CL4.1

Singapore is a small (728 km²) island nation that is vulnerable to rising sea levels with 30% of its land surface area less than 5 m above present sea level. Rising relative sea level (RSL), however, is not uniform with regional RSL changes differing from the global mean due to processes associated with vertical land motion (e.g., glacial-isostatic adjustment) and atmospheric and ocean dynamics. Understanding magnitudes, rates, and driving processes on past and present-day sea level are therefore important to provide greater confidence in accurately quantifying future sea-level rise projections and their uncertainty. Here, we present a synopsis of Singapore’s past and present RSL history using newly developed proxy RSL reconstructions from mangrove peats, coral microatolls and tide gauge data and conclude with probabilistic projections of future RSL change.

Past RSL is characterized by rapid rise during the early Holocene driven primarily by deglaciation of northern hemisphere ice sheets. Sea-level index points (SLIPs) from mangrove peats show sea levels rose rapidly from -20.7 m at 9.5 ka BP to -0.6 m at 7 ka BP at rates of 6-12 mm/yr. This is substantially greater than predicted magnitudes of RSL change from the ICE-6G_C GIA model which shows RSL increasing from -6.4 m at 9.5 ka BP to a ~2.8 m highstand at ~7 ka BP. SLIPs show the mid-Holocene highstand of ~4 ± 3.6 m at 5.2 ka BP before falling towards present at rates up to -2 mm/yr driven by hydro-isostatic processes. The nature of RSL changes during the mid- to late-Holocene transition remains poorly resolved with evidence of sea levels falling below present level to -2.2 ± 2.0 m at 1.2 ka BP. Present RSL reconstructions from coral microatolls coupled with tide-gauge data extend the limited instrumental period in this region beyond ~50 years. They show RSL rose ~0.03 m from 1915 to 1990 at 0.7 ± 1.4 mm/yr before increasing to 1.5 ± 2.1 mm/yr after 1990 to 2019. Future RSL change from probabilistic projections to 2100 under low (RCP 2.6) and high (RCP 8.5) emission scenarios show sea levels rising 0.43 m (50^th percentile) (0.06 – 0.96 m; 95% credible interval) and 0.74 m (0.28 – 1.4 m), respectively. However, projected magnitudes of sea-level rise driven by rapid ice sheet dynamics and the unknown contribution of atmospheric and ocean dynamics in Southeast Asia have the potential to exacerbate projection magnitudes.

How to cite: Shaw, T., Chua, S., Majewski, J., Tanghua, L., Samanta, D., Kopp, R., and Horton, B.: Past, Present and Future Sea Levels in Singapore, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10615, https://doi.org/10.5194/egusphere-egu21-10615, 2021.

Instrumental records show that global mean sea level (GMSL) rose by approximately 15 cm in the 20^th Century, with estimates of contributing factors suggesting the major components are ocean thermal expansion and melting of continental ice sheets and glaciers. However, little is known about the individual contributions to GMSL changes over the preindustrial common era (PCE) and the potential differences in the mechanisms controlling those changes between different time periods. Here, we describe the GMSL changes in the PCE by comparing proxy-based reconstructions with estimates derived from model experiments. The ocean thermal expansion is estimated on the basis of Coupled (Paleoclimate) Model Intercomparison Project (CMIP/PMIP) experiments. The contributions of ice sheets and glaciers are based on simulations with an ice-sheet model (IMAU-ICE) and a global glacier model (The Open Global Glacier Model), respectively. We also describe the thermal expansion response in the different ocean basins over the last millennium. The findings provide new insights on the current anthropogenic warming and sea-level rise in a wider context.

How to cite: Gangadharan, N., Goosse, H., Parkes, D., and Goelzer, H.: Global Mean Sea-level Changes in the Last Two Millennia, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-1951, https://doi.org/10.5194/egusphere-egu21-1951, 2021.

The production of standardized relative sea-level (RSL) databases with a full consideration of uncertainty from many coastlines of the globe have enabled the exploration of RSL variability since the Last Glacial Maximum (LGM, 25 to 21 ka BP). Here, we expanded the global databases by evaluating 430 radiocarbon dated sea-level index points (SLIPs), which provided insights into the variability of RSL along the Atlantic African coast (Morocco to South Africa).

Sea-level data were standardized following the International Geoscience Programme (IGCP) protocols to produce a suite of validated SLIPS as well as limiting points. The Atlantic African coast database was grouped in 21 regions according to geographical position and the distance from LGM ice-sheets. We applied a Gaussian model to estimate regional rates of RSL change and compared the regional data with the ICE-6G Glacial Isostatic Adjustment (GIA) model predictions.

Our analysis indicates the RSL lowstand at the end of LGM was above -105 ± 4 m as indicated by a suite of marine limiting points. Since the LGM, RSL rose rapidly with average rates of up to 15 mm a^-1 between 16 and 9 ka, notably in the Gulf of Guinea. The rates of RSL rise decrease to < 3 mm a^-1 after ~7 ka BP. The mid-Holocene illustrates the emergence of a RSL high-stand which exceed the present mean sea-level between ~6.5 and ~4.5 ka BP. This high-stand is spatially variable and, in some regions was observed at elevations up to 2.5 m (e.g., Morocco, West Sahara, Congo, Namibia). In late Holocene RSL dropped gradually to the present datum. However, the coastal sector comprised between Senegal and Angola reveal late Holocene fluctuations, which are not reproduced by current GIA models. The Atlantic African coast database indicates RSL is controlled by the complex interplay by glacio-isostatic subsidence, rotational effects, ocean syphoning, continental levering, and 3-D variations in mantle viscosity structure as well as local forcing (e.g., compaction related subsidence). The Atlantic African coast database offers the possibility to better understand past RSL thereby providing constraints for more robust future sea-level projections of the west African coast in the framework of the on-going climatic change.

How to cite: Vacchi, M., Spada, G., Anthony, E. E., Renzetti, M., Melini, D., and Horton, B. P.: Variability of the millennial sea-level histories along the western African coasts since the Last Glacial Maximum, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-3019, https://doi.org/10.5194/egusphere-egu21-3019, 2021.

Estimates of global ice volume during MIS 3 (60-29 ka) can be constrained between -25 and -87 m (Shackleton, 2000; Waelbroeck et al., 2002; Clark et al., 2009; Hughes et al., 2013; Grant et al., 2014). As regards the maximum altitude reached during this period there are few observed data for a comparison between the global curves and the variations due to different rheostay of the mantle in coastal areas. Uncertainties on the rheostatic behaviour near- or far-fields from the ice bulk during cold period, make it very difficult to estimate the local sea level during MIS 3. Several factors make investigations of  MIS 3 sea level difficult: i) the areas where suitable coastal sediments formed are currently submerged at depths of few tens of meters below present sea level; ii) the preservation of geomorphic features and sedimentary records is limited due to the erosion occurred during the Last Glacial Maximum (LGM) with sea level at depth of -130m, followed by marine transgression that determined  the development of ravinement surfaces).

Few data were observed worldwide, especially when tectonics or GIA in the near field leads to uplifts. Our research aims to point out what has been published globally and in the Mediterranean, but, above all, to illustrate the sections of new outcrops in Cannitello (Calabria, Italy) where we have found and dated fossiliferous marine pocket beaches deposited on uplifted bed metamorphic rock. Radiocarbon ages of marine shells (about 43 kyrs cal BP) indicate that these outcrops (presently at 28 and 30 meters above sea level) belong to MIS 3.1. Based on some considerations regarding the altitude of MIS 3.1 highstand, the correction for altitude with the local vertical tectonic movements and GIA of the Cannitello outcrops allows us to revise the eustatic altitude of this highstand. This is consistent with the recent findings (Gowan et al., 2020), which are based on a novel ice sheet modelling technique.

Clark, P.U., Dyke, A.S., Shakun, J.D., Carlson, A.E., Clark, J., Wohlfarth, B., Mitrovica, J.X., Hostetler, S.W., McCabe, A.M., 2009. The Last Glacial Maximum. Science 325, 710–714. doi:10.1126/science.1172873

Gowan, E.J., Zhang, X., Khosravi, S., Rovere, A., Stocchi, P., Hughes, A. C., Gyllencreutz, R., Mangerud, J., Svendsen, J. I., Lohmann, G. (in print): Global ice sheet reconstruction for the past 80000 years. PANGEA, Earth & Environmental Science https://doi.org/10.1594/PANGAEA.905800.

Grant, K.M., Rohling, E.J., Ramsey, C.B., Cheng, H., Edwards, R.L., Florindo, F., Heslop, D., Marra, F., Roberts, A.P., Tamisiea, M.E., Williams, F., 2014. Sea-level variability over five glacial cycles. Nature Communications 5, 5076. doi:10.1038/ncomms6076

Hughes, P.D., Gibbard, P.L., Ehlers, J., 2013. Timing of glaciation during the last glacial cycle: evaluating the concept of a global ‘Last Glacial Maximum’ (LGM). Earth-Science Reviews 125, 171–198. doi:10.1016/j.earscirev.2013.07.003

Shackleton, N.J., 2000. The 100,000-Year Ice-Age Cycle Identified and Found to Lag Temperature, Carbon Dioxide, and Orbital Eccentricity. Science 289, 1897–1902. doi:10.1126/science.289.5486.1897

Waelbroeck, C., Labeyrie, L., Michel, E., Duplessy, J.C., McManus, J.F., Lambeck, K., Balbon, E., Labracherie, M., 2002. Sea-level and deep water temperature changes derived from benthic foraminifera isotopic records. Quaternary Science Reviews, EPILOG 21, 295–305. doi:10.1016/S0277-3791(01)00101-9

How to cite: Antonioli, F., Calcagnile, L., Ferranti, L., Mastronuzzi, G., Monaco, C., Montagna, P., Orrù, P., Quarta, G., Pepe, F., Scardino, G., Scicchitano, G., Stocchi, P., and Taviani, M.: Relative sea level change during MIS 3: a black hole in the world. New observations from Calabria, central Mediterranean sea, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-4048, https://doi.org/10.5194/egusphere-egu21-4048, 2021.

The present study examines the Quaternary evolution of the Selinitsa coastal cave in SW Peloponnese, in an attempt to provide new insights on the paleogeographical and paleoclimatological conditions of the Eastern Mediterranean Sea. The entrance of Selinitsa Cave is located +18 m above present sea level (a.p.s.l.) on the eastern coast of Messiniakos Gulf (SW Peloponnese), an area of constant uplift since Middle Pleistocene. Considering the phreatic origin of Selinitsa and the presence of sea level indicators at its entrance (biological and geomorphological markers such as tidal notches and Lithophaga borings), all together qualify the cave suitable for the study of former sea level changes and more particularly, those during the last interglacial period. The MIS 5e is considered the most suitable geological period for the estimation of future sea level rise due to the plethora of geological data at-or-near the coastal zone combined to sea-level fluctuation circles from Middle Pleistocene to-date. Previous results from Selinitsa Cave place the sea level of the latest phase of the last interglacial at +18 m a.p.s.l.

The Eastern Mediterranean is the least studied area relative to the Western Mediterranean, regarding sea level changes during Marine Isotope Stage 5e (MIS 5e). In order to reconstruct the paleogeography of the area and shed light on the climatic conditions of this period, our study involved geological mapping, field measurements and identification of geomorphological features (marine terraces, coastal caves and former sedimentary tidal environments). Additionally, 3D mapping of Selinitsa was conducted in order to precisely define its relative location in respect to the present sea level. Moreover, X-ray diffraction, optical microscopy, mineralogy and major and trace element geochemistry of speleothems and clastic sediments found in the inner part of Selinitsa were also employed and combined to the aforementioned geomorphological data.

The objective of the study is to provide a model for the development and the paleoclimatic conditions of the Selinitsa Cave during Late Pleistocene, how sea-level affected the aforementioned system, and finally provide an estimate of sea-level fluctuation over the last 125 ka.

How to cite: Kampolis, I., Skliros, V., and Triantafyllidis, S.: Quaternary evolution and paleoclimatology of the coastal cave of Selinitsa (SW Peloponnese, Greece) based on geomorphological and geochemical data, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-6516, https://doi.org/10.5194/egusphere-egu21-6516, 2021.

Marine terraces are a cornerstone for the study of paleo sea level and crustal deformation. Commonly, individual erosive marine terraces are attributed to unique sea level high-stands. This stems from early reasoning that marine platforms could only be significantly widened under moderate rates of sea level rise as at the beginning of an interglacial and preserved onshore by subsequent sea level fall. However, if marine terraces are only created during brief windows at the start of interglacials, this implies that terraces are unchanged over the vast majority of their evolution, despite an often complex submergence history during which waves are constantly acting on the coastline, regardless of the sea level stand. 

Here, we question the basic assumption that individual marine terraces are uniquely linked to distinct sea level high stands and highlight how a single marine terrace can be created By reoccupation of the same uplifting platform by successive sea level stands. We then identify the biases that such polygenetic terraces can introduce into relative sea level reconstructions and inferences of rock uplift rates from marine terrace chronostratigraphy.

Over time, a terrace’s cumulative exposure to wave erosion depends on the local rock uplift rate. Faster rock uplift rates lead to less frequent (fewer reoccupations) or even single episodes of wave erosion of an uplifting terrace and the generation and preservation of numerous terraces. Whereas slower rock uplift rates lead to repeated erosion of a smaller number of polygenetic terraces. The frequency and duration of terrace exposure to wave erosion at sea level depend strongly on rock uplift rate.

Certain rock uplift rates may therefore promote the generation and preservation of particular terraces (e.g. those eroded during recent interglacials). For example, under a rock uplift rate of ca. 1.2 mm/yr, Marine Isotope Stage (MIS) 5e (ca. 120 ka) would resubmerge a terrace eroded ca. 50 kyr earlier for tens of kyr during MIS 6d–e stages (ca. 190–170 ka) and expose it to further wave erosion at sea level. This reoccupation could accordingly promote the formation of a particularly wide or well planed terrace associated with MIS 5e with a greater chance of being preserved and identified. This effect is potentially illustrated by a global compilation of rock uplift rates derived from MIS 5e terraces. It shows an unusual abundance of marine terraces documenting uplift rates between 0.8 and 1.2 mm/yr, supporting the hypothesis that these uplift rates promote exposure of the same terrace to wave erosion during multiple sea level stands.

Hence, the elevations and widths of terraces eroded during specific sea level stands vary widely from site-to-site and depend on local rock uplift rate. Terraces do not necessarily correspond to an elevation close to that of the latest sea level high-stand but may reflect the elevation of an older, longer-lived, occupation. This leads to potential misidentification of terraces if each terrace in a sequence is assumed to form uniquely at successive interglacial high stands and to reflect their elevations.

How to cite: Malatesta, L. C., Finnegan, N. J., Huppert, K., and Carreño, E.: Formation and preservation of marine terraces during multiple sea level stands, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-9076, https://doi.org/10.5194/egusphere-egu21-9076, 2021.

With the impending threat of continued sea-level rise and coastal inundation, it is important to understand the short- and long-term factors affecting sea-level in a particular region. Such a feat can be accomplished by turning to indicators of past sea-levels. This study aims to highlight the utility of archaeological indicators in sea-level reconstructions, using Akko on Israel’s northern Mediterranean micro-tidal coast as a case study. Here, installations belonging to the maritime metropolis’ Hellenistic Period (3rd to 1st centuries BCE) harbor, which have well-constrained chronological and elevational limitations, were identified at depths averaging 1.1 to 1.2 meters below present sea-level (mbpsl). These features would have been located sub-aerially during the time of their construction and use, indicating a change in relative sea-level in the area since this time. Utilizing a multiple proxy approach incorporating marine sedimentological and geoarchaeological methodologies with previously recorded regional data, three possible explanations for this apparent sea-level change were assessed: structural deterioration, sea-level rise, and vertical tectonic movements. This study revealed that, although signs of structural deterioration are apparent in some parts of the quay, this particular harbor installation is well-established as in situ as it has a continuous upper surface and its southern edge is built directly on the underlying bedrock. Consequently, the harbor’s current submarine position can instead be attributed to sea-level change and/or vertical tectonic displacements. While this amount of sea-level rise (over 1 m) is in agreement with glacio-hydro-eustatic values suggested for other areas of the Mediterranean, it falls below those previously reported locally. In addition, most studies suggest that the tectonic movement along this stretch of coastline is negligible. These new data provide a reliable relative sea-level marker with very little error with regard to maximum sea-level, thereby renewing the overall consideration of the tectonic and sea-level processes that have been active along this stretch of coastline during the last 2,500 years.

How to cite: Pietraszek, A. V., Katz, O., Sharvit, J., and Goodman-Tchernov, B.: Sea-Level Reconstructions and Archaeological Indicators: A Case Study from the Submerged Hellenistic Harbor at Akko, Israel, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2376, https://doi.org/10.5194/egusphere-egu21-2376, 2021.

Reconstructions of relative sea level (RSL) during the Holocene provide important constraints for Glacial Isostatic Adjustment (GIA) models, determining Earth rheology, estimating ice-equivalent meltwater input, and fingerprinting sources of ice mass loss. In far-field regions such as the Indian Ocean, RSL is characterized by rapid rise during the early Holocene driven primarily by deglaciation of northern hemisphere ice sheets. This cumulated to a characteristic mid-Holocene highstand before falling towards present driven by hydro-isostatic processes. Reconstructions of RSL utilize proxy sea-level indicators to produce sea-level index points (SLIPs) that position RSL in time and space with an associated temporal and vertical uncertainty.

Here we present a standardized RSL database with a full consideration of uncertainty from the Maldives to investigate regional variations in the characteristics of the mid Holocene highstand, and to constrain the eustatic contribution to RSL change during the mid and late Holocene.

We produce new SLIPs from a mangrove forest in Kelaa, part of the Haa Alif Atoll in the northern area of the Maldives. We subsampled for mangrove macro fossils suitable for radiocarbon dating and obtained 5 dates with calibrated ages ranging between 630 – 1340 years BP. These new SLIPs show RSL was between 0.07m – -0.14m during this period.

How to cite: Richards, G., Majewski, J., Tan, C., Tan, F., Li, T., Shaw, T., and Horton, B.: A new Holocene record from a far-field site in the Indian Ocean to constrain Holocene sea level., EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-13812, https://doi.org/10.5194/egusphere-egu21-13812, 2021.

The Last Interglacial (LIG), as well as other warmer periods in the Earth’s geologic history, provides an analogue for predicted warming conditions in the near future. Analysis of sea-level indicators during this period is important in constraining regional drivers of relative sea-level change (RSL) and in modeling future trajectories of sea-level rise. In southeast Asia, several studies have been done to examine LIG sea-level indicators such as coral reef terraces and tidal notches. A synthesis of the state-of-the-art of the LIG RSL indicators in the region, meanwhile, has yet to be done. We reviewed over 50 published works on the LIG RSL indicators in southeast Asia and used the framework of the World Atlas of Last Interglacial Shorelines (WALIS) in building a standardized database of previously published LIG RSL indicators in the region. In total, we identified 38 unique RSL indicators and inserted almost 140 ages in the database. Available data from Indonesia, the Philippines, and East Timor points to variable elevation of sea-level indicators during the LIG highlighting the complex tectonic setting of this region. Variable uplift rates (from as low as 0.02 to as high as 1.1 m/ka) were reported in the study areas echoing various collision and subduction processes influencing these sites. Although several age constraints and elevation measurements have been provided by these studies, more data is still needed to shed more light on the RSL changes in the region. With this effort under the WALIS framework, we hope to identify gaps in the LIG RSL indicators literature in SE Asia and recognize potential areas that can be visited for future work. We also hope that this initiative will help us further understand the different drivers of past sea-level changes in SE Asia and will provide inputs for projections of sea-level change in the future.

How to cite: Maxwell, K., Westphal, H., and Rovere, A.: A standardized database of Last Interglacial sea-level indicators in southeast Asia: Records from coral reef terraces in a tectonically complex region, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-16151, https://doi.org/10.5194/egusphere-egu21-16151, 2021.

Ongoing deformation of the Earth in response to past ice-ocean mass exchange is a significant contributor to contemporary sea-level changes and will be an important contributor to future changes. Calibrated models of this process, conventionally termed glacial isostatic adjustment (GIA), have been used to determine its influence on current and future sea-level changes. To date, the majority of these models have assumed a spherically-symmetric (1-D) representation of Earth structure. Here we apply a model that can simulate the isostatic response of a 3-D Earth in order to consider the contribution of lateral structure to model estimates of current and future sea-level change. We will present results from a global analysis based on two independent ice history reconstructions and a suite of 3-D Earth models with viscosity structure constrained using different seismic velocity models and recent estimates of lithosphere thickness variations. The accuracy of these GIA model parameter sets is assessed by comparing model output to a recently published data set of vertical land motion specifically intended to provide a robust measure of the GIA signal (Schumacher et al., Geophysical Journal International, 2018). This comparison indicates that the inclusion of lateral Earth viscosity structure results in an improved fit to the GPS-determined vertical land motion rates although significant residuals persist in some regions indicating that further efforts to improve constraints on this structure are necessary. Using the model parameter sets that best match the GPS constraints to predict the contribution of GIA to contemporary sea-level change indicates that lateral viscosity structure impacts the model estimates by order 1 mm/yr in some regions and that the model uncertainty is of a similar amplitude. Simulations of the GIA contribution to future sea-level change are also significantly affected, with differences, relative to a 1-D Earth model, reaching several decimetres on century timescales and several metres on millennial timescales. 

How to cite: Milne, G., Yousefi, M., and Latychev, K.: Quantifying the influence of glacial isostatic adjustment on current and future sea-level change using 3-D Earth models, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-13813, https://doi.org/10.5194/egusphere-egu21-13813, 2021.

It is well known that key climatic variability like the El Niño Southern Oscillation and Pacific Decadal Oscillation dominate steric sea-level variability in the Pacific Ocean and that this variability influences global- and regional-mean sea-level time series. Reducing the known internal variability from these time series reduces trend errors and can elucidate other factors including anthropogenic influence and sea-level acceleration, as has been demonstrated for the open ocean. Here we discuss the influence of key climate modes on coastal, decadal sea-level variability. For coastal stakeholders and managers it is important to understand the decadal-scale and local changes in the rate of sea-level rise in the context of internal variability in order to inform management decisions in the short- to medium-term. We use a 53-year run of a high-resolution NEMO ocean model run, forced by the DRAKKAR reanalysis atmospheric data set and with the global-mean sea level at each timestep removed, to investigate modes of decadal sea-level variability at the coast, in different basins and from different sea-level components. At more than 45% of Pacific Ocean coastal locations, greater than 50% of the decadal sea-level change can be explained by a regression of the leading principal component mode with key climate indices; ENSO in the Pacific Ocean. In different ocean basins, 18.5% to 61.0% of coastal locations have more than 33% of decadal sea-level variance explained by our climate index reconstructions. These areas include coastal regions lacking long-duration or good quality tide gauges for long-term observations such as the North-West Africa coastline. Because of the shallow depth of continental shelves, steric sea-level change propagates onto the shelf as a manometric (mass) sea-level signal. We use a set of tide gauge locations to demonstrate the internal, decadal sea-level change observed at many coasts has a substantial contribution from local, manometric signal that is driven by climate variability.

How to cite: Royston, S., Bamber, J., and Bingham, R.: How much of the decadal, coastal sea level variability can we describe by climate modes?, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-11924, https://doi.org/10.5194/egusphere-egu21-11924, 2021.

Satellite altimetry data have revealed a global mean sea level rise of 3.1 mm/yr since 1993 with large regional sea level trend variability. These remote data highlight complex structures especially in strongly eddying regions. A recent study showed that over 38% of the global ocean area, the chaotic variability that spontaneously emerges from the ocean may hinder the attribution to the atmospheric forcing of regional sea level trends from 1993 to 2015. This study aims at complementing this work by first focusing on the atmospherically-forced and chaotic contributions of regional sea level interannual variability and its components (steric and manometric sea level interannual variability). A global ¼° ocean/sea-ice 50-member ensemble simulation is considered to disentangle the imprints of the atmospheric forcing and of the chaotic ocean variability over 1993-2015. The atmospherically-forced and chaotic interannual variabilities of sea level mainly have a steric origin , except in coastal areas. The chaotic part of the interannual variability of sea level and its components is stronger in the Pacific and Atlantic oceans than in the Indian ocean. The chaotic part of the interannual variability of sea level and of its steric component exceeds 20% over 48% of the global ocean area; this fractional area reduces to 26% for the manometric component. As the chaotic part of the regional sea level interannual variability has a substantial imprint, this study then interested in quantifying the periods when it becomes dominant over the atmospherically-forced contribution. This is assessed using spectral analysis on the ensemble simulation in the frequency domain for the sea level and its steric and manometric components over the global ocean as well as in some basins of interest. This enables us to better characterise and quantify the chaotic ocean variability contribution to regional sea level changes and its components.

How to cite: Carret, A., Llovel, W., Penduff, T., and Molines, J.-M.: Characterisation of the chaotic variability of the regional sea level and its components over 1993-2015 at interannual time scales, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-1297, https://doi.org/10.5194/egusphere-egu21-1297, 2021.

Ocean warming accounts for more than 90% of the net Earth energy imbalance. As oceans warm, sea level is rising due to the expansion of seawater. Therefore, estimating ocean heat content (OHC) and thermosteric sea level (TSL) appears of great importance to assess the impact of the on-going global warming.  Different research groups have estimated such climate variables for years now and even routinely (Boyer et al., 2016). These climate variables are derived from in situ temperature measurement at different depths with uneven spatial coverage. Two main sources of uncertainties are attributed to the evolving technology of temperature probes and to the uneven spatio-temporal distribution of in situ measurements (Boyer et al., 2016). A large ensemble of forced eddy-permitting ocean simulations revealed the existence of another uncertainty of regional OHC trend estimates (Sérazin et al 2017): a substantial intrinsic variability emerging from oceanic nonlinearities generates random multi decadal trends, which can mask its atmospherically-forced counterpart. This intrinsic variability can also leave a large imprint on regional sea level trends over the altimetry period (Llovel et al., 2018; Penduff et al., 2019). Less attention has been paid for estimating the imprint of such intrinsic ocean variability in OHC and TSL change associated with the uneven spatial coverage of in situ records. In this study, we investigate the imprint of ocean intrinsic variability and of the uneven distribution of in situ records on OHC and TLS change, by taking advantage of this large ensemble simulation. To do so, we extract synthetic in situ temperature profiles from the simulations in space, time and depth. We then interpolate these synthetic profiles using ISAS (Gaillard et al. 2016) to estimate both the imprint of intrinsic ocean variability and the uneven distribution of in situ data to OHC change and TSL change from 2005 to 2015.

How to cite: Llovel, W., Kolodziejczyk, N., Penduff, T., Molines, J.-M., and Close, S.: Imprint of intrinsic ocean variability on ocean heat content and thermosteric sea level over 2005-2015, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-1188, https://doi.org/10.5194/egusphere-egu21-1188, 2021.

Change in the global mean sea level (GMSL) is the sum of changes in the global mean steric sea level and global mean ocean mass. Over the 1993-2016 period, the GMSL budget was found to be closed, as shown by many independent studies. However, non-closure of the sea level budget after 2016 has been recently reported when using altimetry, Argo and GRACE/GRACE Follow-On data (Chen et al., GRL, 2020). This non-closure may result from errors in one or more components of the sea level budget (altimetry-based GMSL, Argo-based steric sea level or GRACE-based ocean mass). In this study, we investigated possible sources of errors affecting atlimetry and Argo data used to assess closure of the GMSL budget. Concerning altimetry data, we compared the wet tropospheric correction (WTC) applied to Jason-3 data (the reference satellite mission used for the GMSL computation since 2016) with that from the SARAL/AltiKa mission, and found no systematic bias between the radiometer measurements from these two missions. Besides, preliminary comparisons of GMSL trends (using the WTC ECMWF model) between different missions do not suggest discrepancies larger than 0.4 mm/yr over 2016-present. While further analyses are still needed, we find unlikely that non-closure of the sea level budget results from errors of the altimetry system. Concerning Argo data, since 2016, salinity data from different processing groups display strong discrepancies, likely due to instrumental problems and data editing issues. Good agreement is found between all available Argo-based thermosteric products. Given that the halosteric component should be negligible in global average, we re-examined the sea level budget since 2016 using only the thermosteric component and found significant improvement in the budget closure, although it is not yet fully closed. This suggests that the observed discrepancies in the Argo-based halosteric component largely contribute to the non-closure of the GMSL budget in the recent years.

How to cite: Barnoud, A., Cazenave, A., Pfeffer, J., Ablain, M., Guérou, A., and Chen, J.: Closing the global mean sea level budget from altimetry, GRACE/GRACE Follow-On and Argo data (2005-present), EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2051, https://doi.org/10.5194/egusphere-egu21-2051, 2021.

Studies of the global sea-level budget (SLB) and ocean-mass budget (OMB) are essential to assess the reliability of our knowledge of sea-level change and its contributors. The SLB is considered closed if the observed sea-level change agrees with the sum of independently assessed steric and mass contributions. The OMB is considered closed if the observed ocean-mass change is compatible with the sum of assessed mass contributions. 

Here we present results from the Sea-Level Budget Closure (SLBC_cci) project conducted in the framework of ESA’s Climate Change Initiative (CCI). We used data products from CCI projects as well as newly-developed products based on CCI products and on additional data sources. Our focus on products developed in the same framework allowed us to exercise a consistent uncertainty characterisation and its propagation to the budget closure analyses, where the SLB and the OMB are assessed simultaneously. 

We present time series of global mean sea-level changes from satellite altimetry; new time series of the global mean steric component generated from Argo drifter data with incorporation of sea surface temperature data; time series of ocean-mass change derived from GRACE satellite gravimetry; time series of global glacier mass change from a global glacier model; time series of mass changes of the Greenland Ice Sheet and the Antarctic Ice Sheet both from satellite radar altimetry and from GRACE; as well as time series of land water storage change from the WaterGAP global hydrological model. Our budget analyses address the periods 1993–2016 (covered by the satellite altimetry records) and 2003–2016 (covered by GRACE and the Argo drifter system). In terms of the mean rates of change (linear trends), the SLB is closed within uncertainties for both periods, and the OMB, assessable for 2003–2016 only, is also closed within uncertainties. Uncertainties (1-sigma) arising from the combined uncertainties of the elements of the different budgets considered are between 0.26 mm/yr and 0.40 mm/yr, that is, on the order of 10% of the magnitude of global mean sea-level rise, which is 3.05 ± 0.24 mm/yr and 3.65 ± 0.26 mm/yr for 1993-2016 and 2003-2016, respectively. We also assessed the budgets on a monthly time series basis. The statistics of monthly misclosure agrees with the combined uncertainties of the budget elements, which amount to typically 2-3 mm for the 2003–2016 period. We discuss possible origins of the residual misclosure.

How to cite: Horwath, M. and Cazenave, A. and the SLBC_cci Team: Global sea-level and ocean-mass budgets using advanced data products and uncertainty characterisation, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10174, https://doi.org/10.5194/egusphere-egu21-10174, 2021.

Satellite altimetry missions provide a quasi-global synoptic view of sea level variations over more than 25 years and provide regional sea level (SL) indicators such as trends and accelerations. Estimating realistic uncertainties on these quantities is crucial to address current climate science questions. While uncertainty estimates are available for the global mean sea level (GMSL), information is not available at local scales so far. We estimate a local satellite altimetry error budget and use it to derive local error variance-covariance matrices, and estimate confidence intervals on trends and accelerations at the 90% confidence level. Over 1993–2019, we find that the average local sea level trend uncertainty is 0.83 mm.yr⁻¹ with values ranging from 0.78 to 1.22 mm.yr⁻¹. For accelerations, uncertainties range from 0.057 to 0.12 mm.yr⁻², with a mean value of 0.062. We also perform a sensitivity study to investigate a range of plausible error budgets.

A dataset consisiting of a single NetCDF file containing local error levels, error variance-covariance matrices, SL trends and accelerations, along with corresponding uncertainties is provided (https://doi.org/10.17882/74862). Code to reproduce the study is also distributed (https://github.com/pierre-prandi/rsl). With this information, users should be able to reuse these error levels to derive uncertainties on any metric (e.g. inter annual variability) or time period.

How to cite: Prandi, P., Meyssignac, B., Ablain, M., Spada, G., Ribes, A., Legeais, J.-F., and Benveniste, J.: Local sea level trends, accelerations and uncertainties over 1993-2019, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2068, https://doi.org/10.5194/egusphere-egu21-2068, 2021.

Consistent long-term satellite-based data-sets of sea surface elevation exist nowadays to study sea level variability, globally and at regional scales. Two of them are suitable for climate-related studies: one produced in the framework of the European Space Agency (ESA)-funded Sea Level Climate Change Initiative (SL_CCI); the other offered by the European Copernicus Climate Change Service (C3S). Both data-sets cover the global ocean since 1993 to 2015 (SL_CCI) and to present (C3S) at spatial resolution of 0.25 x 0.25 degrees. The first is obtained by merging data from all the available satellite altimetry missions. The second one relies only on a couple of simultaneous altimetry missions at a time to provide stable long-term variability estimates of sea level, is constantly updated and has resolution 0.125 x 0.125 degrees in the Mediterranean Sea.
Previous studies have investigated the relationship between satellite-derived absolute sea level change rates and tide gauge observations of relative sea level change in littoral zones of the Mediterranean basin [Fenoglio-Mark, L., 2002; Fenoglio-Mark et al., 2012]. Other studies made use also of global positioning system measurements of vertical land motion in addition to tide gauge and satellite altimetry data [Rocco F.V., 2015; Zerbini et al., 2017]. Vignudelli et al., [2018] highlighted the difficulty of deriving spatially-consistent information on the sea level rates at regional scale in the Adriatic Sea. Other studies have claimed the possibility to merge locally isolated information into a coherent regional picture using a linear inverse problem approach [Wöppelmann and Marcos, 2012]: such approach has been successfully applied to a number of tide gauges in the Adriatic Sea [De Biasio et al., 2020]. The approach tested in the Adriatic Sea is going to be extended to the Mediterranean and major findings will be presented at conference.
The motivation of this study is that industrial areas are widely spread along the littoral zone of the southern Europe, and residential settlements are densely scattered along the coasts of the Mediterranean Sea. Not least, a strongly rooted seaside tourism is one of the main economic resources of the region, which is particularly exposed to the sea level variability of both natural and anthropogenic origin. A well known example of such a exposition is Venice (northern Italy) which has been recently hit by the second-highest tide in recorded history (November 2019), and is being protected against storm surges by the MOSE barrier since October 2020. Therefore, a re-analyses of the actual sea level rates with novel methodologies that take into account a better usage of all available observations is key to understand the future coastal sea level changes and their relative importance.

Fenoglio-Marc, L. 2002. DOI: 10.1016/S1474-7065(02)00084-0

Fenoglio-Marc, L.; Braitenberg, C.; Tunini, L. 2012. DOI: 10.1016/j.pce.2011.05.014

Rocco, F.V. Ph.D. Thesis, 2015. URI: https://amslaurea.unibo.it/id/eprint/10172

Zerbini, S.; Raicich, F.; Prati, C.M.; Bruni, S.; Conte, S.D.; Errico, M.; Santi, E. 2017. DOI: 10.1016/j.earscirev.2017.02.009

Vignudelli, S., De Biasio, F., Scozzari, A. Zecchetto, S., and Papa, A. 2019. DOI:10.1007/1345_2018_51

Wöppelmann, G. and Marcos, M. 2012. DOI: 10.1029/2011JC007469

De Biasio, F., Baldin, G. and Vignudelli, S. 2020. DOI:10.3390/jmse8110949

How to cite: De Biasio, F. and Vignudelli, S.: Reassessing sea level change rates in the Mediterranean Sea in the age of altimetry, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2371, https://doi.org/10.5194/egusphere-egu21-2371, 2021.

Consistent and long-term satellite-based data-sets to study climate-scale variations of sea level globally and in the coastal zone are available nowadays. Two altimetry data-sets were recently produced: the first one is generated by the European Space Agency’s (ESA) Sea Level Climate Change Initiative (SL_CCI) over a grid of 0.25 x 0.25 degrees, merging and homogenizing the various available satellite altimetry missions. The second one is a climate-oriented altimeter sea level product that started in the framework of the European Copernicus Climate Change Service (C3S), and is now released as daily-means over a grid of 0.25 x 0.25 degrees, covering the global ocean since 1993 to present. Both reach in the Arctic the latitude of 81.5 N degrees. Therefore, these new altimetry products cover the coastal area surrounding Ny-Ålesund (Svalbard Islands, Norway), where a tide gauge station is active since 1976. Near the Svalbard coasts also the along track surface elevations of the CryoSat-2 mission are made available through the European Space Agency’s Grid Processing on Demand (G-POD) for Earth Observation Applications facility.

In this study, we compare sea level measurements from the Ny-Ålesund tide gauge with the climate-oriented altimeter sea level gridded products (SL_CCI and C3S) and with the along track data from the only CryoSat-2 mission. This study has three objectives: 1) to assess the performances of the gridded data moving from offshore to near coasts; 2) to explore how the synergy with along track high resolution CryoSat-2 data might help to detail the sea ice impact on the observation of relative and absolute sea level rise around Svalbard; 3) to verify if the differences between satellite altimetry and tide gauges can be used as a proxy of vertical ground movement in the study area by adopting the approaches elaborated in Vignudelli et al. [2018] and De Biasio et al. [2020] that can be validated with ground vertical displacements estimated using Global Positioning System (GPS) data from the stations close to Ny-Ålesund.

REFERENCES

Vignudelli, S., De Biasio, F., Scozzari, A. Zecchetto, S., and Papa, A. (2019): Sea Level Trends and Variability in the Adriatic Sea and Around Venice, Proceedings of the International Review Workshop on Satellite Altimetry Cal/Val Activities and Applications, 23-26 April 2018, Chania, Crete, Greece. DOI:10.1007/1345_2018_51

De Biasio, F.; Baldin, G.; Vignudelli, S. Revisiting Vertical Land Motion and Sea Level Trends in the Northeastern Adriatic Sea Using Satellite Altimetry and Tide Gauge Data. J. Mar. Sci. Eng. 2020, 8, 949. DOI:10.3390/jmse8110949

How to cite: Vignudelli, S. and De Biasio, F.: Estimating Relative and Absolute Sea Level Rise at Ny-Ålesundwith satellite altimetry and in-situ observations, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2836, https://doi.org/10.5194/egusphere-egu21-2836, 2021.

Sea-level change is geographically non-uniform, with regional departures that can reach several times the global average. Characterizing this spatial variability and understanding its causes is crucial to the design of adaptation strategies for sea-level rise. This, as it turns out, is no easy feat, primarily due to the sparseness of the observational sea-level record in time and space. Long tide gauge records are restricted to a few locations along the coast. Satellite altimetry offers a better spatial coverage but only since 1992. In the Mediterranean Sea, the tide gauge network is heavily biased towards the European shorelines, with only one record with at least 35 years of data on the African coasts. Past studies have attempted to address the difficulties related to this data sparseness in the Mediterranean Sea by combining the available tide gauge records with satellite altimetry observations. The vast majority of such studies represent sea level through a combination of altimetry-derived empirical orthogonal functions whose temporal amplitudes are then inferred from the tide gauge data. Such methods, however, have tremendous difficulty in separating trends and variability, make no distinction between relative and geocentric sea level, and tell us nothing about the causes of sea level changes. Here, we combine observational data from tide gauges and altimetry with sea-level fingerprints of land-mass changes through a Bayesian hierarchical model to quanify the sources of sea-level rise since 1960 at any arbitrary location in the Mediterranean Sea. We find that Mediterranean sea level rose at a relatively low rate from 1960 to 1990, primarily due to dynamic sea-level changes in the nearby Atlantic, at which point it started rising significantly faster with comparable contributions from dynamic sea level and land-mass changes.

How to cite: Mir Calafat, F., Frederikse, T., Horsburgh, K., and Dayoub, N.: The sources of sea-level rise in the Mediterranean Sea since 1960, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-15087, https://doi.org/10.5194/egusphere-egu21-15087, 2021.

Coastal cities are going through rapid and challenging changes. Accurate estimates of probabilities of extreme sea levels are a highly valuable asset to face flooding hazards and support safe planning of coastal zones in the future climate. Probabilities of specific extreme events have been traditionally estimated from the observed extremes independently at each tide gauge location. However, this approach has shortcomings. Firstly, sea level observations often cover a relatively short historical time period and thus contain only a small number of extreme cases (e.g. annual maxima). This causes substantial uncertainties when estimating the distribution parameters. Secondly, exact information on sea level extremes between the tide gauge locations and incorporation of dependencies of adjacent stations is often lacking in the analysis.

One way to partially tackle these issues is to exploit spatial dependencies exhibited by the sea level extremes. These dependencies emerge from the fact that sea level variations are often driven by the same physical and dynamical factors at the neighboring stations. Bayesian hierarchical modeling offers a way to model these dependencies. The model structure allows to share information on sea level extremes between the neighboring stations and also provides a natural way to represent modeling uncertainties.

In this study, we use Bayesian hierarchical modeling to estimate return levels of annual sea level maximum on the Finnish coast, located in the northeast parts of the Baltic Sea. As annual maxima are studied, we use the generalized extreme value (GEV) distribution as the basis of our model. To tailor the model specifically for the target region, spatial dependencies are modeled using covariates, which reflect the distinct geometry of the Baltic Sea. We also account for inter-annual and decadal-scale variations in the distribution parameters by including teleconnection indices such as North Atlantic oscillation (NAO) in our model. Preliminary results show that hierarchical modeling provides added value in comparison to the traditional approach, when applied to the available long-term tidegauge time series in Finland. The work presented here is a part of project PREDICT (Predicting extreme weather and sea level for nuclear power plant safety) that supports nuclear power plant safety in Finland.

How to cite: Räty, O., Laine, M., Leijala, U., Särkkä, J., and Johansson, M.: Bayesian Hierarchical Modeling of Sea Level Extremes on the Finnish Coast, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7826, https://doi.org/10.5194/egusphere-egu21-7826, 2021.

Climate-induced sea-level rise and vertical land movements, including natural and human-induced subsidence in sedimentary coastal lowlands, combine to change relative sea levels around the world's coast. Global-average coastal relative sea-level rise was 2.5 mm/yr over the last two decades. However, as coastal inhabitants are preferentially located in subsiding locations, they experience an average relative sea-level rise up to four times faster at 7.8 to 9.9 mm/yr. This first global quantification of relative sea-level rise shows that the resulting impacts, and adaptation needs are much higher than reported global sea-level rise measurements would suggest. Hence, coastal subsidence is an important global issue that needs more assessment and action. In particular, human-induced subsidence in and surrounding coastal cities can be rapidly reduced with appropriate policy measures for groundwater utilization and drainage. This offers substantial and rapid benefits in terms of reducing growth of coastal flood exposure due to relative sea-level rise.

How to cite: Lincke, D., Nicholls, R. J., Hinkel, J., Brown, S., Vafeidis, A. T., Meyssignac, B., Hanson, S. E., Merkens, J., and Fang, J.: A global analysis of subsidence, relative sea-level change and coastal flood exposure, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-14985, https://doi.org/10.5194/egusphere-egu21-14985, 2021.

The effective climate sensitivity (EffCS) of models in the Coupled Model Intercomparison Project 6 (CMIP6) has increased relative to CMIP5. Consequently, using CMIP6 models tends to lead to larger projections of global mean surface air temperature (GSAT) increase for a given emissions scenario. The effect of increased EffCS on projections of global mean sea-level (GMSL) change however, has so far only been studied using a reduced complexity model. Here, we explore the implications of increased EffCS in CMIP6 models for GMSL change projections in 2100 for three emissions scenarios: SSP5-8.5, SSP2-4.5 and SSP1-2.6.

Whereas CMIP6 projections of GSAT change are substantially higher than in CMIP5, projections of global mean thermal expansion (GTE) are only slightly higher. We use these projections as input to construct projections of GMSL change, using the Monte Carlo approach of IPCC AR5. Isolating the impact of the CMIP6 simulations using consistent methods is an important step to ensure traceability to past IPCC projections of global and regional sea-level change. The resulting 95^th percentile of projected GMSL change at 2100 is only 3-7 cm higher for CMIP6 than for CMIP5, depending on the emissions scenario. Projected rates of GMSL rise around 2100 increase more strongly from CMIP5 to CMIP6, though, implying more pronounced differences beyond 2100 and greater committed sea-level rise. GMSL change in 2100 is accurately predicted by time-integrated temperature change and therefore mitigation requires early reduction of emissions.

We also find that the 95^th percentile projections based on individual CMIP6 models can differ as much as 51 cm and that the 5-95% range of projected GMSL change for individual CMIP6 models can be substantially outside of the 5-95% range of the CMIP6 multi-model ensemble. Thus, through subsetting the CMIP6 ensemble using EffCS, a choice can be made between characterizing the central part of the probability distribution and more comprehensively sampling the high end of the GMSL projection space, which is relevant to risk-averse stakeholders. Our results show this may substantially alter ensemble projections, underlining the need to constrain EffCS in global climate models in order to reduce uncertainty in sea-level projections.

How to cite: Hermans, T., Gregory, J., Palmer, M., Ringer, M., Katsman, C., and Slangen, A.: Projecting Global Mean Sea-Level Change Using CMIP6 Models, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-1965, https://doi.org/10.5194/egusphere-egu21-1965, 2021.

Most of the excess energy stored in the climate system is taken up by the oceans leading to thermal expansion and sea level rise. Future sea level projections allow decision-makers to assess coastal risk, develop climate resilient communities and plan vital infrastructure in low- elevation coastal zones. Confidence in these projections depends on the ability of climate models to simulate the various components of future sea level rise. In this study we estimate the contribution from thermal expansion to sea level rise using the simulations of global mean thermosteric sea level from 15 available models in the Coupled Model Intercomparison Project Phase (CMIP) 6. We calculate a global mean thermosteric sea level rise of 18.8 cm [12.8 - 23.6 cm, 90% range] and 26.8 cm [18.6 - 34.6 cm, 90% range] for the period 2081–2100, relative to 1995-2014 for SSP245 and SSP585 scenarios respectively. In a comparison with a 20 model ensemble from CMIP5, the CMIP6 ensemble mean of future global mean thermosteric sea level rise (2014-2100) is higher for both scenarios and shows a larger variance. By contrast, for the period 1901-1990, global mean thermosteric sea level from CMIP6 has half the variance of that from CMIP5. Over the period 1940-2005, the rate of CMIP6 ensemble mean of global mean thermosteric sea level rise is 0.2 ± 0.1 mm yr^-1, which is less than half of the observed rate (0.5 ± 0.02 mm yr^-1). At a multi-decadal timescale, there is an offset of ~10 cm per century between observed/modelled thermosteric sea level over the historical period and modelled thermosteric sea level over this century for the same rate of change of global temperature. We further discuss the difference in global mean thermosteric sea level sensitivity to the changes in global surface temperature over the historical and future periods.

How to cite: Jevrejeva, S., Palanisamy, H., and Jackson, L.: Global mean thermosteric sea level projections by 2100 in CMIP6 climate models, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-1934, https://doi.org/10.5194/egusphere-egu21-1934, 2021.

Coastal impacts of climate change and the related mitigation and adaptation needs requires assessments of future sea-level changes. Following a common practice in coastal engineering, probabilistic sea-level projections have been proposed for at least 20 years. This requires a probability model to represent the uncertainties of future sea-level rise, which is not achievable because potential ice sheets mass losses remain poorly understood given the knowledge available today. Here, we apply the principles of extra-probabilistic theories of uncertainties to generate global and regional sea-level projections based on uncertain components. This approach assigns an imprecision to a probabilistic measure, in order to quantify lack of knowledge pertaining to probabilistic projections. This can serve to understand, analyze and communicate uncertainties due to the coexistence of different processes contributing to future sea-level rise, including ice-sheets. We show that the knowledge gained since the 5th Assessment report of the IPCC allows better quantification of how global and regional sea-level rise uncertainties can be reduced with lower greenhouse gas emissions. Furthermore, Europe and Northern America are among those profiting most from a policy limiting climate change to RCP 2.6 versus RCP 4.5 in terms of reducing uncertainties of sea-level rise.

How to cite: Le Cozannet, G., Rohmer, J., Manceau, J.-C., Durand, G., Ritz, C., Melet, A., Meyssignac, B., Salas y Mélia, D., Carson, M., Slangen, A., Hinkel, J., Lambert, E., Thiéblemont, R., Le Bars, D., Stammer, D., Van De Wal, R., and Nicholls, R.: Quantifying ambiguity in sea-level projections, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2779, https://doi.org/10.5194/egusphere-egu21-2779, 2021.

Southeast Asia is especially vulnerable to the impacts of sea-level rise due to the presence of many low-lying small islands and highly populated coastal cities. However, our current understanding of sea-level projections and changes in upper-ocean dynamics over this region currently rely on relatively coarse resolution (~100 km) global climate model (GCM) simulations and is therefore limited over the coastal regions. Here using GCM simulations from the High-Resolution Model Intercomparison Project (HighResMIP) of the Coupled Model Intercomparison Project Phase 6 (CMIP6) to (1) examine the improvement of mean-state biases in the tropical Pacific and dynamic sea-level (DSL) over Southeast Asia; (2) generate projection on DSL over Southeast Asia under shared socioeconomic pathways phase-5 (SSP5-585); and (3) diagnose the role of changes in regional ocean dynamics under SSP5-585. We select HighResMIP models that included a historical period and shared socioeconomic pathways (SSP) 5-8.5 future scenario for the same ensemble and estimate the projected changes relative to the 1993-2014 period. Drift corrected DSL time series is estimated before examining the projected changes. Due to improved simulation of heat, salt, and mass distribution in the ocean, HighResMIP models not only reduce mean state biases in the tropical Pacific (such as cold-tongue sea surface temperature bias), but also near Southeast Asia including DSL. Despite intermodel diversity, there is an overall agreement of increasing sea-level over Southeast Asia. The multimodel ensemble of HighResMIP models suggests a rise of 0.2 m sea level in dynamic sea level (combined with thermosteric component) over Southeast Asia by 2070. Sea-level rises further up to 0.5 m by the end of the 21^st century. Further, we found regional heat and mass transport changes have a major role in the projected sea-level pattern over Southeast Asia. For example, heat convergence to the east of Vietnam can account for most of the sea-level rise in the region. Our study can provide better insight into the contribution of regional ocean dynamics to DSL projections and useful to suggest for further ocean modelling studies.

How to cite: Samanta, D., Jevrejeva, S., Palanisamy, H. K., Karnauskas, K. B., Goodkin, N. F., and Horton, B. P.: Role of Regional Ocean Dynamics in Dynamic Sea Level Projections by the end of the 21st Century over Southeast Asia, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-8618, https://doi.org/10.5194/egusphere-egu21-8618, 2021.

Coastal regions are subject to an increasing anthropogenic pressure. Projections of coastal sea level changes are of great interest for coastal risk assessment and decision-making processes. Sea level projections are typically produced using global climate models. However, their coarse resolution limits the realism of the representation of coastal dynamical processes influencing sea level changes at the coast, potentially leading to substantial biases. Dynamical downscaling methods can be used to refine projections at regional scales by increasing the model spatial resolution and by explicitly including more processes. Such methods rely on the implementation of a high-resolution regional climate model (RCM). 

In this work, we developed the IBI-CCS regional ocean model based on a 1/12° North Eastern Atlantic NEMO ocean model configuration. IBI-CCS includes coastal processes such as tides and atmospheric pressure forcing in addition to the ocean general circulation (dynamic sea level). This RCM is used to perform a dynamical downscaling of CNRM-CM6-1-HR, a global climate model (GCM) developed by the Centre National de Recherches Météorologiques (CNRM) with a 1/4° resolution over the ocean. CNRM-CM6-1-HR contributes to the Coupled Model Intercomparison Project 6th Phase (CMIP6). IBI-CCS is thus forced by the GCM ocean and atmospheric outputs at the lateral and air-sea boundaries. Several corrections were applied to the GCM forcings to avoid the propagation of climate drifts and biases into the regional simulations. The computations are performed over the 1950 to 2100 period for several CMIP6 climate change scenarios.

In order to validate the dynamical downscaling method, the regionally downscaled (IBI-CCS) and GCM (CNRM-CM6-1-HR) simulations are compared to reanalyses and observational datasets over the 1993-2014 period. These comparisons are performed at different time scales for a selection of ocean variables including sea level. The results show that large scale performances of IBI-CCS are better than those of the GCM thanks to the corrections applied. In addition, high frequency diagnostics are carried out and highlight for example that IBI-CCS sea level extreme events are similar to those of a reference regional ocean reanalysis. In a second phase, the RCM and GCM sea level rise projections are compared over the 21^st century. These comparisons allow to investigate the impact of the model resolution and of a more complete representation of coastal processes for the simulation of projected sea level changes. 

How to cite: Chaigneau, A., Reffray, G., Voldoire, A., and Melet, A.: High-resolution regional projections of sea level changes along Western European coasts during the 21st century, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10937, https://doi.org/10.5194/egusphere-egu21-10937, 2021.