Articles | Volume 10, issue 6
https://doi.org/10.5194/nhess-10-1085-2010
© Author(s) 2010. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/nhess-10-1085-2010
© Author(s) 2010. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
A new multi-sensor approach to simulation assisted tsunami early warning
J. Behrens
Alfred Wegener Institute for Polar and Marine Research, Bremerhaven, Germany
now at: University of Hamburg, KlimaCampus, Hamburg, Germany
A. Androsov
Alfred Wegener Institute for Polar and Marine Research, Bremerhaven, Germany
A. Y. Babeyko
GFZ German Research Centre for Geosciences, Potsdam, Germany
S. Harig
Alfred Wegener Institute for Polar and Marine Research, Bremerhaven, Germany
F. Klaschka
Alfred Wegener Institute for Polar and Marine Research, Bremerhaven, Germany
L. Mentrup
Alfred Wegener Institute for Polar and Marine Research, Bremerhaven, Germany
now at: GCN Consulting GmbH, Bregenz, Austria
Viewed
Total article views: 3,555 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 01 Feb 2013)
HTML | XML | Total | BibTeX | EndNote | |
---|---|---|---|---|---|
2,004 | 1,428 | 123 | 3,555 | 159 | 110 |
- HTML: 2,004
- PDF: 1,428
- XML: 123
- Total: 3,555
- BibTeX: 159
- EndNote: 110
Cited
34 citations as recorded by crossref.
- Tsunami hazard and exposure on the global scale F. Løvholt et al. 10.1016/j.earscirev.2011.10.002
- Tailoring spatial reference in early warning systems to administrative units M. Lendholt 10.1007/s12145-010-0075-y
- Comparing source inversion techniques for GPS‐based local tsunami forecasting: A case study for the April 2014 M8.1 Iquique, Chile, earthquake K. Chen et al. 10.1002/2016GL068042
- Tsunami risk management for crustal earthquakes and non-seismic sources in Italy J. Selva et al. 10.1007/s40766-021-00016-9
- A parallel machine learning-based approach for tsunami waves forecasting using regression trees E. Cesario et al. 10.1016/j.comcom.2024.07.016
- Machine learning-based tsunami inundation prediction derived from offshore observations I. Mulia et al. 10.1038/s41467-022-33253-5
- Tsunamigenic Analysis in and around Makran K. Rehman et al. 10.1080/13632469.2014.982835
- Real-time forecasting of near-field tsunami waveforms at coastal areas using a regularized extreme learning machine I. Mulia et al. 10.1016/j.coastaleng.2015.11.010
- Sequential Bayesian Update to Detect the Most Likely Tsunami Scenario Using Observational Wave Sequences R. Nomura et al. 10.1029/2021JC018324
- Probabilistic tsunami forecasting for early warning J. Selva et al. 10.1038/s41467-021-25815-w
- Earth observation applications for coastal sustainability: potential and challenges for implementation E. Politi et al. 10.1139/anc-2018-0015
- Addressing administrative units in international tsunami early warning systems: shortcomings in international geocode standards M. Lendholt & M. Hammitzsch 10.1080/17538947.2011.584574
- A human-centered design approach: design a new evacuation alarm system for building fire emergency considering the influence of pre-emergency activity Z. Wang et al. 10.1080/1463922X.2023.2166144
- Operational tsunami modelling with TsunAWI – recent developments and applications N. Rakowsky et al. 10.5194/nhess-13-1629-2013
- Real-time earthquake monitoring at the Indian Tsunami Early Warning System for tsunami advisories in the Indian Ocean E. Devi et al. 10.1177/1759313115623164
- New computational methods in tsunami science J. Behrens & F. Dias 10.1098/rsta.2014.0382
- Real‐time, reliable magnitudes for large earthquakes from 1 Hz GPS precise point positioning: The 2011 Tohoku‐Oki (Japan) earthquake T. Wright et al. 10.1029/2012GL051894
- A New Tool for Inundation Modeling: Community Modeling Interface for Tsunamis (ComMIT) V. Titov et al. 10.1007/s00024-011-0292-4
- Machine Learning for Tsunami Waves Forecasting Using Regression Trees E. Cesario et al. 10.1016/j.bdr.2024.100452
- User interface prototype for geospatial early warning systems – a tsunami showcase M. Hammitzsch et al. 10.5194/nhess-12-555-2012
- Multi-Disciplinary Approaches to Intelligently Sharing Large-Volumes of Real-Time Sensor Data During Natural Disasters S. Middleton et al. 10.2481/dsj.WDS-018
- A Multiple-Parameter Methodology for Placement of Tsunami Sensor Networks J. Meza et al. 10.1007/s00024-019-02381-3
- User Needs Analysis for the Definition of Operational Coastal Services S. Geraldini et al. 10.3390/w13010092
- Physical applications of GPS geodesy: a review Y. Bock & D. Melgar 10.1088/0034-4885/79/10/106801
- Remote sensing for Marine Spatial Planning and Integrated Coastal Areas Management: Achievements, challenges, opportunities and future prospects W. Ouellette & W. Getinet 10.1016/j.rsase.2016.07.003
- E-DECIDER: Using Earth Science Data and Modeling Tools to Develop Decision Support for Earthquake Disaster Response M. Glasscoe et al. 10.1007/s00024-014-0824-9
- Should tsunami simulations include a nonzero initial horizontal velocity? G. Lotto et al. 10.1186/s40623-017-0701-8
- Instant tsunami early warning based on real-time GPS – Tohoku 2011 case study A. Hoechner et al. 10.5194/nhess-13-1285-2013
- Faster Than Real Time Tsunami Warning with Associated Hazard Uncertainties D. Giles et al. 10.3389/feart.2020.597865
- Bayesian networks for tsunami early warning L. Blaser et al. 10.1111/j.1365-246X.2011.05020.x
- Tsunami risk communication and management: Contemporary gaps and challenges I. Rafliana et al. 10.1016/j.ijdrr.2021.102771
- Performance Assessment of the Cloud for Prototypical Instant Computing Approaches in Geoscientific Hazard Simulations J. Behrens et al. 10.3389/feart.2022.762768
- Development of tsunami early warning systems and future challenges J. Wächter et al. 10.5194/nhess-12-1923-2012
- Long-period surface motion of the multipatch Mw9.0 Tohoku-Oki earthquake P. Psimoulis et al. 10.1093/gji/ggu302
Latest update: 21 Nov 2024
Altmetrics