Marine gravity and bathymetry modelling from recent satellite altimetry

Abstract

Marine gravity has been modelled from satellite radar altimetry for more than two decades. Range precision and spatial coverage of altimetry observations are the main factors limiting the accuracy of predicted gravity field. Since 2010, CryoSat-2 has been measuring sea surface heights with a 369-day repeat cycle. By combining these high precision and dense CryoSat-2 observations with Jason-1 and SARAL/Altika geodetic mission data, the accuracy of marine gravity is expected to improve not only over the open ocean, but also near the coastal zone. This study aims to improve the gravity field near the coastal zone using least square collocation algorithm. CryoSat-2 observations obtained from different retrackers are used. Residual Terrain Modelling (RTM) is considered during the modelling process. The resolution of digital topography (including bathymetry) is the limiting factor in the application of RTM. Results from Mediterranean case study show that RTM is partly effective in reducing the residual height anomalies. Sediments in the deep ocean and constant density assumptions are believed to be the error sources. Prediction error for gravity anomalies is better than 4 mGal along the coast. Gravity field predicted from altimetry data with the most coastal coverage and retracked with the narrow primary peak retracker gives the best precision of 2.07 mGal. In the Indonesian case study, height anomalies are reduced by removing RTM effects. Strong signal in the remaining residual field suggests long wavelength problems from Earth Gravitational Model 2008 (EGM08). Existing Arctic bathymetry is compiled from sparse ship soundings and digitized depth contours. Sea floor topography can be inverted from downward continued marine gravity anomalies in a limited wavelength band. Based on the original filter presented in Smith and Sandwell (1994), a modified version, which limits the prediction to the 15-57 km wavelength band, is proposed and successfully used for bathymetry inversion from gravity anomalies. In this study, the first-ever Arctic bathymetry inverted from DTU17 marine gravitymodel is presented. Validation with two independent multi-beam ship soundingsurveys give an absolute mean difference of 50.8 m and 36.9 m, with 119.5 mand 77.6 m standard deviations, respectively. The use of modified filter yield an improvement of more than 50% compared to the original filter which predicts topography in the 15-160 km band. Predicted bathymetry using modified filtershows good agreement with ship soundings. A problematic ∼ 1000 m deep valley in existing bathymetry map is resolved over the Chukchi plateau. Predicted bathymetry from gravity can be used to fill the gaps where there are no ship soundings in the next generation of Arctic bathymetry.