Separating Sea and Slow Slip Signals on the Seafloor

Abstract

Seafloor pressure measurements hold promise for estimating vertical displacements from transient slow slip events on submarine faults. We assess the accuracy of pressure offset estimates that evolve over days to weeks and the confidence with which they may be attributed to tectonic deformation or to the ocean water column. One common approach to resolve this ambiguity assumes water column pressures vary insignificantly over the study region and are represented by stable reference site pressures. Assessing the validity of this assumption requires independent evidence. Correlations between pressures and colocated temperatures collected during the Hikurangi Ocean Bottom Investigation of Tremor and Slow Slip experiment suggest temperatures might provide a useful independent proxy for water column pressures. We compared offsets estimated using several methods, with temperature and other proxies. The use of a temperature proxy was unsuccessful, because seafloor temperatures did not track the seasonal signal that contributes significantly to seafloor pressure changes over the slow slip event period. Regardless of the estimation method, offsets varied within a few cm around some uncertain reference level. Commonly used statistical measures are shown not to be reliable indicators of offset accuracy since offsets contribute minimally to the total variance. Offsets estimated using identical methods but with seafloor pressures simulated using a regional ocean model were larger than those derived from the data but had a similar pattern. Since the model simulates only water column processes, this suggests a significant fraction of the estimated pressure offsets are due to seasonal water column signal and are not of tectonic origin.

The Ocean's Impact on Slow Slip Events

“…The ROMS model reasonably well predicts the first-order features of the nontidal seafloor pressure field, as evidenced in comparisons between a variety of predicted and observed data found in Hadfield et al (2007) and between seafloor predicted and observed pressures recorded during the HOBITSS experiment and low-pass filtered with a corner of 0.5 days −1 (Gomberg et al, 2020). The latter verifies the minimal contribution of the tides with periods longer than several days noted above.…”

“…However, the latter have advantages relative to recorded pressures that include their long durations, an absence of instrumental and localized environmental noise, and importantly contain only the posited causal ocean pressures and not those that may exist due to seafloor deformation from the SSEs. Comparisons between the simulated and observed seafloor pressures are described in Gomberg et al (2020).…”

Detecting Slow Slip Events From Seafloor Pressure Data Using Machine Learning

“…For example, He et al (2018) yielded moderate improvement by using deep current measurements and the geostrophic balance assumption to remove the ocean circulation contribution. Gomberg et al (2019) suggested an approach to reduce the water column and some instrumental noise based on correlations between seafloor temperature and pressure changes. In this paper, we did not apply the machine learning method to these corrected measurements.…”

Improving Detectability of Seafloor Deformation From Bottom Pressure Observations Using Numerical Ocean Models

“…Previous studies have used OBP observations to identify specific slow slips (Ohta et al, 2012;Ito et al, 2013;Wallace et al, 2016). Recent efforts to improve sensitivities to find transient/ramp steps in OBP records have been increasingly made using ocean models, statistical methods, and/or machine learning in these regions (Hino et al, 2014;Gomberg et al, 2019;Muramoto et al, 2019;He et al, 2020).…”

“…Tidal signals have been precisely estimated by observed records or numerical predictions (Tamura et al, 1991;Egbert and Erofeeva, 2002). Lowerfrequency, non-tidal oceanic variations can be estimated by numerical ocean models, but their accuracy is not typically sufficient for detection of slow slips of less than a few centimeters in OBP observations (Fredrickson et al, 2019;Gomberg et al, 2019;Muramoto et al, 2019). Nevertheless, this approach of reducing ambient oceanic noises is fundamental, and is suitably applied for both multiple-station and single-station observations.…”