LAUSR

Abstract In this paper, an improved numerical scheme is developed to estimate the initial conditions (ICs) based on a three-dimensional suspended sediment transport model (3D SSTM) with adjoint data assimilation, and the method is then applied to Hangzhou Bay as an example. Specifically, the ICs are estimated by assimilating artificial observations in twin experiments and suspended sediment concentrations (SSCs) retrieved from the Geostationary Ocean Color Imager (GOCI) in practical experiments. In the twin experiments, the sensitivity of the estimated ICs to several influential factors is discussed. The results demonstrate that the conjugate descent algorithm of Fletcher is proven to be better than the steepest descent, finite memory BFGS, and five other conjugate gradient algorithms in estimating the ICs; the estimated ICs are sensitive to initial guess values, and appropriate initial values are necessary for improving the efficiency of convergence and obtaining good results. Additionally, the errors of observations can significantly influence the estimated results. In contrast, the estimated results are not very sensitive to cloud coverage, errors in the background flow field, and length of the assimilation time window. In practical experiments, according to the conclusions of twin experiments, an improved 3D SSTM with the adjoint method is developed for Hangzhou Bay, and the surface GOCI-retrieved SSCs during typical neap and spring tidal cycles are assimilated to estimate the practical ICs. The experimental results imply that with the present estimation method, more accurate ICs can be obtained, which indicates that the adjoint method is effective in the estimation of the ICs in SSTMs. Furthermore, this study verifies that accurate ICs are critical for the numerical modeling of SSCs on the tidal cycle scale. This study is not only useful for further improving the accuracy of ICs in SSTMs but also suggestive for the initialization schemes of other matter transport models.