Most users are familiar with the “satellite view” on their phones—a simple photograph of clouds. However, for a university-level understanding of meteorology, we must look deeper into the electromagnetic spectrum. At Canavu Starline, our focus is on the dissemination of data derived from Radiometers—the sensors that “see” what the human eye cannot.
By analyzing Infrared (IR) and Water Vapor channels, we can determine cloud-top temperatures and moisture content at various levels of the atmosphere. This isn’t just a picture; it’s a data set. In this post, we explore how these “Starline” data points are processed by AI to predict storm intensification before the first raindrop hits the ground.
Check the Canavu Starline Education Hub for the full lecture on the Physics of Remote Sensing and satellite orbit types.