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At each of five fixed locations along the ground tracks of JASON-1 and ENVISAT, a repeat-track analysis of 1-Hz sea surface height (SSH) data has been conducted to assess the performance of waveform retrackers over Lake Baikal in Siberia, Russia. This simple analysis of time series at each point location is needed to minimize the effect of the range correction artifacts in current Geophysical Data Record (GDR) data products of radar altimeters in in-land areas. Using the retracked data available in the GDRs as the baseline, two retrackers are evaluated in terms of the number of valid data points produced and the degree of agreement with in-situ data of water level record. The threshold retrackers that are based on the amplitude of the robust OCOG algorithm (Offset Center of Gravity) are found to perform the best in Lake Baikal.

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While the barotropic ocean tides in the deep ocean are well modeled to ~2 cm RMS, accurate tidal prediction in the icecovered polar oceans and near coastal regions remain elusive. A notable reason is that the most accurate satellite altimeters (TOPEX/Jason-1/-2), whose orbits are optimized to minimize the tidal aliasing effect, have spatial coverage limited to largely outside of the polar ocean. Here, we update the assessment of tidal models using 7 contemporary global and regional models, and show that the altimetry sea surface height (SSH) anomaly residual after tidal correction is 9 -12 cm RMS in the Subarctic Ocean. We then address the hypothesis whether plausible evidence of variable tidal signals exist in the seasonally ice-covered Subarctic Ocean, where the sea ice cover is undergoing rapid thinning. We first found a difference in variance reduction for multi-mission altimeter SSH anomaly residuals during the summer and winter seasons, with the residual during winter season 15 -30% larger than that during the summer season. Experimental seasonal ocean tide solutions derived from satellite altimetry reveals that the recovered winter and summer tidal constituents generally differ by a few cm in amplitude and tens of degrees in phase. Relatively larger seasonal tidal patterns, in particular for M 2 , S 2 and K 1 tides, have been identified in the Chukchi Sea study region near eastern Siberia, coincident with the seasonal presence and movement of sea ice.

In this study, a consider covariance analysis of error sources limiting the accuracy of the Earth rotation parameters (ERP), which include the polar motion coordinates x and y and the length of the day (LOD), determined from satellite laser ranging (SLR) data to near‐Earth geodetic satellites, has been performed. The solution for the ERP has been obtained from the analysis of the SLR data to Starlette collected primarily during the 14‐month MERIT Campaign that began September 1, 1983. A preliminary Starlette ERP solution based on a Starlette‐tailored Earth gravity model, PGS 1331, was compared with the solutions derived from SLR to LAGEOS, and the weighted rms about the mean of the difference between these solutions was 13 milliarcseconds (mas), 11 mas, and 0.6 milliseconds (ms) for Δx, Δy, and ΔLOD, respectively. A covariance analysis indicated that the accuracy of the Starlette ERP solution was limited primarily by errors in the Earth's gravity field model. In particular, this analysis showed that the first‐order geopotential coefficients produced a systematic perturbation in the solutions for x and y with a maximum value up to 29 mas and a dominant period of 74 days. The LOD determination by Starlette is limited primarily by errors in the Earth's zonal harmonics and long‐period tides. With the improvement of the Starlette force model by simultaneous estimation of selected geopotential coefficients and ocean tide parameters, the weighted rms of the Starlette solution with respect to LAGEOS was reduced to 9 mas and 6 mas for Δx and Δy, respectively. However, this technique was not able to improve the accuracy of the LOD solution. Using an improved gravity field recently developed at the University of Texas Center for Space Research, the weighted rms differences between Starlette and LAGEOS ERP solutions have been further reduced to 4.4 mas and 3.6 mas for Δx and Δy, respectively. These results show that a significant improvement of the ERP solution from Starlette can be achieved through further refinements in the Earth's gravity field and tide model and that a precision of <5 mas in x and y coordinates of the pole is feasible from Starlette.

Abstract. Ice velocity constitutes a key parameter for estimating ice-sheet discharge rates and is crucial for improving coupled models of the Antarctic ice sheet to accurately predict its future fate and contribution to sea-level change. Here, we present a new Antarctic ice velocity map at a 100-m grid spacing inferred from Landsat 8 imagery data collected from December 2013 through March 2016 and robustly processed using the feature tracking method. These maps were assembled from over 73,000 displacement vector scenes inferred from over 32,800 optical images. Our maps cover nearly all the ice shelves, landfast ice, ice streams, and most of the ice sheet. The maps have an estimated uncertainty of less than 10 m yr-1 based on robust internal and external validations. These datasets will allow for a comprehensive continent-wide investigation of ice dynamics and mass balance combined with the existing and future ice velocity measurements and provide researchers access to better information for monitoring local changes in ice glaciers. Other uses of these datasets include control and calibration of ice-sheet modelling, developments in our understanding of Antarctic ice-sheet evolution, and improvements in the fidelity of projects investigating sea-level rise (https://doi.pangaea.de/10.1594/PANGAEA.895738).