S2S AI Challenge

Winners announced: WMO Prize Challenge to improve Sub-seasonal to Seasonal Predictions using Artificial Intelligence

We congratulate the winners of the WMO Prize Challenge to improve Sub-seasonal to Seasonal Predictions using Artificial Intelligence!

? First Prize (CHF 15,000): David Landry, Jordan Gierschendorf, Arlan Dirkson, Bertrand Denis (Centre de recherche informatique de Montréal and ECCC)

? Second Prize (CHF 10,000): Llorenç Lledó, Sergi Bech, Lluís Palma, Andrea Manrique-Suñén, and Carlos Gómez Gonzalez (Barcelona Supercomputing Center)

? Third Prize (CHF 5,000): Adam Bienkowski, Shanglin Zhou, and Hee-Seung Kim (University of Connecticut)

WMO launched the Challenge in June 2021 with the aim to improve, through AI/Machine Learning techniques, the current precipitation and temperature forecasts for 3 to 6 weeks into the future from the best computational fluid dynamic models available today. This Challenge was organized by the Subseasonal-to-Seasonal Prediction Project (S2S Project), coordinated by the World Weather Research Programme (WWRP)/World Climate Research Programme (WCRP), in collaboration with the Swiss Data Science Center and the European Centre for Medium-Range Weather Forecasts (ECMWF).

We received 9 submissions, among which 5 submissions beat the calibrated ECMWF benchmark and climatology. Based on the RPSS scores and their verification by an expert review for the top ranked submissions, we are delighted to announce that the prizes were awarded to the top three submissions.

The organizers would like to congratulate the winners on their great achievements. Thank you to all the participant teams for their efforts and submissions and to all involved in the Challenge. 

For more information on the project and its legacy, please visit:

Challenge to improve Sub-seasonal to Seasonal Predictions using Artificial Intelligence (s2s-ai-challenge.github.io)