Potential utility of three-dimensional temperature and salinity fields estimated from satellite altimetry and Argo data for improving mesoscale reproducibility in regional ocean modeling

Abstract:

Mesoscale oceanic structure and variability are required to be reproduced as accurately as possible in realistic regional ocean modeling. Uchiyama et al. (2012) demonstrated with a submesoscale eddy-resolving JCOPE2-ROMS downscaling oceanic modeling system that the mesoscale reproducibility of the Kuroshio meandering along Japan is significantly improved by introducing a simple restoration to data which we call “TS nudging” (a.k.a. robust diagnosis) where the prognostic temperature and salinity fields are weakly nudged four-dimensionally towards the assimilative JCOPE2 reanalysis (Miyazawa et al., 2009). However, there is not always a reliable reanalysis for oceanic downscaling in an arbitrary region and at an arbitrary time, and therefore alternative dataset should be prepared. Takano et al. (2009) proposed an empirical method to estimate mesoscale 3-D thermal structure from the near real-time AVISO altimetry data along with the ARGO float data based on the two-layer model of Goni et al. (1996). In the present study, we consider the TS data derived from this method as a candidate. We thus conduct a synoptic forward modeling of the Kuroshio using the JCOPE2-ROMS downscaling system to explore potential utility of this empirical TS dataset (hereinafter TUM-TS) by carrying out two runs with the T-S nudging towards 1) the JCOPE2-TS and 2) TUM-TS fields.　An example of the comparison between the two ROMS test runs is shown in the attached figure showing the annually averaged surface EKE. Both of TUM-TS and JCOPE2-TS are found to help reproducing the mesoscale variance of the Koroshio and its extension as well as its mean paths, surface KE and EKE reasonably well. Therefore, the AVISO-ARGO derived empirical 3-D TS estimation is potentially exploitable for the dataset to conduct the T-S nudging to reproduce mesoscale oceanic structure.