Skill of Real-Time Seasonal ENSO Model Predictions During 2002–11: Is Our Capability Increasing?

Real-time model predictions of ENSO conditions during the 2002–11 period are evaluated and compared to skill levels documented in studies of the 1990s. ENSO conditions are represented by the Nino- 3.4 SST index in the east-central tropical Pacific. The skills of 20 prediction models (12 dynamical, 8 statistical) are examined. Results indicate skills somewhat lower than those found for the less advanced models of the 1980s and 1990s. Using hindcasts spanning 1981–2011, this finding is explained by the relatively greater predictive challenge posed by the 2002–11 period and suggests that decadal variations in the character of ENSO variability are a greater skill-determining factor than the steady but gradual trend toward improved ENSO prediction science and models. After adjusting for the varying difficulty level, the skills of 2002–11 are slightly higher than those of earlier decades. Unlike earlier results, the average skill of dynamical models slightly, but statistically significantly, exceeds that of sta...

[1]  F. Wilcoxon Individual Comparisons by Ranking Methods , 1945 .

[2]  W. Hays Statistics for the social sciences , 1973 .

[3]  気象庁 Outline of the operational numerical weather prediction at the Japan Meteorological Agency , 1977 .

[4]  R. Davis A search for short range climate predictability , 1979 .

[5]  G. C. Ramseyer Testing the Difference between Dependent Correlations Using the Fisher Z , 1979 .

[6]  R. E. Livezey,et al.  Statistical Field Significance and its Determination by Monte Carlo Techniques , 1983 .

[7]  Mark A. Cane,et al.  Experimental forecasts of El Niño , 1986, Nature.

[8]  T. Barnett,et al.  Origins and Levels of Monthly and Seasonal Forecast Skill for United States Surface Air Temperatures Determined by Canonical Correlation Analysis , 1987 .

[9]  J. Michaelsen Cross-Validation in Statistical Climate Forecast Models , 1987 .

[10]  Mojib Latif,et al.  Tropical Ocean circulation experiments , 1987 .

[11]  M. Cane,et al.  A Model El Niñ–Southern Oscillation , 1987 .

[12]  A. H. Murphy,et al.  Skill Scores Based on the Mean Square Error and Their Relationships to the Correlation Coefficient , 1988 .

[13]  Cécile Penland,et al.  Random Forcing and Forecasting Using Principal Oscillation Pattern Analysis , 1989 .

[14]  A. Barnston,et al.  Prediction of ENSO Episodes Using Canonical Correlation Analysis , 1992 .

[15]  Cécile Penland,et al.  Prediction of Nino 3 sea surface temperatures using linear inverse modeling , 1993 .

[16]  T. Barnett,et al.  ENSO and ENSO-related Predictability. Part I: Prediction of Equatorial Pacific Sea Surface Temperature with a Hybrid Coupled Ocean–Atmosphere Model , 1993 .

[17]  A. Barnston,et al.  A Degeneracy in Cross-Validated Skill in Regression-based Forecasts , 1993 .

[18]  M. Cane,et al.  On the prediction of ENSO: a study with a low-order Markov model , 1994 .

[19]  M. Déqué,et al.  The ARPEGE/IFS atmosphere model: a contribution to the French community climate modelling , 1994 .

[20]  Lennart Bengtsson,et al.  Climatology and variability in the ECHO coupled GCM , 1994 .

[21]  T. Barnett,et al.  Long-Lead Seasonal ForecastsWhere Do We Stand? , 1994 .

[22]  H. V. D. Dool,et al.  Searching for analogues, how long must we wait? , 1994 .

[23]  Andrew F. Loughe,et al.  A Reduced-Gravity Isopycnal Ocean Model: Hindcasts of El Niño , 1995 .

[24]  Prashant D. Sardeshmukh,et al.  The Optimal Growth of Tropical Sea Surface Temperature Anomalies , 1995 .

[25]  Dake Chen,et al.  An Improved Procedure for EI Ni�o Forecasting: Implications for Predictability , 1995, Science.

[26]  M. Claussen,et al.  The atmospheric general circulation model ECHAM-4: Model description and simulation of present-day climate , 1996 .

[27]  Stanley B. Goldenberg,et al.  Documentation o f a Highly ENSO-Related SST Région in thé Equatorial Pacific , 1997 .

[28]  John A. Knaff,et al.  An El Niño–Southern Oscillation Climatology and Persistence (CLIPER) Forecasting Scheme , 1997 .

[29]  William W. Hsieh,et al.  Forecasting the equatorial Pacific sea surface temperatures by neural network models , 1997 .

[30]  Stanley B. Goldenberg,et al.  Documentation of a highly ENSO‐related sst region in the equatorial pacific: Research note , 1997 .

[31]  Ming Ji,et al.  An Improved Coupled Model for ENSO Prediction and Implications for Ocean Initialization. Part II: The Coupled Model , 1998 .

[32]  F. Tangang,et al.  Forecasting ENSO Events: A Neural Network–Extended EOF Approach. , 1998 .

[33]  David P. Rowell,et al.  Assessing Potential Seasonal Predictability with an Ensemble of Multidecadal GCM Simulations , 1998 .

[34]  Antonio J. Busalacchi,et al.  The Tropical Ocean‐Global Atmosphere observing system: A decade of progress , 1998 .

[35]  Benjamin Kirtman,et al.  Decadal Variability in ENSO Predictability and Prediction , 1998 .

[36]  William W. Hsieh,et al.  Applying Neural Network Models to Prediction and Data Analysis in Meteorology and Oceanography. , 1998 .

[37]  A. Barnston,et al.  Predictive Skill of Statistical and Dynamical Climate Models in SST Forecasts during the 1997-98 El Niño Episode and the 1998 La Niña Onset. , 1999 .

[38]  Ming Ji,et al.  ENSO Prediction with Markov Models: The Impact of Sea Level , 2000 .

[39]  John F. B. Mitchell,et al.  The simulation of SST, sea ice extents and ocean heat transports in a version of the Hadley Centre coupled model without flux adjustments , 2000 .

[40]  John A. Knaff,et al.  How Much Skill Was There in Forecasting the Very Strong 1997–98 El Niño? , 2000 .

[41]  Allan J. Clarke,et al.  ENSO prediction using an ENSO trigger and a proxy for Western Equatorial Pacific Warm Pool Movement , 2001 .

[42]  Jong-Seong Kug,et al.  The impacts of the model assimilated wind stress data in the initialization of an intermediate ocean and the ENSO predictability , 2001 .

[43]  Thomas M. Smith,et al.  An Improved In Situ and Satellite SST Analysis for Climate , 2002 .

[44]  Renate Hagedorn,et al.  Comparison of the ECMWF seasonal forecast System 1 and 2, including the relative performance for the 1997/98 El Nino , 2002 .

[45]  R. Kleeman,et al.  The BMRC Coupled General Circulation Model ENSO Forecast System , 2002 .

[46]  N. Keenlyside,et al.  Annual cycle of equatorial zonal currents in the Pacific , 2002 .

[47]  B. Kirtman The COLA Anomaly Coupled Model: Ensemble ENSO Prediction , 2003 .

[48]  M. Déqué,et al.  Anthropogenic climate change over the Mediterranean region simulated by a global variable resolution model , 2003 .

[49]  Allan J. Clarke,et al.  Improving El Niño prediction using a space‐time integration of Indo‐Pacific winds and equatorial Pacific upper ocean heat content , 2003 .

[50]  N. Keenlyside,et al.  A new intermediate coupled model for El Niño simulation and prediction , 2003 .

[51]  David L. T. Anderson,et al.  Sensitivity of dynamical seasonal forecasts to ocean initial conditions , 2004 .

[52]  Alexey Kaplan,et al.  Predictability of El Niño over the past 148 years , 2004, Nature.

[53]  D. Dewitt Retrospective Forecasts of Interannual Sea Surface Temperature Anomalies from 1982 to Present Using a Directly Coupled Atmosphere–Ocean General Circulation Model , 2005 .

[54]  Michael Ghil,et al.  Multilevel Regression Modeling of Nonlinear Processes: Derivation and Applications to Climatic Variability , 2005 .

[55]  Michael Ghil,et al.  A Hierarchy of Data-Based ENSO Models , 2005 .

[56]  Swadhin K. Behera,et al.  Seasonal Climate Predictability in a Coupled OAGCM Using a Different Approach for Ensemble Forecasts , 2005 .

[57]  S. Saha,et al.  The NCEP Climate Forecast System , 2006 .

[58]  James C. McWilliams,et al.  Diurnal Coupling in the Tropical Oceans of CCSM3 , 2006 .

[59]  R. W. Higgins,et al.  An Alert Classification System for Monitoring and Assessing the ENSO Cycle , 2007 .

[60]  Kristian Mogensen,et al.  Development of the ECMWF seasonal forecast System 3 , 2007 .

[61]  David L. T. Anderson,et al.  The ECMWF Ocean Analysis System: ORA-S3 , 2008 .

[62]  Dake Chen,et al.  El Niño prediction and predictability , 2008, J. Comput. Phys..

[63]  J. Shukla,et al.  Current status of ENSO prediction skill in coupled ocean–atmosphere models , 2008 .

[64]  E. Guilyardi,et al.  UNDERSTANDING EL NINO IN OCEAN-ATMOSPHERE GENERAL CIRCULATION MODELS : Progress and Challenges , 2008 .

[65]  David L. T. Anderson,et al.  Impact of initialization strategies and observations on seasonal forecast skill , 2009 .

[66]  B. Kirtman,et al.  Multimodel Ensemble ENSO Prediction with CCSM and CFS , 2009 .

[67]  H. Hendon,et al.  Representation and prediction of the Indian Ocean dipole in the POAMA seasonal forecast model , 2009 .

[68]  Michael Ghil,et al.  A delay differential model of ENSO variability – Part 2: Phase locking, multiple solutions and dynamics of extrema , 2010, 1003.0028.

[69]  Arun Kumar,et al.  An Assessment of the CFS Real-Time Seasonal Forecasts , 2010 .

[70]  Dominic A. Hudson,et al.  The impact of atmospheric initialisation on seasonal prediction of tropical Pacific SST , 2011 .

[71]  Alberto Arribas,et al.  The GloSea4 Ensemble Prediction System for Seasonal Forecasting , 2011 .

[72]  Kristian Mogensen,et al.  ECMWF seasonal forecast system 3 and its prediction of sea surface temperature , 2011 .

[73]  A. Barnston,et al.  Performance of Recent Multimodel ENSO Forecasts , 2012 .