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Sea‐level change threatens the U.S. East Coast. Thus, it is important to understand the underlying causes, including ocean dynamics. Most past studies emphasized links between coastal sea level and local atmospheric variability or large‐scale circulation and climate, but possible relationships with local ocean currents over the shelf and slope remain largely unexplored. Here we use 7 years of in situ velocity and sea‐level data to quantify the relationship between northeastern U.S. coastal sea level and variable Shelfbreak Jet transport south of Nantucket Island. At timescales of 1–15 days, southern New England coastal sea level and transport vary in anti‐phase, with magnitude‐squared coherences of ∼0.5 and admittance amplitudes of ∼0.3 m Sv−1. These results are consistent with a dominant geostrophic balance between along‐shelf transport and coastal sea level, corroborating a hypothesis made decades ago that was not tested due to the lack of transport data. Plain Language Summary Sea‐level rise is an imminent threat to coastal communities worldwide, including the U.S. East Coast. Therefore, it is crucial to understand the processes driving regional sea‐level change. While past studies documented how coastal sea level may be influenced by large‐scale ocean circulation, less attention has been paid to the role of more local currents over the shelf and slope. Here we explore the relationship between coastal sea level along the northeastern U.S. and the Shelfbreak Jet, a current that flows along the shelfbreak from the Labrador Sea to Cape Hatteras (North Carolina). From 7 years of in situ data of both current velocities and water levels, we see that as coastal sea level rises, Shelfbreak Jet transport increases westward (and vice versa) on timescales of days to weeks. Our results lay the groundwork for understanding relationships between coastal sea level and local ocean dynamics elsewhere. Key Points Daily Shelfbreak Jet transports and Southern New England coastal sea levels are anti‐correlated during 2014–2022 The observed relationship between these two variables is consistent with geostrophic balance For this region, coastal sea levels are more sensitive to local ocean dynamics than to large‐scale circulation

Glacial isostatic adjustment (GIA) modeling is not only useful for understanding past relative sea‐level change but also for projecting future sea‐level change due to ongoing land deformation. However, GIA model predictions are subject to a range of uncertainties, most notably due to uncertainty in the input ice history. An effective way to reduce this uncertainty is to perform data‐model comparisons over a large ensemble of possible ice histories, but this is often impossible due to computational limitations. Here we address this problem by building a deep‐learning‐based GIA emulator that can mimic the behavior of a physics‐based GIA model while being computationally cheap to evaluate. Assuming a single 1‐D Earth rheology, our emulator shows 0.54 m mean absolute error on 150 out‐of‐sample testing data with <0.5 s emulation time. Using this emulator, two illustrative applications related to the calculation of barystatic sea level are provided for use by the sea‐level community. Plain Language Summary Piecing together the history of ice sheet change during past glacial cycles is not only important for understanding past sea‐level change but also for predicting how ongoing glacial rebound contributes to future sea‐level change. Traditionally, a physics‐based “sea‐level model” is used to predict the sea‐level change associated with a particular reconstruction of past ice sheet change and compare the results with geological records of past sea level. However, a fundamental limitation of this approach is the need to compute sea‐level change for a large number of plausible ice histories, which is often prohibited by the computational resources required to repeatedly solve the complex physical equations. In this paper, we describe a machine‐learning‐based statistical model that can mimic the behavior of a physics‐based sea‐level model. This statistical model is computationally cheap and we demonstrate that it is able to accurately predict global sea‐level change for a suite of 150 “unseen” ice histories. Our statistical model predicts sea‐level change 100–1,000 times faster than a physics‐based model, making it an ideal tool for investigating and improving our understanding of global ice sheet change. Key Points The first attempt to build a deep‐learning based Glacial isostatic adjustment (GIA) emulator that can accurately predict global sea‐level change based on a given ice model This emulator (GEORGIA) can predict global sea‐level change history within 0.5 s with minor emulation error This GIA emulator along with two illustrative applications are available for use by the wider sea‐level community

Holocene sea‐level reconstructions from tidal marshes are commonly derived from proxy indicators that have a consistent and quantifiable relationship with tidal elevation. While microfossils are most commonly employed, using multiple indicators leads to more robust reconstructions. We explore the utility of elemental geochemistry obtained through x‐ray fluorescence as a proxy indicator in tidal marshes at Port Alberni, British Columbia, Canada and Willapa Bay, Washington, United States. The elemental composition of bulk surface sediment collected from 141 stations along 10 transects was determined using an ITRAX Core Scanner. Partitioning Around Medoids cluster analysis on the elemental data distinguished between tidal flat, low marsh, and high marsh zones at both locations, similar to zones established from previously published microfossil (foraminifera, diatoms) data sets on the same samples. The elemental composition of low elevation samples from the tidal flat is dominated by lithogenic (Si, K, Ti, Fe) and biogenic (Sr) elements, whereas higher elevation samples have high proportions of organic content (Br, incoherent and coherent scattering ratio). Principal Component Analysis points to differences in organic versus inorganic content, a function of tidal elevation, as the main driver of geochemistry‐derived zones. Approximately 70% of the elemental variability within both marshes is controlled by the inorganic content, as indicated by lithogenic and biogenic elements versus organic content. The elemental composition of bulk surface sediment from two regions spaced ∼300 km apart shows a promising relationship with tidal elevation over a wider spatial scale and highlights the potential of this proxy for use in sea‐level reconstructions. Plain Language Summary In modern tidal wetland environments, the distribution of marsh vegetation and microfossil species is controlled by tidal inundation, for which elevation is the key indicator. The modern relationship between microfossils and tidal elevation is well established and has been applied to tidal marsh sediment to reconstruct sea‐level change through time from marshes around the world. In this study, we show that the relationship between the elemental composition of modern marsh sediment and tidal elevation at two separate locations is comparable to the well‐established relationship between microfossils and tidal elevation. Low‐elevation marsh areas (frequently inundated by tides) are dominated by mineral‐forming elements (e.g., Si, Ti, Fe), whereas high‐elevation areas (less frequently inundated by tides) contain abundant organic‐related elements (e.g., C, N, Br). This relationship is evident at tidal marshes at Port Alberni, British Columbia, Canada and Willapa Bay, Washington, United States, located ∼300 km apart, indicating similar processes controlling elemental distributions at both sites. Results from this study highlight the potential of elemental geochemistry for reconstructing sea‐ and land‐level change in coastal marshes. Key Points Elemental geochemistry of modern tidal marsh sediment shows a consistent relationship with tidal elevation at local spatial scales Elemental composition along a tidal marsh transect is predominantly controlled by the inorganic and organic content of the sediment The use of lower abundance elements contained within tidal marsh sediment warrants exploration

The results from a carefully implemented GPS analysis, using a strategy adapted to determine accurate vertical station velocities, are presented. The stochastic properties of our globally distributed GPS position time series were inferred, allowing the computation of reliable velocity uncertainties. Most uncertainties were several times smaller than the 1–3 mm/yr global sea level change, and hence the vertical velocities could be applied to correct the long tide gauge records for land motion. The sea level trends obtained in the ITRF2005 reference frame are more consistent than in the ITRF2000 or corrected for Glacial‐Isostatic Adjustment (GIA) model predictions, both on the global and the regional scale, leading to a reconciled global rate of geocentric sea level rise of 1.61 ± 0.19mm/yr over the past century in good agreement with the most recent estimates.

Dynamic sea‐level change (ΔDSL)$({\\Delta }\\mathrm{D}\\mathrm{S}\\mathrm{L})$is a key process in shaping the pattern of future sea‐level rise. CMIP6 models predict a range of ΔDSL${\\Delta }\\mathrm{D}\\mathrm{S}\\mathrm{L}$under 1% increase of CO2${\\text{CO}}_{2}$per year. We analyze this CMIP6 spread into contributions from: (a) surface flux change (dF)$(\\mathrm{d}\\mathrm{F})$and (b) model sensitivity to it (Φ)$({\\Phi })$ . Specifically, we force the pre‐industrial simulation of an ocean model with space‐ and time‐varying dF$\\mathrm{d}\\mathrm{F}$diagnosed from different CMIP6 models (one at a time). The CMIP6 spread is thus decomposed into a flux‐driven spread and a residual; the latter is linked to model spread of Φ${\\Phi }$ . We improve upon previous studies by: (a) deriving the perturbed forcing ensemble using an ocean‐only setup and (b) comparing it with the CMIP6 ensemble for both variance and correlation. This reveals distinct roles of surface forcing in driving the CMIP6 spread in different regions. In the North Pacific, differences in windstress forcing primarily explain the CMIP6 spread, while in the North Atlantic, differences in model sensitivity are more important. For the latter region, although buoyancy forcing drives a ΔDSL${\\Delta }\\mathrm{D}\\mathrm{S}\\mathrm{L}$spread there, it correlates poorly with the CMIP6 spread. In the Southern Ocean, differences in both surface forcing and model sensitivity are important for explaining the CMIP6 spread. The surface forcing affects the spread along 40°S via windstress and the spread around the Antarctic via buoyancy flux. Plain Language Summary Climate model simulations provide important information to support planning for future sea‐level rise. Contemporary climate models exhibit large differences in simulated regional sea‐level change under strong CO2${\\text{CO}}_{2}$emission. These model differences can be analyzed in terms of: (a) model differences in simulated surface flux changes (heat, freshwater and wind) and (b) model differences in simulated ocean response to a given surface flux change. We find that model differences in surface flux changes explain most of model diversity in sea‐level change in the North Pacific and part of that in the Southern Ocean, but little of that in the North Atlantic. These results pave the way for reducing sea‐level projection uncertainties in future research. Key Points CMIP6 spread of dynamic sea‐level projections results from both surface forcing and model sensitivity to it Windstress forcing explains the CMIP6 spread in the North Pacific, while model sensitivity is more important in the North Atlantic In the Southern Ocean, both surface forcing and model sensitivity are important for explaining the CMIP6 spread

The Paris agreement focused global climate mitigation policy on limiting global warming to 1.5 or 2 °C above pre-industrial levels. Consequently, projections of hazards and risk are increasingly framed in terms of global warming levels rather than emission scenarios. Here, we use a multimethod approach to describe changes in extreme sea levels driven by changes in mean sea level associated with a wide range of global warming levels, from 1.5 to 5 °C, and for a large number of locations, providing uniform coverage over most of the world’s coastlines. We estimate that by 2100 ~50% of the 7,000+ locations considered will experience the present-day 100-yr extreme-sea-level event at least once a year, even under 1.5 °C of warming, and often well before the end of the century. The tropics appear more sensitive than the Northern high latitudes, where some locations do not see this frequency change even for the highest global warming levels.Combining previous estimates in a multimethod approach, extreme sea levels are assessed under global warming levels of 1.5–5 °C at over 7,000 coastal sites worldwide. By 2100 or before, about 50% of locations exhibit present-day 100-year extreme sea levels at least once per year, even at 1.5 °C of warming.

For over a century, alluvial river terraces have been used as archives of tectonic deformation or changes in water discharge, sediment supply, and sea level. Despite this long history, such efforts remain challenging: using terraces as deformation markers requires knowledge of their initial geometry, and most attempts to attribute terrace formation to paleoclimate forcing rely on qualitative comparisons between paleoclimate archives and terrace ages. We illustrate how simulating alluvial valley profiles and terrace formation can substantially improve such analyses. We apply a physically‐derived model of alluvial river long profiles to the Río Santa Cruz, a glacially‐fed river in Patagonia with extensive terraces. To explore how different geomorphic drivers affect terrace formation, we impose (a) sinusoidal changes in the input sediment‐to‐water discharge ratio, (b) sediment pulses, (c) sinusoidal surface uplift and subsidence simulating glacial isostatic adjustment (GIA), and (d) sea‐level variations. Each forcing mechanism generates distinct terrace geometries and lag‐time distributions, with the river response time relative to the forcing timescale influencing both. We test which terrace‐formation drivers are most likely to have generated the terraces along the Río Santa Cruz, whose response time is considerably longer than timescales of glacial–interglacial cycles. Our results reveal complex patterns of incision and aggradation, including destructive signal interference leading to terrace‐formation gaps. Although terrace profiles may remain non‐unique, when combined with a quantitative understanding of alluvial river processes, they represent a powerful archive of diverse Earth‐system processes, including variations in water and sediment supply, sea‐level change, GIA, tectonic deformation and mantle dynamics. River terraces—flat, elevated, surfaces alongside rivers that represent ancient floodplains—have been used for over a century as evidence of surface deformation or climatic change. We used a numerical model to improve our understanding of how terraces form, with reference to the Río Santa Cruz, a large river in southern Argentina with extensive terraces. We explored how different driving processes effect terrace formation, specifically: (a) cyclical changes in the amount of sediment and water entering the river, (b) sudden sediment pulses, (c) cyclical upward and downward movements of the surface from advancing and retreating glaciers, and (d) sea‐level variations. We find that different driving processes generate terraces with different, potentially diagnostic, shapes, and that terrace formation may be delayed substantially behind the responsible driving processes. We then test systematically which processes are most likely to have generated the terrace sequence observed along the Río Santa Cruz. In this way, we show how, in combination with models of river evolution, river terraces could be used as archives of past tectonic and climatic change. Modeling alluvial valley profiles and terrace formation can improve their interpretations as paleoenvironmental archives Individual drivers and their combinations lead to distinct terrace profile shapes and extents with predictable lag times River response time relative to the forcing frequency plays an important role in terrace profile shape and spatial extent

With an acceleration of global sea‐level rise during the satellite altimetry era (since 1993) firmly established, it is now appropriate to examine sea‐level projections made around the onset of this time period. Here we show that the mid‐range projection from the Second Assessment Report of the IPCC (1995/1996) was strikingly close to what transpired over the next 30 years, with the magnitude of sea‐level rise underestimated by only ∼1 cm. Projections of contributions from individual components were more variable, with a notable underestimation of dynamic mass loss from ice sheets. Nevertheless—and in view of the comparatively limited process understanding, modeling capabilities, and computational resources available three decades ago—these early attempts should inspire confidence in presently available global sea‐level projections. Such multidecadal evaluations of past climate projections, as presented here for sea‐level change, offer useful tests of past climate forecasts, and highlight the essential importance of continued climate monitoring. Plain Language Summary The ultimate test of climate projections occurs by means of subsequent observations. Three decades of satellite‐based measurements of global sea‐level change now enable such a comparison and show that early IPCC climate projections were remarkably accurate. Predictions of glacier mass loss and thermal expansion of seawater were comparatively successful, but the ice‐sheet contributions were underestimated. Nevertheless, these findings provide confidence in model‐based climate projections. Key Points IPCC projections in the mid‐1990s of global sea‐level change over the next 30 years were remarkably robust The largest disparities between projections and observations were due to underestimated dynamic mass loss of ice sheets Comparison of past projections with subsequent observations gives confidence in future climate projections

Cretaceous cyclic peritidal carbonates form the bulk of the Apulia Region in Italy and represent the vestiges of the Apulia Carbonate Platform. To show from a sequence stratigraphic perspective the architecture of peritidal carbonates, the 17 m thick Albian Giovinazzo sea‐cliff section was studied at a centimetre detail, aiming to: (i) describe cyclic facies organisation in beds and bedsets; (ii) reconstruct the relative sea‐level curve and its evolution over time; (iii) interpret the long‐term evolution of the accommodation space in terms of sequence stratigraphy. The hierarchical stacking pattern of facies in beds and bedsets reveals Milankovitch cyclicity. As a working hypothesis, elementary sequences are assumed to represent the precession cycle (ca 20 kyr) and small‐scale and medium‐scale sequences the short (ca 100 kyr) and long (ca 400 kyr) eccentricity cycles, respectively. Four different types of elementary sequences (condensed, catch‐down, catch‐up and give‐up) are recognised and interpreted in terms of relative sea‐level changes to reconstruct the relative sea‐level curve of the entire succession. The envelope of the reconstructed relative sea‐level curve is used to represent the long‐term accommodation change on the platform, which covers a time span of approximately 1.8 Myr. Most of this time was spent in subaerial exposure, as approximately 1.2 Myr was predicted to be condensed in a stratigraphic interval encompassing both the sequence‐boundary zone/falling stage deposits and the lowstand deposits. Moreover, it was interpreted that about two‐third of the total thickness of the succession was formed in only 280 kyr and consisted of both transgressive and maximum‐flooding deposits. The main implication of this study is that unconformities do not necessarily correspond to single surfaces but, rather, to very amalgamated intervals or unconformity zones. Moreover, based on biostratigraphic constraints, there is a correlation between the unconformity zone of the studied succession and the third‐order KAl4 sequence boundary of the Cretaceous eustatic cycle chart. Four different types of elementary sequences (condensed, catch‐down, catch‐up and give‐up) were recognised and interpreted in terms of relative sea‐level changes to reconstruct the relative sea‐level curve of the entire succession. The envelope of the reconstructed relative sea‐level curve was used to represent the long‐term accommodation change on the platform, that covers a time span of approximately 1.8 Myr. Most of this time was spent in subaerial exposure, as approximately 1.2 Myr was predicted to be condensed in a stratigraphic interval encompassing both the sequence boundary zone/falling stage deposits and the lowstand deposits. Moreover, it was interpreted that about two‐third of the total thickness of the studied succession was formed in only 280 kyr and consisted of both transgressive and maximum flooding deposits.

Carbon (δ13Corg, δ13Ccarb) and oxygen (δ18Ocarb) isotope records are presented for an expanded Upper Cretaceous (Turonian–Coniacian) hemipelagic succession cored in the central Bohemian Cretaceous Basin, Czech Republic. Geophysical logs, biostratigraphy and stable carbon isotope chemostratigraphy provide a high‐resolution stratigraphic framework. The δ13Ccarb and δ13Corg profiles are compared, and the time series correlated with published coeval marine and non‐marine isotope records from Europe, North America and Japan. All previously named Turonian carbon isotope events are identified and correlated at high‐resolution between multiple sections, in different facies, basins and continents. The viability of using both carbonate and organic matter carbon isotope chemostratigraphy for improved stratigraphic resolution, for placing stage boundaries, and for intercontinental correlation is demonstrated, but anchoring the time series using biostratigraphic data is essential. An Early to Middle Turonian thermal maximum followed by a synchronous episode of stepped cooling throughout Europe during the Middle to Late Turonian is evidenced by bulk carbonate and brachiopod shell δ18Ocarb data, and regional changes in the distribution and composition of macrofaunal assemblages. The Late Turonian Cool Phase in Europe was coincident with a period of long‐term sea‐level fall, with significant water‐mass reorganization occurring during the mid‐Late Turonian maximum lowstand. Falling Δ13C (δ13Ccarb – δ13Corg) trends coincident with two major cooling pulses, point to pCO2 drawdown accompanying cooling, but the use of paired carbon isotopes as a high‐resolution pCO2 proxy is compromised in the low‐carbonate sediments of the Bohemian Basin study section by diagenetic overprinting of the δ13Ccarb record. Carbon isotope chemostratigraphy is confirmed as a powerful tool for testing and refining intercontinental and marine to terrestrial correlations. Carbonate and organic matter carbon‐isotope chemostratigraphy provides a basis for improved stratigraphic resolution, allows the more precise placement of stage boundaries, the recognition of hiatuses, and enables intercontinental correlation between marine and terrestrial sections. Oxygen isotope trends evidence the development of a Europe‐wide Late Turonian Cool Phase, with up to 4°C fall in bottom‐water temperatures. Cooling was coincident with a period of long‐term sea‐level fall, and significant water‐mass reorganization; falling Δ13C trends, coincident with two major cooling pulses, point to pCO2 drawdown accompanying cooling.