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  A network-based comparative study of extreme tropical and frontal storm rainfall over Japan

Öztürk, U., Malik, N., Cheung, K., Marwan, N., Kurths, J. (2019): A network-based comparative study of extreme tropical and frontal storm rainfall over Japan. - Climate Dynamics, 53, 1-2, 521-532.
https://doi.org/10.1007/s00382-018-4597-1

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Öztürk, Ugur1, Author              
Malik, N.2, Author
Cheung, K.2, Author
Marwan, Norbert1, Author              
Kurths, Jürgen1, Author              
Affiliations:
1Potsdam Institute for Climate Impact Research, ou_persistent13              
2External Organizations, ou_persistent22              

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 Abstract: Frequent and intense rainfall events demand innovative techniques to better predict the extreme rainfall dynamics. This task requires essentially the assessment of the basic types of atmospheric processes that trigger extreme rainfall, and then to examine the differences between those processes, which may help to identify key patterns to improve predictive algorithms. We employ tools from network theory to compare the spatial features of extreme rainfall over the Japanese archipelago and surrounding areas caused by two atmospheric processes: the Baiu front, which occurs mainly in June and July (JJ), and the tropical storms from August to November (ASON). We infer from complex networks of satellite-derived rainfall data, which are based on the nonlinear correlation measure of event synchronization. We compare the spatial scales involved in both systems and identify different regions which receive rainfall due to the large spatial scale of the Baiu and tropical storm systems. We observed that the spatial scales involved in the Baiu driven rainfall extremes, including the synoptic processes behind the frontal development, are larger than tropical storms, which even have long tracks during extratropical transitions. We further delineate regions of coherent rainfall during the two seasons based on network communities, identifying the horizontal (east–west) rainfall bands during JJ over the Japanese archipelago, while during ASON these bands align with the island arc of Japan.

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 Dates: 2019
 Publication Status: Finally published
 Pages: -
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 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1007/s00382-018-4597-1
PIKDOMAIN: RD4 - Complexity Science
eDoc: 8487
Research topic keyword: Complex Networks
Research topic keyword: Atmosphere
Research topic keyword: Extremes
Research topic keyword: Weather
Model / method: Nonlinear Data Analysis
Regional keyword: Asia
Organisational keyword: RD4 - Complexity Science
Working Group: Development of advanced time series analysis techniques
Working Group: Network- and machine-learning-based prediction of extreme events
 Degree: -

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Title: Climate Dynamics
Source Genre: Journal, SCI, Scopus, p3
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Pages: - Volume / Issue: 53 (1-2) Sequence Number: - Start / End Page: 521 - 532 Identifier: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/journals77