Papers

Peer-reviewed
Dec, 2020

MOWLAS: NIED observation network for earthquake, tsunami and volcano

Earth, Planets and Space
  • Shin Aoi
  • ,
  • Youichi Asano
  • ,
  • Takashi Kunugi
  • ,
  • Takeshi Kimura
  • ,
  • Kenji Uehira
  • ,
  • Narumi Takahashi
  • ,
  • Hideki Ueda
  • ,
  • Katsuhiko Shiomi
  • ,
  • Takumi Matsumoto
  • ,
  • Hiroyuki Fujiwara

Volume
72
Number
1
Language
English
Publishing type
Research paper (scientific journal)
DOI
10.1186/s40623-020-01250-x
Publisher
Springer Science and Business Media LLC

<title>Abstract</title>
National Research Institute for Earth Science and Disaster Resilience (NIED) integrated the land observation networks established since the 1995 Kobe earthquake with the seafloor observation networks established since the 2011 Tohoku earthquake and tsunami as MOWLAS (Monitoring of Waves on Land and Seafloor) in November 2017. The purpose of MOWLAS is to provide comprehensive, accurate, and rapid observation and monitoring of earthquake, tsunami, and volcano events throughout Japan and its offshore areas. MOWLAS data are widely utilized for long-term earthquake forecasting, the monitoring of current seismic activity, seismic and tsunami hazard assessments, earthquake early warning, tsunami warning, and earthquake engineering, as well as earthquake science. Ocean bottom observations provide an extension of observations to areas where no people are living and have the advantage of increasing lead time of earthquake early warning and tsunami warning. The application of recent technology advancements to real-time observations as well as the processing of MOWLAS data has contributed to the direct disaster mitigation of ongoing earthquakes. These observations are fundamental for both science and disaster resilience, and thus it is necessary to continue ceaseless operation and maintenance.

Link information
DOI
https://doi.org/10.1186/s40623-020-01250-x
Web of Science
https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000567799700001&DestApp=WOS_CPL
URL
http://link.springer.com/content/pdf/10.1186/s40623-020-01250-x.pdf
URL
http://link.springer.com/article/10.1186/s40623-020-01250-x/fulltext.html
ID information
  • DOI : 10.1186/s40623-020-01250-x
  • eISSN : 1880-5981
  • Web of Science ID : WOS:000567799700001

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