Constraining rates in Earth’s sedimentary archives from their genetic history

Constraining rates in Earth’s sedimentary archives from their genetic history.

Sedimentary rock piles are important archives of paleoclimatic information and also serve as CO2 storage sites in the near future. The deposition rate of sediments is of key importance to all sedimentological studies, as it reveals the sedimentary properties and preserve paleoclimatic history. XRay-Fluorescence spectroscopy (XRF) provide a wealth of new data with ~30 chemical elements measured at ultra-high stratigraphic resolution (>0.1 mm) that can even preserve ‘annual layers’ in sediments of essentially any age and teach us about paleoclimatic events at time scales relevant for humans. We have discovered periodic ‘Milankovitch’ signals dictated by solar insolation forcing on the early Earth in multiple chemical elements detected in the XRF signals, but existing signal analysis is only applicable to unidimensional data. By developing a Bayesian inverse approach, we will take advantage of the multidimensionality of XRF data that can better constrain sedimentation rate because 1) numerous elements oscillate independently in concert with climate-driven Milankovitch forcing and 2) the chemical composition reveals sedimentation rates; e.g. coarse grained material (e.g. sand) deposits faster than fine-grained material (e.g. mud). We will 1) deploy unsupervised learning methods (Self Organizing Maps; SOM) to decipher the underlying formative processes and assign sedimentation rates from XRF data and 2) develop a Bayesian inversion approach to quantitatively link astronomical theory with multidimensional geochemical data. Together, we expect these algorithms will enable rate determination in a wider range of Earth’s sedimentary archives and not only refine the geological time scale, but also set a new standard for the mapping of Earth’s sedimentary archives.