Journal ArticleDOI
The North American multimodel ensemble: Phase-1 seasonal-to-interannual prediction; phase-2 toward developing intraseasonal prediction
Ben P. Kirtman,Dughong Min,Johnna M. Infanti,James L. Kinter,D. A. Paolino,Qin Zhang,Huug van den Dool,Suranjana Saha,Malaquías Peña Mendez,Emily Becker,Peitao Peng,Patrick Tripp,Jin Huang,David G. DeWitt,Michael K. Tippett,Anthony G. Barnston,Shuhua Li,Anthony Rosati,Siegfried D. Schubert,Michele M. Rienecker,Max J. Suarez,Zhao E. Li,Jelena Marshak,Young-Kwon Lim,Joseph Tribbia,Kathleen Pegion,William J. Merryfield,Bertrand Denis,Eric F. Wood +28 more
TLDR
The recent U.S. National Academies report, Assessment of Intraseasonal to Interannual Climate Prediction and Predictability, was unequivocal in recommending the need for the development of a North American Multimodel Ensemble (NMME) operational predictive capability.Abstract:
The recent U.S. National Academies report, Assessment of Intraseasonal to Interannual Climate Prediction and Predictability, was unequivocal in recommending the need for the development of a North American Multimodel Ensemble (NMME) operational predictive capability. Indeed, this effort is required to meet the specific tailored regional prediction and decision support needs of a large community of climate information users. The multimodel ensemble approach has proven extremely effective at quantifying prediction uncertainty due to uncertainty in model formulation and has proven to produce better prediction quality (on average) than any single model ensemble. This multimodel approach is the basis for several international collaborative prediction research efforts and an operational European system, and there are numerous examples of how this multimodel ensemble approach yields superior forecasts compared to any single model. Based on two NOAA Climate Test bed (CTB) NMME workshops (18 February and 8 April 2...read more
Citations
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Journal ArticleDOI
The NCEP climate forecast system version 2
Suranjana Saha,Shrinivas Moorthi,Xingren Wu,Jiande Wang,Sudhir Nadiga,Patrick Tripp,David Behringer,Yu-Tai Hou,Hui Ya Chuang,M. Iredell,Michael Ek,Jesse Meng,Rongqian Yang,Malaquías Peña Mendez,Huug van den Dool,Qin Zhang,Wanqiu Wang,Mingyue Chen,Emily Becker +18 more
TL;DR: The second version of the NCEP Climate Forecast System (CFSv2) was made operational at the National Center for Environmental Prediction (NCEP) in 2011 as discussed by the authors.
Journal ArticleDOI
Understanding ENSO Diversity
Antonietta Capotondi,Andrew T. Wittenberg,Matthew Newman,Emanuele Di Lorenzo,Jin-Yi Yu,Pascale Braconnot,Julia E. Cole,Boris Dewitte,Benjamin S. Giese,Eric Guilyardi,Fei-Fei Jin,Kristopher B. Karnauskas,Benjamin Kirtman,Tong Lee,Niklas Schneider,Yan Xue,Sang-Wook Yeh +16 more
TL;DR: The authors surveys the current state of knowledge of ENSO diversity, identifies key gaps in understanding, and outlines some promising future research directions, as well as identifying key gaps and promising future directions.
Journal ArticleDOI
Deep learning for multi-year ENSO forecasts
TL;DR: It is shown that a statistical forecast model employing a deep-learning approach produces skilful ENSO forecasts for lead times of up to one and a half years, overcoming a weakness of dynamical forecast models.
Journal ArticleDOI
Divergent consensuses on Arctic amplification influence on midlatitude severe winter weather
Judah Cohen,Xiangdong Zhang,Jennifer A. Francis,Thomas Jung,Thomas Jung,Ron Kwok,James E. Overland,Thomas J. Ballinger,Uma S. Bhatt,Hans W. Chen,Hans W. Chen,Dim Coumou,Dim Coumou,Steven B. Feldstein,Hongping Gu,Dörthe Handorf,Gina R. Henderson,Monica Ionita,Marlene Kretschmer,Frédéric Laliberté,Sukyoung Lee,Hans W. Linderholm,Hans W. Linderholm,Wieslaw Maslowski,Yannick Peings,Karl Pfeiffer,Ignatius Rigor,Tido Semmler,Julienne Stroeve,Patrick C. Taylor,Steve Vavrus,Timo Vihma,Shih-Yu Wang,Manfred Wendisch,Yutian Wu,Jin-Ho Yoon +35 more
TL;DR: The Arctic has warmed more than twice as fast as the global average since the late twentieth century, a phenomenon known as Arctic amplification (AA), and progress has been made in understanding the mechanisms that link it to midlatitude weather variability as discussed by the authors.
References
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Journal ArticleDOI
The NCEP climate forecast system version 2
Suranjana Saha,Shrinivas Moorthi,Xingren Wu,Jiande Wang,Sudhir Nadiga,Patrick Tripp,David Behringer,Yu-Tai Hou,Hui Ya Chuang,M. Iredell,Michael Ek,Jesse Meng,Rongqian Yang,Malaquías Peña Mendez,Huug van den Dool,Qin Zhang,Wanqiu Wang,Mingyue Chen,Emily Becker +18 more
TL;DR: The second version of the NCEP Climate Forecast System (CFSv2) was made operational at the National Center for Environmental Prediction (NCEP) in 2011 as discussed by the authors.
Journal ArticleDOI
The NCEP Climate Forecast System
Suranjana Saha,Sudhir Nadiga,C. Thiaw,Julian X. L. Wang,Wanqiu Wang,Q. Zhang,H. M. van den Dool,Hua-Lu Pan,Shrinivas Moorthi,David Behringer,Diane Stokes,Malaquias Peña,Stephen J. Lord,Glenn H. White,Wesley Ebisuzaki,Peitao Peng,Pingping Xie +16 more
TL;DR: The Climate Forecast System (CFS) as discussed by the authors is a fully coupled ocean-land-atmosphere dynamical seasonal prediction system, which became operational at NCEP in August 2004.
Journal ArticleDOI
GFDL’s ESM2 Global Coupled Climate–Carbon Earth System Models. Part I: Physical Formulation and Baseline Simulation Characteristics
John P. Dunne,Jasmin John,Alistair Adcroft,Stephen M. Griffies,Robert Hallberg,Elena Shevliakova,Ronald J. Stouffer,William Cooke,Krista A. Dunne,Matthew Harrison,John P. Krasting,Sergey Malyshev,Paul C.D. Milly,Peter J. Phillipps,Lori T. Sentman,Bonita L. Samuels,Michael J. Spelman,Michael Winton,Andrew T. Wittenberg,Niki Zadeh +19 more
TL;DR: In this article, the authors describe carbon system formulation and simulation characteristics of two new global coupled carbon-climate Earth System Models (ESM), ESM2M and ESM 2G).
Journal ArticleDOI
The multi-institution North American Land Data Assimilation System (NLDAS): Utilizing multiple GCIP products and partners in a continental distributed hydrological modeling system
Kenneth E. Mitchell,Dag Lohmann,Paul R. Houser,Eric F. Wood,John Schaake,Alan Robock,Brian Cosgrove,Justin Sheffield,Qingyun Duan,Lifeng Luo,Lifeng Luo,R. Wayne Higgins,Rachel T. Pinker,J. Dan Tarpley,Dennis P. Lettenmaier,Curtis H. Marshall,Curtis H. Marshall,Jared Entin,Ming Pan,Wei Shi,Victor Koren,Jesse Meng,Jesse Meng,Bruce H. Ramsay,Andrew A. Bailey +24 more
TL;DR: A real-time and retrospective North American Land Data Assimilation System (NLDAS) is presented in this article, which consists of four land models executing in parallel in uncoupled mode, common hourly surface forcing, and common streamflow routing: all using a 1/8° grid over the continental United States.
Journal ArticleDOI
Development of a european multimodel ensemble system for seasonal-to-interannual prediction (demeter)
Tim Palmer,Andrea Alessandri,U. Andersen,Pierre Cantelaube,M. K. Davey,Pascale Delecluse,Michel Déqué,E. Diez,Francisco J. Doblas-Reyes,H. Feddersen,Richard Graham,Silvio Gualdi,J. F. Gueremy,Renate Hagedorn,Moshe Hoshen,Noel Keenlyside,Mojib Latif,Alban Lazar,Eric Maisonnave,V. Marletto,Andrew P. Morse,B. Orfila,P. Rogel,Jean-Michel Terres,Madeleine C. Thomson +24 more
TL;DR: In this article, a multi-model ensemble-based system for seasonal-to-interannual prediction has been developed in a joint European project known as DEMETER (Development of a European Multimodel Ensemble Prediction System for Seasonal to Interannual Prediction).
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