Based on the Zebiak-Cane model, the time-dependent nonlinear forcing singular vector (NFSV)-type tendency errors with components of 4 and 12 (denoted by NFSV-4 and NFSV-12) are calculated for predetermined El Ni?o events and compared with the constant NFSV (denoted by NFSV-1) from their patterns and resultant prediction errors. Specifically, NFSV-1 has a zonal dipolar sea surface temperature anomaly (SSTA) pattern with negative anomalies in the equatorial eastern Pacific and positive anomalies in the equatorial central-western Pacific. Although the first few components in NFSV-4 and NFSV-12 present patterns similar to NFSV-1, they tend to extend their dipoles farther westward; meanwhile, the positive anomalies gradually cover much smaller regions with the lag times. In addition, the authors calculate the prediction errors caused by the three kinds of NFSVs, and the results indicate that the prediction error induced by NFSV-12 is the largest, followed by the NFSV-4. However, when compared with the prediction errors caused by random tendency errors, the NFSVs generate significantly larger prediction errors. It is therefore shown that the spatial structure of tendency errors is important for producing large prediction errors. Furthermore, in exploring the tendency errors that cause the largest prediction error for El Ni?o events, the time-dependent NFSV should be evaluated.