Wondering what Hume would say of Numerical Models at SVP 2003: Second try

[MariusRomanus@aol.com]

Numerical Modeling at SVP 2003...

In stead of giving you my humble opinion on which models I felt were good and 
which were bad, I'd rather let those of you who attended the talks or read the 
posters relating to the numerical models, to figure it out for yourselves by 
implementing simple, generalized, *criteria-type* parameters that are utilized 
during the sound implementation of any numerical model, regardless of its 
purpose. I tend to think that a point will come across much better this way, as 
opposed to me rambling on about my specific likes and dislikes pertaining to 
the certain endeavors of the modelers...

Key Reads... These are the KNOWN fundamental parameters that you apply in order 
to test your model. Example: What are the needed and established criteria 
present in the atmosphere in order for the prediction of fog formation? That 
is, what allows fog to form time and time and time again.

No modeling parroting... *My model says this... My model says that... It 
happens because my model says so.*

Knowing what happens before looking at your model... This goes back to having a 
full understanding of your Key Reads, and encompasses a more important idea, 
which is the prior observation of the phenomenon your are modeling. This 
observation of your modeled subject leads into......

Adjustment and fine-tuning... Guess what? This also goes right back to your Key 
Reads... You better not be using a model designed to predict fog formation in 
the Appellation Mountains in order to see about fog off the California Coast, 
unless you tweak that sucker by adding in the Key Reads specific to California 
and removing the key reads specific for the Appellations while at the same time 
leaving in the tried and true fundamental Key Reads for the formation of fog.

And last but not least...

Models are afraid of real data... Yes, you read that right. Models like to 
throw out real, genuine, verified data that happens not to agree with its 
underlying parameterization and boundary conditions... The ones YOU specified. 
What is the result of such an action you ask? An output that's in error that's 
what. Example: An observation in Fairbanks, AK is too cold when compared to the 
immediate surrounding area. This doesn't follow the pattern. This is an 
*abnormality*... So, the ETA model automatically throws it out of the data 
set... Call it model bias.

So, not that I am preaching here, but sit for a second and think about what you 
observed and what you were told when it came to Numerical Modeling at SVP, and 
apply those simple few ideas listed above. Like I said earlier, I'm not 
pointing fingers, but, it could turn out that a model or two presented at SVP 
2003 wasn't as solid as you might have thought.

And for you philosophers out there, I think that Hume himself put it much 
better than I have when he said:

"In a word, then, every effect is a distinct event from its cause. It could 
not, therefore, be discovered in the cause, and the first invention or 
conception of it, a priori, must be entirely arbitrary. And even after it is 
suggested, the conjunction of it with the cause must appear equally arbitrary, 
since there are always many other effects, which, to reason, must seem fully as 
consistent and natural. In vain, therefore, should we pretend to determine any 
single event, or infer any cause or effect, without the assistance of 
observation and experience. 

If we be, therefore, engaged by arguments to put trust in past experience, and 
make it the standard of our future judgment, these arguments must be probable 
only, or such as regard matter of fact and real existence according to the 
division above mentioned. But that there is no argument of this kind, must 
appear, if our explication of that species of reasoning be admitted as solid 
and satisfactory. We have said that all arguments concerning existence are 
founded on the relation of cause and effect; that our knowledge of that 
relation is derived entirely from experience; and that all our experimental 
conclusions proceed upon the supposition that the future will be conformable to 
the past. To endeavor, therefore, the proof of this last supposition by 
probable arguments, or arguments regarding existence, must be evidently going 
in a circle, and taking that for granted, which is the very point in question."

Brilliant guy.

Kris

http://hometown.aol.com/saurierlagen/Paleo-Photography.html