Data Assimilation for Tsunami Forecast With Ship‐Borne GNSS Data in the Cascadia Subduction Zone

Details

• Journal Title:
  Earth and Space Science
• Personal Author:
  Hossen, M. J. ; Mulia, Iyan E. ; Mencin, David ; Sheehan, Anne F.
• NOAA Program & Office:
  CIRES (Cooperative Institute for Research in Environmental Sciences)
• Description:
  An efficient and cost-effective near-field tsunami warning system is crucial for coastal communities. The existing tsunami forecasting system is based on offshore Deep-Ocean Assessment and Reporting of Tsunamis and Global Navigation Satellite System (GNSS) buoys which are not affordable for many countries. A potential cost-effective solution is to utilize position data from ships traveling in coastal and offshore regions. In this study, we examine the feasibility of using ship-borne GNSS data in tsunami forecasting. We carry out synthetic experiments by applying a data assimilation (DA) method with ship position (elevation and velocity) data. Our findings show that the DA method can recover the reference
• Keywords:
  Environmental Science (miscellaneous) General Earth And Planetary Sciences General Earth And Planetary Sciences General Earth And Planetary Sciences
• Source:
  Earth and Space Science, 8(3)
• DOI:
  https://doi.org/10.1029/2020ea001390
• ISSN:
  2333-5084 ; 2333-5084
• Format:
  PDF
• Publisher:
  American Geophysical Union (AGU)
• Document Type:
  Journal Article
• License:
  https://creativecommons.org/licenses/by/4.0/
• Rights Information:
  CC BY
• Compliance:
  Library
• Main Document Checksum:
  urn:sha256:ef7cd43cad759654b290a2eeb66a096240a5e7942bcfc654692e4c5e92560d84
• Download URL:
  https://repository.library.noaa.gov/view/noaa/53467/noaa_53467_DS1.pdf
• File Type:
  [PDF - 5.33 MB ]