Sub-seasonal to Seasonal Prediction : The Gap between Weather and Climate Forecasting （2ND）

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Sub-seasonal to Seasonal Prediction : The Gap between Weather and Climate Forecasting （2ND）

Robertson, Andrew (EDT)/ Vitart, Frederic (EDT)

ウェブストア価格 ¥27,941（本体¥25,401）
Elsevier - Health Sciences Division（2025/10発売）
外貨定価 US$ 135.00
ポイント 254pt

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製本 Paperback:紙装版/ペーパーバック版／ページ数 600 p.
言語 ENG
商品コード 9780443315381

Full Description

Sub-seasonal 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.

Part I: Setting the scene
1. Introduction: Why S2S?
2. Weather forecasting: What sets the forecast horizon?
3. Weather within Climate: Sub-seasonal predictability of tropical daily rainfall characteristics

Part II: Sources of S2S Predictability
4. The Madden-Julian Oscillation
5. Extratropical sub-seasonal-to-seasonal oscillations and multiple regimes: The dynamical systems view
6. Tropical-Extratropical Interactions and Teleconnections
7. Land surface processes relevant to S2S prediction
8. Role of ocean in sub-seasonal predictability
9. The role of sea ice in sub-seasonal predictability
10. Sub-seasonal Predictability and the Stratosphere

Part III: S2S Modeling and Forecasting
11. Forecast system design, configuration, complexity
12. Ensemble generation: the TIGGE and S2S ensembles
13. Forecast recalibration and multi-model combination
14. Forecast verification for S2S time scales
15. Machine learning S2S prediction

Part IV: S2S Applications
16. Sub-seasonal to Seasonal Prediction of Weather Extremes
17. Communication and dissemination of forecasts and engaging user communities
18. Seamless prediction of monsoon onset and active/break phases
19. Predicting climate impacts on health at sub-seasonal to seasonal timescales
20. Co-produced S2S Climate Services in Africa
21. S2S for Energy
22. Marine weather prediction on S2S timescales
23. Epilogue