Abstract
The sea surface temperature (SST)‐forced predictability in precipitation is investigated in terms of the seasonal mean modes (SMMs) for June–July (JJ) and the sub‐seasonal mode (SSM) using the 24‐year six‐member ensembles simulation with an atmospheric general circulation model (AGCM). The SSM was defined as a 20‐day window length by an extended empirical orthogonal function (EOF) over the East Asian monsoon region. For the JJ mean rainfall, the first EOF of the model ensemble is considered to be the forced SST mode, with being an El Niño Southern Oscillation (ENSO) related pattern from the regressed SST field. The first mode of model was well correlated with the second mode of the observation in the spatial and temporal variation. In the potential predictability, the analysis of variance (ANOVA) was used for the mean mode and the SSM. The potential predictability for the SMM is improved over the north of the 30°N. Compared with JJ mean mode, the SSM has more SST‐forced variance and less internal variability. Copyright © 2008 Royal Meteorological Society