Yuchen Wang

(Author)

Tsunami Data Assimilation for Early Warning (2022)Hardcover - 2022, 27 October 2022

Tsunami Data Assimilation for Early Warning (2022)
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Part of Series
Springer Theses
Print Length
97 pages
Language
English
Publisher
Springer
Date Published
27 Oct 2022
ISBN-10
9811973385
ISBN-13
9789811973383

Description

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

Product Details

Author:
Yuchen Wang
Book Edition:
2022
Book Format:
Hardcover
Country of Origin:
NL
Date Published:
27 October 2022
Dimensions:
23.39 x 15.6 x 0.79 cm
ISBN-10:
9811973385
ISBN-13:
9789811973383
Language:
English
Location:
Singapore
Pages:
97
Publisher:
Weight:
340.19 gm

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