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Sea surface salinity-derived indexes for distinguishing two types of El Niño events in the tropical Pacific 被引量:2

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摘要 In this study,sea surface salinity(SSS)indexes are derived from reanalysis and observational datasets to distinguish the two types of(Central Pacific(CP)and Eastern Pacific(EP))El Niño events in the tropical Pacific.Based on the SSS anomalous spatial and temporal pointwise correlations with sea surface temperature(SST)indexes of two types of El Niño events,the key areas with SSS variations for EP and CP El Niño events are identified.For EP El Niño events,the key areas are located over an arcuate area centered at(0°,130°E)and in the central equatorial Pacific covering(5°S–5°N,175°W–158°W).For CP El Niño events,the key areas are located in the northeastern western Pacific covering(2°N,142°E–170°E)and in the southeastern Pacific covering(20°S–10°S,135°W–95°W).The key areas for EP and CP El Niño events in this study are not located near the dateline in the equatorial Pacific and differ from those obtained from the regression or composite methods.Accordingly,these key areas are used to construct SSS indexes,termed as the CP/EP El Niño SSS index(CSI/ESI),to distinguish EP and CP El Niño events independently.The SSS indexes are verified by different datasets over varying time periods and they can be adequately used to identify the two types of El Niño events and serve as another useful tool for monitoring ENSO.These analyses offer novel insight into how to represent the diversity of El Niño events.
出处 《Science China Earth Sciences》 SCIE EI CSCD 2021年第8期1267-1284,共18页 中国科学(地球科学英文版)
基金 supported by the National Key Research and Development Program on Monitoring,Early Warning and Prevention of Major Natural Disaster(Grant Nos.2018YFC1506002,2016YFC1401601,2019YFC1510004) the Strategic Priority Research Program of Chinese Academy of Sciences(Grant Nos.XDB 40000000,XDB 42000000) the National Natural Science Foundation of China(Grant Nos.42030410,41976026,41931183,41690122) the National Key R&D Program of China(Grant No.2017YFC1404102).
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