| description abstract | Ensembles of hindcasts from seven models are analyzed to evaluate dynamical seasonal predictability of 850-hPa wind and rainfall for the Asian summer monsoon (ASM) during 1987, 1988, and 1993. These integrations were performed using observed sea surface temperatures and from observed initial conditions. The experiments were designed by the Climate Variability and Predictability, Working Group on Seasonal to Interannual Prediction as part of the Seasonal Prediction Model Intercomparison Project. Integrations from the European Union Prediction of Climate Variations on Seasonal to Interannual Timescales experiment are also evaluated. The National Centers for Environmental Prediction?National Center for Atmospheric Research and European Centre for Medium-Range Weather Forecasts reanalyses and observed pentad rainfall form the baseline against which the hindcasts are judged. Pattern correlations and root-mean-square differences indicate errors in the simulation of the time mean low-level flow and the rainfall exceed observational uncertainty. Most models simulate the subseasonal EOFs that are associated with the dominant variations of the 850-hPa flow during the ASM, but not with the fidelity exhibited by the reanalyses as determined using pattern correlations. Pattern correlations indicate that the first EOF, associated with the tropical convergence zone being located over the continental landmass, is best simulated. The higher-order EOFs are less well simulated, and errors in the magnitude and location of their associated precipitation anomalies compromise dynamical seasonal predictability and are related to errors of the mean state. In most instances the models fail to properly project the subseasonal EOFs/principal components onto the interannual variability with the result that hindcasts of the 850-hPa flow and rainfall are poor. In cases where the observed EOFs are known to be related to the boundary forcing, the failure of the models to properly project the EOFs onto the interannual variability indicates that the models are not setting up observed teleconnection patterns. | |
