Developing Real-time Datasets for the NOAA Science on a Sphere

The NOAA Science on a Sphere (SOS) is an educational tool for visualizing imagery and data in a 3D spherical format. This is particularly useful when visualizing data at a global scale. Datasets developed for the SOS are either static or real-time. Real-time datasets update as new data becomes available, while static datasets stay as they are. This presentation is specifically about developing real-time datasets using python. This includes automation of data collection, processing, and visualization. These tasks are applicable to a variety of disciplines, not only development for the SOS. To demonstrate this procedure, I will go over developing a SOS dataset using python’s package ecosystem. Specifically, I will cover automation of data acquisition from NOAA’s public FTP servers using ftplib and data visualization for the SOS using cartopy.