Document Type
Conference Proceeding
Publication Date
7-2024
Abstract
Heatwaves are influenced significantly by El Niño-Southern Oscillation (ENSO), which alters temperature and precipitation patterns throughout the world. Since 2020, we have witnessed a "triple dip" La Niña conditions persisting for three consecutive years resulting in severe weather and climate driven events globally. In this study, we identified the dominant frequency of Niño 3.4 Sea Surface Temperature (SST) signals and correlated them with regions experiencing unprecedented heat waves in 2022, namely, the Indian Ocean, the North Atlantic around England and Spain, and the Mediterranean Sea. The signal's power spectrum and its three highest power components are determined based on the signal's Singular Spectrum Analysis (SSA) for each region. Furthermore, the power spectrum coherence (PSC) of Niño 3.4 and other study regions is obtained to determine whether ENSO and heatwaves are linked. We find that Niño 3.4 and the Indian Ocean have the same dominant frequency for the highest power received, indicating ENSO's influence on the Indian heat wave. Additionally, we discovered that in March 2022, the Jet stream is essential in bringing warm Arctic waves southward, passing through Niño 3.4 and India. Furthermore, we found that no other region shared the dominant frequency of the Niño 3.4 region.
Recommended Citation
S. Perera, J. B. Fisher, M. Allali and H. El-Askary, "Linkages of the 2022 Unprecedented Global Heatwave Events to Triple-Dip La Niña," IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium, Athens, Greece, 2024, pp. 525-528, https://doi.org/10.1109/IGARSS53475.2024.10641697.
Peer Reviewed
1
Copyright
© 2024 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Included in
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Comments
This is a pre-copy-editing, author-produced PDF of an article accepted for publication in the proceedings of the IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium in 2024 following peer review. This article may not exactly replicate the final published version. The definitive publisher-authenticated version is available online at https://doi.org/10.1109/IGARSS53475.2024.10641697