Optimized viscoelastic wave propagation for weakly dissipative media

The representation of viscoelastic media in the time domain becomes more challenging with greater bandwidth of the propagating waves and number of travelled wavelengths. With the continuously increasing computational power, more extreme parameter regimes become accessible, which requires the reassessment and improvement of the standard ‘memory variable' methods to implement attenuation in time-domain seismic wave-propagation methods. In this paper, we propose a method to minimize the error in the wavefield for a fixed complexity of the anelastic medium. This method consists of defining an appropriate misfit criterion based on a first-order analysis of how errors in the discretized medium propagate into errors in the wavefield and a simulated annealing optimization scheme to find the globally optimal parametrization. Furthermore, we derive an analytical time-stepping scheme for the memory variables that encode the strain history of the medium. Then we develop the coarse grained memory variable approach for the spectral element method (SEM) and benchmark it using the 2.5-D code AxiSEM for global body waves up to 1 Hz. Showing very good agreement with a reference solution, it also leads to a speedup of a factor of 5 in the anelastic part of the code (factor 2 in total) in this 2.5-D approach. A factor of ≈15 (3 in total) can be expected for the 3-D case compared to conventional implementation

Seismic wave propagation in fully anisotropic axisymmetric media

We present a numerical method to compute 3-D elastic waves in fully anisotropic axisymmetric media. This method is based on a decomposition of the wave equation into a series of uncoupled 2-D equations for which the dependence of the wavefield on the azimuth can be solved analytically. Four independent equations up to quadrupole order appear as solutions for moment-tensor sources located on the symmetry axis while single forces can be accommodated by two separate solutions up to dipole order. This decomposition gives rise to an efficient solution of the 3-D wave equation in a 2-D axisymmetric medium. First, we prove the validity of the decomposition of the wavefield in the presence of general anisotropy. Then we use it to derive the reduced 2-D equations of motions and discretize them using the spectral element method. Finally, we benchmark the numerical implementation for global wave propagation at 1 Hz and consider inner core anisotropy as an application for high-frequency wave propagation in anisotropic media at frequencies up to 2 H

Triplicated P-wave measurements for waveform tomography of the mantle transition zone

Triplicated body waves sample the mantle transition zone more extensively than any other wave type, and interact strongly with the discontinuities at 410 km and 660 km. Since the seismograms bear a strong imprint of these geodynamically interesting features, it is highly desirable to invert them for structure of the transition zone. This has rarely been attempted, due to a mismatch between the complex and band-limited data and the (ray-theoretical) modelling methods. Here we present a data processing and modelling strategy to harness such broadband seismograms for finite-frequency tomography. We include triplicated P-waves (epicentral distance range between 14 and 30°) across their entire broadband frequency range, for both deep and shallow sources. We show that is it possible to predict the complex sequence of arrivals in these seismograms, but only after a careful effort to estimate source time functions and other source parameters from data, variables that strongly influence the waveforms. Modelled and observed waveforms then yield decent cross-correlation fits, from which we measure finite-frequency traveltime anomalies. We discuss two such data sets, for North America and Europe, and conclude that their signal quality and azimuthal coverage should be adequate for tomographic inversion. In order to compute sensitivity kernels at the pertinent high body wave frequencies, we use fully numerical forward modelling of the seismic wavefield through a spherically symmetric Earth

Seismic waveform inversion for core-mantle boundary topography

The topography of the core-mantle boundary (CMB) is directly linked to the dynamics of both the mantle and the outer core, although it is poorly constrained and understood. Recent studies have produced topography models with mutual agreement up to degree 2. A broad-band waveform inversion strategy is introduced and applied here, with relatively low computational cost and based on a first-order Born approximation. Its performance is validated using synthetic waveforms calculated in theoretical earth models that include different topography patterns with varying lateral wavelengths, from 600 to 2500 km, and magnitudes (∼10 km peak-to-peak). The source-receiver geometry focuses mainly on the Pdiff, PKP, PcP and ScS phases. The results show that PKP branches, PcP and ScS generally perform well and in a similar fashion, while Pdiff yields unsatisfactory results. We investigate also how 3-D mantle correction influences the output models, and find that despite the disturbance introduced, the models recovered do not appear to be biased, provided that the 3-D model is correct. Using cross-correlated traveltimes, we derive new topography models from both P and S waves. The static corrections used to remove the mantle effect are likely to affect the inversion, compromising the agreement between models derived from P and S data. By modelling traveltime residuals starting from sensitivity kernels, we show how the simultaneous use of volumetric and boundary kernels can reduce the bias coming from mantle structures. The joint inversion approach should be the only reliable method to invert for CMB topography using absolute cross-correlation traveltime

Seismic waveform sensitivity to global boundary topography

We investigate the implications of lateral variations in the topography of global seismic discontinuities, in the framework of high-resolution forward modelling and seismic imaging. We run 3-D wave-propagation simulations accurate at periods of 10 s and longer, with Earth models including core-mantle boundary topography anomalies of ∼1000 km spatial wavelength and up to 10 km height. We obtain very different waveform signatures for PcP (reflected) and Pdiff (diffracted) phases, supporting the theoretical expectation that the latter are sensitive primarily to large-scale structure, whereas the former only to small scale, where large and small are relative to the frequency. PcP at 10 s seems to be well suited to map such a small-scale perturbation, whereas Pdiff at the same frequency carries faint signatures that do not allow any tomographic reconstruction. Only at higher frequency, the signature becomes stronger. We present a new algorithm to compute sensitivity kernels relating seismic traveltimes (measured by cross-correlation of observed and theoretical seismograms) to the topography of seismic discontinuities at any depth in the Earth using full 3-D wave propagation. Calculation of accurate finite-frequency sensitivity kernels is notoriously expensive, but we reduce computational costs drastically by limiting ourselves to spherically symmetric reference models, and exploiting the axial symmetry of the resulting propagating wavefield that collapses to a 2-D numerical domain. We compute and analyse a suite of kernels for upper and lower mantle discontinuities that can be used for finite-frequency waveform inversion. The PcP and Pdiff sensitivity footprints are in good agreement with the result obtained cross-correlating perturbed and unperturbed seismogram, validating our approach against full 3-D modelling to invert for such structure

Diurnal self-aggregation

Convective self-aggregation is a modelling paradigm for thunderstorm organisation over a constant-temperature tropical sea surface. This setup can give rise to cloud clusters over timescales of weeks. In reality, sea surface temperatures do oscillate diurnally, affecting the atmospheric state. Over land, surface temperatures vary more strongly, and rain rate is significantly influenced. Here, we carry out a substantial suite of cloud-resolving numerical experiments, and find that even weak surface temperature oscillations enable qualitatively different dynamics to emerge: the spatial distribution of rainfall is only homogeneous during the first day. Already on the second day, the rain field is firmly structured. In later days, the clustering becomes stronger and alternates from day-to-day. We show that these features are robust to changes in resolution, domain size, and surface temperature, but can be removed by a reduction of the amplitude of oscillation, suggesting a transition to a clustered state. Maximal clustering occurs at a scale of $\mathbf{l_{max}\approx 180\;km}$, a scale we relate to the emergence of mesoscale convective systems. At $\mathbf{l_{max}}$ rainfall is strongly enhanced and far exceeds the rainfall expected at random. We explain the transition to clustering using simple conceptual modelling. Our results may help clarify how continental extremes build up and how cloud clustering over the tropical ocean could emerge much faster than through conventional self-aggregation alone.Comment: 27 pages, 4 main figures, 7 supplementary figures, 2 main tables, 1 supplementary tabl