SCEC Project Details
SCEC Award Number | 20082 | View PDF | |||||
Proposal Category | Individual Proposal (Integration and Theory) | ||||||
Proposal Title | Global Earthquake Activity Rate Model | ||||||
Investigator(s) |
|
||||||
Other Participants | Peter Bird, Yan Kagan, Han Bao or other UCLA grad student | ||||||
SCEC Priorities | 5a, 5b, 5d | SCEC Groups | EFP, Seismology, Geodesy | ||||
Report Due Date | 03/15/2021 | Date Report Submitted | 03/15/2021 |
Project Abstract |
The 2015 global earthquake forecast, now being tested using CSEP protocols, is based in part on a Smoothed Seismicity model written by our teammate Yan Kagan. Its input is a global catalog of earthquake locations and magnitudes; its output is estimated earthquake rate density in each of 6,480,000 cells on a 0.1 by 0.1 deg. grid. While the program has worked extremely well, better accessibility and faster performance require that it be reproduced and commented in modern coding language. Han Bao, a UCLA grad student on our team, has written a Python code that does that, and he has tested the agreement between the old Fortran and new Python codes. Comparison would ideally involve using the same input earthquake catalog and parameter settings, expecting identical output. Unfortunately, the GCMT catalog used in the original forecast submitted to CSEP has not been adequately archived, nor have the catalog selection parameters such as maximum depth and magnitude type. Thus comparison required searching many older manuscripts and some trial and error. Furthermore the different coding languages differ in their treatment of functions such as arctangent and their methods for random number generation. |
Intellectual Merit | Our project explores the extent to which prior earthquake forecasts, based on common assumptions, agree with earthquake occurrence before and after the forecasts, contributing to the understanding of earthquake processes. By developing a global forecast we have the ability to test common assumptions such as variability of earthquake rates with tectonic style, dependence of rates on previous history, and comparison of seismic moment rates with tectonic moment rates. Effectively, we are able to trade space for time. We can also develop and employ statistical models using adequate data, not possible for limited regions. |
Broader Impacts | Our research affects seismic hazard and risk estimation, with implications for public safety, risk management, and public policy. We’ve presented our results to students and faculty at universities, including UCLA, UC Riverside, ETH Zurich, EFZ Potsdam, Victoria Univerity Wellington, and at SCEC Annual meetings, showing how Physics, Geology, Geodesy, and Statistics can be combined to solve real world problems. We’ve discussed our analysis with students and faculty in Statistics, showing them applications and encouraging their participation in seismological research. |
Exemplary Figure | Figure 4. Normalized cumulative earthquake rates for magnitude 5.767 + (blue) and magnitude 7+ (red). Cells are sorted in decreasing order of forecast rate, so more active locations are on the left. Agreement between the red and blue curves, especially on the left, indicates that larger earthquake are well forecast by previous smaller ones. |
Linked Publications
Add missing publication or edit citation shown. Enter the SCEC project ID to link publication. |