The session focuses on studies exploring the physical mechanisms for sea level rise and variability as well as the drivers of these changes, at any time scale (from paleo sea level to high-frequency phenomena to long-term projections), using observations and/or model simulations. Investigations on linkages between variability in sea level, heat and freshwater content, ocean dynamics, land subsidence and mass exchanges between the land and the ocean associated with ice sheet and glacier mass loss and changes in the terrestrial water storage are welcome. Studies focusing on future sea level changes are encouraged, as well as those assessing short-, medium-, and long-term impacts on coastal environments and their implications.
Closure of the global mean sea level (GMSL) budget is essential to understand the causes of GMSL rise. Accounting for the recent progress in observing and estimating of GMSL, steric sea level and ocean mass changes, this study assesses the budget for the GMSL trend and acceleration for the three key observational eras of 1960-2021, 1993-2023 and 2005-2023. For 1960-2021, the trend of GMSL is 1.86 ± 0.34 mm yr-1, closely matching the sum of contributions of 1.88 ± 0.13 mm yr-1, with most dominant contributions coming from steric height change and glacier melting. The observed GMSL acceleration of 0.072 ± 0.005 mm yr-2 for 1960-2021 matches contributions of 0.066 ± 0.005 mm yr-2 and is dominated by steric height change. From 1993 to 2023, the GMSL rise of 3.27 ± 0.06 mm yr-1 also aligns with contributions of 3.22 ± 0.15 mm yr-1. The acceleration of observed GMSL is 0.078 ± 0.013 mm yr-2 for this period, which is supported by the acceleration inferred from sum of contributions of 0.072 ± 0.004 mm yr-2. For 2005-2023, the observed GMSL acceleration is 0.084 ± 0.006 mm yr-2, mainly driven by steric sea level change at 0.083 ± 0.016 mm yr-2. Although the acceleration within three periods is consistent, the driver changes depend on the periods. This study reconciles the observed GMSL trend and acceleration with the sum of contributors since 1960, highlighting the importance of adequate data processing and bias corrections.
How to cite: Zheng, H., Cheng, L., Dangendorf, S., Barnoud, A., Trenberth, K., Fasullo, J., and Abraham, J.: Sea level budget in light of recent observational advances since 1960, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7935, https://doi.org/10.5194/egusphere-egu25-7935, 2025.
In the context of the ESA Climate Change Initiative Sea Level project, we performed a complete reprocessing of high resolution (20 Hz, i.e., 350m) along-track altimetry data of the Jason-1, Jason-2 and Jason-3 missions over January 2002 to June 2021 in the world coastal zones. This reprocessing provides along-track sea level time series and associated trends from the coast to 50 km offshore over the study period. We call ‘virtual coastal stations’ the closest along-track point to the coast. This creates a new network of 1160 virtual sites well distributed along the world coastlines. We performed Empirical Orthogonal Decomposition analyses of the sea level time series at the virtual stations, globally and regionally, in order to: (1) identify the main drivers of the coastal sea level variability at interannual time scale, and (2) assess the along-coast coherence of the sea level response to the dominant drivers. The results highlight those coastlines where the EOF first mode reveals a dominant long-term coastal sea level rise They also help in identifying other regions where the coastal sea level is dominated interannual variations, highly correlated to natural climate modes. This analysis allows us to clearly separate portions of the world coastlines displaying different sea level behaviors. In regions where no tide gauge data are available (a large portion of the southern hemisphere), our results provide new information on present day sea level changes at the coast, hopefully useful for coastal adaptation.
How to cite: Leclercq, L., Cazenave, A., Léger, F., Birol, F., Nino, F., and Legeais, J.-F.: Sea level variations at the world coastlines over the past two decades from reprocessed satellite altimetry, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-113, https://doi.org/10.5194/egusphere-egu25-113, 2025.
Global mean sea level (GMSL) derived from satellite altimetry reflects in an integrated way the overall variability in the Earth's climate system. Linear trend analyses suggest that GMSL is currently rising at a rate of 3.3 mm/yr (Guérou et al., 2023). However, understanding GMSL variations beyond the overall trend is critical to correctly interpret long-term changes. At interannual timescales, variability in GMSL is driven by steric changes in ocean heat content and barystatic variations of water mass, with the El Nino-Southern Oscillation (ENSO) contributing about equally to both.
Here, we are interested in quantifying the impact of internal (multi-) decadal climate variability, which is crucial for assessing the anthropogenic contributions and its role in current GMSL acceleration. Specifically, we focus on the statistical interrelationship between GMSL and the Pacific Decadal Variability as expressed by the Pacific Decadal Oscillation (PDO) index. By studying the co-variability between PDO index and GMSL over the full period of existing satellite altimetry records, we demonstrate that the low-frequency variability superposed to (linear) GMSL rise is almost perfectly consistent with PDO over most of the past decades but exhibits a complete decoupling after 2019. Thus, GMSL rise estimated by statistically accounting for low-frequency climate variability is unprecedented since 2019, supporting the recently reported significant acceleration in the rise of global mean sea level.
This work has been financially supported by INESC TEC via the International Visiting Researcher Programme 2024.
How to cite: Donner, R. and Barbosa, S.: Recent decoupling of global mean sea level rise from decadal scale climate variability, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13153, https://doi.org/10.5194/egusphere-egu25-13153, 2025.
Global mean sea level rapidly increased during the 20th century, at a rate that doubled in the past few decades. Global satellite altimetry records, which have only been available since 1993, have additionally shown that the recent rise in sea level is neither spatially uniform nor linear in time. However, this change in sea level over such a short period likely convolves the externally forced climate signal with natural climate variability, and separating these is critical for coastal planners and policymakers to account for sea-level impacts on their communities. Previous studies have demonstrated that the “least damped (eigen)mode” (LDM) of a Linear Inverse Model (LIM) can effectively identify both sea surface temperature and sea level trend patterns in long records, even when they bear some similarity to patterns of natural climate variability, but that this approach becomes problematic for shorter records. In this study, we show that applying a Gram-Schmidt orthonormalization to the LIM’s eigenmodes adjusts the LDM so that it can identify the trend pattern even for record lengths of a few decades. We first test the technique by applying it to output from large ensembles of historical simulations made by two climate models, NCAR’s CESM2 and GFDL’s SPEAR: For record lengths as short as a few decades, our technique successfully identifies the forced response, as estimated by the ensemble mean, from any single ensemble member. Finally, we determine the forced sea level rise signal from observations, both on global and regional ocean scales as well as for coastal regions as measured by a gauge network, over the satellite observational era, and show how it differs from simple linear or quadratic trend estimates.
How to cite: Shin, S.-I., Penland, C., Newman, M., and Alexander, M.: Separating the Global Pattern of Externally Forced Sea Level Rise from Natural Variability in the Short Climate Record, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14972, https://doi.org/10.5194/egusphere-egu25-14972, 2025.
The Mediterranean Sea accounts for less than 0.5% of the global ocean's total volume and is characterized by unique significance in terms of oceanographic complexity. Indeed, an internal conveyor belt, together with complex circulation patterns and gyres, defines the entire domain. The understanding of Mediterranean oceanography has evolved significantly in recent times, transitioning from a static perspective to a dynamic one, as circulation patterns and thermohaline properties in the basin are now acknowledged to vary over time. Within this dynamic framework, the North Ionian Gyre (NIG) emerges as one of the most intriguing oceanographic features. Situated in the Ionian Sea, the NIG is known to reverse its circulation between cyclonic and anticyclonic modes on a quasi-decadal scale. This fluctuation results in significant variations in the redistribution of water masses and thermohaline properties throughout the Mediterranean Sea. Although various hypotheses have been proposed to explain the causes of these reversal episodes, a widely accepted consensus has yet to be reached. Moreover, reversal episodes have been documented only since the late 1980s through direct observations, modeling, and experimental studies, while the historical variability of this phenomenon remains poorly understood.
In this study, to enhance the understanding of the NIG evolution over time, information about sea-level changes has been accounted for. Indeed, variations in thermohaline properties and water mass redistribution, induced by NIG state shifts, might have been recorded in sea-level changes as a response to these modifications. A total of 46 tide gauges, distributed across the entire domain, have been considered, providing signals that often date back decades or even cover the entire 20th century. Furthermore, information from satellite altimetry has been included to provide a detailed spatial view of sea-level changes in recent decades across the Mediterranean Sea. After the removal of effects such as atmospheric pressure, glacial isostatic adjustment, and the sea-level response induced by the water mass exchange from continents, all signals were decomposed into a finite number of mode functions, each theoretically related to a specific phenomenon. At this stage, the influence of vertical land movements recorded in tide gauges has been isolated and attributed to residual signals, while the oscillatory modes primarily represent sea-level changes associated with thermohaline variations and the dynamic redistribution of seawater.
An interesting oscillatory, quasi-decadal signal emerged as the second mode of variability within all datasets considered. Inflections within this signal provide a notable match, both in time and space, with all known NIG reversal episodes, particularly in the eastern Mediterranean sub-basins. These inflections manifest as an acceleration (or deceleration) in sea-level rise during anticyclonic (cyclonic) NIG phases. Despite their low magnitude in terms of amplitude (approximately 4 cm), they appear to be associated with the main driver of short-term variability in sea-level trends across the domain. Since signals from tide gauges provide long-term time series, this correlation enables the reconstruction of the NIG reversal history over the past 120 years based on direct observations.
How to cite: Meli, M.: Sea-level variability as a proxy for ocean dynamics in the Mediterranean Sea, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10181, https://doi.org/10.5194/egusphere-egu25-10181, 2025.
The Mediterranean Sea, as a semi-enclosed basin, is particularly sensitive to climatic changes, making it a critical region for studying sea level variability. This study investigates the decadal variability of the Mean Sea Level (MSL) trend in the Mediterranean and its subregions over the past 30 years (1993-2022), using a combination of satellite altimetry, tide gauges, and reanalysis datasets.
Our findings reveal a slowdown in the overall Mediterranean MSL trend during the 2013-2022 decade compared to previous periods, highlighting significant regional differences. The Western Mediterranean exhibits an accelerating trend consistent with global sea level rise, while the Eastern Mediterranean has experienced a decadal slowdown, including the Adriatic and Aegean Seas, where negative trends are observed. This slowdown is attributed to the combined effects of changes in the water cycle and the balancing of thermal and haline steric components. Increased evaporation emerges as a key driver of the observed trend changes, surpassing contributions from precipitation, runoff, and strait transport.
These results underscore the significance of the Mediterranean's water budget in influencing sea level trends and highlight the complexity of interpreting decadal sea level changes. The findings suggest that continued monitoring and a better understanding of regional water budgets are crucial for refining future projections and developing effective climate adaptation strategies for the Mediterranean coastal areas.
How to cite: Borile, F., Pinardi, N., Lyubartsev, V., Ghani, M. H., Navarra, A., Alessandri, J., Clementi, E., Coppini, G., Mentaschi, L., Verri, G., da Costa, V. S., Scoccimarro, E., Novellino, A., and Oddo, P.: The Eastern Mediterranean Sea mean sea level decadal slowdown: the effects of the water budget, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10449, https://doi.org/10.5194/egusphere-egu25-10449, 2025.
The effects of model resolution on the simulation of sea-level variability were analyzed based on the second-generation climate system ocean model from the State Key Laboratory of Numerical Modeling for Atmospheric Science and Geophysical Fluid Dynamics, Institute of Atmosphere Physics (LICOM2) with resolutions of 1° (LICOM2-L) and 0.1° (LICOM2-H).The interannual variability, decadal variability, and long-term trends of the dynamic sea level (DSL) are estimated using a multivariate linear regression model based on the LICOM2-L and LICOM2-H datasets during 1958–2007. The analysis reveals that the distributions of interannual and decadal variability, as well as long-term trends, are consistent between the LICOM2-L and LICOM2-H simulations in the tropics and mid-latitudes. However, differences in these variabilities are most pronounced in the regions of the western boundary currents and Antarctic Circumpolar Current, primarily due to variations in thermosteric sea level (TSSL) and halosteric sea level. In contrast, the DSL variability differences in the Southern Ocean are mainly due to the TSSL.
Analyses of ocean heat content (OHC) budgets suggest that the differences between the LICOM2-L and LICOM2-H simulations are mainly in decadal variability and long-term trends. The interannual and decadal variabilities of OHC are significantly influenced by both large-scale mean advection and eddy-induced transport. The latter plays a more pronounced role in high-latitude regions and contributes notably to decadal variability and trend differences. At the equator, eddy-induced transport is the primary driver of long-term trends, accounting for 80% of the total contribution, while the large-scale mean advection contributes the remaining 20%. These findings underscore the complex interplay between mean advection and eddy processes in shaping the thermohaline structure and sea level variability in the ocean models.
How to cite: Wang, Y.: Impacts of model resolution on the simulation of sea-level variability by a global ocean-sea ice model, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6336, https://doi.org/10.5194/egusphere-egu25-6336, 2025.
Global, regional and local sea-level projections rely on complex process-based models of the climate-ocean-cryosphere system. While extrapolation of observational data has been examined on global and regional scales, this approach has not yet been used for the additional complexities of local coastal sea-level projections. Here, we evaluate the sea level trend and acceleration for a global network of tide-gauge observations over 1970-2023, which are then extrapolated to provide local projections up to 2050 and compared with the process-based projections from the IPCC Sixth Assessment Report (AR6). For 2050 relative to 2020, the observation-based projections agree with AR6 process-based projections within the 90% uncertainty range at the majority (99%) of 237 tide gauges. Thus, the observation-based projections provide complementary perspectives of near-term local sea-level changes, and this agreement provides increased confidence in the current understanding and projections of sea-level changes over coming decades.
How to cite: Wang, J., Zhang, X., Church, J., King, M., and Chen, X.: Near-term future sea-level projections supported by extrapolation of tide-gauge observations, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-21523, https://doi.org/10.5194/egusphere-egu25-21523, 2025.
Projections of relative sea level rise are central to assess the future impacts of sea level rise, but available projections do not emerge as a continuation of the historical data. This complicates local adaptation planning, coastal impact assessments and communication to policy makers. Here, we present a spatial Bayesian model to provide local projections emerging from past records. The model integrates tide gauges, GPS and satellite altimetry with past and future constraints on mountain glaciers, polar ice sheets, thermal expansion, ocean circulation, land water storage and glacial history. We separate natural, unforced ocean variability from the long-term signal to provide posterior estimates of sea level change and vertical land motion. The model reduces the uncertainty for local projections within this century through the inclusion of local constraints while producing global median projections and uncertainty ranges similar to the IPCC AR6. The model allows to project local relative sea level rise for any given global-mean temperature pathway and we illustrate this with projections for three IPCC AR6 WG3 pathways.
How to cite: Mengel, M. and Perrette, M.: Relative sea level projections constrained by tide gauge trends, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10506, https://doi.org/10.5194/egusphere-egu25-10506, 2025.
Sea level rise increases the flood risk in coastal communities throughout the world. Many studies have shown that enormous property values are at risk already this century. In particular under high emission scenarios. Protecting infrastructure from flooding is thus an important objective for coastal spatial planning, and planning activities are ongoing in states, counties and municipalities around the world. Current coastal spatial planning methods are, however, not well tailored for this task. Problems persist in how such plans can incorporate: uncertainties, time dependence and the interplay between sea level rise and sea level extremes. Here we demonstrate how these different components can be incorporated into a joint probabilistic framework, using Monte Carlo methods. A model called the sea level simulator is used together with a cost function that estimates the value of infrastructure as a function of its height above the current mean sea level, giving a comprehensive coupling between physical and economic risk. That is, between high sea levels and economic loss. The end result is a probabilistic estimate of flooding loss conditioned on user-defined emission scenario probabilities. The framework is well fit both as a decision support tool and as a tool for making uncertainty quantifications. The capabilities of the framework are demonstrated using examples from one of Sweden's oldest cities, the city of Kalmar. Examples are given showing how losses and their uncertainty depend on emission scenario, the length of the planning period and thresholds in the cost curve
How to cite: Hieronymus, M., Hedfors, J., Van Well, L., Göransson, G., Bokhari Irminger, S., and Magnusson, Å.: Estimating the cost of sea level rise, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1418, https://doi.org/10.5194/egusphere-egu25-1418, 2025.
Coastal lowlands in the world increasingly face accelerating rates of relative sea-level rise, as global sea level rises and coastal land subsidence increases. Originating from both natural and anthropogenic processes, land subsidence (i.e. downward vertical land motion) is particularly prominent in densely populated coastal-deltaic settings where human activities can accelerate subsidence rates to several centimetres or even decimetres per year, thereby dominating local, contemporary relative sea-level rise. Proper inclusion of vertical land motion dynamics into sea-level change projects, combined with high-accurate and correctly referenced coastal elevation data, is crucial to accurately project relative sea-level change in these critical, densely populated coastal areas.
Recent advancements in satellite-based InSAR data acquisition and processing capacity provide insights into contemporary vertical land motion dynamics at unprecedented spatial scale, complementary to traditional measurements of vertical land motion by e.g. tide gauges and GNSS stations. However, it requires a robust InSAR-data processing framework that ensures internal consistency of SAR data and rigorously assesses output accuracy. In addition, correct interpretation of InSAR results is important as observations provide reflector movements which may not align with land surface movements, particularly in urban areas. This poses the risks of oversimplification and misinterpretation when linking InSAR results to sea-level change.
In addition, coastal subsidence is the result of various subsurface processes at different depths and can be highly non-linear over time, unlike sea-level change, resulting in complex spatio-temporal patterns and dynamics. This makes projection of non-linear vertical land motions and relative coastal elevation change not straightforward and robust strategies have yet to be developed. We advocate the development of standardized InSAR (post-)processing workflows and interdisciplinary collaboration to improve the observation and proper interpretation of vertical land movement, particularly in coastal cities and river deltas. We also discuss how to move from contemporary observations of coastal vertical land motion towards disentangling drivers and processes, move to process-based projections of coastal subsidence and integrate them in robust projections of future relative sea-level changes and coastal exposure assessments.
How to cite: Minderhoud, P. S. J., Seeger, K., Shirzaei, M., and Teatini, P.: Properly integrating vertical land motion with sea-level change – towards robust projections of relative sea-level rise , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12705, https://doi.org/10.5194/egusphere-egu25-12705, 2025.
The socio-economic impacts of sea-level rise are significant, especially in coastal regions with dense populations and costly infrastructure. Accurate projections of sea-level changes at regional scales are essential for risk assessment but are challenging due to the interplay of processes affecting the height of both the land and sea surface (and, therefore, relative sea level). Rising sea levels from ice melting and ocean expansion exacerbate flooding risks, with nuisance flooding serving as an early warning for vulnerable regions such as Atlantic Canada, which is experiencing GIA-induced land subsidence. The compounded effects of GIA and contemporary sea-level rise escalate regional vulnerability to flooding. This study improves projections of mean sea-level changes and nuisance flooding in Atlantic Canada by integrating the sea-level signal from optimal regional GIA models into the framework adopted in the 6th Assessment Report of the Intergovernmental Panel on Climate Change (IPCC). Projections under SSP1-1.9, SSP3-7.0, and SSP5-8.5 scenarios for 2050, 2100, and 2150 CE are used to assess nuisance flooding frequency at 40 tide gauge stations. Our results demonstrate that the GIA signal contributes significantly to flooding frequency estimates and that these estimates can depart considerably from those estimated using the IPCC (AR6) mean sea level projections. For example, nuisance flooding at Halifax becomes chronic (>50 days annually) by 2050 CE under SSP3-7.0 using our GIA model results. This level of chronic flooding occurs in Halifax at 2050 CE only for the most extreme scenario (SSP5-8.5) when using the IPCC mean sea level projections.
How to cite: Parang, S., Karegar, M. A., and Milne, G. A.: Improved projections of sea-level change and nuisance flooding in Atlantic Canada: The importance of GIA-induced land motion, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11472, https://doi.org/10.5194/egusphere-egu25-11472, 2025.
Sea-level rise in Singapore and Southeast Asia differs from the global average due to various regional and local processes, such as land uplift and subsidence, ocean and atmospheric circulation, and the gravitational effects from melting ice sheets. The current scarcity of sea-level data in Southeast Asia, however, limits our ability to understand the regional and local processes needed to generate more accurate sea-level rise projections. We therefore realize there is a crucial need to produce more sea-level data within Southeast Asia and develop sea-level models that can effectively inform adaptation strategies for rising sea levels.
Using case studies from the Southeast Asia Sea Level (SEA2) program from Singapore and Southeast Asia, we illustrate how historical and geological data can constrain future projections, and how sea-level projections can motivate the development of new sea-level research questions to mitigate and adapt to climate change.
- We showed that rapid sea-level rise driven by ice melting ~14,500 and ~11,500 years ago significantly reduced land area and forced early human migration across Southeast Asia[1]. During these periods, thresholds of coastal habitat survival were also surpassed resulting in large-scale coastal wetland retreat.
- Glacial Isostatic Adjustment (GIA) model predictions suggest Southeast Asia experienced sea levels higher than present between 7,000 and 4,000 years ago, producing a mid-Holocene highstand[2]. Variability in the highstand magnitude is controlled by solid Earth parameters while the highstand timing is controlled by ice sheet melting history.
- We introduced a new fusion method for quantifying a best-estimate of sea-level rise uncertainty to support decision-making[3]. We estimate that by 2100, global sea levels will likely rise between 0.3-1.0 m under low emission and 0.5-1.9 m under high emission scenarios.
- We demonstrate the implications of rising sea levels to coastal ecosystems. With 3°C of warming, nearly all mangrove forests and coral reef islands would be beyond their sea-level rise tipping point for survival[4].
[1] Kim, H.L., Li, T., et al. 2023. Commun Biol 6, 150. https://doi.org/10.1038/s42003-023-04510-0
[2] Li, T., et al. 2023. Quat Sci Rev 319, 108332. https://doi.org/10.1016/j.quascirev.2023.108332
[3] Grandey, B.S., Dauwels, J., Koh, Z.Y., Horton, B., et al. 2024. Earth’s Future. https://doi.org/10.21203/rs.3.rs-2922142/v3
[4] Saintilan, N., Horton, B., et al. 2023. Nature 621, 112–119. https://doi.org/10.1038/s41586-023-06448-z
How to cite: Horton, B. P., Chardot, L., Chua, S., Grandey, B. S., Iksan, M. H., Li, T., Ng, T., Samanta, D., Shaw, T., Tan, F. Y., Tan, S., Tsyrulneva, I., and Yap, W.: Sea-Level Science in Singapore and Southeast Asia, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7702, https://doi.org/10.5194/egusphere-egu25-7702, 2025.
Future sea-level rise will generate hazards for coastal populations, economies, and infrastructure in Singapore and Southeast Asia. However, regional projections remain highly uncertain due to complex regional to local factors, including ocean dynamics, and extreme sea-level events. Here, we review our 4-year project funded by Singapore’s National Sea Level Programme, which focused on enhancing the accuracy of regional sea-level rise projections by 2100. Our approach includes: 1) attributing historical sea-level changes to anthropogenic and natural forcings[1]; 2) quantifying drift uncertainty in global climate model simulations[2]; 3) investigating tide-surge interaction in Singapore and surrounding regions[3]; and 4) addressing ambiguity in sea-level rise projection by fusing multiple projections used in the Intergovernmental Panel on Climate Change 6th Assessment Report (IPCC AR6)[4]. First, using large ensemble climate model simulations we detected and attributed historical (1950–2014) sea-level changes over the Indo-Pacific warm pool region providing insights for future projections. We discovered that the historical rise in sea level is predominantly driven by the influence of greenhouse gases, although aerosols tend to moderate the rate of rise. Notably, the rate of sea-level rise and the time of emergence of anthropogenic signals vary spatially in the region. We also highlight the important role of manometric sea-level changes in shallow and coastal regions in Southeast Asia. Second, we develop a Monte Carlo drift correction technique to quantify uncertainty in drift correction for global climate models, using climate model data. Our findings highlight that drift uncertainty can significantly impact energy balance estimates and sea-level rise, underscoring the need to account for drift uncertainty when analyzing climate model outputs. Third, using a statistical framework, we study tide-surge interaction at seven tide gauges along the coast of Singapore and the east coast of Peninsular Malaysia, focusing on the timing of extreme non-tidal residual relative to tidal high water. We found that tide-surge interaction influences coastal water levels in this region, and our semi-empirical model provides insight into the mechanisms of tidal phase alteration. Finally, we propose a new approach to quantify the best estimate of the scientific uncertainty associated with sea-level rise by fusing the complementary strengths of the ice sheet models and expert elicitations used in IPCC AR6. Under a high-emissions scenario, the very likely range is 0.5–1.9 m. The 95th percentile projection of 1.9 m can inform a high-end storyline, supporting decision-making for activities with low uncertainty tolerance. We plan to use our findings to offer policymakers and coastal planners a robust, high-confidence toolset for long-term adaptation strategies in Singapore and Southeast Asia.
[1] Samanta et al., (2024), https://doi.org/10.1029/2023EF003684
[2] Grandey et al., (2023), https://doi.org/10.5194/gmd-16-6593-2023
[3] Koh et al., (2024), https://doi.org/10.5194/os-20-1495-2024
[4] Grandey et al., (2024), https://doi.org/10.1029/2024EF005295
How to cite: Samanta, D., Grandey, B. S., Koh, Z. Y., Chew, L. Y., and Horton, B. P.: Future Sea-Level Rise in Southeast Asia: New Insights on Uncertainty, Ocean Dynamics, and Extreme Events, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5094, https://doi.org/10.5194/egusphere-egu25-5094, 2025.
The storm surge contribution to coastal extreme sea levels along the European coastlines has been explored using a set of hydrodynamic numerical simulations. When forced by high-resolution atmospheric fields, simulated storm surge time series display good correspondence with observations. Because of their length, accuracy and consistency, these numerical data have been widely used to characterise coastal extreme sea levels, in terms of their magnitude and probability of occurrence. These outputs are then often used to infer coastal hazards and risks. However, higher risks associated to the most extreme events, represented by return periods substantially longer than the simulated time span, are generally accompanied by large uncertainties, thus limiting the robustness of long-term coastal risks assessments based solely on these otherwise valuable datasets. One way to reduce these uncertainties is increasing their sample size. Here, we do so by running a number of hydrodynamic simulations forced by mean sea level pressure and surface wind fields from a set of initialised climate models from the Decadal Climate Prediction Project (DCPP) over a domain covering the European coasts (excluding the Baltic Sea) and amounting for a total of 9000 years. Hydrodynamic simulations forced with atmospheric pressure and wind fields from these models, once are biased-corrected, result in a much larger dataset of coastal storm surges. Large datasets also provide information on the probability of extreme sea levels that are plausible in the current climate but for which there is no observational evidence.
How to cite: Marcos, M., Agulles, M., Amores, A., Feng, X., and Robson, J.: Constraining extreme sea levels along the European coasts from a large ensemble of climate models, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9224, https://doi.org/10.5194/egusphere-egu25-9224, 2025.
Future sea level change in the Mediterranean Sea is one of the major climate hazards for populations living in low-elevation coastal zones (≤10 m above mean sea level). In this study, we analyze projections of mean sea level rise in the Mediterranean Sea by the end of the 21st century. To address this, we use a set of multi-decadal simulations from three pairs of regional climate system models (RCSMs) of the Med-CORDEX initiative together with the simulations of their driving global climate models (GCMs). For the first time, we analyze the mean relative sea level simulated by a set of high-resolution and fully coupled regional models to provide a detailed characterization of regional and local patterns of future Mediterranean sea level change. By 2100, under the high-emission SSP5-8.5 scenario, the basin-averaged total sea level is projected to rise by +71 cm from RCSMs and +76 cm from GCMs (central estimates). Among the sea level components, the sterodynamic term (dynamic sea level + global mean thermosteric sea level) is the largest contributor to total sea level rise, with 91% of its contribution driven by global thermal expansion. The sterodynamic term and the vertical land motion drive local sea level adjustments in regions such as the Balearic Sea and the Ionian islands, leading to the highest sea level rise in the Mediterranean. We find that sea level rise in the Mediterranean is expected to be slower than the nearby Atlantic due to a dynamic adjustment within the basin. Furthermore, compared to the GCMs, the RCSMs show a higher spread (extremes) of the sea level response without a mean regional effect.
How to cite: Parras Berrocal, I. M., Waldman, R., Gonzalez, N., and Somot, S.: Future projections of sea level rise in the Mediterranean Sea, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15515, https://doi.org/10.5194/egusphere-egu25-15515, 2025.
Over the past few decades, the rise of sea level has emerged as a critical concern for coastal regions across the globe, driving intense scientific efforts to understand the underlying processes. However, disentangling and interpreting ocean physics’ contributions (sterodynamic) to these changes remains a complex challenge. To contribute to a better understanding of future sea level rise patterns, this study proposes a sterodynamic sea level decomposition for Boussinesq models with a specific focus on the mass change contribution. In particular, we explore the interplay between mass and density-driven changes and disentangle the respective influences of freshwater and salt mass changes. Based on a high-emission (SSP5-8.5) coupled regional projection of the Mediterranean climate system, we apply this methodology to the Mediterranean Sea.
Under the investigated scenario, the Mediterranean sterodynamic sea level is projected to rise by 32 cm by the end of the 21st century. We find that 24 cm are attributable to the global ocean temperature increase and 8 cm to regional hydrographic and mass changes, the so-called “dynamic sea level change”. Focusing on these regional patterns, our results reveal that the mediterranean dynamic sea level rise is predominantly caused by an increase in salt mass. Specifically, this increase results from an enhanced net volume transport through the Strait of Gibraltar in response to increased evaporation and steeper sea level gradient with the Atlantic Ocean. Finally, we attribute local sea level variations to changes in the mediterranean circulation and horizontal density variations. Overall, this study emphasizes the added value of a comprehensive decomposition of mass’ contribution for interpreting future sea level rise patterns.
How to cite: Gonzalez, N. M., Waldman, R., Parras-Berrocal, I. M., and Somot, S.: Decomposing steric and dynamic sea level trends in a future high-emission scenario of the Mediterranean Sea, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16149, https://doi.org/10.5194/egusphere-egu25-16149, 2025.
Temporarily crossing and subsequently returning below 1.5°C, a so-called temperature ‘overshoot’, is a scenario of increasing relevance and interest. Potential impacts and risks of such an overshoot, including triggering irreversible ice loss and a large multi-century sea-level rise (SLR) commitment, need to be better understood to support well-informed policy and decision making.
Here, we use a set of eight overshoot scenarios from the PROVIDEv1.2 ensemble, covering a wide range of peak temperatures and emission reduction rates, to force an updated MAGICC-SLR emulator to explore the multi-century responses of the main sea level components. The emulator updates include a new calibration for the Greenland solid ice discharge component and different land water storage representations following population assumptions as represented in the Shared Socioeconomic Pathway (SSP) framework. These are the first steps of a comprehensive MAGICC-SLR update to provide overshoot-proof state-of-the-art probabilistic SLR projections.
Under a scenario that extrapolates mitigation efforts resulting from current climate policies out to 2100 and thereafter decreases global average temperatures back to 1.5°C, we project a global mean SLR of 1.4 m (median, 0.7-3.2 m very likely range) by 2300, relative to 1995-2014 levels. By extending the 2300 radiative forcing levels further into the future, we explore SLR projections until 2500, with greatly increasing uncertainties and decreasing robustness of the sea level response. In case of a temperature overshoot below 2.0°C, our results suggest that global mean SLR is reduced by following a SSP1 rather than SSP2 population pathway through dam impoundment and groundwater extraction management. For the updated MAGICC-SLR emulator, we find that the relative contribution of the Greenland solid ice discharge component steadily increases over time and becomes the dominant SLR driver across all scenarios beyond 2300. Our results suggest that by 2500, the committed global SLR from overshooting 1.5°C cannot be returned to levels of a 1.5°C stabilization scenario.
We highlight and discuss the limitations and caveats when projecting SLR under overshoot with simplified modeling approaches and outline next steps to continue overshoot-proofing MAGICC-SLR. We emphasize the need for a careful evaluation of the parameterizations for each SLR component to ensure a physically robust representation of the (ir)reversibile multi-century SLR response under overshoot.
How to cite: Möller, T., Nicholls, Z., Lewis, J., Schleussner, C.-F., and Nauels, A.: Towards overshoot-proof multi-century sea level rise projections, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13297, https://doi.org/10.5194/egusphere-egu25-13297, 2025.
Posters on site: Mon, 28 Apr, 14:00–15:45 | Hall X5
The late Holocene relative sea-level (RSL) history of Scotland is spatially and temporally variable, as it lies close to the boundaries of the former British-Irish Ice Sheet (BIIS) and within the maximum sea-level fingerprint of Antarctic melt. It is therefore an interesting location to understand the interplay of drivers of RSL and the consequences on rates of change, over centennial to millennial timescales. However, there are few late Holocene RSL records from the region, especially islands offshore of mainland Scotland. Along mid-latitude coastlines, salt-marsh deposits provide ideal archives of late Holocene sea level. In this study, we combine stratigraphy, sedimentology (grain size analysis and loss-on-ignition) and diatom biostratigraphy to reconstruct late Holocene sea level, at a newly studied salt marsh at Gress, on the eastern coastline of the Isle of Lewis in the Outer Hebrides. Rather than the typical quantitative transfer function approach, we instead utilise a qualitative visual assessment method to reconstruct RSL due to poor performance by the UK modern diatom transfer function at this location. By combining 14C dates and Bayesian modelling, we derive a chronological model for the core to assess the timing of any RSL change. We consequently present a new, near-continuous RSL record at Gress which shows a stable to slowly falling RSL trend over the last ~2500 years. At ~AD 580, the disappearance of Sphagnum moss, a typical freshwater species, accompanies the appearance of brackish diatoms species, highlighting a potential increase in the proximity of marine conditions which may indicate regionally rising RSL from this time.
How to cite: Leoh, K. K., Barlow, N., Dawson, S., Nicholson, U., and Switzer, A.: 2500 years of late Holocene relative sea-level change at Gress, Isle of Lewis, northwest Scotland, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5300, https://doi.org/10.5194/egusphere-egu25-5300, 2025.
Common Era (last 2000 years) relative sea-level (RSL) records have revealed important insights on the drivers of RSL change; links between climate and sea-level changes; and the timing of the modern acceleration in the rates of sea-level rise. However, the distribution of Common Era RSL records is spatially biased to the North Atlantic. Here, we update the global database of Common Era RSL records with 36 new sea-level index points from coral microatolls and mangrove sediments in Southeast Asia, and 12 RSL data points from a continuous-core mangrove record in Belize. A spatio-temporal hierarchical model is applied to analyse the influence of these new records on the global mean sea-level rate and to attribute regional RSL trends to possible local and regional drivers of RSL change.
How to cite: Tan, F., Walker, J., Lin, Y., Upton, M., Shaw, T., Tan, N. S., and Horton, B.: Common Era sea levels in tropical regions, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14028, https://doi.org/10.5194/egusphere-egu25-14028, 2025.
Records of Holocene relative sea-level (RSL) change from Western Australia, a far-field location distal to former polar ice sheets, offer important constraints on ice melt contributions to global mean sea-level (GMSL) change. Despite this, recent efforts to reconstruct RSL have been limited, and the nature of Holocene RSL evolution in Western Australia remains debated in part due to biased comparisons of data. Here we review, re-evaluate, and aggregate RSL data from Western Australia following international standard protocol and explore the potential of sedimentary archives from beach ridge systems and buried transgressive facies of southwestern Australia to produce accurate, high-resolution records of RSL change. We use these data to test several working hypotheses about ice sheet contributions to GMSL change during the Holocene and the influence of local (e.g., non-stationary tides) or higher-frequency (e.g., El Niño Southern Oscillation) drivers of sea-level variability. Improved constraints on the behaviour of relative sea level during the Holocene will provide necessary data for enhancing our understanding of earth rheology, ice sheet dynamics, and natural variability of sea-level changes under warm, interglacial climate states.
How to cite: Khan, N., O'Leary, M., Li, T., Creel, R., Gao, C., Nugraha, A., Kumar, R., Sefton, J., and Switzer, A.: Holocene sea-level evolution in Western Australia , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15449, https://doi.org/10.5194/egusphere-egu25-15449, 2025.
Reconstructions of past relative sea level (RSL) during the late Holocene have shown a response to natural climate warming and cooling phases such as the Medieval Climate Anomaly and Little Ice Age. Coupled with long-term instrumental measurements from tide gauges, they also showed a timing of emergence in RSL rate centered around the mid-19th century, with a 20th century rise that is extremely likely (P≥0.999) faster than the proceeding 3000 years. These conclusions, however, are derived from RSL reconstructions and tide-gauge records that are limited in tropical latitudes and currently excludes Southeast Asia hindering the interpretation of sea-level changes and validation of models that predict future spatial variability.
Here, we present a new RSL reconstruction using mangrove sediments from the Matang Mangrove Forest Reserve, western Peninsula Malaysia to constrain RSL change during the late Holocene. Following an extensive field reconnaissance, we collected a ~3 m core from the upper intertidal environment and modern surface samples across an intertidal-to-mangrove gradient to constrain modern and fossil indicative meanings. Selected samples were analyzed for organic content, foraminiferal assemblages and environmental DNA and sample sites were surveyed relative to local Malaysian national geodetic benchmarks using differential GPS. We constrained temporal uncertainties in the reconstruction using accelerator mass spectrometry radiocarbon dating of bulk sediment fine-fractions (n=11) coupled with short-lived radionuclide chronohorizons within a Bayesian age-depth framework.
Stratigraphic investigations revealed uniform sedimentary sequences comprising subtidal and intertidal silty clay muds overlain by organic (50% LOI) mangrove peats to depths of ~2.5 m within which foraminiferal tests are well preserved and dominated by typical agglutinated taxa including Arenoparrella mexicana and Trochammina inflata. Radiocarbon dating provides an excellent chronology of in sequence ages approximately ~2200 years old. We combined the proxy reconstruction with nearby tide gauge records and applied a spatiotemporal empirical hierarchical model to quantify magnitudes and rates of RSL change. We compare the RSL reconstruction with other new records from Singapore and use glacial isostatic adjustment model predictions to assess and discuss driving processes throughout the region.
How to cite: Shaw, T., Satyanarayana, B., Yap, W., Li, T., Majewski, J., Tan, F., Walker, J., Fadzil, M., Switzer, A., and Horton, B.: Evaluating late Holocene relative sea-level changes from the tropics: Matang Mangrove Forest Reserve, Malaysia., EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18262, https://doi.org/10.5194/egusphere-egu25-18262, 2025.
The global mean sea-level rise is today well quantified: 1.4 ± 0.1 mm yr-1 over 1901-1993 (based on tide gauge records) and 3.0 ± 0.2 mm y-1 over 1993-2010 (based on satellite altimetry data). However, this rise is not uniform and large departures from the global mean sea-level trend are observed. Given that over 750 million people are living in the low-elevation coastal zone and because sea-level will continue to rise due to climate change, it is crucial to obtain reliable trends at local and regional scale, to design appropriate adaptation policies for the future. In this study, we investigated the North Atlantic sea-level rise over the 20th century along the coasts using tide gauges and climate model outputs from the Coupled Model Intercomparison Project 6 (CMIP6) framework. As climate models do not account for land ice melt, the contribution of ice sheets (Greenland and Antarctica), mountain glaciers and land water storage were added a posteriori. Climate models provide gridded data with a relatively coarse resolution (~1°); whether they correctly simulate sea-level rise at a given point in space is still an open question. We explored the ability of climate models to correctly reproduce the 20th century sea-level trends at the nearest points to tide gauge locations in the North Atlantic ocean over 1900-2014. Based on a multi-member ensemble approach from CMIP6 model outputs, we determine both the externally forced (ensemble mean) and internal variability contribution (ensemble spread) to historical sea-level changes. We showed that the internal variability is higher on the west side of the North Atlantic basin than on the east side.
How to cite: Jacob, B., Pineau-Guillou, L., Llovel, W., and Thierry, V.: Sea-level rise along the North Atlantic coasts since 1900, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4356, https://doi.org/10.5194/egusphere-egu25-4356, 2025.
Accurate evaluation of sea-level return levels is crucial for coastal planning. Two ubiquitous methods are the generalised Pareto distribution (GPD), favoured for its ease of access and cheap computational cost, and the skew surge joint probability method (SSJPM), which models deterministic tides and stochastic surges separately but does not consider tide–surge interaction. We propose a modification to the SSJPM, called the copula joint probability method (CJPM), where a copula is used to model the joint distribution of skew surges and peak tides, to account for correlation between tidal high water and skew surge. We compare the performance of the GPD, SSJPM and CJPM in estimating the 30-year return level using only ten years of training data. To validate the models, we require long observational records which can be provided by tide gauges with approximately 100 calendar years of records. For each tide gauge record, ten calendar years are randomly chosen to train the three models while the remaining years are used to validate model predictions. This procedure is repeated multiple times and the mean absolute error (MAE) of each model is estimated at each tide gauge site. The SSJPM and CJPM have lower MAE than the GPD at most tide gauges. The CJPM complements the SSJPM by accounting for correlation between tidal high water and skew surge, providing improved performance at many tide gauges.
How to cite: Koh, Z. Y., Grandey, B., Dauwels, J., and Chew, L. Y.: Applying copula to joint probability methods: a comparison of extreme sea-level estimation methods, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7949, https://doi.org/10.5194/egusphere-egu25-7949, 2025.
In March of 2018, a winter storm hit Southern New England (US East Coast), with most of the coastal cities experiencing minor to moderate coastal floods. However, days after the storm passed and the winds and waves calmed down, the tide-gauge data continued to reach minor flooding levels. What was the cause of this prolonged recurrent flooding? Here we argue that the lingering effects of local ocean current dynamics contributed to this flooding.
Along the US East Coast, an important driver of coastal sea-level variability is ocean dynamics, related to both large-scale circulation, such as the Gulf Stream, but also smaller local ocean currents. A relevant circulation feature in Southern New England is the Shelfbreak jet (SBJ). The SBJ flows equatorward from the Labrador Sea towards the Gulf Stream at Cape Hatteras following the shelf break along the Northeast US coast. In a recent study, we showed that the SBJ and sea level along the southern New England coast are highly correlated, especially at timescales of 1-15 days (Camargo et al., 2024).
Since this frequency band coincides with the timescales of storm surges, we explore the implication of our findings for coastal flooding. We find that the SBJ explains, on average, about 25% of the storm surge variance for flood days along Southern New England. Specifically, for the March 2018 winter storm, SBJ dynamics are responsible for more than 90% of the storm surge observed 4 days after the peak of the storm. That is, there would have been no flooding so many days after the storm passed if not for SBJ-related-dynamics.
Our results suggest local ocean dynamics are an important component of storm surges in Southern New England, and contribute to lingering flooding after a storm has passed. Thus, we advocate that ocean dynamics should be considered in flood studies elsewhere. Furthermore, our results suggest that focusing only on large-scale circulation, such as the Gulf Stream or ocean overturning, may not be satisfactory for understanding the most basic dynamics essential for making meaningful projections of the future.
Reference: Camargo, C. M. L., Piecuch, C. G., & Raubenheimer, B. (2024). From Shelfbreak to Shoreline: Coastal sea level and local ocean dynamics in the northwest Atlantic. Geophysical Research Letters, 51, e2024GL109583. https://doi.org/10.1029/2024GL109583
How to cite: M.L. Camargo, C., Piecuch, C., and Raubenheimer, B.: Coastal Floods and the Lingering Effects of the Shelfbreak Jet - A case study of how local ocean currents contribute to coastal flooding in Southern New England (US), EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11771, https://doi.org/10.5194/egusphere-egu25-11771, 2025.
Extreme sea level (ESL) events pose the highest risk to coastal communities and infrastructure, with their frequency and intensity projected to increase in the future. These events result from a combination of tidal height, mean sea level, wave height, and storm contributions. However, the spatiotemporal variability of regional extreme sea-level events and its connection to climate teleconnections and large-scale weather processes remain poorly understood.
In this work, we demonstrate that regional ESL variability can be attributed to large-scale teleconnections and traced back to atmospheric and oceanographic patterns in the North-Atlantic.
Applying Empirical Orthogonal Function (EOF) analysis on the daily maximum of hourly detrended and detided sea level from the CODEC dataset, we found that the first three modes explain 90% of the variance (53%, 20%, and 9%, respectively). Clustering using Gaussian Mixture models reveals five distinct regions of sea level variability. The top three EOF modes show significant correlations using linear regression with climate indices, most significantly the North Atlantic Oscillation, Arctic Oscillation, and the Eastern Atlantic. Composite analysis of these modes attributes each mode variability to large-scale atmospheric and oceanographic variables. This highlights significant weather patterns in the North Atlantic, connecting non-local weather sources to regional variability of sea level extremes.
Our findings illustrate how regional sea level variability is driven by large-scale weather and climate patterns. By linking distinct spatial modes to significant drivers and changes in weather variables, we provide new insights on the causes and climatology of high sea levels. This understanding offers valuable applications for early warning systems and coastal planning. Furthermore, understanding the drivers of ESL variability can improve long-term predictions of regional coastal flooding risk. Given the global nature of ESL events and the increasing need for adaptation, our research contributes to a critical foundation for future resilience planning.
How to cite: Blok, L., Oltmanns, M., Marinoni, A., and Mashayek, A.: Linking regional extreme sea level variability in North-Western Europe to large scale climate modes, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13409, https://doi.org/10.5194/egusphere-egu25-13409, 2025.
This study investigates sea level variability in the East Sea (ES) and East China Sea (ECS) using a combination of in-situ observation, satellite altimeter data from the Copernicus Marine Environment Monitoring Service (CMEMS), and reanalysis datasets from the Hybrid Coordinate Ocean Model (HYCOM), Ocean Reanalysis System 5 (ORAS5), and Global Ocean Reanalysis and Simulation (GLORYS) for the period 1993-2023. The analysis focuses on the influences of steric effects and mass components on sea level, excluding atmospheric pressure impacts for simplification. The Ieodo Ocean Research Station (IORS), located in the ECS at 125.18°E and 32.12°N, served as a key observation point. The trends in monthly mean sea level were 5.82 mm yr-1 (in-situ, 2003–2023) and 3.53 mm yr-1 (CMEMS, 1993–2023), 3.09 mm yr-1 (GLORYS, 1993–2023), 2.27 mm yr-1 (ORAS5, 1993–2023) and -0.09 mm yr-1 (HYCOM, 1994–2023). Notably, HYCOM trends exhibited variability over sub-periods, with rates of 0.85 mm yr-1 (1994-2015), 2.75 mm yr-1 (2016-2023), 0.56 mm yr-1 (1994-2017), 8.82 mm yr-1 (2018-2023), and 0.56 mm yr-1 (2003-2023). Cross-correlation analysis demonstrated significant agreement between detrended sea levels, with coefficients of 0.92 (CMEMS & GLORYS), 0.90 (CMEMS & HYCOM), 0.89 (CMEMS & ORAS5), 0.80 (CMEMS & in-situ). Additionally, this methodology was applied to sea level data from Ulleung Island at 130.90°E and 37.50°N and Dok Island at 131.87°E and 37.24°N, providing further insights into sea level variability in the ES and ECS. Understanding sea level changes in these regions using limited but representative datasets contributes to improving knowledge of regional sea level variability and supports analysis and prediction in a warming climate.
How to cite: Han, M. and Lim, H.-S.: Sea Level Variability in the East Sea and East China Sea: Insights from Observations and Reanalysis (1993-2023), EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5302, https://doi.org/10.5194/egusphere-egu25-5302, 2025.
Continental freshwater input from glaciers and ice sheets is responsible for more than half of the ongoing global sea level rise. This freshwater redistributes across the oceans following specific patterns, determined by gravitational, rotational and deformation effects, known as sea level fingerprints. These fingerprints can be uniquely associated with their continental mass sources and could in theory enable the reconstruction of continental water and ice mass changes, helping to better attribute the causes of ongoing sea level change. However, they are very difficult to detect because their magnitude is much smaller than the signals related to ocean sterodynamic changes and atmospheric effects. To address this challenge, our research has employed deep learning techniques to separate sea level fingerprints from synthetic satellite altimetry data. Our findings reveal that deep learning is highly effective at this task, highlighting significant potential of deep learning in detecting large-scale geospatial signals. This deep learning approach could serve as a basis for accurately quantifying mass changes in the cryosphere and land hydrology from satellite altimetry observations over the last three decades, ultimately providing valuable insights into the impacts of climate change on sea level and the global water cycle.
How to cite: Mao, K., Sun, J., and Riva, R.: Detecting Sea Level Fingerprints from Synthetic Satellite Altimetry Data Using Deep Learning, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7344, https://doi.org/10.5194/egusphere-egu25-7344, 2025.
Estimates of mean sea level change in the 20th and 21st centuries are important for monitoring the effects of climate change. In particular, there is increasing interest in attributing the relative contributions to observed sea level change both globally and in specific regions. Here we present a new method for obtaining such quantitative inferences from combinations of satellite gravity, satellite altimetry, and tide gauge data. Our approach is based upon a full Bayesian solution to the associated inference problem which incorporates realistic priors on all unknowns along with a comprehensive treatment of observational uncertainties. An essential step within this method is the solution of both the sea level equation and its adjoint, with the latter approach being a new development. As part of this work, open source python libraries are being developed for sea level modelling and the solution of Bayesian inference problems within a function space setting.
How to cite: Heathcote, D. and Al-Attar, D.: A new Bayesian approach to the inverse modelling of modern sea level change, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17187, https://doi.org/10.5194/egusphere-egu25-17187, 2025.
We focus on the Antarctic contribution to sea level by 2050, intending to improve sea-level rise estimates for decadal decision-making purposes. We compare ISMIP6 2100 ice sheet model-derived projections and data-driven estimates from 2015-2050. We find that models divide into two categories of response based on their initialisation approach, with spin-up-style models generally showing little response to forcing (relative to their control) over this period even under a high emissions scenario, while data assimilation models suggest increased change in the Amundsen Sea Embayment and parts of East Antarctica, and accelerating ice loss along the Siple Coast. We suggest a lower surface mass balance in the forced simulations than the control simulations drives an unrealistic mass loss signal in the Amundsen Sea sector in the ISMIP6 projections over 2015-2050. We then focus on the data assimilation models and explore their projection of the dynamic contribution to sea levels by 2050. We complement these with data-driven estimates based on linear or linear-plus-quadratic models fit to gridded satellite altimeter data while also considering natural climate variability that dominates decadal-scale surface mass balance variations. Historical trends (i.e., pre-2015) are not necessarily captured in the ISMIP6 2100 models, partly due to a lack of observational constraints before the satellite record. Hence, we use gridded empirically-derived surface lowering trends combined with the ISMIP6 projected trends, and compare them to the linear and quadratic linear and quadratic empirical extrapolations to 2050. Finally, we explore the differences and sensitivities in sea level fingerprints deriving from these estimates and their potential implications for decision-making processes.
How to cite: King, M., McCormack, F., and Lin, Y.: What Antarctic sea-level rise estimates to 2050 should be used for decision-making?, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2624, https://doi.org/10.5194/egusphere-egu25-2624, 2025.
Coastal zones in the Maritime Continent are one of the most vulnerable regions in the world to sea level rise and other climate-associated hazards. Ocean circulations transport mass, salt, and heat through the South China Sea (SCS) and the Southeast Asian Seas (SEAS), linking the western tropical Pacific and Indian Oceans. This process significantly influences regional sea-level changes, causing higher rates of sea-level rise than global. Current global general circulation models (GCMs) are mostly limited in resolving regional ocean circulation and boundary currents due to their coarse resolution. Therefore, dynamic downscaling of the global GCMs to regional scales using high-resolution ocean models is widely considered as an efficient solution to derive regional sea-level projections. In this study, we employ an eddy-resolving regional ocean model (NEMO) to dynamically downscale sea-level projections from the global climate model (EC-Earth3) for the SSP2-4.5 and SSP5-8.5 scenarios in the Maritime Continent, encompassing the South China Sea and other Southeast Asian Seas. A novel aspect of our approach is the use of WRF-based downscaled atmospheric fields from the same parent global climate model (EC-Earth3), to provide high resolution surface boundary conditions for the ocean model projections. This study further explores the low-frequency steric sea-level trend and variability, as well as associated heat flux and transport by prevailing climate modes in the region.
How to cite: Ma, P. and Pavel, T.: Low-Frequency Variability and Projected Changes of Steric Sea Level in the Maritime Continent, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5431, https://doi.org/10.5194/egusphere-egu25-5431, 2025.
Sea-level change has garnered significant interest, particularly in recent decades, and is becoming of undeniable concern for numerous stakeholders and communities globally. Vertical land motion contributes to local sea-level change but its causes and rates vary widely. Whilst long term, large scale isostatic adjustment is predictable, short term, local non-linear changes (e.g., subsidence via groundwater extraction, or active tectonics) remain unaccounted for in current sea-level projections. In the eastern Indian Ocean, large uncertainties in VLM remain, which we consider an effect of non-linear behaviour and we assess to improve predictability. Owing to a lack of long term VLM data in the region, we test approaches combining tide gauges and satellite altimetry to derive 30-year VLM time series. We validate the approach using 20 TGs co-located with GNSS measurements of VLM. We separate the signal into linear and non-linear components and demonstrate, for example locations, the effect of propagating non-linear VLM into local sea-level projections.
How to cite: Martin, E., Jackson, L., and Williams, S.: Control of non-linear vertical land motion on future sea-level projections across the eastern Indian Ocean, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10629, https://doi.org/10.5194/egusphere-egu25-10629, 2025.
Global mean sea level is rising due to anthropogenic climate change, via the thermal expansion of seawater and the mass loss of land ice. Regional sea-level change is also affected by changes in ocean currents due to the changing climate and internal climate variability. Global climate models from CMIP6 (Coupled Model Intercomparison Project Phase 6) simulate future sterodynamic sea-level change – the combined contribution of thermal expansion and ocean dynamics – with a resolution on the order of 100 by 100 km. However, at this resolution, the simulation of coastal processes on the continental shelves and the exchange between the European continental shelves and the deep Atlantic Ocean is limited. We address this by dynamically downscaling four CMIP6 models using the ROMS regional ocean model for Western Europe, which has a 12 by 12 km resolution with 30 terrain-following depth layers. Based on the results, we present sea-level projections until 2100 for 2 emission scenarios. We investigate the effect of dynamical downscaling on future sea-level trends in Western Europe. For example, we find that regional sea level rises more in the German Bight than in other regions during the satellite era because of changes in wind. With our ensemble of 4 downscaled CMIP6 models, we are able to quantify the inter-model uncertainty and we can assess the advantages and disadvantages of dynamical downscaling for annual mean sea-level projections.
How to cite: Scheen, J., Bars, D. L., Hermans, T. H. J., Keizer, I. J., Wouters, B., Lhermitte, S., and Slangen, A. B. A.: Increasing the resolution of sea-level simulations for Western Europe with a regional ocean model until 2100, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9785, https://doi.org/10.5194/egusphere-egu25-9785, 2025.
The UK high-plus-plus (H++) scenario for high-end sea-level rise is used in sensitivity testing for significant infrastructure (e.g. nuclear facilities) and forms part of the Environment Agency planning guidance in England. However, the existing H++ scenario, developed as part of the UK Climate Projections in 2009 (UKCP09), does not reflect the latest science knowledge on ice sheet instability processes and has limitations, as revealed in consultations with users of this information. We outline a new H++ framework to inform coastal planning and decision-making. The first step involves users screening decisions using an updated H++ scenario that reflects major scientific advances since UKCP09. For decisions found to be sensitive to high-end sea-level rise in the screening step, the second step involves users evaluating adaptation options and damage costs against a wider library of alternative, plausible storylines. Our H++ screening scenario is based on the Intergovernmental Panel on Climate Change Sixth Assessment Report low-likelihood high-impact sea-level rise assessment. In response to stakeholder needs, all storylines within the H++ framework provide time-continuous, geographically-specific sea-level rise projections to 2300 and information on rates of sea-level rise.
How to cite: Weeks, J. H., Allison, L. C., Beverton, A., Lowe, J. A., Orr, H. G., Roberts, H., and Palmer, M. D.: A new framework to explore high-end sea-level rise for the UK: updating H++, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16137, https://doi.org/10.5194/egusphere-egu25-16137, 2025.
Posters virtual: Thu, 1 May, 14:00–15:45 | vPoster spot 5
EGU25-7561 | Posters virtual | VPS6
Predicting Interannual Sea Level Variations Along the U.S. East Coast Using Machine Learning and Climate IndicatorsThu, 01 May, 14:00–15:45 (CEST) | vP5.15
Coastal sea level changes have profound impacts on coastal ecosystems, infrastructure, and communities. Interannual sea level variations along the U.S. East Coast are influenced by a combination of dynamic and thermodynamic processes, including local wind forcing, Gulf Stream variability, regional ocean circulation changes, and thermosteric contributions. These processes are interconnected and strongly modulated by large-scale climate modes such as the North Atlantic Oscillation (NAO), El Niño-Southern Oscillation (ENSO), and Atlantic Multi-decadal Oscillation (AMO). This study leverages machine-learning-based predictive models to quantify and forecast interannual sea level variability by integrating diverse climate indicators. By incorporating indices of large-scale climate modes alongside local and regional oceanographic parameters, the model quantifies the relative contributions of each factor and identifies the dominant processes driving observed variability. The results demonstrate the potential of machine-learning approaches to capture complex nonlinear relationships between climate modes and regional sea level changes. NAO-driven atmospheric forcing and ENSO-related ocean-atmosphere interactions emerge as key predictors, with the models successfully replicating observed variability along different sections of the U.S. East Coast. The findings highlight the importance of integrating large-scale climate dynamics into regional sea level prediction frameworks and suggest new opportunities for improving forecast accuracy at interannual timescales.
How to cite: Ye, Z., Ye, Z., and Zhao, J.: Predicting Interannual Sea Level Variations Along the U.S. East Coast Using Machine Learning and Climate Indicators, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7561, https://doi.org/10.5194/egusphere-egu25-7561, 2025.
