Subseasonal to Seasonal Prediction

The Gap Between Weather and Climate Forecasting

Andrew Robertson, Frederic Vitart

• Publisher: Elsevier
• Year: 2025
• Edition: 2
• eBook ISBN:
  9780443315398
• Topic: Physical Sciences
• Subtopic: Meteorology & Climatology

Subseasonal-to-Seasonal Prediction provides the latest thinking from experts in the fields of sub-seasonal to seasonal (S2S) predictability science, numerical modeling, operational forecasting, and developing application sectors. This fully updated second edition comprehensively covers the sources of S2S predictability, S2S modeling, and forecasting using dynamical or machine learning methods, and S2S applications. There are brand new chapters on the role of the ocean in sub-seasonal predictability, machine learning in S2S prediction, co-produced S2S climate services in Africa, S2S for energy, and marine weather prediction on S2S timescales. This valuable resource offers atmospheric and climate scientists the very latest developments in this rapidly evolving field. - Contributed chapters from experts in S2S science and forecasting updated for use in an emerging and interdisciplinary field - Synthesis of the state of S2S science, through the use of concrete examples that enable potential users of S2S forecasts to quickly grasp the potential for use in their own decision setting - Broad set of interdisciplinary linked topics, illustrated with graphic examples to powerfully illustrate the interdisciplinary linkages

Table of contents

• Title of Book
• Chapter 1 Introduction: why subseasonal-to-seasonal prediction?
• Chapter 2 Weather forecasting: what sets the forecast skill horizon?
• Chapter 3 Weather within climate: subseasonal predictability of tropical daily rainfall characteristics
• Chapter 4 The Madden–Julian oscillation
• Chapter 5 Extratropical subseasonal-to-seasonal oscillations and multiple regimes: the dynamical systems view
• Chapter 6 Tropical-extratropical interactions and teleconnections
• Chapter 7 Land surface processes relevant to subseasonal-to-seasonal prediction
• Chapter 8 The role of the ocean in subseasonal-to-seasonal predictability and prediction
• Chapter 9 The role of sea ice in subseasonal to seasonal predictability
• Chapter 10 Subseasonal predictability and the stratosphere
• Chapter 11 Forecast system design, configuration, and complexity
• Chapter 12 The THORPEX interactive grand global ensemble and subseasonal-to-seasonal ensembles
• Chapter 13 Forecast recalibration and multimodel combination
• Chapter 14 Forecast verification for subseasonal-to-seasonal timescales
• Chapter 15 Machine learning for subseasonal-to-seasonal prediction
• Chapter 16 Subseasonal-to-seasonal prediction of weather extremes
• Chapter 17 Pilot experiences in using seamless forecasts for early action: Ready–Set–Go approach in the Red Cross
• Chapter 18 Communication and dissemination of forecasts and engaging user communities
• Chapter 19 Subseasonal prediction of Indian summer monsoon variability and extreme weather events
• Chapter 20 Predicting climate impacts on health at subseasonal-to-seasonal timescales
• Chapter 21 Coproducing reliable, actionable subseasonal-to-seasonal climate services across Africa
• Chapter 22 Subseasonal-to-seasonal climate predictions for energy
• Chapter 23 Subseasonal-to-seasonal forecasts enhance effective marine decision-making in a fast-changing ocean
• Chapter 24 Epilogue
• Index