Seafloor Crustal Deformation on Ocean Bottom Pressure Records With Nontidal Variability Corrections: Application to Hikurangi Margin, New Zealand
Abstract
Ocean bottom pressure (OBP) observations are a powerful tool for determining vertical crustal displacements, especially due to earthquakes and slow earthquakes, with centimeter-level resolution. In these studies, removal of oceanographic noise (tens of centimeters) is required to identify centimeter-level crustal deformation. We undertake barotropic modeling to remove oceanographic signals from data from an OBP array deployed offshore New Zealand in 2014/2015. We show that removing the nontidal component calculated from a barotropic ocean model reduces the variance in the data by about 66% and provides a feasible means to resolve pressure changes due to crustal deformation during the slow slip events. We also discuss the vertical displacements from slow slip events that occurred in late September to mid-October 2014, and we outline our procedure for processing OBP data.
Key Points
- The oceanographic corrections from our model help to reduce noise in ocean bottom pressure data recorded during slow slip event
- We show a barotropic oceanographic model can be used to reduce the variance in seafloor pressure measurements by about 66%
- Our oceanographic model is particularly valuable for the shallower-water sites
Plain Language Summary
We developed a new method for determining pressure changes due to slow slip events (SSEs) on offshore subduction plate boundaries by using information from the ocean bottom pressure records and numerical simulation. We use an oceanographic model to correct the seafloor pressure data for oceanographic signals, so that centimeter-level vertical deformation of the seafloor during the SSEs can be isolated. We show that this method can be used to identify SSEs that occurred off the coast of New Zealand in 2014. Our results indicate that our ocean model can be a useful tool to use ocean bottom absolute pressure gauge data to resolve crustal deformation.
1 Introduction
Slow slip events (SSEs) involve transient aseismic slip across a fault that can last weeks to months. The presence and spatiotemporal evolution of SSEs in the shallow portions of subduction zones (near the trench) have been particularly difficult to document due to the submarine nature of the near-trench region. There are relatively few observations of this phenomenon near the trench (e.g., Araki et al., 2017; Davis et al., 2015; Wallace et al., 2016). Ocean bottom pressure (OBP) observation networks are becoming more widely used to measure offshore crustal deformation because they enable centimeter-level resolution of continuous vertical seafloor displacement during SSEs, earthquakes, and other transient deformation events.
Pressure changes observed at the seafloor are dominated by the influence of oceanic variations, such as tidal and nontidal components (e.g., Hino et al., 2014). Conventionally, to detect centimeter-level crustal deformation, oceanographic noise is removed by taking the difference between pressure records at OBP sites in the deforming zone and one or more nearby reference sites (preferably outside of the deforming zone, often on the subducting plate), which cancels out any common-mode tidal and nontidal components (e.g., Ito et al., 2013; Wallace et al., 2016). However, an alternative approach is to estimate the nontidal component through oceanographic modeling, in order to eliminate this component from the raw data. This is particularly useful to help isolate vertical displacement of the seafloor during SSEs, as the duration of the SSEs and nontidal oceanic variations often overlap.
Inazu et al. (2012) developed a global barotropic ocean model driven by assimilated wind vectors that has been used to remove nontidal oceanographic signals to isolate seafloor vertical displacement using OBP data. Applying this ocean model to the 2011 Tohoku-Oki earthquake data, the authors succeeded in detecting crustal deformation due to afterslip during the largest foreshock, which occurred just before the 2011 earthquake (Inazu et al., 2012). These results suggest that detailed modeling of the nontidal component can help to remove this noise from OBP records, to resolve transient tectonic deformation, potentially without the need for nearby reference sites to undertake oceanographic noise removal. In this study, we performed a quantitative evaluation of the method using reference sites compared to a new approach outlined here using a nontidal ocean model, to remove noise from OBP data acquired at the offshore Hikurangi subduction zone during large SSEs in 2014.
2 Seafloor Pressure Data at Offshore Hikurangi to Detect Slow Slip
The Hikurangi margin is the site of westward subduction of the Pacific Plate beneath the east coast of the North Island of New Zealand. It is an area of well-documented shallow SSEs (e.g., Wallace et al., 2012, 2016; Wallace & Beavan, 2010). The northern Hikurangi margin is an ideal location to investigate shallow SSEs using seafloor geodetic methods, owing to the proximity of SSEs to the onshore geodetic network, short SSE recurrence interval of 1–2 years, and a short SSE duration of 2–3 weeks (e.g., Wallace et al., 2012).
The Hikurangi Ocean Bottom Investigation of Tremor and Slow Slip experiment began in 2014 to investigate offshore SSEs and their relationship to tectonic tremor and earthquakes along the northern Hikurangi margin. In 2014, 24 autonomous OBPs and 15 Ocean Bottom Seismometers were deployed from May 2014 to June 2015 off the eastern coast of the North Island (Wallace et al., 2016). During the experiment, two SSEs were observed by the onshore Global Navigation Satellite Systems network in September/October 2014 and December/January 2014/2015 (e.g., Figure 1; the SSEs spanned days 265–285 and 350–370, where day 1 is 1 January 2014). By using reference sites on the subducting Pacific plate to remove the common mode oceanographic noise, Wallace et al. (2016) were able to resolve 1–5 cm of uplift of the seafloor during the September/October SSE. As an alternative to using reference sites to remove oceanographic noise, we attempt to detect SSE signals from the September/October event in the observed OBP data by using a barotropic model to remove the nontidal component of the OBP changes.



3 Methods
3.1 Tidal and Nontidal Effect




As an external forcing, we used 6-hourly surface air pressure and surface wind vector data published by the 55-year Japanese Reanalysis Project (Harada et al., 2016; Kobayashi et al., 2015) and bathymetry and coastline data provided by GEBCO_08 (http://www.gebco.net./). Numerical simulations with a horizontal resolution of 1/12° were carried out, following Inazu et al. (2012), who found that this resolution is optimal when using ocean bottom topography data with similar resolution to that of GEBCO_08. Each fixed parameter setting of the model, including the grid size, was optimized using in situ OBP data (Inazu et al., 2012).
First, we subtracted the tidal components from the raw data using Baytap-G (Tamura et al., 1991). After subtracting the tidal component, we applied a 1-day corner decimation filter to the time series. Following this, we corrected the nontidal oceanic variation predicted by the ocean model described above.
3.2 Evaluating Vertical Displacement and Drift Component


3.3 Variance Reduction

4 Results and Discussion
As a result of calculating VR for each case, we found a depth dependence of VR when we used reference data to cancel oceanographic noise (Figure 2). For the approach using reference sites, shallower-water (
1,000 m) sites LOBS8, TXBPR2, and LOBS1 show lower VR (50–60%), compared to the remaining deeper-water sites (
1,000 m), where VR from using the reference sites was as high as 80–90% (installation depth is shown in Table 1). This is not surprising because there is a much larger horizontal distance between the shallow-water sites and the reference sites compared to the smaller distance between deep-water sites and the reference sites. Thus, the oceanographic signals between the shallow water sites and the reference sites are less similar, and less of this noise can be removed. Differencing pressure data from adjacent shallow water sites also removes most of the variance; however, using that procedure would also remove any slow slip signals that are common to those sites. In contrast, using the barotropic model produces a slightly higher VR for the shallow-water sites TXBPR2 and LOBS8 (58–69%) compared to using the reference data (54–58%) for these two sites (Figures 2 and 3a). However, the VR achieved by using the barotropic model at the remaining sites was 52–75%. This is a substantially smaller VR compared to the approach of using reference sites, suggesting that the reference site data may be more effective in removing the oceanographic noise in this particular case, with the exception of some of the shallow water sites (Figure 2). Overall, when using the barotropic model the average VR is ~66%, and when using reference data, it is ~80%. Calculated formal uncertainties are 44% higher when using the oceanographic model compared to that using reference data.

Site | Installed depth | Site position | Start | End |
---|---|---|---|---|
(m) | Longitude (°E), latitude (°N) | (day/month/year) | (day/month/year) | |
LOBS1 | 993 | 178.82, −38.59 | 14/05/2014 | 21/06/2015 |
EBPR3 | 1031 | 178.65, −38.69 | 12/05/2014 | 21/06/2015 |
TXBPR2 | 779 | 178.57, −38.71 | 17/05/2014 | 25/06/2015 |
SBPR1 | 2453 | 178.89, −38.72 | 13/05/2014 | 26/06/2015 |
EBPR2 | 1013 | 178.62, −38.73 | 11/05/2014 | 20/06/2015 |
EBPR1 | 989 | 178.68, −38.75 | 13/05/2014 | 20/06/2015 |
LOBS8 | 651 | 178.46, −38.84 | 14/05/2014 | 26/06/2015 |
SBPR2 | 2116 | 178.88, −38.85 | 12/05/2014 | 23/06/2015 |
SBPR3 | 1360 | 178.76, −38.89 | 12/05/2014 | 23/06/2015 |
TXBPR5 | 1246 | 178.57, −38.95 | 11/05/2014 | 26/06/2015 |
LOBS6 | 1874 | 178.80, −38.98 | 14/05/2014 | 25/06/2015 |
LOBS9 | 1457 | 178.52, −39.07 | 11/05/2014 | 23/06/2015 |
LOBS10 | 1444 | 178.31, −39.13 | 11/05/2014 | 23/06/2015 |
TXBPR1 | 3532 | 179.00, −38.76 | 16/05/2014 | 27/06/2015 |
LOBS4 | 3441 | 178.98, −39.12 | 17/05/2014 | 26/06/2015 |

We calculated power spectra of the original data time series and the data time series after applying the reference correction or the oceanographic model correction to compare which frequency bands the two methods provide the most VR. The short time series leads to high variance in the spectra, but the comparison shows that the oceanographic model reduces the variance most at periods between 50 and 20 days (Figure 3b). At shorter period the reference data produce more VR, while the oceanographic model may increase the variance slightly at the shortest periods. The net result is that the oceanographic model provides less VR than the reference site data (Table 2) due to insufficient correction of short-period components.
Site | Ocean model (displacement [cm]/σ [hPa]) | Reference: TXBPR1 (displacement [cm]/σ [hPa]) | Reference: (TXBPR1 + LOBS4) /2 (displacement [cm]/σ [hPa]) | Reference: LOBS4 (displacement [cm]/σ [hPa]) |
---|---|---|---|---|
LOBS1 | 0.20/1.66 | 0.31/1.54 | 1.16/1.61 | 1.15/1.58 |
EBPR3 | −0.08/2.25 | 0.73/1.49 | 0.74/1.44 | 0.74/1.42 |
TXBPR2 | 0.47/1.53 | 0.80/1.63 | 0.80/1.60 | 0.79/1.60 |
SBPR1 | 0.28/1.31 | 0.92/0.51 | 1.19/0.56 | 1.11/0.64 |
EBPR2 | −1.88/2.98 | 1.14/2.03 | 1.02/1.61 | 1.10/2.07 |
EBPR1 | 0.32/2.10 | 0.68/1.51 | 0.67/1.45 | 0.66/1.42 |
LOBS8 | 1.83/1.41 | 2.72/1.69 | 2.69/1.63 | 2.68/1.61 |
SBPR2 | 0.29/1.26 | 1.03/0.60 | 1.03/0.61 | 1.44/0.71 |
SBPR3 | 1.01/1.32 | 1.54/0.91 | 2.09/0.90 | 2.07/0.85 |
TXBPR5 | 1.14/1.34 | 2.09/1.13 | 2.07/1.05 | 2.05/1.01 |
LOBS6 | 0.87/1.26 | 1.37/0.66 | 1.36/0.64 | 1.92/0.74 |
LOBS9 | 1.29/1.21 | 1.95/0.82 | 1.97/0.75 | 1.98/0.74 |
LOBS10 | 0.78/1.47 | 1.01/0.80 | 1.67/0.85 | 1.68/0.82 |
The differences between the three choices of reference data (TXBPR1, LOBS4, and an average of the reference sites) used in this study were small. When we use reference data to remove oceanographic noise, the displacement estimates are on average 65% larger compared to those using the oceanographic model (Table 2). In almost all cases, we estimated uplift above the SSE source. These results are generally consistent with Wallace et al. (2016; Figure 4), although the estimated vertical displacements in this study are slightly smaller, we think, due to differences in our procedures used for drift removal.

Coherent signals exist in each time series after correction with the ocean model (Figures 3a and S3). The residual time series show that the barotropic model has some limitations in reproducing the amplitude of the nontidal components, but more of the variance in seafloor pressure in the Hikurangi area is explained by the oceanographic model compared to the average value of variance obtained by Inazu et al. (2012).
The standard deviation (1σ) after removing the nontidal ocean model is still on average 30% higher than the results from removing the oceanographic noise using an average of the reference sites as reference data (Table 2). Further studies with more sophisticated oceanographic models that can remove oceanographic noise more precisely, and that also include additional oceanographic effects, are required to enable more precise determinations of vertical displacement due to SSEs from OBP data.
5 Conclusions
Here we demonstrate a method to correct for nontidal oceanographic variations on OBP data, to help resolve seafloor crustal deformation. We apply this approach to OBP data that were collected during two SSEs offshore New Zealand in late 2014. Correcting the data with the nontidal oceanographic models provides on average a 66% VR, following removal of tidal and instrument drift components. This is 18% less on average than the VR provided by the conventional approach of using nearby reference sites (average VR 80%) to remove the common-mode oceanographic noise. The reference sites (located on the subducting plate) do a more effective job correcting oceanographic noise at the deep-water sites, where the oceanography is more similar to that at the reference sites. In contrast, the barotropic model does a better job reducing variance at some of the shallow-water sites, where the oceanographic characteristics are not as well characterized by the deep-water reference sites. Overall, our work suggests that barotropic models can remove a large component of the oceanographic noise present in OBP records but are not yet sufficient to accurately resolve centimeter-level deformation of the seafloor. We anticipate that future work incorporating improved oceanographic observations and modeling that also accounts for more realistic physical processes will help to further improve use of OBP records for seafloor geodesy.
Acknowledgments
We thank Motoyuki Kido and Makiko Sato for their cooperation in the observations. This research was supported by JSPS KAKENHI (grant 26257206) and JST-JICA SATREPS (grant 15543611) for Y. I. and T. M. and JSPS KAKENHI (grant 26000002) for R. H. and Y. I. The OBP data used in this study are provided by GNS science and Columbia University. Support for data acquisition and ship time was provided by the U.S. National Science Foundation, GNS Science, and Land Information New Zealand's Oceans 2020 program. L. M. W. acknowledges support from a New Zealand MBIE Endeavour grant and NSF grant OCE-1334654. We thank the captain and crew of the New Zealand R/V Tangaroa and U.S. R/V Roger Revelle for deployment and recovery of OBP instruments. GMT software (Wessel et al., 2013) was used to draw the figures.