magnitudes vs vectors. You keep conflating them together. Like I said earlier, you would fail basic 1st year engineering exams with your comments thus far.
“As soon as you assign a positive or negative to it, you change it from a magnitude to a vector”
Does that work for your bank account? But anyway, I’m the one that is resisting applying signs. A magnitude is positive in the sense that your height is positive. What else would it be? In any arithmetic, it is treated as a positive number.
Remember, the excoriation of James Annan was for not providing a sign.
“Does that work for your bank account?”
Most certainly does. Magnitude of the transaction is the $ amount of the transaction. Whether it adds to the account or subtracts from it makes it the vector (I personally like ones that add :)).
“A magnitude is positive in the sense that your height is positive.”
Yes, people’s heights are always positive. Good observation. The magnitude of the error of measurements of those heights if you take the RMS of the errors will also be to use your thinking, a positive number. eg, 1cm. The effect of that error will sometime be positive and sometimes be negative, hence +-1cm.
The magnitude is 4W/m^2, but the effect is +-4W/m^2, not +4W/m^2. Do you still not see your logic error?
Your wasting your time Nick is clearly engaging it semantics and that is all he is interested in to justify an answer. What Nick is not willing to discuss is what the intent of RMS is, which is and lets quote it
Nick is ignoring the intent to be deliberately deceptive.
Nick has the same argument that you can’t have negative money, hence a number such as -$10 can’t be written in an account. You either put it in a different column or color it red would be Nick’s argument.
If Nick or Climate Science is going to engage in this level of semantics they need to publish a formal definition of terms because you can’t use any known standards that are in use by the general community.
Nick, I would also warn you that if you look at all the truely great science papers in physics and I applied your level of semantics I don’t know any of them that would actually have been published.
There are a number of line by line analysis of Einsteins 1905 paper around and most will pick up the couple of errors. Using your level of semantics it would have been thrown out or is at the very least completely wrong.
I am pretty sure you could reject any paper based on semantics if you really put your mind to it.
“Nick has the same argument that you can’t have negative money”,/i>
No. I just said that it would be odd to say from its sign status that it is a vector. I have experienced negative money.
“and lets quote it”
I don’t know what you are quoting there. But it is very rare than you can add RMS directly. More often it is in quadrature. You can add the squares.
“Climate Science is going to engage in this level of semantics “
No, the semantics are from Pat Frank. He blasted James Annan for what is simply standard usage (also used by his source). And surely that raises the question – what’s going on here? What kind of world are we in?
If you and climate science in general go to this level you are on a slippery slope.
I haven’t got the time but if someone wants to do it go to all the important papers in climate science and just look at the quantities and exact wording. Find how many mistakes there are and then suggest they reject the papers based on semantic errors because that is where we have come to.
I guess it would also be interesting to ask Nick about papers with the expression -Energy in a physics paper. Energy is after defined almost everywhere as a positive value. Can I have -Energy in a paper?
Wow. So much commemt space was abused by this RMS nonsense.
As above, don’t trivialize. RMS of what? A square, triangular, sine wave? How about an asymmetric waveform that could have a negative value? How about a +-110v +_5 v.
Sorry Jim missed you had answered that. Yes hopefully we have explained Nick to be careful taking that to far.
With RMS of anything, you square it, which has to be positive, take the mean, and then the positive square root. The answer is a magnitude and has to be positive.
No it doesn’t Nick just look at the waveforms above turn the 2nd and 3rd upside down. You need to be able to separate the two waveforms and one is positive the other is negative. You possibly can’t do that in your problem but it happens in many problems. We get the same thing in QM where we have RMS to some Ket basis.
Nick, “With RMS of anything, you square it, which has to be positive, take the mean, and then the positive square root. The answer is a magnitude and has to be positive”
Now you’re bringing in external physical meaning, Nick, which changes everything.
And which explanation (physical meaning) you’ve always resisted whenever it produced conclusions you didn’t like, such as in the physical meaning of a time-average.
When only one root of a square root has physical meaning, within the context of science or engineering, that root is chosen for that reason: i.e., by reason of an externally located physical meaning.
The rms calculation itself always, repeat always, produces the ±root.
The fact that only physically meaningful roots are chosen in science has no bearing on the general result that RMS is always plus/minus.
“The rms calculation itself always, repeat always, produces the ±root.”
Does your calculator say that? Your computer? It’s nothing about physical meaning. It is a standard definition. RMS is always the positive square root.
Again my challenge – if it as you insist, point to just one reputable publication that uses that convention. For the actual RMS numbers. Your L&H source certainly doesn’t.
Here you go, Nick, Wiki itself:
“In experimental sciences, the [plus/minus] sign commonly indicates the confidence interval or error in a measurement, often the standard deviation or standard error. The sign may also represent an inclusive range of values that a reading might have.”
Standard deviation: rms conditioned by loss of one degree of freedom.
“Here you go, Nick”,/i>
Going round and round endlessly on this incredibly elementary stuff That link is actually to a page on the ± symbol. And it describes its use in defining a confidence interval. That says that the CI is a±b, where b is some rmse, sd or a multiple. That is the CI, but b, the RMSE, is a positive number. It makes no sense to speak of a±±4.
Still no progress with the challenge – to find an RMSE actually specified as, say, ±4, as you say Annan and L&H should have done.
“you know you are referring to a quantity which alternates between +110 and -110”
No. It alternates between about +155 and -155. The point is that RMS is a well-defined term, and is positive. It wouldn’t matter so much that Pat Frank has an eccentric view on it (it isn’t his worst) but one has to respond if he uses Annan’s prefectly conventional use to claim that he isn’t a scientist etc.
“your extremely selective quotation of a reviewers criticism without taking any account of the author’s response to that criticism”
I quoted both rounds, criticism and reply. But the main thing is the stream of accusations directed at Dr Connolly’s honesty (not to mention intellectual vacuity etc). Dr C is an independent scientist who often writes at WUWT. I think he’s a sceptic in good standing. So what is the basis for this? It can’t be supposed CoI.
“Your second point is just plain false.”
OK would you like to quote the parts of the author’s reply that would change the meaning from what I wrote?
Nick, “The point is that RMS is a well-defined term, and is positive.”
Wrong. RMS is always ±.
4^2 = 16
(-4)^2 = 16
sqrt(16) = ±4 and nothing else.
It’s that easy and you never fail to get it wrong, Nick.
Nick’s numerical conundrum was resolved here, and again here, and by micro6500 here.
And that set doesn’t exhaust the retinue.
I can’t tell whether you really don’t get it, Nick, or whether you’re just sticking to an obscurantist narrative.
“If asked I would say that RMS is a magnitude just like he does. If he is right..”
then James Annan was right. It’s Pat who is making an issue of something elementary, that wouldn’t be significant anywhere else..
“it takes him nowhere”
It seems from these posts that it’s Pat’s paper that is going nowhere.
Pat is right to take issue since it is crucial to the topic that all parties understand and are perceived to understand by one another exactly what is being referred to by uncertainty and error. It is painstakingly obvious that many of the reviewers do not get it.
Just to elucidate a little. The RMS value of a waveform is the equivalent DC value that would generate the same heating value if dissipated in a resistance. The DC value can be positive or it can be negative with respect to ground. The same amount of heat is dissipated either way, i.e. +-RMS.
Pat,
“RMS is always ±.”
Your link does not talk about RMS. It talks about what you must do if taking the square root of a quadratic equation. And then indeed the result must reflect the range of possible solutions of that equation. But that is not relevant here. RMS is a measure of the magnitude of variation. It was positive everywhere in Lauer and Hamilton. It was positive in the table of values that LdB showed. I repeat my challenge, if “RMS is always ±” then just show any reputable publication where an RMS is shown so. Now I expect, like LdB, you’ll come back with stuff like a±σ, where σ is some RMS or standard deviation. But while that does express the error range, the measure σ, RMS, is a positive number. The expression wouldn’t make sense otherwise.
Now as I said elsewhere, I’m not so bothered that this is yet another of your “Pat Frank only” notions. The issue is that you savagely condemned James Annan for his standard usage (exactly as used by L&H), which can only show that you just don’t understand it. And it is high school stuff..
Nick, that link shows why taking a square root always produces a plus/minus.
It proves the generality of which rmse is a particular case.
Nick. You are just saying that a standard deviation, as in the parameter, is typically expressed without +/-. So I can pass a paramete value into a function that describes a distribution and that parameter is the standard deviation and it is typically not passed as negative.
The +/- comes into play when a point estimate is made.
In Pat’s 4 +/- case, point estimates are made and there is no reason to suggest that only one tail is required, so +/- is correct.
“so +/- is correct”
So do you mark your students wrong if they don’t provide it?
This is about precision in language as much as it is about precision in measurement. A lot of meta reviews and meta evaluation happening rather than the math, stats, and error analysis that should be happening. We’ve all established that context determines the convention here. Knowledge and awareness of the context (among other things) is cuing fitness to evaluate the submission and the appropriateness of the conduct of the editors and reviewers. So under some circumstances I’d say Pat Frank’s point on +/- was ruthlessly pedantic, but in this case i think he’s within bounds. Picking on his point was a waste of time.
Qualifier: I am not a mathematician nor a statistician. So take what I say with a grain of salt:
Find a Journal who specializes in the nuances of mathematics, statistics and physics, one that is dedicated to tearing apart models and looking for holes. You’ll reach a broader audience. The problem may stem from nihilism, the problem may stem from an abject rejection of any idea that threatens the money train. But your problem is trying to beat down a fortified castle wall with the equivalent of a soap bubble.
Find another castle who’s door is open…preferably a neighboring one that has tunnels running under the climate one–undermining from within. Once an error is discovered, it can not be ignored by those that understand the error.
Just a suggestion, but I’d start shopping that paper to other parties of interest.
Debating the physics and statistical content of the paper is actually a distraction in this posting as it is about integrity, as noted in the title of the post. It would seem that violating the reviewer’s own stated rules regarding maintenance of said integrity should be sufficient to make that point to all that bias is involved in the process and it lacks integrity.
Integrity only counts if we’re talking skeptics. Believers can’t have conflict of interest because they are “pure and saintly”. Funding bias is only on skeptics, as is bad motivations (oil company checks and so forth). Again, all believers are pure and saintly, untainted by personal gain. Everyone knows this. Trying to impune these people is just very bad behaviour. And it hurts their teeny, tiny little feelings, so cut it out.
I don’t pretend to understand the details of the error propagation at the centre of this dispute, but on the one hand it is seen as incompetence and lack of integrity and on the other side it is said to be an obvious error.
What surprises me is that even on its second exposure on this site the technical dispute has still not been resolved though there are plenty of critical comments on both sides. But then, why am I surprised? It seems that climate matters defy agreement as a universal rule.
Yet as others have pointed out, regardless of the technical matter, GMD seems not to have followed its own guidelines and illustrates the level of integrity we associate with pal review.
Outstanding essay. Every media outlet that aspires to maintain the highest ethical standards should publicize the essay as a case study of unethical behavior or worse. Dr. Frank: In my opinion, you could skip the “in my opinion” phrases.
“every media outlet that aspires to maintain the highest ethical standards”
I believe there may be no such thing out there.
Every non-governmental media outlet strives to maintain profits so that it can pay salaries and other operating costs with a residual profit to the owners. Any that doesn’t, doesn’t remain around very long.
If they call themselves a non-profit, private media outlet, then they are merely using a convenient accounting method for the purpose of tax-avoidance by the owners.
Every government media outlet merely serves the political interests of the government in power. Any government media outlet that doesn’t do so, doesn’t remain around very long.
I didn’t want to be sued for defamation, Tom B. Or to put Anthony into such peril.
So called climate scientists refuse to deal with the real world uncertainties and errors that happen in measuring real world things like temperature. They are all mathematicians that are terribly sure that their number crunching and statistical analyses are done correctly and they probably are. However, they are ignoring, mostly willfully, the most important part of the science, error and uncertainty.
Their mistake is that they are not dealing with pure numbers and they refuse to admit that any given number can be fuzzy out to the limits of uncertainty {recorded temperatures) thereby contaminating their well designed output of a simple number. They never dealt with that when learning about how to do math on regular finite numbers that were exact.
Every time they show a graph or state a number without including error and uncertainty they are misleading people into thinking they seeing exactly what will happen. Nothing could be further from the truth. Someday, people will ask them how they could ignore this. I hope they have a good answer.
The name of the modeling company is of course how a modeler’s model has to see the planet for it to have any physical validity. Which of course to say, that if Earth didn’t actually have a condensing 1%-3% precipitable GHG component, the models would do a much better job of estimating the forcing effects on climate of non-precipitable GHG changes.
A true blue sky planet with a small ocean:land ratio – the Earth is not. The Earth of course has a 7:3 ocean:land ratio. Those large oceans have decadal-scale internal non-linear cycles which the models cannot replicate. The planet has significant clouds, cloudy days, and rain which alters albedo over large areas in ways the models cannot caluculate. Water’s phase changes and large latent heats produce significant convective energy transport (at scales smaller than the calculable grid box) in ways which cannot be calculated by first principles. Thus the modelers parameterize those quite non-blue sky features.
So yes, a true blue sky planet is the climate modeler’s Platonic utopia. Damn those clouds and rain.
Even a water world will have a deterministic climate which is actually easier to calculate than our mix of land and water. The problem is that climate science sees the chaos of weather which blinds them to how predictable the LTE state must be consequential to some change.
It would be interesting to see a water world modelled using a pedantic GCM. Many of its knobs and dials will go away, leaving only the core assumptions to affect the results.
A decent modeler will exactly do that: simulate not just current Earth, but Earth in a lot of states: snowball, no land, land in a single mass, all land,…
Yes. One of the tests I do for any model of a causal system is to vary initial conditions and make sure it converges to the same answer each time. If it doesn’t, then there’s something wrong with the model.
‘Consensus Climatology in a Nuccitellishell’
As far as I can see, the problem with all of AGW is the suppositions are built into the models. It’s a giant circular argument. However, to prove or disprove the theory would require starting over with scientists who knew nothing of the theory and were asked to account for the current temperature rise based on the elements of climate we currently understand. This is probably impossible. Almost all theories I’ve seen either assume CO2 is the driver or one of the major drivers, assume one variable is dominent such as the sun, ocean currents, etc, and all have to guestimate many of the components of climate. Finding scientists that could take known factors and generate a model of today’s climate with no assumed conclusions may not be possible. Barring such an exercise, we will remain mired in the “my theory is right” battle forever or until such time as the earth gets very hot or very cold. Even then, the blame game will continue.
Yes! It is a giant circular argument. Still, the models could be scientifically useful if the modeling was done with the assumption that the result will be wrong, and then compared to what has really happened in an attempt to gain understanding. That would be in line with the scientific method. It would be a form a trial and error. But it would fail miserably as political motivation, which needs more definitive, alarming statements to persuade the masses.
The atmospheric scientific community was left with a choice: stick to science and settle for very little funding, or move away from science, giving the funders what they wanted, and vastly increase funding. Over time, they abandoned science for scientific funding. This is exactly what Eisenhower warned us about in 1961, when he said: ““Partly because of the huge costs involved, a government contract becomes virtually a substitute for intellectual curiosity. We must also be alert to the equal and opposite danger that public policy could itself become the captive of a scientific-technological elite.”
Both of these predictions have come to pass with an accuracy that climate models can only dream of. Government contracts have replaced intellectual curiosity as the main driver of the scientific community. And government policy is being driven by self-anointed, scientific elites, as the distinction between science and government fades, to the detriment of both.
The regrettable reality of the bias and ignorance issues highlighted by Dr. Frank’s essay is that the wall of censorship created by Geoscientific Model Development on a small scale and by apparatchiks in massive government bureaucracies on a very large scale, so far, has been impenetrable.
Consider the U.S. Global Change Research Program (USGCRP). USGCRP “was established by Presidential Initiative in 1989 and mandated by Congress in the Global Change Research Act (GCRA) of 1990 to “assist the Nation and the world to understand, assess, predict, and respond to human-induced and natural processes of global change.” Thirteen Federal entities participate in the USGCRP programs
(Department of Commerce, Department of Agriculture, Department of Defense, Department of Energy, Department of Health & Human Services, Department of the Interior, Department of State, Department of Transportation, Environmental Protection Agency, National Aeronautics & Space Administration, National Science Foundation, Smithsonian Institution, U.S. Agency for International Development).
In the 1990 mandate, human-induced climate change is a given. That implies to me that from at least 1990 to the present, billions of dollars have been spent to indoctrinate the world on the untested hypothesis of CO2-driven global warming and not a cent has been spent to challenge orthodox thinking. Unorthodox thinking is prohibited by the mandate. Every result from their studies is a “What if” result. Where are the “What if not” studies?
What chance do a few rational scientists have against this vast Establishment juggernaut of money and power? The resources are in place to accomplish good science. The mandate of the USGCRP must be redirected by Congress to emphasis finding the truth instead of managing a multi-billion-dollar program to promote a political doctrine. That would really be draining the swamp. I wish I could be optimistic that the efforts of Dr. Frank and a few others will lead to positive changes in thinking about climate change. Sadly, I fear that those who desire change are whistling in the wind.
Looked up Annan & Hargreaves on Facebook (gasp). A married couple. She seems to be fond of cats and lists herself as self employed.
Imagine… A married couple thwarting publication of a paper that threatens their livelihood. Simply inconceivable.
I used to review potential contractors for construction projects. Companies that swept the floors on a project would claim to be project managers in their slick sheet brochures. You have to look at financial statements and tangential things, not just the company resumes. Is Blue Sky a slick sheet website trying to get on the AGW cash bandwagon? I doubt they carry enough weight to justify all this discussion.
The most recent product of the U.S. Global Change Research Program is a Congress mandated quadrennial report that is archetypal of how the Establishment perpetuates group think on climate change. The report is filled with hyperbolic language intended to invoke apprehension about present and future threats of an out of control warming planet. The report has been widely publicized in scientific journals and elsewhere, including WUWT (https://wattsupwiththat.com/2017/11/03/what-you-wont-find-in-the-new-national-climate-assessment/) Check it out again re Dr. Frank’s experience with Geoscientific Model Development.
There is no consensus on the AGW conjecture because scientists never registered and voted on the matter. Science is not a democracy. The laws of science are not some form of legislation. Scientific theories are not validated by a voting process. Much of the so called peer review is largely political in nature. Passing peer review does not make something correct or valid.
https://youtu.be/rmTuPumcYkI?t=7m23s
This is an example of someone who is sloppy in his attention to detail in significant figures in measurements. He is demonstrating what is wrong with the alarmist position.
where is “Dr. Annan’s positive sign” ? I don’t see one, this is a false charge made up to suit then rant.
Apparently for Pat Frank ~ = +
If that is where this vitriolic attack on Annan starts, I won’t bother my time with the rest.
I recall last time this “paper” came up it got fairly dismal reception here on WUWT, too.
When there is no sign it is a plus, by definition. I can understand why you had to stop, you simply don’t understand basic mathematical symbolism and were incapable of understanding the rest. This is probably the weakest of his arguments (and even that was too much for you), all things considered.
Unspecified sign is always positive by default, Greg.
Further, later in his paragraph, Dr. Annan wrote, “Of course this is what underpins the use of anomalies for estimating change…,” which treats the value as an offset error and is an unambiguous indicator that he meant positive-sign 4 W/m^2.
Nothing in my post constituted a “vitriolic attack.”
https://youtu.be/rmTuPumcYkI?t=10m17s
https://youtu.be/rmTuPumcYkI?t=13m36s