CL3.1.1

Coastal areas are highly diverse, ecologically rich, regions of key socio-economic activity, and are particularly sensitive to sea- level change. Over most of the 20th century, global mean sea level has risen mainly due to warming and subsequent expansion of the upper ocean layers and the melting of glaciers and ice caps. Over the last three decades, increased mass loss of the Greenland and Antarctic ice sheets has also started to contribute significantly to contemporary sea-level rise. The future mass loss of these ice sheets, which combined represent a sea-level rise potential of ~65 m, constitutes the main source of uncertainty in long-term (centennial to millennial) sea-level rise projections. Improved knowledge of the magnitude and rate of future sea-level change is therefore of utmost importance. Moreover, sea level does not change uniformly across the globe, and can differ greatly at both regional and local scales. The most appropriate and feasible sea level mitigation and adaptation measures in coastal regions strongly depend on local land use and associated risk aversion. Here, we advocate that addressing the problem of future sea-level rise and its impacts requires (i) bringing together a transdisciplinary scientific community, from climate and cryospheric scientists to coastal impact specialists, and (ii) interacting closely and iteratively with users and local stakeholders to co-design and co-build coastal climate services, including addressing the high-end risks. Following these principles, as also adopted in the EU project “Projecting sea-level rise: from projections to local implications” (PROTECT), we encourage the formation of research consortia that cover the entire knowledge chain. In this way global sea-level science can be linked to effective coastal climate services at the scale of risk and adaptation

How to cite: Durand, G., van den Broeke, M. R., Le Cozannet, G., Edwards, T. L., Holland, P. R., Jourdain, N. C., Marzeion, B., Mottram, R., Nicholls, R. J., Pattyn, F., Paul, F., Slangen, A. B. A., Winkelmann, R., Burgard, C., van Calcar, C. J., Barré, J.-B., Bataille, A., and Chapuis, A.: Sea-level rise: from global perspectives to local services, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-13026, https://doi.org/10.5194/egusphere-egu22-13026, 2022.

Quantifying paleo sea-level changes is an important challenge given its intricate relation with paleo-climate, -ice-sheets and geodynamics, but pre-Holocene uncertainties currently span several tens of meters. The world’s coastlines provide an enormous geomorphologic dataset, and recent modelling studies have showed their potential in constraining paleo sea-level through forward landscape evolution modeling. We take a next step, by applying a Bayesian approach to invert the geometry of marine terrace sequences to paleo sea-level. Using a Markov chain Monte Carlo sampling method, we test our model on synthetic profiles and two observed marine terrace sequences. The synthetic profiles – with known input parameters – show that there are optimal values for uplift rate, erosion rate, initial slope and wave base depth to obtain a well-constrained inversion. Both the inversion of synthetic profiles and a terrace profile from Santa Cruz (Ca, US) show how sea-level peaks are easier to constrain than sea-level troughs, but that also solutions for peaks tend to be non-unique. Synthetic profiles and profiles from the Corinth Rift (Greece) both show how inverting multiple profiles from a sequence can lead to a narrower range of possible paleo sea-level, especially for sea-level troughs. This last result emphasizes the potential of inverting coastal morphology: joint inversion of globally distributed marine terrace profiles may eventually reveal not only local relative sea-level histories, but catalyse a better understanding of both global paleo sea-level and glacio-isostatic adjustments.

How to cite: de Gelder, G., Hedjazian, N., Pastier, A.-M., Husson, L., and Bodin, T.: Inverting marine terrace morphology to constrain paleo sea-level, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2605, https://doi.org/10.5194/egusphere-egu22-2605, 2022.

We present Version 1.0 of the World Atlas of Last Interglacial Shorelines (WALIS), a global database containing samples and sea-level proxies dated to Marine Isotope Stage 5 (~70 to 130 ka). The database was built through manuscripts and associated datasets compiled in a Special Issue of the journal Earth System Science data (https://essd.copernicus.org/articles/special_issue1055.html). We collated the single contributions (archived in Zenodo at this link: https://zenodo.org/communities/walis_database/) into an open-access standalone database. Database documentation is available at this link: https://doi.org/10.5281/zenodo.3961544. Version 1.0 of the database contains 4005 sea-level index points and 4390 dated samples connected with several tables containing relevant metadata (e.g., elevation measurement techniques, sea-level datums, and literature references).

How to cite: Rovere, A., Ryan, D. D., Vacchi, M., Dutton, A., Simms, A., and Murray-Wallace, C.: Introducing WALIS, the World Atlas of Last Interglacial Shorelines Version 1.0, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2489, https://doi.org/10.5194/egusphere-egu22-2489, 2022.

Using the framework of the World Atlas of Last Interglacial Shorelines (WALIS), we produced a standardized database of Last Interglacial (LIG) sea-level indicators in Southeast Asia after reviewing available studies on relative sea-level (RSL) proxies such as coral reef terraces and tidal notches in the Philippines; Sulawesi; and Sumba, Timor, and Alor regions. In total, we reviewed 43 unique RSL proxies in the region and highlighted sites for future studies. Following this work, we revisited a site in west Luzon, Philippines where LIG coral reef terraces were previously reported. In this paper, we present new geomorphic and stratigraphic data on the fossil coral reef terraces in Pangasinan, west Luzon which adds to the limited sea-level indicators in the region. The low-lying areas of western Pangasinan are underlain by sequences of calcareous sandstone-mudstone with minor pebbly conglomerate and tuffaceous sandstone units belonging to the Sta. Cruz Formation, with tentative age designation of Late Miocene to Early Pliocene. Unconformably overlying the tentatively assigned sandstone unit of Sta. Cruz Formation is the Plio-Pleistocene Bolinao Limestone, the youngest formational unit in the area. Based on previous literature, a sequence of coral reef terraces (possibly LIG) is cut onto the Bolinao Limestone. Rising to about 14 meters above mean sea level (m amsl) along the coast of western Pangasinan are previously dated Holocene coral reef terraces. While additional data is needed to shed more light on the RSL changes in the region, our work proves to be more challenging due to the difficulties of doing field surveys during a global pandemic. Nonetheless, we hope that data from this research will help us further understand the different drivers of past sea-level changes in SE Asia providing necessary geologic baseline data for projections of sea-level change in the future.

How to cite: Maxwell, K., Westphal, H., Rovere, A., and Garas, K.: Late Cenozoic sea-level indicators in west Luzon, Philippines, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10973, https://doi.org/10.5194/egusphere-egu22-10973, 2022.

The last interglacial (LIG), ca. 128-116 ka, is widely considered a process analogue in understanding Earth’s systems in a future warmer climate. In particular, significant effort has been made to better constrain ice sheet contributions to sea level rise through direct field observation of relative sea level (RSL) indicators. In order to extract the RSL, a series of corrections for formational parameters and post-depositional processes need to be applied. Along tropical coastal margins, LIG RSL observations are predominately based on exposed shallow coral reef sequences due to their relatively narrow indicative range and reliable U-series chronological constraints. However, the often-limited sub-stadial temporal preservation of many Pleistocene reef sequences on stable coastlines restrict many reported RSLs to a series of distinct points in within the LIG. This in turn, limits ability to elucidate different commonly reported meter-scale sub-stadial sea level peak patterns and their associated uncertainties. In order to address this shortcoming, lithostratigraphic and geomorphologic traces are often used to place RSLs into a broader context. Unfortunately, this is often subjective, with significant reliance on field observations where missing facies and incomplete sequences can distort interpretations. Stepping back from a conventional approach, in this study we generate a spectrum of synthetic Quaternary subtropical fringing reefs in southwestern Madagascar within the DIONISOS forward stratigraphic model environment. Each reef sequence has been subjected to distinct Greenland and Antarctica melt scenarios produced by a coupled ANICE-SELEN global isostatic adjustment model, matching previously hypothesized LIG sea level curves in the Indo-Pacific Basin. The resulting suite of synthetic reef sequences provides the ability to probabilistically test any number of melt scenarios against the sensitivity of the stratigraphic record. We propose this accessible additional quantitative quality control during the final interpretation phase of establishing emergent reef sequence based LIG RSL indicators can assist in narrowing down the wide uncertainty surrounding inter-stadial ice sheet behaviors.   

How to cite: Boyden, P., Stocchi, P., and Rovere, A.: Assessing Last Interglacial Greenland and Antarctic Ice Sheet melting through forward stratigraphic derived synthetic outcrops: test case from Southwestern Madagascar, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8270, https://doi.org/10.5194/egusphere-egu22-8270, 2022.

Cultural heritage not only witnesses past spiritual and aesthetic attitudes of mankind, but also represents a unique means to investigate the intimate relationship between humanity and the environment.  We present an overview and preliminary data of the SPHeritage Project, which investigates evidence of Palaeolithic human occupation and cultural heritage in the NW Mediterranean area in conjunction with Pleistocene sea-level change studies. A tightly interdisciplinary approach is necessary to use cultural heritage as a proxy for sea-level change evidence. The SPHeritage Project (MUR grant: FIRS2019_00040, P.I.: M. Pappalardo) investigates how human populations have responded to environmental changes and sea-level variations over the last 400,000 years in the Ligurian-Provençal coastal area (along the border between Italy and France) using a combination of micro-invasive methods applied to in situ and previously excavated sediments of uttermost archaeological relevance. In this area, particularly in the archaeological area of Balzi Rossi, a unique assemblage of archaeological sites dating to the Palaeolithic can be found in a rocky coast geomorphological setting where sea-level indicators of the last 3 or 4 interglacials are present. They lack reliable dating and a standardized assessment of the palaeo sea level they record. Improved age constraint of the coastal deposits and recording of relative sea-level (RSL) change evidence is necessary for: i) contribution to the standardized inventory of past interglacial sea-leves; ii) investigating changes in the biodiversity of rocky coastal marine ecosystems triggered by different interglacial environmental conditions; iii) the development of a self-consistent Glacial Isostatic Adjustment model capable of including the residual effect of previous interglacials’ rebound on the isostatic response of later interglacials; iv) investigating how RSL change and consequent shoreline fluctuations can drive settlement strategies and human migration/dispersal patterns. This project is challenged by the previous removal of large portions of the local archaeological sequences in earlier investigations beginning at the end of the nineteenth century. The challenge in this Project is that most of the local archaeological sequences have been extensively investigated since the end of the nineteenth century and large part of the deposits were removed. Therefore, we will combine analyses of relict in situ sediments with those of stratigraphically constrained materials preserved in museums and archaeological deposits worldwide. Moreover, traces of past shorelines will be searched for in the sedimentary sequence of the continental shelf through geophysical surveys and, if this will prove possible, through direct sediment coring. Our preliminary data are promising, and suggest that this interdisciplinary and microinvasive approach can provide valuable evidence on sea-level change from archaeological areas without hampering cultural heritage preservation.

How to cite: Pappalardo, M. and the SPHeritage Project members: Investigating Pleistocene sea-level changes along the northern Mediterranean coast through Palaeolithic cultural heritage: perspectives from the S-P-Heritage Project, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11357, https://doi.org/10.5194/egusphere-egu22-11357, 2022.

A sea-level budget improves understanding of driving processes and their relative contributions. However, most sea-level budget assessments are limited to the 20^th and 21^st centuries and are global in scale. Here, we estimate the sea-level budget on centennial to millennial timescales of the Common Era (last 2000 years). We expand upon previous analysis of sites along the U.S. mid-Atlantic coast (Walker et al., 2021) and produce site-specific sea-level budgets for all of the eastern and western North American coastlines and Gulf coast. This broader scope further improves understanding of the temporal evolution and variability of driving processes of sea-level changes in the past and present, and which will shape such changes in the future.

To produce the sea-level budgets, we use an updated global database of instrumental and proxy sea-level records coupled with a spatiotemporal model. Using the unique spatial scales of driving processes, we separate relative sea-level records into global, regional, and local-scale components. Preliminary results along the eastern North American coastline reveal that each budget is dominated by regional-scale, temporally-linear processes driven by glacial isostatic adjustment until at least the mid-19^th century. This signal exhibits a spatial gradient, ranging from 1.0 ± 0.02 mm/yr (1σ) in Newfoundland to a maximum of 1.6 ± 0.02 mm/yr in southern New Jersey to 0.5 ± 0.02 mm/yr in Florida. Non-linear regional and local-scale processes, such as ocean/atmosphere dynamics and groundwater withdrawal, are smaller in magnitude and vary temporally and spatially. The most significant change to the budgets is the increasing influence of the global signal due to ice melt and thermal expansion since ~1800 CE, which reaches a 20^th century rate of 1.3 ± 0.1 mm/yr, accounting for 43-65% of each budget.

How to cite: Walker, J., Kopp, R., Shaw, T., Richards, G., and Horton, B.: Common Era sea-level budgets of North America, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6530, https://doi.org/10.5194/egusphere-egu22-6530, 2022.

Under high seasonal monsoon rainfall and active tectonics, the Ayeyarwady delta is a large delta plain characterized by a high sediment supply. Also, the Ayeyarwady river, together with the Sittaung, and the Salween Rivers are bringing ~600 Mt/yr of sediments to the Andaman Sea through the Gulf of Martaban. A recent research effort have allowed characterizing the sedimentation at present and since the mid-Holocene. We here propose to integrate these published observations in a stratigraphic reconstruction and to determine by numerical modelling how much these Holocene massive sediment transfers play on coastal subsidence and relative sea level at present.

The present average sedimentation rate at the front of Ayeyarwady delta is ~10 cm/yr and the delta may be divided in two sectors: an eastern embayed sector and a western open coast sector. During the mid-Holocene, the aerial part of the delta have experimented fast progradation rate, reaching prograding rate of ~ 30 m/yr. When applying this sedimentation pattern on a preliminary (radial) viscoelastic Earth model, we show that sediment isostasy plays on the regional coastal dynamics and subsidence at present. In addition, the Ayeyarwady delta lies in a complex tectonic setting, bounded to the west by the Indo-Burman collision zone, and to the east by the sub-vertical dextral Sagaing Fault. We are integrating this tectonic setting in an earth model that allows lateral vertical discontinuity for exploring how much this significantly changes the modelling results.

How to cite: Grall, C., Henry, A., Karpytchev, M., and Becker, M.: Effect of Holocene sediment redistributions on the relative sea level at present in the Ayeyarwady delta (aka Irrawaddy delta, Myanmar), EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-13467, https://doi.org/10.5194/egusphere-egu22-13467, 2022.

In this study we have quantified the role of seasonal cycles in globally observed sea level variability from satellite altimetry over 1993-2018. We show the largest seasonal variability, with contribution more than 80% of total variance, is detected in particular regions- the marginal seas over the continental shelf regions in South East Asia and Gulf of Carpentaria, tropical Atlantic along the coastal regions of east Atlantic Ocean, Arabian Sea, regions of Mediterranean, Red Sea with amplitudes greater than 20cm in majority of these locations. The rest of the ocean, mainly deep open ocean, exhibits strong signatures of non-seasonal variability related to interannual and longer scale cycles.

For the regions with large seasonal variability (e.g. South East Asia coastline), analysis of seasonal variability demonstrate a good agreement in amplitude and phase from satellite altimetry and tide gauges records. While steric contribution can explain more than 80% of total variability in the deep ocean areas, in shallow areas we explain a large part of variability though wind driven during the two monsoon seasons, and not attributed to the steric changes.

How to cite: Jevrejeva, S. and Palanisamy, H.: Seasonal signal and regional sea level variability over the past 25 years , EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4426, https://doi.org/10.5194/egusphere-egu22-4426, 2022.

Globally variable ocean and atmospheric dynamics lead to spatially complex seasonal cycles in sea level. The China Seas, that is the Bohai, Yellow, East China and the South China seas, is a region with strong seasonal amplitudes, and straddles the transition between tropical and temperature zones, monsoonal and westerlies, shelf and deep ocean zones. Here we investigate the drivers for seasonal variability in sea level from tide gauge records, satellite altimetry along with output from the NEMO (Nucleus for European Modeling of the Ocean) model including sea surface height and ocean bottom pressure along with meteorological data in the China Seas. The seasonal cycle accounts for 37% - 94% of sea level variability in 81 tide gauge records, ranging from 18 to 59 cm. We divided the seasonal cycles into four types: 1) an asymmetric sinusoid; 2) a clearly defined peak on a flat background; 3) a relatively flat signal; 4) a symmetric co-sinusoid. Type 1 is found in northern China and Taiwan, Korea, Japan and The Philippines where Inverse Barometer (IB) effects dominates seasonality along with a steric contribution. The seasonal monsoon associated with barotropic response and freshwater exchange play important roles in type 2, (eastern and southern Chinese coasts), type 3 (East Malaysia) and type 4 (Vietnam and Gulf of Thailand). IB corrected seasonal cycle amplitudes are larger in continental shelf areas than the deep ocean, with a maximum in the Gulf of Thailand, and NEMO underestimates the seasonal amplitude along the coast by nearly 50%.

How to cite: Qu, Y., Jevrejeva, S., Williams, J., and Moore, J.: Drivers for seasonal variability in sea level around the China seas, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3307, https://doi.org/10.5194/egusphere-egu22-3307, 2022.

The relative contributions of local and remote wind stress and air-sea buoyancy forcing to sea-level variations along the East Coast of the United States are not well quantified, hindering the understanding of sea-level predictability there. Here, we use an adjoint sensitivity analysis together with an Estimating the Circulation and Climate of the Ocean (ECCO) ocean state estimate to establish the causality of interannual sea-level variations near the Nantucket island, the approximate geographic center of the northeast US coast where sea-level fluctuations are coherent. Wind forcing explains 68% of the Nantucket interannual sea-level variance, while wind and buoyancy forcing together explain 97% of the variance. Wind stress contribution is near-local, primarily from the New England shelf northeast of Nantucket. We disprove a previous hypothesis about Labrador Sea wind stress being an important driver of Nantucket sea-level variations and another hypothesis suggesting local wind stress being a secondary driver. Buoyancy forcing, as important as wind stress in some years, includes local contributions as well as remote contributions from the subpolar North Atlantic that influence Nantucket sea level a few years later. Our rigorous adjoint-based analysis corroborates previous correlation-based studies that sea-level variations in the subpolar gyre and the northeast US coast can both be influenced by subpolar buoyancy forcing. Forward forcing perturbation experiments further indicate remote buoyancy forcing affects Nantucket sea level mostly through slow advective processes, although waves can cause rapid Nantucket sea level response within a few weeks. Our results quantifying the spatial distribution of forcing contributions to Nantucket sea-level variations are also useful for the development of machine-learning models for predicting sea-level variation off the northeast US coast.

How to cite: Lee, T., Wang, O., Piecuch, C., Fukumori, I., Fenty, I., Frederikse, T., Menemenlis, D., Ponte, R., and Zhang, H.: Local and remote forcing of sea-level variation off the northeast US coast, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3342, https://doi.org/10.5194/egusphere-egu22-3342, 2022.

Sea level change affects hundreds of millions of people living in coastal regions. In addition to measuring the total sea level change via satellite altimetry, it is important to understand individual mass and steric contributors on global and regional scales. Consequently, deriving accurate global and regional sea level budgets is of key interest for understanding the underlying processes and aid in assessing future impacts of sea level rise. Furthermore, steric sea level change is related to the Earth’s Energy Imbalance and thus a key indicator of global warming.

The global fingerprint inversion method (Rietbroek et al., 2016) allows to combine GRACE(-FO) gravity measurements and along-track satellite altimetry observations in order to jointly estimate the individual mass and steric changes in a consistent manner. We use an extended fingerprint approach which allows further separation of the ocean mass variations into contributions from the melting of land glaciers and the Greenland and Antarctic ice-sheets as well as terrestrial hydrology effects and changes of the internal mass transport within the ocean. Furthermore, the updated inversion presented here, aims at splitting the steric sea level change into contributions of the upper 700m and the deeper ocean.

Here, we present the inversion results of a closed global sea level budget (within 0.1 mm/yr) during the GRACE era (2002-04 till 2015-12) attributing 1.68 mm/yr and 1.40 mm/yr to ocean mass and steric changes, respectively. Compared to state-of-the art studies the steric contribution is found to be in line while the mass estimates are slightly lower. We provide budgets for major ocean basins and compare our results to individually processed GRACE, altimetry and ocean re-analysis datasets as well as published estimates. Furthermore, we will show preliminary results when extending the inversion to incorporate additional GRACE-FO data. Finally, we extent our investigations to regional sea level budgets for selected regions of interest, such as the Bay of Bengal or the North Sea, which are dominated by completely different sea level components.

How to cite: Uebbing, B., Rietbroek, R., and Kusche, J.: Investigating global and regional sea level budgets by combining GRACE(-FO) and altimetry data in a joint fingerprint inversion, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2190, https://doi.org/10.5194/egusphere-egu22-2190, 2022.

Understanding the drivers of present-day sea-level change is vital for improving sea-level projections and for adaptation and mitigation plans against sea-level rise. Sea-level budget (SLB) studies focus on attributing the observed sea-level change to its different drivers (steric and barystatic changes). While the global mean SLB is closed, explaining the drivers of sea-level change on a finer spatial scale leads to large discrepancies. Recent studies have shown that closing the regional budget on a regular 1x1˚ grid is not possible due to limitations of the observations itself, but also due to the spatial patterns and variability of the underlying processes. Consequently, the regional budget has been mainly analyzed on a basin-wide scale.

 In this study we use Self-Organizing Maps (SOM), an unsupervised learning neural network, to extract regions of coherent sea-level variability based on 27 years of satellite altimetry data. The SOM clusters have a higher level of spatial detail compared to entire ocean basins, while being large enough to allow for a consistent sea-level budget analysis. The clusters also show how sea-level variability is interconnected among different ocean regions (for example, due to large-scale climate patterns). We perform the clustering analysis on the Atlantic and Indo-Pacific Oceans separately, obtaining a total of 18 clusters. Preliminary results show that we can close the sea-level budget from 1993-2017 in 67% of the clusters. The regions with discrepancies highlight important regional processes that are affecting sea-level change and have not thus far been included in the sea-level budget. In this way, using neural networks provides new insight into regional sea-level variability and its drivers.

How to cite: Machado Lima de Camargo, C., Marcos, M., Hernandez-Carrasco, I., Hermans, T. H. J., Riva, R. E. M., and Slangen, A. B. A.: Regionalizing the Sea-level Budget Using a Neural Network Approach, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3512, https://doi.org/10.5194/egusphere-egu22-3512, 2022.

One of the less well-known contributions to global sea level change is the net mass loss or gain of non-cryospheric land water storage, here abbreviated as hydrology-driven global mean sea level rise (HDGMSL). HDGMSL is due to natural variability in the climate system and direct and indirect anthropogenic processes, such as reservoir building, deforestation and land use change, land glacier mass imbalance,  groundwater depletion, and changes in the atmosphere-ocean water fluxes. It has a large inter-annual variability, as  otherwise only observed in the thermo-steric contribution to sea level, and the sign of its net rate over the last decades is still debated.

Here, we revisit estimates of HDGMSL from GRACE and from global hydrological models. We scrutinize the robustness of estimates in the presence of climate variability within the limited GRACE time-frame, in particular large ENSO modes. To this end we make use of an ensemble of three GRACE solutions and a 32-member ensemble of the WGHM hydrological model where various parameters were realistically perturbed. Moreover we consider two different 40-year reconstructions of terrestrial water storage that were trained on GRACE data, two methods of mode decomposition, and we employ different trend estimators including a state-space parameterization. We conclude that HDGMSL was positive in the GRACE time frame with different estimators pointing to rates between -0.01 and 0.30 mm/a, which is probably not representative for a 40-year span. In addition, all conventional error estimates are found to be over-optimistic.

How to cite: Kusche, J., Mielke, C., Engels, O., Fupeng, L., and Uebbing, B.: How robust are estimates of hydrology–driven global sea level change based on modelling and GRACE data?, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4091, https://doi.org/10.5194/egusphere-egu22-4091, 2022.

In order to carry out a proper coastal management it is compulsory to have oceanographic databases that accurately characterize the spatiotemporal variability of sea level along the coast. A first source of sea level observations are tide gauges, which cover different time periods, some of them dating back to the 17th century. Whereas tide gauges generally provide very accurate measurements, their main limitation is that they are point-wise measurements with a heterogeneous spatial distribution and temporal coverage. Therefore, it is difficult to represent the complexity of sea level variability at the coast directly from tide gauge observations. Since 1992, sea level measurements provided by satellite altimetry are also available. This technique has a quasi-global coverage, and by minimising all sources of error affecting the measurements, an accuracy close to 1 cm can be achieved. However, altimetric products have a limited spatial and temporal resolution due to the separation between adjacent satellite ground tracks and to the revisiting time of the satellites. Most important, the accuracy of altimetry observations decreases very rapidly near the coast; despite the advances reached in recent years, standard altimetric data are only available from 5-10 km offshore.

As an alternative to coastal altimetric products, in this work we develop a new methodology to reconstruct coastal sea level from a number of tide gauge observations, which in our case is applied to the western basin of the Mediterranean sea. The reconstruction covers all coastal regions and has the spatial and temporal resolution required to characterise coastal processes. The sea level reconstruction is based on a multiscale optimal interpolation where the spatial correlations between tide gauges and all the coastal points has to be determined prior to the interpolation. In our case, these correlations are computed from the outputs of a high-resolution numerical model. As for observations, for the monthly reconstruction we use PSMSL tide gauge records, which cover the period from 1884 to 2015. For the daily reconstruction we use the series of the GESLA-2 data set, which cover from 1980 to 2015.

A cross-validation test developed to validate the skills of the method shows that our reconstruction clearly outperforms altimetric and modelling products at different time scales, and therefore represents a valuable contribution to the attempts of recovering coastal sea level. Thus, the obtained reconstruction has been used to complement the characterization of open sea level variability in the western Mediterranean previously done by other authors, allowing us to estimate coastal sea level trends, and to examine the correlation between Western Mediterranean coastal sea level and the main North Atlantic climate indices. The limitations and applicability of the method to other regions will also be discussed in the presentation.

How to cite: Ramos Alcántara, J., Gomis Bosch, D., and Jordà Sánchez, G.: Mediterranean coastal sea level reconstruction based on tide gauge observations, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5203, https://doi.org/10.5194/egusphere-egu22-5203, 2022.

The relationship between satellite-derived absolute sea level change rates, tide gauge (TG) observations of relative sea level change and global positioning system (GPS) measurements of vertical land motion (VLM) at local scale has been investigated in previous studies [eg. Vignudelli et al., 2018]. The paucity of collocated TG-GPS data and the lack of a well-established mathematical frame in which simultaneous and optimal solutions can be derived, have emphasized the difficulty of deriving spatially-consistent information on the sea level rates. Other studies have claimed the possibility to set locally isolated information into a coherent regional framework using a constrained linear inverse problem approach [Kuo et al., 2004; Wöppelmann and Marcos, 2012].

The approach cited in the above papers has been recently improved in De Biasio et al. [2020]. A step in advance is now to develop an effective synergistic use of global positioning system (GPS) data, tide gauge measurements and satellite altimetry observations. In this study GPS data are used as a real source of information on the relative Vertical Land Motion (VLM) between pairs of tide gauges, and not as mere term of comparison of the results obtained by differencing relative and absolute sea level observations time series.

Long, consistent and collocated tide gauge and GPS observations time series are extracted for a handful of suitable coastal locations, and used in the original formulation of the constrained linear inverse problem, together with satellite altimetry data. Some experiments are conducted without GPS observations (traditional setup), and with GPS observations (the new proposed approach) Results are compared in order to assess the impact of GPS observations directly into the formulation of the constrained linear inverse problem.

The satellite altimetry data-set used in this study is that offered by the European Copernicus Climate Change Service (C3S) through its Climate Data Store archive. It covers the global ocean since 1993 to present, with spatial resolution of 0.25 x 0.25 degrees. This data set is constantly updated and relies only on a couple of simultaneous altimetry missions at a time to provide stable long-term variability estimates of sea level. Tide gauge data are extracted from the Permanent Service for Mean Sea Level archive and from other local sea level monitoring services. GPS vertical position time series and/or VLM rates are taken from the Nevada Geodetic Laboratory and other public GPS repositories.

REFERENCES

Vignudelli, S.; De Biasio, F.; Scozzari, A.; Zecchetto, S.; Papa, A. In Proceedings of the International Association of Geodesy Symposia; Mertikas, S.P., Pail, R., Eds.; Springer: Cham, Switzerland, 2020; Volume 150, pp. 65–74. DOI: 10.1007/1345_2018_51

Kuo, C.Y.; Shum, C.K.; Braun, A.; Mitrovica, J.X. Geophys. Res. Lett. 2004, 31. DOI: 10.1029/2003GL019106

Wöppelmann, G.; Marcos, M. J. Geophys. Res. Ocean. 2012, 117. DOI: 10.1029/2011JC007469

De Biasio, F.; Baldin, G.; Vignudelli, S. J. Mar. Sci. Eng. 2020, 8, 949. DOI: 10.3390/jmse8110949

How to cite: De Biasio, F. and Vignudelli, S.: Synergistic use of tide gauges, satellite altimetry and GPS data for sea level studies, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8092, https://doi.org/10.5194/egusphere-egu22-8092, 2022.

Global mean sea-level rise (SLR) has accelerated since 1900 from less than 2 mm/year during most of the century to more than 3 mm/year since 1993. At the regional scale, detection of an acceleration in SLR is difficult, because the long-term sea-level signal is obscured by large inter-annual variations with multi-year trends that are easily one order of magnitude larger than global mean values. Here, we developed a time series approach to determine whether regional SLR is accelerating based on tide gauge data. We applied the approach to eight 100-year records in the southern North Sea and detected, for the first time, a common breakpoint in the early 1990s. The mean SLR rate at the eight stations increases from 1.7±0.3 mm/year before the breakpoint to 2.7±0.4 mm/year after the breakpoint (95% confidence interval), which is unprecedented in the regional instrumental record. These findings are robust provided that the record starts before 1970 and ends after 2015.

How to cite: Riva, R., Steffelbauer, D., Timmermans, J., Kwakkel, J., and Bakker, M.: Evidence of acceleration in sea-level rise for the North Sea, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2577, https://doi.org/10.5194/egusphere-egu22-2577, 2022.

How to cite: Keizer, I., Le Bars, D., Jüling, A., Drijfhout, S., and van de Wal, R.: Long-Term Wind Influence on Sea Level Along the Dutch Coast , EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8657, https://doi.org/10.5194/egusphere-egu22-8657, 2022.

The 2021 Intergovernmental Panel on Climate Change report highlighted how rates of sea level rise are the fastest in at least the last 3000 years. As a result, it is important to understand historical sea level trends at a global and local level in order to comprehend the drivers of sea level change and the potential impacts. The influence of different sea level drivers, for example thermal expansion, ocean dynamics and glacial – isostatic adjustment (GIA), has changed throughout time and space. Therefore, a useful statistical model requires both flexibility in time and space and have the capability to examine these separate drivers, whilst taking account of uncertainty.

The aim of our project is to develop statistical models to examine historic sea level changes for North America's and Ireland's Atlantic Coast. For our models, we utilise sea-level proxy data and tide gauge data which provide relative sea level estimates with uncertainty. The statistical approach employed is that of extensions of Generalised Additive Models (GAMs), which allow separate components of sea level to be modelled individually and efficiently and for smooth rates of change and accelerations to be calculated.

The model is built in a Bayesian framework which allows for external prior information to constrain the evolution of sea level change over space and time. The proxy data is collected from salt-marsh sediment cores and dated using biological and geochemical sea level indicators. Additional tide gauge data is taken from the Permanent Service for Mean Sea Level online. Uncertainty in dating is extremely important when using proxy records and is accounted for using the Noisy Input uncertainty method (McHutchon and Rasmussen 2011).

By combining statistical models, proxy and tidal gauge data, our results have shown that current sea level along North America’s east coast is the highest it has been in at least the last 15 centuries. The GAMs have the capability of examining the different drivers of relative sea level change such as GIA, local factors and eustatic influences. Our models have demonstrated that GIA was the main driver of relative sea level change along North America’s Atlantic coast, until the 20^th century when a sharp rise in rates of sea level change can be seen.

This work is part of the larger nationally funded Irish A4 project (Aigéin, Aeráid, agus Athrú Atlantaigh — Oceans, Climate, and Atlantic Change), funded by the Marine Institute. It aims to examine ocean and climate changes in the Atlantic Ocean. The project targets three aspects of the Atlantic: its changing ocean dynamics; sea level changes; and Irish decadal climate predictions. In the future, we will apply this modelling technique to produce a long term historical record for relative sea level change in Ireland.

How to cite: Upton, M., Parnell, A., Kemp, A., McCarthy, G., and Cahill, N.: Noisy Input Generalised Additive Model for Relative Sea Level along the East Coast of North America, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8674, https://doi.org/10.5194/egusphere-egu22-8674, 2022.

This paper describes a major update to the quasi-global, higher-frequency sea-level dataset known as GESLA (Global Extreme Sea Level Analysis). Versions 1 (released 2009) and 2 (released 2016) of the dataset have been used in many published studies, across a wide range of oceanographic and coastal engineering-related investigations concerned with evaluating tides, storm surges, extreme sea levels and other related processes. The third version of the dataset (released 2021), presented here, contains twice the number of years of data (91,021), and nearly four times the number of records (5,119), compared to version 2. The dataset consists of records obtained from multiple sources around the world. This paper describes the assembly of the dataset, its processing and its format, and outlines potential future improvements. The dataset is available from https://www.gesla.org.

How to cite: Haigh, I. D., Marcos, M., Talke, S. A., Woodworth, P. L., Hunter, J. R., Hague, B. S., Arns, A., Bradshaw, E., and Thompson, P.: GESLA Version 3: A major update to the global higher-frequency sea-level dataset, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9778, https://doi.org/10.5194/egusphere-egu22-9778, 2022.

Rising seas are a threat for human and natural systems along coastlines. The relation between global warming and sea-level rise is established, but impacts due to historical sea-level rise are not well quantified on a global scale. To foster the attribution of observed coastal impacts to sea-level rise, we here present HLT, a sea-level forcing dataset encompassing factual and counterfactual sea-level evolution along global coastlines from 1979 to 2015. HLT combines observation-based long-term changes with reanalysis-based hourly water level variation. Comparison to tide gauge records shows improved performance of HLT, mainly due to the inclusion of density-driven sea-level change. We produce a counterfactual by removing the trend in relative sea level since 1900. The detrending preserves the timing of historical extreme sea-level events. Hence, the data can be used in event-based impact attribution to sea-level rise with tuples of impact simulations driven with the factual and counterfactual dataset. The dataset is made available openly through the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP).

How to cite: Mengel, M., Treu, S., Muis, S., Dangendorf, S., Wahl, T., Heinicke, S., and Frieler, K.: Hourly sea-level change with long-term trends for impact attribution: the HLT Dataset, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11672, https://doi.org/10.5194/egusphere-egu22-11672, 2022.

Extreme sea levels can lead to floods that cause significant damage to coastal infrastructure and put people's lives in danger. These floods are a result of physical processes occurring at various time and space scales, including sub-hourly scales. To estimate the contribution of sub-hourly sea level oscillations to extreme sea levels, raw sea level data from about 300 tide gauge stations along the European coasts, with a sampling resolution of less than 20 minutes, were collected. The data were obtained from: (1) the IOC-SLSMF website (290 stations); (2) National agencies (Portugal, Finland, Croatia –24 stations). Portions of the raw dataset had various data quality issues (i.e., spikes, shifts, drifts) hence quality control procedure was required. Out of range values, values with a 50 cm difference from one neighbouring value or a 30 cm difference from both neighbouring values, were automatically removed. The automatic spike detection procedure was carried out by removing values that differed by three standard deviations from a spline fitted with the least squares method. Following the automatic quality control, all remaining data were visually examined and spurious data were removed manually.

The resulting data set contains sea level data from 2007. to 2021., with an average record length of approximately 7 years, however the length varies from a few months at some stations to 13 years at others. Tide gauges with longer records (>10 years) are based in the Baltic region, France and Spain, whereas the ones with shorter records (<3 years) are mostly based in the Eastern Mediterranean. The Western Mediterranean and western Europe have a high station coverage with records of various lengths. Tide gauges mostly provide data with a one-minute sampling frequency, however, some of them still record on a multi-minute scale (i.e., United Kingdom with 15 minutes and Norway and the Netherlands with 10 minutes sampling frequency).

Preliminary statistical analyses were done, resulting with spatial and temporal distribution of contribution of high-frequency sea level oscillations to total sea level extremes along the European coasts.

How to cite: Balić, M., Šepić, J., Ćatipović, L., Čupić, S., Kim, J., Međugorac, I., Omira, R., Pellikka, H., Ruić, K., Vilibić, I., and Zemunik, P.: Sub-hourly sea level quality-controlled dataset to quantify extreme sea levels along the European coasts, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12063, https://doi.org/10.5194/egusphere-egu22-12063, 2022.

The Black Sea is an almost enclosed basin interacted with the Mediterranean Sea through the Bosporus. It has a large catchment area receiving freshwater from the second longest river in Europe, the Danube, and other rivers spread over Europe and Asia. The total riverine discharge is 350 km³/year where the Danube contributes about 65% of the total discharge. Although evaporation rates (280 km³/year) exceed precipitation rates (200 km³/year), large riverine discharge makes the Black Sea an estuarine type basin.  The main feature of the Black Sea is a basin-wide cyclonic circulation, namely Rim Current. The cyclonic circulation causes a lower sea level in the inner part of the basin and a higher sea level in the shelf region. The freshwater budget and thermal expansion of the water are other factors affecting sea level of the Black Sea.  The North Atlantic Oscillation (NAO) could also influence sea level through changes in atmospheric pressure and the above-mentioned factors.  

In this study, firstly we investigated long term trends in sea level of the Black Sea on the basis of the tide gauge measurements, satellite altimetry, and gravity measurements from the Gravity Recovery and Climate Experiment (GRACE). Then, we assessed role of the wind curl, freshwater budget, and NAO on sea level variations through temporal and spatial data analysis. The tide gauge measurements suggest a positive sea level trend of about 1.05 – 2.37 mm/years, for a time period >50 years. Basin mean sea level derived from altimeter and GRACE (years between 2003-2019), does not exhibit a statistically significant trend (p<0.05) which might result from the shift towards a positive NAO condition in the last 30-years. We found that sea level variations both in the coastal and inner part of the basin are significantly correlated (p<0.05) with Danube discharge but these correlations are smaller in the inner part. The agreement between interannual variations of Danube discharge and the NAO index suggests that sea level variations are also associated with NAO index. An Empirical Orthogonal Function (EOF) analysis with associated time series (Principal Components, PC) is applied to the gridded altimeter data to capture space and time features of sea level variability. The first mode of the EOF explained about %81.9 of the total variability and showed the same sign over the basin indicating an in-phase oscillation of the whole Black Sea. The PC1 shows interannual variations in accordance with freshwater budget (r=0.76, p<0.05). The second mode of the EOF accounts for %5.7 of the total variability, has opposite signs in coastal and inner parts, the oscillation implied by this mode could be related to the Rim Current intensity governed by wind curl.

How to cite: Saçu, Ş. and Şen, O.: Long-term trends and variations in sea level of the Black Sea, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-13328, https://doi.org/10.5194/egusphere-egu22-13328, 2022.

In this study, an analysis of the observed Adriatic mean sea level time series has been carried out in order to determine the primary causes of the changes documented during the last 50 years.  Monthly sea level data were downloaded from the Permanent Service for Mean Sea Level for seven stations located along the northern and eastern Adriatic coast: Venice, Trieste, Rovinj, Bakar, Zadar, Split and Dubrovnik. Significant positive sea level trend, related to climate change, was detected at the majority of the stations. Further on, using Rodionov’s regime shift index algorithm, several regime shifts were detected. The first pronounced regime shift occurred in 1989 resulting with mean sea level lower than usual for an average of 4.37 cm; the second regime shift occurred in 1996 when mean sea level increased for an average of 2.07 cm; and the third regime shift, which is still on-going, started in 2009 when mean sea level abruptly increased to 5.3 cm above average.  A relationship between North Atlantic Oscillation (NAO) and sea level data has been explored, using both monthly and yearly data. High and significant correlation between the two was established for all data, and in particular for the winter season (December, January, February, March). All climate shifts were related to pronounced changes of NAO. The negative shift starting in 1989 was related to the positive phase of NAO, i.e. to weaker cyclonic activity over the Mediterranean and the Adriatic Sea. Oppositely, the two latter positive regime shifts were related to significant decrease and negative phases of NAO, with NAO reaching the most negative values of the entire observation period during the shift starting in 2009. Negative phase of NAO corresponds to stronger cyclonic activity over the Mediterranean and the Adriatic Sea. In conclusion, documented rise of the Adriatic sea level during the last 50 years, and in particular accelerated rise during the last 20 years represent a combination of mean sea level rise due to climate change and due to atmospherically induced shift of climate regimes.

How to cite: Pupić Vurilj, M., Šepić, J., and Pilić, P.: Decadal changes of the Adriatic sea level – exploring the combined effect of sea level rise and climate regime’s shift , EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7733, https://doi.org/10.5194/egusphere-egu22-7733, 2022.

Estimating the magnitude of future sea level rise is among the primary goals of current climate research. Sea level projections contain inherent irreducible uncertainty, which is due to internal climate variability (ICV). This uncertainty is commonly estimated from a spread of sea level projections obtained from Global Climate Models (GCM) under the same forcing but with slightly different initial conditions. Here we analyze the ICV contribution to the sea level variations (1) across the Large Ensembles (LE) of Community Earth System Model (CESM) obtained under different warming scenarios and (2) from an alternative approach based on the power-law statistics theory. The magnitude of the sea level response to ICV is also evaluated by comparison with actual tide gauge data. We show that certain coastal regions of the globe are more sensitive to ICV than others, both in observations and in the GCM results. We identify regions where the sea level change will become significant beyond the ICV, providing useful climate change adaptation guidance.

How to cite: Becker, M., Karpytchev, M., and Hu, A.: Understanding the role of internal climate variability in future sea level trends, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11476, https://doi.org/10.5194/egusphere-egu22-11476, 2022.

Vertical land motion (VLM) is a major contributor to relative sea level change (RSLC). Hence, understanding and estimating VLM is critical for the investigation of contemporary and projected coastal RSLC and the allocation of its uncertainties. However, there are several challenges involved in the determination of the linear component of VLM. Firstly, the sparse and inhomogeneous distribution of point-wise VLM observations hinder the direct analysis of VLM continuously in space along the coastline. Secondly, the commonly applied working-hypothesis that VLM can be generally assumed as ‘linear’, is not entirely valid for regions, which are affected by nonlinear processes such as earthquakes, surface mass loading changes or other phenomena. Thus, in order to overcome the limitations of data-availability and to account for time-variable VLM, we develop a new approach to estimate continuous time- and space-resolving (3D) VLM over the period 1995-2020.

We apply a Bayesian Principal Component Analysis to a global network of quality controlled VLM observations (GNSS data and differences of satellite altimetry and tide gauge observations) to extract common modes of variability and to cope with the incomplete VLM data. The estimated modes represent a superposition of large scale VLM fingerprints. These include linear motion signatures, e.g., associated with the Glacial Isostatic Adjustment (GIA), as well as regional patterns of coherent responses to earthquakes or terrestrial water storage changes, which exhibit inter-annual to decadal variability. To generate the 3D VLM reconstruction, the VLM fingerprints are interpolated in space with a Bayesian transdimensional regression, which automatically infers the spatial resolution based on the distribution of the data.

Our approach not only provides an essential observation-based alternative to previously employed VLM estimates from GIA models or interpolated VLM maps, but also allows to directly attribute VLM trend uncertainties to the temporal variability estimated over the period of observation. We combine the VLM dataset with century-long tide gauge RSLC observations to demonstrate the limitations of extrapolating nonlinear VLM back in time and to identify regional differences (in the order of mm/year) of contemporary absolute sea level (ASL) change (1900-2015) w.r.t. a recent sea level reconstruction, which employs a GIA-VLM signature only. Using the present-day VLM estimates, we disentangle the contributions of VLM and projected ASL change (from CMIP6 models) and uncertainties to RSLC (2020-2150). The regional RSLC error budget analysis enables the identification of regions where robust assessments of future RSLC are feasible and where VLM uncertainties dominate the projected ASL uncertainties, while explaining up to 75% of the combined uncertainties. Besides these applications, the VLM estimate represents a vital source of information for various sea level studies focused on the analysis of tide gauge or satellite altimetry observations in coastal areas.

How to cite: Oelsmann, J., Marcos, M., Passaro, M., Sánchez, L., Dettmering, D., and Seitz, F.: The impact of continuous space and time-resolving vertical land motion on relative sea level change, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5281, https://doi.org/10.5194/egusphere-egu22-5281, 2022.

Mangroves have many benefits, both for humans and for the surrounding ecosystem. One of the most benefits from mangroves is that mangroves have coastal blue carbon reserves up to five times greater than the total carbon storage of temperate, taiga, and tropical forests. But recently, mangroves have decreased in extent by 20-35% due to both anthropogenic and naturogenic factors. One of the naturogenic factors that impact mangroves is sea-level rise. Mangroves cannot survive if sediment accumulation cannot keep pace with sea-level rise. This can result in mangrove death or zonal shifts in plant communities.

The decline in mangrove areas has resulted in increases in carbon emissions. This increase in carbon costs $US6-24 billion in economic damage annually. Indonesia experienced the highest increase in carbon dioxide emissions in the world in 1990-2010. Whereas in the Paris agreement, 2015, countries in the world including Indonesia have committed to reducing emissions by 29-41% by 2030. Therefore, rehabilitation and restoration of mangroves need to be undertaken, as well as identification of those mangroves most under threat.

The aim of this study is to model future sea-level rise and the impact of its exposure on land suitability for mangrove rehabilitation and restoration in Indonesia. This study uses the integration of remote sensing, statistical, and future climate model data combined with GIS methods to produce a sea-level rise model. This study also uses several scenarios both climate and temporal to predict sea-level rise.

The results of this study indicate that there are several areas that have high exposure caused by sea-level rise. This is exacerbated by low rates of sedimentation or land subsidence in some areas. In contrast, several other areas experienced high rates of accretion and thus are at less risk. Changes in rates of inundation caused by sea-level rise have caused some areas suitable for planting mangroves to become unsuitable. Therefore, if planting is carried out in the area now, it is very likely that the mangrove will be submerged by excessive tidal inundation and any rehabilitation and restoration carried out will fail.

This study is expected to be taken into consideration in driving new policy based on the results of the model. This study can also be used as a guide to consider which areas are suitable for mangrove rehabilitation and restoration without the threat of a sea-level rise in the future.

How to cite: Syahid, L. N., Ward, R. D., Sakti, A. D., Rosleine, D., Wikantika, K., and Windupranata, W.: Prediction of future sea-level rise in land suitability for mangrove rehabilitation and restoration in Indonesia, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9058, https://doi.org/10.5194/egusphere-egu22-9058, 2022.

In the coming decades, regions across the globe will be faced with increases in coastal flooding due to sea-level rise and changes in climate extremes. In a collective effort, we have produced new extreme sea level projections derived from an ensemble of high-resolution climate models. Our approach is based on the Global Tide and Surge Model forced with model outputs from the HighResMIP experiments. The HighResMIP models have a much higher spatial resolution than the previous generation of climate models, and can better resolve storms, including tropical cyclones. The dataset has global coverage and spans the period 1950-2050. The dataset provides: 1) timeseries of storm surges, astronomical tides, and total still water levels; and 2) water level statistics for different time slices, including percentiles and return periods.

In this contribution we focus on storm surges and have a first look at model performance for present-day climate conditions and at projected changes. Comparison of the 1 in 10-year surge levels against the ERA5 reanalysis reveals a large spatial bias for some of the HighResMIP models, highlighting the need for multi-model ensembles and bias correction. Comparison of the 1 in 10-year surge levels between the 1951-1980 and 2021-2050 period, shows that some regions, such as Northwest Europe, Alaska, China, and Patagonia, may be faced with an increase in storm surges (>0.1 m), while other regions, such as the Mediterranean and South Australia may see a decrease in storm surges. Overall, the projected changes are characterized by large intermodel variability due the uncertainties that arise from the climate models, internal variability, and extreme value statistics. Future research should aim to better constrain the uncertainties, which can be achieved by a more in-depth exploration of the changes in the meteorological conditions, enlarging the model ensemble, and the implementation of bias correction methods.

The full datasets will soon become openly available at the C3S Climate Data Store and can be used to inform climate impact assessments.

How to cite: Muis, S., Aerts, J. C. J. H., A. Á. Antolínez, J., Le Bars, D., Dullaart, J. C., Minh Dong, T., Erikson, L., Haarsma, R., Irazoqui Apecechea, M., O'Neill, A., Ranasinghe, R., Roberts, M., Yan, K., Verlaan, M., and Ward, P. J.: High-resolution climate ensemble reveals low confidence in projected changes in storm surges for the mid-century, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4414, https://doi.org/10.5194/egusphere-egu22-4414, 2022.

Extreme sea levels (ESLs) are a major threat for coastal and low-lying regions. Climate change induced sea level (SL) rise will increase the frequency of ESLs. Projections of ESLs are thus of great interest for coastal risk assessment and decision-making. SL projections are typically produced using global climate models (GCMs). However, GCMs do not explicitly resolve key processes driving ESL changes at the coast (e.g. waves, tides). In this study, a regional model IBI-CCS is set up to refine SL projections of a GCM over the north-eastern Atlantic region bordering western Europe using dynamical downscaling. For a more complete representation of processes driving coastal ESL changes, tides and atmospheric surface pressure forcing are explicitly resolved in IBI-CCS in addition to the ocean general circulation. Furthermore, to include the wave setup contribution to ESLs, a dynamical downscaling of a wave global model is performed over the same north-eastern Atlantic domain using the currents and sea level outputs of the IBI-CCS regional ocean model. All the regional simulations are performed over the 1950 to 2100 period for two climate change scenarios (SSP1-2.6 and SSP5-8.5).

Comparisons to reanalyses and observations over the 1993-2014 indicate that ESLs are satisfactorily represented in the regional simulations. In a second phase, the projected changes in ESLs are analyzed, particularly in term of changes in return levels and return periods. The coupling effects between the key processes driving ESL changes at the coast are investigated. We notably assess the influence of the wave setup contribution to ESLs and to projected changes in ESLs and to their return periods. In addition, the impact of accounting for hourly sea level changes in the wave regional model on ESLs and projections of ESLs is estimated.

How to cite: Chaigneau, A., Melet, A., Law-Chune, S., Voldoire, A., Reffray, G., and Aouf, L.: High-resolution projections of extreme sea level changes along the coasts of western Europe, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5156, https://doi.org/10.5194/egusphere-egu22-5156, 2022.

The existence of reliable coastal sea-level projections is essential for identifying necessary adaptation and mitigation strategies of policymakers and coastal communities over the following decades. However, today only a few ocean components of climate projections can resolve the small-scale processes that affect the Dynamic Sea Level (DSL) change in the open ocean and in coastal areas, predominantly in the eddy rich regions such as Antarctic Circumpolar Current (ACC) and the western boundary currents. Therefore, we investigate the dependence of regional sea-level projections on ocean model resolution using the recent Max Planck Institute Earth System Model (MPI-ESM) for the shared socioeconomic pathway 585 (SSP585, fossil-fuel development). By comparing the climate change scenario from 2080 to 2099 to a historical simulation from 1995 to 2014, our results indicate that the models, from eddy-rich (ER), eddy-permitting (HR) to coarser resolution (LR), successfully produce the previously identified global DSL patterns. However, the magnitude of the DSL increase in the North Atlantic subpolar gyre and the decrease in the subtropical gyre is significantly larger in the ER ocean in contrast to HR and LR; the same holds for the magnitude of the opposite dipole pattern in the North Pacific. In the southern ocean, the DSL increases north of ACC but decreases further to the south, projecting much smaller changes in the ER. We note that the meridional shift of ACC, associated with sea-level change, is smaller in ER than in HR and LR, indicating an accelerated ACC compared to HR simulation, which shows no acceleration at the end of the 21st century.

How to cite: Wickramage, C., Köhl, A., Stammer, D., and Jungclauss, J.: Sensitivity of SSP585 sea-level projections to ocean model resolution in the MPI-ESM climate model, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8462, https://doi.org/10.5194/egusphere-egu22-8462, 2022.

Wind patterns projected for the region, together with sea level rise and land rise, call into question our current understanding of extreme storm surges in the Danish coastal area. The Danish Meteorological Institute (DMI) will research changes in the extreme statistics of sea level in the twenty-first century through the 'Danish Climate Atlas,' a new national climate service initiative. The study will make use of multi-scenarios, multi-models and multi-parameters approach to focus on the uncertainty of the projected change in extreme statistics of sea level.  Historical sea level records suggest that the relative sea level (RSL) along the Danish North Sea coast south of Skagerrak has been increasing with the global mean sea level (GMSL) rise. However, RSL has been absent in the central Skagerrak-Kattegat Seas, owing to the Fennoscandian post-glacial land-uplift offsetting the GMSL rise. According to the recent IPCC Special Report on the Ocean and Cryosphere in a Changing Climate (SROCC), due to Antarctic ice sheet dynamics, GMSL would grow more than previously estimated in the IPCC Fifth Assessment Report (AR5) by the end of the twenty-first century under RCP8.5. We regionalized the SROCC sea level forecasts for the "Danish Climate Atlas" dataset. Our findings indicate that sea level projections under RCP8.5 result in a > 40 cm RSL rise in the Skagerrak-Kattegat Seas by the end of the twenty-first century, which may necessitate a new adaptation strategy in this region. Under the RCP8.5 scenario, the rate of mean sea level rise will exceed the rate of land rise earlier than previously estimated by AR5. We emphasize, in particular, the impact of these new predictions on future severe sea levels in this region. Our findings suggest that this more current GMSL prediction should be factored into coastal risk assessments in the Skagerrak-Kattegat Seas in this century.

How to cite: Su, J., Andrée, E., Nielsen, J. W., Olsen, S. M., and Madsen, K. S.: Danish Climate Atlas view on sea level change in future, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11156, https://doi.org/10.5194/egusphere-egu22-11156, 2022.

Small island developing states are particularly at risk from extreme water levels and coastal erosion. Policy makers require information to support decision making on how to improve resilience and adapt to future changes. Here we present a web portal designed to display different sea level projections across the Caribbean Sea, developed as part of our contribution to the UK Government’s Commonwealth Marine Economies (CME) programme and the UK Natural Environment Research Council’s ACCORD programme.

The portal has been designed using free and open-source software, and is self-contained, allowing it to be deployed on local partner websites with minimal effort. The responsive design allows the portal to work as well on as it does on PCs.

Currently the portal displays projected sea level for over 50 locations across the Caribbean, along with sea level data available at the site, but extra sites can be added easily. Quality controlled data has been used where possible; where this is not available, we have used automated software developed earlier in the CME programme to perform basic quality control.

Similarly, the portal provides projections from four sea level scenarios based on earlier National Oceanography Centre work, but other projections can be added by updating configuration files.

The portal can be accessed at https://psmsl.org/accord/projections.html

How to cite: Matthews, A. and Jevrejeva, S.: Sea level projections portal for communicating impacts to policymakers, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3934, https://doi.org/10.5194/egusphere-egu22-3934, 2022.

Abstract

In recent decades, the sea level has risen notably compared to the most recent millennia. This poses serious threats to environment and human population over the next century especially in coastal zones. Every region has climatic and non-climatic drivers of sea level rise which needs to be considered when adaptation and mitigation policies are implemented. We analyzed the coastal consequences of sea level rise along the Caribbean and Pacific coastlines of Colombia. Sea level rise projections published in August 2021 by the Intergovernmental Panel on Climate Change in the 6th assessment report were used in this study (IPCC, 2021). Five Shared Socioeconomic Pathways for the 21^st century (SSP1-1.9, SSP1-2.6, SSP2-4.5. SSP3-7.0, SSP5-8.5) were examined. Our results indicate a sea level rise of 1.04 m in the worst-case scenario (SSP5-8.5) which could cause land loss in an area of 2840.64 km². The area at risk will impact 12 departments or 86 municipalities with different social, environmental, economic, and cultural conditions that need to be considered when implementing mitigation policies. Our results illustrate how the projected sea level changes influence a variety of parameters such as area at the potential risk of inundation, land use of the affected area and general socio-economic impacts along the Caribbean and Pacific coastlines of Colombia.

Reference

IPCC (2021), Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. Cambridge University Press. In Press.

How to cite: Nevermann, H., Becerra Gomez, J. N., Fröhle, P., and Shokri, N.: Sea level rise along the coastline of Colombia: A vulnerability assessment, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4228, https://doi.org/10.5194/egusphere-egu22-4228, 2022.