[A-TT49] Machine Learning Techniques in Weather, Climate, Ocean, Hydrology and Disease Predictions

[ATT49-01] Fine-tuning an AI weather model (GraphCast) for improved ensemble subseasonal forecasting

★Invited Papers

Vateanui Sansine^1,2,3, *Takeshi Izumo^1,2,3, Marania Hopuare^4,3, Damien Specq⁵, Sophie Martinoni-LaPierre⁵ (1. IRD (Institut de Recherche pour le Developpement; French National Research Institute for Sustainable Development), 2. UMR241 SECOPOL (Tahiti, French Polynesia), 3. Universite de Polynesie Francaise (UPF), 4. GEPASUD, University of Polynesia, Campus d ’ Outumaoro, 98718 Puna ’ auia, Tahiti, French Polynesia, 5. Météo - France, 42 Av. Gaspard Coriolis, 31100 Toulouse)

Keywords:Machine Learning (ML), subseasonal forecasting, fine-tuning, ensemble modeling, cost-effective AI training, weather and climate