Paula Koelemeijer

New Insights Into the Cooling of the Oceanic Lithosphere From Surface‐Wave Tomographic Inferences We present SS3DPacific: a new VSV model of the Pacific ocean with 3D resolution and uncertainty We show that interpretations of oceanic lithosphere cooling are strongly biased by vertical resolut...

Whole story, credits, links to model files and acknowledgements in the paper, here: agupubs.onlinelibrary.wiley.com/doi/10.1029/...

Exciting then: We observe an intriguing pattern of anomalies aligned along the giant oceanic fracture zones. While the exact origin of the pattern remains to be clarified, it surely tells us that the cooling structure of the oceanic lithosphere is laterally complex, and fracture zones play a role!

Disappointing first: Surface-wave tomography has limited power to discuss the ageing of the lithosphere, and can be very misleading, resolution tells us. This emphasises we should interpret models to their limits, but not beyond!

This model is not necessarily higher resolution than its predecessors, but it's a model whose resolution we control and we know, and this empowers us to say new things on the oceanic lithosphere.

New paper alert, led by @flatallerie.bsky.social at @oxuniearthsci.bsky.social.

We propose new insights into the cooling of the oceanic lithosphere based on 'SS3DPacific', a new model of Vsv in the upper mantle beneath the Pacific Ocean.

See: agupubs.onlinelibrary.wiley.com/doi/10.1029/...

PGVnet: A Machine Learning Framework for the Generation of Rapid, Physics-Consistent PGV Maps Summary. The rapid and accurate estimation of strong ground motion is essential for seismic hazard assessment and near-real-time disaster response. Althoug

Validated in the geologically complex San Francisco Bay Area, our approach generates PGV maps consistent with physics-based simulations, offering an effective balance between computational speed and accuracy.

Link to paper:
doi.org/10.1093/gji/...
Link to Github:
github.com/fatimarmdnn/...

PGVnet is ideal for applications such as rapid earthquake disaster response, as well as large-scale probabilistic seismic hazard analyses and multi-hazard digital ecosystems.

This framework provides spatially continuous PGV predictions and inherently accounts for complex 3D geological and topographic effects. It can deliver results within seconds while maintaining accuracy up to the highest frequency captured in the physics-based simulations.

To overcome these limitations, we introduce PGVnet - a novel two-step machine learning framework that predicts peak ground velocity (PGV) for arbitrary double-couple sources positioned anywhere within a given medium, combining the accuracy of physics-based models with near-instantaneous inference.

The rapid and accurate estimation of strong ground motion is essential for seismic hazard assessment and near-real-time disaster response. Current methods are limited: empirical ground motion models simplify the underlying physics while physics-based simulations are computational expensive.

Schematic overview of the two step machine learning framework used in PGVnet

New paper out in GJI: "PGVnet: A Machine Learning Framework for the Generation of Rapid, Physics-Consistent PGV Maps” led by PhD student Fatima Ramadan, Tarje Nissen-Meyer and Bill Fry.
See: doi.org/10.1093/gji/...

Thank you!

Wanna see how an earthquake works? Here's today's lab in my seismology class. An explanation follows.

🧪

Thank you!

I feel very honoured to receive this award from the RAS! It is not just reflection of my work, but also acknowledges a large group of people I have had the pleasure of working with.

Still thinking about attending EGU 2026? Consider submitting an abstract to our session on quantitative imaging! We hope to see you in Vienna!

We particularly invite contributions that develop or apply novel methods for quantifying uncertainty in seismic imaging, compare different approaches or explore the impact of uncertainty on interpretations and the propagation of uncertainties into other fields (i.e. geodynamics, hazard modelling).

We welcome studies covering global and regional scales, body-wave and surface-wave tomography, full-waveform inversion, ambient noise imaging, and any seismic method where uncertainty is crucial. Cross-disciplinary and innovative methodological contributions are particularly encouraged.

We have solicited abstracts from:
- Professor Malcolm Sambridge (Australian National University)
- Dr Xuebin Zhao (University of Edinburgh)

The abstract submission deadline is 15th January 2026. More information and a full description of the session can be found at www.egu26.eu/session/55671

Planning to attend the EGU General Assembly in Vienna in 2026 and working on seismic imaging? Consider submitting your abstract to our session on quantitative imaging: "SM2.3: Quantifying and Interpreting Uncertainties in Seismic Tomography"! www.egu26.eu/session/55671

In this paper, we focus our discussion on a subslab hot mantle upwelling beneath the Sumatra slab, while we find no evidence of slab holes under Java or East Sumbawa given the model resolution. Stay tuned for more interpretation of the model!

By selecting areas with the same local resolution for Vs and Vp, we can obtain meaningful estimates of the ratio including uncertainties. Using this approach, we obtain several features that we can now quantitatively interpret.

Read more about our new GJI paper, led by Emile Serra in Strasbourg, where we image the upper mantle and mantle transition zone under Indonesia. By utilising the Backus-Gilbert SOLA method, we develop seismic velocity models with quantified resolution and uncertainties.

Extent, timing, and cause of Quaternary uplift along the Atlantic margin of Morocco Primary Supervisor: Richard Walker

New fully-funded DPhil project with Professor Richard Walker (@richardthomasw.bsky.social) researching the extent, timing, and cause of Quaternary uplift along the Atlantic margin of Morocco!

For more information visit our website
www.earth.ox.ac.uk/extent-timin...

Finally, take a look at my website for more information about active research projects of members in the DEEPSCAPE group: earth.ox.ac.uk/~univ4152/in...
Again, do not hesitate to get in touch to discuss project ideas and for advice on your application! (6/6)

Academic futures | University of Oxford Academic Futures is a series of scholarship programmes that seeks to address under-representation and help improve equality, diversity and inclusion in our graduate student body.

The Academic Futures scheme (www.ox.ac.uk/admissions/g...) may be particularly interesting, with scholarships specifically designated to applicants from BME backgrounds. (5/n)

Graduate Admissions

Oxford also has many other scholarships and funding schemes. See the department’s admission page for some examples: www.earth.ox.ac.uk/graduate/adm.... The system is quite complex, so again, get in touch to discuss possibilities - I am happy to help! (4/n)

Applicants can apply for competitive funding via the ILESLA programme (iles.web.ox.ac.uk/how-apply) or Intelligent Earth CDT (intelligent-earth.ox.ac.uk/how-apply) - deadline 8th Jan 2026. This is competitive funding that anyone worldwide can apply for, also without a project in mind. (3/n)

For some project suggestions by me, see project EARTH-26-PK03 (MTZ structure) and EARTH-26-PK04 (Proxies for phase transitions) on this page: www.earth.ox.ac.uk/graduate/pro..., but note that these are merely conversation starters. (2/n)

Looking for a PhD in seismology based in Oxford @oxuniearthsci.bsky.social? Interested in global seismology, deep Earth processes, mantle dynamics and mineralogy, seismic imaging, inverse problems, or urban seismology, seismic deployments, seismicity? Please get in touch to discuss ideas! (1/n)