A classified El Niño index using AVHRR remote-sensing SST data. Issue 2 (17th January 2016)

• Record Type: Journal Article
• Authors: Song, Wanjiao; Dong, Qing; Xue, Cunjin
• Is Part Of: International journal of remote sensing. Volume 37:Issue 2(2016)
• Page Start: 403
• Page End: 417
• Publication Date: 2016-01-17
• Subjects: Remote sensing -- Periodicals; Télédétection -- Périodiques; 621.3678
• DOI: 10.1080/01431161.2015.1125553
• Languages: English
• ISSNs: 0143-1161

Abstract

ABSTRACT: A process-orientated El Niño index (PEI) is constructed to determine the detailed classification of two major types of El Niño events during 1985–2009 from remote-sensing monthly sea surface temperature (SST) anomaly data sets. Four revised Niño regions are defined in the tropical Pacific, and the index uses SST anomalies and their duration in each region. Based on their varying evolution, the index allows eastern Pacific (EP) El Niño events to be either weak or strong EP type, and central Pacific (CP) El Niño events to be either weak CP, strong CP, or mixed EPCP type. The El Niño types identified by this index are compared to those obtained using previously published methods, and the differences are examined and discussed. The results suggest that the PEI is optimal for monitoring El Niño events of weaker amplitude and shorter duration. The PEI is focused on the development process of El Niño events, providing a novel perspective for classifying El Niño types. Analysis of the SST evolution of the El Niño events identified here reveals several misclassifications in previous studies, stressing the disadvantage of relying solely on single areas or short time periods. Existing EP and CP El Niño events in the study period were reclassified by the PEI into weak, strong, and mixed events. The listing of El Niño types produced here can be used for selecting El Niño events for further study of their dynamics and climatic impacts.