TBI Webinar Series 3 - Understanding Extreme Climate Events: 2023-24 El Niño, Hottest Years, and More

Thursday, April 24, 2025
Event City: 
Online
Event Description: 

The CLIVAR Research Focus on Tropical Basin Interaction is pleased to invite you to join its new webinar series, the third edition by invited speakers
Dr. Shang-Ping Xie (Scripps/UCSD).

Understanding Extreme Climate Events: 2023-24 El Niño, Hottest Years, and More
When? April 24, 2025 at 00:00 UTC 
Where? GoTo Meeting App - Link

You can watch the recording here.

Abstract

2023 was the hottest year on record by then for global-mean temperature, beating the previous instrumental record by a large margin. The year opened with extreme ocean warming, heavy rainfall, and an unprecedented cyclone Yaku off the Peruvian coast in March. A strong basin-scale El Niño then developed. This El Niño event was unusual for its combination of strong oceanic warming but muted atmospheric responses, particularly in terms of the Southern Oscillation and wind anomalies over the tropical Pacific. This discrepancy is perplexing given the historically close coupling of El Niño and the Southern Oscillation. We ask two mutually related questions: 
Meteorologically, why were the zonal wind anomalies weak over the equatorial Pacific in 2023 despite a growing El Nino? Atmospheric model simulations show that sea surface temperature anomalies in other ocean basins suppress the Southern Oscillation, indicating the importance of trans-basin interactions. 
Oceanographically, how did El Nino grow despite the lack of zonal wind anomalies over the tropical Pacific? A novel hindcast system we developed for equatorial ocean variability shows that the strong buildup of ocean heat content in the western Pacific associated with the preceding prolonged La Niña caused the growth of El Niño warming through wave dynamics and thermocline feedback, even without wind stress feedback during much of 2023. 
Each El Niño is different. Scrutinizing each unique El Niño will deepen and enrich our understanding of tropical variability and predictability. 

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