Validation of recent altimeter missions at non-dedicated tide gauge stations in the Southeastern North Sea

<p>The absolute and relative accuracy of sea surface heights derived from six altimeter missions (Jason-1/2/3, Envisat, Saral, Sentinel-3A) is evaluated at five GNSS-controlled tide gauge stations in the German Bight (SE North Sea). The precision of the total water level envelope (TWLE) is assessed for the period 2000 to 2019 based on RMS errors and explained variances. The comparison is based on TWLE instead of dealiased sea level data since the tidal and barotropic dynamic is not known with sufficient accuracy in this area. The tide gauges are partly located at the open sea, partly at the coast close to mudflats. The tide gauge data is available every minute, the 20 Hz level 2 altimetry data is interpolated to virtual stations at distances between 2 and 15 km to the tide gauges. The altimeter data is based on standard retrackers, the correction models are adjusted to coastal applications and exclude the corrections for ocean tides and dynamic atmosphere to allow a direct comparison to the tide gauge data. To account for slight differences of the tidal dynamics between gauge and altimetry an optimal time shift and scale between each pair of locations is estimated and applied. This tidal correction improves the RMS errors by 15-75%. The explained variances are excellent at all stations (> 96%). The resultant RMS errors are mainly between 2-5 cm depending on location and mission. The RMS errors rise up to 10 cm where coastal dynamics play a dominant role or the altimeter approaches the land very closely (<7 km). The accuracy of the absolute biases is strongly dependent on the knowledge of the mean sea surface heights in the region.</p>

Past, Present and Future Sea Levels in Singapore

<p>Singapore is a small (728 km<sup>2</sup>) island nation that is vulnerable to rising sea levels with 30% of its land surface area less than 5 m above present sea level. Rising relative sea level (RSL), however, is not uniform with regional RSL changes differing from the global mean due to processes associated with vertical land motion (e.g., glacial-isostatic adjustment) and atmospheric and ocean dynamics. Understanding magnitudes, rates, and driving processes on past and present-day sea level are therefore important to provide greater confidence in accurately quantifying future sea-level rise projections and their uncertainty. Here, we present a synopsis of Singapore’s past and present RSL history using newly developed proxy RSL reconstructions from mangrove peats, coral microatolls and tide gauge data and conclude with probabilistic projections of future RSL change.</p><p>Past RSL is characterized by rapid rise during the early Holocene driven primarily by deglaciation of northern hemisphere ice sheets. Sea-level index points (SLIPs) from mangrove peats show sea levels rose rapidly from -20.7 m at 9.5 ka BP to -0.6 m at 7 ka BP at rates of 6-12 mm/yr. This is substantially greater than predicted magnitudes of RSL change from the ICE-6G_C GIA model which shows RSL increasing from -6.4 m at 9.5 ka BP to a ~2.8 m highstand at ~7 ka BP. SLIPs show the mid-Holocene highstand of ~4 ± 3.6 m at 5.2 ka BP before falling towards present at rates up to -2 mm/yr driven by hydro-isostatic processes. The nature of RSL changes during the mid- to late-Holocene transition remains poorly resolved with evidence of sea levels falling below present level to -2.2 ± 2.0 m at 1.2 ka BP. Present RSL reconstructions from coral microatolls coupled with tide-gauge data extend the limited instrumental period in this region beyond ~50 years. They show RSL rose ~0.03 m from 1915 to 1990 at 0.7 ± 1.4 mm/yr before increasing to 1.5 ± 2.1 mm/yr after 1990 to 2019. Future RSL change from probabilistic projections to 2100 under low (RCP 2.6) and high (RCP 8.5) emission scenarios show sea levels rising 0.43 m (50<sup>th</sup> percentile) (0.06 – 0.96 m; 95% credible interval) and 0.74 m (0.28 – 1.4 m), respectively. However, projected magnitudes of sea-level rise driven by rapid ice sheet dynamics and the unknown contribution of atmospheric and ocean dynamics in Southeast Asia have the potential to exacerbate projection magnitudes.</p>

Sea Level Fusion of Satellite Altimetry and Tide Gauge Data by Deep Learning in the Mediterranean Sea

Satellite altimetry and tide gauges are the two main techniques used to measure sea level. Due to the limitations of satellite altimetry, a high-quality unified sea level model from coast to open ocean has traditionally been difficult to achieve. This study proposes a fusion approach of altimetry and tide gauge data based on a deep belief network (DBN) method. Taking the Mediterranean Sea as the case study area, a progressive three-step experiment was designed to compare the fused sea level anomalies from the DBN method with those from the inverse distance weighted (IDW) method, the kriging (KRG) method and the curvature continuous splines in tension (CCS) method for different cases. The results show that the fusion precision varies with the methods and the input measurements. The precision of the DBN method is better than that of the other three methods in most schemes and is reduced by approximately 20% when the limited altimetry along-track data and in-situ tide gauge data are used. In addition, the distribution of satellite altimetry data and tide gauge data has a large effect on the other three methods but less impact on the DBN model. Furthermore, the sea level anomalies in the Mediterranean Sea with a spatial resolution of 0.25° × 0.25° generated by the DBN model contain more spatial distribution information than others, which means the DBN can be applied as a more feasible and robust way to fuse these two kinds of sea levels.

Tide gauge data archaeology provides natural subsidence rates along the coasts of the Po Plain and of the Veneto-Friuli Plain, Italy

Summary In Northern Italy, natural subsidence affects the Po and Veneto-Friuli Plains. Anthropogenic activities which started during the 1930s enhanced the natural rates considerably. Information on land lowering can be obtained not only by geodetic or geological data, but also analyzing and comparing sea-level time series of neighboring tide gauges. In the Northern Adriatic, several tide gauge stations were operational before the onset of the anthropogenic activities. We analyzed data spanning the period 1873–1922 from Marina di Ravenna, Venice and Trieste, in Italy. The 1897–1922 data of Pula, Croatia, were also considered for the analysis, but this time series was finally discarded because too short. Trieste, located in a relatively stable area, is characterized by a sea-level rate of 1.21 ± 0.35 mm/yr (1875–1922) that can be assumed to be a reliable estimate of the local sea-level rise during the period of interest. We compared the rate observed at Trieste with those obtained at Marina di Ravenna, 3.09 ± 0.31 mm/yr (1873–1922), and Venice, 2.05 ± 0.22 mm/yr (1873–1922). This comparison shows that the natural subsidence rate decreases from Marina di Ravenna to Venice and Trieste, turning out to be 1.88 ± 0.47 mm/yr and 0.84 ± 0.41 mm/yr at Marina di Ravenna and Venice, respectively.