Sound speed profiles in high spatiotemporal resolution using multigrid three-dimensional variational method: a coastal experiment off northern Shandong Peninsula

It is essential to acquire sound speed profiles (SSPs) in high-precision spatiotemporal resolution for undersea acoustic activities. However, conventional observation methods cannot obtain high-resolution SSPs. Besides, SSPs are complex and changeable in time and space, especially in coastal areas. We proposed a new space-time multigrid three-dimensional variational method with weak constraint term (referred to as STC-MG3DVar) to construct high-precision spatiotemporal resolution SSPs in coastal areas, in which sound velocity is defined as the analytical variable, and the Chen-Millero sound velocity empirical formula is introduced as a weak constraint term into the cost function of the STC-MG3DVar. The spatiotemporal correlation of sound velocity observations is taken into account in the STC-MG3DVar method, and the multi-scale information of sound velocity observations from long waves to short waves can be successively extracted. The weak constraint term can optimize sound velocity by the physical relationship between sound velocity and temperature-salinity to obtain more reasonable and accurate SSPs. To verify the accuracy of the STC-MG3DVar, SSPs observations and CTD observations (temperature observations, salinity observations) are obtained from field experiments in the northern coastal area of the Shandong Peninsula. The average root mean square error (RMSE) of the STC-MG3DVar-constructed SSPs is 0.132 m/s, and the STC-MG3DVar method can improve the SSPs construction accuracy over the space-time multigrid 3DVar without weak constraint term (ST-MG3DVar) by 10.14% and over the spatial multigrid 3DVar with weak constraint term (SC-MG3DVar) by 44.19%. With the advantage of the constraint term and the spatiotemporal correlation information, the proposed STC-MG3DVar method works better than the ST-MG3DVar and the SC-MG3DVar in constructing high-precision spatiotemporal resolution SSPs.