Sub-seasonal to Seasonal Prediction: The Gap Between Weather and Climate Forecasting

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Download Sub-seasonal to Seasonal Prediction: The Gap Between Weather and Climate Forecasting written by Andrew Robertson, Frederic Vitart in PDF format. This book is under the category Geography and bearing the isbn/isbn13 number 128117141/9780128117149. You may reffer the table below for additional details of the book.

SKU: dbb422937d7f Category: Tag:

Specifications

book-author

Andrew Robertson, Frederic Vitart

publisher

Elsevier

file-type

PDF

pages

550 pages

language

English

asin

B07JQN2ZQ7

isbn10

128117141

isbn13

9780128117149


Book Description

The Gap Between Weather and Climate Forecasting: Sub-seasonal to Seasonal Prediction (PDF) is an ideal reference for practitioners and researchers across the range of disciplines involved in the modeling; science; 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 modelling 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 ebook 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.

 

 

    • Includes a broad set of topics; illustrated with graphic examples; that highlight interdisciplinary linkages

 

    • Contains contributed chapters from leaders and experts in sub-seasonal to seasonal science; forecasting and applications

 

    • Provides a one-stop-shop for academic and applied researchers; graduate students; 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

 

 

Additional information

book-author

Andrew Robertson, Frederic Vitart

publisher

Elsevier

file-type

PDF

pages

550 pages

language

English

asin

B07JQN2ZQ7

isbn10

128117141

isbn13

9780128117149

Table of contents


Table of contents :
Cover……Page 1
SUB-SEASONAL TO
SEASONAL
PREDICTION:
The Gap Between Weather and
Climate Forecasting
……Page 3
Copyright……Page 4
Contributors……Page 5
Preface……Page 9
Acknowledgements……Page 11
Part I: Setting the Scene
……Page 12
1.
Introduction: Why Sub-seasonal to Seasonal Prediction (S2S)?……Page 13
History of Numerical Weather and Climate Forecasting……Page 15
Sub-seasonal to Seasonal Forecasting……Page 18
Improvements in Numerical Weather Forecasting……Page 19
Development of Seamless Prediction……Page 20
Demand From Users for S2S Forecasts……Page 22
Recent National and International Efforts on Sub-seasonal to Seasonal Prediction……Page 24
Structure of This Book……Page 25
Introduction……Page 26
Predictability……Page 28
Scale-Dependent Behavior……Page 30
Coupled Systems……Page 33
The Evolution of NWP Techniques……Page 34
Observing Systems……Page 35
Data Assimilation……Page 37
Modeling……Page 38
Improvements in Forecast Performance……Page 39
Weather Versus Climate Prediction……Page 43
Spatiotemporal Aggregation……Page 44
Removal of Systematic Errors……Page 45
Background……Page 46
Methodology……Page 47
Use of Ensembles……Page 49
Expanding the Forecast Skill Horizon……Page 50
Concluding Remarks: Lessons for S2S Forecasting……Page 53
Acknowledgments……Page 54
Introduction……Page 55
S2S Forecasts……Page 58
Daily Rainfall Characteristics of the Indian Summer Monsoon……Page 59
Sub-seasonal Modulation of Spatial Coherence Over the Whole Tropical Zone……Page 61
Skill and Spatial Coherence of S2S Reforecasts……Page 66
Discussion and Concluding Remarks……Page 69
4.
Identifying Wave Processes Associated With Predictability Across Time Scales: An Empirical Normal Mode Approach……Page 73
Introduction……Page 74
Partitioning Atmospheric Behavior Using Its Conservation Properties……Page 76
Partitioning Variability: Background State and Wave Activity……Page 77
Wave Activity Conservation Laws……Page 82
The Implications of Wave-Activity Conservation for Modes of Variability……Page 85
The ENM Approach to Observed Data and Models and Its Relevance to S2S Dynamics and Predictability……Page 86
ENMs: Bridging Principal Component, Normal Modes, and Conservation Laws……Page 87
ENM in Applications Relevant to Predictability Across Time Scales……Page 91
ENM Application to the Atmospheric S2S Variability……Page 94
Conclusion……Page 97
Acknowledgments……Page 98
Part II: Sources of S2S Predictability
……Page 99
Introduction……Page 100
The Real-Time Multivariate MJO Index……Page 101
Observed MJO Structure……Page 105
The Relationship Between the MJO and Tropical and Extratropical Weather……Page 113
Theories and Mechanisms for MJO Initiation, Maintenance, and Propagation……Page 114
The Representation of the MJO in Weather and Climate Models……Page 116
MJO Prediction……Page 117
Sub-seasonal and Interannual Variations in Forecast Skill……Page 122
Predicting the Impacts of the MJO……Page 123
Acknowledgments……Page 124
6.
Extratropical Sub-seasonal to Seasonal Oscillations and Multiple Regimes: The Dynamical Systems View……Page 125
Introduction and Motivation……Page 126
The Case for Multiple Regimes and Their Classification……Page 127
Rossby Wave Propagation and Interference……Page 130
Variations of Geopotential Height……Page 132
Oscillatory Features in Time and Space……Page 133
Topographic Instability and Hopf Bifurcation……Page 136
Background and Methodological LOM Developments……Page 137
Dynamical Diagnostics and Empirical Prediction on S2S Scales……Page 141
LFV and Multilayer Stochastic Closure: A Simple Illustration……Page 144
Concluding Remarks……Page 146
Acknowledgments……Page 148
Introduction……Page 149
Observed MJO Influences……Page 151
Extratropical Atmospheric Response to Tropical Thermal Forcing……Page 154
Extratropical Influences on Tropical Convection and the MJO……Page 158
Diagnosing Intraseasonal Extratropical Influences on the Tropics……Page 160
Three-Dimensional Instability Theory……Page 164
Summary and Discussion……Page 168
Appendix. Technical Matters Relating to Section 4.2……Page 169
8.
Land Surface Processes Relevant to Sub-seasonal to Seasonal (S2S) Prediction……Page 171
Surface Fluxes……Page 172
Land-Surface States……Page 174
Boundary Layer (BL) Response……Page 175
Origin and Evolution of Land-Surface Models……Page 176
LSMs at Operational Forecast Centers……Page 177
LSM Initialization and Data Assimilation……Page 179
Predictability and Prediction……Page 181
Validation……Page 184
Initialization……Page 185
Unconsidered Elements……Page 186
Coupled Land-Atmosphere Model Development……Page 187
Introduction……Page 188
Uncoupled Integrations……Page 191
Coupled Integrations……Page 193
Mesoscale Ocean-Atmosphere Interaction in the Atmospheric Boundary Layer……Page 194
Local Tropospheric Response……Page 195
Impact on Ocean Circulation……Page 199
Implications for S2S Prediction……Page 202
Summary and Conclusions……Page 204
Acknowledgments……Page 205
10.
The Role of Sea Ice in Sub-seasonal Predictability……Page 206
Introduction……Page 207
Sea Ice Physics……Page 208
Sea Ice Observations……Page 209
Sea Ice in Models and Reanalyses……Page 210
Sea Ice Distribution, Seasonality, and Variability……Page 211
Persistence……Page 213
Other Mechanisms……Page 215
Potential Sea Ice Predictability……Page 218
Sub-seasonal to Seasonal Predictions……Page 221
Impact of Sea Ice on Sub-seasonal Predictability……Page 223
Impacts Outside Polar Regions……Page 224
Concluding Remarks……Page 225
Acknowledgments……Page 226
11.
Sub-seasonal Predictability and the Stratosphere……Page 227
Introduction……Page 228
Stratosphere-Troposphere Coupling in the Tropics……Page 229
How Does the QBO Influence the Tropical Troposphere?……Page 230
Predictability Related to Tropical Stratosphere-Troposphere Coupling……Page 231
Stratosphere-Troposphere Coupling in the Extratropics……Page 232
An Overview of Polar Vortex Variability……Page 233
What Drives Polar Vortex Variability?……Page 234
How Does Stratospheric Polar Vortex Variability Influence Surface Climate?……Page 235
Other Manifestations of Extratropical Stratosphere-Troposphere Coupling……Page 237
How Accurately Can the Polar Stratosphere be Predicted?……Page 238
S2S Extratropical Forecast Skill Associated With Stratosphere-Troposphere Pathways……Page 240
Summary and Outlook……Page 242
Influence of the Tropospheric State and Biases……Page 243
Influence of Different Drivers on Stratosphere-Troposphere Coupling Efficacy……Page 244
How Can We Use Sub-seasonal Prediction Data in New Ways to Study Stratospheric Dynamics and Stratosphere-Troposphere ………Page 245
Part III: S2S Modeling and Forecasting
……Page 246
Introduction……Page 247
Requirements and Constraints of the Operational Sub-seasonal Forecast……Page 249
Effect of Ensemble Size……Page 250
Effect of LAF Ensemble……Page 254
Real-Time Forecast Configuration……Page 257
Reforecast Configuration……Page 259
Acknowledgments……Page 261
Global Sub-seasonal and Seasonal Prediction Is an Initial Value Problem……Page 262
Ensembles Provide More Complete and Valuable Information Than Single States……Page 264
Reliability and Accuracy of an Ensemble……Page 265
A Brief Introduction to Data Assimilation……Page 269
A Brief Introduction to Model Uncertainty Simulation……Page 275
The TIGGE Global, Medium-Range Operational Ensembles……Page 278
BMRC-ENS……Page 280
The CPTEC-ENS……Page 281
The ECMWF-ENS……Page 282
The JMA-ENS……Page 285
The KMA-ENS……Page 286
The MSC-ENS……Page 287
The NCEP-ENS……Page 288
The UKMO-ENS……Page 289
The S2S Global, Monthly Ensembles……Page 290
The BMRC Monthly Ensemble……Page 291
The CMA-BCC Monthly Ensemble……Page 293
The HMRC Monthly Ensemble……Page 294
The KMA Monthly Ensemble……Page 295
The UKMO Monthly Ensemble……Page 296
Does an Ensemble Performance Depend on its Configuration?……Page 297
Ensembles: Considerations About Their Future……Page 301
Summary and Key Lessons……Page 304
Introduction……Page 305
Global CRM……Page 307
Superparameterized GCM……Page 310
GCM With Full Representation of Cloud Microphysics and Scale-Adaptive Convection……Page 313
Summary and Conclusion……Page 318
Acknowledgments……Page 319
Introduction……Page 320
Statistical Methods for Forecast Recalibration……Page 323
Model Output Statistics……Page 324
Nonhomogeneous Gaussian Regression……Page 327
Further Remarks on Recalibration……Page 329
Forecast Combination……Page 330
Hierarchical Linear Regression……Page 331
Why Is It So Hard to Beat the Recalibrated Multimodel Mean?……Page 334
Acknowledgments……Page 335
16.
Forecast Verification for S2S Timescales……Page 336
Introduction……Page 337
Nature of Available Observations……Page 339
Observational References……Page 340
Review of the Most Common Verification Measures……Page 343
Metrics for Continuous Deterministic Forecasts……Page 344
Verification Methods for Categorical Deterministic Forecasts……Page 345
Verification Measures for Probability Forecasts……Page 348
Spatial Methods……Page 352
Deterministic S2S Forecast Verification Practices……Page 353
Probabilistic S2S Forecast Verification Practices……Page 354
Madden and Julian Oscillation (MJO) Forecast Verification……Page 355
Summary, Challenges, and Recommendations in S2S Verification……Page 359
Part IV: S2S Applications
……Page 361
17.
Sub-seasonal to Seasonal Prediction of Weather Extremes……Page 362
Introduction……Page 363
Heat Wave/Cold Spell Prediction Over Europe……Page 364
Heat-Wave Prediction in Australia……Page 365
Drought Prediction……Page 367
Prediction of Mesoscale Events……Page 370
Tropical Cyclones……Page 371
Heavy Precipitation/Flooding……Page 372
Tornadoes/Thunderstorms……Page 374
Windstorms……Page 379
Display and Verification of Sub-seasonal Forecasts of Extreme Events……Page 381
Conclusions……Page 383
Introduction……Page 384
Why Sub-seasonal?……Page 385
Case Study: Peru El Niño……Page 386
Forecast Thresholds……Page 387
Reflections on the Use of S2S Forecasts……Page 391
Conclusions……Page 392
19.
Communication and Dissemination of Forecasts and Engaging User Communities……Page 396
Availability to the Public……Page 397
Improving S2S Public Service Through Community Engagement: Example From the Australian Bureau of Meteorology……Page 400
Current S2S Research and Applications for Weather- and Climate-Sensitive Sectors……Page 403
Agricultural Sector……Page 405
Energy and Water Management Sectors……Page 407
Natural Hazards and Disaster Risk Reduction (DRR)……Page 409
Health Sector……Page 412
Guiding Principles for Improved Communication Practices……Page 413
Summary and Recommendations for Future Research……Page 415
20.
Seamless Prediction of Monsoon Onset and Active/Break Phases……Page 417
Introduction……Page 418
Extended-Range Forecast of Monsoon Sub-seasonal Variability……Page 420
Criteria for Monsoon Onset Over Kerala (MOK)……Page 424
Active/Break Spells Associated With MISOs……Page 425
Phase-Dependent Skill of Large-Scale MISO Indices……Page 427
MISO Forecast Ensemble Spread Versus RMSE……Page 428
The Forecast Skill of Active and Break Spells for Meteorological Subdivisions……Page 429
Feasibility of MME Prediction to Further Smaller Spatial Scales……Page 430
Application of MME to the Forecast of Extreme Events: An Example……Page 432
Future Directions for Spatially Seamless Sub-seasonal Prediction……Page 433
Acknowledgments……Page 434
21.
Lessons Learned in 25 Years of Informing Sectoral Decisions With Probabilistic Climate Forecasts……Page 435
Introduction……Page 436
Characterization of Uncertainties and Associated Exposure……Page 437
Summary……Page 438
Embedding a Probabilistic Climate Forecast Into Decisions……Page 439
Assessing Changes in Risk and Options……Page 440
Involvement With Stakeholders……Page 441
The Management of the Interconnected Electric System……Page 442
The Ministry of Agriculture and Fisheries and Three Recent Droughts……Page 446
Final Remarks……Page 449
22.
Predicting Climate Impacts on Health at Sub-seasonal to Seasonal Timescales……Page 450
Climate Impacts on Health……Page 451
Toward S2S Predictions in Health……Page 453
Malaria (Tompkins and Thomson)……Page 454
Dengue (Lowe)……Page 457
Meningitis (Martiny, Roucou, and Nakazawa)……Page 460
Heat Waves (Nissan and Lowe)……Page 464
Data Access and Usage……Page 467
Operationalization of Climate Information……Page 468
Interaction Through Workshops……Page 470
Outlook……Page 471
Acknowledgments……Page 472
23.
Epilogue……Page 473
References……Page 476
C……Page 550
E……Page 551
F……Page 552
L……Page 553
M……Page 555
N……Page 556
P……Page 557
S……Page 558
T……Page 561
W……Page 562
Back Cover……Page 563

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