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Updated: Jul 16, 2025

Investigating the Relationship between Sea Surface Chlorophyll and Major Features of the South China Sea with Satellite Information
Published on: June 13, 2020
Propagation pathways of Indo-Pacific rainfall extremes are modulated by Pacific sea surface temperatures
Felix M Strnad1, Jakob Schlör2, Ruth Geen3
1Machine Learning in Climate Science, University of Tübingen, Tübingen, Germany. felix.strnad@uni-tuebingen.de.
Abstract:
Intraseasonal variation of rainfall extremes within boreal summer in the Indo-Pacific region is driven by the Boreal Summer Intraseasonal Oscillation (BSISO), a quasi-periodic north-eastward movement of convective precipitation from the Indian Ocean to the Western Pacific. Predicting the spatiotemporal location of the BSISO is essential for subseasonal prediction of rainfall extremes but still remains a major challenge due to insufficient understanding of its propagation pathway. Here, using unsupervised machine learning, we characterize how rainfall extremes travel within the region and reveal three distinct propagation modes: north-eastward, eastward-blocked, and quasi-stationary. We show that Pacific sea surface temperatures modulate BSISO propagation - with El Niño-like (La Niña-like) conditions favoring quasi-stationary (eastward-blocked) modes-by changing the background moist static energy via local overturning circulations. Finally, we demonstrate the potential for early warning of rainfall extremes in the region up to four weeks in advance.
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