Tsunami Data Assimilation for Early Warning (Hardback)

Chapter 1 Introduction 1.1 Tsunami Early Warning 1.2 Numerical Modeling of Tsunami Propagation 1.3 Tsunami Data Assimilation Approach 1.4 Network of Offshore Bottom Pressure Gauges 1.5 Real-time Tsunami Detection 1.6 Objectives Chapter 2 Green's Function-based Tsunami Data Assimilation (GFTDA) 2.1 Principles of GFTDA 2.2 Assimilation Process and Mathematical Equivalence 2.3 Validation Test-2012 Haida Gwaii Earthquake 2.4 Adoption of Linear Dispersive Model-2004 off the Kii Peninsula Earthquake 2.5 Application to Real-time Data-2015 Torishima Volcanic Tsunami Earthquake 2.6 Discussion Chapter 3 Tsunami Data Assimilation with Interpolated Virtual Stations 3.1 Linear Interpolation with Huygens-Fresnel Principle 3.2 Test with Synthetic Data-2004 Sumatra-Andaman Earthquake 3.3 Test with Real Data-2009 Dusky Sound Earthquake 3.4 Application to Far-field Event-2015 Illapel Earthquake 3.5 Discussion Chapter 4 Real-Time Tsunami Detection based on Ensemble Empirical Mode Decomposition (EEMD) 4.1 EEMD 4.2 Validation Test-2016 Fukushima Earthquake 4.3 Discussion Chapter 5 Real-time Tsunami Data Assimilation of S-net Pressure Gauge Records during the 2016 Fukushima Earthquake 5.1 Introduction 5.2 Data and Methods 5.3 Results 5.4 Discussion Chapter 6 Tsunami Early Warning System Using Data Assimilation of Offshore Data 6.1 Practical Implementation 6.2 Future Improvements Chapter 7 Summary

Author:

Yuchen Wang

Publisher:

Springer

Publication Date:

Oct 27, 2022

Number of pages:

NA pages

Language:

English

Binding:

Hardcover

ISBN-10:

9811973385

ISBN-13:

9789811973383