A network-based comparative study of extreme tropical and frontal storm rainfall over Japan
- 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 BaiuFrequent 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.…
Verfasserangaben: | Ugur OzturkORCiDGND, Nishant MalikORCiD, Kevin CheungORCiD, Norbert MarwanORCiDGND, Jürgen KurthsORCiDGND |
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DOI: | https://doi.org/10.1007/s00382-018-4597-1 |
ISSN: | 0930-7575 |
ISSN: | 1432-0894 |
Titel des übergeordneten Werks (Englisch): | Climate dynamics : observational, theoretical and computational research on the climate system |
Verlag: | Springer |
Verlagsort: | New York |
Publikationstyp: | Wissenschaftlicher Artikel |
Sprache: | Englisch |
Datum der Erstveröffentlichung: | 09.01.2019 |
Erscheinungsjahr: | 2019 |
Datum der Freischaltung: | 18.01.2021 |
Freies Schlagwort / Tag: | Baiu; Complex networks; Event synchronization; Extreme rainfall; Tropical storms |
Band: | 53 |
Ausgabe: | 1-2 |
Seitenanzahl: | 12 |
Erste Seite: | 521 |
Letzte Seite: | 532 |
Fördernde Institution: | Deutsche Forschungsgemeinschaft within the Research Training Group "Natural Hazards and Risks in a Changing World (NatRiskChange)" at the University of Potsdam [DFG GRK 2043/1]; Federal Ministry of Education and Research (BMBF) within the project CLIENT II-CaTeNAFederal Ministry of Education & Research (BMBF) [FKZ 03G0878A] |
Organisationseinheiten: | Mathematisch-Naturwissenschaftliche Fakultät / Institut für Geowissenschaften |
DDC-Klassifikation: | 5 Naturwissenschaften und Mathematik / 55 Geowissenschaften, Geologie / 550 Geowissenschaften |
Peer Review: | Referiert |