Coastal Sea Level Change from in the North Eastern Atlantic

2020 ◽  
Author(s):  
Luciana Fenoglio-Marc ◽  
Bernd Uebbing ◽  
Jürgen Kusche ◽  
Salvatore Dinardo
Keyword(s):  
Time Series ◽  
Sea Level ◽  
Sea Level Change ◽  
Altimeter Data ◽  
Level Change ◽  
The North ◽  
North Eastern ◽  
Coastal Sea

<p>A significant part of the World population lives in the coastal zone, which is affected by coastal sea level rise and extreme events. Our hypothesis is that the most accurate sea level height measurements are derived from the Synthetic Aperture Altimetry (SAR) mode. This study analyses the output of dedicated processing and assesses their impacts on the sea level change of the North-Eastern Atlantic. </p><p>It will be shown that SAR altimetry reduces the minimum usable distance from five to three kilometres when the dedicated coastal retrackers SAMOSA+ and SAMOSA++ are applied to data processed in SAR mode. A similar performance is achieved with altimeter data processed in pseudo low resolution mode (PLRM) when the Spatio-Temporal Altimeter sub-waveform Retracker (STAR) is used. Instead the Adaptive Leading Edge Sub-waveform retracker (TALES) applied to PLRM is less performant. SAR processed altimetry can recover the sea level heights with 4 cm accuracy up to 3-4 km distance to coast. Thanks to the low noise of SAR mode data, the instantaneous SAR and in-situ data have the highest agreement, with the smallest standard deviation of differences and the highest correlation. A co-location of the altimeter data near the tide gauge is the best choice for merging in-situ and altimeter data. The r.m.s. (root mean squared) differences between altimetry and in-situ heights remain large in estuaries and in coastal zone with high tidal regimes, which are still challenging regions. The geophysical parameters derived from CryoSat-2 and Sentinel-3A measurements have similar accuracy, but the different repeat cycle of the two missions locally affects the constructed time-series.</p><p>The impact of these new SAR observations in climate change studies is assessed by evaluating regional and local time series of sea level. At distances to coast smaller than 10 Kilometers the sea level change derived from SAR and LRM data is in good agreement. The long-term sea level variability derived from monthly time-series of LRM altimetry and of land motion-corrected tide gauges agrees within 1 mm/yr for half of in-situ German stations. The long-term sea level variability derived from SAR data show a similar behaviour with increasing length of the time series.</p><p> </p>

Wind-Driven Coastal Sea Level Variability in the Northeast Pacific

2014 ◽  
Vol 27 (12) ◽  
pp. 4733-4751 ◽  
Author(s):  
Philip R. Thompson ◽  
Mark A. Merrifield ◽  
Judith R. Wells ◽  
Chantel M. Chang
Keyword(s):  
Time Series ◽  
Sea Level ◽  
Wind Stress ◽  
Sea Level Change ◽  
Minor Importance ◽  
Trade Winds ◽  
Sea Levels ◽  
Northeast Pacific ◽  
Level Change ◽  
Coastal Sea

Abstract The rate of coastal sea level change in the northeast Pacific (NEP) has decreased in recent decades. The relative contributions to the decreased rate from remote equatorial wind stress, local longshore wind stress, and local windstress curl are examined. Regressions of sea level onto wind stress time series and comparisons between NEP and Fremantle sea levels suggest that the decreased rate in the NEP is primarily due to oceanic adjustment to strengthened trade winds along the equatorial and coastal waveguides. When taking care to account for correlations between the various wind stress time series, the roles of longshore wind stress and local windstress curl are found to be of minor importance in comparison to equatorial forcing. The predictability of decadal sea level change rates along the NEP coastline is therefore largely determined by tropical variability. In addition, the importance of accounting for regional, wind-driven sea level variations when attempting to calculate accelerations in the long-term rate of sea level rise is demonstrated.

Developing constraints on the relative sea-level curve for the northeast of Ireland from the mid-Holocene to the present day

2006 ◽  
Vol 364 (1841) ◽  
pp. 857-866 ◽  
Author(s):  
Julian D Orford ◽  
Joanne Murdy ◽  
Robert Freel
Keyword(s):  
Sea Level ◽  
Annual Variation ◽  
Tide Gauge ◽  
Sea Level Change ◽  
Tidal Level ◽  
Tide Gauge Records ◽  
Relative Sea Level ◽  
Level Change ◽  
The North

Tide-gauge records from the north of Ireland have been digitized to generate annual estimates of both mean-sea-level (MSL) position from Malin Head (1958–1998), and mean tidal level (MTL) from Belfast Harbour (1918–2002). Both sites exhibit substantial annual variation, but show overall long-term shallow rates of falling relative sea-level change (RSLC) that are very similar at −0.2 mm a −1 (±0.37 mm a −1 ) for Belfast and −0.16 mm a −1 (±0.17 mm a −1 ) for Malin. Using these rates as constraints, plus other constraints of inferred RSLC rates from the mid-Holocene, an approximation of the likely profile of RSLC rates for the northeast of Ireland since 6 ka ago is presented.

scholarly journals Comparison of in situ time-series of temperature with gridded sea surface temperature datasets in the North Atlantic

2009 ◽  
Vol 66 (7) ◽  
pp. 1467-1479 ◽  
Author(s):  
Sarah L. Hughes ◽  
N. Penny Holliday ◽  
Eugene Colbourne ◽  
Vladimir Ozhigin ◽  
Hedinn Valdimarsson ◽  
...  
Keyword(s):  
Time Series ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
North Atlantic ◽  
Sea Surface ◽  
The North ◽  
Spatial Coverage ◽  
The North Atlantic

Abstract Hughes, S. L., Holliday, N. P., Colbourne, E., Ozhigin, V., Valdimarsson, H., Østerhus, S., and Wiltshire, K. 2009. Comparison of in situ time-series of temperature with gridded sea surface temperature datasets in the North Atlantic. – ICES Journal of Marine Science, 66: 1467–1479. Analysis of the effects of climate variability and climate change on the marine ecosystem is difficult in regions where long-term observations of ocean temperature are sparse or unavailable. Gridded sea surface temperature (SST) products, based on a combination of satellite and in situ observations, can be used to examine variability and long-term trends because they provide better spatial coverage than the limited sets of long in situ time-series. SST data from three gridded products (Reynolds/NCEP OISST.v2., Reynolds ERSST.v3, and the Hadley Centre HadISST1) are compared with long time-series of in situ measurements from ICES standard sections in the North Atlantic and Nordic Seas. The variability and trends derived from the two data sources are examined, and the usefulness of the products as a proxy for subsurface conditions is discussed.

Towards a vulnerability assessment of the UK and northern European coasts: the role of regional climate variability

2005 ◽  
Vol 363 (1831) ◽  
pp. 1329-1358 ◽  
Author(s):  
M.N Tsimplis ◽  
D.K Woolf ◽  
T.J Osborn ◽  
S Wakelin ◽  
J Wolf ◽  
...  
Keyword(s):  
Sea Level ◽  
Wave Height ◽  
North Sea ◽  
Positive Response ◽  
Sea Level Change ◽  
Empirical Relationships ◽  
Level Change ◽  
The North ◽  
The North Sea ◽  
The Uk

Within the framework of a Tyndall Centre research project, sea level and wave changes around the UK and in the North Sea have been analysed. This paper integrates the results of this project. Many aspects of the contribution of the North Atlantic Oscillation (NAO) to sea level and wave height have been resolved. The NAO is a major forcing parameter for sea-level variability. Strong positive response to increasing NAO was observed in the shallow parts of the North Sea, while slightly negative response was found in the southwest part of the UK. The cause of the strong positive response is mainly the increased westerly winds. The NAO increase during the last decades has affected both the mean sea level and the extreme sea levels in the North Sea. The derived spatial distribution of the NAO-related variability of sea level allows the development of scenarios for future sea level and wave height in the region. Because the response of sea level to the NAO is found to be variable in time across all frequency bands, there is some inherent uncertainty in the use of the empirical relationships to develop scenarios of future sea level. Nevertheless, as it remains uncertain whether the multi-decadal NAO variability is related to climate change, the use of the empirical relationships in developing scenarios is justified. The resulting scenarios demonstrate: (i) that the use of regional estimates of sea level increase the projected range of sea-level change by 50% and (ii) that the contribution of the NAO to winter sea-level variability increases the range of uncertainty by a further 10–20 cm. On the assumption that the general circulation models have some skill in simulating the future NAO change, then the NAO contribution to sea-level change around the UK is expected to be very small (<4 cm) by 2080. Wave heights are also sensitive to the NAO changes, especially in the western coasts of the UK. Under the same scenarios for future NAO changes, the projected significant wave-height changes in the northeast Atlantic will exceed 0.4 m. In addition, wave-direction changes of around 20° per unit NAO index have been documented for one location. Such changes raise the possibility of consequential alteration of coastal erosion.

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

&lt;p&gt;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.&lt;br&gt;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 &amp;#8220;29% of the GLOSS [Global Sea Level Observing System] GNSS-co-located tide gauges have a geodetic tie available at SONEL [Syst&amp;#232;me d'Observation du Niveau des Eaux Littorales]&amp;#8221; 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.&lt;br&gt;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.&lt;br&gt;Ponte, Rui M., et al. (2019) &quot;Towards comprehensive observing and modeling systems for monitoring and predicting regional to coastal sea level.&quot; &lt;em&gt;Frontiers in Marine Science&lt;/em&gt; 6(437).&lt;/p&gt;

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