WRF Official Repository – Weather Research and Forecasting
github.com
github.com
I believe national-wide weather forecasting by computers was been done since the 1960s. As today's personal workstations are much more powerful than a supercomputer built in the 1990s, and the old models and numerical methods (not the state-of-art ones) are well-known (and have multiple open-source implementations), the calculation should be possible today on an ordinary workstation for educational purposes.
But exactly what kind of data do I need to run my own weather forecast on my computer? Is it possible to calculate my personal 12-hour weather report based on public data published by NOAA, etc? Is there a tutorial for setting up a weather forecast?
> But what kind of data do I need to run my own weather forecast on my computer?
I believe it's a combination of plain old measurements (wind direction + speed, temperature, humidity, etc etc), RADAR, and a lot of historic precedence. I don't know how much of that is open-sourced, but I think it'd be easier to hook onto the api of your national weather broadcasting websites and ask them what your weather will be for the next 12 hours.
You can easily run WRF with the NOAA GFS as initial conditions, it would easily run on an iPhone computationally, but practically it will work on your desktop Linux box.
http://www2.mmm.ucar.edu/wrf/users/supports/tutorial.html
They have a containerized version too, which will save much fiddling with compilers and libraries.
A 16-node (116 Intel Xeon 2.3GHz processors) Linux PC Beowulf cluster
For all but the most extreme configurations, WRF will run on a modern 2-4 core Linux desktop. It will be fairly slow, but it will run.
You can use the raw data from the official model runs published by NOAA as initial and boundary conditions for your model runs: https://nomads.ncep.noaa.gov . One of the coolest and most under appreciated things about NOAA is that they publish everything online for free for everyone.
Or you can just get the raw data from the official runs from the link above and do your own extraction, and maybe post processing if you like.
(Source: PhD in meteorology. Finally made an account when I saw this posted)
NOAA just upgraded last year to a system that hits 8.4 petaflops, which is about the same as the European system, and the Japanese and UK systems are fairly similar.
More computing power would absolutely help the NOAA models (primarily GFS) increase resolution, improve the data assimilation method that generates the initial conditions, and increase the number of ensembles run. The GFS lags the European model in all of these areas. It would especially help increase the number of ensembles, since that is an embarrassingly parallel problem. However, NOAA also needs more researchers and funding. For example, model configuration changes not only need to be developed, but also tested to ensure that there aren't unexpected regressions in forecast skill. And, for example, the Europeans have put a lot of research and development into their data assimilation method, and it's one of the reasons they tend to outperform other models.
https://www.nytimes.com/2016/10/23/magazine/why-isnt-the-us-...
And also this blog post by Cliff Mass:
https://cliffmass.blogspot.com/2016/10/us-operational-numeri...
Http://Strc.comet.ucar.edu/index.html
– Meteorological studies
– Real-time NWP
– Idealized simulations
– Data assimilation
– Earth system model coupling
– Model training and educational support