3D assimilation of Hiroshima Bay acoustic tomography data into a Princeton Ocean Circulation Model

Abstract

A baroclinic data assimilation, based on the ensemble Kalman filter (EnKF) method, with coastal acoustic tomography (CAT) data is first applied to Princeton Ocean Model (POM) to elucidate a 3D structure of coastal upwelling which occurred in Hiroshima Bay due to a northerly wind from a typhoon. The CAT experiment with four acoustic stations was performed from Sept. 11 to Sept. 25, 2013, in the northern part of Hiroshima Bay, Japan. Reciprocal data were acquired at three stations and along three transmission lines with a triangular array and travel time were identified every 10 min for the first and second arrival rays which travel at different depth ranges. As for the EnKF method, the Kalman gain was determined to minimize the observed and simulated travel time differences and summations. The model error covariance was given by adding pseudorandom noises (zero mean value and one variance) with an appropriate multiplication factor to the POM result. The observation error covariance was estimated from the variation of observed travel times. A 3D structure of coastal upwelling which was difficult to be simulated by the POM was reconstructed by data assimilation and compared with the CTD result.