Global Forecast System source code

ML techniques certainly are being used to predict the weather, maybe just not at NOAA or the Weather Channel. The weather derivative industry[0] is an $8 billion dollar industry, making it larger than the entire rocket launch industry (public and private combined). Just as there are Elon Musks in the rocket launch industry, there are maverick hedge funds out there making a killing by predicting the weather using the latest Big Data tools.

[0] http://en.wikipedia.org/wiki/Weather_derivative

Sometimes Machine Learning is the wrong approach. Direct mathematical modeling, if the underlying causal phenomenon are well known, bypasses the whole learning aspect of an explanatory system. Machine learning might help make sense of the residual noise that can't be accounted for with direct mathematical modeling. But at the level of sophistication that I've seen (predicting wind patterns using Finite Element Analysis methods mapped to topographical patterns fine-grained enough to model small buildings), I can't imagine any machine learning methods that could make any sense of the residual noise.

Probably because if it worked they'd already be doing it.

To create a global NWP system from this code you would need observations (soundings, SST, satellite measurements) as well as a super computer.

You don't want the "raw sensor data". You need it after it's been processed to the appropriate level, to retrieve geophysically-relevant quantities (like temperatures and wind speeds) from the data that is measured. That is not done by the forecasters.

I'm a part of this community. I assure you speed in number crunching is a huge reason this is written in F90.

If you look at Julia[0] they have quite a lot of performance benchmarks and you will see that Fortran is always at or near the top. What is really important, from a numerical code point of view, is that with Fortran it is easy to be at the top by operating on matrices and vectors etc. You do not have to torture your mind and think too much to optimize your code, "remove the IF in the loops" is often just what you need.

I am writing code in Fortran 77/90 every day, I really really enjoy it. Calling your Fortran code from Python is also so easy that you can really have clear cut between data management in Python and computational work in Fortran.

[0]: http://julialang.org/

inertia would have something to do with it, like there's an 'anal.sh' file which even made it into the documentation.

I can't seem to access the SVN repo, I wonder how/if they unit tested it all.

imo, fortran90 is about the easiest language to follow - if language is all that is stopping you (and you know some other language already), then you should just pile straight in.

From looking at some of the code, what is hard for me to follow is the 'overall view'. The documentation (of the model) looks quite nicely done, but there must be a huge amount of fluid dynamics etc etc knowledge, that would take me years to learn.

Your first sentence sniped me and I almost wrote a Big Response before I read the second line and realized you're obviously joking…