Hurricane annual cycle controlled by both seeds and genesis probability

Understanding tropical cyclone (TC) climatology is a problem of profound societal significance and deep scientific interest. The annual cycle is the biggest radiatively forced signal in TC variability, presenting a key test of our understanding and modeling of TC activity. TCs over the North Atlanti...

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Published in:Proceedings of the National Academy of Sciences
Main Authors: Yang, Wenchang, Hsieh, Tsung-Lin, Vecchi, Gabriel A.
Format: Text
Language:English
Published: National Academy of Sciences 2021
Subjects:
Online Access:http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8522279/
http://www.ncbi.nlm.nih.gov/pubmed/34611020
https://doi.org/10.1073/pnas.2108397118
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spelling ftpubmed:oai:pubmedcentral.nih.gov:8522279 2023-05-15T17:33:18+02:00 Hurricane annual cycle controlled by both seeds and genesis probability Yang, Wenchang Hsieh, Tsung-Lin Vecchi, Gabriel A. 2021-10-12 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8522279/ http://www.ncbi.nlm.nih.gov/pubmed/34611020 https://doi.org/10.1073/pnas.2108397118 en eng National Academy of Sciences http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8522279/ http://www.ncbi.nlm.nih.gov/pubmed/34611020 http://dx.doi.org/10.1073/pnas.2108397118 Copyright © 2021 the Author(s). Published by PNAS. https://creativecommons.org/licenses/by-nc-nd/4.0/This open access article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND) (https://creativecommons.org/licenses/by-nc-nd/4.0/) . CC-BY-NC-ND Proc Natl Acad Sci U S A Physical Sciences Text 2021 ftpubmed https://doi.org/10.1073/pnas.2108397118 2021-10-31T00:29:17Z Understanding tropical cyclone (TC) climatology is a problem of profound societal significance and deep scientific interest. The annual cycle is the biggest radiatively forced signal in TC variability, presenting a key test of our understanding and modeling of TC activity. TCs over the North Atlantic (NA) basin, which are usually called hurricanes, have a sharp peak in the annual cycle, with more than half concentrated in only 3 mo (August to October), yet existing theories of TC genesis often predict a much smoother cycle. Here we apply a framework originally developed to study TC response to climate change in which TC genesis is determined by both the number of pre-TC synoptic disturbances (TC “seeds”) and the probability of TC genesis from the seeds. The combination of seeds and probability predicts a more consistent hurricane annual cycle, reproducing the compact season, as well as the abrupt increase from July to August in the NA across observations and climate models. The seeds-probability TC genesis framework also successfully captures TC annual cycles in different basins. The concise representation of the climate sensitivity of TCs from the annual cycle to climate change indicates that the framework captures the essential elements of the TC climate connection. Text North Atlantic PubMed Central (PMC) Sharp Peak ENVELOPE(-37.900,-37.900,-54.050,-54.050) Proceedings of the National Academy of Sciences 118 41
institution Open Polar
collection PubMed Central (PMC)
op_collection_id ftpubmed
language English
topic Physical Sciences
spellingShingle Physical Sciences
Yang, Wenchang
Hsieh, Tsung-Lin
Vecchi, Gabriel A.
Hurricane annual cycle controlled by both seeds and genesis probability
topic_facet Physical Sciences
description Understanding tropical cyclone (TC) climatology is a problem of profound societal significance and deep scientific interest. The annual cycle is the biggest radiatively forced signal in TC variability, presenting a key test of our understanding and modeling of TC activity. TCs over the North Atlantic (NA) basin, which are usually called hurricanes, have a sharp peak in the annual cycle, with more than half concentrated in only 3 mo (August to October), yet existing theories of TC genesis often predict a much smoother cycle. Here we apply a framework originally developed to study TC response to climate change in which TC genesis is determined by both the number of pre-TC synoptic disturbances (TC “seeds”) and the probability of TC genesis from the seeds. The combination of seeds and probability predicts a more consistent hurricane annual cycle, reproducing the compact season, as well as the abrupt increase from July to August in the NA across observations and climate models. The seeds-probability TC genesis framework also successfully captures TC annual cycles in different basins. The concise representation of the climate sensitivity of TCs from the annual cycle to climate change indicates that the framework captures the essential elements of the TC climate connection.
format Text
author Yang, Wenchang
Hsieh, Tsung-Lin
Vecchi, Gabriel A.
author_facet Yang, Wenchang
Hsieh, Tsung-Lin
Vecchi, Gabriel A.
author_sort Yang, Wenchang
title Hurricane annual cycle controlled by both seeds and genesis probability
title_short Hurricane annual cycle controlled by both seeds and genesis probability
title_full Hurricane annual cycle controlled by both seeds and genesis probability
title_fullStr Hurricane annual cycle controlled by both seeds and genesis probability
title_full_unstemmed Hurricane annual cycle controlled by both seeds and genesis probability
title_sort hurricane annual cycle controlled by both seeds and genesis probability
publisher National Academy of Sciences
publishDate 2021
url http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8522279/
http://www.ncbi.nlm.nih.gov/pubmed/34611020
https://doi.org/10.1073/pnas.2108397118
long_lat ENVELOPE(-37.900,-37.900,-54.050,-54.050)
geographic Sharp Peak
geographic_facet Sharp Peak
genre North Atlantic
genre_facet North Atlantic
op_source Proc Natl Acad Sci U S A
op_relation http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8522279/
http://www.ncbi.nlm.nih.gov/pubmed/34611020
http://dx.doi.org/10.1073/pnas.2108397118
op_rights Copyright © 2021 the Author(s). Published by PNAS.
https://creativecommons.org/licenses/by-nc-nd/4.0/This open access article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND) (https://creativecommons.org/licenses/by-nc-nd/4.0/) .
op_rightsnorm CC-BY-NC-ND
op_doi https://doi.org/10.1073/pnas.2108397118
container_title Proceedings of the National Academy of Sciences
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container_issue 41
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