Creating an Animation from Geostationary Satellite Images to Dynamically Monitor Storms (Atmospheric River) in Real-time using Python and Google Colab
- 🌟 Introduction
- 🌐 Geostationary Operational Environmental Satellite (GOES)
- 🔍 GOES Database in AWS
- ⏳ Download GOES NetCDFs
- 📊 Visualization of GOES Images
- 🎥 Timelapse of the Storm
- 📄 Conclusion
- 📚 References
🌟 Introduction
If you are keeping up with the news, one of the breaking stories right now is about the powerful storms known as the Atmospheric River set to hit California and affect central and southern regions. An atmospheric river is a narrow channel of winds that transports concentrated water vapor (moisture) from the tropics. The upcoming storm is expected to bring heavy rainfall and significant flash flooding to parts of the state.
Last night, while checking my Twitter account (now called X), I came across numerous tweets about the storm, along with colorful maps projecting and simulating the amount of rainfall over California. These maps quickly became my motivation to write this story.
In this post, we will explore how to download images captured by Geostationary satellites and visualize them using Python. Since we can download a sequence of images with a relatively short time interval, we will expand our code to display these images like an animation (timelapse). By the end of reading this post, I hope you feel that you are at a fixed point in space, watching the Earth from top to bottom!
🌐 Geostationary Operational Environmental Satellite (GOES)
The Geostationary Operational Environmental Satellite (GOES) is a series of weather satellites operated by the United States National Oceanic and Atmospheric Administration (NOAA) and the National Aeronautics and Space Administration (NASA). These satellites are positioned over specific locations, allowing for constant monitoring of changing weather conditions in particular regions.