Water depth dependence of long-range correlation in nontidal variations in seafloor pressure

Abstract

Temporal fluctuations in ocean bottom pressure originate from phenomena at varying spatio-temporal scales over the Earth's surface driven by atmospheric and oceanic circulation, tides, tsunamis, and tectonic deformation of the crust. Ocean-bottom pressure gauges (OBPs) are becoming widely used to measure tectonic signals, particularly those caused by tectonic deformation in some subduction zones (e.g.,

Using Seafloor Geodesy to Detect Vertical Deformation at the Hikurangi Subduction Zone: Insights From Self‐Calibrating Pressure Sensors and Ocean General Circulation Models

“…Fredrickson et al. (2019) demonstrated a clear depth‐dependence of oceanographic variations in APG data from Cascadia, and such depth dependence was also observed in the 2014 HOBITSS experiment in the northern portion of our study area (Inoue et al., 2021).…”

“…(2019) and Inoue et al. (2021). The APGs/POBSs are closer in depth to the composite reference site than the deep‐water reference site, therefore the reduction in noise level is likely due to the composite reference site recording more similar pressure variations on the slope caused by eddies and currents.…”

“…Removal of oceanographic noise from APG time series for seafloor geodetic studies is typically done by either (a) using a reference APG deployed in close proximity, assuming that the oceanographic noise is common‐mode across the network (Davis et al., 2015; Ito et al., 2013; Wallace et al., 2016), or (b) using simulated seafloor pressure data from OGCMs (Dobashi & Inazu, 2021; Gomberg et al., 2019; Muramoto et al., 2019). Thus far, the reference station method has produced the best results in terms of APG data variance reduction (e.g., Fredrickson et al., 2019; Inoue et al., 2021; Muramoto et al., 2019).…”

Non-tidal oceanographic fluctuation characteristics recorded in DONET ocean-bottom pressure time series using principal component analysis

“…Muramoto et al (2019) found that the oceanographic fluctuations recorded in the OBP time series off Hikurangi, New Zealand [Hikurangi Ocean Bottom Investigation of Tremor and Slow Slip (HOBITSS), which extends ~60km square; e.g., Wallace et al, 2016], became less similar as the difference in sea depth between OBP sites increased. Inoue et al (2021) used the standard deviation of the relative pressure time series between stations in the same observational network and observation period as Muramoto et al (2019), to evaluate the station distance and sea-depth difference in the similarity of the time series. These studies showed that the depth dependence was more significant than the station-distance dependence in the OBP time series.…”

Monitoring the 2021 Mw 8.2 Alaska Earthquake by an Offshore Seismic and Fluid Pressure Observation Network and Implications for Ocean‐Crust Dynamic Coupling

“…Besides its wide use in studying various types of ocean dynamics such as interannual upwelling variations, seasonal circulation variations, mesoscale oceanic eddies, ocean currents (e.g., Chelton et al., 2007; Hughes et al., 2018; Osborne & Burch, 1980; Saldías et al., 2021; Thomson et al., 2014), and tsunami generation and propagation (e.g., Kubota et al., 2022; Mulia & Satake, 2021; Saito & Kubota, 2020; Tanioka, 2020; Thomson et al., 2011), seafloor pressure monitoring has been used as a geodetic tool to monitor crustal deformation associated with submarine earthquakes and slow slip events (Davis et al., 2015; Hino et al., 2014; Ito et al., 2013; Sun et al., 2017; Wallace et al., 2016). For the same purpose, many recent studies were focused on untangling the mixed oceanographic and geophysical signals in ocean bottom pressure records (Dobashi & Inazu, 2021; Fredrickson et al., 2019; Gomberg et al., 2019; He et al., 2020; T. Inoue et al., 2021; Watts et al., 2021). Furthermore, high‐sampling‐rate seafloor pressure records were used as seismological measurements to characterize earthquake and slow earthquake source properties (e.g., An et al., 2017; Kubota et al., 2017; Kubota, Kubo, et al., 2021; Kubota, Saito, et al., 2021).…”