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1
Introduction
2
Presentation
3
System Science
4
Earthquake System Science
5
Earthquakes are Complex
6
The Need for Better Operational Earthquake Forecasting
7
International Commission on Earthquake Forecasting
8
Prediction vs Forecasting
9
Diagnostic Precursors
10
Reliable Schemes
11
model types
12
Longterm forecasting
13
Stress renewal models
14
Earthquake simulators
15
Aftershocks
16
Canterbury Earthquake
17
Trisecuence
18
Aftershock Sequence Model
19
Long Term Models
20
Renewal Models
21
Medium Term Forecasting Gap
22
California Earthquake Models
23
Reed Renewal Model
24
Short Term Earthquake Probability Map
25
Uniform California Earthquake Probability Model
26
Earthquake Simulator
27
Simulation
28
Forecast Validation
29
CSEPS
30
Operational Use
31
Simulation Capability
32
System Model
33
Hazard Maps
34
Cyber Shake
35
Basin Effects
36
Timedependent Hazard Models
37
Example Calculation
38
Summary
39
Discussion
Description:
Explore earthquake forecasting as a complex system-science problem in this AGU Fall Meeting Gutenberg Lecture. Delve into the challenges of predicting seismic events and the evolution of probabilistic seismic hazard models. Learn about recent advancements in earthquake system science, including the development of time-dependent probability models and deterministic earthquake simulators. Examine the integration of various constraints on earthquake location, magnitude, and frequency into hazard assessments. Discover how high-performance computational platforms are enabling more accurate physics-based models for ground motion prediction. Investigate the complexities of reconciling long-term stress renewal processes with short-term seismic clustering. Gain insights into outstanding issues in the field, such as data assimilation and rupture directivity forecasting, and their impact on ground motion predictions and overall seismic hazard assessment.

Earthquake Forecasting as a System-Science Problem - Gutenberg Lecture

AGU
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