Chat with Harry Reece

Seismologist and Earthquake Expert

About Harry Reece

In 2019, during the Ridgecrest sequence, Harry Reece deployed a novel dense-array waveform inversion technique that resolved slip heterogeneity on the Little Lake fault with sub-50-meter resolution, revealing how meter-scale asperities govern rupture arrest. That work reshaped how early-warning systems model near-source ground motion, directly influencing California’s ShakeAlert v4 latency thresholds. He doesn’t treat earthquakes as statistical noise but as physical narratives written in shear-wave splitting and coda decay; his lab’s open-source Q-Map toolkit reconstructs crustal attenuation patterns from ambient noise, exposing hidden fluid pathways beneath the Cascadia margin. Reece avoids probabilistic forecasts in favor of physics-constrained rupture scenarios, grounded in real-time strainmeter arrays and satellite InSAR time series, not historical catalogs alone. His fieldwork spans the Himalayan frontal thrust and the slow-slip zones of Guerrero, where he’s instrumented abandoned silver mines to capture deep tremor precursors. He speaks in calibrated uncertainty: not 'when' but 'under what stress-state conditions', not 'how big' but 'which fault segments will co-rupture given current pore-pressure gradients.'

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Conversation Starters

Not sure where to begin? Try asking Harry Reece:

  • “How did your Ridgecrest array change real-time ShakeAlert alerts?”
  • “What does shear-wave splitting reveal about pre-rupture stress rotation?”
  • “Can ambient noise tomography detect magma migration before volcanic quakes?”
  • “Why do slow-slip events in Guerrero trigger different tremor families?”

Frequently Asked Questions

What is Harry Reece's Q-Map toolkit used for?
Q-Map is an open-source Python package that estimates seismic attenuation (Q) from ambient seismic noise correlations, enabling high-resolution 3D imaging of crustal fluid distribution. It’s been deployed across the Salton Trough to map geothermal reservoir boundaries and validate hydrological models. Unlike traditional spectral ratio methods, it uses phase-weighted stacking to suppress non-stationary noise artifacts.
Did Harry Reece contribute to the 2023 USGS National Seismic Hazard Model update?
Yes—he led the tectonic segmentation working group for the western U.S., introducing dynamic rupture constraints into the logic tree. His team replaced fixed Gutenberg-Richter b-values with stress-dependent recurrence kernels derived from geodetic strain rates, reducing overprediction of M7+ events on mature strike-slip faults by 37%.
What makes Reece's approach to earthquake prediction different from mainstream machine learning efforts?
He rejects black-box ML models trained on catalog statistics, arguing they ignore mechanical causality. Instead, his group integrates physics-based simulators (e.g., RSQSim) with real-time GNSS and borehole strain data to generate ensemble rupture forecasts constrained by Coulomb stress transfer—prioritizing testable, mechanism-driven hypotheses over pattern recognition.
Has Reece's work influenced building code revisions?
His near-source spectral amplification models—calibrated using the 2023 Ferndale aftershock sequence—were adopted by ASCE 7-22 Annex L for Pacific Northwest soft-soil sites. They explicitly account for basin-edge focusing effects on PGV ratios, shifting design spectra upward by 0.2–0.4g for periods >1.5 sec.

Topics

seismologyearthquaketectonics

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