The persistent signature of tropical cyclones in ambient seismic noise
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ArticleDate
2017-12-28Online Publication Date
2017-12-28Print Publication Date
2018-02Permanent link to this record
http://hdl.handle.net/10754/626810
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The spectrum of ambient seismic noise shows strong signals associated with tropical cyclones, yet a detailed understanding of these signals and the relationship between them and the storms is currently lacking. Through the analysis of more than a decade of seismic data recorded at several stations located in and adjacent to the northwest Pacific Ocean, here we show that there is a persistent and frequency-dependent signature of tropical cyclones in ambient seismic noise that depends on characteristics of the storm and on the detailed location of the station relative to the storm. An adaptive statistical model shows that the spectral amplitude of ambient seismic noise, and notably of the short-period secondary microseisms, has a strong relationship with tropical cyclone intensity and can be employed to extract information on the tropical cyclones.Citation
Gualtieri L, Camargo SJ, Pascale S, Pons FME, Ekström G (2018) The persistent signature of tropical cyclones in ambient seismic noise. Earth and Planetary Science Letters 484: 287–294. Available: http://dx.doi.org/10.1016/j.epsl.2017.12.026.Sponsors
We thank the US Geological Survey (USGS) and the Incorporated Research Institutions for Seismology (IRIS) for providing openly available seismic data. L.G. acknowledges support from a Lamont–Doherty Earth Observatory Postdoctoral Fellowship. L.G. also acknowledges partial support for this work from Princeton University and King Abdullah University of Science and Technology. S.J.C. acknowledges support from NOAA grants NA15OAR4310095 and NA16OAR4310079. S.P. was supported by the NOAA CICS grant NA14OAR4320106. We would like to thank John Knaff (NOAA) for making the tropical cyclone size data available for this study. We also wish to acknowledge the editor Peter Shearer and the two anonymous reviewers, whose comments helped us to improve the manuscript. This is the Lamont–Doherty Contribution Number 8172.Publisher
Elsevier BVae974a485f413a2113503eed53cd6c53
10.1016/j.epsl.2017.12.026