Data Services Products: ASWMS Automated Surface Wave Phase Velocity Measuring System


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.

Processing workflow:

  1. For a selected event, automatically generate a time window that includes only fundamental-mode surface waves based on group delay estimates.
  2. For a given station, cross correlate the windowed waveform with the waveforms from several nearby stations.
  3. Window around the peak of the resulting cross-correlation waveforms.
  4. Apply narrow-band filters.
  5. Fit the waveforms with a five-parameter wavelet, which is a cosine function multiplied by a Gaussian envelope.
  6. Correct cycle skipping and get the phase delay between each station pair as a function of frequency
  7. Repeat 2-6 for each station in the array
  8. At each frequency, use the collection of phase-difference measurements to invert for apparent phase velocity using Eikonal tomography.
  9. Using the measured amplitude field, apply Helmholtz tomography to invert for structural phase velocity
  10. 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:

  1. Download the package
  2. set up the setup_parameters.m file
  3. run main_driver.m in MATLAB
  4. 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:

USArray ASWMS results:

USArray movie
Evolution of the 40s Rayleigh wave phase velocity (km/s) map produced by ASWMS as TA rolled across the US.

USArray, Contiguous United States results:

Weekly updated USArray, Alaska results:

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.

Citations and DOIs

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,

To cite the IRIS DMC ASWMS Data Product:

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,


  • 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


Ge Jin
Lamont-Doherty Earth Observatory, Columbia University





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