Investigating Periodicities in Abyssal Hill Morphology of the Atlantic Ocean: Possible Evidence of Mantle Dynamics

Non-Technical Description

Though covered by the oceans, abyssal hills are the most common landform on earth. They form at the world’s mid-ocean ridge spreading centers and are important records of the plate spreading process. Past studies of abyssal hills have treated them as purely random processes.

The statistical parameters of such processes, such as mean, variance, characteristic scale, etc., can be correlated to plate spreading conditions, such as spreading rate, magma supply and crustal thickness. In this way, abyssal hills across the oceans can be used to probe plate dynamics through space and time. Recently, however, some studies have reported the detection of periodic signals embedded within otherwise random abyssal hill profiles.

Such a signal could be evidence of previously-unrecognized influence on mid-ocean ridge magma processes, such as climate-driven changes in sea level, or deep-seated modulations of magma delivery. This study will use a new, robust algorithm developed by the lead PI. It detects and quantifies (amplitude, wavelength) periodic signals embedded within a random field.

The algorithm will be applied to bathymetric data in the North and South Atlantic Oceans. There, decades-worth of surveys and transits provide abundant data for analysis. Periodic values will first be correlated to past spreading parameters to establish basic relationships.

Regional variations in periodic values will then be investigated. This will permit investigating possible deep-earth controls on the formation of periodic signals. The result should establish key constraints in the future modeling of mid-ocean ridges.

In addition, the code will be made available to the general public with a user-friendly interface. This will enable non-expert researchers and students in a variety of fields to make use of the algorithm. Technical Description

The existence, or not, of periodicities in abyssal hill morphology has been vigorously debated in recent publications, and some have hypothesized that such periodicities are evidence of external forcing, such as by the impact of Milankovitch cycle-caused sea level fluctuations on the volcanic construction process at mid-ocean ridges (MORs), or internally forced, such as by modulations of mantle upwelling. This project will employ a newly-developed empirically pre-whitening algorithm for detecting and quantifying periodic signals that are embedded in a random field.

It will be applied to the abundant archival trackline bathymetry data in the North and South Atlantic Oceans, which samples large and diverse regions of abyssal hills formed at slow-spreading MORs. This will enable testing of a first hypothesis: that temporal periodicities are present in slow-spreading MOR-generated abyssal hills. Preliminary analysis provides initial support, but confidently doing so requires much more than a few anecdotal examples.

The existence of periodicities in the seafloor fabric could have significant implications for understanding and modeling MOR dynamics. If periodicities in abyssal hill morphology do exist, what factors of MOR spreading are they responsive to? This question leads us to a second hypothesis: that variations in temporal periodicities exist that are related to spreading properties and mantle conditions at the MOR at the time of formation.

It can be tested directly by correlating periodic parameters to paleo-spreading rates, and indirectly by comparing periodic parameters to aperiodic statistical parameters, such as RMS height and characteristic scale, which are themselves correlated with various MOR parameters as noted above. This project will also investigate whether or not there are regional patterns to the periodicities measured, which could be indicative of responsiveness to mantle heterogeneities.

For example, recent modeling indicates that periods and amplitudes of crustal thickness-derived seafloor periodicities will be dependent on mantle permeability, a poorly-constrained parameter that is critical for modeling melt transport in the mantle.

By modernizing the original code for operation in a Python coding environment, the technique will be accessible to a wider audience, and has the potential to be used in interpreting a wide variety of Earth science and other time series (e.g., climate and weather, oceanographic, etc…). The team will promote the code through social media and develop materials to train interested users.

Support of an early career scientist and building capacity in computational geoscience is a further broader impact.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.