Sea-level variability and change along the Norwegian coast between 2003 and 2018 from satellite altimetry, tide gauges and hydrography

Sea-level variations in coastal areas can differ significantly from those in the nearby open ocean. Monitoring coastal sea-level variations is therefore crucial to understand how climate variability can affect the densely populated coastal regions of the globe. In this paper, we study the sea-level variability along the coast of Norway by means of in situ records, satellite altimetry data, and a network of eight hydrographic stations over a period spanning 16 years (from 2003 to 2018). At first, we evaluate the performance of the ALES-reprocessed coastal altimetry dataset by comparing it with the sea-level anomaly from tide gauges over a range of timescales, which include the long-term trend, the annual cycle and the detrended and deseasoned sea level anomaly. We find that coastal altimetry outperforms conventional altimetry products at most locations along the Norwegian coast. We later take advantage of the coastal altimetry dataset to perform a sea level budget along the Norwegian coast. We find that the thermosteric and the halosteric signals give a comparable contribution to the sea-level trend along the Norwegian coast, except for three, non-adjacent hydrographic stations, where salinity variations affect the sea-level trend more than temperature variations. We also find that the sea-level annual cycle is more affected by variations in temperature than in salinity, and that both temperature and salinity give a comparable contribution to the detrended and deseasoned sea-level along the entire Norwegian coast.

Sea Level Trend and Fronts in the South Atlantic Ocean

The understanding of the physical drivers of sea level trend is crucial on global and regional scales. In particular, little is known about the sea level trend in the South Atlantic Ocean in comparison with other parts of the world. In this work, we computed the South Atlantic mean sea level (SAMSL) trend from 25 years of satellite altimetry data, and we analyzed the contributions of steric height (thermosteric and halosteric components) and ocean mass changes for the period 2005–2016 when all the source data used (Argo, GRACE and satellite altimetry) overlap. The SAMSL trend is 2.65 ± 0.24 mm/yr and is mostly explained by ocean mass trend, which is 2.22 ± 0.21 mm/yr. However, between 50° S–33° S, the steric height component constitutes the main contribution in comparison with the ocean mass component. Within that latitudinal band, three regions with trend values higher than the SAMSL trend are observed when considering 25 years of satellite SLA. In the three regions, a southward displacement of the Subtropical, Subantarctic, and Polar Fronts is observed. The southward shift of the fronts is associated with the strengthening and polar shift of westerly winds and contributes to a clear thermosteric trend that translates to the SLA trend observed in those regions.

Steric Sea Level Changes from Ocean Reanalyses at Global and Regional Scales

Sea level has risen significantly in the recent decades and is expected to rise further based on recent climate projections. Ocean reanalyses that synthetize information from observing networks, dynamical ocean general circulation models, and atmospheric forcing data offer an attractive way to evaluate sea level trend and variability and partition the causes of such sea level changes at both global and regional scales. Here, we review recent utilization of reanalyses for steric sea level trend investigations. State-of-the-science ocean reanalysis products are then used to further infer steric sea level changes. In particular, we used an ensemble of centennial reanalyses at moderate spatial resolution (between 0.5 × 0.5 and 1 × 1 degree) and an ensemble of eddy-permitting reanalyses to quantify the trends and their uncertainty over the last century and the last two decades, respectively. All the datasets showed good performance in reproducing sea level changes. Centennial reanalyses reveal a 1900–2010 trend of steric sea level equal to 0.47 ± 0.04 mm year−1, in agreement with previous studies, with unprecedented rise since the mid-1990s. During the altimetry era, the latest vintage of reanalyses is shown to outperform the previous ones in terms of skill scores against the independent satellite data. They consistently reproduce global and regional upper ocean steric expansion and the association with climate variability, such as ENSO. However, the mass contribution to the global mean sea level rise is varying with products and its representability needs to be improved, as well as the contribution of deep and abyssal waters to the steric sea level rise. Similarly, high-resolution regional reanalyses for the European seas provide valuable information on sea level trends, their patterns, and their causes.

SEA LEVEL TREND AND VARIABILITY IN THE SOUTH CHINA SEA

<p><strong>Abstract.</strong> Sea level rise due to climate change is nonuniform globally, necessitating regional estimates. Spatial-temporal behaviour of sea level anomalies (SLAs) in the South China Sea (SCS) was investigated over 24 years period from 1993 to 2016. Based on the spatial distribution of monthly and seasonal mean SLAs in the SCS, the strong regularity of SLAs performed maybe mainly predominantly driven by monsoonal wind. Variations of SLA were different in each month, which was the largest in July and December, and the smallest in April. Positive sea level linear trends were estimated in most cases. The averaged sea level trend in the SCS showed a rise of 4.42&amp;thinsp;&amp;plusmn;&amp;thinsp;0.25&amp;thinsp;mm/year from 1993 to 2016. Further investigations are expected from muliti-resources such as ENSO, wind stress, and vertical land movement data.</p>

Sea State Bias Variability in Satellite Altimetry Data

Sea State Bias (SSB) contributes to global mean sea level variability and it needs cm-level range adjustment due to the instrumental drift over time. To investigate its variations and correct the global and regional sea level trend precisely, we calculate the temporal and spatial variability of the SSB correction in TOPEX, Jason-1, Jason-2 and Jason-3 missions, separately, as well as in the combined missions over the period 1993–2017. The long-term trend in global mean operational 2D non-parametric SSB correction is about −0.03 ± 0.03 mm/yr, which accounts for 1% of current global mean sea level change rate during 1993–2016. This correction contributes to sea level change rates of −1.27 ± 0.21 mm/yr and −0.26 ± 0.13 mm/yr in TOPEX-A and Jason-2 missions, respectively. The global mean SSB varies up to 7–10 mm during the very strong ENSO events in 1997–1998 and 2015–2016. Furthermore, the TOPEX SSB trend, which is consistent with recently reported sea level trend drift during 1993–1998, may leak into the determined global sea level trend in the period. Moreover, the Jason-1/2 zonal SSB variability is highly correlated with the significant wave height (SWH). On zonal average, SSB correction causes about 1% uncertainty in mean sea level trend. At high SWH regions, the uncertainties grow to 2–4% near the 50°N and 60°S bands. This should be considered in the study of regional sea level variability.