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Creating an Animation from Geostationary Satellite tv for pc Photographs to Dynamically Monitor Storms (Atmospheric River) in Actual-time utilizing Python and Google Colab
- 🌟 Introduction
- 🌐 Geostationary Operational Environmental Satellite tv for pc (GOES)
- 🔍 GOES Database in AWS
- ⏳ Obtain GOES NetCDFs
- 📊 Visualization of GOES Photographs
- 🎥 Timelapse of the Storm
- 📄 Conclusion
- 📚 References
🌟 Introduction
If you’re maintaining with the information, one of many breaking tales proper now could be concerning the highly effective storms referred to as the Atmospheric River set to hit California and have an effect on central and southern areas. An atmospheric river is a slim channel of winds that transports concentrated water vapor (moisture) from the tropics. The upcoming storm is predicted to convey heavy rainfall and vital flash flooding to elements of the state.
Final evening, whereas checking my Twitter account (now known as X), I got here throughout quite a few tweets concerning the storm, together with colourful maps projecting and simulating the quantity of rainfall over California. These maps shortly turned my motivation to write down this story.
On this publish, we’ll discover find out how to obtain photos captured by Geostationary satellites and visualize them utilizing Python. Since we will obtain a sequence of photos with a comparatively brief time interval, we’ll increase our code to show these photos like an animation (timelapse). By the top of studying this publish, I hope you’re feeling that you’re at a hard and fast level in area, watching the Earth from prime to backside!
🌐 Geostationary Operational Environmental Satellite tv for pc (GOES)
The Geostationary Operational Environmental Satellite tv for pc (GOES) is a sequence of climate satellites operated by america Nationwide Oceanic and Atmospheric Administration (NOAA) and the Nationwide Aeronautics and Area Administration (NASA). These satellites are positioned over particular places, permitting for fixed monitoring of fixing climate circumstances specifically areas.
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