Earthly Machine Learning
by Amirpasha
Machine learning is revolutionizing weather forecasting – the next…
About this podcast
“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.
Episodes
The newest 20 of 57 episodes
- Machine learning is revolutionizing weather forecasting – the next step is a change in how we work · 21 min · Season 2 Episode 14Citation: Dueben, P., Bauer, P., Fuhrer, O., Koldunov, N., & Kristiansen, J. (2026). Machine learning is revolutionizing weather forecasting – the next step is a change in how we…
- CORDEX-ML-Bench: A Benchmark for Data-Driven Regional Climate Downscaling—Experiment Design and Overview · 20 min · Season 2 Episode 13Citation: Rampal, N., González-Abad, J., Addison, H., Baño-Medina, J., Bettolli, M. L., Blasone, V., Booth, B., Coppola, E., Di Gioia, S., Oldham-Dorrington, J., Doury, A…
- AIMIP Phase 1: Systematic Evaluations of AI Weather and Climate Models · 19 min · Season 2 Episode 12Citation: Henn, B., Bretherton, C. S., Kodunov, N., Lessig, C., Molina, M. J., Arcomano, T., Watt-Meyer, O., Couairon, G., Singh, R., Brunstein, R., Hasson, Y., Jost, A…
- WV-Net: A Foundation Model for SAR Ocean Satellite Imagery · 21 min · Season 2 Episode 11Citation: Glaser, Y., Stopa, J. E., Wolniewicz, L. M., Foster, R., Vandemark, D., Mouche, A., Chapron, B., & Sadowski, P. (2025). WV-Net: A Foundation Model for SAR Ocean…
- Toward Skillful Forecasting of Super El Niño Events Using a Diffusion-Based Westerly Wind Burst Parameterization · 17 min · Season 2 Episode 10Citation: Ji, C., Mu, M., Qin, B., Lian, T., Yuan, S., Feng, J., Song, S., Wei, Y., Dai, G., Wang, J., & Fang, X. (2025). Toward skillful forecasting of super El Niño events…
- Aligning artificial intelligence with climate change mitigation · 19 min · Season 2 Episode 9Citation: Kaack, L. H., Donti, P. L., Strubell, E., Kamiya, G., Creutzig, F., & Rolnick, D. (2022). Aligning artificial intelligence with climate change mitigation. Nature…
- Machine learning for the physics of climate · 20 min · Season 2 Episode 8Machine learning for the physics of climate Citation: Bracco, A., Brajard, J., Dijkstra, H. A., Hassanzadeh, P., Lessig, C., & Monteleoni, C. (2025). Machine learning for the…
- Atmospheric Transport Modeling of CO2 With Neural Networks · 21 min · Season 2 Episode 7Citation: Benson, V., Bastos, A., Reimers, C., Winkler, A. J., Yang, F., & Reichstein, M. (2025). Atmospheric transport modeling of CO2 with neural networks. Journal of Advances…
- On the foundations of Earth foundation models · 18 min · Season 2 Episode 6Citation: Zhu, X. X., Xiong, Z., Wang, Y., Stewart, A. J., Heidler, K., Wang, Y., Yuan, Z., Dujardin, T., Xu, Q., & Shi, Y. (2026). On the foundations of Earth foundation models…
- Whose weather is it? A fairness framework for data-driven weather forecasting · 22 min · Season 2 Episode 5Citation: Olivetti, L., & Messori, G. (2025). Whose weather is it? A fairness framework for data-driven weather forecasting. Environmental Research Letters, 20, 121006…
- Learning predictable and informative dynamical drivers of extreme precipitation using variational autoencoders · 18 min · Season 2 Episode 4Citation: Spuler, F. R., Kretschmer, M., Balmaseda, M. A., Kovalchuk, Y., & Shepherd, T. G. (2025). Learning predictable and informative dynamical drivers of extreme…
- Green and intelligent: the role of AI in the climate transition · 18 min · Season 2 Episode 3Green and intelligent: the role of AI in the climate transition Citation: Stern, N., Romani, M., Pierfederici, R., Braun, M., Barraclough, D., Lingeswaran, S., Weirich-Benet, E…
- Climate Knowledge in Large Language Models · 12 min · Season 2 Episode 2Climate Knowledge in Large Language Models Kuznetsov, I., Grassi, J., Pantiukhin, D., Shapkin, B., Jung, T., & Koldunov, N. (2025). Alfred Wegener Institute, Helmholtz Centre for…
- Artificial Intelligence for Atmospheric Sciences: A Research Roadmap · 14 min · Season 2 Episode 1Artificial Intelligence for Atmospheric Sciences: A Research Roadmap Citation: Zaidan, M. A., Motlagh, N. H., Nurmi, P., Hussein, T., Kulmala, M., Petäjä, T., & Tarkoma, S…
- Differentiable and accelerated spherical harmonic and Wigner transforms · 13 min · Season 1 Episode 43Differentiable and accelerated spherical harmonic and Wigner transforms Matthew A. Price, Jason D. McEwen *Journal of Computational Physics (2024)* * This work introduces novel…
- Score-based diffusion nowcasting of GOES imagery · 13 min · Season 1 Episode 42Score-based diffusion nowcasting of GOES imagery *Randy J. Chase, Katherine Haynes, Lander Ver Hoef, Imme Ebert-Uphoff, a Cooperative Institute for Research in the Atmosphere…
- FuXi-Ocean: A Global Ocean Forecasting System with Sub-Daily Resolution · 16 min · Season 1 Episode 41FuXi-Ocean: A Global Ocean Forecasting System with Sub-Daily Resolution *Qiusheng Huang, Yuan Niu, Xiaohui Zhong, Anboyu Guo, Lei Chen, Dianjun Zhang, Xuefeng Zhang, Hao Li*…
- Beyond the Training Data: Confidence-Guided Mixing of Parameterizations in a Hybrid AI-Climate Model · 15 min · Season 1 Episode 40Beyond the Training Data: Confidence-Guided Mixing of Parameterizations in a Hybrid AI-Climate Model *By Helge Heuer, Tom Beucler, Mierk Schwabe, Julien Savre, Manuel Schlund…
- Climate in a Bottle: Towards a Generative Foundation Model for the Kilometer-Scale Global Atmosphere · 14 min · Season 1 Episode 39Climate in a Bottle: Towards a Generative Foundation Model for the Kilometer-Scale Global Atmosphere (By Noah D. Brenowitz, Tao Ge, Akshay Subramaniam, Peter Manshausen, Aayush…
- Probabilistic Measures for Fair AI and NWP Model Comparison · 13 min · Season 1 Episode 38Probabilistic measures afford fair comparisons of AIWP and NWP model output (Tilmann Gneiting, Tobias Biegert, Kristof Kraus, Eva-Maria Walz, Alexander I. Jordan, Sebastian…







