Improving Detectability of Seafloor Deformation From Bottom Pressure Observations Using Numerical Ocean Models - Dobashi, Yoichiro; Inazu, Daisuke (Frontiers in Earth Science, 2021)
We investigated ocean bottom pressure (OBP) observation data at six plate subduction zones around the Pacific Ocean. The six regions included the Hikurangi Trough, the Nankai Trough, the Japan Trench, the Aleutian Trench, the Cascadia Subduction Zone, and the Chile Trench. For the sake of improving the detectability of seafloor deformation using OBP observations, we used numerical ocean models to represent realistic oceanic variations, and subtracted them from the observed OBP data. The numerical ocean models included four ocean general circulation models (OGCMs) of HYCOM, GLORYS, ECCO2, and JCOPE2M, and a single-layer ocean model (SOM). The OGCMs are mainly driven by the wind forcing. The SOM is driven by wind and/or atmospheric pressure loading. The modeled OBP was subtracted from the observed OBP data, and root-mean-square (RMS) amplitudes of the residual OBP variations at a period of 3–90 days were evaluated by the respective regions and by the respective numerical ocean models. The OGCMs and SOM driven by wind alone (SOMw) contributed to 5–27% RMS reduction in the residual OBP. When SOM driven by atmospheric pressure alone (SOMp) was added to the modeled OBP, residual RMS amplitudes were additionally reduced by 2–15%. This indicates that the atmospheric pressure is necessary to explain substantial amounts of observed OBP variations at the period. The residual RMS amplitudes were 1.0–1.7 hPa when SOMp was added. The RMS reduction was relatively effective as 16–42% at the Hikurangi Trough, the Nankai Trough, and the Japan Trench. The residual RMS amplitudes were relatively small as 1.0–1.1 hPa at the Nankai Trough and the Chile Trench. These results were discussed with previous studies that had identified slow slips using OBP observations. We discussed on further accurate OBP modeling, and on improving detectability of seafloor deformation using OBP observation arrays.