scholarly journals Detection and Characterization of Meteotsunamis in the Gulf of Genoa

2019 ◽  
Vol 7 (8) ◽  
pp. 275 ◽  
Author(s):  
Picco ◽  
Schiano ◽  
Incardone ◽  
Repetti ◽  
Demarte ◽  
...  
Keyword(s):  
Sea Level ◽  
Atmospheric Pressure ◽  
Tidal Elevation ◽  
Port Management ◽  
Time Frequency ◽  
Abrupt Jump ◽  
Level Data ◽  
Work Planning

A long-term time series of high-frequency sampled sea-level data collected in the port of Genoa were analyzed to detect the occurrence of meteotsunami events and to characterize them. Time-frequency analysis showed well-developed energy peaks on a 26–30 minute band, which are an almost permanent feature in the analyzed signal. The amplitude of these waves is generally few centimeters but, in some cases, they can reach values comparable or even greater than the local tidal elevation. In the perspective of sea-level rise, their assessment can be relevant for sound coastal work planning and port management. Events having the highest energy were selected for detailed analysis and the main features were identified and characterized by means of wavelet transform. The most important one occurred on 14 October 2016, when the oscillations, generated by an abrupt jump in the atmospheric pressure, achieved a maximum wave height of 50 cm and lasted for about three hours.

scholarly journals Changing storminess? An analysis of long-term sea level data sets

1999 ◽  
Vol 11 ◽  
pp. 161-172 ◽  
Author(s):  
W Bijl ◽  
R Flather ◽  
JG de Ronde ◽  
T Schmith
Keyword(s):  
Sea Level ◽  
Data Sets ◽  
Level Data

Sea level in the Global Geodetic Observing System

2020 ◽  
Author(s):  
Elizabeth Bradshaw ◽  
Andy Matthews ◽  
Kathy Gordon ◽  
Angela Hibbert ◽  
Sveta Jevrejeva ◽  
...  
Keyword(s):  
Sea Level ◽  
Working Group ◽  
Sea Level Change ◽  
Tide Gauges ◽  
Controlled Vocabularies ◽  
Mean Sea Level ◽  
Level Change ◽  
Level Data ◽  
Metadata Standards

<p>The Permanent Service for Mean Sea Level (PSMSL) is the global databank for long-term mean sea level data and is a member of the Global Geodetic Observing System (GGOS) Bureau of Networks and Observations. As well as curating long-term sea level change information from tide gauges, PSMSL is also involved in developing other products and services including the automatic quality control of near real-time sea level data, distributing Global Navigation Satellite System (GNSS) sea level data and advising on sea level metadata development.<br>At the GGOS Days meeting in November 2019, the GGOS Focus Area 3 on Sea Level Change, Variability and Forecasting was wrapped up, but there is still a requirement in 2020 for GGOS to integrate and support tide gauges and we will discuss how we will interact in the future. A recent paper (Ponte et al., 2019) identified that only “29% of the GLOSS [Global Sea Level Observing System] GNSS-co-located tide gauges have a geodetic tie available at SONEL [Système d'Observation du Niveau des Eaux Littorales]” and we as a community still need to improve the ties between the GNSS sensor and tide gauges. This may progress as new GNSS Interferometric Reflectometry (GNSS-IR) sensors are installed to provide an alternative method to observe sea level. As well as recording the sea level, these sensors will also provide vertical land movement information from one location. PSMSL are currently developing an online portal of uplift/subsidence land data and GNSS-IR sea level observation data. To distribute the data, we are creating/populating controlled vocabularies and generating discovery metadata.<br>We are working towards FAIR data management principles (data are findable, accessible, interoperable and reusable) which will improve the flow of quality controlled sea level data and in 2020 we will issue the PSMSL dataset with a Digital Object Identifier. We have been working on improving our discovery and descriptive metadata including creating a use case for the Research Data Alliance Persistent (RDA) Identification of Instruments Working Group to help improve the description of a time series where the sensor and platform may change and move many times. Representatives from PSMSL will sit on the GGOS DOIs for Data Working Group and would like to contribute help with controlled vocabularies, identifying metadata standards etc. We will also contribute to the next GGOS implementation plan.<br>Ponte, Rui M., et al. (2019) "Towards comprehensive observing and modeling systems for monitoring and predicting regional to coastal sea level." <em>Frontiers in Marine Science</em> 6(437).</p>

scholarly journals Wind driven currents in the channel of São Sebastião: winter, 1979

1990 ◽  
Vol 38 (2) ◽  
pp. 111-132 ◽  
Author(s):  
Belmiro Mendes de Castro Fo
Keyword(s):  
Sea Level ◽  
Atmospheric Pressure ◽  
Time Lag ◽  
The South ◽  
Frequency Bands ◽  
Level Data ◽  
Wind Driven Currents ◽  
South Brazil ◽  
And Sea Level

Simultaneous 40 h low-passed wind, current and sea level data in the Channel of São Sebastião (CSS) and atmospheric pressure and sea level data in the South Brazil Bight (SBB) during winter of 1979 were analysed and compared. Currents in the CSS were predominantly northeastward, associated with frontal southerly winds. Current reversals occurred between meteorological disturbance passages. There were significant correlation between alongchannel components of wind and current, with a time lag of 12-18 h, wind leading; and between alongchannel component of current and sea level, with a time lag of 6-12 h, current leading. Most of the variance in the CSS series is concentrated in two frequency bands: 11-16 d and 3 d. SBB series also show high variance in those two bands. Coherences in those two bands show significant values when calculated between alongchannel components of wind and current, and sea level, in the CSS. Those three last signals were almost in phase in the 11-16 d band; and there was a lead of 16 h (25 h) by wind over current (sea level) in the 3 d band. There are several indications that in die subtidal band currents in the CSS are not totally locally forced.

scholarly journals An extreme sea level indicator for the contiguous United States coastline

2019 ◽  
Vol 6 (1) ◽  
Author(s):  
Md. Mamunur Rashid ◽  
Thomas Wahl ◽  
Don P. Chambers ◽  
Francisco M. Calafat ◽  
William V. Sweet
Keyword(s):  
United States ◽  
Sea Level ◽  
Decadal Variability ◽  
Level Indicator ◽  
Relative Contribution ◽  
Level Data ◽  
Water Level Data ◽  
The Individual

AbstractWe develop an aggregated extreme sea level (ESL) indicator for the contiguous United States coastline, which is comprised of separate indicators for mean sea level (MSL) and storm surge climatology (SSC). We use water level data from tide gauges to estimate interannual to multi-decadal variability of MSL and SSC and identify coastline stretches where the observed changes are coherent. Both the MSL and SSC indicators show significant fluctuations. Indicators of the individual components are combined with multi-year tidal contributions into aggregated ESL indicators. The relative contribution of the different components varies considerably in time and space. Our results highlight the important role of interannual to multi-decadal variability in different sea level components in exacerbating, or reducing, the impacts of long-term MSL rise over time scales relevant for coastal planning and management. Regularly updating the proposed indicator will allow tracking changes in ESL posing a threat to many coastal communities, including the identification of periods where the likelihood of flooding is particularly large or small.

scholarly journals Accuracy of the mean sea level continuous record with future altimetric missions: Jason-3 vs. Sentinel-3a

2015 ◽  
Vol 12 (4) ◽  
pp. 1511-1536 ◽  
Author(s):  
L. Zawadzki ◽  
M. Ablain
Keyword(s):  
Sea Level ◽  
Regional Scale ◽  
Mean Sea Level ◽  
Level Data ◽  
Continuous Record ◽  
Climate Evolution ◽  
The Mean ◽  
Altimetric Measurements ◽  
The Impact

Abstract. The current mean sea level (MSL) continuous record, essential for the understanding of climate evolution, is computed with the altimetric measurements of the TOPEX/Poseidon mission, succeeded by Jason-1 and later Jason-2. The accurate continuity of the record is ensured by the conservation of the "historical" TOPEX orbit, but also by calibration phases between the successive missions which enable a rigorous computation of their relative biases. In order to extend the current MSL record, Jason-3 will be the natural successor of Jason-2: on the same orbit with a calibration phase. Shortly after Jason-3, another altimetric climate-oriented mission, Sentinel-3a, will be launched on a different orbit. In this paper, simulated altimetric sea level data is used to study the sensitivity of the MSL continuous record to the change of the "historical" orbit for the new Sentinel-3a orbit. By estimating the impact of the absence of calibration phase on the MSL continuous record trend accuracy at global and regional scale and the impact of the orbit change on the long-term continuity of this MSL record, this study shows that linking Sentinel-3a data instead of Jason-3 to the MSL continuous record would prevent from meeting climate users requirements regarding the MSL trend accuracy.

scholarly journals Accuracy of the mean sea level continuous record with future altimetric missions: Jason-3 vs. Sentinel-3a

Ocean Science ◽  
2016 ◽  
Vol 12 (1) ◽  
pp. 9-18 ◽  
Author(s):  
L. Zawadzki ◽  
M. Ablain
Keyword(s):  
Sea Level ◽  
User Requirements ◽  
Mean Sea Level ◽  
Level Data ◽  
Continuous Record ◽  
Climate Evolution ◽  
The Mean ◽  
Altimetric Measurements ◽  
The Impact

Abstract. The current mean sea level (MSL) continuous record, essential to understanding the climate evolution, is computed with the altimetric measurements of the TOPEX/Poseidon mission, succeeded by Jason-1 and later Jason-2. The accurate continuity of the record is ensured by the conservation of the "historical" TOPEX orbit as well as by calibration phases between the successive missions which enable a rigorous computation of their relative biases. In order to extend the current MSL record, Jason-3 will be the natural successor of Jason-2: on the same orbit with a calibration phase. Shortly after Jason-3, another altimetric climate-oriented mission, Sentinel-3a, will be launched on a different orbit. In this paper, simulated altimetric sea level data are used to study the sensitivity of the MSL continuous record to the change of the "historical" orbit for the new Sentinel-3a orbit. By estimating the impact of the absence of calibration phase on the MSL continuous record trend accuracy at the global and regional scales and the impact of the orbit change on the long-term continuity of this MSL record, this study shows that linking Sentinel-3a data instead of Jason-3 to the MSL continuous record would not meet climate user requirements regarding the MSL trend accuracy.

Characterization of Sea-level Variations Along the Metropolitan Coasts of France: Waves, Tides, Storm Surges and Long-term Changes

2019 ◽  
Vol 88 (sp1) ◽  
pp. 10 ◽  
Author(s):  
Guillaume Dodet ◽  
Xavier Bertin ◽  
Frédéric Bouchette ◽  
Médéric Gravelle ◽  
Laurent Testut ◽  
...  
Keyword(s):  
Sea Level ◽  
Storm Surges ◽  
Long Term Changes ◽  
Sea Level Variations

Development of an Atlantic Canadian Coastal Water Level Neural Network Model

2008 ◽  
Vol 25 (11) ◽  
pp. 2117-2132 ◽  
Author(s):  
Guoqi Han ◽  
Yu Shi
Keyword(s):  
Neural Network ◽  
Water Level ◽  
Sea Level ◽  
Coastal Water ◽  
Water Levels ◽  
Atlantic Canada ◽  
Level Data ◽  
Coastal Water Level ◽  
Term Data

Abstract Coastal water-level information is essential for coastal zone management, navigation, and oceanographic research. However, long-term water-level observations are usually only available at a limited number of locations. This study discusses a complementary and simple neural network (NN) approach, to predict water levels at a specified coastal site from the data gathered at other nearby or remote permanent stations. A simple three-layer, feed-forward, back-propagation network and a neural network ensemble, named Atlantic Canadian Coastal Water Level Neural Network (ACCSLENNT) models, was developed to correlate the nonlinear relationship of sea level data among stations by learning from their historical characteristics. Instantaneous hourly observations of water level from five stations along the coast of Atlantic Canada—Argentia, Belledune, Halifax, North Sydney, and St. John’s—are used to formulate and validate the ACCSLENNT models. Qualitative and quantitative comparisons of the network output with target observations showed that despite significant changes in sea level amplitudes and phases in the study area, appropriately trained NN models could provide accurate and robust long-term predictions of both tidal and nontidal (tide subtracted) water levels when only short-term data are available. The robust results indicate that the NN models in conjunction with limited permanent stations are able to supplement long-term historical water-level data along the Atlantic Canadian coast. Because field data collection is usually expensive, the ACCSLENNT models provide a cost-effective alternative to obtain long-term data along Atlantic Canada.

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