Dr Andrew Robertson is a Senior Research Scientist at the International Research Institute for Climate and Society, part of the Earth Institute at Columbia University. He heads the IRI Climate Group and teaches as an adjunct professor at Columbia. Graduating with a PhD in atmospheric dynamics, he has over 30 years of experience in topics ranging from midlatitude meteorology, coupled ocean-atmosphere climate dynamics, sub-seasonal and seasonal forecasting, downscaling, and tailoring of climate information for use in conjunction with sectoral models for climate adaptation and risk management. He has taught in capacity building training courses around the world. Frédéric Vitart is a Senior Research Scientist at the European Centre for Medium-range Weather Forecasts (ECMWF). After graduating with a PhD in atmospheric and oceanic sciences from Princeton University, he joined ECMWF in 1998, where he leads the research on ensemble sub-seasonal forecasts. He has over 20 years of experience in sub-seasonal and seasonal prediction, couple ocean-atmosphere modeling, tropical and mid-latitude meteorology, tropical cyclone prediction. He is the author of over 100 publications in the peer-review literature and has taught in several training courses around the world.

• 1. Introduction: why subseasonal-to-seasonal prediction?2. Weather forecasting: what sets the forecast skill horizon?3. Weather within climate: subseasonal predictability of tropical daily rainfall characteristics4. The Madden–Julian oscillation5. Extratropical subseasonal-to-seasonal oscillations and multiple regimes: the dynamical systems view6. Tropical-extratropical interactions and teleconnections7. Land surface processes relevant to subseasonal-to-seasonal prediction8. The role of the ocean in subseasonal-to-seasonal predictability and prediction9. The role of sea ice in subseasonal to seasonal predictability10. Subseasonal predictability and the stratosphere11. Forecast system design, configuration, and complexity12. The THORPEX interactive grand global ensemble and subseasonal-to-seasonal ensembles13. Forecast recalibration and multimodel combination14. Forecast verification for subseasonal-to-seasonal timescales15. Machine learning for subseasonal-to-seasonal prediction16. Subseasonal-to-seasonal prediction of weather extremes17. Pilot experiences in using seamless forecasts for early action: Ready–Set–Go approach in the Red Cross18. Communication and dissemination of forecasts and engaging user communities19. Subseasonal prediction of Indian summer monsoon variability and extreme weather events20. Predicting climate impacts on health at subseasonal to seasonal timescales21. Coproducing reliable, actionable subseasonal-to-seasonal climate services across Africa22. Subseasonal to seasonal climate predictions for energy23. Subseasonal to seasonal forecasts enhance effective marine decision-making in a fast-changing ocean24. Epilogue