3 ms·

If you want to set up and use the WRF model linked in the submission to generate your own forecasts, you can follow this tutorial: http://www2.mmm.ucar.edu/wrf/

If you want to set up and use the WRF model linked in the submission to generate your own forecasts, you can follow this tutorial: http://www2.mmm.ucar.edu/wrf/OnLineTutorial/index.php http://www2.mmm.ucar.edu/wrf/OnLineTutorial/index.php 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 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)

ip26 8y ago
A corollary, would faster hardware help NOAA & friends? Do they already have the best available? Or are the models not able to take advantage of extra computational power?
- pr0tonic 8y ago
  More computational power is definitely better but that's not the whole story. For example the initial conditions of the model are really important.
- andrew42 8y ago
  (Disclaimer: I don't work in operational modeling) 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.
- sampo 8y ago
  New York Times has this 2016 article on how the European model is more advanced in many respects: https://www.nytimes.com/2016/10/23/magazine/why-isnt-the-us-better-at-predicting-extreme-weather.html 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-numerical-weather.html https://cliffmass.blogspot.com/2016/10/us-operational-numeri...

ip26 8y ago

A corollary, would faster hardware help NOAA & friends? Do they already have the best available? Or are the models not able to take advantage of extra computational power?

pr0tonic 8y ago
More computational power is definitely better but that's not the whole story. For example the initial conditions of the model are really important.
andrew42 8y ago
(Disclaimer: I don't work in operational modeling) 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.
sampo 8y ago
New York Times has this 2016 article on how the European model is more advanced in many respects: https://www.nytimes.com/2016/10/23/magazine/why-isnt-the-us-better-at-predicting-extreme-weather.html 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-numerical-weather.html https://cliffmass.blogspot.com/2016/10/us-operational-numeri...