Novel Method for the Estimation of Vertical Temperature Profiles Using a Coastal Acoustic Tomography System

Abstract

Systems based on remote sensing technology, which use reciprocal acoustic signals to continuously monitor changes in the coastal oceanic environment, are referred to as coastal acoustic tomography (CAT) systems. These systems have been applied in regions in which heavy ship traffics, fishing and marine aquaculture activities make it difficult to establish in situ oceanic sensor moorings. Conventionally, CAT measurements were used to successfully produce horizontal maps of the depth-averaged current velocity and temperature in these coastal regions without attempting to produce a vertical temperature profile. This prompted us to propose a new method for vertical temperature profile estimation (VTPE) from CAT data using the available sea surface temperature (SST), near-bottom temperature (NBT), and water depth. The VTPE method was validated using data-assimilated and tide-included high-resolution ocean model outputs, including tide data, by comparing the estimated and simulated temperatures. Measurements were performed in the southern coastal region of Korea, where two CAT stations were moored to establish a continuous coastal ocean monitoring system. The validation results revealed that the algorithm performed well across all seasons. Sensitivity tests of the VTPE method with reasonable realistic random errors in the SST, NBT, and acoustic travel time measurements demonstrate that the method is applicable to CAT observation data because the monthly mean root-mean-squared difference (RMSD) for the vertical profiles for February, May, August, and November were 0.23, 0.30, 0.50, and 0.24°C, respectively. The VTPE method was applied to the CAT observation datasets acquired in February and August. The transceivers at the CAT stations were at depths 11 and 6 m on average. The RMSD between the estimated and observed temperatures in the middle layer (∼3 m depth) between two stations in February and August were 0.08 and 0.60°C, respectively, the accuracy of which is sufficient in largely time-varying coastal environments. We provide a novel method for continuous coastal subsurface environmental monitoring without interrupting maritime traffic, fishing, and marine aquaculture activities.