works on

From the 1 of 4 linked papers with an AI index.

collaborators

4 papers

physics.ao-ph2026

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…

physics.ao-ph2026

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.

physics.ao-ph2026

Hybrid weather prediction using spectral nudging toward machine-learning forecasts

I. Polichtchouk, M. C. A. Clare, M. Chantry +4

A hybrid approach to numerical weather prediction is investigated, in which the unperturbed physics-based ECMWF Integrated Forecasting System (IFS) is spectrally nudged toward fore…

physics.ao-ph2026

Hybrid ensemble forecasting combining physics-based and machine-learning predictions through spectral nudging

Inna Polichtchouk, Simon Lang, Sarah-Jane Lock +2

We present the first application of spectral nudging in a probabilistic ensemble forecasting framework, combining the physics-based ECMWF Integrated Forecasting System ensemble (IF…