Peter Shearer ushered the global deep Earth research community into the modern practice of big data science by assembling and stacking vast numbers of accumulated digital seismograms to extract subtle features that had been largely undetected by prior approaches and applying innovative modeling techniques to interpret the revealed structures in the mantle and core.
Peter’s early focus on seismogram intervals dominated by top-side or bottom-side reflections from internal velocity discontinuities provided the first global maps of topography of mantle transition zone velocity and density contrasts near 410-, 520-, and 660-kilometer depths, along with additional laterally varying reflectors in the upper and lower mantles. In implementing his waveform stacking approaches, which exploit constructive interference to enhance signal-to-noise ratios, he greatly expanded the categories of signals brought to bear on mapping discontinuity depths, sharpness, and velocity contrasts. Drawing on constraints on chemical and thermal sensitivity of mantle phase changes and compositional contrasts, the internal boundary topography provided new constraints on the configuration of mantle convection, supplementing surface observations of the geoid, and dynamic topography. The power of stacking large waveform data sets was thus brought to the global stage, providing unprecedented observations to fuel seismic tomography, mineral physics, and geodynamics investigations of the mantle and core.
Large data sets were also used for constraining statistical attributes of fine-scale velocity heterogeneities inside the deep Earth in Peter Shearer’s innovative applications to scattered wave fields. This work extended characterization of the mantle structure to wavelengths shorter than the deterministic resolution enabled by seismic tomography. This remains the best approach to accessing fine, geologic-scale structures that have evolved over billions of years of mantle mixing and fractionation. Application of large data sets to determine anisotropy and heterogeneity of the remarkably complex inner core has also drawn his attention, providing important constraints that bound the thermochemical processes associated with inner core growth and evolution.
Big data strategies to constrain dynamic processes such as earthquake ruptures and source spectra for massive numbers of global and regional earthquakes have been additional areas in which Peter has made major contributions. The common link of many of his studies has been the extraction of deterministic structure and source information from complex signals by stacking many seismograms, supplemented by clever modeling techniques.
For his profound impact on revealing internal core and mantle structure by innovative analysis of very large data sets, Peter Shearer is a superb choice for AGU’s Lehmann Medal.
—Thorne Lay, University of California, Santa Cruz
Thank you, Thorne, for your generous citation. It’s truly an honor to receive an award named after Inge Lehmann, and it’s humbling to be joining the illustrious list of previous medalists.
It is traditional and appropriate to thank people who have helped one’s career, and I have certainly been fortunate in this regard. There are too many names to list here, but I would like to mention my Ph.D. and postdoctoral advisers, John Orcutt and Chris Chapman. John welcomed me to his seagoing research team and demonstrated the value of making field observations and applying new modeling approaches to probe Earth structure. He also encouraged me to take a postdoc at Cambridge with Chris Chapman, who showed me the rigor and power of applied mathematics in geophysics and made me realize that my talents, such as they are, are in observational rather than theoretical seismology.
To my students, postdocs, and colleagues and anyone who has ever written a paper with me, I am grateful for the fun times that we shared doing science together. The whole is greater than the sum of its parts, and it makes me happy to know that our names will be forever linked through our coauthorships.
Seismology is a data-driven science, and I owe a debt of thanks to the many talented people who collect and distribute the data that have made my research possible.
Most of my career has been at Scripps and the University of California, San Diego. I have to admit my decision to go to Scripps as a grad student was largely made once I saw the beach (“you had me at hello” as the line goes), but I’ve never regretted it—I could not ask for a more stimulating and supportive environment. America’s public universities are great engines of opportunity, and in these difficult times they need our support more than ever.
Finally, I thank my wife, Susan, who has always encouraged me and my career and gave me three wonderful daughters, Rachel, Hannah, and Sarah. I love you all and thank you for being part of my life.
—Peter M. Shearer, University of California, San Diego, La Jolla