EGU General Assembly 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Teleseismic P-wave travel time tomography of the Alpine upper mantle using AlpArray seismic network data

Marcel Paffrath1, Wolfgang Friederich1, and the AlpArray Working Group*
Marcel Paffrath and Wolfgang Friederich and the AlpArray Working Group
  • 1Institut für Geologie, Mineralogie und Geophysik, Ruhr-Universität Bochum, Bochum, Germany (
  • *A full list of authors appears at the end of the abstract

We perform a teleseismic P-wave travel time tomography to examine geometry and slab structure of the upper mantle beneath the Alpine orogen. Vertical component data of the extraordinary dense seismic network AlpArray are used which were recorded at over 600 temporary and permanent broadband stations deployed by 24 different European institutions in the greater Alpine region, reaching from the Massif Central to the Pannonian Basin and from the Po plain to the river Main. Mantle phases of 347 teleseismic events between 2015 and 2019 of magnitude 5.5 and higher are evaluated automatically for direct and core diffracted P arrivals using a combination of higher-order statistics picking algorithms and signal cross correlation. The resulting database contains over 170.000 highly accurate absolute P picks that were manually revised for each event. The travel time residuals exhibit very consistent and reproducible spatial patterns, already pointing at high velocity slabs in the mantle.

For predicting P-wave travel times, we consider a large computational box encompassing the Alpine region up to a depth of 600 km within which we allow 3D-variations of P-wave velocity. Outside this box we assume a spherically symmetric earth and apply the Tau-P method to calculate travel times and ray paths. These are injected at the boundaries of the regional box and continued using the fast marching method. We invert differences between observed and predicted travel times for P-wave velocities inside the box. Velocity is discretized on a regular grid with an average spacing of about 25 km. The misfit reduction reaches values of up to 75% depending on damping and smoothing parameters.

The resulting model shows several steeply dipping high velocity anomalies following the Alpine arc. The most prominent structure stretches from the western Alps into the Apennines mountain range reaching depths of over 500 km. Two further anomalies extending down to a depth of 300 km are located below the central and eastern Alps, separated by a clear gap below the western part of the Tauern window. Further to the east the model indicates a possible high-velocity connection between the eastern Alps and the Dinarides. Regarding the lateral position of the central and eastern Alpine slabs, our results confirm previous studies. However, there are differences regarding depth extent, dip angles and dip directions. Both structures dip very steeply with a tendency towards northward dipping. We perform various general, as well as purpose-built resolution tests, to verify the capabilities of our setup to resolve slab gaps as well as different possible slab dipping directions.

AlpArray Working Group:

The complete member list of the AlpArray Working Group can be found at

How to cite: Paffrath, M. and Friederich, W. and the AlpArray Working Group: Teleseismic P-wave travel time tomography of the Alpine upper mantle using AlpArray seismic network data, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13779,, 2020

Comments on the presentation

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Presentation version 1 – uploaded on 04 May 2020
  • CC1: Comment on EGU2020-13779, Anne Paul, 05 May 2020

    Dear Marcel,

    Thank you for dowloading your presentation. Really nice, impressive and very interesting work.

    I already have one comment/question. In slide 16, you write that there is "no connection of lithospheric slab to crust in Zhao model". This appears to be true in the cross-section from Zhao et al. wich starts below the deepest Moho at 70-75 km depth. But when we replace the white shallow part by the crustal structure derived from our crustal tomographies (Zhao et al., 2015; Solarino et al., 2018; Zhao et al., 2020 published last week in Nature Communications), the Zhao et al's high-vel slab is clearly connected to the subducted European crust, with a Moho reaching 75-80 km depth. I agree that there is no connection to the crustal model by Diehl et al that you are using for crustal corrections; but their model does not detect the deeply subducted European crust, because it is not possible with local earthquake tomography.

    "See" you in the chat on thursday morning.


    • AC1: Reply to CC1, Marcel Paffrath, 05 May 2020

      Dear Anne,

      thank you for your comment. Do I understand you correctly that there is a connection of the high velocity anomaly to the crust, but it is simply further east in your crustal model compared to T. Diehl?

      Are there any profiles of the crustal model available at the location of profile A? It would also be interesting to have another crustal model of the Alpine region for correction/comparison.

      Best regards,


      • CC2: Reply to AC1, Anne Paul, 07 May 2020

        Hi Marcel,

        Big success this morning in the chat session! Your slides are really great and spectacular.

        Yes, you got my point: the most recent results on the crustal structure of the W-Alps show that the European Moho reaches its maximum depth at 75-80 km in the continuation of the Moho imaged in previous tomographies, or deep-seismic sounding data like ECORS-CROP. This deepest Moho is beneath the westernmost Po plain, further east than in previous images. And along the Cifalps line (slightly south of your line B in slide 16), this deep Moho is directly connected to Zhao et al's high-vel. anomaly. I cannot send you a cross-section in our last crustal Vs model along line B right now; but I will remember that I should do that and contact you again.

        You also ask about any other available crustal model of the Alps. We do have quite a few, but they were all computed by ambient-noise tomography. They are all Vs models, probably not that useful for your crustal corrections. But they are all published and available (Lu et al. GJI 2018; Lu et al., GJI 2020 ; Zhao et al., Nature Comm. 2020,

        By the way, I have another question: do the crustal corrections change the residuals significantly? We tested with and without a crustal model in Zhao et al., 2016 and the influence of the crustal correction on residuals were minor.

        If you like, you can reply by email:

        Do you have plans to write and submit a paper soon?

        Regards. Anne