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Bonnefond P., M. Calzas & C. Brachet. |
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Mission FOAM 2018, janvier 2018 |
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2018 |
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7625 |
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Téchiné P., Testut L. |
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Title |
Compte-rendu de campagne à la mer – IFREMER-CNRS-IPEV-IRD |
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Report |
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2019 |
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Valorisation des campagnes océanographiques en série, 29 pages, 12 avril 2019 |
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688 |
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Bachelor's thesis |
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7740 |
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Author |
Prouteau E., P. Téchiné, R. Lhullier, N. Pouvreau |
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Title |
Création de DOI sur un jeu de données |
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Book Chapter |
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2019 |
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Journées REFMAR, 27-29 mars 2019, Paris, France |
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688 |
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Bachelor's thesis |
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7741 |
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Téchiné P., G. Alory, L. Testut, L'us-imago Brest &Amp; Nouméa Et La Dt/insu Brest. |
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Title |
ROSAME / SSS – Gestion d'observations océanographiques |
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Peer-reviewed symposium |
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2020 |
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Journées Développement Logiciel (JDEV), 6-10 juillet 2020, visioconférence |
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yes |
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7746 |
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Author |
Téchiné P., L. Testut. |
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Title |
Préparation HCERES Groupe numérique liée à la donnée scientifique |
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Report |
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2019 |
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Rapport sur les données rosame pour l'OMP, 4 pages, 10 avril 2019 |
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7760 |
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Author |
Calzas M., C. Brachet, C. Drezen, L. Fichen, A. Guillot, P. Téchiné, L. Testut, P. Bonnefond, O. Laurain, V. Ballu, E. Poirier, N. Picot. |
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Title |
Mesure du geoïde marin avec le système CalNaGEO (GNSS) |
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Peer-reviewed symposium |
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Year |
2019 |
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Journées REFMAR, 27-29 mars 2019, Paris, France |
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yes |
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7764 |
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Author |
André F., P. Téchiné, G. Alory, J. Llido. |
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Title |
Bilan d'activités et prospectives du CDS-IS OMP |
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Non peer-reviewed symposium |
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2019 |
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Réunion du bureau exécutif du pôle océan odatis, 6-7 juin 2019, Paris |
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yes |
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7798 |
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Marta Marcos, Guy Wöppelmann, Andrew Matthews, Rui M. Ponte, Florence Birol, Fabrice Ardhuin, Giovanni Coco, Alvaro Santamaría-Gómez, Valerie Ballu, Laurent Testut, Don Chambers, Justin E. Stopa |
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Title |
Coastal Sea Level and Related Fields from Existing Observing Systems |
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Year |
2019 |
Publication |
Surveys in Geophysics |
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Volume |
40 |
Issue |
6 |
Pages |
1293-1317 |
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Abstract |
We review the status of current sea-level observing systems with a focus on the coastal zone. Tide gauges are the major source of coastal sea-level observations monitoring most of the world coastlines, although with limited extent in Africa and part of South America. The longest tide gauge records, however, are unevenly distributed and mostly concentrated along the European and North American coasts. Tide gauges measure relative sea level but the monitoring of vertical land motion through high-precision GNSS, despite being essential to disentangle land and ocean contributions in tide gauge records, is only available in a limited number of stations. (25% of tide gauges have a GNSS station at less than 10 km.) Other data sources are new in situ observing systems fostered by recent progress in GNSS data processing (e.g., GPS reflectometry, GNSS-towed platforms) and coastal altimetry currently measuring sea level as close as 5 km from the coastline. Understanding observed coastal sea level also requires information on various contributing processes, and we provide an overview of some other relevant observing systems, including those on (offshore and coastal) wind waves and water density and mass changes. |
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688 |
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1573-0956 |
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yes |
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7954 |
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Author |
Adam T. Devlin, Jiayi Pan, Hui Lin |
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Title |
Multi-Timescale Analysis of Tidal Variability in the Indian Ocean Using Ensemble Empirical Mode Decomposition |
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Year |
2020 |
Publication |
Journal of Geophysical Research: Oceans |
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125 |
Issue |
12 |
Pages |
e2020JC016604 |
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Keywords |
Coastal risks Ensemble Empirical Mode Decomposition Indian Ocean Sea level variability Tidal evolution Tidal variability |
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Abstract |
Ocean tides have been observed to be changing worldwide for nonastronomical reasons, which can combine with rising mean sea level (MSL) to increase the long-term impact to coastal regions. Tides can also exhibit variability at shorter timescales, which may be correlated with short-term variability in MSL. This short-term coupling may yield higher peak water levels and increased impacts of exceedance events that may be equally significant as long-term sea level rise. Previous studies employed the tidal anomaly correlation (TAC) method to quantify the sensitivity of tides to MSL fluctuations at long-period (>20 years) tide gauges in basin-scale surveys of the Pacific and Atlantic Ocean, finding that TACs exist at most locations. The Indian Ocean also experiences significant sea level rise and tidal variability yet has been less studied due to a sparse network of tide gauges. However, since the beginning of the 21st century, more tide gauges have been established in a wider geographical range, bringing the possibility of better estimates of tidal and MSL variability. Here, we improve the TAC approach, using the ensemble empirical mode decomposition (EEMD) method to analyze tidal amplitudes and sea level at multiple frequency bands, allowing a more effective use of shorter record tide gauges and better understanding of multiple timescales of tidal variability. We apply this approach to 73 tide gauges in the Indian Ocean to better quantify tidal variability in these under-studied regions, finding that the majority of locations exhibit significant correlations of tides and MSL. |
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2169-9291 |
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7956 |
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Author |
Sanne Muis, Maialen Irazoqui Apecechea, Job Dullaart, Joao de Lima Rego, Kristine Skovgaard Madsen, Jian Su, Kun Yan, Martin Verlaan |
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Title |
A High-Resolution Global Dataset of Extreme Sea Levels, Tides, and Storm Surges, Including Future Projections |
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2020 |
Publication |
Frontiers in Marine Science |
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Volume |
7 |
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263 |
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The world’s coastal areas are increasingly at risk of coastal flooding due to sea-level rise (SLR). We present a novel global dataset of extreme sea levels, the Coastal Dataset for the Evaluation of Climate Impact (CoDEC), which can be used to accurately map the impact of climate change on coastal regions around the world. The third generation Global Tide and Surge Model (GTSM), with a coastal resolution of 2.5 km (1.25 km in Europe), was used to simulate extreme sea levels for the ERA5 climate reanalysis from 1979 to 2017, as well as for future climate scenarios from 2040 to 2100. The validation against observed sea levels demonstrated a good performance, and the annual maxima had a mean bias (MB) of -0.04 m, which is 50% lower than the MB of the previous GTSR dataset. By the end of the century (2071–2100), it is projected that the 1 in 10-year water levels will have increased 0.34 m on average for RCP4.5, while some locations may experience increases of up to 0.5 m. The change in return levels is largely driven by SLR, although at some locations changes in storms surges and interaction with tides amplify the impact of SLR with changes up to 0.2 m. By presenting an application of the CoDEC dataset to the city of Copenhagen, we demonstrate how climate impact indicators derived from simulation can contribute to an understanding of climate impact on a local scale. Moreover, the CoDEC output locations are designed to be used as boundary conditions for regional models, and we envisage that they will be used for dynamic downscaling. |
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2296-7745 |
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8031 |
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