🌎 𝐓𝐡𝐞 𝐟𝐢𝐫𝐬𝐭 𝐞𝐯𝐞𝐫 𝐅𝐨𝐮𝐧𝐝𝐚𝐭𝐢𝐨𝐧 𝐰𝐞𝐚𝐭𝐡𝐞𝐫 𝐦𝐨𝐝𝐞𝐥: 𝐏𝐫𝐢𝐭𝐡𝐯𝐢 𝐖𝐱𝐂 𝐞𝐧𝐚𝐛𝐥𝐞𝐬 𝐥𝐢𝐟𝐞-𝐬𝐚𝐯𝐢𝐧𝐠 𝐰𝐞𝐚𝐭𝐡𝐞𝐫 𝐩𝐫𝐞𝐝𝐢𝐜𝐭𝐢𝐨𝐧𝐬

Hurricane Katrina killed hundreds of people as it made landfall on New Orleans in 2005 - many of these deaths could have been avoided if alerts had been given one day earlier. Accurate weather forecasts are really life-saving.

🔥 Now, NASA and IBM just dropped a game-changing new model: the first ever foundation model for weather! This means, it's the first time we have a generalist model not restricted to one task, but able to predict 160 weather variables!

Prithvi WxC (Prithvi, “पृथ्वी”, is the Sanskrit name for Earth) - is a 2.3 billion parameter model, with an architecture close to previous vision transformers like Hiera.

💡 But it comes with some important tweaks: under the hood, Prithvi WxC uses a clever transformer-based architecture with 25 encoder and 5 decoder blocks. It alternates between "local" and "global" attention to capture both regional and global weather patterns.

𝗞𝗲𝘆 𝗶𝗻𝘀𝗶𝗴𝗵𝘁𝘀:
🔮 Nails short-term forecasts - Prithvi WxC crushed it on 6-12 hour predictions, even outperforming some traditional numerical weather models
🌀 Tracks hurricanes like a champ - For Hurricane Ida, it predicted the landfall location within 5 km (vs 20+ km errors from other AI models), which is a huge progress!
🔍 6x downscaling power - Can zoom in on weather data to 6x higher resolution with 4x lower error than basic methods
🌊 Models elusive gravity waves - Accurately simulates these crucial but hard-to-capture atmospheric oscillations

As climate change intensifies, tools like Prithvi WxC will become more and more crucial to avoid disasters!

Announcement post 👉 https://newsroom.ibm.com/2024-09-23-ibm-and-nasa-release-open-source-ai-model-on-hugging-face-for-weather-and-climate-applications

Model on the Hub 👉 https://huggingface.co/Prithvi-WxC

Thank you @clem for highlighting it!