资源环境科技发展态势分析平台

This work demonstrates the influence of the initial amplitude of the sea surface temperature anomaly (SSTA) associated with El Nino-Southern Oscillation (ENSO) following its evolutionary phase on the forecast skill of ENSO in retrospective predictions of the Climate Forecast System, version 2. It is noted that the prediction skill varies with the phase of the ENSO cycle. The averaged skill (linear correlation) of Nino-3.4 index is in a range of 0.15-0.55 for the amplitude of Nino-3.4 index smaller than 0.5 degrees C (e.g., initial phase or neutral condition of ENSO), and 0.74-0.93 for the amplitude larger than 0.5 degrees C (e.g., mature condition of ENSO) for 0-6-month lead predictions. The dependence of the prediction skills of ENSO on its phase is linked to the variation of signal-to-noise ratio (SNR). This variation is found to be mainly due to the changes in the amplitude of the signal (prediction of the ensemble mean) during different phases of the ENSO cycle, as the noise (forecast spread among the ensemble members), both in the Nino-3.4 region and the whole Pacific, does not depend much on the Nino-3.4 amplitude. It is also shown that the spatial pattern of unpredictable noise in the Pacific is similar to the predictable signal. These results imply that skillful prediction of the ENSO cycle, either at the initial time of an event or during the transition phase of the ENSO cycle, when the anomaly signal is weak and the SNR is small, is an inherent challenge.