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Sub-seasonal to Seasonal Prediction: The Gap Between Weather and Climate Forecasting [Mīkstie vāki]

Edited by (Senior Research Scientist, European Centre for Medium-range Weather Forecasts (ECMWF), UK), Edited by (Senior Research Scientist, International Research Institute for Climate and Society, Earth Institute, Columbia University, NY, USA)
  • Formāts: Paperback / softback, 585 pages, height x width: 235x191 mm, weight: 1180 g
  • Izdošanas datums: 24-Oct-2018
  • Izdevniecība: Elsevier Science Publishing Co Inc
  • ISBN-10: 0128117141
  • ISBN-13: 9780128117149
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Sub-seasonal to Seasonal Prediction: The Gap Between Weather and Climate ForecastingPalielināt
  • Formāts: Paperback / softback, 585 pages, height x width: 235x191 mm, weight: 1180 g
  • Izdošanas datums: 24-Oct-2018
  • Izdevniecība: Elsevier Science Publishing Co Inc
  • ISBN-10: 0128117141
  • ISBN-13: 9780128117149
Citas grāmatas par šo tēmu:
Permanent link: https://www.kriso.lv/db/9780128117149.html
Keywords:

The 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
Contributors ix
Preface xiii
Acknowledgements xv
PART I SETTING THE SCENE
1 Introduction: Why Sub-seasonal to Seasonal Prediction (S2S)?
Frederic Vitart
Andrew W. Robertson
1 History of Numerical Weather and Climate Forecasting
5(3)
2 Sub-seasonal to Seasonal Forecasting
8(6)
3 Recent National and International Efforts on Sub-seasonal to Seasonal Prediction
14(1)
4 Structure of This Book
15(2)
2 Weather Forecasting: What Sets the Forecast Skill Horizon?
Zoltan Toth
Roberto Buizza
1 Introduction
17(2)
2 The Basics of Numerical Weather Prediction
19(6)
3 The Evolution of NWP Techniques
25(10)
4 Enhancement of Predictable Signals
35(2)
5 Ensemble Techniques: Brief Introduction
37(4)
6 Expanding the Forecast Skill Horizon
41(3)
7 Concluding Remarks: Lessons for S2S Forecasting
44(1)
Acknowledgments
45(2)
3 Weather Within Climate: Sub-seasonal Predictability of Tropical Daily Rainfall Characteristics
Vincent Moron
Andrew W. Robertson
Lei Wang
1 Introduction
47(3)
2 Data and Methods
50(1)
3 Results
51(10)
4 Discussion and Concluding Remarks
61(5)
4 Identifying Wave Processes Associated With Predictability Across Time Scales: An Empirical Normal Mode Approach
Gilbert Brunet
John Methven
1 Introduction
66(2)
2 Partitioning Atmospheric Behavior Using its Conservation Properties
68(10)
3 The ENM Approach to Observed Data and Models and its Relevance to S2S Dynamics and Predictability
78(11)
4 Conclusion
89(1)
Acknowledgments
90(3)
PART II SOURCES OF S2S PREDICTABILITY
5 The Madden-Julian Oscillation
Steven J. Woolnough
1 Introduction
93(1)
2 The Real-Time Multivariate MJO Index
94(4)
3 Observed MJO Structure
98(8)
4 The Relationship Between the MJO and Tropical and Extratropical Weather
106(1)
5 Theories and Mechanisms for MJO Initiation, Maintenance, and Propagation
107(2)
6 The Representation of the MJO in Weather and Climate Models
109(1)
7 MJO Prediction
110(6)
8 Future Priorities for MJO Research for S2S Prediction
116(1)
Acknowledgments
117(3)
6 Extratropical Sub-seasonal to Seasonal Oscillations and Multiple Regimes: The Dynamical Systems View
Michael Ghil
Andreas Groth
Dmitri Kondrashov
Andrew W. Robertson
1 Introduction and Motivation
120(1)
2 Multiple Midlatitude Regimes and Low-Frequency Oscillations
121(5)
3 Extratropical Oscillations in the S2S Band
126(5)
4 Low-Order, Data-Driven Modeling, Dynamical Analysis, and Prediction
131(9)
5 Concluding Remarks
140(2)
Acknowledgments
142(1)
7 Tropical-Extratropical Interactions and Teleconnections
Hai Lin
Jorgen Frederiksen
David Straus
Cristiana Stan
1 Introduction
143(2)
2 Tropical Influence on the Extratropical Atmosphere
145(7)
3 Extratropical Influence on the Tropics
152(6)
4 Tropical-Extratropical, Two-Way Interactions
158(4)
5 Summary and Discussion
162(1)
Appendix. Technical Matters Relating to Section 4-2
163(3)
8 Land Surface Processes Relevant to Sub-seasonal to Seasonal (S2S) Prediction
Paul A. Dirmeyer
Pierre Genttne
Michael B. Ek
Gianpaolo Balsamo
1 Introduction
166(1)
2 Process of Land-Atmosphere Interaction
166(4)
3 A Brief History of Land-Surface Models
170(5)
4 Predictability and Prediction
175(3)
5 Improving Land-Driven Prediction
178(5)
9 Midlatitude Mesoscale Ocean-Atmosphere Interaction and its Relevance to S2S Prediction
R. Saravanan
P. Chang
1 Introduction
183(3)
2 Data and Models
186(3)
3 Mesoscale Ocean-Atmosphere Interaction in the Atmospheric Boundary Layer
189(1)
4 Local Tropospheric Response
190(4)
5 Remote Tropospheric Response
194(1)
6 Impact on Ocean Circulation
194(3)
7 Implications for S2S Prediction
197(2)
8 Summary and Conclusions
199(1)
Acknowledgments
200(2)
10 The Role of Sea Ice in Sub-seasonal Predictability
Matthieu Chevallier
Franqois Massonnet
Helge Goessling
Virginie Guemas
Thomas Jung
1 Introduction
202(1)
2 Sea Ice in the Coupled Atmosphere-Ocean System
203(3)
3 Sea Ice Distribution, Seasonality, and Variability
206(2)
4 Sources of Sea Ice Predictability at the Sub-seasonal to Seasonal Timescale
208(5)
5 Sea Ice Sub-seasonal to Seasonal Predictability and Prediction Skill in Models
213(5)
6 Impact of Sea Ice on Sub-seasonal Predictability
218(2)
7 Concluding Remarks
220(1)
Acknowledgments
221(3)
11 Sub-seasonal Predictability and the Stratosphere
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
1 Introduction
224(1)
2 Stratosphere-Troposphere Coupling in the Tropics
225(3)
3 Stratosphere-Troposphere Coupling in the Extratropics
228(6)
4 Predictability Related to Extratropical Stratosphere-Troposphere Coupling
234(4)
5 Summary and Outlook
238(7)
PART III S2S MODELING AND FORECASTING
12 Forecast System Design, Configuration, and Complexity
Yuhei Takaya
1 Introduction
245(2)
2 Requirements and Constraints of the Operational Sub-seasonal Forecast
247(1)
3 Effect of Ensemble Size and Lagged Ensemble
248(7)
4 Real-Time Forecast Configuration
255(2)
5 Reforecast Configuration
257(2)
6 Summary and Concluding Remarks
259(1)
Acknowledgments
259(2)
13 Ensemble Generation: The TIGGE and S2S Ensembles
Roberto Buizza
1 Global Sub-seasonal and Seasonal Prediction is an Initial Value Problem
261(2)
2 Ensembles Provide More Complete and Valuable Information Than Single States
263(5)
3 A Brief Introduction to Data Assimilation
268(6)
4 A Brief Introduction to Model Uncertainty Simulation
274(3)
5 An Overview of Operational, Global, Sub-seasonal, and Seasonal Ensembles, and Their Initialization and Generation Methods
277(23)
6 Ensembles: Considerations About Their Future
300(3)
7 Summary and Key Lessons
303(2)
14 GCMs With Full Representation of Cloud Microphysics and Their MJO Simulations
In-Sik Kang
Min-Seop Ahn
Hiroaki Miura
Aneesh Subramanian
1 Introduction
305(2)
2 Global CRM
307(3)
3 Superparameterized GCM
310(3)
4 GCM With Full Representation of Cloud Microphysics and Scale-Adaptive Convection
313(5)
5 Summary and Conclusion
318(1)
Acknowledgments
319(2)
15 Forecast Recalibration and Multimodel Combination
Stefan Siegert
David B. Stephenson
1 Introduction
321(3)
2 Statistical Methods for Forecast Recalibration
324(1)
3 Regression Methods
325(6)
4 Forecast Combination
331(5)
5 Concluding Remarks
336(1)
Acknowledgments
336(2)
16 Forecast Verification for S2S Timescales
Caio A.S. Coelho
Barbara Brown
Laurie Wilson
Marion Mittermaier
Barbara Casati
1 Introduction
338(2)
2 Factors Affecting the Design of Verification Studies
340(1)
3 Observational References
341(3)
4 Review of the Most Common Verification Measures
344(10)
5 Types of S2S Forecasts and Current Verification Practices
354(6)
6 Summary, Challenges, and Recommendations in S2S Verification
360(6)
PART IV S2S APPLICATIONS
17 Sub-seasonal to Seasonal Prediction of Weather Extremes
Frederic Vitart
Christopher Cunningham
Michael Deflorio
Emanuel Dutra
Laura Ferranti
Brian Golding
Debra Hudson
Charles Jones
Christophe Lavaysse
Joanne Robbins
Michael K. Tippett
1 Introduction
366(1)
2 Prediction of Large-Scale, Long-Lasting Extreme Events
367(6)
3 Prediction of Mesoscale Events
373(11)
4 Display and Verification of Sub-seasonal Forecasts of Extreme Events
384(2)
5 Conclusions
386(1)
18 Pilot Experiences in Using Seamless Forecasts for Early Action: The "Ready-Set-Go!" Approach in the Red Cross
Juan Bazo
Roop Singh
Mathieu Destrcoper
Erin Coughlan De Perez
1 Introduction
387(1)
2 Why Sub-seasonal?
388(1)
3 Case Study: Peru El Nino
389(5)
4 Reflections on the Use of S2S Forecasts
394(1)
5 Conclusions
395(5)
19 Communication and Dissemination of Forecasts and Engaging User Communities
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
1 Introduction
400(1)
2 Sector-Specific Methods and Practices in S2S Forecast Communication, Dissemination, and Engagement
400(16)
3 Guiding Principles for Improved Communication Practices
416(2)
4 Summary and Recommendations for Future Research
418(4)
20 Seamless Prediction of Monsoon Onset and Active/Break Phases
A.K. Sahai
Rajib Chattopadhyay
Susmitha Joseph
Phani M. Krishna
D.R. Pattanaik
S. Abhilash
1 Introduction
422(2)
2 Extended-Range Forecast of Monsoon Sub-seasonal Variability
424(4)
3 Monsoon Onset and Identification of Active/Break Spells
428(3)
4 Demonstration of Seamless Sub-seasonal Prediction
431(6)
5 Conclusions
437(1)
Acknowledgments
438(2)
21 Lessons Learned in 25 Years of Informing Sectoral Decisions With Probabilistic Climate Forecasts
Rafael Terra
Walter E. Baethgen
1 Introduction
440(1)
2 Learning and Understanding the Status Quo
441(2)
3 Embedding a Probabilistic Climate Forecast Into Decisions
443(3)
4 Examples
446(7)
5 Final Remarks
453(3)
22 Predicting Climate Impacts on Health at Sub-seasonal to Seasonal Timescales
Adrian M. Tompkins
Rachel Lowe
Hannah Nissan
Nadege Martiny
Pascal Roucou
Madeleine C. Thomson
Tetsuo Nakazawa
1 Introduction
456(3)
2 Case Studies
459(13)
3 Operationalization: Challenges and Opportunities
472(4)
4 Outlook
476(1)
Acknowledgments
477(6)
23 Epilogue
Andrew W. Robertson
Frederic Vitart
References 483(74)
Index 557
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.