Data Assimilation for Tsunami Forecast With Ship‐Borne GNSS Data in the Cascadia Subduction Zone
Data Assimilation for Tsunami Forecast With Ship‐Borne GNSS Data in the Cascadia Subduction Zone
复制标题
利用卡斯卡迪亚俯冲带船载 GNSS 数据进行海啸预报的数据同化
DOI:
10.1029/2020ea001390
复制
发表时间:
2021
影响因子:
3.1
通讯作者:
Sheehan, Anne F.
中科院分区:
文献类型:
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作者:
Hossen, M. J.;Mulia, Iyan E.;Mencin, David;Sheehan, Anne F.
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 model with high accuracy if a dense network of ship elevation data is used. However, the use of ship velocity data alone is unable to recover the reference model. In addition, we carried out sensitivity studies of the DA method to the ship spatial distribution. We find that a 20 km gap between the ships works well in terms of accuracy and computational time for the example source model that we explored. The highest accuracy is obtained when data from a sufficient number of ships traveling in and around the tsunami source area are available.
DOI:
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发表时间:
2012
期刊:
影响因子:
--
作者:
J. Foster;B. Brooks;Dailin Wang;G. Carter;M. Merrifield
通讯作者:
M. Merrifield
DOI:
--
发表时间:
1993
期刊:
影响因子:
--
作者:
F. Bouttier;J. Mahfouf;J. Noilhan
通讯作者:
J. Noilhan
DOI:
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发表时间:
1991
期刊:
影响因子:
--
作者:
N. Shuto
通讯作者:
N. Shuto