The Influence of Five Teleconnection Patterns on Wintertime Extratropical Cyclones over Northwest Pacific

Extratropical cyclones (ETCs) over the Northwest Pacific are identified and tracked by applying an objective tracking algorithm to the 6-h time interval relative vorticity fields from the European Center for Medium-range Weather Forecasts (ECMWF) reanalysis data. A total of 2145 ETCs in the November...

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Main Authors: Naru Xie, Yidi Sun, Meng Gao
Format: Article
Language:English
Published: MDPI AG 2020-11-01
Series:Atmosphere
Subjects:
Online Access:https://www.mdpi.com/2073-4433/11/11/1248
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author Naru Xie
Yidi Sun
Meng Gao
author_facet Naru Xie
Yidi Sun
Meng Gao
author_sort Naru Xie
collection DOAJ
description Extratropical cyclones (ETCs) over the Northwest Pacific are identified and tracked by applying an objective tracking algorithm to the 6-h time interval relative vorticity fields from the European Center for Medium-range Weather Forecasts (ECMWF) reanalysis data. A total of 2145 ETCs in the November–February winters for the period of 1979–2018 were identified. First, by comparing the ETC track densities in the two periods 1979–1998 and 1999–2018, a significant difference in ETC track density was detected over the Japan Sea, Japan, and North Pacific. Next, the influence of five teleconnection patterns, the El Niño-Southern Oscillation (ENSO), Western Pacific (WP), North Atlantic Oscillation (NAO), Pacific/North American (PNA), and Pacific Decadal Oscillation (PDO) on the ETC track density was investigated by using composite analysis and correlation analysis. WP, NAO, and PDO patterns contributed more to the interannual variability of ETC track density, and higher cyclone densities usually occur in the negative phase of these teleconnection patterns. In contrast, the effects of ENSO and PNA were relatively weak. Finally, a Poisson generalized linear regression model for the ETC counts with respect to the five teleconnection indices was also developed for the purpose of linking all the teleconnection patterns with ETC activities over Northwest Pacific; and the Bayesian model averaging (BMA) procedure was used for model selection in the statistical modeling. The influence of the five teleconnection patterns on ETC track density was also verified in the regression model. The predicted winter ETC counts agreed well with the historical records during 1979–2018 over the Northwest Pacific.
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spelling doaj.art-ca5af1241da44eadaa543657ff15d9ac2023-11-20T21:35:09ZengMDPI AGAtmosphere2073-44332020-11-011111124810.3390/atmos11111248The Influence of Five Teleconnection Patterns on Wintertime Extratropical Cyclones over Northwest PacificNaru Xie0Yidi Sun1Meng Gao2Key Laboratory of Coastal Zone Environmental Processes and Ecological Remediation, Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Yantai 264003, ChinaKey Laboratory of Coastal Zone Environmental Processes and Ecological Remediation, Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Yantai 264003, ChinaKey Laboratory of Coastal Zone Environmental Processes and Ecological Remediation, Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Yantai 264003, ChinaExtratropical cyclones (ETCs) over the Northwest Pacific are identified and tracked by applying an objective tracking algorithm to the 6-h time interval relative vorticity fields from the European Center for Medium-range Weather Forecasts (ECMWF) reanalysis data. A total of 2145 ETCs in the November–February winters for the period of 1979–2018 were identified. First, by comparing the ETC track densities in the two periods 1979–1998 and 1999–2018, a significant difference in ETC track density was detected over the Japan Sea, Japan, and North Pacific. Next, the influence of five teleconnection patterns, the El Niño-Southern Oscillation (ENSO), Western Pacific (WP), North Atlantic Oscillation (NAO), Pacific/North American (PNA), and Pacific Decadal Oscillation (PDO) on the ETC track density was investigated by using composite analysis and correlation analysis. WP, NAO, and PDO patterns contributed more to the interannual variability of ETC track density, and higher cyclone densities usually occur in the negative phase of these teleconnection patterns. In contrast, the effects of ENSO and PNA were relatively weak. Finally, a Poisson generalized linear regression model for the ETC counts with respect to the five teleconnection indices was also developed for the purpose of linking all the teleconnection patterns with ETC activities over Northwest Pacific; and the Bayesian model averaging (BMA) procedure was used for model selection in the statistical modeling. The influence of the five teleconnection patterns on ETC track density was also verified in the regression model. The predicted winter ETC counts agreed well with the historical records during 1979–2018 over the Northwest Pacific.https://www.mdpi.com/2073-4433/11/11/1248extratropical cyclonesteleconnection patternscomposite analysisPoisson regressionBayesian model averaging
spellingShingle Naru Xie
Yidi Sun
Meng Gao
The Influence of Five Teleconnection Patterns on Wintertime Extratropical Cyclones over Northwest Pacific
Atmosphere
extratropical cyclones
teleconnection patterns
composite analysis
Poisson regression
Bayesian model averaging
title The Influence of Five Teleconnection Patterns on Wintertime Extratropical Cyclones over Northwest Pacific
title_full The Influence of Five Teleconnection Patterns on Wintertime Extratropical Cyclones over Northwest Pacific
title_fullStr The Influence of Five Teleconnection Patterns on Wintertime Extratropical Cyclones over Northwest Pacific
title_full_unstemmed The Influence of Five Teleconnection Patterns on Wintertime Extratropical Cyclones over Northwest Pacific
title_short The Influence of Five Teleconnection Patterns on Wintertime Extratropical Cyclones over Northwest Pacific
title_sort influence of five teleconnection patterns on wintertime extratropical cyclones over northwest pacific
topic extratropical cyclones
teleconnection patterns
composite analysis
Poisson regression
Bayesian model averaging
url https://www.mdpi.com/2073-4433/11/11/1248
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