Estimating climatic temperature change in the ocean with synthetic acoustic apertures

An acoustic tomography simulation is carried out in the eastern North Pacific ocean to assess whether climate trends are better detected and mapped with mobile or fixed receivers. In both cases, acoustic signals from two stationary sources are transmitted to ten receivers. Natural variability of the sound-speed field is simulated with the Naval Research Laboratory (NRL) layered-ocean model. A sequential Kalman-Bucy filter is used to estimate the sound speed field, where the a priori error covariance matrix of the parameters is estimated from the NRL model. A spatially homogeneous climate trend is added to the NRL fluctuations of sound speed, but the trend is not parameterized in the Kalman filter. Acoustic travel times are computed between the sources and receivers by combining sound speeds from the NRL model with those from the unparameterized climate trend. The effects of the unparameterized climate trend are projected onto parameters which eventually drift beyond acceptable limits. At that time, the unparameterized trend is detected. Mobile and fixed receivers detect the trend at about the same time. At detection time, however, maps from fixed receivers are less accurate because some of the unparameterized climate trend is projected onto tile spatially varying harmonics of the sound-speed field. With mobile receivers, the synthetic apertures suppress the projection onto these harmonics. Instead, the unparametrized trend is correctly projected onto the spatially homogeneous portion of the parameterized sound-speed field