In recent years, El Nino Modoki （a type of pseudo-El Nino） has been distinguished as a unique large-scale ocean warming phenomenon happening in the central tropical Pacific that is quite different from the tradition...In recent years, El Nino Modoki （a type of pseudo-El Nino） has been distinguished as a unique large-scale ocean warming phenomenon happening in the central tropical Pacific that is quite different from the traditional El Nino. In this study, EOF analysis was used to successfully separate El Nino and El Nino Modoki. The abilities of the NINO3 index, NINO3.4 index, NINO1＋2 index and NINO4 index in characterizing El Nino were explored in detail. The resulting suggestion was that, comparatively, NINO3 is the optimal index for monitoring El Nino among the four NINO indices, as the other NINO indices were found to be less good at distinguishing between El Nino and El Nino Modoki signals, or were easily disturbed by El Nino Modoki signals. Further, an improved El Nino Modoki index （IEMI） was introduced in the current paper to better represent the El Nino Modoki that is captured by the second leading EOF mode of monthly tropical Pacific sea surface temperature anomalies （SSTAs）. The IEMI is an improvement of the El Nino Modoki index （EMI） through adjustments made to the inappropriate weight coefficients of the three boxes of EMI. The IEMI therefore overcomes the EMI’s inability to monitor the two historical El Nino Modoki events, as well as avoids the possible risk （present in the EMI） of excluding the interference of the El Nino signal. The realistic and potential advantages of the IEMI are clear.展开更多
基金supported by the National Natural Science Foun-dation of China (Grant Nos. 40675028 and 40975029)the National Basic Research Program of China (Grant No.2006CB403600)the State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics (LASG)
文摘In recent years, El Nino Modoki （a type of pseudo-El Nino） has been distinguished as a unique large-scale ocean warming phenomenon happening in the central tropical Pacific that is quite different from the traditional El Nino. In this study, EOF analysis was used to successfully separate El Nino and El Nino Modoki. The abilities of the NINO3 index, NINO3.4 index, NINO1＋2 index and NINO4 index in characterizing El Nino were explored in detail. The resulting suggestion was that, comparatively, NINO3 is the optimal index for monitoring El Nino among the four NINO indices, as the other NINO indices were found to be less good at distinguishing between El Nino and El Nino Modoki signals, or were easily disturbed by El Nino Modoki signals. Further, an improved El Nino Modoki index （IEMI） was introduced in the current paper to better represent the El Nino Modoki that is captured by the second leading EOF mode of monthly tropical Pacific sea surface temperature anomalies （SSTAs）. The IEMI is an improvement of the El Nino Modoki index （EMI） through adjustments made to the inappropriate weight coefficients of the three boxes of EMI. The IEMI therefore overcomes the EMI’s inability to monitor the two historical El Nino Modoki events, as well as avoids the possible risk （present in the EMI） of excluding the interference of the El Nino signal. The realistic and potential advantages of the IEMI are clear.
