Arctic Sea Level Budget Assessment during the GRACE/Argo Time Period

Sea level change is an important indicator of climate change. Our study focuses on the sea level budget assessment of the Arctic Ocean using: (1) the newly reprocessed satellite altimeter data with major changes in the processing techniques; (2) ocean mass change data derived from GRACE satellite gravimetry; (3) and steric height estimated from gridded hydrographic data for the GRACE/Argo time period (2003–2016). The Beaufort Gyre (BG) and the Nordic Seas (NS) regions exhibit the largest positive trend in sea level during the study period. Halosteric sea level change is found to dominate the area averaged sea level trend of BG, while the trend in NS is found to be influenced by halosteric and ocean mass change effects. Temporal variability of sea level in these two regions reveals a significant shift in the trend pattern centered around 2009–2011. Analysis suggests that this shift can be explained by a change in large-scale atmospheric circulation patterns over the Arctic. The sea level budget assessment of the Arctic found a residual trend of more than 1.0 mm/yr. This nonclosure of the sea level budget is further attributed to the limitations of the three above mentioned datasets in the Arctic region.

High-Efficiency Determination of Coastline by Combination of Tidal Level and Coastal Zone DEM from UAV Tilt Photogrammetry

To meet the needs of coastline efficient extraction and dynamic monitoring, this paper proposes a new method for coastline extraction by combining the tidal level and the digital elevation model (DEM) of the coastal zone from tilt photography. Firstly, the DEM of coastal zone was obtained by using unmanned aerial vehicle (UAV) tilt photography; at the same time, the accuracy of aerial triangulation(AT) is improved referencing to the constraint of water boundary points, and then the mean high water spring tide was obtained by combining tidal harmonic analysis and Global Navigation Satellite System (GNSS) tidal level. Finally, the coastline and the dynamic water-surface line are extracted from the DEM of the coastal zone by tracking the contour lines with the elevation of the mean high water springs (MHWS) and the instantaneous sea-surface elevation, respectively. The experiments carried out in the coastal zones of Liaoning Province, China, proved the proposed method and achieved better than 0.2 m of horizontal position accuracy and 0.1 m of the vertical accuracy.

Improving the Positioning Accuracy of Satellite-Borne GNSS-R Specular Reflection Point on Sea Surface Based on the Ocean Tidal Correction Positioning Method

The positioning error of the specular reflection point is the main error source of Global Navigation Satellite System Reflectometry (GNSS-R) satellite sea surface altimetry. The existing specular reflection point geometric positioning methods do not consider the static-state elevation difference of tens of meters and the decimeter-level time-varying elevation difference between the reflection reference surface and the instantaneous sea surface. The resulting positioning error restricts the GNSS-R satellite sea surface altimetry from reaching cm-level high accuracy on the reference datum. Under the premise of the basic static-state elevation positioning error correction, reducing the time-varying elevation positioning error is the key to improving positioning accuracy. In this study, based on the principle of elevation correction of GNSS-R reflection reference surface, the main parameter that determines the real-time variation of sea surface height, ocean tide, is used to correct the specular reflection point from geoid to ocean tidal surface. The positioning error caused by the time-varying elevation error of the reflection reference surface is reduced, the positioning accuracy is improved, and the improvement is quantified. According to the research results, the ocean tidal correction positioning (OTCP) method improves the positioning accuracy by 0.31 m. The positioning accuracy improvement has a good correlation with the corresponding tidal height modulo, and the improvement is 1.07 times of the tidal height modulo. In the offshore, the tidal height gradient modulo is greater than the deep sea, the gradient of the tidal positioning correction has a good response to the tidal height gradient modulo, while the sensitivity of this response decreases in the deep sea.

Assessment of the Accuracy of Recent Empirical and Assimilated Tidal Models for the Great Barrier Reef, Australia, Using Satellite and Coastal Data

The latest satellite and in situ data are a fundamental source for tidal model evaluations. In this work, the satellite missions TOPEX/Poseidon, Jason-1, Jason-2 and Sentinel-3A, together with tide gauge data, were used to investigate the performance of recent regional and global tidal models over the Great Barrier Reef, Australia. Ten models, namely, TPXO8, TPXO9, EOT11a, HAMTIDE, FES2012, FES2014, OSUNA, OSU12, GOT 4.10 and DTU10, were considered. The accuracy of eight major tidal constituents (i.e., K1, O1, P1, Q1, M2, S2, N2 and K2) and one shallow water constituent (M4) were assessed based on the analysis of sea-level observations from coastal tide gauges and altimetry data (TOPEX series). The outcome was compared for four different subregions, namely, the coastline, coastal, shelf and deep ocean zones. Sea-level anomaly data from the Sentinel-3A mission were corrected using the tidal heights predicted by each model. The root mean square values of the sea level anomalies were then compared. According to the results, FES2012 compares more favorably to other models with root mean square (RMS) values of 10.9 cm and 7.7 cm over the coastal and shelf zones, respectively. In the deeper sections, the FES2014 model compares favorably at 7.5 cm. In addition, the impact of sudden fluctuations in bottom topography on model performances suggest that a combination of bathymetric variations and proximity to the coast or islands contributes to tidal height prediction accuracies of the models.

Aliased Tidal Variability in Mesoscale Sea Level Anomaly Maps

Sea level anomaly (SLA) maps are routinely produced by objective analysis of data from the constellation of satellite altimeter missions in operation since 1992. Beginning in 2014, changes in the Data Unification and Altimeter Combination System (DUACS) used to create the SLA maps resulted in improved spatial resolution of mesoscale variability, but it also increased the levels of aliased tidal variability compared to the methodology employed prior to 2014. The present work investigates the magnitude and spatial distribution of these tidal signals, which are typically smaller than 1 cm in the open ocean but can reach tens of centimeters in the coastal ocean. In the open ocean, the signals are caused by a combination of phase-locked and phase-variable baroclinic tides. In the coastal ocean, the signals are a combination of aliased high-frequency nontidal variability and aliased variability caused by erroneous tidal corrections applied to the along-track altimetry prior to objective analysis. Several low-pass and bandpass filters are implemented to reduce the tidal signals in the mapped SLA, and independent tide gauge data are used to provide an objective assessment of the performance of the filters. The filter that attenuates both the small-scale (less than 200 km) and the high-frequency (period shorter than 108 days) components of SLA removes aliased baroclinic tidal variability and improves the accuracy of tidal analysis in the open ocean while also performing acceptably in the coastal ocean.