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stat.AP2026
Probabilistic forecasting of weather-driven faults in electricity networks: a flexible approach for extreme and non-extreme events
Mateus Maia, Daniela Castro-Camilo, Jethro Browell
Electricity networks are vulnerable to weather damage, with severe events often leading to faults and power outages. Timely forecasts of fault occurrences, ranging from nowcasts to…
stat.AP2025
XGBoost meets INLA: a two-stage spatio-temporal forecasting of wildfires in Portugal
Chenglei Hu, Regina Baltazar Bispo, Håvard Rue +3
Wildfires pose a major threat to Portugal, with over 115,000 hectares burned annually on average during 1980-2024, and the country has faced devastating mega-fires such as those in…
stat.AP2025
On the importance of tail assumptions in climate extreme event attribution
Mengran Li, Daniela Castro-Camilo
Extreme weather events are becoming more frequent and intense, posing serious threats to human life, biodiversity, and ecosystems. A key objective of extreme event attribution (EEA…