Variability analysis of Kuroshio intrusion through Luzon Strait using growing hierarchical self-organizing map

I. Fong Tsui, Chau-Ron Wu

Research output: Contribution to journalArticle

26 Citations (Scopus)

Abstract

An advanced artificial neural network classification algorithm is applied to 18 years of gridded mean geostrophic velocity multi-satellite data to study the Kuroshio intrusion into the South China Sea through the Luzon Strait. The results suggest that the Kuroshio intrusion may occur year round. However, intrusion is not the major characteristic of the region. The intrusion mode occurs only 25.8 % of the time. Winter intrusion events are more frequent than summer events. Both stronger intrusion (which is related to wind speed) and weaker intrusion (which may be related to the upstream Kuroshio transport) may occur during winter, but stronger intrusion is dominant. In summer, the Kuroshio intrusion is almost the weaker type. The Kuroshio intrusion through the Luzon Strait usually occurs when the Pacific decadal oscillation index is positive (72.1 % of the time). This study shows that growing hierarchical self-organizing map is a useful tool for analyzing Kuroshio intrusion through the Luzon Strait.

Original languageEnglish
Pages (from-to)1187-1194
Number of pages8
JournalOcean Dynamics
Volume62
Issue number8
DOIs
Publication statusPublished - 2012 Aug 1

Fingerprint

strait
analysis
Pacific Decadal Oscillation
winter
summer
artificial neural network
satellite data
wind velocity

Keywords

  • Growing hierarchical self-organizing map (GHSOM)
  • Kuroshio intrusion
  • Luzon strait
  • Pacific decadal oscillation (PDO)

ASJC Scopus subject areas

  • Oceanography

Cite this

Variability analysis of Kuroshio intrusion through Luzon Strait using growing hierarchical self-organizing map. / Tsui, I. Fong; Wu, Chau-Ron.

In: Ocean Dynamics, Vol. 62, No. 8, 01.08.2012, p. 1187-1194.

Research output: Contribution to journalArticle

@article{e1eb4a6989634ba0982de43a2b98e214,
title = "Variability analysis of Kuroshio intrusion through Luzon Strait using growing hierarchical self-organizing map",
abstract = "An advanced artificial neural network classification algorithm is applied to 18 years of gridded mean geostrophic velocity multi-satellite data to study the Kuroshio intrusion into the South China Sea through the Luzon Strait. The results suggest that the Kuroshio intrusion may occur year round. However, intrusion is not the major characteristic of the region. The intrusion mode occurs only 25.8 {\%} of the time. Winter intrusion events are more frequent than summer events. Both stronger intrusion (which is related to wind speed) and weaker intrusion (which may be related to the upstream Kuroshio transport) may occur during winter, but stronger intrusion is dominant. In summer, the Kuroshio intrusion is almost the weaker type. The Kuroshio intrusion through the Luzon Strait usually occurs when the Pacific decadal oscillation index is positive (72.1 {\%} of the time). This study shows that growing hierarchical self-organizing map is a useful tool for analyzing Kuroshio intrusion through the Luzon Strait.",
keywords = "Growing hierarchical self-organizing map (GHSOM), Kuroshio intrusion, Luzon strait, Pacific decadal oscillation (PDO)",
author = "Tsui, {I. Fong} and Chau-Ron Wu",
year = "2012",
month = "8",
day = "1",
doi = "10.1007/s10236-012-0558-0",
language = "English",
volume = "62",
pages = "1187--1194",
journal = "Ocean Dynamics",
issn = "1616-7341",
publisher = "Springer Verlag",
number = "8",

}

TY - JOUR

T1 - Variability analysis of Kuroshio intrusion through Luzon Strait using growing hierarchical self-organizing map

AU - Tsui, I. Fong

AU - Wu, Chau-Ron

PY - 2012/8/1

Y1 - 2012/8/1

N2 - An advanced artificial neural network classification algorithm is applied to 18 years of gridded mean geostrophic velocity multi-satellite data to study the Kuroshio intrusion into the South China Sea through the Luzon Strait. The results suggest that the Kuroshio intrusion may occur year round. However, intrusion is not the major characteristic of the region. The intrusion mode occurs only 25.8 % of the time. Winter intrusion events are more frequent than summer events. Both stronger intrusion (which is related to wind speed) and weaker intrusion (which may be related to the upstream Kuroshio transport) may occur during winter, but stronger intrusion is dominant. In summer, the Kuroshio intrusion is almost the weaker type. The Kuroshio intrusion through the Luzon Strait usually occurs when the Pacific decadal oscillation index is positive (72.1 % of the time). This study shows that growing hierarchical self-organizing map is a useful tool for analyzing Kuroshio intrusion through the Luzon Strait.

AB - An advanced artificial neural network classification algorithm is applied to 18 years of gridded mean geostrophic velocity multi-satellite data to study the Kuroshio intrusion into the South China Sea through the Luzon Strait. The results suggest that the Kuroshio intrusion may occur year round. However, intrusion is not the major characteristic of the region. The intrusion mode occurs only 25.8 % of the time. Winter intrusion events are more frequent than summer events. Both stronger intrusion (which is related to wind speed) and weaker intrusion (which may be related to the upstream Kuroshio transport) may occur during winter, but stronger intrusion is dominant. In summer, the Kuroshio intrusion is almost the weaker type. The Kuroshio intrusion through the Luzon Strait usually occurs when the Pacific decadal oscillation index is positive (72.1 % of the time). This study shows that growing hierarchical self-organizing map is a useful tool for analyzing Kuroshio intrusion through the Luzon Strait.

KW - Growing hierarchical self-organizing map (GHSOM)

KW - Kuroshio intrusion

KW - Luzon strait

KW - Pacific decadal oscillation (PDO)

UR - http://www.scopus.com/inward/record.url?scp=84865687092&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84865687092&partnerID=8YFLogxK

U2 - 10.1007/s10236-012-0558-0

DO - 10.1007/s10236-012-0558-0

M3 - Article

VL - 62

SP - 1187

EP - 1194

JO - Ocean Dynamics

JF - Ocean Dynamics

SN - 1616-7341

IS - 8

ER -