Improving Forecast Accuracy With Tsunami Data Assimilation: The 2009 Dusky Sound, New Zealand, Tsunami. Issue 1 (10th January 2019)

• Record Type: Journal Article
• Authors: Sheehan, Anne F.; Gusman, Aditya R.; Satake, Kenji
• Is Part Of: Journal of geophysical research. Volume 124:Issue 1(2019)
• Page Start: 566
• Page End: 577
• Publication Date: 2019-01-10
• Subjects: tsunami -- Dusky Sound -- data assimilation -- seafloor pressure -- ocean bottom seismometer -- earthquake; Geomagnetism -- Periodicals; Geochemistry -- Periodicals; Geophysics -- Periodicals; Earth sciences -- Periodicals; 551.1
• DOI: 10.1029/2018JB016575
• Languages: English
• ISSNs: 2169-9313

Abstract

Abstract: 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. Plain Language Summary: Most tsunami warnings rely on first locating and determining size of a large earthquake and then using a computer model to estimate the size and timing of the resulting tsunami. Seafloor pressure gauges can also provide important data for studying tsunamis. Seafloor pressure increases as the peak of a tsunami wave passes overhead due to the increase in the height of the water column. In cases where a dense array of seafloor pressure gauges is available, a new "data assimilation" method can be applied to estimate the tsunami using the observations of pressure changes. In this paper we apply the data assimilation method to the tsunami generated from the 2009 Dusky Sound, New Zealand, magnitude 7.8 earthquake and determine a rapid and accurate estimate of the tsunami wave arrival time and size along the west coast of New Zealand. We next merge the two methods—first using a computer model to estimate the tsunami given information about the earthquake and then using seafloor pressure observations to refine the tsunami model—and find that the tsunami forecast accuracy is further improved. Studies such as this are important to test and further develop rapid and accurate tsunami warning systems. Key Points: Tsunami source for 2009 Dusky Sound, New Zealand, earthquake is determined using sparse deep water absolute pressure gauge and coastal tide gauge data Assimilation of tsunami data from dense array of seafloor differential pressure gauges is used in simulation of rapid forecast of 2009 Dusky Sound tsunami Improvement of tsunami forecast is found by merging forward computation from rapid earthquake W‐phase model with tsunami data assimilation