Open and coastal seas interactions south of Japan represented by an ensemble Kalman filter

Abstract

We investigated the feasibility of the ensemble Kalman filter (EnKF) to reproduce oceanic conditions south of Japan. We have adopted the local ensemble transformation Kalman filter algorithm based on 20 members' ensemble simulations of the parallelized Princeton Ocean Model (the Stony Brook Parallel Ocean Model) with horizontal resolution of 1/36°. By assimilating satellite sea surface height anomaly, satellite sea surface temperature, and in situ temperature and salinity profiles, we reproduced the Kuroshio variation south of Japan for the period from 8 to 28 February 2010. EnKF successfully reproduced the Kuroshio path positions and the water mass property of the Kuroshio waters as observed. It also detected the variation of the steep thermohaline front in the Kii Channel due to the intrusion of the Kuroshio water based on the observation, suggesting efficiency of EnKF for detection of open and coastal seas interactions with highly complicated spatiotemporal variability.

Assimilation of high-resolution sea surface temperature data into an operational nowcast/forecast system around Japan using a multi-scale three-dimensional variational scheme

“…In this case, skills of MS-3DVARs and SS3DVARs are comparable to each other (Li et al 2015a). In real situations, however, the distributions of the available data are not uniform; in particular, the high-resolution infrared SST including the Himawari-8 product involves the data missing areas due to the cloud noise (e.g., Miyazawa et al 2013), and in situ temperature and salinity data are obtained with quite coarse resolution (e.g., Miyazawa et al 2012). The MS-3DVAR scheme effectively assimilates the localized and patchy dense-distributed observation data without unrealistic smoothing and well spreads the information of the sparse-distributed data (Li et al 2015a).…”

Data Assimilation of the High-Resolution Sea Surface Temperature Obtained from the Aqua-Terra Satellites (MODIS-SST) Using an Ensemble Kalman Filter

“…We examine the assimilation effects of high-resolution SST data using an EnKF system developed for investigation of the Kuroshio variation south of Japan [10]. The EnKF system utilizes twenty members of ensemble simulations, calculated by a sigma-coordinate ocean circulation model covering a region south of Japan: 30°-35°N, 133°-140°E ( Figure 1) with horizontal 1/36° resolution and 31 vertical levels, which was developed on the basis of a parallel calculation code of the Princeton Ocean Model (sbPOM) [15].…”

“…Recent developments of oceanic data assimilation combined with numerical ocean models are fundamentally based on intensive use of satellite data including SST, e.g., [10]. A proper combination of advanced data assimilation methods and high-resolution ocean models could contribute to production of the noise-free SST analysis with a high resolution because dynamic interpolation of physical variables is one of important roles of the data assimilation.…”

“…As a first step, focusing on the SST front variability affected by the internal ocean dynamics, we examine the winter SST condition rather than the summer SST condition, in which the SST front tends to be undetectable due to increased solar insolation [12]. We adopt the Ensemble Kalman Filter (EnKF) [13], which may be suitable for the fine representation of the front variability, because EnKF allows spatiotemporally varying 'flow-dependent' error covariance working to reasonably conserve the sharp front property without unrealistic smoothing, given that the model resolves the associated front variability [10]. This paper is organized as follows.…”

Editorial—the 5th International workshop on modeling the ocean (IWMO 2013)

“…Although the assimilation model does not beat persistence (from AVISO), the level of EKE is in better agreement with the drifter data. It will be interesting in the future to compare their results with those obtained using the Princeton Ocean Model (POM) and different assimilation schemes (e.g., Miyazawa et al 2012;Xu et al 2013;Xu and Oey 2014). Chang and Oey (2014) used a parallelized version of the POM to analyze eddies that are generated by the instability of the North Pacific Subtropical Counter Current (STCC).…”