Understanding future changes in tropical cyclogenesis using Self-Organizing Maps
Future changes in tropical cyclone (TC) genesis locations and frequency are explored by identifying relationships between TC genesis and dominant daily large-scale patterns, and evaluating the strength of these relationships under a climate change scenario. Self-Organizing Maps (SOMs) are used to ch...
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ftdoajarticles:oai:doaj.org/article:f1f5f0bdec3d450d891cd611b277a9b9 2023-05-15T17:33:27+02:00 Understanding future changes in tropical cyclogenesis using Self-Organizing Maps Abigail B. Jaye Cindy L. Bruyère James M. Done 2019-12-01T00:00:00Z https://doi.org/10.1016/j.wace.2019.100235 https://doaj.org/article/f1f5f0bdec3d450d891cd611b277a9b9 EN eng Elsevier http://www.sciencedirect.com/science/article/pii/S2212094719300301 https://doaj.org/toc/2212-0947 2212-0947 doi:10.1016/j.wace.2019.100235 https://doaj.org/article/f1f5f0bdec3d450d891cd611b277a9b9 Weather and Climate Extremes, Vol 26, Iss , Pp - (2019) Meteorology. Climatology QC851-999 article 2019 ftdoajarticles https://doi.org/10.1016/j.wace.2019.100235 2022-12-31T13:20:25Z Future changes in tropical cyclone (TC) genesis locations and frequency are explored by identifying relationships between TC genesis and dominant daily large-scale patterns, and evaluating the strength of these relationships under a climate change scenario. Self-Organizing Maps (SOMs) are used to characterize the dominant large-scale patterns in reanalysis data and in a regional climate model ensemble simulation of current climate. The main features on the resulting sea level pressure (SLP) SOMs are nodes that resemble both the negative and positive phases of the North Atlantic Oscillation, as well as blocking and ridging regimes. The frequency of the NAO-like nodes is strongly linked to TC genesis frequency and preferred genesis locations. This link is used to develop a statistical relationship between the frequency of large scale SLP patterns and TC genesis. The application of this relationship to an ensemble regional climate simulation under a future climate forcing scenario predicts fewer TCs, which is consistent with the regional climate model that explicitly simulates fewer TCs. This demonstrates the strength of the relationships and their use in assessing future changes in TC genesis locations and frequency. Keywords: Self-organizing maps, Tropical cyclones, WRF, Regional climate modeling Article in Journal/Newspaper North Atlantic North Atlantic oscillation Directory of Open Access Journals: DOAJ Articles Weather and Climate Extremes 26 100235 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
Meteorology. Climatology QC851-999 |
spellingShingle |
Meteorology. Climatology QC851-999 Abigail B. Jaye Cindy L. Bruyère James M. Done Understanding future changes in tropical cyclogenesis using Self-Organizing Maps |
topic_facet |
Meteorology. Climatology QC851-999 |
description |
Future changes in tropical cyclone (TC) genesis locations and frequency are explored by identifying relationships between TC genesis and dominant daily large-scale patterns, and evaluating the strength of these relationships under a climate change scenario. Self-Organizing Maps (SOMs) are used to characterize the dominant large-scale patterns in reanalysis data and in a regional climate model ensemble simulation of current climate. The main features on the resulting sea level pressure (SLP) SOMs are nodes that resemble both the negative and positive phases of the North Atlantic Oscillation, as well as blocking and ridging regimes. The frequency of the NAO-like nodes is strongly linked to TC genesis frequency and preferred genesis locations. This link is used to develop a statistical relationship between the frequency of large scale SLP patterns and TC genesis. The application of this relationship to an ensemble regional climate simulation under a future climate forcing scenario predicts fewer TCs, which is consistent with the regional climate model that explicitly simulates fewer TCs. This demonstrates the strength of the relationships and their use in assessing future changes in TC genesis locations and frequency. Keywords: Self-organizing maps, Tropical cyclones, WRF, Regional climate modeling |
format |
Article in Journal/Newspaper |
author |
Abigail B. Jaye Cindy L. Bruyère James M. Done |
author_facet |
Abigail B. Jaye Cindy L. Bruyère James M. Done |
author_sort |
Abigail B. Jaye |
title |
Understanding future changes in tropical cyclogenesis using Self-Organizing Maps |
title_short |
Understanding future changes in tropical cyclogenesis using Self-Organizing Maps |
title_full |
Understanding future changes in tropical cyclogenesis using Self-Organizing Maps |
title_fullStr |
Understanding future changes in tropical cyclogenesis using Self-Organizing Maps |
title_full_unstemmed |
Understanding future changes in tropical cyclogenesis using Self-Organizing Maps |
title_sort |
understanding future changes in tropical cyclogenesis using self-organizing maps |
publisher |
Elsevier |
publishDate |
2019 |
url |
https://doi.org/10.1016/j.wace.2019.100235 https://doaj.org/article/f1f5f0bdec3d450d891cd611b277a9b9 |
genre |
North Atlantic North Atlantic oscillation |
genre_facet |
North Atlantic North Atlantic oscillation |
op_source |
Weather and Climate Extremes, Vol 26, Iss , Pp - (2019) |
op_relation |
http://www.sciencedirect.com/science/article/pii/S2212094719300301 https://doaj.org/toc/2212-0947 2212-0947 doi:10.1016/j.wace.2019.100235 https://doaj.org/article/f1f5f0bdec3d450d891cd611b277a9b9 |
op_doi |
https://doi.org/10.1016/j.wace.2019.100235 |
container_title |
Weather and Climate Extremes |
container_volume |
26 |
container_start_page |
100235 |
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1766131962254196736 |