Contribution of El Niño Southern Oscillation (ENSO) Diversity to Low-Frequency Changes in ENSO Variance

被引:2
作者
Schloer, Jakob [1 ]
Strnad, Felix [1 ]
Capotondi, Antonietta [2 ,3 ]
Goswami, Bedartha [1 ]
机构
[1] Univ Tubingen, Machine Learning Climate Sci, Tubingen, Germany
[2] Univ Colorado, Cooperat Inst Res Environm Sci, Boulder, CO USA
[3] NOAA, Phys Sci Lab, Boulder, CO USA
关键词
El Ni & ntilde; o Southern Oscillation; decadal variability; unsupervised clustering; machine learning; LA-NINA EVENTS; EASTERN-PACIFIC; MODEL; EVOLUTION;
D O I
10.1029/2024GL109179
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
El Ni & ntilde;o Southern Oscillation (ENSO) diversity is characterized based on the longitudinal location of maximum sea surface temperature anomalies (SSTA) and amplitude in the tropical Pacific, as Central Pacific events are typically weaker than Eastern Pacific events. SSTA pattern and intensity undergo low-frequency modulations, affecting ENSO prediction skill and remote impacts, and resulting in low-frequency changes in ENSO variance. Yet, how different ENSO types contribute to these decadal variance changes remains unclear. Here, we decompose the low-frequency changes of ENSO variance into contributions from ENSO diversity categories. We propose a fuzzy clustering of monthly SSTA to allow for non-binary event category memberships, where each event can belong to different clusters. Our approach identifies two La Ni & ntilde;a and three El Ni & ntilde;o categories and shows that the major shift of ENSO variance in the mid-1970s was associated with an increasing likelihood of strong La Ni & ntilde;a and extreme El Ni & ntilde;o events. The El Ni & ntilde;o Southern Oscillation (ENSO) is a climate phenomenon that involves changes in ocean temperatures in the central and eastern tropical Pacific and greatly influences the weather around the globe. ENSO events are usually categorized based on where these temperature variations are the strongest and how intense they are. However, these categories are at times ambiguous and the way ENSO behaves can change over decades. Our study introduces a new way to estimate how different kinds of ENSO events contribute to its overall variation over time. We base our variability analysis on a fuzzy categorization of ENSO events, which results in three different kinds of El Ni & ntilde;o events and two kinds of La Ni & ntilde;a events. We find that the decadal changes in ENSO variance, including the decadal shift in the mid-1970s, were primarily associated with strong La Ni & ntilde;a and extreme El Ni & ntilde;o events. Using a fuzzy categorization, five different El Ni & ntilde;o Southern Oscillation (ENSO) types are identified in observations Extreme El Ni & ntilde;o events emerge as a distinct category Strong La Ni & ntilde;a and Extreme El Ni & ntilde;o categories mainly contributed to the shift in decadal ENSO variance around 1970
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页数:11
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