Improving Forecast Accuracy With Tsunami Data Assimilation: The 2009 Dusky Sound, New Zealand, Tsunami
Supporting Files
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2019
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Source JGR Solid Earth (2019). 124(1): 566-577
Sheehan, A. F., Gusman, A. R., & Satake, K. (2019). Improving Forecast Accuracy With Tsunami Data Assimilation: The 2009 Dusky Sound, New Zealand, Tsunami. Journal Of Geophysical Research: Solid Earth, 124(1). https://doi.org/10.1029/2018JB016575
Sheehan, Anne F., Aditya R. Gusman, and Kenji Satake. "Improving Forecast Accuracy With Tsunami Data Assimilation: The 2009 Dusky Sound, New Zealand, Tsunami." Journal Of Geophysical Research: Solid Earth 124, no. 1 (2019). https://doi.org/10.1029/2018JB016575.
Sheehan, Anne F., et al. "Improving Forecast Accuracy With Tsunami Data Assimilation: The 2009 Dusky Sound, New Zealand, Tsunami." Journal Of Geophysical Research: Solid Earth, vol. 124, no. 1, 2019. NOAA IR. https://doi.org/10.1029/2018JB016575.
Details
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Journal Title:Journal Of Geophysical Research: Solid Earth
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Description:We use tsunami waveforms recorded on deep water absolute pressure gauges (Deep‐ocean Assessment and Reporting of Tsunamis), coastal tide gauges, and a temporary array of seafloor differential pressure gauges (DPG) to study the tsunami generated by the 15 July 2009 magnitude 7.8 Dusky Sound, New Zealand, earthquake. We first use tsunami waveform inversion applied to Deep‐ocean Assessment and Reporting of Tsunamis seafloor pressure gauge and coastal tide gauge data to estimate the fault slip distribution of the Dusky Sound earthquake. This fault slip estimate is then used to generate synthetic tsunami waveforms at each of the DPG sites. DPG instruments are unfortunately not well calibrated, but comparison of the synthetic tsunami waveforms to those observed at each DPG site allows us to determine an appropriate amplitude scaling to apply. We next use progressive data assimilation of the amplitude‐scaled DPG observations to retrospectively forecast the Dusky Sound tsunami wavefields and find a good match between forecast and observed tsunami wavefields at the Charleston tide gauge station on the west coast of New Zealand's South Island. While an advantage of the data assimilation method is that no initial condition is needed, we find that our forecast is improved by merging tsunami forward modeling from a rapid W‐phase earthquake source solution with the data assimilation method.
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Source:JGR Solid Earth (2019). 124(1): 566-577
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Rights Information:Other
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Main Document Checksum:urn:sha-512:b814d908c9b7137dbbc93eb6b30b287295eafdc7d1154485f13ca879b6eb8253b8607bb19ae21f2f8bb197d81949b0c5af5e6b6751332798962b1ec8178c7d9b
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Sheehan, A. F., Gusman, A. R., & Satake, K. (2019). Improving Forecast Accuracy With Tsunami Data Assimilation: The 2009 Dusky Sound, New Zealand, Tsunami. Journal Of Geophysical Research: Solid Earth, 124(1). https://doi.org/10.1029/2018JB016575
Sheehan, Anne F., Aditya R. Gusman, and Kenji Satake. "Improving Forecast Accuracy With Tsunami Data Assimilation: The 2009 Dusky Sound, New Zealand, Tsunami." Journal Of Geophysical Research: Solid Earth 124, no. 1 (2019). https://doi.org/10.1029/2018JB016575.
Sheehan, Anne F., et al. "Improving Forecast Accuracy With Tsunami Data Assimilation: The 2009 Dusky Sound, New Zealand, Tsunami." Journal Of Geophysical Research: Solid Earth, vol. 124, no. 1, 2019. NOAA IR. https://doi.org/10.1029/2018JB016575.
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