Re: [asa] The Mathematics of Global Warming

From: William Hamilton <willeugenehamilton@gmail.com>
Date: Sat Dec 12 2009 - 16:42:04 EST

On Fri, Dec 11, 2009 at 1:43 PM, John Burgeson (ASA member) <
hossradbourne@gmail.com> wrote:

> William makes a compelling argument here why the climate models may be
> incorrect.
>
> Let's use Dick Cheny's "1% rule," which he used to justify the Iraq
> invasion. This rule states that if there is even a very small chance
> of a catastropic event then one is justified in taking measures
> against it. In the Iraq case, Cheney was speaking of thepossibility of
> WMDs.
>
> The obvious application to you and to me is the seatbelt rule. The
> chances of me being in a catastropic accident are very very small
> (I've driven and been driven for over 70 years and it hasn't happened
> yet). Yey I put on my seat belt and happily pay the extra $$ for an
> airbag in my vehicular contrivance -- because of the 1% rule. It is a
> good rule.
>
> So -- apply this to the IPCC reports. They run multiple models and all
> say we are in serious trouble. Maybe they are all wrong. Maybe the
> science is not as robust as some people think. Let's take the most
> optimistic view of all this we can. Is there even a 1% chance the IPCC
> is right and the denialists are wrong? Even a 0.1% chance?
>
> It seems to me -- in this case -- we ought to be taking all measures
> to prevent a global catastrophe. Even if it costs us something. Even
> if it costs us a lot.
>

However, this rule can work the other way as well: If there is a 1% chance
that people will die because of extraordinary measures we take to limit
greenhouse gases, then we ha better be *very* sure we know what we are
doing, and the need for it, before we proceed.

>
>
>
> On 11/30/09, William Hamilton <willeugenehamilton@gmail.com> wrote:
> > Hi John
> >
> > I'm not a mathematician, but I spent 33 years developing computer models
> of
> > various systems. Most of the systems I modeled were pretty well-behaved,
> but
> > in the mid 70's I developed a radar bomb-scoring system (RBS) for the
> Navy.
> > The Navy uses huge quantities of ordnance in training. Not only is this
> > costly it leaves tons of unexploded ordnance around that eventually has
> to
> > be cleaned up. And the noise annoys civilians, making it necessary to do
> > training in remote locations. They wanted me to write a program that
> would
> > track an aircraft making a practice bomb run and simulate the bomb
> > ballistics to determine whare the bomb would land. In addition to being
> able
> > to detect the moment when the bomb was released, we had to determine or
> > estimate the bomb's initial velocity with respect to the aircraft and
> > correctly model the bomb's aerodynamics, which were highly nonlinear.
> There
> > was an additional complication: some bombs, known as cluster bombs,
> > consisted of a shell containing a number of smaller "bomblets". At a
> > specified altitude the shell would open and the bomblets would be
> released.
> > Of course the bomblets had completely different aerodynamics from the
> shell,
> > so the solution had to be stopped an restarted with new initial
> conditions.
> >
> > We tested the RBS system by having aircraft drop real practice bombs
> (bombs
> > without explosives but with the correct mass and aerodynamics) and
> comparing
> > the real impact point with the predicted. As I remember the results were
> > close enough to be usable, but had the bombing been from any higher
> altitude
> > or had the aircraft been taking evasive action they wouldn't have been.
> > Variations in barometric pressure and humidity affected the results too.
> >
> > But trying to predict climate years in advance is a great deal more
> > difficult than trying to predict a bomb trajectory from an aircraft
> flying a
> > few hundred to a few thousand feet above the deck.
> >
> > I've spent some time looking at computer models of climate. Most of them
> are
> > too complicated to be easily analyzed. Even a retiree has limited time
> :-).
> > And most of them are too big to be run on the equipment available to me:
> a
> > macbook pro. But the complexity of the models argues for careful
> assessment
> > by people not having a vested interest in the accuracy of the models. I
> > don't know whether this has been done.
> >
> > However there is one paper by Tobias and Weiss: Resonant Interactions
> > between Solar Activity and Climate that you can get at
> >
> http://ams.allenpress.com/perlserv/?request=get-document&doi=10.1175%2F1520-0442%282000%29013%3C3745%3ARIBSAA%3E2.0.CO%3B2
> > that uses the Lorenz equations to model the earth's climate. They find a
> > stochastic resonance phenomenon that can result in warming of the earth's
> > climate with very small variation in solar activity. Now one might
> rightly
> > question the simplification of using the Lorenz Differential equations to
> > model the earth's climate, but still the model points out a possible
> > connection between solar activity and earth's climate. I made a fairly
> > extensive study of the CCSM climate model, one of the models commonly
> used
> > by the GW community, and solar input is just a constant, so that model
> > doesn't model solar variation at all. The GISS model is somewhat more
> > difficult to analyze, and I haven't yet determined how or whether they
> model
> > solar variation.
> >
> > Another approach to studying climate dynamics is that used by Scafetta.
> His
> > web site is http://www.fel.duke.edu/~scafetta/<http://www.fel.duke.edu/%7Escafetta/>on which he has reprinted
> > many of his papers. In addition there is a video of a talk he gave at the
> > EPA back in February that is worth watching. Among other things Scafetta
> has
> > done extensive analysis of the statistics of climate data and solar
> output
> > and found "echoes" of the solar input in the climate data, leading him to
> > conclude that solar variation is exciting global warming. (I'm not doing
> > justice to Scafett' research, which is extensive)
> >
> > So, while I admit the possibility that the various climate models used by
> > IPCC could be correct, I am very leery of basing policy decision on them
> > until more analysis of the models and their input data and results is
> done
> > by an impartial party.
> >
> >
> > On Mon, Nov 30, 2009 at 6:34 AM, John Walley <john_walley@yahoo.com>
> wrote:
> >
> >> I found this to be very interesting. I wonder if any of the
> mathematicians
> >> on the list have any comment?
> >>
> >> John
> >>
> >> November 30, 2009
> >> The Mathematics of Global Warming
> >> By Peter Landesman
> >>
> http://www.americanthinker.com/2009/11/the_mathematics_of_global_warm.html
> >>
> >> The forecasts of global warming are based on the mathematical solutions
> of
> >> equations in models of the weather. But all of these solutions are
> >> inaccurate. Therefore no valid scientific conclusions can be made
> >> concerning
> >> global warming. The false claim for the effectiveness of mathematics is
> an
> >> unreported scandal at least as important as the recent climate data
> fraud.
> >> Why is the math important? And why don't the climatologists use it
> >> correctly?
> >>
> >> Mathematics has a fundamental role in the development of all physical
> >> sciences. First the researchers strive to understand the laws of nature
> >> determining the behavior of what they are studying. Then they build a
> >> model
> >> and express these laws in the mathematics of differential and difference
> >> equations. Next the mathematicians analyze the solutions to these
> >> equations
> >> to improve the understanding of the scientist. Often the mathematicians
> >> can
> >> describe the evolution through time of the scientist's model.
> >>
> >> The most famous successful use of mathematics in this way was Isaac
> >> Newton's demonstration that the planets travel in elliptical paths
> around
> >> the sun. He formulated the law of gravity (that the rate of change of
> the
> >> velocity between two masses is inversely proportional to the square of
> the
> >> distance between them) and then developed the mathematics of
> differential
> >> calculus to demonstrate his result.
> >>
> >> Every college physics student studies many of the simple models and
> their
> >> successful solutions that have been found over the 300 years after
> Newton.
> >> Engineers constantly use models and mathematics to gain insight into the
> >> physics of their field.
> >>
> >> However, for many situations of interest, the mathematics may become too
> >> difficult. The mathematicians are unable to answer the scientist's
> >> important
> >> questions because a complete understanding of the differential equations
> >> is
> >> beyond human knowledge. A famous longstanding such unsolved problem is
> >> the
> >> n-body problem: if more than two planets are revolving around one
> >> another,
> >> according to the law of gravity, will the planets ram each other or will
> >> they drift out to infinity?
> >>
> >> Fortunately, in the last fifty years computers have been able to help
> >> mathematicians solve complex models over short time periods. Numerical
> >> analystshave developed techniques to graph solutions to differential
> >> equations and thus to yield new information about the model under
> >> consideration. All college calculus students use calculators to find
> >> solutions to simple differential equations called integrals.
> Space-travel
> >> is possible because computers can solve the n-body problem for short
> times
> >> and small n. The design of the stealth jet fighter could not have been
> >> accomplished without the computing speed of parallel processors. These
> >> successes have unrealistically raised the expectations for the
> application
> >> of mathematics to scientific problems.
> >>
> >> Unfortunately, even assuming the model of the physics is correct,
> >> computers
> >> and mathematicians cannot solve more difficult problems such as the
> >> weather
> >> equations for several reasons. First, the solution may require more
> >> computations than computers can make. Faster and faster computers push
> >> back
> >> the speed barrier every year. Second, it may be too difficult to
> collect
> >> enough data to accurately determine the initial conditions of the model.
> >> Third, the equations of the model may be non-linear. This means that no
> >> simplification of the equations can accurately predict the properties of
> >> the
> >> solutions of the differential equations. The solutions are often
> unstable.
> >> That is a small variation in initial conditions lead to large variations
> >> some time later. This property makes it impossible to compute solutions
> >> over
> >> long time periods.
> >>
> >> As an expertin the solutions of non-linear differential equations, I can
> >> attest to the fact that the more than two-dozen non-linear differential
> >> equations in the models of the weather are too difficult for humans to
> >> have
> >> any idea how to solve accurately. No approximation over long time
> periods
> >> has any chance of accurately predicting global warming. Yet
> approximation
> >> is exactly what the global warming advocates are doing. Each of the
> more
> >> than 30 modelsbeing used around the world to predict the weather is just
> a
> >> different inaccurate approximation of the weather equations. (Of course
> >> this is only an issue if the model of the weather is correct. It is
> >> probably
> >> not because the climatologists probably do not understand all of the
> >> physical processes determining the weather.)
> >>
> >> Therefore, logically one cannot conclude that any of the predictions are
> >> correct. To base economic policy on the wishful thinking of these
> >> so-called
> >> scientists is just foolhardy from a mathematical point of view. The
> >> leaders
> >> of the mathematical community, ensconced in universities flush with
> global
> >> warming dollars, have not adequately explained to the public the above
> >> facts.
> >>
> >> President Obama should appoint a Mathematics Czar to consult before he
> >> goes
> >> to Copenhagen.
> >>
> >> Peter Landesman mathmaze@yahoo.comis the author of the 3D-maze
> >> bookSpacemazes for children to have fun while learning mathematics.
> >>
> >>
> >>
> >>
> >>
> >> To unsubscribe, send a message to majordomo@calvin.edu with
> >> "unsubscribe asa" (no quotes) as the body of the message.
> >>
> >
> >
> >
> > --
> > William E (Bill) Hamilton Jr., Ph.D.
> > Member American Scientific Affiliation
> > Austin, TX
> > 248 821 8156
> >
>
>
> --
> Burgy
>
> www.burgy.50megs.com
>

-- 
William E (Bill) Hamilton Jr., Ph.D.
Member American Scientific Affiliation
Austin, TX
248 821 8156
To unsubscribe, send a message to majordomo@calvin.edu with
"unsubscribe asa" (no quotes) as the body of the message.
Received on Sat Dec 12 16:42:26 2009

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