Unraveling El Niño's impact on the East Asian Monsoon and Yangtze River summer flooding. Issue 21 (15th November 2016)

• Record Type: Journal Article
• Authors: Zhang, Wenjun; Jin, Fei‐Fei; Stuecker, Malte F.; Wittenberg, Andrew T.; Timmermann, Axel; Ren, Hong‐Li; Kug, Jong‐Seong; Cai, Wenju; Cane, Mark
• Is Part Of: Geophysical research letters. Volume 43:Issue 21(2016)
• Page Start: 11, 375
• Page End: 11, 382
• Publication Date: 2016-11-15
• Subjects: ENSO -- monsoon -- tropical climate; Geophysics -- Periodicals; Planets -- Periodicals; Lunar geology -- Periodicals; 550
• DOI: 10.1002/2016GL071190
• Languages: English
• ISSNs: 0094-8276

Abstract

Abstract: Strong El Niño events are followed by massive summer monsoon flooding over the Yangtze River basin (YRB), home to about a third of the population in China. Although the El Niño–Southern Oscillation (ENSO) provides the main source of seasonal climate predictability for many parts of the Earth, the mechanisms of its connection to the East Asian monsoon remain largely elusive. For instance, the traditional Niño3.4 ENSO index only captures precipitation anomalies over East Asia in boreal winter but not during the summer. Here we show that there exists a robust year‐round and predictable relationship between ENSO and the Asian monsoon. This connection is revealed by combining equatorial (Niño3.4) and off‐equatorial Pacific sea surface temperature anomalies (Niño‐A index) into a new metric that captures ENSO's various aspects, such as its interaction with the annual cycle and its different flavors. This extended view of ENSO complexity improves predictability of YRB summer flooding events. Key Points: ENSO's complex temporal and spatial diversities can be well captured when combining equatorial and off‐equatorial SSTAs to a new metric This metric captures a robust year‐round ENSO/monsoon relationship and the Yangtze River basin summer flooding events The ENSO complexity captured by the metric can be predicted several months in advance, thereby providing monsoon predictability