Sea level variability and trends in the Adriatic Sea in 1993–2008 from tide gauges and satellite altimetry

2012 ◽  
Vol 40-41 ◽  
pp. 47-58 ◽  
Author(s):  
Luciana Fenoglio-Marc ◽  
Carla Braitenberg ◽  
Lavinia Tunini
Keyword(s):  
Sea Level ◽  
Satellite Altimetry ◽  
Adriatic Sea ◽  
Tide Gauges ◽  
Sea Level Variability

Validation of the ALES Coastal Altimetry Dataset against the Norwegian Tide Gauges

2021 ◽  
Author(s):  
Fabio Mangini ◽  
Antonio Bonaduce ◽  
Léon Chafik ◽  
Laurent Bertino
Keyword(s):  
Sea Level ◽  
Satellite Altimetry ◽  
Tide Gauge ◽  
Linear Trend ◽  
Tide Gauges ◽  
Sea Level Variability ◽  
Preliminary Results ◽  
In Situ Data ◽  
Coastal Sea

<p>Satellite altimetry measurements, complemented by in-situ records, have made a fundamental contribution to the understanding of global sea level variability for almost 30 years. Due to land contamination, it performs best over the open ocean. However, over the years, there has been a significant effort to improve the altimetry products in coastal regions. Indeed, altimetry observations could be fruitfully used in the coastal zone to complement the existing tide gauge network which, despite its relevance, does not represent the entire coast. Given the important role of coastal altimetry in oceanography, we have recently decided to check the quality of a new coastal altimetry dataset, ALES, along the coast of Norway. The Norwegian coast is well covered by tide gauges and, therefore, particularly suitable to validate a coastal altimetry dataset. Preliminary results show a good agreement between in-situ and remote sensing sea-level signals in terms of linear trend, seasonal cycle and inter-annual variability. For example, the linear correlation coefficient between the inter-annual sea level variability from altimetry and tide gauges exceeds 0.8. Likewise, the root mean square difference between the two is less than 2 cm at most tide gauge locations. A comparison with Breili et al. (2017) shows that ALES performs better than the standard satellite altimetry products at estimating sea level trends along the coast of Norway. Notably, in the Lofoten region, the difference between the sea level trends computed using ALES and the tide gauges range between 0.0 to 0.7 mm/year, compared to circa 1 to 3 mm/year found by Breili et al. (2017). These preliminary results go in the direction of obtaining an accurate characterization of coastal sea-level at the high latitudes based on coastal altimetry records, which can represent a valuable source of information to reconstruct coastal sea-level signals in areas where in-situ data are missing or inaccurate.</p>

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

2021 ◽  
Author(s):  
Fabio Mangini ◽  
Léon Chafik ◽  
Antonio Bonaduce ◽  
Laurent Bertino ◽  
Jan Even Øie Nilsen
Keyword(s):  
Sea Level ◽  
Annual Cycle ◽  
Satellite Altimetry ◽  
Tide Gauges ◽  
Sea Level Anomaly ◽  
Sea Level Variability ◽  
Norwegian Coast ◽  
Coastal Sea ◽  
Sea Level Variations ◽  
Sea Level Trend

Abstract. 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.

scholarly journals Sea level variability in the Arctic Ocean observed by satellite altimetry

2012 ◽  
Vol 9 (4) ◽  
pp. 2375-2401 ◽  
Author(s):  
P. Prandi ◽  
M. Ablain ◽  
A. Cazenave ◽  
N. Picot
Keyword(s):  
Arctic Ocean ◽  
Sea Level ◽  
Satellite Altimetry ◽  
The Arctic ◽  
Altimetry Data ◽  
Tide Gauges ◽  
Sea Level Variability ◽  
Ocean Mass ◽  
The Arctic Ocean ◽  
Satellite Altimetry Data

Abstract. We investigate sea level variability in the Arctic Ocean from observations. Variability estimates are derived both at the basin scale and on smaller local spatial scales. The periods of the signals studied vary from high frequency (intra-annual) to long term trends. We also investigate the mechanisms responsible for the observed variability. Different data types are used, the main one being a recent reprocessing of satellite altimetry data in the Arctic Ocean. Satellite altimetry data is compared to tide gauges measurements, steric sea level derived from temperature and salinity fields and GRACE ocean mass estimates. We establish a consistent regional sea level budget over the GRACE availability era (2003–2009) showing that the sea level drop observed by altimetry over this period is driven by ocean mass loss rather than steric effects. The comparison of altimetry and tide gauges time series show that the two techniques are in good agreement regarding sea level trends. Coastal areas of high variability in the altimetry record are also consistent with tide gauges records. An EOF analysis of September mean altimetry fields allows identifying two regions of wind driven variability in the Arctic Ocean: the Beaufort Gyre region and the coastal European and Russian Arctic. Such patterns are related to atmospheric regimes through the Arctic Oscillation and Dipole Anomaly.

scholarly journals Studying Sea Level Variability in Indonesia Sea Based on Satellite Altimetry

2020 ◽  
Vol 618 ◽  
pp. 012040
Author(s):  
Dina A Sarsito ◽  
Muhammad Syahrullah ◽  
Dudy D Wijaya ◽  
Dhota Pradipta ◽  
Heri Andreas
Keyword(s):  
Sea Level ◽  
Satellite Altimetry ◽  
Sea Level Variability

Impact of Satellite Altimetry on Simulations of Sea Level Variability by an Indian Ocean Model

2001 ◽  
Vol 24 (1) ◽  
pp. 53-63 ◽  
Author(s):  
S. K. Singh ◽  
Sujit Basu ◽  
Raj Kumar ◽  
Vijay K. Agarwal
Keyword(s):  
Indian Ocean ◽  
Sea Level ◽  
Satellite Altimetry ◽  
Ocean Model ◽  
Sea Level Variability

scholarly journals Sea level trend and variability around Peninsular Malaysia

Ocean Science ◽  
2015 ◽  
Vol 11 (4) ◽  
pp. 617-628 ◽  
Author(s):  
Q. H. Luu ◽  
P. Tkalich ◽  
T. W. Tay
Keyword(s):  
Sea Level Rise ◽  
Sea Level ◽  
Satellite Altimetry ◽  
Tide Gauge ◽  
Peninsular Malaysia ◽  
Tide Gauges ◽  
Tide Gauge Records ◽  
Regional Sea Level ◽  
Malacca Strait ◽  
Singapore Strait

Abstract. Sea level rise due to climate change is non-uniform globally, necessitating regional estimates. Peninsular Malaysia is located in the middle of Southeast Asia, bounded from the west by the Malacca Strait, from the east by the South China Sea (SCS), and from the south by the Singapore Strait. The sea level along the peninsula may be influenced by various regional phenomena native to the adjacent parts of the Indian and Pacific oceans. To examine the variability and trend of sea level around the peninsula, tide gauge records and satellite altimetry are analyzed taking into account vertical land movements (VLMs). At annual scale, sea level anomalies (SLAs) around Peninsular Malaysia on the order of 5–25 cm are mainly monsoon driven. Sea levels at eastern and western coasts respond differently to the Asian monsoon: two peaks per year in the Malacca Strait due to South Asian–Indian monsoon; an annual cycle in the remaining region mostly due to the East Asian–western Pacific monsoon. At interannual scale, regional sea level variability in the range of ±6 cm is correlated with El Niño–Southern Oscillation (ENSO). SLAs in the Malacca Strait side are further correlated with the Indian Ocean Dipole (IOD) in the range of ±5 cm. Interannual regional sea level falls are associated with El Niño events and positive phases of IOD, whilst rises are correlated with La Niña episodes and negative values of the IOD index. At seasonal to interannual scales, we observe the separation of the sea level patterns in the Singapore Strait, between the Raffles Lighthouse and Tanjong Pagar tide stations, likely caused by a dynamic constriction in the narrowest part. During the observation period 1986–2013, average relative rates of sea level rise derived from tide gauges in Malacca Strait and along the east coast of the peninsula are 3.6±1.6 and 3.7±1.1 mm yr−1, respectively. Correcting for respective VLMs (0.8±2.6 and 0.9±2.2 mm yr−1), their corresponding geocentric sea level rise rates are estimated at 4.4±3.1 and 4.6±2.5 mm yr−1. The geocentric rates are about 25 % faster than those measured at tide gauges around the peninsula; however, the level of uncertainty associated with VLM data is relatively high. For the common period between 1993 and 2009, geocentric sea level rise values along the Malaysian coast are similar from tide gauge records and satellite altimetry (3.1 and 2.7 mm yr−1, respectively), and arguably correspond to the global trend.

scholarly journals Non-tidal aliasing in seasonal sea-level variability and annual Rossby waves as observed by satellite altimetry

1997 ◽  
Vol 15 (11) ◽  
pp. 1478-1488 ◽  
Author(s):  
G. Chen ◽  
R. Ezraty
Keyword(s):  
Numerical Simulations ◽  
Systematic Error ◽  
Sea Level ◽  
Satellite Altimetry ◽  
Rossby Waves ◽  
Altimeter Data ◽  
Ocean Tides ◽  
Satellite Altimeter ◽  
Sea Level Variability ◽  
Satellite Altimeter Data

Abstract. It is becoming well known that aliasing associated with ocean tides could be a major source of systematic error in altimeter sea-level measurements, due to asynoptic sampling and imperfect tide modelling. However, it has been shown that signals of non-tidal origin may also contribute significantly to the observed aliasing. In this paper, numerical simulations are performed to demonstrate the full aliasing potential associated with altimeter observations of seasonal sea-level variability and annual Rossby waves. Our results indicate that ignorance of non-tidal aliasing may lead to the possibility of underestimating the total aliasing and misinterpreting or overlooking existing geophysical phenomena. Therefore, it is argued that an entire aliasing picture should be kept in mind when satellite altimeter data are analysed.

scholarly journals The zone of influence: matching sea level variability from coastal altimetry and tide gauges for vertical land motion estimation

Ocean Science ◽  
2021 ◽  
Vol 17 (1) ◽  
pp. 35-57
Author(s):  
Julius Oelsmann ◽  
Marcello Passaro ◽  
Denise Dettmering ◽  
Christian Schwatke ◽  
Laura Sánchez ◽  
...  
Keyword(s):  
Sea Level ◽  
Spatial Scales ◽  
Tide Gauges ◽  
Sea Level Changes ◽  
Relative Sea Level ◽  
Sea Level Variability ◽  
Vertical Land Motion ◽  
Spatial Coverage ◽  
Coupling Procedure ◽  
Zone Of Influence

Abstract. Vertical land motion (VLM) at the coast is a substantial contributor to relative sea level change. In this work, we present a refined method for its determination, which is based on the combination of absolute satellite altimetry (SAT) sea level measurements and relative sea level changes recorded by tide gauges (TGs). These measurements complement VLM estimates from the GNSS (Global Navigation Satellite System) by increasing their spatial coverage. Trend estimates from the SAT and TG combination are particularly sensitive to the quality and resolution of applied altimetry data as well as to the coupling procedure of altimetry and TGs. Hence, a multi-mission, dedicated coastal along-track altimetry dataset is coupled with high-frequency TG measurements at 58 stations. To improve the coupling procedure, a so-called “zone of influence” (ZOI) is defined, which confines coherent zones of sea level variability on the basis of relative levels of comparability between TG and altimetry observations. Selecting 20 % of the most representative absolute sea level observations in a 300 km radius around the TGs results in the best VLM estimates in terms of accuracy and uncertainty. At this threshold, VLMSAT-TG estimates have median formal uncertainties of 0.58 mm yr−1. Validation against GNSS VLM estimates yields a root mean square (rmsΔVLM) of VLMSAT-TG and VLMGNSS differences of 1.28 mm yr−1, demonstrating the level of accuracy of our approach. Compared to a reference 250 km radius selection, the 300 km zone of influence improves trend accuracies by 15 % and uncertainties by 35 %. With increasing record lengths, the spatial scales of the coherency in coastal sea level trends increase. Therefore, the relevance of the ZOI for improving VLMSAT-TG accuracy decreases. Further individual zone of influence adaptations offer the prospect of bringing the accuracy of the estimates below 1 mm yr−1.

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