Sea Surface Height Research Articles

Mode-1 N2 internal tides observed by satellite altimetry

Abstract. Satellite altimetry provides a unique technique for observing the sea surface height (SSH) signature of internal tides from space. Previous studies have constructed empirical internal tide models for the four largest constituents M2, S2, K1, and O1 by satellite altimetry. Yet no empirical models have been constructed for minor tidal constituents. In this study, we observe mode-1 N2 internal tides (the fifth largest constituent) using about 100 satellite years of SSH data from 1993 to 2019. We employ a recently developed mapping procedure that includes two rounds of plane wave analysis and a two-dimensional bandpass filter in between. The results show that mode-1 N2 internal tides have millimeter-scale SSH amplitudes. Model errors are estimated from background internal tides that are mapped using the same altimetry data but with a tidal period of 12.6074 h (N2 minus 3 min). The global mean error variance is about 25 % that of N2, suggesting that the mode-1 N2 internal tides can overcome model errors in some regions. We find that the N2 and M2 internal tides have similar spatial patterns and that the N2 amplitudes are about 20 % of the M2 amplitudes. Both features are determined by the N2 and M2 barotropic tides. The mode-1 N2 internal tides are observed to propagate hundreds to thousands of kilometers in the open ocean. The globally integrated N2 and M2 internal tide energies are 1.8 and 30.9 PJ, respectively. Their ratio of 5.8 % is larger than the theoretical value of 4 % because the N2 internal tides contain relatively larger model errors. Our mode-1 N2 internal tide model is evaluated using independent satellite altimetry data in 2020 and 2021. The results suggest that the model can make internal tide correction in regions where the model variance is greater than twice the error variance. This work demonstrates that minor internal tidal constituents can be observed using multiyear multi-satellite altimetry data and dedicated mapping techniques.

Marine gravity modelling from SARAL/AltiKA data using the Least Square Collocation for the Red Sea

Marine gravity has been modeled using satellite radar altimetry for more than two decades. However, the accuracy of the predicted gravity field is constrained by the range precision and spatial coverage of the altimetry observations. The objective of this research is to enhance the gravity field over the Red Sea by utilizing the Least Square Collocation (LSC) algorithm with SARAL/AltiKA mission observations. The marine gravity field in the Red Sea was determined by using observed Sea Surface Heights (SSHs) obtained from the SARAL/AltiKA mission. The Remove-Compute-Restore (RCR) technique, the Residual Terrain Modelling (RTM) reduction method, and the LSC technique are used to estimate the marine gravity. To evaluate the accuracy of the SARAL/AltiKA predicted model, it was compared against two global altimetry gravity models (DTU21 and SSv29.1) using 42331 shipborne gravity measurements over the Red Sea. The SARAL/AltiKA predicted model showed the best results, with root mean square error and standard deviation values of 6.29 and 5.93 mGal, respectively. The impact of bathymetry depths on the SARAL/AltiKA predicted gravity model accuracy was also investigated. The SARAL/AltiKA predicted gravity model produced better results for water depths up to 1000 m when compared with shipborne data, while the SSv29.1 model performed better for depths between 1000 and 3000 m due to the performance of the residual slopes of the SSH estimation technique used in the deep areas.

Fishing Area Prediction Using Scene-Based Ensemble Models

This study utilized Chlorophyll-a, sea surface temperature (SST), and sea surface height (SSH) as the environmental variables to identify skipjack tuna catch hotspots. This study conducted statistical methods (decision tree, DT, and generalized linear model, GLM) as ensemble models that were employed for predicting skipjack area for each time slice. Using spatial historical data, each model was trained for one of the ensemble model sets. For prediction, the correlations of historical and new inputs were applied to select the predictive model. Using the scene-based model with the highest input correlation, this study further identified the fishing area of skipjack tuna in every case whether the alterations in their environment affected their abundance or not. Overall, the performance achieved over 83% for correlation coefficients (CC) based on the accuracy assessment. This study concluded that DT appears to perform better than GLM in predicting skipjack tuna fishing areas. Moreover, the most influential environmental variable in model construction was sea surface temperature (SST), indicating that the presence of skipjack tuna was primarily influenced by regional temperature.

Calibration of the Instrumental Errors on Marine Gravity Recovery from SWOT Altimeter

The wide-swath altimetry mission, Surface Water and Ocean Topography (SWOT), makes it possible to further break through the accuracy and resolution of marine gravity field recovery. However, as its main payload, the Ka-band radar interferometer (KaRIN) is easy to be affected by the spacecraft attitude, mechanical deformations and dual antenna signal reception status, which generates instrumental errors including roll errors, phase errors, baseline dilation errors, timing errors, and KaRIN noise. Together with ocean temporal variations, the instrumental errors have large effects on the SWOT Sea Surface Height (SSH) observations and hence the marine gravity field recovery. Here, taking the sea area around Japan as an example, we investigated the calibrations of instrumental errors and ocean temporal variations on the recovery of the marine gravity field. The SSH observations of SWOT are first simulated by Mean Sea Surface (MSS), Absolute Dynamic Topography (ADT), Mean Dynamic Topography (MDT) and instrumental errors. Next, the influence of instrumental errors on determining vertical deflection within single-cycle data was analyzed. Then, three calibration methods (KaRIN/KaRIN cross-calibration, Representative KaRIN/KaRIN cross-calibration, and KaRIN/Nadir cross-calibration) are used to reduce the instrumental errors; the experimental results show KaRIN/KaRIN cross-calibration is the optimal one. Last, for the multi-cycle observations containing ocean temporal variations, crossover calibration is done in single cycle and then followed by collinear adjustment in multi-cycles. This approach is verified by considering 18 simulated cycles that cover almost 1 year. Our result indicates an improvement in the accuracy of marine gravity anomaly by about 45% compared to that of one cycle. The calibration strategy of instrumental errors and ocean temporal variations can be used for high-precision marine gravity field recovery with abundant SWOT observations in the near future.

Seasonal variability in Antarctic ice shelf velocities forced by sea surface height variations

Abstract. Antarctica's ice shelves resist the flow of grounded ice towards the ocean through “buttressing” arising from their contact with ice rises, rumples, and lateral margins. Ice shelf thinning and retreat reduce buttressing, leading to increased delivery of mass to the ocean that adds to global sea level. Ice shelf response to large annual cycles in atmospheric and oceanic processes provides opportunities to study the dynamics of both ice shelves and the buttressed grounded ice. Here, we explore whether seasonal variability of sea surface height (SSH) can explain observed seasonal variability of ice velocity. We investigate this hypothesis using several time series of ice velocity from the Ross Ice Shelf (RIS), satellite-based estimates of SSH seaward of the RIS front, ocean models of SSH under and near RIS, and a viscous ice sheet model. The observed annual changes in RIS velocity are of the order of 1–10 m a−1 (roughly 1 % of mean flow). The ice sheet model, forced by the observed and modelled range of SSH of about 10 cm, reproduces the observed velocity changes when sufficiently large basal drag changes near the grounding line are parameterised. The model response is dominated by grounding line migration but with a significant contribution from SSH-induced tilt of the ice shelf. We expect that climate-driven changes in the seasonal cycles of winds and upper-ocean summer warming will modify the seasonal response of ice shelves to SSH and that nonlinear responses of the ice sheet will affect the longer trend in ice sheet response and its potential sea-level rise contribution.

The intrinsic variability of the Indonesian Throughflow

The Indonesian Throughflow (ITF) carries an annual average of about 15 Sv of water from the Pacific through the Indonesian Seas Into the Indian Ocean, and its year-to-year variation ranges from 1 to 4 Sv. A 10-member ensemble of 41-year integrations of a semi-global eddy-resolving oceanic general circulation model is examined to explore the intrinsic (chaotic) variability of the ITF transport and associated flow. It is found that the annual-mean ITF transport is different by about 1 Sv between the ensemble members at several years. The characteristic vertical and horizontal structures of the ensemble anomaly (deviation from the ensemble average) are described. These structures and the basin-scale spread of the anomaly suggest that the intrinsic variability of the ITF is a genuine increase or decrease of the classical ITF rather than variability due to local eddies or nonlinear currents within the Indonesian Seas. The lagged correlation of the intrinsic component of the ITF transport with sea-surface height and barotropic streamfunction suggests that the intrinsic variability may come from zonal jets in the western subtropical North Pacific.

Assessing the capability of three different altimetry satellite missions to observe the Northern Current by using a high-resolution model

Abstract. Over the last 3 decades, satellite altimetry has observed sea surface height variations, providing a regular monitoring of the surface ocean circulation. Altimetry measurements have an intrinsic signal-to-noise ratio that limits the spatial scales of the currents that can be captured. However, the recent progress made on both altimetry sensors and data processing allows us to observe smaller geophysical signals, offering new perspectives in coastal areas where these structures are important. In this methodological study, we assess the ability of three altimeter missions with three different technologies to capture the Northern Current (northwestern Mediterranean Sea) and its variability, namely Jason-2 (Ku-band low-resolution-mode altimeter, launched in 2008), SARAL/AltiKa (Ka-band low-resolution-mode altimeter, launched in 2013) and Sentinel-3A (synthetic aperture radar altimeter, launched in 2016). Therefore, we use a high-resolution regional model as a reference. We focus along the French coast of Provence, where we first show that the model is very close to the observations of high-frequency radars and gliders in terms of surface current estimates. In the model, the Northern Current is observed 15–20 km from the coast on average, with a mean core velocity of 0.39 m s−1. Its signature in terms of sea level consists of a drop whose mean value at 6.14∘ E is 6.9 cm, extending over 20 km. These variations show a clear seasonal pattern, but high-frequency signals are also present most of the time. In comparison, in 1 Hz altimetry data, the mean sea level drop associated with the Northern Current is overestimated by 3.0 cm for Jason-2, but this overestimation is significantly less with SARAL/AltiKa and Sentinel-3A (0.3 and 1.4 cm respectively). In terms of corresponding sea level variability, Jason-2 and SARAL altimetry estimates are larger than the model reference (+1.3 and +1 cm respectively), whereas Sentinel-3A shows closer values (−0.4 cm). When we derive geostrophic surface currents from the satellite sea level variations without any data filtering, in comparison to the model, the standard deviations of the velocity values are also very different from one mission to the other (3.7 times too large for Jason-2 but 2.4 and 2.9 times too large for SARAL and Sentinel-3A respectively). When low-pass filtering altimetry sea level data with different cutoff wavelengths, the best agreement between the model and the altimetry distributions of velocity values are obtained with a 60, 30 and 40–50 km cutoff wavelength for Jason-2, SARAL and Sentinel-3A data respectively. This study shows that using a high-resolution model as a reference for altimetry data allows us not only to illustrate how the advances in the performances of altimeters and in the data processing improve the observation of coastal currents but also to quantify the corresponding gain.

Influence of the El Niño-Southern Oscillation on upper-ocean salinity changes in the southeast Indian ocean

The interannual-decadal variability in the upper-ocean salinity of the southeast Indian Ocean (SEIO) was found to be highly correlated with the El Niño-Southern Oscillation (ENSO). Based on multisource data, this study revealed that this ENSO-like salinity variability mainly resides in the domain between 13°S-30°S and 100°E-120°E, and at depths above 150 m. This variability is principally driven by meridional geostrophic velocity (MGV), which changes with the zonal pattern of the sea surface height (SSH). Previous studies have reported that the variability in the SSH in the south Indian Ocean is principally driven by local-wind forcing and eastern-boundary forcing. Here the eastern-boundary forcing denotes the influence of SSH anomaly radiated from the western coast of Australia. A recent study emphasized the contribution of local-wind forcing in salinity variability in the SEIO, for its significant role in generation of the zonal dipole pattern of SSH anomaly in the south Indian Ocean, which was considered to be responsible for the anomalous MGV in the SEIO. While our results revealed a latitudinal difference between the domain where the SSH dipole pattern exists (north of 20°S) and the region in which the ENSO-like salinity variability is strongest (20°S-30°S), suggesting that this salinity variability cannot be attributed entirely to the SSH dipole pattern. Our further investigation shows that, the MGV in the SEIO changes with local zonal SSH gradient that principally driven by eastern-boundary forcing. In combination with the strong meridional salinity gradient, the boundary-driven MGV anomalies cause significant meridional salinity advection and eventually give rise to the observed ENSO-like salinity variability. This study revealed the leading role of eastern-boundary forcing in interannual variability of the upper-ocean salinity in the SEIO.

Southwestern Atlantic ocean fronts detected from the fusion of multi-source remote sensing data by a deep learning model

In the Southwestern Atlantic, the Falkland Current intrudes onto the South American shelf, resulting in the meeting of two water masses which are completely different in temperature and dynamic characteristics, thus generating the Southwestern Atlantic Front (SAF). Therefore, the SAF has prominent characteristics of thermal and dynamics. The current ocean front detection is mainly by performing gradient operations on sea surface temperature (SST) data, where regions with large temperature gradients are considered as ocean fronts. The thermal gradient method largely ignores the dynamical features, leading to inaccurate manifestation of SAF. This study develops a deep learning model, SAFNet, to detect the SAF through the synergy of 10-year (2010-2019) satellite-derived SST and sea surface height (SSH) observations to achieve high accuracy detection of SAF with fused thermal and dynamic characteristics. The comparative experimental results show that the detection accuracy of SAFNet reaches 99.45%, which is significantly better than other models. By comparing the frontal probability (FP) obtained by SST, SSH and SST-SSH fusion data respectively, it is proved that the necessity of fusion multi-source remote sensing data for SAF detection. The detection results of fusion data can reflect the spatial distribution of SAF more comprehensively and accurately. According to the meridional variation of FP, the main reason for the seasonal variation of the SAF is the change in its thermal characteristics, and the SAF has stable dynamic characteristics.

Spatial and temporal variations in sea surface pCO2 and air-sea flux of CO2 in the Bering Sea revealed by satellite-based data during 2003–2019

The understanding of long-time-series variations in air-sea CO2 flux in the Bering Sea is critical, as it is the passage area from the North Pacific Ocean water to the Arctic. Here, a data-driven remote sensing retrieval method is constructed based on a large amount of underway partial pressure of CO2 (pCO2) data in the Bering Sea. After several experiments, a Gaussian process regression model with input parameters of sea surface temperature, sea surface height, mixed-layer depth, chlorophyll a concentration, dry air mole fractions of CO2, and bathymetry was selected. After validation with independent data, the root mean square error of pCO2 was< 24 μatm (R2 = 0.94) with satisfactory performance. Then, we reconstructed the sea surface pCO2 in the Bering Sea from 2003 to 2019 and estimated the corresponding air-sea CO2 fluxes. Significant seasonal variations were identified, with higher sea surface pCO2 in winter/spring than in summer/autumn in both the basin and shelf area. Semiquantitative analysis reveals that the Bering Sea is a non-temperature-dominated area with a mean temperature effect on pCO2 of 12.7 μatm and a mean non-temperature effect of −51.8 μatm. From 2003 to 2019, atmospheric pCO2 increased at a rate of 2.1 μatm yr−1, while sea surface pCO2 in the basin increased rapidly (2.8 μatm yr−1); thus, the CO2 emissions from the basin increased. However, the carbon sink in the continental shelf still continuously increased. The whole Bering Sea exhibited an increasing carbon sink with the area integral of air-sea CO2 fluxes increasing from 6 to 19 TgC over 17 years. Meanwhile, the seasonal amplitudes in pCO2 in the shelf area also increased, approaching 14 μatm per decade. The reaction of the continuously added CO2 in continental seawater reduced the ocean CO2 system capacity. This is the first study to present long-time-series satellite data with high resolution in the Bering Sea, which is beneficial for studying the changes in ocean ecosystems and carbon sink capacity.

Effect of western Pacific current uncertainties on the forecasting of eddy shedding from the Kuroshio loop into the South China Sea: A case study

The process of eddy shedding from the Kuroshio loop current (LC) into the South China Sea via the Luzon Strait is highly variable and significantly controlled by the uncertainties in the Western Pacific (WP) currents. This study investigates the forecast of a strong eddy shedding event from the Kuroshio LC during the winter 2016–2017 using the regional ocean modeling system and ensemble Kalman filter assimilation method. Experiments are conducted to explore the sensitivity of forecasts to the assimilation of satellite sea surface height anomaly data from different key regions of the WP, such as the subtropical countercurrent (STCC) and Northern Equatorial Current (NEC) regions. The results indicate that the improved forecast performance of the strong Kuroshio LC eddy shedding event is mainly attributed to assimilation in the STCC region and partly owing to assimilation in the NEC region. Specifically, assimilation in the STCC region reproduces a westward-propagating cyclonic eddy that collides with the Kuroshio in the Luzon Strait, blocking the Kuroshio northward flow and causing Kuroshio LC eddy shedding. Furthermore, assimilation in the NEC region enhances the simulation of the weak Kuroshio background current, which further facilitates the formation of a strong Kuroshio background LC and the occurrence of Kuroshio LC eddy shedding.

DUACS DT2021 reprocessed altimetry improves sea level retrieval in the coastal band of the European seas

Abstract. More than 29 years of altimeter data have been recently reprocessed by the multi-satellite Data Unification and Altimeter Combination System (DUACS) and made available under the name of DT2021 through the Copernicus Marine Service (CMEMS) and the Copernicus Climate Change Service (C3S). New standards have been applied and various geophysical correction parameters have been updated compared to the previous release in order to improve the product quality. This paper describes the assessment of this new release through the comparison of both the all satellites and the two satellites product with external in situ tide gauge measurements in the coastal areas of the European seas for a time period from 1 January 1993 to 31 May 2020. The aim is to quantify the improvements on the previous DT2018 processing version for the retrieval of sea level in the coastal zone. The results confirmed that the CMEMS product in the new DT2021 processing version better solves the signal in the coastal band. The all satellites dataset showed a reduction of 3 % in errors when compared with tide gauges and of 5 % in the variance of the differences between the datasets compared to DT2018 reprocessing. Moreover, the all satellites dataset provided more accurate sea level measurements when making a comparison with tide gauges with respect to the climatic two satellites dataset due to the better performance of the former for the assessment of higher than climatic frequency signals. By contrast, the two satellite dataset is the most suitable product for the assessment of long-term sea level sea surface height (SSH) trends in the coastal zone due to its larger stability to the detriment of the all satellites dataset.

Modeling the spatio-temporal distribution of Karenia brevis blooms in the Gulf of Mexico

Background: Harmful algal blooms (HABs) of the toxic dinoflagellate Karenia brevis impact the overall ecosystem health. Methods: K. brevis cell counts were extracted from Harmful Algal BloomS Observing System (HABSOS) in situ data and matched with 0.25º resolution environmental information from the Copernicus database to generate spatio-temporal maps of HABs in the Gulf of Mexico (GoM) between 2010 and 2020. The data was used to analyze the relationship between spatial and temporal variability in the presence/absence of K. brevis blooms (≥100,000 cells/L) and biotic and abiotic variables using Generalized Additive Models (GAM). Results: The variability of blooms was strongly linked to geographic location (latitude and salinity), and temporal variables (month and year). A higher probability of K. brevis blooms presence was predicted in areas with negative sea surface height (SSH) values, silicate concentration (0, 30-35 mmol. m-3), sea surface temperature of 22-28 oC, and water currents moving south-westward (225º). The smooth effect of each environmental variable shows a bimodal pattern common in semi-enclosed basins such as GoM. The spatial predictions from the model identified an important permanent area in (1) Southwest Florida (25.8-27.4o latitude), and four seasonally important areas, (2) North Central Florida (3) Central West Florida, (4) Alabama on Gulf Shores and (5) Mississippi with higher bloom probabilities during the fall to winter season (November-January). Results also suggest that HABs can extend until ≥ 300 km offshore; starting to form in March and reaching a peak in September, and were swept to the coastal area during fall and winter. This suggests the role of upwelling and water circulation in GoM for the accumulation of cells and HABs. Information on the spatio-temporal dynamics of K. brevis blooms and understanding the environmental drivers are crucial to support more holistic spatial management to decrease K. brevis blooms incidence in bodies of water.

The CNES CLS 2022 Mean Sea Surface: Short Wavelength Improvements from CryoSat-2 and SARAL/AltiKa High-Sampled Altimeter Data

A new mean sea surface (MSS) was determined by focusing on the accuracy provided by exact-repeat altimetric missions (ERM) and the high spatial coverage of geodetic (or drifting) missions. The goal was to obtain a high-resolution MSS that would provide centimeter-level precision. Particular attention was paid to the homogeneity of the oceanic content of this MSS, and specific processing was also carried out, particularly on the data from the geodetic missions. For instance, CryoSat-2 and SARAL/AltiKa data sampled at high frequencies were enhanced using a dedicated filtering process and corrected from oceanic variability using the results of the objective analysis of sea-level anomalies provided by DUACS multi-missions gridded sea-level anomalies fields (MSLA). Particular attention was also paid to the Arctic area by combining traditional sea-surface height (SSH) with the sea levels estimated within fractures in the ice (leads). The MSS was determined using a local least-squares collocation technique, which provided an estimation of the calibrated error. Furthermore, our technique takes into account altimetric noises, ocean-variability-correlated noises, and along-track biases, which are determined independently for each observation. Moreover, variable cross-covariance models were fitted locally for a more precise determination of the shortest wavelengths, which were shorter than 30 km. The validations performed on this new MSS showed an improvement in the finest topographic structures, with amplitudes exceeding several cm, while also continuing to refine the correction of the oceanic variability. Overall, the analysis of the precision of this new CNES_CLS 2022 MSS revealed an improvement of 40% compared to the previous model, from 2015.

Causal Forcing Analysis on the Low-Frequency Variations of Eddy Kinetic Energy in the Kuroshio Extension Region

Abstract The eddy kinetic energy (EKE) in the Kuroshio Extension (KE) region may be affected by two factors: EKE in the Kuroshio large meander (KLM) region and the North Pacific Gyre Oscillation (NPGO). Previous studies reported that the Kuroshio path variations south of Japan may affect the low-frequency variability of the KE jet and related EKE, but the linear correlation between these phenomena derived from long time series is low and not significant, implying that the linkage between EKE in the KLM and KE regions is still unclear. Besides, whether NPGO has a causal effect on the KE EKE remains under debate. In this study, we investigate the causal forcing of the KLM EKE and NPGO on the KE EKE using the convergent cross mapping (CCM) approach based on satellite sea surface height observations. The analysis shows that the KLM EKE affects the EKE only in the KE upstream area (west of 146°E), with no significant causal effect on the EKE in the downstream area; the NPGO plays, instead, a remarkable role on the EKE in both areas. The effect of the KLM EKE on the KE EKE is found to depend on the Kuroshio latitudinal position over the Izu Ridge. Changes in the KLM EKE affect the downstream advection of eddies and induce changes in the Kuroshio position over the ridge, which cause different EKE levels in the KE upstream region. The NPGO affects the KE EKE through the westward propagation of sea surface height anomalies remotely forced by wind stress anomalies associated with the North Pacific Oscillation.

Subsurface Eddy Detection Optimized with Potential Vorticity from Models in the Arabian Sea

Abstract Coherent ocean vortices, or eddies, are usually tracked on the surface of the ocean. However, tracking subsurface eddies is important for a complete understanding of deep ocean circulation. In this study, we develop an algorithm designed for the detection of subsurface eddies in the Arabian Sea using Nucleus for European Modelling of the Ocean (NEMO) model simulations. We optimize each parameter of our algorithm to achieve favorable results when compared with an algorithm using sea surface height (SSH). When compared to similar methods, we find that using the rescaled isopycnal potential vorticity (PV) is best for subsurface eddy detection. We proceed to demonstrate that our new algorithm can detect eddies successfully between specific isopycnals, such as those that define the Red Sea Water (RSW). In doing so, we showcase how our method can be used to describe the properties of eddies within the RSW and even identify specific long-lived subsurface eddies. We conduct one such case study by discerning the structure of a completely subsurface RSW eddy near the Chagos Archipelago using Lagrangian particle tracking and PV diagnostics. We conclude that our rescaled PV method is an efficient tool for investigating eddy dynamics within the ocean’s interior, and publicly provide our optimization methodology as a way for other researchers to develop their own subsurface detection algorithms with optimized parameters for any spatiotemporal model domain. Significance Statement Eddies are a key part of ocean circulation both at the surface and in the subsurface. The purpose of our study was to design the first detection method comprehensively optimized for subsurface eddy detection from numerical simulations. We demonstrate that potential vorticity (PV) is the best field to use when algorithmically tracking eddies in subsurface water masses, using our new method to identify and track eddies in the Red Sea Water (RSW). Additionally, our method allows us to efficiently evaluate the dynamics of eddies through potential vorticity diagnostics, exemplified with a previously undescribed eddy near the Chagos Archipelago. Our methodology can be used by future researchers to study the eddy dynamics hidden within subsurface water masses around the world.

Drastic Fluctuation in Water Exchange Between the Yellow Sea and Bohai Sea Caused by Typhoon Lekima in August 2019: A Numerical Study

AbstractConnecting the Bohai Sea (BS) and Yellow Sea (YS), the Bohai Strait is vital in controlling physical‐biogeochemical conditions in the East Asian marginal seas. In August 2019, Typhoon Lekima moved northward inland into eastern China and caused drastic water exchange through the Bohai Strait. The specific variation and underlying dynamics involved were investigated with observations and high‐resolution numerical simulations. Volume transport featured an intense inflow followed by an intense outflow, with a fluctuation magnitude of 1.88 Sv, which was much greater than the seasonal‐interannual variations. The corresponding current patterns presented three phases: strait‐wide inflow, strait‐wide outflow, and outflow in the south and inflow in the north. The strait‐wide inflow was driven by strong east‐northeasterly winds through local Ekman dynamics. The strait‐wide outflow resulted from the dynamic adjustment of ocean currents accompanying the rapid weakening of easterly winds. The third current pattern was part of a large‐scale cyclonic circulation in the BS and North YS and was governed by different factors in the southern and northern straits. Further comparisons indicated that transport caused by winter storms and other typhoons in the year had opposite phase variations to that caused by Lekima. The underlying dynamics mainly involved local Ekman dynamics and/or remote wind forcing via the propagation of coastal trapped waves but could differ greatly from events. Finally, we found that to a large extent, geostrophic transport derived from the sea surface height difference across the Bohai Strait could be used as actual transport during synoptic weather events.

Structure and Variability of the Barrow Canyon Outflow From Two High‐Resolution Shipboard Surveys in 2018

AbstractBarrow Canyon in the northeast Chukchi Sea is a critical choke point where Pacific‐origin water, heat, and nutrients enter the interior Arctic. While the flow through the canyon has been monitored for more than 20 years, questions remain regarding the dynamics by which the Pacific‐origin water is fluxed offshore, as well as what drives the variability. In 2018, two high‐resolution shipboard surveys of the canyon were carried out—one in summer and one in fall—to investigate the water mass distribution and velocity structure of the outflow. During the summer survey, high percentages of Pacific water (summer water + winter water) were present seaward of the canyon, associated with strong northward outflow from the canyon and a well‐developed westward‐flowing Chukchi Slope Current (CSC). By contrast, high percentages of Pacific water were confined to the canyon proper and outer Chukchi shelf during the late‐fall survey, at which time the canyon outflow and CSC were considerably weaker. These differences can be attributed to differences in wind forcing during the time period of two surveys. A cyclone‐like circulation was present in the canyon during both surveys, which was also evident in the satellite‐derived sea surface height anomaly field. We argue that this feature corresponds to an arrested topographic Rossby wave, generated as the outflow responds to the deepening bathymetry of the canyon. By applying a self‐organizing map analysis using the satellite altimeter data from 2001 to 2020, we demonstrate that such a cyclone‐like structure is a prevailing aspect of the canyon outflow.

Obtaining accurate measurements of the sea surface height from a GPS buoy

Obtaining accurate measurements of the sea surface height from a GPS buoy

Characteristics of submesoscale eddy structures within mesoscale eddies in the Gulf of Mexico from 1/48° ECCO estimates

Submesoscale oceanic structures (<10-20 km) such as eddies and fronts are often difficult to describe given the influence of the mesoscale. In order to characterize the surface signatures of submesoscale structures, we utilize a custom spatial filtering function to separate the meso- and large-scale sea surface height (SSH) signal from the small scale SSH signal of 1/48° high resolution estimates provided by NASA’s Estimating the Circulation and Climate of the Oceans (ECCO) project. In this study, we use ECCO estimates from a 14-month global simulation between September 2011 and November 2012 with a 2 km horizontal grid spacing in the Gulf of Mexico. We then use an eddy detection and tracking algorithm to identify persistent circular features on both scales, giving rise to an atlas of submesoscale eddy-like variabilities (SEVs). We briefly investigate the geographic and temporal variability of SEVs as a whole before collocating SEVs inside mesoscale eddies, allowing us to evaluate the characteristics of internal SEVs and the impact of SEVs on mesoscale eddies. We find that SEVs, both anticyclonic and cyclonic, are ubiquitous inside mesoscale eddies with lifetimes longer than a week, accounting for an average of 10-20% of the spatial area and eddy kinetic energy of mesoscale eddies. We also show that internal SEVs are persistently associated with temperature and salinity anomalies in both eddy centers and edges of up to 0.1 °C and 0.05 psu, with anticyclonic internal SEVs being warmer and fresher while cyclonic internal SEVs are colder and saltier. Finally, we examine the life cycle of an anticyclonic Loop Current eddy, demonstrating that the number and intensity of internal SEVs within increases as the eddy approaches separation from the Loop Current until a maximum is obtained just after separation. In light of forthcoming submesoscale SSH observations from NASA’s Surface Water and Ocean Topography (SWOT) mission, our results showcase the variability of submesoscale eddy structures and their possible implications for biogeochemical cycling, the inverse energy cascade, and Loop Current prediction techniques.