Amirpasha

Earthly Machine Learning

Science EN ↓ Odcinki: 52

“Earthly Machine Learning (EML)” offers AI-generated insights into cutting-edge machine learning research in weather and climate sciences. Powered by Google NotebookLM, each episode distils the essence of a standout paper, helping you decide if it’s worth a deeper look. Stay updated on the ML innovations shaping our understanding of Earth. It may contain hallucinations.

Koniecznie odwiedź stronę podcastu i wesprzyj twórcę: amozaffari.github.io

Autor

Amirpasha

Kategoria

Science

Strona podcastu

amozaffari.github.io

Ostatni odcinek

9 maj 2026

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Odcinki

Robustness of AI-based weather forecasts in a changing climate 07.01.2025 17:37

Abstract : Data-driven machine learning models for weather forecasting have made transformational progress in the last 1-2 years, with state-of-the-art ones now outperforming the best physics-based models for a wide range of skill scores. Given the strong links between weather and climate modelling, this raises the question whether machine learning models could also revolutionize climate science,...

GenCast - Probabilistic weather forecasting with machine learning 02.01.2025 22:18

Abstrac t : Weather forecasts are fundamentally uncertain, so predicting the range of probable weather scenarios is crucial for important decisions, from warning the public about hazardous weather to planning renewable energy use. Traditionally, weather forecasts have been based on numerical weather prediction (NWP) 1 , which relies on physics-based simulations of the atmosphere. Recent advances i...