Abstract
A new Mean Sea Surface (MSS) model called Shandong University of Science and Technology Antarctic Mean Sea Surface model (SDUST_ANT MSS) in the Antarctic Ocean is presented and validated in this paper. The SDUST_ANT MSS updates the DTU18 MSS with 6 years of Exact Repeat Mission (ERM) and Geodetic Mission (GM) data from HY-2A. Collinear adjustment was applied to all the ERM data to obtain the along-track mean sea surface height. Oceanic variability has been removed from the GM data. Crossover adjustment was applied to both the ERM and GM data. We constructed the HY-2A_MSS using HY-2A altimetry data based on optimal interpolation method. Several types of errors (such as white noise, residual effect of oceanic variability, and long wavelength bias) have been taken into account for the determination of MSS using optimal interpolation method. The SDUST_ANT MSS was constructed by mapping HY-2A_MSS onto the DTU18 MSS. The SDUST_ANT MSS was compared with DTU18 MSS and CNES_CLS15 MSS. At wavelengths below 150 km, differences between models are consistent with seafloor topographic gradient. At wavelengths above 150 km, differences are affected by the mesoscale activities and the altimetry errors in coastal areas. The errors of the three models, as indicated by their power spectral densities (PSDs), are of similar orders of magnitude. The absolute error is slightly smaller in SDUST_ANT than in CNES_CLS15 or DTU18.
Highlights
The Mean Sea Surface (MSS) is an essential parameter in oceanography and geophysics
This paper describes the development of the Shandong University of Science and Technology Antarctic (SDUST_ANT) MSS model on the basis of the earlier DTU18 MSS model and HY-2A altimetry data
We calculated the average trajectory and average sea level from repeat orbit altimetry data to reduce the influence of the variability of sea level with time, and especially the effects of abnormal sea level changes caused by large-scale oceanographic anomalies on the results
Summary
The Mean Sea Surface (MSS) is an essential parameter in oceanography and geophysics. An accurate MSS is necessary for the analysis of oceanic variability using satellite altimetry and can be used for the calibration or validation of satellite altimetry data (Jin et al, 2016). Oceanic variabilities are dominated by seasonal variability and interannual signal, they include sea surface anomalies caused by large scale oceanographic anomalies (such as El Nino and La Nina) occurring at specific times. The emergence of satellite altimetry technology has changed the way that we understand and observe the Earth, especially the oceans. Substantial improvements in the spatial and temporal resolution of altimetry data have ushered global ocean system research into a new era. Satellite altimetry was initially used for telemetry
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