When developing weather software, one of the most important pieces of data you will work with is a location list. A weather application is useless if the user can’t find a city and download weather data for it. There are several different methods users might want to be able to search for a weather location. The methods Seasonality supports include zip codes (U.S. only, for now), city, state, country, and ICAO. Actually, ICAO was just a convenience method I added, so when a user double-clicks on an ICAO weather station in the satellite imagery, the add location dialog box will pop up with a listing of locations that use that ICAO.

So where do you find a good location listing online? The best resource I’ve found is the GeoNames database. They have slightly over 80,000 cities, each having a population over 1,000 people in a simple CSV file you can download from their website. Each city has a state (if applicable), a country, latitude/longitude, elevation, population, time zone, and some other fields as well. Our basic needs are only the city name and it’s latitude/longitude, but some of these other fields come in handy when trying to calculate the local time, deciding which cities to mark on the map (higher population cities should take precedence), etc.

It’s not much use to have this location data unless you can correlate it with your weather data sources. You’ll definitely need a relational database to keep track of everything. I prefer PostgreSQL for my master location database. There are several aspects of data correlation that you’ll need to think about here. Everything from matching every location with the closest weather station ICAO, to getting zip code listings and matching each one with an appropriate city. It’s a lot of work (you’ll learn a lot of SQL along the way) but eventually you’ll have a giant web of location data that you can pull from.

Now that you have this master location database, you’ll want to trim it down to something you can actually ship with your application. For example, Seasonality’s master location database is over 4.5GB in size, which would obviously be too large to include in an application archive. A small download size is desirable, so only include the data you absolutely need. Also, PostgreSQL is a bit of overkill to be running in the background for a database this size, so convert your dataset to something different, like SQLite. Selecting a subset of data and converting it from PostgreSQL to SQLite all takes place in a custom script I wrote, so each time I update a location (and trust me, with so many locations there will be errors and corrections) all I need to do is re-run the export script and I have a fresh location database to include in the next version of Seasonality.