Calibration of the Instrumental Errors on Marine Gravity Recovery from SWOT Altimeter

Abstract

Abstract The wide-swath altimetry mission, Surface Water and Ocean Topography (SWOT), makes it possible to further break through the accuracy and resolution of marine gravity field recovery. However, as its main payload, the Ka-band radar interferometer (KaRIN) is easy to be affected by the spacecraft attitude, mechanical deformations and dual antenna signal reception status, which generates instrumental errors including roll errors, phase errors, baseline dilation errors, timing errors, and KaRIN noise. Together with ocean temporal variations, the instrumental errors have large effects on the SWOT Sea Surface Height (SSH) observations and hence the marine gravity field recovery. Here, taking the sea area around Japan as an example, we investigated the calibrations of instrumental errors and ocean temporal variations on the recovery of the marine gravity field. The SSH observations of SWOT are first simulated by Mean Sea Surface (MSS), Absolute Dynamic Topography (ADT), Mean Dynamic Topography (MDT) and instrumental errors. Next, the influence of instrumental errors on determining vertical deflection within single-cycle data was analyzed. Then, three calibration methods (KaRIN/KaRIN cross-calibration, Representative KaRIN/KaRIN cross-calibration, and KaRIN/Nadir cross-calibration) are used to reduce the instrumental errors; the experimental results show KaRIN/KaRIN cross-calibration is the optimal one. Last, for the multi-cycle observations containing ocean temporal variations, crossover calibration is done in single cycle and then followed by collinear adjustment in multi-cycles. This approach is verified by considering 18 simulated cycles that cover almost 1 year. Our result indicates an improvement in the accuracy of marine gravity anomaly by about 45% compared to that of one cycle. The calibration strategy of instrumental errors and ocean temporal variations can be used for high-precision marine gravity field recovery with abundant SWOT observations in the near future.