Predictive Skill of AGCM Seasonal Climate Forecasts Subject to Different SST Prediction Methodologies

Abstract This study examines skill of retrospective forecasts using the ECHAM4.5 atmospheric general circulation model (AGCM) forced with predicted sea surface temperatures (SSTs) from methods of varying complexity. The SST fields are predicted in three ways: persisted observed SST anomalies, empirically predicted SSTs, and predicted SSTs from a dynamically coupled ocean–atmosphere model. Investigation of relative skill of the three sets of retrospective forecasts focuses on the ensemble mean, which constitutes the portion of the model response attributable to the prescribed boundary conditions. The anomaly correlation skill analyses for precipitation and 2-m air temperature indicate that dynamically predicted SSTs generally improve upon persisted and empirically predicted SSTs when they are used as boundary forcing in the AGCM predictions. This is particularly the case for precipitation forecasts. The skill differences in these experiments are ascribed to the skill of SST predictions in the tropical ocea...

[1]  Simon J. Mason,et al.  Evaluation of the IRI's “Net Assessment” Seasonal Climate Forecasts: 1997–2001 , 2003 .

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

[3]  C. Ropelewski,et al.  Current approaches to seasonal to interannual climate predictions , 2001 .

[4]  Renate Hagedorn,et al.  The rationale behind the success of multi-model ensembles in seasonal forecasting-II , 2005 .

[5]  P. Sardeshmukh,et al.  Sensitivity of global warming to the pattern of tropical ocean warming , 2006 .

[6]  T. Palmer,et al.  Development of a European Multi-Model Ensemble System for Seasonal to Inter-Annual Prediction (DEMETER) , 2004 .

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

[8]  A. Barnston,et al.  Multimodel Ensembling in Seasonal Climate Forecasting at IRI , 2003 .

[9]  T. Barnett,et al.  A Two-Tiered Approach to Long-Range Climate Forecasting , 1993, Science.

[10]  Peter J. Webster,et al.  Monsoon and Enso: Selectively Interactive Systems , 1992 .

[11]  Renate Hagedorn,et al.  The rationale behind the success of multi-model ensembles in seasonal forecasting — I. Basic concept , 2005 .

[12]  Upmanu Lall,et al.  Improved Combination of Multiple Atmospheric GCM Ensembles for Seasonal Prediction , 2004 .

[13]  L. Goddarda,et al.  CURRENT APPROACHES TO SEASONAL-TO-INTERANNUAL CLIMATE PREDICTIONS , 2000 .

[14]  Andrew P. Morse,et al.  DEVELOPMENT OF A EUROPEAN MULTIMODEL ENSEMBLE SYSTEM FOR SEASONAL-TO-INTERANNUAL PREDICTION (DEMETER) , 2004 .

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

[16]  Tom M. L. Wigley,et al.  A Bivariate Time Series Approach to Anthropogenic Trend Detection in Hemispheric Mean Temperatures , 2003 .

[17]  Daniel S. Wilks,et al.  Statistical Methods in the Atmospheric Sciences: An Introduction , 1995 .

[18]  N. Graham,et al.  Importance of the Indian Ocean for simulating rainfall anomalies over eastern and southern Africa , 1999 .

[19]  T. D. Mitchell,et al.  An improved method of constructing a database of monthly climate observations and associated high‐resolution grids , 2005 .

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

[21]  Thomas M. Smith,et al.  Extended Reconstruction of Global Sea Surface Temperatures Based on COADS Data (1854–1997) , 2003 .

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

[23]  Phillip A. Arkin,et al.  The IRI Seasonal Climate Prediction System and the 1997/98 El Niño Event , 1999 .

[24]  P. Sardeshmukh,et al.  Global Atmospheric Sensitivity to Tropical SST Anomalies throughout the Indo-Pacific Basin , 2002 .

[25]  K. Taylor.  Summarizing multiple aspects of model performance in a single diagram , 2001 .

[26]  Thomas M. Smith,et al.  Improved Global Sea Surface Temperature Analyses Using Optimum Interpolation , 1994 .

[27]  L. Goddard,et al.  El Niño: Catastrophe or Opportunity , 2005 .

[28]  Thomas M. Smith,et al.  Improved Extended Reconstruction of SST (1854–1997) , 2004 .

[29]  S. Mason,et al.  Sensitivity of seasonal climate forecasts to persisted SST anomalies , 2002 .

[30]  Tim Palmer,et al.  The prospects for seasonal forecasting—A review paper , 1994 .