The WWRP/WCRP S2S Project and Its Achievements

Abstract The World Weather Research Programme (WWRP)/World Climate Research Programme (WCRP) Subseasonal to Seasonal (S2S) Prediction project was launched in 2013 with the primary goals of improving forecast skill and understanding sources of predictability on the subseasonal time scale (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 application communities. This 10-yr 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 toward 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 coorganized 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 Subseasonal Prediction Multi-Model Ensemble, which will provide real-time subseasonal multimodel ensemble (MME) products to national and regional meteorological services. Significance Statement There is a growing interest in the research and application communities for subseasonal forecasts which cover the time range from 2 weeks to a season and fill the gap between medium-range weather and long-range seasonal forecasts. Skillful subseasonal prediction provides an important opportunity to inform decision-makers of, for example, changes in risks of extreme events or opportunities for optimizing resource management decisions. The WWRP/WCRP S2S project, mostly through the development of a large dataset of subseasonal ensemble predictions, known as the S2S database, helped improve our understanding of subseasonal predictability and the performance of state-of-the-art subseasonal prediction models and multimodel ensembles.