Towards Comprehensive Observing and Modeling Systems for Monitoring and Predicting Regional to Coastal Sea Level

Ponte, Rui M.; Carson, Mark; Cirano, Mauro; Domingues, Catia M.; Jevrejeva, Svetlana; Marcos, Marta; Mitchum, Gary T.; Wal, R. S. W. van de; Woodworth, Philip L.; Ablain, Michaël; Ardhuin, Fabrice; Ballu, Valérie; Becker, Mélanie; Benvéniste, Jérôme; Birol, Florence; Bradshaw, Elizabeth; Cazenave, Anny; Mey-Frémaux, Pierre de; Durand, Fabien; Ezer, Tal; Fu, Lee‐Lueng; Fukumori, Ichiro; Gordon, Kathy; Gravelle, Médéric; Griffies, Stephen M.; Han, Weiqing; Hibbert, Angela; Hughes, Chris W.; Idier, Déborah; Kourafalou, Villy; Little, Christopher M.; Matthews, Andrew; Melet, Angélique; Merrifield, M. A.; Meyssignac, Benoît; Minobe, Shoshiro; Penduff, Thierry; Picot, Nicolas; Piecuch, Christopher G.; Ray, Richard D.; Rickards, Lesley; Santamaría-Gómez, Álvaro; Stammer, Detlef; Staneva, Joanna; Testut, Laurent; Thompson, Keith R.; Thompson, Philip R.; Vignudelli, Stefano; Williams, Joanne; Williams, Simon; Wöppelmann, Guy; Zanna, Laure; Zhang, Xuebin

doi:10.3389/fmars.2019.00437

Cited by 55 publications

(41 citation statements)

References 204 publications

(231 reference statements)

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“…Models will inevitably perform well for some regions and timescales, but less well for others (e.g., Chepurin et al 2014;Becker et al 2016;Meyssignac et al 2017). In particular, models that are capable of reproducing coastal sea level variability observed to date will provide confidence in projecting future coastal sea level change (Ponte et al 2019). • Concerning our knowledge of tides at the coast, users of satellite altimetry in the deep ocean have grown accustomed to having reliable tide models that account for that dominant component of variability in their data.…”

Section: Discussionmentioning

confidence: 99%

“…Progress cannot be made with these and many other questions to do with sea level variability without access to the best, and most complete, observational and modelling data sets, as discussed further by Ponte et al (2019). One may note:…”

Section: Discussionmentioning

confidence: 99%

“…In addition, there is a need for continuous monitoring of vertical land motion at tide gauges, requiring the installation of permanent GNSS stations at as many tide gauges as possible, and as near as possible to the tide gauges, and the undertaking of regular levelling campaigns between the tide gauge benchmarks and GNSS benchmarks (Woodworth et al 2017b). See also discussion of this topic in Marcos et al (2019) and Ponte et al (2019). • It is important also to extend the historical coastal sea level data set via a programme in 'data archaeology' (Bradshaw et al 2015) and the use of 'proxy' (geological) data sets (e.g., Barlow et al 2014).…”

Section: Discussionmentioning

confidence: 99%

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Forcing Factors Affecting Sea Level Changes at the Coast

et al. 2019

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We review the characteristics of sea level variability at the coast focussing on how it differs from the variability in the nearby deep ocean. Sea level variability occurs on all timescales, with processes at higher frequencies tending to have a larger magnitude at the coast due to resonance and other dynamics. In the case of some processes, such as the tides, the presence of the coast and the shallow waters of the shelves results in the processes being considerably more complex than offshore. However, 'coastal variability' should not always be considered as 'short spatial scale variability' but can be the result of signals transmitted along the coast from 1000s km away. Fortunately, thanks to tide gauges being necessarily located at the coast, many aspects of coastal sea level variability can be claimed to be better understood than those in the deep ocean. Nevertheless, certain aspects of coastal variability remain under-researched, including how changes in some processes (e.g., wave setup, river runoff) may have contributed to the historical mean sea level records obtained from tide gauges which are now used routinely in large-scale climate research.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Forcing Factors Affecting Sea Level Changes at the Coast

et al. 2019

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“…Other studies found no correlation between river discharge and sea level variation, such as Blaha [15] for nonseasonal monthly records in the Chesapeake Bay (from tide gauge) or Han and Webster [16] for interannual sea level variability in the Bay of Bengal (based on simulations). Investigations on the importance of river discharges to coastal sea level variations have been made from hours to seasonal and interannual time scales [17]. Less attention has been brought on open ocean variations caused by river runoffs.…”

Section: Introductionmentioning

confidence: 99%

Contribution of the Amazon River Discharge to Regional Sea Level in the Tropical Atlantic Ocean

Giffard

Llovel

Jouanno

et al. 2019

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The Amazon River is by far the largest river by volume of water in the world, representing around 17% of the global riverine discharge to the oceans. Recent studies suggested that its impact on sea level is potentially important at global and regional scales. This study uses a set of regional simulations based on the ocean model NEMO to quantify the influence of the Amazon runoff on sea level in the Tropical Atlantic Ocean. The model is forced at its boundaries with daily fields from the ocean reanalysis GLORYS2V4. Air-sea fluxes are computed using atmospheric variables from DFS5.2, which is a bias-corrected version of ERAinterim reanalysis. The particularity of this study is that interannual daily runoffs from the up-to-date ISBA-CTRIP land surface model are used. Firstly, mean state of sea level is investigated through a comparison between a simulation with an interannual river discharge and a simulation without any Amazon runoff. Then, the impact of the Amazon River on seasonal and interannual variability of sea level is examined. It was shown that the Amazon River has a local contribution to the mean state sea level at the river mouth but also a remote contribution of 3.3 cm around the whole Caribbean Archipelago, a region threatened by the actual sea level rise. This effect is mostly due to a halosteric sea level contribution for the upper 250 m of the ocean. This occurs in response to the large scale advection of the plume and the downward mixing of subsurface waters at winter time. The Amazon discharge also induces an indirect thermosteric sea level contribution. However, this contribution is of second order and tends to counterbalance the halosteric sea level contribution. Regional mass redistributions are also observed and consist in a 8 cm decrease of the sea level at the river mouth and a 4.5 increases on continental shelves of the Gulf of Mexico and Caribbean Sea. In terms of variability, simulations indicate that the Amazon discharge may contributes to 23% and 12% of the seasonal and interannual sea level variances in the Caribbean Archipelago area. These variances are first explained by the Amazon time mean discharge and show very weak sensitivity to the seasonal and interannual variability of the Amazon runoff.

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“…Specifically, its components should cover climate-observing parameters concerned with changes of the ocean circulation and its budgets of heat, freshwater, carbon, and nutrients, and the exchanges of heat, momentum, freshwater, and gases between the ocean, atmosphere, land, and cryosphere. Parameters concerned with sea level as an integral indicator for climate change (see also Ponte et al, 2019) should also be included. Several of the observing requirements are general in nature and concern the global ocean domain; others concern regional specificities and are presented separately in each ocean basin.…”

Section: Observing Requirements For Climatementioning

confidence: 99%