Array Response Functions with ArrayGUI Nawa Dahal Robert Martin-Short Sharmin Shamsalsadati Voon Hui Lai IRIS Short Course Aug, 2015.

Array Response Functions with ArrayGUI

Nawa DahalRobert Martin-Short

Sharmin ShamsalsadatiVoon Hui Lai

IRIS Short CourseAug, 2015

Array SeismologyNumerous seismometers placed at discrete points in a well-defined configuration to record ground motions.

Applications:

• Lower the detection threshold of global earthquakes• Detect and identify nuclear explosion• Detect phases that usually are not detected by single station• High-resolution tomographic images on regional scale• Detect small-scale structures in the Earth’s mantle • Use in ambient noise interferometry studies

New trend in seismology

Challenges in Array Seismology

• Need a good array configuration to ensure wave coherency.

• Need an easy way to check station quality for large number of stations.

• Need to determine the direction of seismic sources (particularly for ambient noise interferometry)

Importance of choosing array configuration

to study scattered tsunami waves

Dataset: ALBACORE OBS Array

All stations

9 selective stations Higher frequencyAll stations

Introducing ArrayGUI

One stop to access array and station quality PSD plots

ARFs

Beamforming analysis over time(future development)

Interactive python GUI

Input:

Specify 1. Network / Area of interest

2. Time interval

Screen shots from the example GUI:

Polygon drawing tool: select array geometry

Create response function for stations of interest

Look at station metadata; create PSD plots

Note: Assure user already has the data, in future, call use GUI to download this too

User inputs network code, time window

User choose array geometry

GUI displays network map

User makes ARF

Option to view station

PFD/PDF plots, and metadata

Draw a Bad ARF

User creates beamforming plot

Good ARF

Set array response function defaults: frequency range of interest, approximate phase velocity.Also set PSD and station metadata defaults.

.

A Python GUI

• Tkinter module (Tk GUI toolkit) • Contains functionality (ex: make buttons, menus, pop-up windows) • Easy to use within code organized in classes: each method can

describe a different GUI aspect.

Buttons link to commands:

- Make new maps on the fly

- Allow selection of individual stations

- Link to Obspy modules and to IRIS PDF/PSD noise toolkit

- Download/analyse waveforms from the selected stations

Existing toolsProblem with Existing Tools• Open source codes but not integrated. (ref)

• Established codes can be optimized

• Improve workflow

IRIS Tools:• IRIS DMC PSD plot• Plot ARFs using obspy function. • Example of beamforming in backprojection tools. No physical

product except personal Matlab scripts.

Power Spectral Density plot

• Allows analysis of noise characteristics of a selected station over a selected time window

• User select station in ‘station options’ window; inputs time range.

• Program links to IRIS noise toolkit; produces enhanced PSD plot

Array Response Function (ARF)• Array response function

• Purpose: Access quality of array configuration (geometry, interstation distance, wave frequencies)

• Input: station coordinates, frequencies, limits of wavenumber• Main code: (obspy-array_transff_wavenumber)• Output: plot of ARF, list of parameters, and map

Station list.Frequency.Parameters.

Future development: Beamforming Analysis

Purpose: Determine signal source directivity over time

Steps:-Fix slowness, frequencies, stations -Perform beamforming using “delay-and-sum” method acrossall back-azimuths -Plot relative power for each back-azimuth over time

Rewrite existing MATLAB scripts intoPython (consider using HPC)

Potential Applications/Users

• Simplify usage of large array data sets• Detect direction of ambient noise sources• Facilitate education and outreach

Thank You!