Two worlds collide

GWPF have release a very interesting report about stochastic modelling by Terence Mills, professor of applied statistics and econometrics at Loughborough University. This is a bit of a new venture for Benny and the team because it's written with a technical audience in mind and there is lots of maths to wade through. But even from the introduction, you can see that Mills is making a very interesting point:

The analysis and interpretation of temperature data is clearly of central importance to debates about anthropogenic globalwarming (AGW). Climatologists currently rely on large-scale general circulation models to project temperature trends over the coming years and decades. Economists used to rely on large-scale macroeconomic models for forecasting, but in the 1970s an increasing divergence between models and reality led practitioners to move away from such macro modelling in favour of relatively simple statistical time-series forecasting tools, which were proving to be more accurate.

In a possible parallel, recent years have seen growing interest in the application of statistical and econometric methods to climatology. This report provides an explanation of the fundamental building blocks of so-called ‘ARIMA’ models, which are widely used for forecasting economic and financial time series. It then shows how they, and various extensions, can be applied to climatological data. An emphasis throughout is that many different forms of a model might be fitted to the same data set, with each one implying different forecasts or uncertainty levels, so readers should understand the intuition behind the modelling methods. Model selection by the researcher needs to be based on objective grounds.

There is an article (£) in the Times about the paper.

I think it's fair to say that the climatological community is not going to take kindly to these ideas. Even the normally mild-mannered Richard Betts seems to have got a bit hot under the collar.

Are @thetimes so desperate for subscribers that they're reduced to covering daft GWPF reports for trashy clickbait? https://t.co/u8VqcNOOJc

— Richard Betts (@richardabetts) February 23, 2016

Comments

[thinkingscientist]

Oh dear Phil, what possible physical meaning has the "multi-model mean" of your "ensembles of model solutions?", as shown in that picture? How come they all seem to be summarised as what looks like stochastic noise around a pseudo-linear trend?

Funny the satellite and balloon data are not on that graph, eh? Just lots of inter-dependent surface temperature measurements.

Please refer back to random walk. And assumptions about stationarity.

[rhoda]

Don't I recall that it is the Canadian model which ALWAYS reads high? Why not chuck it out and improve the ensemble?

And yes, what possible relevance does an ensemble have in this kind of work?

[...and Then There's Physics]

But even from the introduction, you can see that Mills is making a very interesting point:

The only thing interesting about the report is that a Professor of Statistic could have written it. It is garbage. I'm not surprised you're promoting it, but it has absolutely no physics whatsoever. What he was doing can tell us absolutely nothing about the future.

I think it's fair to say that the climatological community is not going to take kindly to these ideas.

Quite rightly. It's trash. Mills should be embarassed to have written such complete and utter nonsense.

[Green Sand]

rhoda

'Why not chuck it out and improve the ensemble?'

Politics? What would be the Canadian, or any other government's attitude to funding if the model it had paid for was deemed an outlier and excluded as detrimental to the cause?

[John Shade]

Statistics is a wonderful, although often hard, subject. It helps us devise testable theories, and helps us test testable theories in efficient ways.

Sometimes, the statistical thinking concentrates on understanding systems (for example by designing highly informative experiments to explore the influences of multiple factors).

Sometimes the thinking concentrates on prediction (for example by analysing time-series of some measure to expose regularities that can improve forecasting skill).

The highly-gifted statistician Galit Shmueli has written a masterful overview of these two angles to scientific research, noting that they are often conflated:

Statistical modeling is a powerful tool for developing and testing theories by way of causal explanation, prediction, and description. In many disciplines there is near-exclusive use of statistical modeling for causal explanation and the assumption that models with high explanatory power are inherently of high predictive power. Conflation between explanation and prediction is common, yet the distinction must be understood for progressing scientific knowledge. While this distinction has been recognized in the philosophy of science, the statistical literature lacks a thorough discussion of the many differences that arise in the process of modeling for an explanatory versus a predictive goal. The purpose of this article is to clarify the distinction between explanatory and predictive modeling, to discuss its sources, and to reveal the practical implications of the distinction to each step in the modeling process.

Get her 2010 paper here: http://arxiv.org/pdf/1101.0891.pdf

[Phillip Bratby]

ATTP "it has absolutely no physics whatsoever". Perhaps that's what you expect from a statistician. And all the climate scientists and modellers at the Met Office don't do physics either. The whole AGW is a scam based on false physics.

[Jeremy Poynton]

Not sure what all the fuss is about anyway. The planet has been cooling for c5000 years, so a small warming blip should surely be welcomed rather than chicken-lickened?

[Stephen Richards]

"The one in which the GWPF hilariously "forecasts" last year's temperatures to be lower than what they actually were.."

As opposed to all those Comedy Consensus Central forecasts made by our dear old Met Office, Richard, EH,

On which betts gets to forecast their impacts 100yrs ahead so that we can spend £trillions ameliorating his useless impact forecasts.

Still he gets paid a hansom salary and a great pension all paid for by the ever suffering plebs of the UK.

Have you ever considered how many parasites can suck on one poor production worker? You know, the workers who actually save the planet and keep his fellow plebs alive? Start with climate scientists, ending with Junker et al. MILLIONS

[hunter]

By Gavin's standard of dismissing predictions for one year errors we can now add him to the list of skeptics dismissing the consensus predictions for being wrong for over a decade. Welcome aboard, Gavin!

[Harry Passfield]

Stephen Richards: Perhaps Shakespeare, brought up to date, would have got Hamlet to lay off the lawyers and set to with the scientists at the Met.

[Mark Hodgson]

Oh dear, ATTP's back; how tiresome - and on work time too, as usual.

[Richard Betts]

Looking through the GWPF report's references, I see Terence Mills cites (favourably) his own paper from 2009 entitled How robust is the long-run relationship between temperature and radiative forcing?

However, strangely he does not mention that his report (with its zero climate sensitivity) flatly contradicts his earlier conclusions - his 2009 abstract says:

This paper examines the robustness of the long-run, cointegrating, relationship between global temperatures and radiative forcing. It is found that the temperature sensitivity to a doubling of radiative forcing is of the order of 2 ± 1°C. This result is robust across the sample period of 1850 to 2000, thus providing further confirmation of the quantitative impact of radiative forcing and, in particular, CO2 forcing, on temperatures.

Like Nic Lewis's estimates, these earlier estimates by Mills overlap the low side of the IPCC range, and are very different from zero.

I wonder if this means that Mills now rejects his earlier work, despite still citing it?

[Harry Passfield]

Ken Rice:

Quite rightly. It's trash. Mills should be embarassed to have written such complete and utter nonsense.

Terence Mills is Professor of Applied Statistics at Loughborough University, and you, Ken Rice, what are you, [snip - venting] ]And you can't spell embarrassed.

[Simon Hopkinson]

Whoa! When did the warmies suddenly switch from defending failed predictions to attacking them? This is a significant change of direction.

[...and Then There's Physics]

Richard,
Bizarre, so he wasn't unaware of the basic physics and yet still authored this report.

Harry,

Terence Mills is Professor of Applied Statistics at Loughborough University

Exactly, he should know better.

and you, Ken Rice, what are you, who the f*ck are you

Since you appear to know my name, you can look me up.

We laymen are quite capable of that but, within academe, you show that you're all a load of shits anyway.

Not everyone in academia is.

And you can't spell embarrassed.

Thanks, my bad.

[JamesG]

Well I don't have much time for econometrics methods since the entire profession signally failed to predict the 2008 crash that was obvious to us contrarians. However I'd be more interested to know the temperature predictions from Gavin, Richard et al for 2016/17. I'm guessing their empty bluster that the temperature will stay high because it doesn't depend on the el nino will be as accurate as the busted forecasts for the 2006 and 2007 hurricane seasons or the arctic death spiral predictions or..........well pick anything! The absolutely last thing these climateers can do is gloat because their predictions are demonstrably worse than random monkeys.

I predict that the coming la nina will be every bit as large as the one following the 1998 el nino. I also predict that coral die back will be less than in 1998, demonstrating (for those that somehow can't work out the obvious) that satellite data is more reliable than extrapolations from a smattering of ship bucket measurements.

[Harry Passfield]

Since you appear to know my name, you can look me up

I wouldn't waste the keystrokes. Terence Mills put his name and his position behind his findings. You hide behind an alias - and get off on blogers 'knowing' who you are. Well, we know.

[ATheoK]

Ah, yes.

The climate team members are out in force and splashing mightily. All of their splashing illustrates that they have a real problem splashing at any real depth. It's all showy splashing without actually moving any water.

"...increasing divergence between models and reality led practitioners to move away from such macro modeling..."

Why do they react so to other professionals recognizing their errors and moving to actual working models?

The climate models are busted. No matter how much the gavinator smudges up the temps, he can not get actual temperatures to the climatic guesstimates. Yet he and his bully prats are out in force trying to quash all rational questions.

Like; "When will the climateers dump their broke models and start using models that work?"

We've discussed real world models before. All engineers and most scientists are well aware that in the private world, badly programmed models means the programmer finds new work. Period!

There is not a lot of patience in the real world for broken models that do not work, never worked and as long as CO2 rules the program, will never work.
With years of non-functional models from a team, walking in and telling the boss you need a 'newer' computer would have gotten us kicked down the stairs.
Let alone asking for bigger better computers; "Prove your logic, on what you can afford", would've been the response.

Almost two decades into terrible climate models, a joke of a BOM and METO offices combined with plummeting NOAA credibility and here are the climate team members behaving badly when a paper is produced with helpful analysis and suggestions... Nuff said.

[John Smith-Smith, Ministry of Silly Science]

It has long been my understanding that the "climate models" contain stochastic elements. Is this incorrect? Please enlighten me.

[Spence_UK]

When I saw the title of the paper (and being published by the GWPF) I was quite excited - the contrast between stochastic modelling and deterministic modelling of climate is a critical one and something that is underexplored.

Reading the paper was a bit of a disappointment to be honest. Although it touches on the key issues surrounding stochastic modelling (as you would expect from a good statistician, as the text shows Prof. Mills to be), ultimately I do think the text is too divorced from physics - albeit for very different reasons to that given by Rice and co.

Physics has stochastic modelling absolutely at its heart. In many fields, such as quantum mechanics or thermodynamics, the fundamental relationships governing physics can only be described by stochastic models, and the deterministic models are entirely consequences of the underlying statistical behaviour of these systems. But the statistical models that underpin these models must be of the correct form. In this sense, neither the building blocks of GCMs nor the ARIMA model used by Prof Mills are good choices to represent natural variability of climate. They are easily shown to be poor choices.

It's a shame, as this is an opportunity missed. My recommendation for climate stochastics is to continue to read Koutsoyiannis' work; less glossy but properly rooted in physics:

From Climate Certainties to Climate Stochastics

... illustrating example failures of GCMs and how climate stochastics flows from physics.

[Pcar]

@Kevin Marshall, Feb 23, 2016 at 12:32 PM

Whether theory-based or time-series, economic forecasting needs some empirical relationships to remain unchanged. They are therefore quite good at forecasting over a few months when an economy is fairly steady, but pretty useless are predicting a large scale downturn such as the credit crunch. That is, the accuracy is inversely related to the utility. At least with the economic forecasting models there is competition to get the most accurate

The "large scale downturn such as the credit crunch" was forecast by many for a few years before it happened, myself included. Liam Haligan at the Telegraph regularly wrote about the looming crash and George Soros also saw it coming. As for me, I predicted it and and stated the Conservatives did not want to win the 2005 UK election as Blair and Brown had created an economy which would collapse in the near future whoever won.

@It doesn't add up..., Feb 23, 2016 at 12:54 PM
Kevin Marshall:

Macro economic forecasting is not about being accurate, but about producing forecasts that are consistent with being politically acceptable (when produced by the IMF, OECD, or Treasury), or are attempts at producing forecasts that turn out to be close to the consensus opinion. Outlier forecasts (e.g. those made by Nouriel Roubini "Dr Doom" in the run up to the financial crisis) are usually largely suppressed and ignored. Large sums are wagered on the basis of the consensus, and the wall of money usually wins. Or, as Keynes allegedly ruefully put it "The market can remain irrational longer than you can remain solvent"

It was obvious to anyone not a blind supporter of consensus views that the USA sub-prime mortgage market was a disaster waiting to happen and all Gov'ts actions were merely delaying the inevitable collapse. What was not expected was the USA Gov't allowing a TBTF bank (Lehmans) to fail. Right or wrong, Bush made a decision to end the rent seeking profits Wall Street was enjoying from Gov't rules and largesse.

The rules in question were initiated by Carter and then gold-plated and hugely enlarged by Clinton supporting Obama's lobbying for more initially subsidised mortgage loans to "the poor". Once the initial subsidy ended, repayments could not be afforded. Thus the crash.

How does this impact on the Global Warming consensus: when all political parties, "leaders" of industry and others in positions of authority form a consensus group think agreement, they have been calamitously wrong on most occasions. Examples: 1930s the pound, peace with Hitler, 1970s EEC, 1980s Global Warming, 1990s ERM, 1990s Euro entry (Brown's war with Blair was all that stopped that), 2000s Iraq, Afghanistan and CCA.

[John Shade]

Well, this sure is interesting. A cat has landed amongst some pigeons. Ruffled feathers, lots of squawking, probably high-pitched calls for help to others not here. We might therefore expect more noise and fury. Let us be sure to study what promises to be an even more informative event as it unfolds.

[Richard Betts]

JamesG

However I'd be more interested to know the temperature predictions from Gavin, Richard et al for 2016/17.

The Met Office global temperature forecast for 2016 is here. It's expected to be at least as warm as last year.

For 2017, check the 5-year global temperature forecast here.

As you suggest yourself, the forecast says:

the recent run of consecutive record years is likely to end in 2017 as El Niño declines.

but also

The forecast is for continued global warming largely driven by continued high levels of greenhouse gases. However, other changes in the climate system, including the largest El Niño since 1997 and longer term shifts in both the Pacific Decadal Oscillation (PDO) and Atlantic Multidecadal Oscillation (AMO), are also contributing. Near record temperatures are predicted for the coming five years

[Martin A]

The only thing interesting about the report is that a Professor of Statistic could have written it. It is garbage(...)
It's trash. Mills should be embarassed to have written such complete and utter nonsense.

Feb 23, 2016 at 4:51 PM | Unregistered Commenter...and Then There's Physics

[I am Professor of Computational Astrophysics at the Institute for Astronomy, an institute within the School of Physics and Astronomy at the University of Edinburgh ]

The professional etiquette of a British university professor in action.

[Salopian]

Martin A:

He's just providing yet more evidence that he's a professional a hole.

[rhoda]

Is not the correct procedure for an academic not to proclaim 'it's trash' but to issue a proposed correction? Isn't there a protocol for this sort of thing which does not, IIRC, involve twitter? I'm sure I've seen a similar argument used against sceptics a few million times. Perhaps I exaggerate. But not much.

Now, why not chuck out that Canadian model?

[Henry Galt]

Here is a refreshingly falsifiable forecast for the UK (based on signals that do allow a more loose global interpretation) He was >90% accurate last year.

https://docs.google.com/document/d/1zn9MUBGHRYJH1x7vt4E9fuYbHLROrMCpePuJcUQE1VI/pub

Of course, in this fast moving present only farmers have the need for such accuracy and the tenacity to revisit and compare the reality with prognostications ;)

[Chris Hanley]

“… the approach of a fully stochastic model without any forcing terms presumes insensitivity to effects from greenhouse gases, etc., which is contrary to our knowledge of the physical systems … “ HaroldW @ 12:52 PM.
======================
But that is the whole point of the exercise viz. to ignore theory because there is no verified theory of climate.
As the author says:
“… relatively simple statistical models
that had no obvious basis in economic theory were proving much more reliable at
forecasting. It took many years for economists to rationalise statistical forecasting by
working out its structural connections to this theory. But before this had happened,
economic practitioners were already relying on these models simply because of their
relative success …
Is there a parallel with climatology? …”.

[ThinkingScientist]

I just love this meme from Betts, Clark, aTTP etc that the climate models are "physics" and everything else should therefore be disparaged. Feynman got the models about right. Yes, they contain physics. General circulation (pretty straightforward) is ok, spectral bands etc. But the "physics" meme is used to give the impression that all the physics is known. It isn't. Some critical elements are terrible. The models work in uncalibrated relative temps, not absolute, so how do they handle phase transition correctly? Models use an unproven positive water feedback, without this the sensitivity to CO2 would be very much lower (close to Nic Lewis sensitivity, perhaps). Clouds. Grid scale. Chaos - have they forgotten Lorenz?

Spence_uk comment re deterministic or stochastic is important too. It is unclear how "physics" can model a chaotic process through deterministic models. Do the models contain stochastic parameters? Unclear, and i have asked this question many times before. How do they handle cumulative error terms and truncations?

Physics? Yeah, of course. All the physics? Definitely not. Do they even know all the relevent physics? Nope. Can they include all the appropriate scales and still compute the output of a chaotic process? Nope, and never likely to either unless quantum computing becomes widespread. And if you are picking "projections" from modelling chaos, how would you know which to pick? Answer - you couldn't. They would be equiprobable. And unknowable. Its called "uncertainty " for a reason.

And just explain the justification for the ensemble mean to us please. Richard? Attp?

[Martin A]

Even a model containing "physics", if it cannot be validated, is no more than an illustration of somebody's hypothesis.

[Mark Hodgson]

Mr Betts

I was surprised to wake up this morning to snow, when the Met Office didn't forecast this for where I live. May I have my money back, please?

[Dave Salt]

ThinkingScientist (Feb 24, 2016 at 7:55 AM), thank you for describing in clear and simple terms the fundamental problems within the models (i.e. the limits of their 'physics').

When so-called experts consistently refuse to discuss these problems in an open forum, or even to admit that they exist, it merely confirms the suspicion that their 'science' is built upon extremely shaky ground.

[John Shade]

How simple is the physics of two point masses affected only by their gravitational attraction. We've cracked that one, but add a third mass and trouble ensues. A struggle to find special cases that continued through the 20th C, and still is problematic. Add a fourth or more, and the physics is of little practical use. Statistical results can be derived, and some mathematical patterns can be discerned in remote asymptopia. Claims that the GCMs are based on physics is of modest assurance when it comes to guidance as to what will happen, and thinkingscientist alludes to some reasons why a few comments up. But oh my, such claims are handy for claiming some kind of high priestess (Julia longing to be in white robes, surrounded by incense smoke?) status when talking to the politicians upon whose beneficence you so depend.

This report from the House of Commons is quite informative, with hints of jostling between rival sects from time to time: http://www.publications.parliament.uk/pa/cm201012/cmselect/cmsctech/1538/153806.htm. {readers following up that link might like to note these thoughts of Richard Lindzen: “In brief, we have the new paradigm where simulation and programs have replaced theory and observation, where government largely determines the nature of scientific activity, and where the primary role of professional societies is the lobbying of the government for special advantage.” [hat-tip Dave L]}.

More allusions to the physics deity here, but some robust comments below calling the Met Office 'statistically inept': http://blog.metoffice.gov.uk/2015/12/07/did-climate-change-have-an-impact-on-storm-desmond/.

I tentatively conclude that while the physics thing is good for PR (the models belonging more to departments of applied maths and computation - the Navier-Stokes approximations in fluid dynamics, the handy wheeze of 'forcing' - the programmer's friend, and a lot of ad hoc parameterisation not to mention adjustments to keep a steady keel), the statistics thing might serve them better for climate prediction, but they have staked (or rather gained) their fortune on GCMs and see no elegant way out of that in the short term. But the Mills paper will I hope see them beefing up their statistical resources so that they can get a bit of that action in due course - just in case the paymasters get to hear about it.

[...and Then There's Physics]

How simple is the physics of two point masses affected only by their gravitational attraction. We've cracked that one, but add a third mass and trouble ensues. A struggle to find special cases that continued through the 20th C, and still is problematic. Add a fourth or more, and the physics is of little practical use.

What? Have you never heard of N-body simulations. We might not be able to solve some of these problems analytically, but that doesn't mean that we can't determine the gravitational evolution of a multi-body system. I'm doing a 5 planet system at this very moment.

[John Shade]

Does 'Statistical results can be derived, and some mathematical patterns can be discerned in remote asymptopia.' not speak to you of n-body simulations? Are you very highly-strung by any chance?

[...and Then There's Physics]

Does 'Statistical results can be derived, and some mathematical patterns can be discerned in remote asymptopia.' not speak to you of n-body simulations?

No.

[John Shade]

The general consensus in the N-body community is that statistical results of an ensemble of collisional N-body simulations are accurate, even though individual simulations are not.

From: Cornell University Library

Don't tell me, P, you're working on an 'individual simulation'.

[...and Then There's Physics]

Don't tell me, P, you're working on an 'individual simulation'.

No, multiple simulations and two different codes. Don't tell me that you think that some mathematical patterns can be discerned in remote asymptopia and [a]dd a fourth or more, and the physics is of little practical use is somehow consistent with your Cornell quote.

[John Shade]

Are you suggesting it is time to move on from the relevance of statistics when doing n-body simulations , P? Now why would you want to do that?

[...and Then There's Physics]

Are you suggesting it is time to move on from the relevance of statistics when doing n-body simulations , P? Now why would you want to do that?

No. Why would you misrepresent what I've said? That's rhetorical, in case that wasn't obvious.

[John Shade]

Well P, I do hope you are at least a little bit grateful that I have drawn your attention to the relevance of statistical methods to simulations of n-bodies. You can't be expected to know everything, and you didn't know that, but somehow I feel your gratitude will not be forthcoming.

[...and Then There's Physics]

You can't be expected to know everything, and you didn't know that, but somehow I feel your gratitude will not be forthcoming.

Mainly because I did know it. Bizarre.

[John Shade]

The announcement of this GWPF paper, and also the Bish's post about it has appeared at WUWT A new climate war brewing

The early comments are mostly trivial, but I did like this one from an 'Andrew patullo' at 1:04pm Watts Time yesterday:

Statistical forecasting is obviously deficient compared to computer modelling. It is unable to incorporate politically correct dogma as to what is supposed to happen, but limits itself to a short-sighted preoccupation with what actually does happen. It fails to capture all the emotion and guilt of human caused climate devastation and, will be of little help to climate modellers when grant time comes around. Left to its own devices this perversion of climate science runs the risk of becoming widely accepted in the science community due to its peculiar ability to actually predict future trends, and, Gaia forbid, might even end up part of the high school science curriculum. Where will society be if our children don’t learn to properly fear their own exhaled breath?

[Mark Hodgson]

Oh dear

ATTP's quite busy on here in work time, isn't he?

[...and Then There's Physics]

Mark,
Are you off school today, or do you have Wi-Fi access in the classroom?

[ATheoK]

"
Oh dear

ATTP's quite busy on here in work time, isn't he?

Feb 24, 2016 at 12:20 PM | Unregistered CommenterMark Hodgson"

There are other times, besides "on the clock", that he shows up here?

"...gravitational evolution of a multi-body system. I'm doing a 5 planet system at this very moment..."

Indeed?
Where are the online details?

What's the starting point?
Galaxy collision?
Supernova debris?
Magnetar destruction of nearby solar systems?

All have some particular starting point? Good for a stochastic input factors that you control?

Just how does the system evolve consistently into a five planet body system? Why didn't it evolve into a single giant planet or into thousands of asteroids?

Self determined, no doubt. Statistics abuse or abused statistics; whatever.

[not banned yet]

"I'm doing a 5 planet system at this very moment."

What does "doing" mean in this context? Waiting for a prewritten code to run? Writing a code? Developing and defining parameters? Developing theory? Other?

I'd like to know more please ATTP - or anybody else with skills and knowledge in this area.

Thanks.

Discussion > N-body simulations

http://www.bishop-hill.net/discussion/post/2577906

[Anonymouse]

Oh dear.

http://julesandjames.blogspot.co.uk/2016/02/no-terence-mills-does-not-believe-his.html

[diogenes]

It is ingteresting to see the line of attack being used by McNeall, Betts and Schmidt because it seems more than slighlty self-defeating. If you can laugh at a statistics-based model for going outside a certain uncertainty envelope then what should we make of the glorious "ensemble" of GCMs all of which are happily off the rails. I sense some kind of panic in the climate priesthood, which is supported by the appearance of the "consensus" enforcing attack chihuahua ATTP.

With his characteristically incisive argumentation style, he gets straight down to it:

"The only thing interesting about the report is that a Professor of Statistic could have written it. It is garbage. I'm not surprised you're promoting it, but it has absolutely no physics whatsoever. What he was doing can tell us absolutely nothing about the future. "

Making convincing arguments is, as we all know, something that is alien to this professor but surely he could do better than that. It is as if he is saying that a model (or "ensemble" of models) that makes worse predictions is better just because it contains this thing called "physics".

Physics helps you breathe more easily. Physics makes it easier for you to be wrong. This religious belief in the power of physics....Quite crazy. It never even occurs to these clowns that they might have got the physics wrong. Perhaps they should go back to measuring things rather than guessing them on the basis of some God called "physics".

[diogenes]

Bugger those blockquotes...that'll learn me!