【摘要】 通过寻找过程相似的有效指标 ,建立了一个适合于时间序列分析的相似预报模式。将该模式应用于 ENSO的重要指标—— NINO3区海温指数预报 ,结果表明 :海温相似预报较持续性预报在预报效果 (如误差和相关系数 )上有明显的提高 ,特别是在 6～ 8个月时效上更为突出 ;模式的有效预报时效为 8个月 ,基本上达到国际上同期的模式水平。在有效预报时效 8个月内 ,冬半年的预报相关性普遍高于夏半年 ,其中 ,1 2月份的预报相关性最高 ,而 6,7月份的预报相关性最低。对于所有时效 ,2～ 4月份的预报误差最小 ,而 1 2月份的预报误差最大。相似预报对于转折事件具有较好的预报能力 ,尤其是对于 El Nino结束和强 El Nino开始更多还原

【Abstract】 After defining a effective index for process similarity, an analogue model, which is suitable for doing similarity forecast for a time series, was established. The model was applied to an important index for ENSO’s monitoring NINO 3 SST anomaly, and some results had been discovered. Firstly, similarity forecast is obviously better than persistence forecast in prediction effects such as mean absolute error and correlation coefficient, especially in 6-8 months lead predictions, the maximum lead of effective prediction is 8 months, so the prediction ability of the model almostly reaches the level of the models in the world. Secondly, for the effective lead time(≤8 months) predictions, the correlation skills are generally better in winter half year than in summer half year, with the best in December and the worst in June and July. Meanwhile, for all lead predictions, the smallest mean absolute error occurs during February to April, and the larggest in December. Finally, similarity forecast has better ability in turn point prediction, especially for El Nino’s ending and strong El Nino’s beginning.更多还原