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

Autor: Hideto Otsuka, Yusaku Ohta, Ryota Hino, Tatsuya Kubota, Daisuke Inazu, Tomohiro Inoue, Narumi Takahashi
Rok vydání: 2023
DOI: 10.22541/essoar.167458069.92503323/v1
Popis: Ocean bottom pressure-gauge (OBP) records play an important role in seafloor geodesy, but oceanographic fluctuations in OBP data are a major source of noise in seafloor transient crustal deformation observations, including slow slip events (SSEs), so it is important to evaluate them properly. To extract the significant characteristics of the oceanographic fluctuations, we applied principal component analysis (PCA) to the 3-year Dense Oceanfloor Network System for Earthquakes and Tsunamis (DONET) OBP time series for 40 stations during 2016–2019. PCA can separate several oceanographic signals based on the characteristics of their spatial distributions, although transient tectonic signals could not be clearly confirmed from the observed pressure records. The higher-order modes of the principal component reflected the oceanographic variation along the sea depth, and we interpreted that they were caused by the strength or weakness and meandering of ocean geostrophic currents, based on a comparison to the global ocean model ECCO2 by “Estimating the Circulation and Climate of the Ocean” (ECCO) consortium. In addition, to evaluate the ability of PCA to separate transient crustal deformation from oceanographic fluctuations, we conducted a synthetic test assuming an SSE by rectangular faults. The assumed synthetic tectonic signal can be separated from the oceanographic signals and included in the principal component independently depending on its amplitude. We proposed a transient event-detection method based on the spatial distribution variation of a specific principal component with or without a tectonic signal. This method can detect transient tectonic signals larger than moment-magnitude scale M 5.9 from OBP records.
Databáze: OpenAIRE