Rats! You uncovered me. I'm actually paid $250,000/year to be a shill
for the Koch brothers and Exxon-Mobil. Well, at least that's what many
folks would like to believe about folks like me who can't see that we
should simply accept the judgment of 97% of all climate scientists, etc.
I suppose I was long ago conditioned to be leery of modelers since I
myself was heavily involved in a simulation model of one of IBM's
smallest manufacturing plants in the early 70s. The intent was to try
to predict the actual output of the plant. In a nutshell, the model
kept growing more and more complex. It finally met its end when the
complexity of the model caused the runtime to exceed real time. The
net: You would need more than a month to predict the month's output.
Unfortunately, even today's far faster computers wouldn't have helped
because the answer would still be very wrong anyhow.
If you're serious about understanding the modeling problem of chaotic
systems (rather than assuming I really am a stupid shill) you can find a
synopsis and discussion here:
<http://climateaudit.org/2006/05/15/gerry-browning-numerical-climate-models/>
There are a few snide comments in the discussion but most of it is
serious discussion of the complexity (and feasibility) of the work.
Bear in mind as you read this that the vast majority of "climate
scientists" have absolutely nothing to do with climate modeling. Yet it
is climate models which are the only predictors of damaging temperature
rise 50 or 100 years from now.
Here's part of a comment from a financial modeler
-------------------------------------------------------------------
Moreover, because of the very natural feedback of our industry, we
cannot “game” our models. For example, I cannot create a model that
looks great in testing but loses money in actual use; the finance
literature is full of such models, but using them will cause one to go
bankrupt. In the same fashion, I cannot examine behavior in individual
financial markets and then “tweak” various differential equations and
statistical parameters so that the model forecasts better match that
market’s returns – such gamed models also fail miserably when used in
reality.
Now I will tie this in more directly with climate research. The measure
of skill quoted by Pielke from Annan’s website:
“Forecast skill is generally defined as the performance of particular
forecast system in comparison to some other reference technique.”
is exactly the definition I would expect from someone who does not have
to be right more often than wrong. In fact, unlike what I do in the
applied finance world, there has been little feedback whatsoever on
whether or not climate model forecasts created to date have been correct
thus far. Instead, the feedback seems to be how well one can fit a GCM
to an observed data set in a publication (such data include historical
near-surface temps, satellite observations, etc.) to see if it indeed
matches historical data. Even though such GCM forecasts are integrated
over time, the continual process of re-running and re-running them until
better matches are created is a form of in-sample maximization that
provides no information on what the model’s realized forecast efficacy
will be (even the in-sample matches are currently poor, as has been
noted above).
------------------------------------------------------------------
When you look under the covers you may find disturbing things.
Chuck Norcutt
On 2/22/2013 1:18 AM, Andrew Fildes wrote:
> You were doing fine until you said that - and went just a little
> touch conspiracy theorist. In fact, I suspect that anyone who came up
> with a really, really good argument against 'warming' would do very
> well indeed. S/he would be grabbed, encouraged and funded by a
> significant number of industry conservatives, related political
> factions and plain conspiracy nutters.
>
>
> Andrew Fildes afildes@xxxxxxxxxxxxx www.soultheft.com
> Author/Publisher: The SLR Compendium -
> http://www.blurb.com/books/3732813
>
>
>
> On 22/02/2013, at 12:15 PM, Chuck Norcutt wrote:
>
>> I believe the task cannot be accomplished due to the chaotic nature
>> of climate and the (still poor) understanding of what drives it.
>> Of course, the modelers would never say that as they wouldn't have
>> a job.
>
--
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