> Didn't downvote myself, but if I had to lay money on it, I'd guess that you got downvoted for not providing links to the raw NOAA data? Sources FTW.
Yeah probably true, I didn't post a source because I thought it was common knowledge which in retrospect I'm not sure why I thought that.
And I'm glad you enjoyed the links, when I first started looking into the raw NOAA data and PRISM[1] data it took a bit to figure out what to do with it. But I've found the GDAL library helpful for parsing various weather data formats, and there are a lot of them[2].
PRISM is not NOAA raw data. It's a product produced by interpolating data from validated weather stations, taking into account elevation among other things. For example, doing straight interpolation between weather stations without taking into account elevation can lead to some very wrong results. In fact, PRISM stands for "Parameter-elevation Regressions on Independent Slopes Model"[0]. Also, the high-resolution PRISM data is not free, as it's a data product of OSU/NACSE. It costs real $$$.
Aside from point, weather station observations, most weather/climate data is gridded and you are right, GDAL provides lots of tools for processing and transforming gridded (raster) data products. DevelopmentSeed (no affiliation) creates some neat tools and I'd recommend following OSGEO[2] and the FOSS4G conference.
In a nutshell, we instinctively assume others know what we know. This was probably true when we lived in small tribes on the Serengeti, but not so much in the global information age.
It takes practice, but you can grow the habit of always providing a little extra context without sounding patronizing, as well, at least in-person, a better sense for when people are following the conversation.
What helped me grow this skill was lots of pair-programming, because that daily pair rotation forces you to be really good at context-sharing on the quick.
On that note: thank you for providing those links!
I learned something new today, and I can think of some uses for that data.