

A Deep Hybrid Model for Weather Forecasting [pdf] - runesoerensen
http://research.microsoft.com/en-us/um/people/horvitz/weather_hybrid_representation.pdf

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yyyyyak
as a grad student in atmospheric science, I am a little skeptical of the
applicability and robustness of these approaches. There are people in our
group who apply machine learning ideas for prediction, and I use them for data
analysis, so I am not against data-based approaches. however, the partial
differential equations which govern the atmosphere are known, can be
approximated in a computer, and have been done so for decades. It seems silly
to pretend otherwise, and the best/current weather predictions use data and
physics.

This report make some pretty intense statements about the "limited success" of
"analytical techniques", but in the end, they only claim to make an
improvement of 1-2%. The kicker is that they make this comparison to the NOAA
model, which is one of the crappiest models out there. The model the europeans
use is about 5-10% more skillful, and it is generally recognized that the USA
has fallen behind in this regard: [http://cliffmass.blogspot.com/2012/03/us-
fallen-behind-in-nu...](http://cliffmass.blogspot.com/2012/03/us-fallen-
behind-in-numerical-weather.html).

