Seasonal predictions of summer compound humid heat extremes in the southeastern United States driven by sea surface temperatures
Abstract Humid heat extreme (HHE) is a type of compound extreme weather event that poses severe risks to human health. Skillful forecasts of HHE months in advance are crucial for developing strategies to enhance community resilience to extreme events1,2. This study demonstrates that the frequency of...
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ftdoajarticles:oai:doaj.org/article:470cdf2c05e64bda9daa571cdbfc1259 2024-09-09T19:57:08+00:00 Seasonal predictions of summer compound humid heat extremes in the southeastern United States driven by sea surface temperatures Liwei Jia Thomas L. Delworth Xiaosong Yang William Cooke Nathaniel C. Johnson Liping Zhang Youngji Joh Feiyu Lu Colleen McHugh 2024-08-01T00:00:00Z https://doi.org/10.1038/s41612-024-00723-0 https://doaj.org/article/470cdf2c05e64bda9daa571cdbfc1259 EN eng Nature Portfolio https://doi.org/10.1038/s41612-024-00723-0 https://doaj.org/toc/2397-3722 doi:10.1038/s41612-024-00723-0 2397-3722 https://doaj.org/article/470cdf2c05e64bda9daa571cdbfc1259 npj Climate and Atmospheric Science, Vol 7, Iss 1, Pp 1-9 (2024) Environmental sciences GE1-350 Meteorology. Climatology QC851-999 article 2024 ftdoajarticles https://doi.org/10.1038/s41612-024-00723-0 2024-08-12T15:24:01Z Abstract Humid heat extreme (HHE) is a type of compound extreme weather event that poses severe risks to human health. Skillful forecasts of HHE months in advance are crucial for developing strategies to enhance community resilience to extreme events1,2. This study demonstrates that the frequency of summertime HHE in the southeastern United States (SEUS) can be skillfully predicted 0–1 months in advance using the SPEAR (Seamless system for Prediction and EArth system Research) seasonal forecast system. Sea surface temperatures (SSTs) in the tropical North Atlantic (TNA) basin are identified as the primary driver of this prediction skill. The responses of large-scale atmospheric circulation and winds to anomalous warm SSTs in the TNA favor the transport of heat and moisture from the Gulf of Mexico to the SEUS. This research underscores the role of slowly varying sea surface conditions in modifying large-scale environments, thereby contributing to the skillful prediction of HHE in the SEUS. The results of this study have potential applications in the development of early warning systems for HHE. Article in Journal/Newspaper North Atlantic Directory of Open Access Journals: DOAJ Articles npj Climate and Atmospheric Science 7 1 |
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Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
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ftdoajarticles |
language |
English |
topic |
Environmental sciences GE1-350 Meteorology. Climatology QC851-999 |
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Environmental sciences GE1-350 Meteorology. Climatology QC851-999 Liwei Jia Thomas L. Delworth Xiaosong Yang William Cooke Nathaniel C. Johnson Liping Zhang Youngji Joh Feiyu Lu Colleen McHugh Seasonal predictions of summer compound humid heat extremes in the southeastern United States driven by sea surface temperatures |
topic_facet |
Environmental sciences GE1-350 Meteorology. Climatology QC851-999 |
description |
Abstract Humid heat extreme (HHE) is a type of compound extreme weather event that poses severe risks to human health. Skillful forecasts of HHE months in advance are crucial for developing strategies to enhance community resilience to extreme events1,2. This study demonstrates that the frequency of summertime HHE in the southeastern United States (SEUS) can be skillfully predicted 0–1 months in advance using the SPEAR (Seamless system for Prediction and EArth system Research) seasonal forecast system. Sea surface temperatures (SSTs) in the tropical North Atlantic (TNA) basin are identified as the primary driver of this prediction skill. The responses of large-scale atmospheric circulation and winds to anomalous warm SSTs in the TNA favor the transport of heat and moisture from the Gulf of Mexico to the SEUS. This research underscores the role of slowly varying sea surface conditions in modifying large-scale environments, thereby contributing to the skillful prediction of HHE in the SEUS. The results of this study have potential applications in the development of early warning systems for HHE. |
format |
Article in Journal/Newspaper |
author |
Liwei Jia Thomas L. Delworth Xiaosong Yang William Cooke Nathaniel C. Johnson Liping Zhang Youngji Joh Feiyu Lu Colleen McHugh |
author_facet |
Liwei Jia Thomas L. Delworth Xiaosong Yang William Cooke Nathaniel C. Johnson Liping Zhang Youngji Joh Feiyu Lu Colleen McHugh |
author_sort |
Liwei Jia |
title |
Seasonal predictions of summer compound humid heat extremes in the southeastern United States driven by sea surface temperatures |
title_short |
Seasonal predictions of summer compound humid heat extremes in the southeastern United States driven by sea surface temperatures |
title_full |
Seasonal predictions of summer compound humid heat extremes in the southeastern United States driven by sea surface temperatures |
title_fullStr |
Seasonal predictions of summer compound humid heat extremes in the southeastern United States driven by sea surface temperatures |
title_full_unstemmed |
Seasonal predictions of summer compound humid heat extremes in the southeastern United States driven by sea surface temperatures |
title_sort |
seasonal predictions of summer compound humid heat extremes in the southeastern united states driven by sea surface temperatures |
publisher |
Nature Portfolio |
publishDate |
2024 |
url |
https://doi.org/10.1038/s41612-024-00723-0 https://doaj.org/article/470cdf2c05e64bda9daa571cdbfc1259 |
genre |
North Atlantic |
genre_facet |
North Atlantic |
op_source |
npj Climate and Atmospheric Science, Vol 7, Iss 1, Pp 1-9 (2024) |
op_relation |
https://doi.org/10.1038/s41612-024-00723-0 https://doaj.org/toc/2397-3722 doi:10.1038/s41612-024-00723-0 2397-3722 https://doaj.org/article/470cdf2c05e64bda9daa571cdbfc1259 |
op_doi |
https://doi.org/10.1038/s41612-024-00723-0 |
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npj Climate and Atmospheric Science |
container_volume |
7 |
container_issue |
1 |
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1809928026437189632 |