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Complex networks for tracking extreme rainfall during typhoons

Authors
/persons/resource/ugur.oeztuerk

Öztürk,  Ugur
Potsdam Institute for Climate Impact Research;

/persons/resource/Marwan

Marwan,  Norbert
Potsdam Institute for Climate Impact Research;

Korup,  O.
External Organizations;

Saito,  H.
External Organizations;

/persons/resource/agarwal

Agarwal,  Ankit
Potsdam Institute for Climate Impact Research;

Grossman,  M. J.
External Organizations;

Zaiki,  M.
External Organizations;

/persons/resource/Juergen.Kurths

Kurths,  Jürgen
Potsdam Institute for Climate Impact Research;

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Citation

Öztürk, U., Marwan, N., Korup, O., Saito, H., Agarwal, A., Grossman, M. J., Zaiki, M., Kurths, J. (2018): Complex networks for tracking extreme rainfall during typhoons. - Chaos, 28, 7, 075301.
https://doi.org/10.1063/1.5004480


Cite as: https://publications.pik-potsdam.de/pubman/item/item_22140
Abstract
Reconciling the paths of extreme rainfall with those of typhoons remains difficult despite advanced forecasting techniques. We use complex networks defined by a nonlinear synchronization measure termed event synchronization to track extreme rainfall over the Japanese islands. Directed networks objectively record patterns of heavy rain brought by frontal storms and typhoons but mask out contributions of local convective storms. We propose a radial rank method to show that paths of extreme rainfall in the typhoon season (August-November, ASON) follow the overall southwest-northeast motion of typhoons and mean rainfall gradient of Japan. The associated eye-of-the-typhoon tracks deviate notably and may thus distort estimates of heavy typhoon rainfall. We mainly found that the lower spread of rainfall tracks in ASON may enable better hindcasting than for westerly-fed frontal storms in June and July. Complex network is a special type of graph describing meaningful interactions of real life systems (e.g., social, biological); it is also a popular tool to investigate the spatiotemporal dynamics of climate systems, such as extreme precipitation. Tropical storms incur substantial losses each year, particularly in the western Pacific. Despite many advances in their monitoring and forecasting, the dynamics of extreme rainfall patterns remains partly unresolved. We use complex networks for investigating how extreme rainfall correlates in space and time during the passage of tropical storm over the Japanese archipelago. We found that the rainfall tracks consistently diverge from eye-of-the-typhoon tracks, while the mean difference in track azimuths decreases from frontal storm (June-July) to typhoon seasons (August-November). This outcome might increase the predictability of the extreme precipitation during the typhoon season