Subseasonal to Seasonal Prediction
The Gap Between Weather and Climate Forecasting
- 2 Edición - 7 de noviembre de 2025
- Última edición
- Editores: Andrew Robertson, Frederic Vitart
- Idioma: Inglés
Subseasonal-to-Seasonal Prediction provides the latest thinking from experts in the fields of sub-seasonal to seasonal (S2S) predictability science, numerical modeling, operat… Leer más
Descripción
Descripción
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.
Puntos claves
Puntos claves
- 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
De interès para
De interès para
Research scientists, professors, graduate students and post-docs in atmospheric, ocean, and climate sciences
Índice
Índice
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 characteristics
4. The Madden–Julian oscillation
5. Extratropical subseasonal-to-seasonal oscillations and multiple regimes: the dynamical systems view
6. Tropical-extratropical interactions and teleconnections
7. Land surface processes relevant to subseasonal-to-seasonal prediction
8. The role of the ocean in subseasonal-to-seasonal predictability and prediction
9. The role of sea ice in subseasonal to seasonal predictability
10. Subseasonal predictability and the stratosphere
11. Forecast system design, configuration, and complexity
12. The THORPEX interactive grand global ensemble and subseasonal-to-seasonal ensembles
13. Forecast recalibration and multimodel combination
14. Forecast verification for subseasonal-to-seasonal timescales
15. Machine learning for subseasonal-to-seasonal prediction
16. Subseasonal-to-seasonal prediction of weather extremes
17. Pilot experiences in using seamless forecasts for early action: Ready–Set–Go approach in the Red Cross
18. Communication and dissemination of forecasts and engaging user communities
19. Subseasonal prediction of Indian summer monsoon variability and extreme weather events
20. Predicting climate impacts on health at subseasonal to seasonal timescales
21. Coproducing reliable, actionable subseasonal-to-seasonal climate services across Africa
22. Subseasonal to seasonal climate predictions for energy
23. Subseasonal to seasonal forecasts enhance effective marine decision-making in a fast-changing ocean
24. Epilogue
2. Weather forecasting: what sets the forecast skill horizon?
3. Weather within climate: subseasonal predictability of tropical daily rainfall characteristics
4. The Madden–Julian oscillation
5. Extratropical subseasonal-to-seasonal oscillations and multiple regimes: the dynamical systems view
6. Tropical-extratropical interactions and teleconnections
7. Land surface processes relevant to subseasonal-to-seasonal prediction
8. The role of the ocean in subseasonal-to-seasonal predictability and prediction
9. The role of sea ice in subseasonal to seasonal predictability
10. Subseasonal predictability and the stratosphere
11. Forecast system design, configuration, and complexity
12. The THORPEX interactive grand global ensemble and subseasonal-to-seasonal ensembles
13. Forecast recalibration and multimodel combination
14. Forecast verification for subseasonal-to-seasonal timescales
15. Machine learning for subseasonal-to-seasonal prediction
16. Subseasonal-to-seasonal prediction of weather extremes
17. Pilot experiences in using seamless forecasts for early action: Ready–Set–Go approach in the Red Cross
18. Communication and dissemination of forecasts and engaging user communities
19. Subseasonal prediction of Indian summer monsoon variability and extreme weather events
20. Predicting climate impacts on health at subseasonal to seasonal timescales
21. Coproducing reliable, actionable subseasonal-to-seasonal climate services across Africa
22. Subseasonal to seasonal climate predictions for energy
23. Subseasonal to seasonal forecasts enhance effective marine decision-making in a fast-changing ocean
24. Epilogue
Detalles del producto
Detalles del producto
- Edición: 2
- Última edición
- Publicado: 10 de noviembre de 2025
- Idioma: Inglés
Sobre los editores
Sobre los editores
AR
Andrew Robertson
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.
Afiliaciones y experiencia
Senior Research Scientist, International Research Institute for Climate and Society, Earth Institute, Columbia University, NY, USAFV
Frederic Vitart
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.
Afiliaciones y experiencia
Senior Research Scientist, European Centre for Medium-range Weather Forecasts (ECMWF), UKVer libro en ScienceDirect
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