Altimeter Data Research Articles

A two-stage deep learning architecture for detection global coastal and offshore submesoscale ocean eddy using SDGSAT-1 multispectral imagery

Submesoscale ocean eddies are essential oceanic phenomenon that control and influence the ocean energy cascade. Most existing eddy detection methods rely on low-resolution satellite altimeter data, which fail to capture submesoscale ocean features and oceanographic phenomena in shallow water. Introducing high-resolution multispectral data can alleviate these problems, yet it has been largely overlooked. A generalized and efficient deep learning architecture that combines developments in deep learning with Sustainable Development Goals Science Satellite 1 (SDGSAT-1) multispectral data from earth observations offers a potential pathway for more fine detection of ocean eddies. Considering that oceanic eddy exhibits spatially sparse characteristics on high-resolution remote sensing scenes, the oceanic eddy detection (OED) model suitable for global coastal and offshore regions is divided into two stages: eddy information judgment and eddy position determination. Correspondingly, SDGSAT-1 multispectral data from November 2021 to December 2022 were carried out to construct two submesoscale eddy datasets for training and testing each stage model. The union validation of multiple metrics demonstrates that the proposed OED model and its stage models achieve state-of-the-art (SOTA) performance, especially in optically complex coastal and offshore waters. We applied the model to real-world scenes captured by SDGSAT-1 in 2023, and found that the detected results were mainly located at the water depth below 200 m. The authenticity of the recognition results is validated using sea surface chlorophyll concentration, temperature, and topography data, indicating that the OED model has achieved remarkable effectiveness under various sea conditions. In addition, the temporal distributions and statistical characteristics of detected submesoscale eddies are analyzed over an extended period (November 2021 to November 2023). Finally, HISEA-2, Landsat-9, and Sentinel-2 served as testing grounds to validate the generalization of the proposed methodology, with experimental results demonstrating that the OED model possesses significant developmental potential for multi-source remote sensing data. This paper presents a comprehensive deep learning framework for the global-scale detection of submesoscale eddies and underscores the pivotal role of high-resolution multispectral imagery as an innovative data source for global coastal and offshore eddy identification.

Analysis of Lofoten Vortex Merging Based on Altimeter Data

The Lofoten Vortex (LV), which is identified as a quasi-permanent anticyclonic eddy, strengthens through continuous merging with external anticyclonic eddies. Our investigation used the Lagrangian method to monitor the LV on a daily basis. Utilizing satellite altimeter data, we conducted multi-year tracking and statistical analysis of merging events involving the LV. The results indicate a characteristic radius of approximately 42.72 km and a mean vorticity at the eddy center of approximately −2.23 × 10−5 s−1. The eddy exhibits oscillatory motion within the sea basin depression, centered at 70°N, 3°E, characterized by counterclockwise trajectories between 0.5°E and 6°E and between 69°N and 70.5°N. There are two types of merging events: fusion events (55%), in which eddies of similar strengths interact within a closed flow line and then merge to form a new eddy; and absorption events (45%), in which the stronger LV absorbs the weaker anticyclonic eddies without destroying the structure of the LV itself. The nodes where strong vorticity advection occurs correspond to the nodes where merging occurs, suggesting that their effect on merging can be well characterized by the vorticity advection time series. We also observe occasional fluctuations and substitution events involving the LV and external anticyclonic eddies, suggesting a dynamic succession rather than a single vortex entity.

Multi-decadal Sea Level Prediction using Neural Networks and Spectral Clustering on Climate Model Large Ensembles and Satellite Altimeter Data

Multi-decadal Sea Level Prediction using Neural Networks and Spectral Clustering on Climate Model Large Ensembles and Satellite Altimeter Data

Assessment of Pollution of the Waters in the South Kuril Fishing Zone of Russia by Radioactive Waters from the Fukushima-1 NPP Based on Lagrangian Modeling

The study investigates the potential hazard arising from the actions taken by the Japanese government regarding the discharge of technical radioactive water from the Fukushima-1 nuclear power plant storage facilities. The contamination of the South Kuril Fishing Zone (SKFZ), which is one of the most promising fishing areas for the Russian Federation, with radioactive particles, is considered. Based on the modeling of passive markers simulating radioactive contamination, the study analyzes the pathways and mechanisms of pollution transfer into the SKFZ. The research is conducted using altimetric data on geostrophic currents for the period from August 24, 2022, to August 24, 2023. The pollution transfer into the SKFZ is determined by a set of conditions related to the current development regime of the First Kuril Meander and the local vortex system with varying characteristics, both near the discharge site and at the SKFZ border. A seasonal dependence of the speed and quantity of polluted water infiltration toward the Russian Federation’s shores is established. The possibility of rapid pollution advection into the SKFZ within 13 days has been discovered. This speed is due to the entrainment of contamination by the Kuril Meander and its further transport by the mesoscale vortex system to the SKFZ border. The study reveals periodicity in the influx of pollution into the SKFZ. Graphs depicting the distribution of the quantity of “dirty” markers over their release times and the arrival of polluted water at the SKFZ border have been created.

Convergence and divergence of storm waves induced by multi-scale currents: Observations and coupled wave-current modeling

Current effects on waves (CEW) are among the most intricate physical processes in wave evolution. In this study, we used a coupled wave-tide-circulation model for the Northwest Atlantic to investigate current effects on storm waves during Hurricane Igor in 2010. Validated with extensive buoy and altimeter data, the inclusion of CEW in the model significantly improves the accuracy in simulating significant wave heights (Hs) by up to 21.3% for a wave buoy. Storm waves experience significant temporal and spatial modulation by multi-scale currents. Storm-driven currents have the most pronounced impact to the right of the storm track, which typically align with wave propagation and reduce Hs by up to 12.1%. The subsequent near-inertial oscillations induce temporal fluctuations of wave convergence and divergence at near-inertial frequencies, which also occurs in regions with strong tidal currents but at tidal frequencies. Furthermore, storm waves are modulated by the Gulf Stream, Labrador Current and associated mesoscale eddies. Overall, these multi-scales yield strong effects on storm waves (Hs > 3.0 m), significantly modulating Hs (−25.2%–+55.4%) and mean wave periods (−14.9%–+15.7%). The mean wave energy power shows more significant modulation by multi-scale currents, reflecting the combined effects of changing wave states and current-induced transport of wave energy. CEW are governed by the interactive dynamic and kinematic effects. The relative wind effect is the primary mechanism for lower storm waves by reducing energy input to waves and influences downstream wave states. Among kinematic effects, current-induced wave refraction typically plays a dominant role in redistributing wave energy. This study systematically quantified the modulation of storm waves by multi-scale currents and revealed the underlying mechanisms, providing a comprehensive understanding of extreme wave states under coupled ocean dynamics.

Response of Upper Ocean to Parameterized Schemes of Wave Breaking under Typhoon Condition

The study of upper ocean mixing processes, including their dynamics and thermodynamics, has been a primary focus for oceanographers and meteorologists. Wave breaking in deep water is believed to play a significant role in these processes, affecting air–sea interactions and contributing to the energy dissipation of surface waves. This, in turn, enhances the transfer of gas, heat, and mass at the ocean surface. In this paper, we use the FVCOM-SWAVE coupled wave and current model, which is based on the MY-2.5 turbulent closure model, to examine the response of upper ocean turbulent kinetic energy (TKE) and temperature to various wave breaking parametric schemes. We propose a new parametric scheme for wave breaking energy at the sea surface, which is based on the correlation between breaking wave parameter RB and whitecap coverage. The impact of this new wave breaking parametric scheme on the upper ocean under typhoon conditions is analyzed by comparing it with the original parametric scheme that is primarily influenced by wave age. The wave field simulated by SWAVE was verified using Jason-3 satellite altimeter data, confirming the effectiveness of the simulation. The simulation results for upper ocean temperature were also validated using OISST data and Argo float observational data. Our findings indicate that, under the influence of Typhoon Nanmadol, both parametric schemes can transfer the energy of sea surface wave breaking into the seawater. The new wave breaking parameter RB scheme effectively enhances turbulent mixing at the ocean surface, leading to a decrease in sea surface temperature (SST) and an increase in mixed layer depth (MLD). This further improves upon the issue of uneven mixing of seawater at the air–sea interface in the MY-2.5 turbulent closure model. However, it is important to note that wave breaking under typhoon conditions is only one aspect of wave impact on ocean disturbances. Therefore, further research is needed to fully understand the impact of waves on upper ocean mixing, including the consideration of other wave mechanisms.

Cloud computing and spatial hydrology for monitoring the Buyo and Kossou reservoirs in Côte d'Ivoire

The Buyo and Kossou reservoirs are crucial for water supply, agricultural irrigation, and hydroelectric power generation in Côte d'Ivoire. However, climate change threatens the stability and availability of these water resources by increasing rainfall variability, extending drought periods, and intensifying extreme weather events. These challenges underscore the need for precise and continuous monitoring of water levels and surface areas to ensure sustainable management. Due to the scarcity of gauging stations, the objective of this study is to leverage cloud computing technologies along with altimetric and satellite data, for effective reservoir monitoring. Tools like the EO-Africa program's Innovation Lab and Google Earth Engine (GEE), along with advanced image processing software such as PyGEE-SWToolbox and AlTis, were used to process large datasets from the Sentinel-1, Sentinel-2, and Sentinel-3 satellites. These satellites delivered extensive, high-resolution imagery and altimetric data, crucial for monitoring changes in the reservoirs. The processed data were validated with in-situ measurements, yielding a Root Mean Square Error (RMSE) of less than 0.4 m and a correlation coefficient exceeding 0.90. The results highlighted water surface and level changes from 2016 to 2022, with downward trends and seasonal variations closely aligning with in-situ measurements. The study also revealed that the relationship between water levels and surface areas is influenced by both precipitation and the hydrological regimes of the Bandama and Sassandra rivers, demonstrating the complexity of water dynamics in these reservoirs. This research emphasizes the effectiveness of integrating spatial hydrology with cloud computing tools for fast and accurate monitoring of large reservoir. The use of these advanced technologies provides near real-time, reliable, and easily accessible data, offering a significant advantage for water resource management in Côte d'Ivoire.

Performance assessment of sentinel-3/6 altimeter data for marine gravity recovery

High-precision sea surface height is crucial for determining the marine gravity field. The Sentinel-3/6 altimetry missions, equipped with SRAL and Poseidon-4 altimeters, provide this essential data. However, there is a lack of comprehensive assessment of the Sentinel-3/6 altimeters for inverting marine gravity anomalies (MGA). In this study, we employ the inverse Venning-Meinsz method to derive nine sets of 1’×1’ MGAs in the South China Sea (SCS) and the Ross Sea (RS). Specifically, MGAs from Sentinel-3A, Sentinel-3B, Sentinel-6 SARM, Sentinel-6 LRM, HY-2A, ICESat-2, and CryoSat-2 are denoted as S3A, S3B, S6S, S6L, H2A, IS2, and CS2, respectively. MGA from the combined HY-2A, ICESat-2, and CryoSat-2 is referred to as HIC, while 3SHIC denotes the MGA from the combination of Sentinel-3/6 SARM, HY2A, ICESat-2, and CryoSat-2. We assess the performance of these MGAs using the EGM08, DTU17, SIO V32.1, and SDUST2021 gravity field models, as well as shipboard gravity across different ocean regions. Among the Sentinel-3/6 MGAs, S3B exhibits the highest accuracy in the SCS, with a root mean square error (RMSE) of 5.277 mGal, followed closely by S3A. Conversely, S3A demonstrates the highest accuracy with an RMSE of 4.635 mGal, followed by S3B in the RS. The inversion accuracy of MGAs from S6S and S6L are comparable, though S6S outperforms S6L in the open sea. The performance of MGAs from Sentinel-3/6 matches or surpasses that of other altimetry missions during the same period. In the SCS, the best-performing MGA is 3SHIC, with an RMSE of 4.585 mGal, closely matching DTU17. However, 3SHIC exhibits superior performance in the RS with an RMSE of 4.263 mGal compared to DTU17 and SDUST 2021. Furthermore, the performance of 3SHIC, which integrates Sentinel-3/6 data, improves that of HIC by 0.74% and 3.37% in the SCS and RS, respectively. These results underscore the contribution of Sentinel-3/6 altimeters to the MGA, particularly in coastal and high-latitude regions. Integration of Sentinel-3/6 data with other altimetry satellites is expected to enhance the spatial resolution and accuracy of the global marine gravity field, especially with the successful establishment of the network of Sentinel-6 in the future.

Residual and Unmodeled Ocean Tide Signal From 20+ Years of GRACE and GRACE‐FO Global Gravity Field Models

AbstractWe analyze remaining ocean tide signal in K/Ka‐band range‐rate (RR) postfit residuals, obtained after estimation of monthly gravity field solutions from 21.5 years of Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow‐On sensor data. Low‐pass filtered and numerically differentiated residuals are assigned to grids and a spectral analysis is performed using Lomb‐Scargle periodograms. We identified enhanced amplitudes at over 30 ocean tide periods. Spectral replicas revealed several tides from sub‐semidiurnal bands. Increased ocean tide amplitudes are located in expected regions, that is, in high‐latitude, coastal and shallow water regions, although some tides also show distinct patterns over the open ocean. While most identified tides are considered during processing, and therefore the amplitudes represent residual signal w.r.t. the ocean tide model, several unmodeled tides were found, including astronomical degree‐3 tides , , , , and radiational and/or compound tides , , , and . The astronomical degree‐3 tides were observed on a global level for the first time a few years ago in altimeter data. We are unaware of any global data‐constrained solutions for the other tides. The amplitude patterns of these tides exhibit similarities to purely hydrodynamic solutions, and altimeter observations (astronomical degree‐3 only). The sensitivity of the satellites to these rather small tidal effects demands their inclusion into the gravity field recovery processing to reduce orbit modeling errors and a possible aliasing. The conducted study shows enormous potential of RR postfit residuals analysis for validating ocean tide models and improving gravity field recovery processing strategies.

The performance of Tiangong-2 InIRA in gravity anomaly recovery from fused conventional nadir-observing altimeter data

Satellite altimetry has emerged as the primary data source for deriving marine gravity, owing to advancements in satellite altimetry technologies. The Tiangong-2 interferometric imaging radar altimeter (TG2 InIRA) is a new generation wide-swath altimeter (WSA) launched by China on 15 September 2016. TG2 InIRA employs a short-baseline interferometry measurement method at a small incidence angle, thereby enabling the precise measurement of wide-swath sea surface heights (SSHs). The present study demonstrates the efficacy of utilizing data from the TG2 InIRA in conjunction with data from the CryoSat-2 (CS2) satellite to recover marine gravity anomalies. In the Northwest Pacific region (15°N ∼ 25°N, 140°E ∼ 150°E), the TG2 InIRA data were filtered to a 2 km × 2 km grid and any anomalous values were excluded using a mean sea surface model. Deflections of the vertical (DOVs) were calculated using the remove-restore technique, and the inverse Vening-Meinesz formula was applied to invert the gravity anomaly. A power spectral density analysis was conducted to assess variations in gravity anomalies at ship locations in the frequency domain. The results, based on the SIO V31.1 (DOV) model, indicate that the gridded vertical deflections derived from CS2 and TG2 InIRA data achieve more balanced accuracy in the east–west and north–south directions. The integration of TG2 InIRA and CS2 data yielded gravity results exhibiting a root mean square (RMS) of 0.519 mGal lower than those derived from TG2 InIRA data alone, and 0.034 mGal lower than those derived from CS2 data. These findings were derived from shipborne gravity data. Furthermore, the inversion of gravity anomalies from TG2 InIRA demonstrated an enhanced capability in the reduction of high-frequency gravity noise.

Submesoscale ocean dynamic process contributions to diurnal subsurface chlorophyll variation along Lagrangian recirculation inside mesoscale eddies: A case study in the Southern Ocean

Studies regarding oceanic mesoscale and submesoscale processes and their impact on chlorophyll are mainly confined to weeks to decadal time scales. Based on biogeochemical-Argo float observations and altimeter data in the Southern Ocean in summer of 2016, we show the day-night chlorophyll difference inside a cyclonic eddy (ΔChlTCE) and an anticyclonic eddy (ΔChlTACE) associated with submesoscale processes. A diurnal cycle of chlorophyll is observed in the upper 50 m, with ΔChlTCE (1.5 mg m−3) as much as ten times that of ΔChlTACE (0.15 mg m−3). However, there are similar ratios of day-night chlorophyll difference to the maximum chlorophyll concentration in a day for the cyclonic and anticyclonic eddies (∼67%). Submesoscale processes present different impacts on the subsurface chlorophyll between the cyclonic and anticyclonic eddies on the diurnal scale. More significant submesoscale processes in the cyclonic eddy dominate the subsurface negative ΔChlTCE. It causes the phytoplankton to penetrate the bottom of the mixed layer and extend ∼50 m below the mixed layer. In contrast, submesoscale processes and their associated with vertical buoyancy flux only generate weak negative subsurface ΔChlTACE. The strong vertical gradient of ΔChlTACE is mainly dominated by the vertical displacement of the deep chlorophyll maximum.

“Gear-like” process between asymmetric dipole eddies from satellite altimetry

Mesoscale dipoles compose two counter-rotating mesoscale eddies. They are observed in oceans worldwide and significantly impact the biogeochemical cycle, marine ecosystems, and ocean water transport. This study investigates the evolution of asymmetric dipole eddies based on the satellite altimeter data for the period January 1993–December 2020. The coupling and decoupling of eddy dipoles impact various eddy properties. When the movement of eddies has a dipolar structure, a gentle convergence in parameters (rotational speed, amplitude, eddy kinetic energy, propagation speed, and advective nonlinearity) between the asymmetric dipole eddies is observed–this study refers to it as the “gear-like” process. Kinematic characteristics further indicate that the stronger dipole eddies generally drive the weaker ones to revolve during the “gear-like” process. The revolution direction remains consistent with the rotation direction of stronger dipole eddies. Additionally, eddy size remains relatively stable during the “gear-like” process. The composites of sea level anomaly (SLA) demonstrate that dipole eddies are compressed into a kidney-like shape along the line through their centers. This shape is confirmed by the composites of sea surface temperature anomalies, which closely correspond to the structure of SLA. These findings augment the knowledge regarding the evolution of asymmetric dipole eddies and provide a novel perspective for studying dipoles and eddy-eddy interactions.

Optimized estimation of marine deflection of the vertical from multibeam laser altimeter data of ICESat-2

SUMMARY Satellite altimetry data, with its increasing density and quality, has become the primary source for marine deflection of the vertical (DOV) and gravity anomaly modelling. Limited by orbital inclinations, the precision of the meridian component of the gridded deflection of the vertical (GDOV) calculated by traditional altimetry satellites is significantly better than that of the prime vertical component, and the excessive precision difference between these two components restricts the inversion precision of marine gravity anomaly model. The study of cross-track deflection of the vertical (CTDOV) is enabled by the multibeam synchronous observation mode of the new laser altimetry satellite, Ice, Cloud and Land Elevation Satellite-2 (ICESat-2). Based on the remove-restore method, residual geoid gradients are first calculated in this paper using three approaches: along-track (A-T), cross-track (C-T) and an integration of along-track and cross-track. Vertical deflections are then computed on a 1′ × 1′ grid using the least squares collocation (LSC) method, and the precision is verified against the SIO V32.1_DOV model. An optimized combination is proposed to address the issue of precision differences between the meridian and prime vertical components, and to enhance the precision of DOV inversion. A new DOV combination is formed by combining the meridian component from along-track deflection of the vertical (ATDOV) with the prime vertical component from cross-track deflection of the vertical (CTDOV) based on the remove-restore method. The Philippine Sea (0°–35°N, 120°–150°E) is selected as the test area to verify the feasibility of the optimized combination. The results indicate that the optimized combination of the meridian and prime vertical components achieved test precision of 2.63 and 3.33 μrad, respectively, when compared against the SIO V32.1_DOV model. The precision gap between the components is effectively narrowed by this approach, which maintains the precision of the meridian component and enhances that of the prime vertical component, thereby achieving optimal inversion precision for gravity anomalies.

Estimates of Baroclinic Tidal Sea Level and Currents from Lagrangian Drifters and Satellite Altimetry

Abstract Internal waves generated by the interaction of the surface tides with topography are known to propagate long distances and lead to observable effects such as sea level variability, ocean currents, and mixing. In an effort to describe and predict these waves, the present work is concerned with using geographically distributed data from satellite altimeters and drifting buoys to estimate and map the baroclinic sea level associated with the M2, S2, N2, K1, and O1 tides. A new mapping methodology is developed, based on a mixed L1/L2-norm optimization, and compared with previously developed methods for tidal estimation from altimeter data. The altimeter and drifter data are considered separately in their roles for estimating tides and for cross-validating estimates obtained with independent data. Estimates obtained from altimetry and drifter data are found to agree remarkably well in regions where the drifter trajectories are spatially dense; however, heterogeneity of the drifter trajectories is a disadvantage when they are considered alone for tidal estimation. When the different data types are combined by using geodetic mission altimetry to cross validate estimates obtained with either exact-repeat altimetry or drifter data, and subsequently averaging the latter estimates, the estimates significantly improve on the previously published HRET8.1 model, as measured by their utility for predicting sea level and surface currents in the open ocean. The methodology has been applied to estimate the annual modulations of M2, which are found to have much smaller amplitudes compared to those reported in HRET8.1, and suggest that the latter estimates of these tides were not reliable. Significance Statement The mechanical and thermodynamic forcing of the ocean occurs primarily at very large scales associated with the gravitational perturbations of the sun and moon (tides), atmospheric wind stress, and solar insolation, but the frictional forces within the ocean act on very small scales. This research addresses the question of how the large-scale tidal forcing is transformed into the smaller-scale motion capable of being influenced by friction. The results show where internal waves are generated and how they transport energy across ocean basins to eventually be dissipated by friction. The results are useful to scientists interested in mapping the flows of mechanical energy in the ocean and predicting their influences on marine life, ocean temperature, and ocean currents.

A novel Slepian approach for determining mass-term sea level from GRACE over the South China Sea

Treatment of land-to-ocean leakage is crucial in modeling the mass-term sea level (MSL) using the Gravity Recovery and Climate Experiment (GRACE) satellite gravity measurements. In this study, we utilized the Spherical Slepian functions (SSFs) to determine MSL variations in the South China Sea. A sensitivity simulation in terms of trend, annual amplitude, and phase revealed that the SSF solution with a 1° coastal buffer zone provides a better land-to-ocean leakage correction than traditionally used Spherical Harmonics (SH). It was also found that an additional smoothing procedure for SSF with low concentrating energy could significantly reduce the high-frequency noise in GRACE (e.g., the north–south strips). The spatiotemporal characteristics of the true MSL were further compared among GRACE SH and Mascon solutions, model-predicted ocean bottom pressure, and steric-corrected altimetric data (i.e., satellite-altimetric sea level minus steric effect). Results revealed that despite the SSF-inverted regional MSL solution being generally similar to other results, this technique notably recovered the realistic magnitude of detailed features. The apparent MSL signal was, for instance, precisely recovered in the central part of the Gulf of Thailand and the Sunda Shelf by the SSF, while the SH significantly underestimated it due to smoothing. In addition to the seasonality, the interannual signal decomposed from the SSF-inverted residual MSL (by removing the trend and periodic signals) was the strongest and well cross-correlated with the Southern Oscillation Index. With more detailed spatial patterns revealed by MSL from GRACE SSF, our findings demonstrate that SSF is more suitable for regional-scale studies.

Machine learning models applied to altimetry era tide gauge and grid altimetry data for comparative long-term trend estimation: A study from Shikoku Island, Japan

Estimation of sea level trends is essential for understanding sea level rise dynamics. In this study, the performance of traditional Ordinary Least Squares (OLS) linear trend forecasting is compared with modern machine learning techniques, specifically Random Forests (RF) and Least Squares Support Vector Machines (LS-SVM).These methods are applied to 50 years of long-term tide gauge (TG) data from six tide gauge stations off the coast of Shikoku Island, Japan, and CMEMS Grid Altimetry data from 1993 to the present. The analysis uses OLS, RF, and LS-SVM to estimate trends from both data sets and compares the results. The objective is to determine the consistency and accuracy of RF and LS-SVM methods compared to the OLS method. The results indicate that machine learning algorithms (LS-SVM) effectively estimate sea level trends, offering potential improvements in precision for both long-term and medium-term analyses. Shikoku Island's coastal sea level trend is determined as 2.91±1.44 mm/yr using TG data and 3.00±1.52 mm/yr using CMEMS Grid Altimeter data with the OLS approach. Using the LS-SVM approach, the trend is found as 2.96±1.58 mm/yr with TG data and 3.02±1.60 mm/yr with CMEMS Grid Altimetry data. The novelty of this study lies in its thorough comparison of traditional and machine learning approaches for sea level trend estimation, providing valuable insights for future predictions of the sea level rise.

Estimating Nearshore Morphological Change through Ensemble Optimal Interpolation with Altimetric Data

Estimating Nearshore Morphological Change through Ensemble Optimal Interpolation with Altimetric Data

Southwest Pacific Ocean Warming Driven by Circulation Changes

AbstractAn area of ocean centered on 179°E, 46°S has warmed to full depth since 2006, with surface warming around 5 times the global rate. This Subtropical Front area is associated with a confluence of warm, salty, subtropical water from the north carried in a western boundary current and cold, fresh, subantarctic water from the south carried in the northernmost branch of the Antarctic Circumpolar Current. Temperature and salinity changes observed from Argo floats indicate that the Subtropical Frontal Zone has moved west ∼120 km, creating this area of strong warming analogous to changes in extension regions of other western boundary currents. The warming is a result of changes in the local flows of subantarctic water, evident in satellite altimeter data and 1,000 m Argo trajectories, which in turn likely result from changes in meridional ocean heat content and winds. The warming has placed this biologically‐significant region in almost perpetual marine heatwave conditions.

Variability and Dynamics of the Kuroshio and Mindanao Current during the 2010/11 La Niña and in Late 2012

Abstract Variability of two Pacific western boundary currents (WBCs)—the Kuroshio and the Mindanao Current—during the strong 2010/11 La Niña event is investigated using ship-based hydrographic observations and moored current-meter data collected off the east coasts of the Philippines. The geostrophic currents calculated using the hydrographic data show that, during the 2010/11 La Niña winter, the Kuroshio decreased by ∼10 Sv (1 Sv ≡ 106 m3 s−1), whereas the Mindanao Current increased by ∼5–10 Sv, relative to the normal winter in late 2012. The interannual variability based on the hydrographic data is confirmed by moored current-meter measurements and satellite altimeter geostrophic currents. A coastally trapped Kelvin wave model is used to explain the interannual variability of the two WBCs during the different ENSO phases. The good comparison of the simulated sea level anomalies around the Philippines with the altimeter data suggests that the interannual variability of the WBCs is associated with Kelvin wave propagation from the Sulawesi–Sulu Seas clockwise around the Philippine Archipelago. We identified that the Kelvin waves are excited by downwelling equatorial Rossby waves propagating into the Indonesian Seas during the La Niña. The transport anomalies of the WBCs are comparable to the total meridional transport anomalies integrated across the interior North Pacific Ocean, suggesting the importance of the WBCs in the heat charge–discharge processes of the western Pacific warm pool during ENSO events. Significance Statement The two western boundary currents (WBCs)—the Kuroshio and the Mindanao Current—play the role of closing the subtropical and tropical gyre circulation of the Pacific Ocean. Their variability during ENSO is unknown. Existing studies based on numerical modeling suggest that their variability is highly correlated with ENSO, with the Kuroshio stronger and Mindanao Current weaker during La Niña and vice versa during El Niño. Here, we use in situ hydrographic observations combined with mooring and satellite altimeter data to show that the Kuroshio transport decreases and the Mindanao Current transport increases during the 2010/11 La Niña, the dynamics of which are controlled by the Kelvin wave propagation from the Sulawesi–Sulu Seas clockwise around the Philippine Archipelago. The result is important for the warm pool dynamics during ENSO.

Assessment of Sentinel-6 SAR mode and reprocessed Jason-3 sea level measurements over global coastal oceans

With dedicated coastal processing strategies and advanced Delay-Doppler technique, the quality of altimeter data from Low-Resolution Mode (LRM) and Synthetic Aperture Radar (SAR) mode altimeters in coastal areas have been greatly improved. In this study, we present a new 20-Hz along-track sea level anomaly (SLA) dataset of Jason-3 within 100 km to the global coastlines using the modified SCMR (Seamless Combination of Multiple Retrackers) processing strategy. The new reprocessed Jason-3 dataset, along with Sentinel-6 Michael Freilich (MF) SAR mode data, are evaluated and validated over global coastal oceans. The evaluation results show that the modified SCMR has significantly increases the data availability by 16%–67% for Jason-3 when compared to the official SGDR MLE4 dataset, especially in the last 5 km to the coast. The resultant data availability retains >90% beyond 5 km to the coast and 80% within 5 km to the coast, which is slightly higher (2%–10%) than that obtained by the Sentinel-6 MF. Most importantly, the modified SCMR mitigates the hump artifacts observed for the SLA spectrums of LRM altimeters, which makes the noise level of 20-Hz SLA estimates from Jason-3 (5.52 cm) comparable with that from Sentinel-6 MF (5.42 cm). This result demonstrates that the modified SCMR strategy would improve the LRM altimeters' capability of monitoring the mesoscale eddies. The evaluation results also show that the Sentinel-6 MF SAR mode data obtain higher data precision but lower data availability than reprocessed Jason-3 LRM data, especially in the 0–5 km coastal strip and mid-to-high latitude (>40°N or < 40°S) regions. Although the quality of altimeter data in the 0–5 km coastal strip has been significantly improved, the validation results against tide gauges demonstrate that the degraded performance still occurs when compared to the results beyond 5 km offshore. The significant discrepancy between tide gauge records and altimeter data is found in places such as sheltered bays and archipelagos where the land contamination is severe, and thus the development of dedicated coastal retrackers and corrections for SAR mode altimeters is still of great importance. Finally, the good consistency between reprocessed Jason-3 LRM and Sentinel-6 MF SAR mode altimeter datasets has been found by examining the inter-mission SLA biases (−0.12 ± 0.01 m).