
Sub-seasonal to Seasonal Prediction
The Gap Between Weather and Climate Forecasting
- 1st Edition - October 19, 2018
- Imprint: Elsevier
- Editors: Andrew Robertson, Frederic Vitart
- Language: English
- Paperback ISBN:9 7 8 - 0 - 1 2 - 8 1 1 7 1 4 - 9
- eBook ISBN:9 7 8 - 0 - 1 2 - 8 1 1 7 1 5 - 6
The Gap Between Weather and Climate Forecasting: Sub-seasonal to Seasonal Prediction is an ideal reference for researchers and practitioners across the range of disciplin… Read more

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Request a sales quoteThe Gap Between Weather and Climate Forecasting: Sub-seasonal to Seasonal Prediction is an ideal reference for researchers and practitioners across the range of disciplines involved in the science, modeling, forecasting and application of this new frontier in sub-seasonal to seasonal (S2S) prediction. It provides an accessible, yet rigorous, introduction to the scientific principles and sources of predictability through the unique challenges of numerical simulation and forecasting with state-of-science modeling codes and supercomputers. Additional coverage includes the prospects for developing applications to trigger early action decisions to lessen weather catastrophes, minimize costly damage, and optimize operator decisions.
The book consists of a set of contributed chapters solicited from experts and leaders in the fields of S2S predictability science, numerical modeling, operational forecasting, and developing application sectors. The introduction and conclusion, written by the co-editors, provides historical perspective, unique synthesis and prospects, and emerging opportunities in this exciting, complex and interdisciplinary field.
- Contains contributed chapters from leaders and experts in sub-seasonal to seasonal science, forecasting and applications
- Provides a one-stop shop for graduate students, academic and applied researchers, and practitioners in an emerging and interdisciplinary field
- Offers a synthesis of the state of S2S science through the use of concrete examples, enabling potential users of S2S forecasts to quickly grasp the potential for application in their own decision-making
- Includes a broad set of topics, illustrated with graphic examples, that highlight interdisciplinary linkages
Climatologists, meteorologists, atmospheric scientists, Oceanographers. Professionals working in the fields of energy, insurance, public health, water resource management, disaster risk reduction, agriculture
Part I: Setting the scene
- Introduction: Why S2S?
- Weather forecasting: What sets the forecast horizon?
- Weather within Climate: Sub-seasonal predictability of tropical daily rainfall characteristics
- Identifying wave processes associated with predictability across time scales: An empirical normal mode approach
- The Madden-Julian Oscillation
- Extratropical sub-seasonal–to–seasonal oscillations and multiple regimes: The dynamical systems view
- Tropical-Extratropical Interactions and Teleconnections
- Land surface processes relevant to S2S prediction
- Midlatitude Meso-scale Ocean-Atmosphere Interaction and Its Relevance to S2S Prediction
- The role of sea ice in subseasonal predictability
- Sub-seasonal Predictability and the Stratosphere
- Forecast system design, configuration, complexity
- Ensemble generation: the TIGGE and S2S ensembles
- GCMs with Full Representation of Cloud Microphysics and Their MJO Simulation
- Forecast recalibration and multi-model combination
- Forecast verification for S2S time scales
- Sub-seasonal to Seasonal Prediction of Weather Extremes
- Pilot experiences in using seamless forecasts for early action: Ready-Set-Go approach in the Red Cross
- Communication and dissemination of forecasts and engaging user communities
- Seamless prediction of monsoon onset and active/break phases
- Lessons learned in 25 years informing sectoral decisions with probabilistic climate forecasts
- Predicting climate impacts on health at sub-seasonal to seasonal timescales
Frederic Vitart and Andrew W. Robertson
Zoltan Toth & Roberto Buizza
Vincent Moron, Andrew W. Robertson, Lei Wang
Gilbert Brunet & John Methven
Part II: Sources of S2S Predictability
Steve J. Woolnough
Michael Ghil, Andreas Groth, Dmitri Kondrashov, Andrew W. Robertson
Hai Lin, Jorgen Frederiksen, David Straus, and Cristiana Stan
Paul A. Dirmeyer, Pierre Gentine, Michael B. Ek, Gianpaolo Balsamo
R. Saravanan and P. Chang
Matthieu Chevallier, Helge Goessling, Virginie Guémas, Thomas Jung and François Massonnet
Amy Butler, Andrew Charlton-Perez, Daniela I.V. Domeisen, Chaim Garfinkel, Edwin P. Gerber, Peter Hitchcock, Alexey Yu. Karpechko, Amanda C. Maycock, Michael Sigmond, Isla Simpson, Seok-Woo Son
Part III: S2S Modeling and Forecasting
Yuhei Takaya
Roberto Buizza
In-Sik Kang, Min-Seop Ahn, Hiroaki Miura, and Aneesh Subramanian
Stefan Siegert, David Stephenson
Caio A. S. Coelho, Barbara Brown, Laurie Wilson, Marion Mittermaier, Barbara Casati
Part IV: S2S Applications
Frédéric Vitart,
Christopher Cunningham, Michael DeFlorio, Emanuel Dutra, Laura Ferranti, Brian Golding, Debra Hudson, Charles Jones, Christophe Lavaysse, Joanne Robbins, Michael K. Tippett
Juan Bazo, Roop Singh, Mathieu Destrooper, Erin Coughlan de Perez
Joanne Robbins, Christopher Cunningham, Rutger Dankers, Matthew DeGennaro, Giovanni Dolif, Robyn Duell, Victor Marchezini, Brian Mills, Juan Pablo Sarmiento, Amber Silver, Rachel Trajber, Andrew Watkins
A.K. Sahai, Rajib Chattopadhyay, Susmitha Joseph, Phani M Krishna, D. R. Pattnaik, S Abhilash
Rafael Terra and Walter E. Baethgen
Adrian M. Tompkins, Rachel Lowe, Hannah Nissan, Nadege Martiny, Pascal Roucou, Madeleine C. Thomson, Tetsuo Nakazawa
- Edition: 1
- Published: October 19, 2018
- Imprint: Elsevier
- No. of pages: 585
- Language: English
- Paperback ISBN: 9780128117149
- eBook ISBN: 9780128117156
AR
Andrew Robertson
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