Abstract/Summary

The World Weather Research Programme (WWRP)/World Climate Research Programme (WCRP) Subseasonal to Seasonal Prediction (S2S) project was launched in 2013 with the primary goals of improving forecast skill and understanding sources of predictability on the subseasonal timescale (from 2 weeks to a season) around the globe. Particular emphasis was placed on high-impact weather events, on developing coordination among operational centers, and on promoting the use of subseasonal forecasts by the applications communities. This 10-year project ended in December 2023. A key accomplishment was the establishment of a database of subseasonal forecasts, called the S2S database. This database enhanced collaboration between the research and operational communities, enabled studies on a wide range of topics and contributed to significant advances towards a better understanding of subseasonal predictability and windows of opportunity that contributed to improvements in forecast skill. It was used to train machine learning methods and test their performance in the S2S Artificial Intelligence/Machine Learning (AI/ML) Prize Challenge. The S2S project co-organized several coordinated research experiments to advance understanding of subseasonal predictability, and the Real-Time Pilot Initiative that provided real-time access to subseasonal data for 15 application projects. A sequence of training courses sustained over 10 years enhanced the capacity of national meteorological services in the Global South to make subseasonal forecasts. A major legacy of the S2S project was the establishment and designation of the World Meteorological organization (WMO) Global Producing Centres and Lead Centre for Sub-seasonal Predictions Multi-Model Ensemble, which will provide real-time subseasonal multi-model ensemble (MME) products to national and regional meteorological services.