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[python #NNT-425178]: Multivariate Surface Analysis


Provided LAPS doesn't end up too complicated with too much manual intervention, 
configuration, I could see something like that included in MetPy.

If it was too big/complicated, it might make sense in a standalone project that 
uses MetPy.

I don't have a good handle on how much this would be a system vs. a function 


> Hello there folks!
> I was, just now, taking a look at the wonderful world of MetPy. So many
> great advances. Well done!
> Then, I had a thought.
> In MetPY, it is clear that Cressman and Barnes analyses are possible. Nice
> tools to make those. That said, they are - as near as I can tell - not
> multivariate. Nor do they have any sort of 'balance' as a part of what
> they do.
> The thought:
> Ages ago, NOAA Global System Laboratory, under a group led by John
> McGinley, had a thing called "LAPS". Local Analysis and Prediction
> System. One of the things it could do is to make a surface analysis. I
> seem to recall it was multivariate (temperature obs could influence
> dewpoint and pressure as well as temperature, pressure obs could influence
> winds as well as pressure, etc.). I also remember a bit of code that
> would bring all things into gradient wind balance as a final pass.
> I know that LAPS is still out there, thought it seems to be a big FORTRAN 
> thing for the most part:
> https://github.com/huangshouyou/laps-1
> So the question to you all is: has there ever been any discussion of
> any sort in 'porting' LAPS (or something like it) into METPY? The idea
> would be to take a collection of surface metars, as well as some sort of
> background field (maybe a short-range forecast), and make a nice smooth
> surface analysis of all things that is consistent.
> Best regards,

Ticket Details
Ticket ID: NNT-425178
Department: Support Python
Priority: Low
Status: Closed
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