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  • 1
    Call number: PIK N 456-18-91895 ; AWI A5-18-91895
    Type of Medium: Monograph available for loan
    Pages: xv, 569 Seiten , Illustrationen, Diagramme, Karten
    ISBN: 9780128117149
    Language: English
    Note: Contents: Contributors. - Preface. - Acknowledgements. - PART I SETTING THE SCENE. - 1. Introduction: Why Sub-seasonal to Seasonal Prediction (S2S)? / Frédéric Vitart, Andrew W. Robertson. - 1 History of Numerical Weather and Climate Forecasting. - 2 Sub-seasonal to Seasonal Forecasting. - 3 Recent National and International Efforts on Sub-seasonal to Seasonal Prediction. - 4 Structure of This Book. - 2. Weather Forecasting: What Sets the Forecast Skill Horizon? / Zoltan Toth, Roberto Buizza. - 1 Introduction. - 2 The Basics of Numerical Weather Prediction. - 3 The Evolution of NWP Technique. - 4 Enhancement of Predictable signals. - 5 Ensemble Techniques: Brief Introduction. - 6 Expanding the forecast skill Horizon. - 7 Concludmg Remarks: Lessons for S2S Forecasting. - Acknowledgements. - 3. Weather Within Climate: Sub-seasonal Predictability of Tropical Daily Rainfall Characteristics / Vincent Moron, Andrew W. Robertson, Lei Wang. - 1 Introduction. - 2 Data and Methods. - 3 Results. - 4 Discussion and Concluding Remarks. - 4. Identifying Wave Processes Associated With Predictability Across Time Scales: An Empirical Normal Mode Approach / Gilbert Brunet, John Methven. - 1 Introduction. - 2 Partitioning Atmospheric Behavior Using Its Conservation Properties. - 3 The ENM Approach to Observed Data and Models and Its Relevance to S2S Dynamics and Predictability. - 4 Conclusion. - Acknowledgments. - PART II SOURCES OF S2S PREDICTABILITY. - 5. The Madden-Julian Oscillation / Steven J. Woolnough. - 1 Introduction. - 2 The Real-Time Multivariate MJO Index. - 3 Observed MJO Structure. - 4 The Relationship Between the MJO and Tropical and Extratropical Weather. - 5 Theories and Mechanisms for MJO Initiation, Maintenance, and Propagation. - 6 The Representation of the MJO in Weather and Climate Models. - 7 MJO Prediction. - 8 Future Priorities for MJO Research for S2S Prediction. - Acknowledgments. - 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. - 2 Multiple Midlatitude Regimes and Low-Frequency Oscillations. - 3 Extratropical Oscillations in the S2S Band. - 4 Low-Order, Data-Driven Modeling, Dynamical Analysis, and Prediction. - 5 Concluding Remarks. - Acknowledgments. - 7. Tropical-Extratropical Interactions and Teleconnections / Hai Lin, Jorgen Frederiksen, David Straus, Christiana Stan. - 1 Introduction. - 2 Tropical Influence on the Extratropical Atmosphere. - 3 Extratropical Influence on the Tropics. - 4 Tropical-Extratropical, Two-Way Interactions. - 5 Summary and Discussion. - Appendix. Technical Matters Relating to Section 4.2. - 8. Land Surface Processes Relevant to Sub-seasonal to Seasonal (S2S) Prediction / Paul A. Dirmeyer, Pierre Gentine, Michael B. Ek, Gianpaolo Balsamo. - 1 Introduction. - 2 Process of Land-Atmosphere Interaction. - 3 A Brief History of Land-Surface Models. - 4 Predictability and Prediction. - 5 Improving Land-Driven Prediction. - 9. Midlatitude Mesoscale Ocean-Atmosphere Interaction and Its Relevance to S2S Prediction / R. Saravanan, P. Chang. - 1 Introduction. - 2 Data and Models. - 3 Mesoscale Ocean-Atmosphere Interaction in the Atmospheric Boundary Layer. - 4 Local Tropospheric Response. - 5 Remote Tropospheric Response. - 6 Impact on Ocean Circulation. - 7 Implications for S2S Prediction. - 8 Summary and Conclusions. - Acknowledgments. - 10. The Role of Sea Ice in Sub-seasonal Predictability / Matthieu Chevallier, François Massonnet, Helge Goessling, Virginie Guémas, Thomas Jung. - 1 Introduction. - 2 Sea Ice in the Coupled Atmosphere-Ocean System. - 3 Sea Ice Distribution, Seasonality, and Variability. - 4 Sources of Sea Ice Predictability at the Sub-seasonal to Seasonal Timescale. - 5 Sea Ice Sub-seasonal to Seasonal - Predictability and Prediction Skill in Models. - 6 Impact of Sea Ice on Sub-seasonal Predictability. - 7 Concluding Remarks. - Acknowledgments. - 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. - 2 Stratosphere-Troposphere Coup ling in the Tropics. - 3 Stratosphere-Troposphere Coupling in the Extratropics. - 4 Predictability Related to Extratropical Stratosphere-Troposphere Coupling. - 5 Summary and Outlook. - PART Ill S2S MODELING AND FORECASTING. - 12. Forecast System Design, Configuration, and Complexity / Yuhei Takaya. - 1 Introduction. - 2 Requirements and Constraints of the Operational Sub-seasonal Forecast. - 3 Effect of Ensemble Size and Lagged Ensemble. - 4 Real-Time Forecast Configuration. - 5 Reforecast Configuration. - 6 Summary and Concluding Remarks. - Acknowledgments. - 13. Ensemble Generation: The TIGGE and S2S Ensembles / Roberto Buizza. - 1 Global Sub-seasonal and Seasonal Prediction Is an Initial Value Problem. - 2 Ensembles Provide More Complete and Valuable Information Than Single States. - 3 A Brief Introduction to Data Assimilation. - 4 A Brief Introduction to Model Uncertainty Simulation. - 5 An Overview of Operational, Global, Sub-seasonal, and Seasonal Ensembles, and Their Initialization and Generation Methods. - 6 Ensembles: Considerations About Their Future. - 7 Summary and Key Lessons. - 14. GCMs With Full Representation of Cloud Microphysics and Their MJO Simulations / In-Sik Kang, Min-Seop Ahn, Hiroaki Miura, Aneesh Subramanian. - 1 Introduction. - 2 Global CRM. - 3 Superparameterized GCM. - 4 GCM With Full Representation of Cloud Microphysics and Scale-Adaptive Convection. - 5 Summary and Conclusion. - Acknowledgments. - 15. Forecast Recalibration and Multimodel Combination / Stefan Siegert, David B. Stephenson. - 1 Introduction. - 2 Statistical Methods for Forecast Recalibration. - 3 Regression Methods. - 4 Forecast Combination. - 5 Concluding Remarks. - Acknowledgments. - 16. Forecast Verification for S2S Timescales / Caio A. S. Coelho, Barbara Brown, Laurie Wilson, Marion Mittermaier, Barbara Casati. - 1 Introduction. - 2 Factors Affecting the Design of Verification Studies. - 3 Observational References. - 4 Review of the Most Common Verification Measures. - 5 Types of S2S Forecasts and Current Verification Practices. - 6 Summary, Challenges, and Recommendations in S2S Verification. - PART IV S2S APPLICATIONS. - 17. Sub-seasonal to Seasonal Prediction of Weather Extremes / Frédérik Vitart, Christopher Cunningham, Michael Deflorio, Emanuel Dutra, Laura Ferranti, Brian Golding, Debra Hudson, Charles Jones, Christophe Lavaysse, Joanne Robbins, Michael K. Tippett. - 1 Introduction. - 2 Prediction of Large-Scale, Long-Lasting Extreme Events. - 3 Prediction of Mesoscale Events. - 4 Display and Verification of Sub-seasonal Forecasts of Extreme Events. - 5 Conclusions. - 18. Pilot Experiences in Using Seamless Forecasts for Early Action: The "Ready-Set-Go!" Approach in the Red Cross / Juan Bazo, Roop Singh, Mathieu Destrooper, Erin Coughlan de Perez. - 1 Introduction. - 2 Why Sub-seasonal?. - 3 Case Study: Peru El Niño. - 4 Reflections on the Use of S2S Forecasts. - 5 Conclusions. - 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. - 2 Sector-Specific Methods and Practices in S2S Forecast Communication, Dissemination, and Engagement. - 3 Guiding principles for improved communication Practices. - 4 Summary and Recommendations for Future Research. - 20. Seamless Prediction of Monsoon Onset and Active/Break Phases / A.
    Location: A 18 - must be ordered
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  • 2
    Publication Date: 2017-02-01
    Print ISSN: 0003-0007
    Electronic ISSN: 1520-0477
    Topics: Geography , Physics
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  • 3
    Publication Date: 2018-02-01
    Description: Atmospheric rivers (ARs) are global phenomena that transport water vapor horizontally and are associated with hydrological extremes. In this study, the Atmospheric River Skill (ATRISK) algorithm is introduced, which quantifies AR prediction skill in an object-based framework using Subseasonal to Seasonal (S2S) Project global hindcast data from the European Centre for Medium-Range Weather Forecasts (ECMWF) model. The dependence of AR forecast skill is globally characterized by season, lead time, and distance between observed and forecasted ARs. Mean values of daily AR prediction skill saturate around 7–10 days, and seasonal variations are highest over the Northern Hemispheric ocean basins, where AR prediction skill increases by 15%–20% at a 7-day lead during boreal winter relative to boreal summer. AR hit and false alarm rates are explicitly considered using relative operating characteristic (ROC) curves. This analysis reveals that AR forecast utility increases at 10-day lead over the North Pacific/western U.S. region during positive El Niño–Southern Oscillation (ENSO) conditions and at 7- and 10-day leads over the North Atlantic/U.K. region during negative Arctic Oscillation (AO) conditions and decreases at a 10-day lead over the North Pacific/western U.S. region during negative Pacific–North America (PNA) teleconnection conditions. Exceptionally large increases in AR forecast utility are found over the North Pacific/western United States at a 10-day lead during El Niño + positive PNA conditions and over the North Atlantic/United Kingdom at a 7-day lead during La Niña + negative PNA conditions. These results represent the first global assessment of AR prediction skill and highlight climate variability conditions that modulate regional AR forecast skill.
    Print ISSN: 1525-755X
    Electronic ISSN: 1525-7541
    Topics: Geography , Geosciences , Physics
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  • 4
    Publication Date: 2018-07-03
    Description: Subseasonal probabilistic prediction of tropical cyclone (TC) genesis is investigated here using models from the Seasonal to Subseasonal (S2S) Prediction dataset. Forecasts are produced for basin-wide TC occurrence at weekly temporal resolution. Forecast skill is measured using the Brier skill score relative to a seasonal climatology that varies monthly through the TC season. Skill depends on models’ characteristics, lead time, and ensemble prediction design. Most models show skill for week 1 (days 1–7), the period when initialization is important. Among the six S2S models examined here, the European Centre for Medium-Range Weather Forecasts (ECMWF) model has the best performance, with skill in the Atlantic, western North Pacific, eastern North Pacific, and South Pacific at week 2. Similarly, the Australian Bureau of Meteorology (BoM) model is skillful in the western North Pacific, South Pacific, and across northern Australia at week 2. The Madden–Julian oscillation (MJO) modulates observed TC genesis, and there is a relationship, across models and lead times, between models’ skill scores and their ability to accurately represent the MJO and the MJO–TC relation. Additionally, a model’s TC climatology also influences its performance in subseasonal prediction. The dependence of the skill score on the simulated climatology, MJO, and MJO–TC relationship, however, varies from one basin to another. Skill scores increase with the ensemble size, as found in previous weather and seasonal prediction studies.
    Print ISSN: 0882-8156
    Electronic ISSN: 1520-0434
    Topics: Geography , Physics
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  • 5
    Publication Date: 2016-02-01
    Description: Seasonal forecast skill of the basinwide and regional tropical cyclone (TC) activity in an experimental coupled prediction system based on the ECMWF System 4 is assessed. As part of a collaboration between the Center for Ocean–Land–Atmosphere Studies (COLA) and the ECMWF called Project Minerva, the system is integrated at the atmospheric horizontal spectral resolutions of T319, T639, and T1279. Seven-month hindcasts starting from 1 May for the years 1980–2011 are produced at all three resolutions with at least 15 ensemble members. The Minerva system demonstrates statistically significant skill for retrospective forecasts of TC frequency and accumulated cyclone energy (ACE) in the North Atlantic (NA), eastern North Pacific (EP), and western North Pacific. While the highest scores overall are achieved in the North Pacific, the skill in the NA appears to be limited by an overly strong influence of the tropical Pacific variability. Higher model resolution improves skill scores for the ACE and, to a lesser extent, the TC frequency, even though the influence of large-scale climate variations on these TC activity measures is largely independent of resolution changes. The biggest gain occurs in transition from T319 to T639. Significant skill in regional TC forecasts is achieved over broad areas of the Northern Hemisphere. The highest-resolution hindcasts exhibit additional locations with skill in the NA and EP, including land-adjacent areas. The feasibility of regional intensity forecasts is assessed. In the presence of the coupled model biases, the benefits of high resolution for seasonal TC forecasting may be underestimated.
    Print ISSN: 0894-8755
    Electronic ISSN: 1520-0442
    Topics: Geography , Geosciences , Physics
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  • 6
    Publication Date: 2016-05-13
    Description: The characteristics of the MJO propagation across the Maritime Continent are investigated using a 20-yr reforecast dataset from the ECMWF ensemble prediction system. Analysis of the MJO events initialized over the Indian Ocean (phase 2) shows that the initial MJO amplitude and prediction skill relationship is not linear, particularly when the predictions start in moderate (between strong and weak) MJO amplitude category. To examine the key factors that determine the prediction skill, reforecasts in the moderate category are grouped into high- and low-skill events, and the differences in their ocean–atmospheric conditions as well as the physical processes during reforecast period are examined. The initial distribution of OLR anomalies in high-skill events shows a clear dipole pattern of convection with an enhanced convective anomalies over the Indian Ocean and strongly suppressed convective anomalies in the western Pacific Ocean. This dipole mode may support the MJO propagation across the Maritime Continent via the Rossby wave response and associated meridional moisture advection. Prominent ocean–atmosphere coupled processes are also simulated during the propagation of high-skill events. However, in low-skill events, the convective signal over the western Pacific is almost absent and less organized, and the ocean–atmosphere coupled processes are not simulated correctly. It is found that in both high- and low-skill events, the amplitude of the convective anomaly decreases significantly after about day 15, possibly due to the systematic mean model bias. A strong wet bias in the vicinity of the Maritime Continent, a cold SST bias in the equatorial Pacific, and associated circulation biases make the west Pacific area unfavorable for MJO propagation, thus limiting its prediction skill.
    Print ISSN: 0894-8755
    Electronic ISSN: 1520-0442
    Topics: Geography , Geosciences , Physics
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  • 7
    Publication Date: 2016-05-20
    Description: The ECMWF twentieth century reanalysis (ERA-20C; 1900–2010) assimilates surface pressure and marine wind observations. The reanalysis is single-member, and the background errors are spatiotemporally varying, derived from an ensemble. The atmospheric general circulation model uses the same configuration as the control member of the ERA-20CM ensemble, forced by observationally based analyses of sea surface temperature, sea ice cover, atmospheric composition changes, and solar forcing. The resulting climate trend estimations resemble ERA-20CM for temperature and the water cycle. The ERA-20C water cycle features stable precipitation minus evaporation global averages and no spurious jumps or trends. The assimilation of observations adds realism on synoptic time scales as compared to ERA-20CM in regions that are sufficiently well observed. Comparing to nighttime ship observations, ERA-20C air temperatures are 1 K colder. Generally, the synoptic quality of the product and the agreement in terms of climate indices with other products improve with the availability of observations. The MJO mean amplitude in ERA-20C is larger than in 20CR version 2c throughout the century, and in agreement with other reanalyses such as JRA-55. A novelty in ERA-20C is the availability of observation feedback information. As shown, this information can help assess the product’s quality on selected time scales and regions.
    Print ISSN: 0894-8755
    Electronic ISSN: 1520-0442
    Topics: Geography , Geosciences , Physics
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  • 8
    Publication Date: 2018-12-01
    Print ISSN: 0894-8755
    Electronic ISSN: 1520-0442
    Topics: Geography , Geosciences , Physics
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  • 9
    Publication Date: 2018-09-28
    Description: The fact that aerosols are important players in Earth’s radiation balance is well accepted by the scientific community. Several studies have shown the importance of characterizing aerosols in order to constrain surface radiative fluxes and temperature in climate runs. In numerical weather prediction, however, there has not been definite proof that interactive aerosol schemes are needed to improve the forecast. Climatologies are instead used that allow for computational efficiency and reasonable accuracy. At the monthly to subseasonal range, it is still worth investigating whether aerosol variability could afford some predictability, considering that it is likely that persisting aerosol biases might manifest themselves more over time scales of weeks to months and create a nonnegligible forcing. This paper explores this hypothesis using the ECMWF’s Ensemble Prediction System for subseasonal prediction with interactive prognostic aerosols. Four experiments are conducted with the aim of comparing the monthly prediction by the default system, which uses aerosol climatologies, with the prediction using radiatively interactive aerosols. Only the direct aerosol effect is considered. Twelve years of reforecasts with 50 ensemble members are analyzed on the monthly scale. Results indicate that the interactive aerosols have the capability of improving the subseasonal prediction at the monthly scales for the spring/summer season. It is hypothesized that this is due to the aerosol variability connected to the different phases of the Madden–Julian oscillation, particularly that of dust and carbonaceous aerosols. The degree of improvement depends crucially on the aerosol initialization. More work is required to fully assess the potential of interactive aerosols to increase predictability at the subseasonal scales.
    Print ISSN: 0027-0644
    Electronic ISSN: 1520-0493
    Topics: Geography , Geosciences , Physics
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  • 10
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