Improving Forecast Accuracy With Tsunami Data Assimilation: The 2009 Dusky Sound, New Zealand, Tsunami
Advanced Search
Select up to three search categories and corresponding keywords using the fields to the right. Refer to the Help section for more detailed instructions.

Search our Collections & Repository

For very narrow results

When looking for a specific result

Best used for discovery & interchangable words

Recommended to be used in conjunction with other fields



Document Data
Clear All
Clear All

For additional assistance using the Custom Query please check out our Help Page


Improving Forecast Accuracy With Tsunami Data Assimilation: The 2009 Dusky Sound, New Zealand, Tsunami

Filetype[PDF-2.16 MB]


  • Journal Title:
    Journal Of Geophysical Research: Solid Earth
  • Personal Author:
  • NOAA Program & Office:
  • 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.
  • Keywords:
  • Source:
    JGR Solid Earth (2019). 124(1): 566-577
  • DOI:
  • Document Type:
  • Rights Information:
  • Compliance:
  • Main Document Checksum:
  • Download URL:
  • File Type:

Supporting Files

More +

Related Documents