From the 1 of 18 linked papers with an AI index.
18 papers
AIFS-TC: A simple correction competitive with the operational frontier for tropical cyclone intensity forecasting
Anna Allen, Wessel P. Bruinsma, Michael Maier-Gerber +3
AI weather models are in the process of revolutionising weather forecasting. While these models have been shown to achieve superior performance to physics-based NWP in forecasting…
HourGlass: A probabilistic data-driven temporal downscaler for global and regional weather forecasting
Magnus Sikora Ingstad, Mariana C. A. Clare, Olav Ersland +16
HourGlass is a probabilistic, data‑driven method that downscales 6‑hourly weather forecasts to hourly resolution, preserving small‑scale spatial detail and temporal consistency.
Global reanalysis from observations alone with machine learning
Peter Lean, Ewan Pinnington, Patrick Laloyaux +9
Earth system reanalysis datasets are foundational for weather and climate research and provide the gridded training data used by most machine learning weather prediction systems. H…
AIFS-SUBS: Extending Data-Driven Forecasting to Sub-Seasonal Timescales
Jakob Schloer, Steffen Tietsche, Christopher D. Roberts +6
Data-driven models now rival numerical weather prediction in the medium range, but extending them to sub-seasonal lead times raises challenges absent at shorter horizons. Errors ac…
AIFS-DOP: End-to-End Medium-Range Weather Prediction from Observations Alone with Machine Learning
Ewan Pinnington, Peter Lean, Mihai Alexe +8
We introduce the Artificial Intelligence Forecasting System for Direct Observation Prediction (AIFS-DOP). AIFS-DOP is trained on a 40-year harmonized dataset of gridded observation…
Representing the Surface Ocean in ECMWF's data-driven forecasting system AIFS
Sara Hahner, Lorenzo Zampieri, Jean-Raymond Bidlot +22
Machine-learning (ML) models, such as the AIFS at the ECMWF, have revolutionised weather forecasting in recent years. We present an extension of the AIFS that jointly models the at…