This is neat, though there are far better methods for doing this type of thing. Now that the Nexrads are dual-pol, you can look at the correlation between the horizontal and the vertical polarizations to filter out the vast majority of the noise.<p>The noise you are filtering out is primarily insect returns. If you watch it, it will get worse at some times of the day rather than others. If inversions happen, you'll also see some beam bending that can cause you to pick up powerlines/roads, etc. You can verify it is mostly bugs by looking at the differential reflectivity. The differential reflectivity(difference of horizontal and vertical returned powers) will be somewhat random for ground clutter, and higher values for bugs.<p>With this approach, without knowing exactly how you do it, I'd be worried that it would have the tendency to filter out initial formations of stratiform clouds, and just leave convective formations.
I can point you to some theory on how a lot of the filtering is done for research in atmos if you'd like, feel free to message me(I'm working on my Ph.D. in weather radar).
Seeing this on HN, I realize I didn't go into a lot of technical detail in the blog post (we still aren't quite sure who our audience is with the Forecast blog). So if anyone has any specific questions, ask away.
See also Making Clouds Go Away on MapBox Satellite <a href="http://mapbox.com/blog/improving-mapbox-satellite-by-making-clouds-disappear/" rel="nofollow">http://mapbox.com/blog/improving-mapbox-satellite-by-making-...</a> <a href="https://news.ycombinator.com/item?id=5475571" rel="nofollow">https://news.ycombinator.com/item?id=5475571</a>
Hey there. I've done a GPGPU implementation of a physical weather prediction model[1]. I'm interested in how you get your weather data. Do you use WSM for modeling? Also, have you considered licensing out Dark Sky for data assimilation purposes to weather agencies? What I hear from the weather researchers this is one of the hardest aspects of this field. I think that once you have a product that's able to integrate an automated feedback loop into existing weather models for all kinds of weather data, you've basically won the weather game.<p>[1]<a href="https://github.com/muellermichel/Hybrid-Fortran" rel="nofollow">https://github.com/muellermichel/Hybrid-Fortran</a>
Meteorologist turned HN junkie here: this is really cool and I love the commenter suggesting using dual pol data to do the heavy lifting for you.<p>My question about your radar data is this; it's beautiful but I absolutely hate the color palette you are using, from a weather perspective - why not just stick with the 'standard' green-to-red colors we all know and love? The purples are different, for sure - but really hard to make sense of!
Interesting... as part of a little site I threw together, I have a ton of radar data for the region of Italy where I live, and have always thought it'd be fun to do something with it:<p><a href="http://www.meteo-veneto.net/" rel="nofollow">http://www.meteo-veneto.net/</a>