Description:

Subseasonal-to-seasonal (S2S; approximately week-2 through month-3) climate prediction has rapidly developed over the past decade, and demand for these predictions has increased apace. This session seeks submissions that discuss important developments in S2S prediction. Examples include advances in our understanding of sources of predictability such as modes of climate variability and the role of trends, statistical and dynamical modeling including multi-model ensembles, coupling between the ocean, sea ice, snow cover, or land surface with the atmosphere, and novel methods such as attribution, statistical post-processing, or machine learning techniques. Skill and predictability of extremes, cCase studies, novel applications, climate services activities, and forecast communication topics are also encouraged. Submissions that make use of the North American Multi-Model Ensemble (NMME), Unified Forecast System, Subseasonal Prediction Experiment (SubX) data, and/or the Subseasonal to Seasonal Prediction Project are particularly encouraged.