5:15 PM - 6:30 PM
[MIS19-P02] Effect of ocean fluid changes on pressure on the seafloor: JCOPE2M ocean assimilation data analysis on warm-core rings off the southeastern coast of Hokkaido, Japan on an interannual timescale
★Invited Papers
Keywords:pressure on the seafloor (PSF), steric effect on PSF, ocean isostasy anomaly (OIA), barotropic and baroclinic components, warm core ring (WCR), slow earthquakes
The relationship between sea surface height (SSH) and seawater density anomalies, which affects the pressure on the seafloor (PSF) anomalies off the southeastern coast of Hokkaido, Japan, was analyzed using the eddy-resolving spatial resolution ocean assimilation data of the JCOPE2M for the period 2001–2018. On an interannual (i.e., year-to-year) timescale, positive SSH anomalies of nearly 0.1 m appeared off the southeastern coast of Hokkaido, Japan, in 2007, associated with a warm-core ring (WCR), while stronger SSH anomalies (approximately 0.2 m) related to a stronger WCR occurred in 2016. The results show that the effects of such positive SSH anomalies on the PSF are almost canceled out by the effects of negative seawater density anomalies from the seafloor to the sea surface (SEP; steric effect on PSF) due to oceanic baroclinic structures related to the WCRs, especially in offshore regions with bottom depths greater than 1000 m. This means that oceanic isostasy is well established in deep offshore regions, compared with shallow coastal regions.
To further verify the strength of the oceanic isostasy, oceanic isostasy anomalies (OIAs), which represent the barotropic component of SSH anomalies, are introduced and analyzed in this study. OIAs are defined as the sum of the SSH anomalies and SEP anomalies. Our results indicate that the effect of oceanic fluid changes due to SSH and seawater density anomalies (i.e., OIAs) on PSF changes cannot be neglected on an interannual timescale, although the amplitudes of the OIAs are nearly 10% of those of the SSH anomalies in the offshore regions. Therefore, to better estimate the interannual-scale PSF anomalies due to crustal deformation related to slow earthquakes including afterslips, long-term slow slip events, or plate convergence, the OIAs should be removed from the PSF anomalies.
The analysis method used in this study, using the SSH anomalies and vertical profiles of temperature and salinity of the JCOPE2M to calculate the OIA, can be applied to observational data such as shipboard-CTD observation, Argo profiling floats observation CTD data, XCTD observations, and outputs of continuously-stratified ocean numerical models. If vertical profiles of temperature and salinity data from the sea floor to the sea surface are not available for the analysis period, the SEP cannot be calculated directly. In this case, we can approximately estimate the OIA indirectly from the regression coefficient between the SSH and SEP anomalies, calculated using the data observed during a period before (or after) the analysis period in the analysis area. In this study, the estimated OIA using such a method is called the “proxy of OIA” (POIA). In the presentation, we will demonstrate the POIA method using the observational AVISO SSH anomalies and regression coefficients between the JCOPE2M SSH anomalies and SEP anomalies.
This work was partly supported by the Japan Society for the Promotion of Science (JSPS), Grant-in-Aid for Scientific Research (KAKENHI) Grant Numbers JP15H02835, JP15H04228, JP17K05660, JP17K19093, JP19H02411, JP20H04349, JP20H2236, and JP20K04072.
To further verify the strength of the oceanic isostasy, oceanic isostasy anomalies (OIAs), which represent the barotropic component of SSH anomalies, are introduced and analyzed in this study. OIAs are defined as the sum of the SSH anomalies and SEP anomalies. Our results indicate that the effect of oceanic fluid changes due to SSH and seawater density anomalies (i.e., OIAs) on PSF changes cannot be neglected on an interannual timescale, although the amplitudes of the OIAs are nearly 10% of those of the SSH anomalies in the offshore regions. Therefore, to better estimate the interannual-scale PSF anomalies due to crustal deformation related to slow earthquakes including afterslips, long-term slow slip events, or plate convergence, the OIAs should be removed from the PSF anomalies.
The analysis method used in this study, using the SSH anomalies and vertical profiles of temperature and salinity of the JCOPE2M to calculate the OIA, can be applied to observational data such as shipboard-CTD observation, Argo profiling floats observation CTD data, XCTD observations, and outputs of continuously-stratified ocean numerical models. If vertical profiles of temperature and salinity data from the sea floor to the sea surface are not available for the analysis period, the SEP cannot be calculated directly. In this case, we can approximately estimate the OIA indirectly from the regression coefficient between the SSH and SEP anomalies, calculated using the data observed during a period before (or after) the analysis period in the analysis area. In this study, the estimated OIA using such a method is called the “proxy of OIA” (POIA). In the presentation, we will demonstrate the POIA method using the observational AVISO SSH anomalies and regression coefficients between the JCOPE2M SSH anomalies and SEP anomalies.
This work was partly supported by the Japan Society for the Promotion of Science (JSPS), Grant-in-Aid for Scientific Research (KAKENHI) Grant Numbers JP15H02835, JP15H04228, JP17K05660, JP17K19093, JP19H02411, JP20H04349, JP20H2236, and JP20K04072.