A Novel Algorithm for Deriving Volcanic Eruption Ages from U-Pb Zircon Dates

From the oldest rocks on Earth to rhyolites younger than 1 Ma, zircon U-Pb geochronology is the most commonly applied tool for measuring geologic time. For example, depositional ages of sedimentary surfaces can be determined by dating volcanically derived zircons within their sediment. Recent improvements in the precision of U-Pb zircon geochronology by LA-ICPMS (laser ablation inductively coupled mass spectrometry), SIMS (secondary ion mass spectrometry), and ID-TIMS (isotope dilution thermal ionization mass spectrometry) have resolved previously unrecognized dispersion between measured dates in many published datasets. This dispersion has, until recently, masked the protracted (hundreds of ka) crystallization history of zircons which is now quantifiable at U-Th and U-Pb ID-TIMS analytical precision. LA-ICPMS measurements often cannot resolve this dispersion, and instead produce a continuous, overlapping series of dates.

Current approaches to addressing this problem include two common techniques. The first approximates an eruption age by looking solely at the youngest one or three measured zircon dates. This could be potentially problematic as an increasing n increases the likelihood that the youngest measurement may not overlap the true eruption age within uncertainty. Alternately, a subset of measured dates can be selected, usually until their weighted mean has an MSWD of 1. There is no guarantee, however, that this selection will include only measurements related to the eruption age, or conversely, that it will include all measurements that are relevant.

We present a new algorithm to more accurately determine an eruption age and its uncertainty from U-Pb zircon dates. This algorithm is informed by zircon crystallization histories from a compilation of high-resolution U-Th disequilibrium data that are matched with independently measured eruption ages. We will test current and novel approaches to deriving eruption ages (e.g., youngest grain) by simulating TIMS and LA-ICPMS datasets using a Monte Carlo approach. With insights from our modeling, we will then test LA-ICPMS U-Pb data interpretations by re-analyzing zircons with ID-TIMS. Using our data-derived algorithm will enable more precise time control where volcanogenic sediments are present.