Sea Level Anomalies Research Articles

The Influence of Typhoon-Induced Wave on the Mesoscale Eddy

The strong wind-induced current and sea level have influences on the wave distribution in a tropical cyclone (TC). In particular, the wave–current interaction is significant in the period in which the TC passed the mesoscale eddy. In this study, the wave fields of Typhoon Chan-hom (2015) are hindcastly simulated using a coupled oceanic model that utilizes a nested triangle grid, i.e., the finite-volume community ocean model-simulating waves nearshore (FVCOM-SWAVE) model. The forcing wind field is composited from the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis data and the simulation using a parametric Holland model, denoted as H-E. The open boundary fields include tide data from TPOX.5 and the hybrid coordinate ocean model (HYCOM) global datasets, including sea surface temperature (SST), sea surface salinity, sea surface current, and sea level data. The simulated oceanic parameters (e.g., the significant wave height, SWH) are validated against the measurements from the Jason-2 altimeter, yielding a root mean square error (RMSE) of 0.58 m for the SWH, a correlation (COR) coefficient of 0.94, and a scatter index (SI) of 0.23. Similarly, the simulated SSTs are compared with the remote sensing products of the remote sensing system (REMSS) and the measurements from Argos, yielding an RMSE of <0.8 °C, a COR of >0.95, and an SI of <0.04. The significant zonal asymmetry of the wave distribution along the typhoon track is observed. The Stokes drift is calculated from the FVCOM-SWAVE simulation results, and then the contribution of the Stokes transport is estimated using the Ekman–Stokes numbers. It is found that the ratio of the Stokes transport to the total net transport can reach >80% near the typhoon center, and the ratio is reduced to approximately <20% away from the typhoon center, indicating that Stokes transport is an essential aspect in the water mixing during a TC. The mesoscale eddies are detected by the sea level anomalies (SLA) fusion data from AVISO. It is found that the significant wave heights, Stokes drift, and Stokes transport inside the eddy area were higher than those outside the eddy area. These parameters inside the cold mesoscale eddies were higher than t inside the warm mesoscale eddies. Otherwise, the SST mainly increased within the cold mesoscale eddies area, while decreased within the warm mesoscale eddies area. The influence of mesoscale eddies on the SST was in proportion to the eddy radius and eddy EKE.

Modeling Extreme Water Levels in the Salish Sea: The Importance of Including Remote Sea Level Anomalies for Application in Hydrodynamic Simulations

Extreme water-level recurrence estimates for a complex estuary using a high-resolution 2D model and a new method for estimating remotely generated sea level anomalies (SLAs) at the model boundary have been developed. The hydrodynamic model accurately resolves the dominant physical processes contributing to extreme water levels across the Washington State waters of the Salish Sea, including the relative contribution of remote SLA and other non-tidal residual processes that drive extreme water levels above the predicted tide. The model’s predictions have errors of less than 15 cm (<5% of 3–4 m tidal range) at eight tide gauge locations across the model domain. The influence of remote SLAs at the seaward boundary of the model was implemented using a multivariate regression of readily available and locally relevant wind, sea surface temperature, and pressure anomaly data, combined with El Niño Index data (R2 = 0.76). The hydrodynamic model simulations using the remote SLA predictor compared well with simulations using the widely used data-assimilative global ocean model HYCOM SLA data (root mean square difference of 5.5 cm). Extreme water-level recurrence estimates with and without remote SLA show that remote forcing accounts for 50–60% of the total water level anomaly observed along Salish Sea shorelines. The resulting model simulations across decadal timescales provide estimates of extreme water level recurrence across the Salish Sea, capturing climate variability important to long-term coastal hazard planning. This approach has widespread applications for other complex estuarine systems.

Explained predictions of strong eastern Pacific El Niño events using deep learning

Global and regional impacts of El Niño-Southern Oscillation (ENSO) are sensitive to the details of the pattern of anomalous ocean warming and cooling, such as the contrasts between the eastern and central Pacific. However, skillful prediction of such ENSO diversity remains a challenge even a few months in advance. Here, we present an experimental forecast with a deep learning model (IGP-UHM AI model v1.0) for the E (eastern Pacific) and C (central Pacific) ENSO diversity indices, specialized on the onset of strong eastern Pacific El Niño events by including a classification output. We find that higher ENSO nonlinearity is associated with better skill, with potential implications for ENSO predictability in a warming climate. When initialized in May 2023, our model predicts the persistence of El Niño conditions in the eastern Pacific into 2024, but with decreasing strength, similar to 2015–2016 but much weaker than 1997–1998. In contrast to the more typical El Niño development in 1997 and 2015, in addition to the ongoing eastern Pacific warming, an eXplainable Artificial Intelligence analysis for 2023 identifies weak warm surface, increased sea level and westerly wind anomalies in the western Pacific as precursors, countered by warm surface and southerly wind anomalies in the northern Atlantic.

Sea level anomalies affect the ocean circulation at abyssal depths

Abyssal channels are the key points controlling bottom circulation of the World Ocean. They provide meridional transport of the coldest Antarctic Bottom Water between deep-water basins influencing the meridional overturning circulation and the climate on a global scale. Here we show that the synoptic variability of deep-water flows including blocking abyssal currents between deep ocean basins is related to sea level anomalies observed over the channels. Our results demonstrate that processes at the ocean surface have a more significant connection with the bottom circulation than it was considered earlier. This study opens a discussion of the importance of mesoscale eddies and air-sea interactions on water exchange between abyssal basins, meridional heat transport in the ocean, and possible responses of the ocean to the observed sea level rise in a changing climate.

Statistical analysis of dynamic behavior of continental shelf wave motions in the northern South China Sea

Abstract. This study aims to analyze statistical behavior of the continental shelf wave motions, including continental shelf waves (CSWs) and arrested topographic waves (ATWs), in the northern South China Sea. The baseline consists of tide-gauge data from stations Kanmen, Xiamen, Shanwei, and Zhapo as well as along-track sea level anomaly (SLA) data derived from multiple satellite altimeters from 1993 to 2020. The subtidal signals propagating along the coast with periods shorter than 40 d and phase speeds of about 10 m s−1 are interpreted as CSWs. The cross-shelf structure of along-track SLAs indicates that Mode 1 of CSWs is the predominant component trapped in the area shallower than about 200 m. The amplitudes of CSWs reach a maximum of 0.6 m during July–September and a minimum of 0.2 m during April–June. The inter-seasonal and seasonal signals represent ATWs. The amplitudes of ATWs reach 0.10 m during October–December, twice that during July–September. These observations can be well interpreted in the framework of linear wave theory. The cross-shelf structures of CSWs and ATWs derived from along-track SLAs illustrate that the methods are suitable for observing dynamic behavior of the CSWs.

Diagnostic Analysis of the Response of Volume Transport through the Tsushima Strait to the Eddy-Induced Variations in the Kuroshio Region

Abstract The Tsushima Strait (TS) is the sole passage for volume transport from the East China Sea to the Sea of Japan. To date, the process underlying the interannual variability in volume transport remains unclear. In this study, 27-yr (1993–2019) reanalysis data from the Japan Coastal Ocean Predictability Experiment 2 (JCOPE2M) system and in situ/satellite observations were employed to understand this process. The results suggest that TS transport was generally high in 1999, 2003/04, and 2010 and low in 1995/96, 2005/06, 2008, and 2014/15. The sea level anomaly (SLA) outside the entrance of the TS, that is, the upstream TS forcing, dominates the interannual TS transport variation. A high SLA pumps more water into the Sea of Japan via the TS, and vice versa. By synthesizing JCOPE2M reanalysis data and satellite observations, further analysis revealed that cyclonic mesoscale eddies from the subtropical countercurrent (STCC) could be responsible for this high SLA by reducing Kuroshio transport, enhancing Kuroshio intrusion across the shelf, and increasing the SLA around the upstream TS region. The reverse was true for anticyclonic STCC eddies. Variability in the Kuroshio intrusion southwest of Kyushu induces variations in the TS transport on an interannual time scale.

Sea-level trends and variability along the coast of Vietnam over 2002–2018: Insights from the X-TRACK/ALES altimetry dataset and coastal tide gauges

The changes in coastal sea levels are now considered a significant concern for densely-populated coastal regions such as Vietnam, which hosts a long coastline and two large deltaic areas. In this study, we used high-resolution (20-Hz) altimetry data from the X-TRACK/ALES product to investigate the trends and variability of sea-level anomalies (SLAs) along the Vietnam coast from 2002 to 2018. We conducted comparisons of SLAs from X-TRACK/ALES with SLAs from four coastal tide gauges, and the results present a good root mean square error (0.03 m on average) and good statistically significant correlation (for p < 0.05) with an average value of 0.66. There is an exception for the Quy Nhon site (r ∼ 0.5) as its closest altimetry points lie in the open ocean. Regarding trend calculations, the tide gauge sites exhibit two-to-three times larger trends than altimetry points, indicating a significant deviation from the coast to the open ocean. We then examined the contribution of various forcing factors by stepwise regression analysis for the 2002 – 2018 and 2008–2018 periods. The stepwise model can explain the observed data in the latter period (about 63 % on average). As local factors, SST and meridional wind stress appear important, whereas PDO and ENSO are significant as remote factors, particularly at the southern sites. However, we could not find the best common forcing factors for all sites suggesting the inconsistent mechanisms causing sea-level variability along the Vietnam coast. Our study demonstrates complicated regional sea-level variability and emphasizes the benefit of high-resolution altimetry data in studying dynamic coastal regions.

Intra-Seasonal Variability of Sea Level on the Southwestern Bering Sea Shelf and Its Impact on the East Kamchatka and East Sakhalin Currents

The East Kamchatka and East Sakhalin Currents (EKC and ESC) are the western boundary currents of the subarctic North Pacific and Okhotsk Sea. Variability in the EKC and ESC velocities could exert a substantial effect on ecosystems and fish stocks in the southwestern Bering Sea and Okhotsk Sea. Using satellite-derived data (sea surface heights, geostrophic current velocities, and sea surface temperatures, 2002–2020), we demonstrate that changes in zonal wind generate sea level variations on the shelf in the southwestern Bering Sea over a period of 18–29 days and with an amplitude of 5–20 cm. The ebb/flood events on the shelf lead to changes in the velocity, direction, and position of the EKC. The sea level anomalies propagate along the western Kamchatka, northern Kuril Islands and the northern and western Okhotsk Sea and result in the variability of geostrophic current velocities in the ESC zone. The strengthening (weakening) of ESC leads to an increase (a decrease) in SST in the southern part of the Okhotsk Sea by 1–3 °C. In the northwestern Okhotsk Sea, in addition to wind-induced variability, there are temporary changes in the geostrophic currents with a period of 14 days caused by fortnightly tides.

In Situ Validation of Altimetry and CFOSAT SWIM Measurements in a High Wave Environment

Abstract While satellite altimeters have revolutionized ocean science, validation measurements in high wave environments are rare. Using geodetic Global Navigation Satellite System (GNSS) data collected from the Southern Ocean Flux Station (SOFS; −47°S, 142°E) since 2019, as part of the Southern Ocean Time Series (SOTS), we present a validation of satellite missions in this energetic region. Here we show that high rate GNSS observations at SOFS can successfully measure waves in the extreme conditions of the Southern Ocean and obtain robust measurements in all wave regimes [significant wave height (SWH) ranging from 1.5 to 12.6 m]. We find good agreement between the in situ and nadir altimetry SWH (RMSE = 0.16 m, mean bias = 0.04 m, and n = 60). Directional comparisons with the Chinese–French Ocean Satellite (CFOSAT) Surface Waves Investigation and Monitoring (SWIM) instrument also show good agreement, with dominant directions having an RMSE of 9.1° (n = 22), and correlation coefficients between the directional spectra ranging between 0.57 and 0.79. Initial sea level anomaly (SLA) estimates capture eddies propagating through the region. Comparisons show good agreement with daily gridded SLA products (RMSE = 0.03 m, and n = 205), with scope for future improvement. These results demonstrate the utility of high rate geodetic GNSS observations on moored surface platforms in highly energetic regions of the ocean. Such observations are important to maximize the geophysical interpretation from altimeter missions. In particular, the ability to provide collocated directional wave observations and SLA estimates will be useful for the validation of the recently launched Surface Water and Ocean Topography (SWOT) mission where understanding the interactions between sea state and sea surface height poses a major challenge.

The DTU21 global mean sea surface and first evaluation

Abstract. A new mean sea surface (MSS) from the Technical University of Denmark (DTU) called DTU21MSS for referencing sea-level anomalies from satellite altimetry is introduced in this paper, and a suite of evaluations are performed. One of the reasons for updating the existing mean sea surface is the fact that during the last 6 years, nearly 3 times as many data have been made available by space agencies, resulting in more than 15 years of altimetry from long-repeat orbits (LROs) or geodetic missions. This includes the two interleaved long-repeat cycles of Jason-2 with a systematic cross-track distance as low as 4 km. A new processing chain with updated filtering and editing has been implemented for the DTU21MSS. This way, the DTU21MSS has been computed from 2 Hz altimetry in contrast to the former DTU15MSS and DTU18MSS which were computed from 1 Hz altimetry. The new DTU21MSS is computed over the same 20-year averaging time from 1 January 1993 to 31 December 2012 with a well-specified central time of 1 January 2003 and is available from https://doi.org/10.11583/DTU.19383221.v1 (Andersen, 2022). Cryosat-2 employs synthetic aperture radar (SAR) and SAR interferometric (SARin) modes in a large part of the Arctic Ocean due to the presence of sea ice. For SAR- and SARin-mode data we applied the SAMOSA+ physical retracking to make it compatible with the physical retracker used for conventional low-resolution-mode data in other parts of the ocean.

Impact of tropical Indian Ocean warming on the surface phytoplankton biomass at two significant coastal upwelling zones in the Arabian Sea

The Sea Surface Temperature (SST) of the Arabian Sea undergoes large seasonal variations owing to the monsoonal forcing and upwelling. Warming of the ocean adversely affects its biological productivity. The present study examined the role of the rapid warming of the tropical Indian Ocean and associated changes in physical forcing parameters on phytoplankton biomass in the Arabian Sea. SST during the summer monsoon period (June-September) of 1971–2020 showed an increasing trend of 0.6 °C in the southeastern Arabian Sea (SEAS) and 1.6 °C in the northwestern Arabian Sea. During the recent summer monsoon period of 1998–2020, surface chlorophyll-a (chl-a) concentration showed a decreasing trend of – 0.32 mg m−3 in the SEAS and an increasing trend of 0.56 mg m−3 in the northwestern Arabian Sea. High-resolution satellite and reanalysis data of physical forcing parameters such as surface winds, SST, Sea Level Anomaly (SLA) that influence the surface chl-a concentration at two distinct upwelling locations in the Arabian Sea, were analysed for the recent two decades (1998–2020). Multiple linear regression (MLR) analysis showed that SLA was the most important parameter that determines the surface chl-a variability in the SEAS, whereas alongshore wind stress was dominant in the northwestern Arabian Sea. An epochal analysis showed that in the most recent decade, SLA in the SEAS became less favourable for upwelling, whereas summer monsoon winds became increasingly favourable for upwelling in the northwestern Arabian Sea. These differences corroborate the contrasting trends in surface chl-a in the two locations in the Arabian Sea. The present study has shown that the inconsistent response of surface chl-a at distinct locations within the Arabian Sea depends on the relative strength of the influencing physical forcing mechanisms.

Characterizing the Variability of a Physical Driver of North Atlantic Right Whale Foraging Habitat Using Altimetric Indices

Physical ocean circulation features, especially the Gaspé Current (GC) intrusion, influence the transport and aggregation of whale prey, thereby influencing the whale foraging habitat in the Gulf of St. Lawrence (GSL), Canada. We employ satellite altimetry-derived sea level anomaly (SLA) indices to monitor interannual variations in the intensity of the GC in the North Atlantic Right Whale (Eubalaena glacialis; NARW) habitat in the GSL. Measurements of surface slope and volume transport are taken from the SLA profiles along a repeating ground track of the Jason-2/3 satellites. These are employed as complementary proxies in characterizations of physical processes in the GSL. The relationship between altimetric indices and indices of zooplankton abundance are explored in the southern GSL. Results demonstrate that an altimetric index estimated from surface slope (Indexslope−half) is correlated with river discharge of the St. Lawrence River and can be utilized to infer variations in GC intensities. Time series of the altimetric indices during 2009–2021 are found to exhibit interannual and seasonal environmental variability, which influence transport into the southern GSL. As captured by the altimetric indices, these features of the surface ocean circulation can be linked to zooplankton variations in the Shediac Valley, where NARWs are frequently observed. Therefore, in linking physical drivers of ocean dynamics to the NARW foraging habitat, variations in these indices can also potentially help describe some features of the distribution patterns of NARW sightings in this area.

Analysis of mesoscale Eddy in the Nordic seas and Barents Sea using multi-satellite data

Under the background of climate change, the characteristics of meso-scale eddies (radius > 20 km) in the Nordic Sea are worthy of further study. In this study, the daily sea level anomaly (SLA) product provided by archiving, validation, and interpretation of satellite oceanographic data (AVISO) and the daily sea surface temperature (SST) data provided by remote sensing systems (REMSSs) were collected from January 2003 to December 2021. The collected data were daily averaged with a spatial grid resolution of 0.25°. The large-scale eddies with a radius of >80 km and activity intensity (EKE) values of >0.02 m2/s were more detectable using SST data Moreover, the spatial distribution between the SLA-based and SST-based eddies had the opposite correlation with respect to the water depth. The SST-based eddies were more sensitive to seasonal variations. The long-term variations in the eddy parameters and the North Atlantic Oscillation Index (NAOI) during 2003–2021 were studied, and it was found that the radius of the SLA-based eddies was likely consistent with the NAOI and the EKE of the SLA-based eddies has the highest correlation (=0.2) with the NAOI, however, the correlation between eddy parameters and the NAOI is not significant. Collectively, SLA data has good performance on eddy identification in most cases, while SST data is suitable for investigating the activities of mesoscale eddies with large radius (> 80 km) and strong EKE (>0.02 m2/s).

The Rossby Normal Mode as a Physical Linkage in a Machine Learning Forecast Model for the SST and SSH of South China Sea Deep Basin

AbstractMachine learning (ML) has been widely applied in Earth sciences, but its black‐box nature still remains. Existing techniques for interpretable ML developed by deep learning researchers are not satisfactory in understanding physical problems. In this study, our objective is to establish the physical linkage between features extracted from ML model and results derived from physical equations that describe the problem. This approach aims to provide a more comprehensible way of understanding an ML model. We select a less complex ML forecasting model, consisting of traditional statistical algorithms, which effectively forecast sea surface temperature anomaly (SSTA) and sea level anomaly (SLA) of the South China Sea (SCS) in 30 days ahead. Here, we focus on the SLA prediction and detect the physical mechanism of model capability to predict SCS SLA. Previous study has identified Rossby normal modes as the physical mechanism for long‐lived eddies in SCS in previous study. We here demonstrate the relationship between the ML model and Rossby normal modes in SCS in terms of temporal variations and spatial distributions of water mass. The model's skill in predicting Rossby normal modes partially explains its skill in predicting SLA, thereby providing a more transparent and interpretable basis for forecasts in SCS.

Utilization of Jason-3 Satellite Altimetry Data for Observation of TC Seroja

The Jason-3 Satellite Altimetry has two main instruments: the Poseidon-3B Altimeter and the Advanced Microwave Radiometer. The two sensors produce many output data. Satellite altimetry data commonly used to observe TC are Sea Level Anomaly (SLA) and Significant Wave Height (SWH). This research tries something new by adding three other data, namely Precipitable Water Vapor (PWV), Liquid Water Content (LWC), and Wind Speed (WS). The object of this research is TC Seroja which occurred from 2 to 12 April 2021. This research was conducted to obtain all variable’s spatial and temporal profiles. The results of this study indicate that TC Seroja causes an increase in SLA, PWV, SWH, LWC, and WS. The highest SLA was 0.495 m, SWH was 4.649 m, PWV was 0.10760 m, LWC was 2.08 kg/m2, and WS was 18.42 m/s. In addition, the spatial model for the five variables in April 2021 obtained using IDW (Inverse Distance Weighting) can also provide information on the influence of TC in various places.

Assessment and exploitation of coastal low resolution mode sea level data from CryoSat-2 on the entrance to the Gulf of California

The CryoSat-2 mission (CS2), initially conceived for sea ice measurements, is also useful for sea level monitoring in oceanic and coastal areas. Only specific regions have two high resolution modes (SAR Delay/Doppler and SAR-Interferometric modes), while the rest of the areas are measured in low-resolution mode (LRM). The entrance to the Gulf of California presents this mode of operation. Sea Level Anomalies (SLA) obtained from CS2 are compared with tide gauges at three locations, Cabo San Lucas (CSL) south of the Baja California peninsula, Mazatlán (MZ) and San Blas (SB) on the continental margin. The comparison shows good agreement between SLAs in CSL and MZ, with standard deviations of the differences (SDD) lower than 0.09 m and Pearson’s correlations higher than 0.7 (95% of confidence level). San Blas is in a complex location and with less data, presenting an SDD greater than 0.13 m and a correlation below 0.55. We present the cross-shore seasonal and interannual variability in CSL and MZ using the CS2 SLA time series from 2011 to 2020. The variability shows the presence of events such as El Niño (2015 to early 2016), La Niña (2011) and the warm event of 2014 (nicknamed “the Blob”). Additionally, the residual time series of CS2 obtained after extracting the annual, semi-annual and monthly components, shows the East side (at MZ) is more affected by El Niño/La Niña variability while the West side (at CSL) is more influenced by the Blob/El Niño. Estimated long-term SLA trend at both locations are around 3.1 mm/yr, supporting similar findings by previous studies.

Analisis Kenaikan Muka Air Laut di Belawan

Climate change can cause an increase in sea temperatures which will have an impact on sea level rise due to the expansion of sea water volume and melting ice at the poles. Rising sea levels pose a threat to areas in coastal and coastal areas, one of which is Medan Belawan District. One of the impacts is tidal flooding. Tidal floods caused by high tides are then exacerbated by the phenomenon of rising sea levels so that it becomes a factor in increasing tidal flood inundation. The purpose of this study is to analyze sea level rise in Medan Belawan District by processing tidal data for 2012-2022 and sea level anomalies for 1993-2022 in the rate of sea level rise. The method used to calculate the tidal component uses the Admiralty method, sea level rise uses the linear regression method. The results of this study show that the value of sea level rise based on tidal data is 0.22 mm/year and 4.5 mm/year based on altimetry satellite data.

Sea level variability and coastal inundation over the northeastern Mediterranean Sea

ABSTRACT Sea level is a key element of global-scale climatic changes with significant coastal impacts. The northeastern Mediterranean Sea (Aegean, Ionian, and Cretan Seas: AICS) consists of extended low-lying coastal zones exposed to coastal inundation due to seawater level increases. The variability of the Sea Level Anomaly (SLA) in the AICS has been evaluated with the use of satellite-derived observations from 1993 to 2021. The general SLA trend over the AICS domain was 3.6 mm/year, which is higher than that of the overall Mediterranean Sea. The coastal inundation variability along the AICS coastline, specifically in 20 characteristic study areas, was investigated based on the long-term satellite-derived sea level observations, high-resolution land elevation data, and numerical simulations, conducted with a coastal inundation (CoastFLOOD) model. The coastal zones were categorized based on the frequency of occurrence and percentage coverage of flooding incidents during the 29-year period, while the interannual trends and the seasonality of inundated littoral and inland areas also showed intense spatial variation. High flooding levels occurred at coastal areas of either extended low-lying areas and/or high sea level elevations. The coastal zones were categorized based on a heuristic Coastal Inundation Hazard Index (CIHI: 1–5 ranking) that was determined by the occurrence frequency of severe floods (temporal component) and their impact area (spatial component). Our study findings provide vital information about the coastal inundation conditions and the respective hazard level of the AICS, useful to support enhanced coastal zone management for the improvement of coastal protection and decisions about coastal hazards’ mitigation.

The Iceland–Faroe warm-water flow towards the Arctic estimated from satellite altimetry and in situ observations

Abstract. The inflow of warm and saline Atlantic water to the Arctic Mediterranean (Nordic Seas and Arctic Ocean) between Iceland and the Faroes (IF inflow) is the strongest Atlantic inflow branch in terms of volume transport and is associated with a large transport of heat towards the Arctic. The IF inflow is monitored in a section east of the Iceland–Faroe Ridge (IFR) by use of sea level anomaly (SLA) data from satellite altimetry, a method that has been calibrated by in situ observations gathered over 2 decades. Monthly averaged surface velocity anomalies calculated from SLA data were strongly correlated with anomalies measured by moored acoustic Doppler current profilers (ADCPs) with consistently higher correlations when using the reprocessed SLA data released in December 2021 rather than the earlier version. In contrast to the earlier version, the reprocessed data also had the correct conversion factor between sea level slope and surface velocity required by geostrophy. Our results show that the IF inflow crosses the IFR in two separate branches. The Icelandic branch is a jet over the Icelandic slope with average surface speed exceeding 20 cm s−1, but it is narrow and shallow with an average volume transport of less than 1 Sv (106 m3 s−1). Most of the Atlantic water crosses the IFR close to its southernmost end in the Faroese branch. Between these two branches, water from the Icelandic branch turns back onto the ridge in a retroflection with a recirculation over the northernmost bank on the IFR. Combining multi-sensor in situ observations with satellite SLA data, monthly mean volume transport of the IF inflow has been determined from January 1993 to December 2021. The IF inflow is part of the Atlantic Meridional Overturning Circulation (AMOC), which is expected to weaken under continued global warming. Our results show no weakening of the IF inflow. Annually averaged volume transport of Atlantic water through the monitoring section had a statistically significant (95 % confidence level) increasing trend of (0.12±0.10) Sv per decade. Combined with increasing temperature, this caused an increase of 13 % in the heat transport, relative to 0 ∘C, towards the Arctic of the IF inflow over the 29 years of monitoring. The near-bottom layer over most of the IFR is dominated by cold water of Arctic origin that may contribute to the overflow across the ridge. Our observations confirm a dynamic link between the overflow and the Atlantic water flow above. The results also provide support for a previously posed hypothesis that this link may explain the difficulties in reproducing observed transport variations in the IF inflow in numerical ocean models, with consequences for its predictability under climate change.

Nonstationary Roles of Regional Forcings in Driving Low‐Frequency Sea Level Variability Along the U.S. East Coast Since the 1950s

AbstractThe nonstationary roles of regional forcings from alongshore wind stress and sea level pressure (SLP) in driving low‐frequency (interannual‐to‐decadal) sea level variability along the U.S. east coast for the 1959–2020 period are investigated. The role of regional forcings increases with time north of Cape Hatteras particularly during summer when their contributions to the variance of observed summertime coastal sea level anomalies increase by approximately 58%–87% from 1959–1989 to 1990–2020. The enhanced impact of regional forcings in recent decades results from an increase in the Inverted Barometer (IB) effect that act constructively with alongshore wind stress especially during summer, and to a lesser extent for the Gulf of Maine during fall. The summertime North Atlantic Oscillation (NAO) is largely responsible for the increased IB effect, owing to the stronger NAO‐associated low SLP anomalies centered around the Mid‐Atlantic Bight in recent decades compared to earlier decades.