期刊
JOURNAL OF CLIMATE
卷 26, 期 13, 页码 4816-4827出版社
AMER METEOROLOGICAL SOC
DOI: 10.1175/JCLI-D-12-00649.1
关键词
ENSO; La Nina; El Nino; Neural networks; Trends; Tropical variability
资金
- NOAA Climate Test Bed program
It is now widely recognized that El Nino-Southern Oscillation (ENSO) occurs in more than one form, with the canonical eastern Pacific (EP) and more recently recognized central Pacific (CP) ENSO types receiving the most focus. Given that these various ENSO flavors may contribute to climate variability and long-term trends in unique ways, and that ENSO variability is not limited to these two types, this study presents a framework that treats ENSO as a continuum but determines a finite maximum number of statistically distinguishable representative ENSO patterns. A neural network-based cluster analysis called self-organizing map (SOM) analysis paired with a statistical distinguishability test determines nine unique patterns that characterize the September-February tropical Pacific SST anomaly fields for the period from 1950 through 2011. These nine patterns represent the flavors of ENSO, which include EP, CP, and mixed ENSO patterns. Over the 1950-2011 period, the most significant trends reflect changes in La Nina patterns, with a shift in dominance of La Nina-like patterns with weak or negative western Pacific warm pool SST anomalies until the mid-1970s, followed by a dominance of La Nina-like patterns with positive western Pacific warm pool SST anomalies, particularly after the mid-1990s. Both an EP and especially a CP El Nino pattern experienced positive frequency trends, but these trends are indistinguishable from natural variability. Overall, changes in frequency within the ENSO continuum contributed to the pattern of tropical Pacific warming, particularly in the equatorial eastern Pacific and especially in relation to changes of La Nina-like rather than El Nino-like patterns.
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