Do-it-yourself automated surface wave tomography using the MATLAB based ASWMS package developed by Ge Jin & James Gaherty. This product provides 1) the ASWMS software package and 2) weekly updated USArray, Alaska surface wave tomography maps using ASWMS.
The Automated Surface-Wave Phase-Velocity Measuring System (ASWMS) is a MATLAB based package developed by Ge Jin & James Gaherty to automatically download, analyze, and measure the phase and amplitude of surface waves and then generate surface-wave tomography maps. This cross-correlation based method can be applied to continental, regional or local scales as long as the array is dense enough such that inter-station distances are less than a few wavelengths of the shortest periods analyzed. The ASWMS package can provide near real-time surface-wave tomography maps with minimal user effort or computing resources. Examples applied to USArray and PASSCAL experiments are given below.
- For a selected event, automatically generate a time window that includes only fundamental-mode surface waves based on group delay estimates.
- For a given station, cross correlate the windowed waveform with the waveforms from several nearby stations.
- Window around the peak of the resulting cross-correlation waveforms.
- Apply narrow-band filters.
- Fit the waveforms with a five-parameter wavelet, which is a cosine function multiplied by a Gaussian envelope.
- Correct cycle skipping and get the phase delay between each station pair as a function of frequency
- Repeat 2-6 for each station in the array
- At each frequency, use the collection of phase-difference measurements to invert for apparent phase velocity using Eikonal tomography.
- Using the measured amplitude field, apply Helmholtz tomography to invert for structural phase velocity
- Stack the results from different events to produce the final maps at each frequency.
The GSDF project page provides a more detailed summary. The theory & additional details can be found in Jin and Gaherty, 2014.
The ASWMS manual v2015.04.25 provides usage & technical details.
Do-it-yourself fully automated surface wave tomography workflow:
- Download the package GSDF_v1.4.zip
- set up the setup_parameters.m file
- run main_driver.m in MATLAB
- tomography maps! .xyz ascii output files are also given
Notes on software:
- be sure to have the latest versions of IRIS-WS-VERSION.jar and irisFetch.m in your /matgsdf directory
- MATLAB toolboxes needed:
- Optimization- for lsqcurvefit
- Mapping- for map figures. ASWMS also outputs ASCII .xyz files which can be used for plotting with GMT, python…
- Statistics- for nanmedian, nanmean etc… If you don’t have this toolbox, a workaround is to have the NaNsuite functions in the /matgsdf dir
Notes on setting up the setup_paramters.m file:
- To get started, only the Global Settings, start_time & end_time need to be set
- The ASWMS manual provides further details
- Example setup_parameters.m file
USArray ASWMS results:
USArray, Contiguous United States results: ASWMS_USArray.zip
Weekly updated USArray, Alaska results: ASWMS_USArray_Alaska.zip
Example results using ASWMS for various array data available from the DMC
The .zip files below contain results for multiple frequency bands as well as the setup_parameters.m file used from ASWMS ran on various PASSCAL and other arrays.
To cite the IRIS DMC Data Products effort:
- Hutko, A. R., M. Bahavar, C. Trabant, R. T. Weekly, M. Van Fossen, T. Ahern (2017), Data Products at the IRIS‐DMC: Growth and Usage, Seismological Research Letters, 88, no. 3, doi:10.1785/0220160190.
To cite the IRIS DMC ASWMS Data Product:
- IRIS DMC (2014), Data Services Products: ASWMS Automated Surface Wave Phase Velocity Measuring System, doi:10.17611/DP/ASWMS.1.
To cite the source of the Automated Surface Wave Phase Velocity Measuring System:
- Ge Jin and James B. Gaherty, Surface wave phase-velocity tomography based on multichannel cross-correlation, Geophys. J. Int. 2015 201: 1383-1398, doi:10.1093/gji/ggv079.
- Ge Jin, James Gaherty
- Alexander Hutko
- ASWMS online at IRIS
- ASWMS updated to v1.1 : Changed from velocity stacking to slowness stacking. Changed some parameters for better data selection. Changed cross-correlation window shape for smaller window bias. Adding anti-aliasing filter in the data downloading.
- ASWMS updated to v1.2 : Manual updated and minor revision to codes that don't affect results.
- ASWMS updated to v1.3 : Fixed minor bug in data_download.m.
- ASWMS updated to v1.4 : Remove the Love-wave support (horizontal components) due to the overtone interference
Lamont-Doherty Earth Observatory, Columbia University