Coral microatolls are precise proxies of relative sea-level (RSL) change in low-latitude coastal regions. These coral colonies live in the intertidal zone where partial mortality due to low-water events produces a characteristic planform ring structure. Since ring elevations reflect changes in local RSL during a coral’s lifetime, we can use the surface profiles of microatolls to quantify short-term (decadal) rates of RSL change. Therefore, Holocene fossil microatolls can produce sea-level index points (SLIPs) with relatively high spatial and temporal resolution. In this study, we present preliminary sea-level reconstructions from Pulau Biola (Violin Island), Singapore, based upon several Porites sp. and Diploastrea heliopora fossil microatolls. We calculated the difference in elevation between the fossils and local living microatolls of the same genus to quantify the magnitude of past water level. We also combined U-Th ages, structure-from-motion photogrammetry and LiDAR 3D models, and survey data to generate a RSL history spanning more than two centuries in the mid Holocene. The highest-elevation fossil microatolls at Pulau Biola are consistent with an overall rise in sea level, from 0.2 to 0.7 m above present, between 7.7 and 7.4 kyr BP. In addition, decimetre-scale sea-level fluctuations during this period are inferred from decreasing and increasing ring elevations within corals. These fluctuations indicate a more complex sea-level history than resolved by other proxies or glacial isostatic adjustment models, and ongoing work aims to reconcile conflicting Holocene sea-level models and datasets in the Singapore region.

How to cite: Quye-Sawyer, J., Yeo, J. Y., Neo, W. L., Aw, Z., Aung, L. T., Tan, N. S., Komori, J., Lin, K., Wang, X., and Meltzner, A. J.: Mid Holocene relative sea-level changes from coral microatolls of Pulau Biola, Singapore , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5010, https://doi.org/10.5194/egusphere-egu24-5010, 2024.

How to cite: Sukumaran, V. and Vishwakarma, B. D.: Comparing altimetry-derived coastal sea level anomaly with tide gauge observations along the global coastline by accounting for shelf-width , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1007, https://doi.org/10.5194/egusphere-egu24-1007, 2024.

Studying how ocean water mass is redistributed can help with a better understanding of the regional sea level change. This study investigates the roles of the different physical processes involved in low-frequency ocean water mass, including the sea level fingerprint and the dynamic ocean mass change, from regional to global scales over the period 2004-2021. Global water mass redistribution data from the GRACE and GRACE-FO satellites were used, as well as surface wind and sea surface temperature data from the ERA5 reanalysis. The sea-level equation is used to simulate the sea level fingerprint, and the maximum covariance analysis is used to extract possible signals of the wind-forcing and temperature-gradient-forcing ocean mass redistribution. The results show that the low-frequency ocean water mass is dominated by the long-term trend and the decadal-like fluctuation. Sea level fingerprint significantly contributes to the open ocean. Compared with temperature gradients, wind forcing plays a more important role in dynamic ocean mass redistribution. The wind-forcing dynamic processes significantly drive the anomalies near the North Indian Ocean, North Atlantic Ocean, South Pacific Ocean, and some marginal seas. After removing the sea level fingerprint and ocean dynamics, some non-negligible noise, located in seismic zones, was also found, suggesting the misestimation of seafloor deformation resulting from earthquakes in the GRACE/GRACE-FO data processing. These findings may improve our understanding of the long-term anomalies in regional and global sea levels.

How to cite: Deng, S., Liu, Y., Zhang, W., and Hu, A.: Attributing low-frequency variations in ocean water mass redistribution during 2002-2020, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20096, https://doi.org/10.5194/egusphere-egu24-20096, 2024.

Future sea-level rise on shallow continental shelves differs in one important aspect from open ocean sea-level rise: the local steric effect, that is the change in the water column height due to changes in sea water density, plays a minor role compared to the much deeper open ocean. Instead, the bulk of oceanic sea-level rise on continental shelves arises from an increase in ocean water mass that is being imported from the open ocean – the so-called shelf mass loading (SML). This redistribution is mainly driven by thermal expansion of water masses below shelf depth and magnifies as the subsurface ocean layers continue to warm.

Few studies have tried to detect SML as the signal is only expected to become dominant over decadal to multidecadal periods given the large natural variability in shallow regions.

Here, we combine hydrographic data from a section crossing the Norwegian shelf, with observations of total sea-level change from altimetry and estimates of mass changes from GRACE gravity missions to estimate the strength of SML over the past decades. We compare the residual of total sea level (from altimetry) and steric height (from hydrography) with GRACE estimates from three different solutions. Over the common period (2002 -2020), both estimates show a consistently higher trend over the shallow shelf area compared to the deep ocean. We estimate the shelf mass contribution in the order of 0.5 – 1.0 mm/yr, depending on the GRACE solution selected.

How to cite: Richter, K., Mangini, F., Bonaduce, A., and Raj, R.: Estimating the long-term sea-level contribution from shelf mass loading on the Norwegian shelf using hydrographic in-situ data, satellite altimetry and GRACE, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19016, https://doi.org/10.5194/egusphere-egu24-19016, 2024.

Dynamical downscaling employing high-resolution ocean models is widely considered as an efficient approach for modelling of regional ocean dynamics and sea-level changes using output of original coarse-resolution global general circulation models (GCMs). In this study, the historical dynamic variability and trends of sea level in the South China Sea (SCS) and the Southeast Asia Seas (SEAS) are investigated using the high-resolution regional ocean model (NEMO). Two hindcast ocean modelling experiments are conducted for the period 1960-2014. One is driven by global reanalysis data (ERA5 and ORAS5) forcings at the lateral and surface boundaries. The other is driven by global modelling oceanic data (EC-EARTH3) at the lateral boundary and by WRF-based downscaled atmospheric fields from the same parent model (EC-Earth3) at the surface boundary. Using the hindcast model runs, variability and trends of low-frequency sea-levels, as well as the driving mechanisms and the related processes are discussed, and the model performance and biases are analysed.

This Research is supported by Singapore’s National Research Foundation and National Environment Agency under the National Sea Level Programme Funding Initiative (Award No. USS-IF-2020-4).

How to cite: Ma, P., Gangadharan, N., and Tkalich, P.: Modelling of Low Frequency Sea Level Variability Over the Maritime Continent: Historical Dynamic Variability and Changes, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2405, https://doi.org/10.5194/egusphere-egu24-2405, 2024.

The application of satellite altimetry allows us to acquire global sea level height data with higher spatial and temporal resolution, enabling a systematic understanding of spatial differences in sea level rise. In our study, we reconstructed the barystatic sea level and steric sea level change during the altimetry era (1993-2022). This involved utilizing mass change data and ocean heat content data from various sources. Notably, we incorporated the latest observation and model-simulation data, ensuring coverage of the entire altimetry era compared with previous reconstructions. Based on altimetry-observed relative sea level change, the global sea level rise rate is 3.38 [3.09 3.68] mm/yr, the global barystatic and steric sea level change is 1.80 [1.45 2.15] mm/my, and 1.02 [0.67 1.37] mm/yr, respectively. Subsequently, we further analyzed the regional characteristics of these sea level rises.

Over the past three decades, sea levels have exhibited a faster rate of increase in the western basins, as well as in the equatorial and mid-latitude region, surpassing the global average. Conversely, sea level rise at higher latitudes has been relatively slower than the global average. In the mid-low latitude regions, the higher rate of sea level rise is primarily dominated by the expansion of ocean water due to its heating. In high-latitude regions, the lower sea level rise rate is primarily attributed to the far-field effects of the melting of land ice. The distribution of halosteric sea level changes is nearly uniform across latitudes. However, in the western Atlantic, a significant counteracting effect against the rise in thermosteric sea level is observed. This is linked to the weakening Atlantic Meridional Overturning Circulation (AMOC).

Furthermore, we selected 8 regions, North Pacific (NP), South China Sea (SCS), Western Tropical Pacific (WTP), Bay of Bengal (BOB), Tropical Indian Ocean (TIO), Southwest Pacific (SWP), Gulf of Mexico (GOM), and North Atlantic (NA), with sea level rise rates faster than the global average. We analyzed the contributions of different components to the sea level rise in these areas. These regions are all adjacent to land or have a significant number of islands, the faster sea level rise poses a greater threat to the corresponding coastal areas. The contributions of barystatic and steric sea level components are approximately equal in most of these regions. However, in SCS and GOM, the contributions of the barystatic component exceed 60%. The halosteric sea level has a significant negative contribution to the sea level rise in the GOM and NA. The Antarctic Ice Sheet and Greenland Ice Sheet melting contribute to sea level rise in these regions by less than 15%, and more than 15%, respectively. The highest contribution of glacier melting is in the SCS, approximately 23%. Compared to the melting of land ice, changes in land water contribute limitedly to sea level rise in these regions. The contribution is less than 10%, except for in NA.

How to cite: Deng, R. and Dong, W.: Understanding the Regional Disparity of the Sea Level Rise during Altimetry Era, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18660, https://doi.org/10.5194/egusphere-egu24-18660, 2024.

Sea level rises pose significant risks to densely populated coastal regions, threatening human lives and vital infrastructures. Coastal societies, economies, and properties face acute vulnerability from saltwater intrusion, coastal erosion, and flooding resulting from extreme sea level variations. These occurrences are a confluence of factors, including local sea level rises, tidal changes, storm surges, waves, and shifts in coastal morphology.

In the Baltic Sea basin, where tides and North Atlantic storm surges are mitigated by the Danish Straits due to its semi-enclosed nature, coastal extreme sea levels are primarily driven by storm surges propelled by atmospheric pressure and surface winds from extratropical cyclones. Consequently, the surge in extreme sea levels here is predominantly wind-induced, regulated by meteorological processes.

This research focuses on the meteorological conditions, specifically wind patterns, that contribute to sudden sea level rises along the Swedish Baltic coastline. By integrating observations and model data like the ERA5 reanalysis, the study correlates the rapid increase in relative sea levels across 14 tide-gauge stations with wind and wave data. The aim is to exclusively utilize meteorological information for identifying extreme sea level occurrences, thereby enhancing the prediction of such events through weather forecasting.

How to cite: Minola, L., Re, A., Bedoya-Valestt, S., Motta, C., Azorin-Molina, C., Pezzoli, A., and Chen, D.: Quantifying the impact of near-surface winds on the occurrence of extreme sea level rises along the Swedish Baltic coastline: A statistical analysis, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3440, https://doi.org/10.5194/egusphere-egu24-3440, 2024.

In climatological research, understanding past and accurately simulating future sea level variability is paramount due to the considerable risk that sea level changes pose to low-lying regions, coupled with their significant influence on the occurrence and severity of extreme meteorological events  . This research insights are vital in evaluating the potential impact on renewable energy sources, particularly offshore wind, wave, and tidal energy, where changes in sea level can significantly alter the efficiency and viability of these energy converters. This study comprehensively analyses sea level variability on interannual and decadal scales in the Indo-Pacific region, integrating data from the Ocean Reanalysis System 5 (ORAS5), CMIP6 historical simulations spanning from 1850-2014, and future projections under the CMIP6 future intermediate emission scenario (rcp245/ssp245) for the period 2015 to 2100. Our investigation spans key areas such as the Northwest Central Pacific Ocean (NWCPO), the Eastern Equatorial Pacific Ocean (EEPO), and the Thermocline Ridge of the Indian Ocean (TRIO), among others.
We report findings on interannual and decadal Sea Level Anomaly (SLA) variability, especially highlighting the TRIO region and various Pacific Ocean zones such as the SWPO, NWCPO, EEPO, and NWNPO. Our study identifies a substantial increase in interannual variability in the NWNPO. We also observe consistent sea-level variability patterns across these regions, extending into future projections under moderate emission scenarios.
We find that the El Niño Southern Oscillation (ENSO), the Indian Ocean Dipole, and the Pacific Decadal Oscillation are key drivers of these variabilities. Our study reveals a strong connection between sea levels in the Equatorial Pacific and the Niño 3.4 index, suggesting its potential as a sea level-based indicator for El Niño and La Niña events.
Our research highlights the critical role of atmospheric forcing in driving sea level variability. We link high sea-level variability regions to significant wind stress curl anomalies, with distinct differences between hemispheres. We explore the mechanics of equatorial variability, emphasizing the role of equatorial Kelvin waves and local and remote Rossby waves in different oceanic regions.
Our study concludes that most CMIP6 models, despite large model uncertainty, predict an increase in sea level variability for the upcoming century, particularly in the Pacific Ocean, emphasizing the need for heightened attention to this dynamic region in the context of global climate change .

How to cite: Maya, P., Álvarez Antolínez, J. A., Js, D., and Gnanaseelan, C.: The interannual and decadal sea level variabilities over the Indo-Pacific Oceans in the Reanalysis and CMIP6 Historical Simulations and Projections, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9762, https://doi.org/10.5194/egusphere-egu24-9762, 2024.

The excess anthropogenic ocean heat is causing thermal expansion, which has driven approximately 40% of the industrial-era global mean sea level rise. This relation between ocean heat uptake H and thermosteric sea level rise h_θ is mediated by the so-called expansion efficiency of heat (EEH=h_θ/H, in m/YJ) which characterises the expansion of a water-mass under a unit increase of its enthalpy. The EEH of a water-mass depends on its temperature, salinity and pressure. At global scale the EEH has been characterized in both historical observations and climate simulations, but the the role of regional EEH and of individual water-mass layers in the formation of this global expansion efficiency remains undocumented. Here we propose a new approach where the EEH is decomposed in temperature coordinate into a temperature plus a pressure contribution to seawater thermal expansion. We show that the temperature contribution largely dominates the global signal. We also show that the global EEH can be interpreted as a weighted global average thermal expansion coefficient.

We make use of the global EEH decomposition in temperature coordinate to estimate the contribution of individual water-mass layers to global thermal expansion in both historical reference observational datasets and Climate Model Intercomparison Project (CMIP5-6) historical and scenario simulations. Results show a contrasting picture of water mass contributions to global thermal expansion and sea level rise. Whereas ocean warming is distributed between mode, intermediate and deep waters, a disproportionate share of global ocean expansion occurs within tropical waters and subtropical mode waters. Regionally, tropical Pacific waters and subtropical north Atlantic mode waters appear as key contributors to global thermal expansion. These results show that the regional distribution of ocean heat uptake is a key driver of thermal expansion and sea level rise not only at regional scale but also at global scale. We also show that projections of future sea level rise at global scale critically depend on the ability of climate models to simulate both the regional water mass properties and their heat uptake.

How to cite: Waldman, R., Meyssignac, B., Fourest, S., Guillaume-Castel, R., von Schuckmann, K., and Sallée, J.-B.: Revisiting the relation between ocean heat storage and thermal expansion from a water mass perspective, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7891, https://doi.org/10.5194/egusphere-egu24-7891, 2024.

Ocean mass change is the primary driver of sea level rise. Understanding the mechanisms of mass sea level change can help coastal areas scientifically respond to climate change. Under combined the self-attraction and loading effect and the Earth's rotational feedback, land-source freshwater input leads to global spatiotemporal heterogeneity of mass sea level, known as Sea Level Fingerprints. In this study, Sea Level Fingerprints were simulated under three different scenarios, covering periods from January 1901 to July 2019, January 1981 to June 2020, and July 1979 to June 2020. These scenarios encompassed: (1) consideration of climate variability alone; (2) consideration of both climate variability and actual glacial mass balance; and (3) alignment with recent climate change trends. The study aimed to analyze the contribution of Sea Level Fingerprints to satellite-derived mass sea level across these three scenarios. Results showed that in all three scenarios, the significant seasonal amplitude regions include the South China Sea and the Bay of Bengal, with peak values ranging from 42.60 to 45.20 mm. Changes in mass sea level are primarily caused by climate variability. Sea Level Fingerprints, which considered only precipitation and temperature as key indicators of climate variability, best reproduced the variation signal of the GRACE-derived data and the Altimetry-derived mass component. The spatial similarity coefficient derived between their global change range distributions were 0.67 and 0.87, respectively. Sea Level Fingerprints, which additionally considered glacial mass balance, provided a more accurate depiction of the spatial distribution and long-term trend of mass sea level derived from Altimetry satellites and Argo systems. This was demonstrated by the similarity between the sea-level fingerprints and altimetry-derived mass components across global long-term trend distribution patterns, with a spatial similarity coefficient of 0.75. The main contributing regions to these patterns include the Greenland Ice Sheet, Alaska, the Southern Andes, the Caucasus, the Middle East, and West Antarctica.

How to cite: Liu, Y., Deng, S., Zhang, W., and Hu, A.: Progress in the Global Sea Level Fingerprints since the 20th century, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19505, https://doi.org/10.5194/egusphere-egu24-19505, 2024.

How to cite: Edwards, T., Turner, F., and Malagon Santos, V. and the EU PROTECT project: Improving, evaluating and sharing projections of global mean sea level rise, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3503, https://doi.org/10.5194/egusphere-egu24-3503, 2024.

Sea-level rise is one of the most hazardous climate-change impacts and is projected to trigger dramatic increases of coastal flooding frequency in Europe in the current century and beyond.  As such, adaptation-related effective decision making relies on the availability of authoritative and locally relevant information on future coastal sea-levels and their extremes, which include uncertainty quantification. However, current available sea-level projections are typically limited by either too low spatial resolution and therefore missing physical processes relevant at the coast, they account for only part of the sea-level signal (e.g. storm surges), and/or are typically limited to the downscaling of a single atmospheric model and therefore offer no quantification of the potentially significant inter-model uncertainty.   

In response to this knowledge gap, we present a novel extreme sea-level (ESL) projection dataset which focuses on the North-east Atlantic region. The dataset consists of a CMIP6-forced multi-model ensemble of downscaled projections until the end of the century, generated with a regional 3-dimensional ocean model at ~7km resolution. As such, the model captures not only storm-surge and tide induced ESLs, typically captured in barotropic 2-dimensional models, but also accounts for the contribution of circulation and density-driven modulations to extremes. Therefore, the ensemble dataset offers an excellent opportunity to explore ESL drivers at different spatio-temporal scales, their projected future changes, and associated uncertainties.

This dataset will help to advance scientific knowledge on climate-change induced coastal flood risk changes, but also to increase confidence in quantitative assessments of impacts of sea-level rise through its contribution to the Coastal Climate Core Service (CoCliCo), a decision-oriented platform which will inform users on present-day and future coastal risks, and which is currently under development as part of a European Union’s Horizon 2020 project.

The CoCliCo project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 101003598

How to cite: Irazoqui Apecechea, M., Melet, A., Reffray, G., and Le Cozannet, G.: Extreme sea-level projections along European coasts for climate adaptation services , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10576, https://doi.org/10.5194/egusphere-egu24-10576, 2024.

Although the mass loss of land ice is projected to be the largest contribution to sea-level rise in the coming centuries, thermal expansion will also be an important contributor and its accurate projection is primordial to understanding sea-level change over (multi-)centennial timescales. Earth System Models (ESMs) are the main tools for projecting thermosteric sea-level rise. ESMs, however, are computationally demanding and therefore long, multi-centennial simulations are challenging. In this study, we use a physical-based emulator that simplifies the climate system by using three vertically stacked layers, allowing us to mimic the energy balance response of ESMs to reproduce their thermal expansion simulations. We use this emulator to extrapolate simulations from the Coupled Model Intercomparison Project Phase 6 (CMIP6) from 2100 to 2300 and validate our method with CMIP6 runs that are available over that time scale. Overall, the three-layer emulator outperforms its two-layer predecessor in simulating thermal expansion up to 2300, providing a reduction of up to 78% in cumulative error for the projection period covering 2100 to 2300. Finally, we demonstrate how using temperature output from the three-layer model can help us capture non-linearities in dynamic sea-level change better than its two-layer counterpart. The latter is a first step towards building more reliable emulation approaches for oceanic processes affecting regional sea-level change.

How to cite: Malagón-Santos, V., Slangen, A., Hermans, T., Edwards, T., and Turner, F.: Emulating Thermosteric Sea-Level Rise Using a Three-Layer Energy Balance Model, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6564, https://doi.org/10.5194/egusphere-egu24-6564, 2024.

Our ability to characterize and quantify the complex uncertainties surrounding future sea-level changes is crucial for coastal risk assessments and adaptation strategies. This study focuses on the role of steric and dynamic changes (i.e., sterodynamics) in sea level projections, particularly regarding their contribution to the uncertainty of global and regional sea level changes in relation to other components such as ice sheet dynamics. A probabilistic framework is used to estimate probability distributions of sea-level change for each component. Through variance decomposition, the total uncertainty in sea-level change is dissected into its constituent sources. Subsequently, the relative contribution of sterodynamics uncertainty is quantified across various regions, time frames, emission scenarios, and projection methodologies utilized to estimate future sea-level distributions. The contribution of sterodynamics to overall uncertainty reduces over time as the contribution from ice sheets becomes more pronounced. The spatiotemporal pattern of sterodynamic significance is not strongly dependent on future greenhouse gas emissions, yet its overall role is highly dependent on the representation (e.g., emulation) of ice sheets. When high-end, low-probability estimates of future Antarctic ice sheet contributions are excluded, sterodynamics remain a dominant source of regional sea-level uncertainty at the end of this century, particularly along the US East Coast and European coast. These regions are also identified as hotspots for future sea-level rise, indicating that sterodynamic processes will play a significant role in assessing coastal vulnerabilities there. This study suggests that ocean model development can most effectively reduce the overall uncertainty in future sea-level projections by focusing on these areas.

How to cite: Tesdal, J.-E., Krasting, J., Kopp, R., Kumar, P., Griffies, S., and Sweet, W.: The defining roles of sterodynamic sea level in future climate projections, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-21107, https://doi.org/10.5194/egusphere-egu24-21107, 2024.

Decision-makers need reliable projections of future sea level change for risk assessment. Untangling the sources of uncertainty in sea level projections will help narrow the projection uncertainty. Here, we separate and quantify the contributions of internal variability, intermodel uncertainty, and scenario uncertainty to the ensemble spread of dynamic sea level (DSL) at both the basin and regional scales using Coupled Model Intercomparison Project Phase 6 (CMIP6) and FGOALS-g3 large ensemble (LEN) data. For basin-mean DSL projections, intermodel uncertainty is the dominant contributor (>55%) in the near- (2021-2040), mid- (2041-2060), and long-term (2081-2100) relative to the climatology of 1995-2014.  Internal variability is of secondary importance in the near- and mid-term until scenario uncertainty exceeds it in all basins except the Indian Ocean in the long-term. For regional-scale DSL projections, internal variability is the dominant contributor (60~100%) in the Pacific Ocean, Indian Ocean and western boundary of the Atlantic Ocean, while intermodel uncertainty is more important in other regions in the near-term. The contribution of internal variability (intermodel uncertainty) decreases (increases) in most regions from mid-term to long-term. Scenario uncertainty becomes important after emerging in the Southern, Pacific, and Atlantic oceans. The signal-to-noise (S/N) ratio maps for regional DSL projections show that anthropogenic DSL signals can only emerge from a few regions. Assuming that model differences are eliminated, the perfect CMIP6 ensemble can capture more anthropogenic regional DSL signals in advance. These findings will help establish future constraints on DSL projections and further improve the next generation of climate models.

How to cite: Jin, C., Liu, H., Lin, P., and Li, Y.: Uncertainties in the projection of dynamic sea level in CMIP6 and FGOALS-g3 large ensemble, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4335, https://doi.org/10.5194/egusphere-egu24-4335, 2024.

Human-induced increases in atmospheric carbon dioxide (CO₂) cause global warming, which leads global mean sea level rise. Previous research has shown that even with the reduction or removal of atmospheric CO₂, the global mean sea level will not return to its initial level. However, the regional effects of reducing or removing atmospheric CO₂ on sea level change have not been extensively studied. In this study, we analyzed global and regional sea level changes over a 560-year period, including 140 years of a linear increase in atmospheric CO₂ of 1% per year, followed by 140 years of a linear decrease, and finally 280 years of maintenance at pre-industrial CO₂ levels. Our analysis showed that the sea level in the North Atlantic region increased rapidly relative to the global mean, and then recovered rapidly. We attribute these variations to fluctuations in the Atlantic Meridional Overturning Circulation (AMOC). As the AMOC weakened, heat and salt were trapped in the lower latitudes of the North Atlantic region, resulting in a slower transfer of these elements to higher latitudes. As the AMOC recovered and overshoot, the accumulated heat and salt were rapidly transferred to higher latitudes, resulting in changes in sea level. Our results suggest that the North Atlantic region is more sensitive to changes in atmospheric CO₂ compared to the global mean. The North Atlantic region has a high population density and is expected to suffer significant damage as a result of sea level change. Therefore, continuous research on sea level change in this region is needed, and our study could help improve the ability to predict future sea level change in this area.

How to cite: Wang, S., Shin, Y., Oh, J.-H., and Kug, J.-S.: Fast recovery of North Atlantic sea level in response to atmospheric CO2 removal, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-21090, https://doi.org/10.5194/egusphere-egu24-21090, 2024.