El Niño indices based on subareas of SST in Pacific

Wanjiao Song; Qing Dong; Cunjin Xue; Xueyan Hou; Lijuan Qin

doi:10.1117/12.2069191

10 December 2014 El Niño indices based on subareas of SST in Pacific

Wanjiao Song, Qing Dong, Cunjin Xue, Xueyan Hou, Lijuan Qin

Proceedings Volume 9261, Ocean Remote Sensing and Monitoring from Space; 92611D (2014) https://doi.org/10.1117/12.2069191
Event: SPIE Asia-Pacific Remote Sensing, 2014, Beijing, China

Abstract

El Niño continues the most important coupled ocean-atmosphere phenomenon to cause global climate variability on seasonal to inter annual time scales. The first independent spatial mode which carried out by EOF analysis of tropical and north Pacific sea surface temperature (SST) for the period of 1985-2009 in AVHRR dataset is found to be associated with well-known regional climate phenomena: the El Niño. This paper addresses the need for a reliable El Niño index that allows for the historical definition of El Niño events in the instrumental record back to 1985-2009 with a new perspective. For quantitative purposes, possible definitions are explored that match the El Niño identified historically in 1985-2009, and it is suggested that an El Niño can be said to occur if difference of sea surface temperature (SST) anomalies between the tropical and north Pacific exceeds 0.6 times standard deviation for 5 months or more. An advantage of such a definition is that it combines the characteristics between tropical and north Pacific. Through seasonal analysis of SST in El Niño event, we found that the El Niño events are almost beginning in boreal spring or perhaps boreal summer and peak from November to February. It provides a more complete and flexible description of the El Niño phenomenon than single area in tropical Pacific.

Citation Download Citation

Wanjiao Song, Qing Dong, Cunjin Xue, Xueyan Hou, and Lijuan Qin "El Niño indices based on subareas of SST in Pacific", Proc. SPIE 9261, Ocean Remote Sensing and Monitoring from Space, 92611D (10 December 2014); https://doi.org/10.1117/12.2069191

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Electroluminescence

Climatology

Remote sensing

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