Marine gravity modelling from SARAL/AltiKA data using the Least Square Collocation for the Red Sea

Abstract

Marine gravity has been modeled using satellite radar altimetry for more than two decades. However, the accuracy of the predicted gravity field is constrained by the range precision and spatial coverage of the altimetry observations. The objective of this research is to enhance the gravity field over the Red Sea by utilizing the Least Square Collocation (LSC) algorithm with SARAL/AltiKA mission observations. The marine gravity field in the Red Sea was determined by using observed Sea Surface Heights (SSHs) obtained from the SARAL/AltiKA mission. The Remove-Compute-Restore (RCR) technique, the Residual Terrain Modelling (RTM) reduction method, and the LSC technique are used to estimate the marine gravity. To evaluate the accuracy of the SARAL/AltiKA predicted model, it was compared against two global altimetry gravity models (DTU21 and SSv29.1) using 42331 shipborne gravity measurements over the Red Sea. The SARAL/AltiKA predicted model showed the best results, with root mean square error and standard deviation values of 6.29 and 5.93 mGal, respectively. The impact of bathymetry depths on the SARAL/AltiKA predicted gravity model accuracy was also investigated. The SARAL/AltiKA predicted gravity model produced better results for water depths up to 1000 m when compared with shipborne data, while the SSv29.1 model performed better for depths between 1000 and 3000 m due to the performance of the residual slopes of the SSH estimation technique used in the deep areas.