The system of oceanic flows constituting the Atlantic Meridional Overturning Circulation (AMOC) moves heat and other properties to the subpolar North Atlantic, controlling regional climate, weather, sea levels, and ecosystems. Climate models suggest a potential AMOC slowdown towards the end of this century due to anthropogenic forcing, accelerating coastal sea level rise along the western boundary and dramatically increasing flood risk. While direct observations of the AMOC are still too short to infer long-term trends, we show here that the AMOC-induced changes in gyre-scale heat content, superimposed on the global mean sea level rise, are already influencing the frequency of floods along the United States southeastern seaboard. We find that ocean heat convergence, being the primary driver for interannual sea level changes in the subtropical North Atlantic, has led to an exceptional gyre-scale warming and associated dynamic sea level rise since 2010, accounting for 30-50% of flood days in 2015-2020. The regional sea level variations driven by the ocean and atmospheric dynamics, corrected for the inverted barometer effect and not directly related to ice loss or net heat absorbed by the ocean, are termed dynamic sea level changes. State-of-the-art climate models project a decline in the AMOC towards the end of the century, which, as a consequence of geostrophic balance, would be accompanied by a dynamic sea level rise along the western boundary of the North Atlantic 35 – 38 . Higher sea levels are expected to dramatically increase the risk of coastal flooding 9 , 39 . While century-long proxy data indicates that the AMOC may already be slowing down 40 , the direct observations of the AMOC are still too short to confirm this centennial trend 41 , and they mainly showcase interannual-to-decadal variations 42 – 45 . The regional dynamic sea level changes and the GMSL rise superimpose on each other and provide background conditions for large-amplitude synoptic and tidal fluctuations. In addition, land subsidence with an average rate of about 1 mm yr −1 is a sizable contributor to the accelerated sea level rise along the U.S. East coast 15 , 46 – 49 . In low-lying coastal regions, an increase of even a few centimeters in the background sea level can break the regional flooding thresholds and lead to coastal inundation. Furthermore, as the GMSL continues to rise, the impact of the regional dynamic sea level changes on coastal inundation is increasing. In this study, by analyzing Sea Surface Height (SSH) measurements from satellite altimetry and tide gauge records, we quantify how the gyre-scale dynamic SSH changes in the subtropical North Atlantic are already influencing the frequency of flooding events along the U.S. southeast coast, including the Gulf of Mexico. We show that these sea-level changes are mainly due to changes in Oceanic Heat Content (OHC), and we use an ocean-circulation model constrained by observations to demonstrate that heat advection is the dominant term in the subtropical North Atlantic heat budget. We thus establish a link between the AMOC-driven gyre-scale ocean heat convergence and coastal-flood risk. The key hypothesis behind this study is that the AMOC plays an important role in the development of anomalous large-scale OHC and sea level patterns, which, in turn, affect the coastal sea level and the frequency of floods. For example, it has recently been shown that the tripole explains up to 60–80% of the interannual coastal sea level variance along the U.S. southeastern seaboard 33 . The amplitudes of the tripole-related coastal sea level changes, obtained by regressing tide gauge records on the PC 1 of the altimetric SSH (Methods), are small (0–2 cm) at the tide gauges situated to the north of Cape Hatteras, but they sometimes exceed 10 cm at the tide gauges located to the south of Cape Hatteras and in the Gulf of Mexico (Fig. 3a ). a The locations of tide gauges and the amplitude of the tripole-related SSH changes at these tide gauges (colored circles). An insert shows (black) the Global Mean Sea Level (GMSL) change and (other color curves) the tripole-related SSH time series at several tide gauges. The vertical error bar in the insert shows the 95% confidence interval for regression. By regressing tide gauge measurements on the temporal evolution of the tripole, we have shown that the tripole is most influential south of Cape Hatteras and in the Gulf of Mexico, where the tripole-related coastal sea level changes can reach amplitudes of about 10 cm, which is close to the GMSL rise magnitude over the last 30 years. Together with the GMSL rise and the seasonal SSH variability, the tripole-related interannual-to-decadal SSH changes provide background conditions for larger-amplitude synoptic and tidal fluctuations. This study provides observational evidence that tripole-related SSH changes impact the frequency of floods. The first two terms on the right side of (1) determine ocean heat convergence between 26°N and 41°N. The seasonal cycle was subtracted from the budget terms and the residual time series were low-pass filtered with a cutoff period of 1.5 years (Fig. 2c ). To investigate how the gyre-scale ocean variability affects coastal sea level and flood risk, we analyzed hourly records from 43 National Oceanic and Atmospheric Administration (NOAA) tide gauges along the U.S. east coast from Maine to Texas (Fig. 3a ), available from NOAA’s National Ocean Service ( https://oceanservice.noaa.gov/ ). 3a were computed as the half-range of the tripole-related sea level changes at tide gauges. We used the up-to-date minor flood threshold water levels published in a NOAA Technical Report 9 . A day was counted as a flood day when the hourly averaged water level exceeded the minor flood threshold at least once in 24 h. The expected exceedances in Fig. 4 show the number of days per year, during which water levels exceeded a particular value above the MHHW.

The rising sea levels due to climate change are a significant concern, particularly for vulnerable, low-lying coastal regions like the Gulf of Guinea (GoG). To effectively address this issue, it is crucial to gain a comprehensive understanding of historical sea level variability, and the influencing factors, and develop a reliable modeling system for future projections. This knowledge is essential for informed planning and mitigation strategies aimed at protecting coastal communities and ecosystems. This study presents a comprehensive analysis of mean sea level anomaly (MSLA) trends in the GoG between 1993 and 2020, covering three distinct periods (1993-2002, 2003-2012, and 2013-2020). It investigates the connections between interannual sea level variability and large-scale oceanic and atmospheric forcings. Furthermore, the study evaluates the performance of supervised machine learning techniques to optimize sea level modeling. The findings reveal a consistent rise in MSLA linear trends across the basin, particularly pronounced in the northern region, with a total linear trend of 88 mm over the entire period. The highest decadal trend (38.7 mm) emerged during 2013-2020, with the most substantial percentage increment (100%) occurring in 2003-2012. Spatial variation in decadal sea-level trends was influenced by subbasin physical forcings. Strong interannual signals in the spatial sea level distribution were identified, linked to large-scale oceanic and atmospheric phenomena. Seasonal variations in sea level trends are attributed to seasonal changes in the forcing factors. The evaluation of supervised learning modeling methods indicates that Random Forest Regression and Gradient Boosting Machines are the most accurate, reproducing interannual sea level patterns in the GoG with 97% and 96% accuracy. These models could be used to derive regional sea level projections via downscaling of climate models. These findings provide essential insights for effective coastal manage Seasonal variations in sea level trends are attributed to seasonal changes in the forcing factors. The evaluation of supervised learning modeling methods indicates that Random Forest Regression and Gradient Boosting Machines are the most accurate, reproducing interannual sea level patterns in the GoG with 97% and 96% accuracy. These models could be used to derive regional sea level projections via downscaling of climate models. These findings provide essential insights for effective coastal management and climate adaptation strategies in the GoG. Subject terms Ocean sciences Physical oceanography pmc-status-qastatus 0 pmc-status-live yes pmc-status-embargo no pmc-status-released yes pmc-prop-open-access yes pmc-prop-olf no pmc-prop-manuscript no pmc-prop-legally-suppressed no pmc-prop-has-pdf yes pmc-prop-has-supplement no pmc-prop-pdf-only no pmc-prop-suppress-copyright no pmc-prop-is-real-version no pmc-prop-is-scanned-article no pmc-prop-preprint no pmc-prop-in-epmc yes pmc-license-ref CC BY issue-copyright-statement © Springer Nature Limited 2023 Introduction Climate change is a pressing global concern, with its escalating impacts significantly affecting sea levels 1 . The examination of regional sea level variability and the identification of its driving factors are of paramount importance in understanding the consequences of climate change on coastal areas 2 . The range of sea level variability encompasses a wide spectrum of challenges, with profound implications for coastal communities, infrastructure, and marine ecosystems. These challenges encompass elevated storm surges, coastal erosion, flooding, saltwater intrusion, disruption of marine ecosystems, and infrastructure damage, all of which carry substantial economic implications. This division was based on the need to capture and analyze long-term trends while avoiding the potential masking of significant shorter-term variability. This approach allows us to distinguish between gradual, sustained changes and shorter-term variations, and to assess how sea level variability and its drivers have evolved over time. In general, analysis of MSLA variability revealed a distinct spatial and temporal pattern across the basin, which was significantly influenced by subbasin-scale drivers. AMOC is a powerful oceanic current system that plays a crucial role in regulating the climate in the Atlantic by transporting warm surface water northward and cold deep water southward 26 . The temperature distribution by AMOC consequently affects the sea level variability as observed in EOF3 (Fig. 4 C). Seasonal variability Analysis of the spatial seasonal variability of MSLA in the GoG, as depicted in Fig. 5 , shows a distinct spatial seasonal variability of sea level across the basin. The northern basin, which has the highest MSLA distribution throughout the seasons compared to the southern This result is consistent with the interannual variability of MSLA in the GoG, as observed in PC3. While the variability in the AMOC has been linked to the sea level variability in the GoG 35 , to the best of our knowledge, no research has reported the interannual variability of AMOC in the GoG. Therefore, the work of Moat et al. could offer valuable comparative insights, as most of the variability in AMOC originates from the tropical Atlantic. Furthermore, seasonal variability in sea level trends emerged due to seasonal changes in forcing factors. Parameterization TSLA and HSLA were computed using the Thermodynamic Equation Of Seawater 2010 (TEOS-10), which comprises a set of standardized equations for determining the thermodynamic properties of seawater. TSLA and HSLA account for the individual impact of temperature and salinity, respectively, which can cause expansion or contraction of sea level depending on their respective values at a specific location and time. Their combined impact forms the steric sea level anomaly (SSLA), which measures how changes in water density affect the sea level.

underlying land, and when the ice melts away the land slowly rebounds. Changes in ground-based ice volume also affect local and regional sea levels by the readjustment Mean sea level (MSL, often shortened to sea level) is an average surface level of one or more among Earth's coastal bodies of water from which heights such as elevation may be measured. The global MSL is a type of vertical datum – a standardised geodetic datum – that is used, for example, as a chart datum in cartography and marine navigation, or, in aviation, as the standard sea level at which atm P… Local mean sea level (LMSL) is defined as the height of the sea with respect to a land benchmark, averaged over a period of time long enough that fluctuations caused by waves and tides are smoothed out, typically a year or more. One must adjust perceived changes in LMSL to account for vertical movements of the land, which can occur at rates similar to sea level changes (millimetres per year). Some land movements occur because of isostatic adjustment to the melting of ice sheets at the end of the last ice age. The weight of the ice sheet depresses the underlying land, and when the ice melts away the land slowly rebounds. Changes in ground-based ice volume also affect local and regional sea levels by the readjustment of the geoid and true polar wander. Atmospheric pressure, ocean currents and local ocean temperature changes can affect LMSL as well. Eustatic sea level change (global as opposed to local change) is due to change in either the volume of water in the world's oceans or the volume of the oceanic basins. Two major mechanisms are currently causing eustatic sea level rise. First, shrinking land ice, such as mountain glaciers and polar ice sheets, is releasing water into the oceans. Second, as ocean temperatures rise, the warmer water expands. Precise determination of a "mean sea level" is difficult because of the many factors that affect sea level. Instantaneous sea level varies substantially on several scales of time and space. This is because the sea is in constant motion, affected by the tides, tsunamis, wind, atmospheric pressure, local gravitational differences, temperature, salinity, and so forth. The mean sea level at a particular location may be calculated over an extended time period and used as a datum. For example, hourly measurements may be averaged over a full Metonic 19-year lunar cycle to determine the mean sea level at an official tide gauge. Still-water level or still-water sea level (SWL) is the level of the sea with motions such as wind waves averaged out. Then MSL implies the SWL further averaged over a period of time such that changes due to, e.g., the tides, also have zero mean. Global MSL refers to a spatial average over the entire ocean area, typically using large sets of tide gauges and/or satellite measurements. One often measures the values of MSL with respect to the land; hence a change in relative MSL or (relative sea level) can result from a real change in sea level, or from a change in the height of the land on which the tide gauge operates, or both. In the UK, the ordnance datum (the 0 metres height on UK maps) is the mean sea level measured at Newlyn in Cornwall between 1915 and 1921. Before 1921, the vertical datum was MSL at the Victoria Dock, Liverpool. Since the times of the Russian Empire, in Russia and its other former parts, now independent states, the sea level is measured from the zero level of Kronstadt Sea-Gauge. In Hong Kong, "mPD" is a surveying term meaning "metres above Principal Datum" and refers to height of 0.146 m (5.7 in) above chart datum and 1.304 m (4 ft 3.3 in) below the average sea level. In France, the Marégraphe in Marseille measures continuously the sea level since 1883 and offers the longest collated data about the sea level. It is used for a part of continental Europe and the main part of Africa as the official sea level. Spain uses the reference to measure heights below or above sea level at Alicante, while the European Vertical Reference System is calibrated to the Amsterdam Peil elevation, which dates back to the 1690s. Satellite altimeters have been making precise measurements of sea level since the launch of TOPEX/Poseidon in 1992. A joint mission of NASA and CNES, TOPEX/Poseidon was followed by Jason-1 in 2001 and the Ocean Surface Topography Mission on the Jason-2 satellite in 2008. Local mean sea level (LMSL) is defined as the height of the sea with respect to a land benchmark, averaged over a period of time long enough that fluctuations caused by waves and tides are smoothed out, typically a year or more. One must adjust perceived changes in LMSL to account for vertical movements of the land, which can occur at rates similar to sea level changes (millimetres per year). Some land movements occur because of isostatic adjustment to the melting of ice sheets at the end of the last ice age. The weight of the ice sheet depresses the underlying land, and when the ice melts away the land slowly rebounds. Changes in ground-based ice volume also affect local and regional sea levels by the readjustment of the geoid and true polar wander. Atmospheric pressure, ocean currents and local ocean temperature changes can affect LMSL as well. Eustatic sea level change (global as opposed to local change) is due to change in either the volume of water in the world's oceans or the volume of the oceanic basins. Two major mechanisms are currently causing eustatic sea level rise. First, shrinking land ice, such as mountain glaciers and polar ice sheets, is releasing water into the oceans. Second, as ocean temperatures rise, the warmer water expands. Sea Level Rise:Understanding the past – Improving projections for the future Permanent Service for Mean Sea Level Global sea level change: Determination and interpretation Environment Protection Agency Sea level rise reports Properties of isostasy and eustasy Measuring Sea Level from Space Rising Tide Video: Scripps

Climate change affects different places in different ways. In Africa, droughts may get worse. In the Atlantic Ocean, hurricanes may become stronger. Changing rainfall patterns may harm farming and water supplies. Scientists study past climates, using ice cores, tree rings, and ocean sediments to learn how Earth’s climate has changed before. The Intergovernmental Panel on Climate Change (IPCC) brings together scientists from all over the world to study climate change and give advice to governments. Understanding how Earth’s atmosphere works helps us find solutions, such as cutting greenhouse gas emissions, planting more trees to absorb carbon, or using new technologies to cool the planet. Astronomy: Earth in Space Astronomy, when connected to Earth science, helps us understand how Earth fits into the larger universe. It looks at how objects in space, like the Sun, the Moon, and the planets, affect life on Earth. These celestial events play a big role in shaping things like our climate, seasons, tides, and even some geological processes such as how the Earth’s crust behaves over time. For example, Earth’s orbit around the Sun and its tilted axis are what cause the seasons.

In the idealized (and, as we shall see, oversimplified) model just described, the height of the tides would be only a few feet. The rotation of Earth would carry an observer at any given place alternately into regions of deeper and shallower water. An observer being carried toward the regions under or opposite the Moon, where the water was deepest, would say, “The tide is coming in”; when carried away from those regions, the observer would say, “The tide is going out.” During a day, the observer would be carried through two tidal bulges (one on each side of Earth) and so would experience two high tides and two low tides. The Sun also produces tides on Earth, although it is less than half as effective as the Moon at tide raising. The actual tides we experience are a combination of the larger effect of the Moon and the smaller effect of the Sun. When the Sun and Moon are lined up (at new moon or full moon), the tides produced reinforce each other and so are greater than normal (Figure 4.19). These are called spring tides (the name is connected not to the season but to the idea that higher tides “spring up”).