Interactive Receiver Functions Forward Modeller (IRFFM)

The Interactive Receiver Function Forward Modeller (IRFFM) is 2 Java programs for interactive forward modelling of teleseismic receiver functions (the first version, v1.0, was released in 2009).

IRFFM 1.4 (IRFFM1 v1.3 and IRFFM2 v1.3 together) are the current versions that have been available since November 2010.

Several functionalities have been added since v1.0, most notably:

  1. the program now comes with a display indicating the goodness of fit (variance reduction in percentages)
  2. an option to print the resulting plots to either a printer or a jpg file.

Manuals

These describe the programs and the main requirements. Please read them for some important information before download and installation: irffm1-1.4_info_and_manual.pdf irffm2-1.4_info_and_manual.pdf

Download

The IRFFM code is written in Java, with helper programs in C, Fortran and C shell script. It depends on the swt graphics library and the sac seismic package. It should run on most computers that have access to Java, Java swt and GNU tools such as gfortran. The complete source code, manual and example input files, can be downloaded here. You will need to register with iEarth prior to download. The README can be viewed separately. Enquires should be directed to the author.

Screenshots

Screen snapshots showing the IRFFM1 and IRFFM2 interfaces

References

Tkalčić, H., Pasyanos, M., Rodgers, A., Gök, R., Walter, W. & Al-Amri, A. (2006), A multi-step approach in joint modeling of surface wave dispersion and teleseismic receiver functions: Implications for lithospheric structure of the Arabian peninsula, J. Geophys. Res. 111, B11311, doi:10.1029/2005JB004130.

IRRFM1 featured in:

Tkalčić, H., Y. Chen, R. Liu, Z. Huang, L. Sun and W. Chan, Multi-Step modelling of teleseismic receiver functions combined with constraints from seismic tomography: Crustal structure beneath southeast China, Geophys. J. Int., 187, doi:10.1111/j.1365-246X.2011.05132.x, 303-326, 2011.

IRFFM2 featured in:

Tkalčić, H., N. Rawlinson, P. Arroucau, A. Kumar and B.L.N. Kennett, Multi-Step modeling of receiver-based seismic and ambient noise data from WOMBAT array: Crustal structure beneath southeast Australia, Geophys. J. Int., doi:10.1111/j.1365-246X.2012.05442.x, 189, 1681-1700, 2012.

Multi-Step Modelling of Teleseismic Receiver Functions Combined With Constraints From Seismic Tomography:
Crustal Structure Beneath Southeast China

In this study, in which IRFFM software is featured for the first time, we perform a receiver-based study of the lithosphere of southeast China using the waveform records of excellent quality from fourteen Chinese National Digital Seismic Network (CNDSN) and four Global Seismic Network (GSN) stations. Receiver functions (RFs) are predominantly sensitive to the gradients in the lithospheric elastic parameters, and it is impossible to determine a non-unique distribution of seismic parameters such as absolute shear-wave speeds as a function of depth unless other geophysical data are combined with RFs. Thus we combine RFs with independent information from shear- and compressional-wave speeds below the Mohorovičić discontinuity, available from the existing tomographic studies. The preparation of RFs and consequent analysis consist of multiple steps. First, a statistical approach based on a calculation of the cross-correlation matrix is described and used to estimate averaged RFs for a large number of waveforms available in this study (see Figure 1 below). Second, an interactive forward modelling software (IRFFM) is introduced and applied to observed RFs to define a prior, physically acceptable range of elastic parameters in the lithosphere. This is followed by a grid-search for a simple crustal structure. An initial model for a linearised, iterative inversion is constructed from multiple constraints, including results from the grid-search for shear-wave speed, the Moho-depth versus vp/vs ratio domain search and tomography. We obtain 1-D velocity profiles for all eighteen stations. The thickness of the crust constrained by the three independent techniques appears to be more variable in comparison with tomographic studies, with the crust thinning significantly towards the east (see Figure 2 below).
We used IRFFM to get a quick understanding of the features present in RFs, as well as a quantitative measure about the range of parameters that produce theoretical RFs similar to the observed RFs. For example, one can explore how the crustal thickness and the impedance contrast affect the P to S conversion, seen as the second peek in observed RFs. The estimated model parameters using IRFFM are in a good agreement with the results from the H-k search.

Figure 1. Radial RFs calculated for one of the stations in the study from the southeastern azimuths for all earthquakes without rejecting waveforms based on signal-to-noise ratio are shown in black. Mutually coherent waveforms selected using the cross-correlation matrix approach are shown in blue. The selected waveforms are correlated with the cross-correlation coefficient 0.9 or higher with a) at least 25% of other waveforms and b) at least 50% of other waveforms. The thick red line is the average calculated from the selected RFs.


Figure 2. Comparison of interpolated maps of crustal thickness (Moho depth) for southeast China using eighteen data points corresponding to the locations of the stations from this study. a) P-wave tomography (Sun and Toksöz, 2006) and b) this study, using RFs inversion modelling results

Multi-Step modeling of receiver-based seismic and ambient noise data from WOMBAT array:
Crustal structure beneath southeast Australia

A limitation of most forms of passive seismic tomography using distant earthquakes lies in the fact that crustal structure is poorly resolved. An attempt is made here to address this issue by modelling teleseismic receiver functions (RFs) and dispersion curves derived from ambient noise through a multistep approach. The SEAL3 experiment in central and southern NewSouth Wales (NSW) used here, represents one of 13 array deployments that so far comprise the large WOMBAT project, which aims to cover a significant portion of the Australian continent with a rolling array of seismometers. An interactive, forward-modelling software package (IRFFM2) is introduced and applied to the observed RFs and surface wave dispersion curves to define a prior, physically acceptable range of elastic parameters in the lithosphere, which is combined with a grid-search and a linearized inversion. Our results emphasize the importance of a joint treatment of RFs and dispersion data as the predictions from 1-D velocity models at individual stations derived from only RFs display large departures from the observed ambient noise dispersion curves. In total, 27 jointly constrained 1-D shear wave models are produced, which provide sufficient sampling of the crust beneath SEAL3 to permit detailed inferences about lateral variations in structure to be made. Of particular note is the observation that the Moho deepens towards the mountainous southeast, where it exceeds 50 km in depth beneath the Southern Highlands of NSW, thus marking out some of the thickest crust in Australia. The complex lateral variations in midlower crustal velocity that we observe probably reflect the manifold interactions of a thinning lithosphere, associated igneous underplating, recent hot-spot-related volcanism and uplift. Our results image an important part of the lithosphere that is poorly constrained by regional and teleseismic tomography, and contribute to the understanding of the formation of the southern highlands and the Palaeozoic Lachlan Orogen.

Figure 3. Comparison of interpolated maps of crustal thickness (Moho depth) in southeast Australia from different datasets: a) Moho depth from Collins et al. (2003) (COL) including Clitheroe et al. (2000) (CLI) and Shibutani et al. (1996) (SHI) data; b) Moho depth from IRFFM2 and grid-search (Step 2); c) Moho depth from linearised inversion (Step 3); d) Moho depth from joint inversion of RFs and ambient noise Rayleigh wave dispersion curves (Step 5); e) Same as d) including CLI and SHI points; f) Same as d) including COL, CLI and SHI points. Figure taken from Tkalčić et al. (2012).