"Legacy business" or not, I believe that listening to local public radio makes me a better citizen of my city. NPR needs to do everything it can to keep the local stations alive because it's not just the nationally popular programming that matters. Honestly, my local NPR station, WNYC, is the only remotely intelligent source of local news. Where else am I going to hear Andrew Cuomo, Bill de Blasio, and other influential people having a frank discussion on important local issues? The only alternatives are random internet blogs, NY Daily News, and Fox 5, and some crazy right wing talk shows in Jersey.
I don't see any problem with doing what it takes to keep these stations alive, even if it means that Ira Glass can't tell me to download this American Life using iTunes (which I already do).
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....
I always get drawn in by these things. "Here's a tool you know and love, and here's why it sucks and you need to change." I remember feeling the exact same way when I switched to homebrew from macports from fink.