Sea Surface Height Research Articles

The response of sea ice and high-salinity shelf water in the Ross Ice Shelf Polynya to cyclonic atmosphere circulations

Abstract. Coastal polynyas in the Ross Sea are important source regions of high-salinity shelf water (HSSW) – the precursor of Antarctic Bottom Water that supplies the lower limb of the thermohaline circulation. Here, the response of sea ice production and HSSW formation to synoptic-scale and mesoscale cyclones was investigated for the Ross Ice Shelf Polynya (RISP) using a coupled ocean–sea ice–ice shelf model targeted on the Ross Sea. When synoptic-scale cyclones prevailed over RISP, sea ice production (SIP) increased rapidly by 20 %–30 % over the entire RISP. During the passage of mesoscale cyclones, SIP increased by about 2 times over the western RISP but decreased over the eastern RISP, resulting respectively from enhancement in the offshore and onshore winds. HSSW formation mainly occurred in the western RISP and was enhanced responding to the SIP increase under both types of cyclones. Promoted HSSW formation could persist for 12–60 h after the decay of the cyclones. The HSSW exports across the Drygalski Trough and the Glomar Challenger Trough were positively correlated with the meridional wind. Such correlations are mainly controlled by variations in geostrophic ocean currents that result from sea surface elevation change and density differences.

Seasonal West‐East Seesaw of M2 Internal Tides From the Luzon Strait

AbstractSatellite altimetry sea surface height (SSH) measurements from 1993 to 2017 are used to investigate the seasonal variability of mode‐1 M2 internal tides from the Luzon Strait. The 25 years of SSH data are divided into four seasonal subsets, from which four seasonal internal tide models are constructed following the same mapping procedure. Climatological seasonal hydrography in the World Ocean Atlas 2013 is used to calculate two seasonally variable parameters required in the mapping procedure: Wavelength and the transfer function from the SSH amplitude to depth‐integrated energy flux. The M2 internal tides from the Luzon Strait are extracted using propagation direction determined in plane wave analysis. The satellite results show that the westward and eastward M2 internal tides both demonstrate significant seasonal variation. The westward and eastward internal tides seesaw seasonally: The westward internal tides strengthen (weaken) in summer and fall (winter and spring); while the eastward internal tides strengthen (weaken) in winter and spring (summer and fall). We suggest that the seasonal seesaw is mainly determined by ocean stratification and the Kuroshio Current; however, further studies are needed to quantify their relative contributions.

Iterative data assimilation approach for the refinement of marine geoid models using sea surface height and dynamic topography datasets

Iterative data assimilation approach for the refinement of marine geoid models using sea surface height and dynamic topography datasets

An Assessment of the Oceanic Physical and Biogeochemical Components of CMIP5 and CMIP6 Models for the Ross Sea Region

AbstractThe physical and biogeochemical performance of 16 CMIP5 and 16 CMIP6 Earth System models (ESM) are examined relative to present day (1976–2005) observational data sets for a Ross Sea Region (RSR) containing the Ross Gyre (RG) and the Ross Sea Continental Shelf. A relative ranking scheme using error metrics and published ESM properties (including climate sensitivity parameters and anomalous deep ocean convection statistics) enables identification of a “best” ensemble of models for the RSR. Over the RSR the CMIP6 models are generally found to have improved physical representations compared to the CMIP5 set (based on our metrics for sea ice concentration, sea surface temperature, salinity, and height, and mixed layer depth), but the CMIP5 and CMIP6 biogeochemical representations remain similar. Examination of mean properties for the period 2081 to 2100 for RCP8.5 and SSP585 for CMIP5 and CMIP6, respectively, shows significant surface temperature increases, with significant decreases in sea surface salinity, sea ice concentration, and mixed layer depth across the RSR. Biogeochemically, there are generally small increases in surface values for chlorophyll, integrated primary production, and zooplankton carbon concentrations. The projections also have robust reductions in surface nitrate, phosphate, and silicate across the RSR. For that part of the RG circulation to the east of 180°E—which we refer to as the “inner RG”—significant barotropic transport increases are found by the end of century.

Subinertial Sea Surface Heights Anomalies Estimated Using High Frequency Radar Surface Current Data in the Mississippi Bight

AbstractSea level studies in the Mississippi Bight (MSB) are less abundant than in other coastal waters of USA. This study investigates the subinertial (time scales >2 days) sea level anomalies in the MSB shelf. The diagnostics of the terms in the invariant form of the momentum equation were computed to determine which terms have the most influence on the anomalies in sea level. It was determined that at subinertial scales the geostrophic balance is the dominant balance in the MSB while the non‐linear and time derivative terms are insignificant relative to the Coriolis term. A Least Squares procedure was applied to the subinertial surface currents data from high frequency radar surface currents (filtered with a window of 2‐day Butterworth filter) to extract subinertial sea level anomalies in the MSB shelf using both geostrophic balance and the invariant form of Reynolds' averaged momentum equations. The resulting subinertial sea level anomalies were validated using sea level observations from an offshore buoy and Sentinel‐3 along‐track satellite altimeter data. The estimated sea level anomalies were reasonably close to observations (more than half had root mean square difference of <0.04 m) and mostly influenced by geostrophic balance. Analysis of the empirical orthogonal functions showed that the first two modes explained the majority (85%) of the variance in the sea level anomalies estimated using the geostrophic approximation. Absolute sea level could be estimated if Global Navigation Satellite System buoys are deployed in the radar footprint.

A Large Winter Chlorophyll‐a Bloom in the Southeastern Bay of Bengal Associated With the Extreme Indian Ocean Dipole Event in 2019

AbstractA large Chlorophyll‐a (Chla) bloom developed in the southeastern Bay of Bengal (BoB) (4°N–10°N, 88°E−95°E) during winter 2019 and was observed from Moderate Resolution Imaging Spectroradiometer‐Aqua Chla data. By analyzing various observational and reanalysis datasets, we found that remote Equatorial Indian Ocean (EIO) upwelling waves and local Ekman pumping associated with the extreme Indian Ocean Dipole (IOD) event in 2019 were responsible for the Chla bloom. The extreme IOD 2019 favored strong upwelling Kelvin waves propagating from the eastern EIO into the BoB along the eastern boundary. These Kelvin waves were reflected into the central BoB as upwelling Rossby waves manifested by eddylike sea surface height propagating westward approximately along 5°N. In addition, local wind stress curl generated strong Ekman pumping in the southeastern BoB. As a result, upwelling processes associated with westward‐propagating Rossby waves and local Ekman pumping together uplifted the thermocline, breaking the stratification so that subsurface nutrient‐rich water was transported to the surface to cause a large Chla bloom in the southeastern BoB during winter 2019. The Chla bloom had a ring structure and its spatial shape was modulated by westward upwelling Rossby waves and cyclonic eddies. This study highlights the important role of IOD events in the formation of Chla bloom in the southeastern BoB during winter.

Brightness Temperature and Wet Tropospheric Correction of HY-2C Calibration Microwave Radiometer Using Model-Derived Wet Troposphere Path Delay from ECMWF

The Calibration Microwave Radiometer (CMR) is a three-band radiometer deployed on the HY-2C satellite in a near-Earth orbit, and since it launched, there are few studies presented on the performance of CMR to date. Therefore, this paper focuses on providing an assessment of HY-2C CMR brightness temperature and wet troposphere correction (WTC). CMR works at 18.7 GHz, 23.8 GHz and 37 GHz in a nadir-viewing direction, aligned with the HY-2C radar altimeter. The wet troposphere path delay of the radar altimeter signal caused by water vapour and cloud liquid water content can be monitored and corrected by CMR. In this paper, guided by the concept of antenna pattern correction algorithm and a purely statistical method, we directly establish the function between the CMR antenna temperature and the model-derived WTC calculated by the European Centre from Medium-Range Weather Forecasting (ECMWF) Reanalysis data, which can obtain the brightness temperature and the WTC of CMR simultaneously. Firstly, the algorithm principle of CMR to establish the function between the antenna temperature and the model-derived WTC is introduced, and then the brightness temperature of CMR is evaluated using reference brightness temperatures of the Advanced Microwave Radiometer 2 (AMR-2) on Jason-3 satellite at crossover points. Furthermore, the performance of the CMR WTC is validated in three ways: (1) directly comparing with the colocated WTC measured by Jason-3 AMR-2, (2) directly comparing with model-derived WTC from ECMWF, which allows a rapid check at a global scale, (3) comparing the standard deviation of the Sea Surface Height (SSH) difference at crossover points using different WTC retrieval methods. The linear fit with Jason-3 brightness temperature and WTC in all non-precipitation conditions demonstrated a good agreement with Jason-3. In addition, the WTC of CMR has an obvious decrease in the standard deviation of the SSH difference compared with model-derived WTC, indicating the CMR can significantly improve the accuracy of the HY-2C SSH measurements. All the assessments indicate that the CMR performances are satisfying the expectations and fulfilling the mission requirements.

Particulate organic carbon in the deep-water region of the Gulf of Mexico

Ocean eddies play a major role in lateral and vertical mixing processes of particulate organic carbon (POC), as well as in the transport of heat, salinity, and biogeochemical tracers. In the open waters of the Gulf of Mexico (GoM), however, there are limited observations to characterize how these mesoscale structures affect the spatial distribution of POC in the upper water column, which is important for organic matter cycling and export. We present the distribution patterns of POC relative to mesoscale features throughout the water column in the deep-water region of the GoM during three oceanographic cruises held during the summer months of 2015, 2016, and 2017. Samples were collected under well-stratified upper ocean conditions, which allowed us to assess the spatial and temporal distribution of POC as a function of non-steric sea surface height, density, apparent oxygen utilization, and chlorophyll fluorescence. We further explored the variability of integrated surface layer POC concentrations at stations located within the cores and the edges of cyclonic and anticyclonic eddies, and those collected outside these structures. Although our results indicate mesoscale eddies modulate several important physical and biogeochemical variables and POC concentrations in the upper ocean, these features do not fully explain the spatial distribution of POC concentrations throughout the deep-water region of the GoM. Relatively lower POC concentrations were observed in the border of the cyclonic and the center of the anticyclonic eddies, in contrast to the relatively higher POC concentrations at the center of the cyclonic and the border of anticyclonic eddies. We observed high variability in POC concentration variability outside mesoscale structures, which may be attributed to other processes such as upwelling over the shelves, and the contribution by rivers during the summer especially in the northern and southern GoM.

A Synthetic Spring‐Neap Tidal Cycle for Long‐Term Morphodynamic Models

AbstractExisting tidal input reduction approaches applied in accelerated morphodynamic simulations aim to capture the dominant tidal forces in a single or double representative tidal cycle, often referred to as a “morphological tide.” These strongly simplified tidal signals fail to represent the tidal extremes and hence poorly allow to represent hydrodynamics in the intertidal areas. Here, a generic method is developed to construct a synthetic spring‐neap tidal cycle that (a) represents the original signal; (b) is exactly periodic; and (c) is derived directly from tidal time series or harmonic constituents. The starting point is a fortnightly modulation of the semidiurnal tide to represent spring‐neap variations, while conserving periodicity. Diurnal tides and higher harmonics of the semidiurnal tide are included to represent the asymmetry of the tide. The amplitudes and phases of the synthetic signal are then fitted to histograms of water levels and water level gradients derived from the original sea surface elevation time series. A depth‐averaged model of the Ems estuary (The Netherlands) demonstrates the effects of alternative tidal input reduction techniques. Adopting the new approach, the along‐estuary variation in tidal wave shape is well‐represented, leading to an improved representation of extreme tidal conditions. Especially the more realistic representation of intertidal dynamics improves the overall hydrodynamics and residual sand transport patterns, approaching nonschematized tidal dynamics.

Impact of satellite and regional in-situ profile data assimilation on a high-resolution ocean prediction system in the Northwest Pacific

The impacts of observation data sets on the high-resolution (1/24°) Northwest Pacific prediction system were investigated with the model sensitivity tests. We compared the model experiments assimilating the different combinations of the observation data sets, such as the sea surface height derived from satellite altimetry, sea surface temperature, and in-situ profiles, based on the Ensemble Optimal Interpolation. Pseudo-profiles constructed by the method of Cooper and Haines (1996, CH96) were assimilated into the model to assimilate sea surface height data. CH96 applied a conservation principle to derive pseudo-profiles by rearranging preexisting profiles. The comparison of the model experiments suggests that each observation data set enhances the model performance. Especially, the assimilation of the sea surface height reduces the model error by more than 9.81% and 6.44%, respectively, in terms of the root-mean-square error of the ocean temperature and salinity in the subsurface layer. It is interesting that the assimilation of the in-situ temperature profiles in the Korean marginal seas contributes to improving the reproducibility of the subsurface temperature and salinity in the East/Japan Sea (EJS) as well as Kuroshio-Kuroshio Extension (K-KE) regions. The improvement in the K-KE region seems to be related to the reproducibility of the Kuroshio axis. As the water mass in the EJS flows into the Pacific Ocean through the Tsugaru Strait, it affects the front of the Sanriku confluence, and it seems to eventually control the Oyashio Current and Kuroshio axis. In conclusion, this study evaluated the contribution of each observation component to ocean analysis in the KOOS-OPEM and confirmed the role of the existing observation networks. This study also suggests that greater attention should be paid to the role of regional ocean observation networks to improve the forecast skill of the ocean prediction system not only in the region but also in the open ocean, such as the Pacific Ocean.

The Impact of Altimetry Corrections of Sentinel-3A Sea Surface Height in the Coastal Zone of the Northwest Atlantic

Corrections to altimeter-measured sea surface height anomalies (SSHA) have a larger proportional effect for synthetic aperture radar (SAR) altimetry than conventional, pulse-limited altimetry because of lower range noise. Here, we quantified the impact of the current generation of altimeter corrections in the coastal zone of the Northwest Atlantic, a region with significant dynamic activity. In this study, we used the sea level variance analysis to determine the change in variance for the altimeter corrections—range, geophysical, and mean surface—compared to the baseline. We also evaluated the performance of two coastal retrackers, ALES (empirical) and SAMOSA++ (fully analytical), against the SSHA from the Radar Altimeter Database System (RADS), which uses the standard SAR retracker. Tide corrections caused the largest change in sea level variance, followed by wet tropospheric corrections and sea state bias. Most non-standard altimeter corrections failed to reduce the sea level variance and performed markedly worse closer to the coast. Coastal retrackers showed a higher deviation from the standard SSHA closer to the coast, especially when the backscatter coefficient was high and the significant wave height was low. We conclude that further development of coastal corrections is needed. Contrary to our prior expectation, we found that standard altimetry corrections appear to perform as well as alternative more advanced/tailored corrections.

Application of the random forest algorithm for mapping potential fishing zones of Rastrelliger kanagurta off the east coast of peninsular Malaysia

Indian mackerel, Rastrelliger kanagurta, play an important role in the marine fisheries of Malaysia, and their distribution is reported to be influenced by various oceanographic conditions. In this study, a modeling framework of machine learning techniques (random forest [RF]) and spatial analysis with geographic information systems (hotspot analysis) was used to predict and map potential fishing zones of R. kanagurta in the exclusive economic zone (EEZ) waters off the east coast of peninsular Malaysia. The RF model was constructed with a training dataset (n = 2535) and externally validated by a testing dataset (n = 1087). Model validation using Lin’s concordance correlation coefficient (CCC) on the testing dataset indicated good agreement (CCC = 0.811) between the predicted and observed catch per unit effort (CPUE) of R. kanagurta. The variable importance plot revealed the relative importance of four predictors of potential habitat, ranked in decreasing order of importance: sea surface height anomaly (SSHA), eddy kinetic energy (EKE), sea surface temperature (SST) and surface chlorophyll-a (CHL) concentration. Partial dependence shows that R. kanagurta prefers a habitat with the following parameters: SSHA -0.05–0.20 m, EKE < 0.02 m2/s2 or > 0.07 m2/s2, SST 30–31 °C and CHL 0.1–0.3 mg/m3. Spatial distribution of predicted CPUE hotspots were found to be closely related to the thermal fronts, which influenced by the monsoonal wind and occurrence of upwelling event in the study area. Our study indicates that cost-effective satellite-derived products can be used to predict potential fishing zones of R. kanagurta and provide useful information on relationship between environmental factors and CPUE of R. kanagurta.

A study on the quality of GNSS signals for extracting the sea level height and tidal frequencies utilizing the GNSS-IR approach

Coastal global navigation satellite system (GNSS) stations equipped with a standard geodetic receiver and antenna enable water level measurement using the GNSS interferometry reflectometry (GNSS-IR) technique. By using GNSS-IR, the vertical distance between the antenna and the reflector surface (e.g., water surface) can be obtained in the vertical (height) reference frame. In this study, the signal-to-noise ratio (SNR) data from four selected stations over three months are used for this purpose. We determined the predominant multipath frequency in SNR data that is obtained using Lomb–Scargle periodogram (LSP) method. The obtained sea surface heights (SSH) are assessed using tide gauge observations regarding accuracy and correlation coefficients. In this study, we investigated daily and hourly GNSS observations and used single frequencies of GPS (L1, L2 and L5), GLONASS (L1 and L2), Galileo (L1, L5, L6, L7 and L8), and BeiDou (L2 and L7) signals to estimate the SSH. The results show that the optimal signals for extracting the SSH are the L1 signal for the GPS, Galileo, and GLONASS systems and the L2 signal for the BeiDou system. The accuracy and correlation parameters for the optimal GPS signal in the daily mode are 2 cm and 0.87, respectively. The same parameters for the optimal GLONASS signal are 4 cm and 0.91. However, the obtained accuracy and correlation coefficients using the best Galileo and BeiDou signals are reduced, i.e., 4 cm and 0.88 using Galileo and 12 cm and 0.52 by employing the Galileo signals, respectively. Our results also show that the GPS L1 signal is more consistent with the tide gauge data. In the following, using the time series derived from the L1 signal and tide gauge readings, the tidal frequencies are extracted and compared using the Least Square Harmonic Estimation (LS-HE) approach. The findings demonstrate that 145 significant tidal frequencies can be extracted using the GNSS-IR time series. The existence of an acceptable correlation between the tidal frequencies of the GNSS-IR and the tide gauge time series indicates the usefulness of the GNSS-IR time series for tide studies. From our results, we can conclude that the GNSS-IR technique can be applied in coastal locations alongside tide gauge measurements for a variety of purposes.

Comparison of two deep learning model YOLOF and Detectron2 for mesoscale eddies identification in the South China Sea

ABSTRACT Ocean mesoscale eddy is a special mesoscale phenomenon in the ocean, which widely exists in all oceans and marginal seas around the world. Compared with ordinary ocean circulation, mesoscale eddy has high rotating speed, strong current velocity, and average vertical depths of several kilometres, which play an important role in ocean circulation and material transport. The traditional mesoscale eddy identification and recognition have great subjectivity and usually depends on the parameters predefined or adjusted by experts, which cannot guarantee the accuracy. With the development of artificial intelligence, deep learning method has also been widely used in the detection and recognition of ocean eddies. Based on the sea-level anomaly (SLA) data provided by Copernicus Marine Environment Detection Service, this study compares the results of the ‘you only look once level feature’ (YOLOF) model and Detectron2 model in deep learning on marine mesoscale eddy detection. The mesoscale eddies in the South China Sea from 2011 to 2013 are detected and identified. The accuracy of Detectron2 model is about 57%, while the accuracy of YOLOF model can reach 90%. Comparing the performance of the two models on the same data set, it can be found that YOLOF model improves the accuracy and speed of recognition to a certain extent. The deep learning network model provides an effective technical method for the study of mesoscale eddy detection by sea surface height.

Comparison of methods for coupled earthquake and tsunami modelling

SUMMARY Tsunami generation by offshore earthquakes is a problem of scientific interest and practical relevance, and one that requires numerical modelling for data interpretation and hazard assessment. Most numerical models utilize two-step methods with one-way coupling between separate earthquake and tsunami models, based on approximations that might limit the applicability and accuracy of the resulting solution. In particular, standard methods focus exclusively on tsunami wave modelling, neglecting larger amplitude ocean acoustic and seismic waves that are superimposed on tsunami waves in the source region. In this study, we compare four earthquake-tsunami modelling methods. We identify dimensionless parameters to quantitatively approximate dominant wave modes in the earthquake-tsunami source region, highlighting how the method assumptions affect the results and discuss which methods are appropriate for various applications such as interpretation of data from offshore instruments in the source region. Most methods couple a 3-D solid earth model, which provides the seismic wavefield or at least the static elastic displacements, with a 2-D depth-averaged shallow water tsunami model. Assuming the ocean is incompressible and tsunami propagation is negligible over the earthquake duration leads to the instantaneous source method, which equates the static earthquake seafloor uplift with the initial tsunami sea surface height. For longer duration earthquakes, it is appropriate to follow the time-dependent source method, which uses time-dependent earthquake seafloor velocity as a forcing term in the tsunami mass balance. Neither method captures ocean acoustic or seismic waves, motivating more advanced methods that capture the full wavefield. The superposition method of Saito et al. solves the 3-D elastic and acoustic equations to model the seismic wavefield and response of a compressible ocean without gravity. Then, changes in sea surface height from the zero-gravity solution are used as a forcing term in a separate tsunami simulation, typically run with a shallow water solver. A superposition of the earthquake and tsunami solutions provides an approximation to the complete wavefield. This method is algorithmically a two-step method. The complete wavefield is captured in the fully coupled method, which utilizes a coupled solid Earth and compressible ocean model with gravity. The fully coupled method, recently incorporated into the 3-D open-source code SeisSol, simultaneously solves earthquake rupture, seismic waves and ocean response (including gravity). We show that the superposition method emerges as an approximation to the fully coupled method subject to often well-justified assumptions. Furthermore, using the fully coupled method, we examine how the source spectrum and ocean depth influence the expression of oceanic Rayleigh waves. Understanding the range of validity of each method, as well as its computational expense, facilitates the selection of modelling methods for the accurate assessment of earthquake and tsunami hazards and the interpretation of data from offshore instruments.

Distribution and densities of fish larvae species with contrasting life histories as a function of oceanographic variables in the deep-water region of the southern Gulf of Mexico.

We describe the larval occurrence and density of six fish species with contrasting life histories and examine their relationships with oceanographic variables during two seasons in the deep-water region (> 1000 m) of the southern Gulf of Mexico based on 12 cruises (2011-2018). Given that Caranx crysos adults are neritic, larval presence close to the continental shelf indicates offshore cross-shelf transport to oceanic waters, which likely leads to mortality. Generalized additive models indicated that C. crysos density was not related with oceanographic variables, while Auxis spp. (with neritic and oceanic adults) was related to wind speed, sea surface temperature, sea surface height, and surface chlorophyll a. The mesopelagic Benthosema suborbitale, Notolychnus valdiviae and Bregmaceros atlanticus were more abundant and broadly distributed, and higher density was found in conditions indicative of higher nutrient availability and productivity, suggesting greater feeding success and survival. The distribution of the epi- and mesopelagic Cubiceps pauciradiatus extended through the southern Gulf of Mexico, and was related to wind speed, sea surface temperature, stratification and chlorophyll a. Our results suggest that the density of the neritic species in oceanic waters could be mediated by regional cross-shelf transport, while for oceanic species is linked with productivity.

Species distribution models describe spatial variability in mesopelagic fish abundance in the Southern Ocean

IntroductionMesopelagic fishes play a central role in the transfer of energy through open-ocean food webs, particularly in the Southern Ocean where they are both important predators of zooplankton and a key prey group for many higher predators. However, they are notoriously difficult to sample, which has limited our understanding of the bio-physical predictors of their abundance and spatiotemporal variability. Species distribution models can be used to help understand species’ ecological requirements by relating records of their presence or abundance to environmental data.MethodsHere, we used data from Myctobase – a new circumpolar database of mesopelagic fishes – to model patterns in abundance of eight key myctophid species (family Myctophidae) and the genus Bathylagus in the Southern Ocean south of 45°S. We developed species-specific boosted regression tree models to obtain circumpolar predictions of abundance. Average daytime and night-time summer predictions for the period 1997 to 2011 at 0 to 200m depths were generated for each species.ResultsDepth and solar position were important predictors and species were stratified in their depth distribution. For all species, except for G. nicholsi, there was an interaction between depth of capture and solar position, reflecting diel vertical migration. Other important variables included sea surface temperature, dissolved oxygen at 200 m, chlorophyll a, and sea surface height, indicating an association with water mass properties. Circumpolar patterns of abundance varied between species with some displaying affinities for oceanic regions at Antarctic latitudes (e.g., E. antarctica and Bathylagus spp.) or sub-Antarctic latitudes (e.g., K. anderssoni and P. tenisoni); and affinities for shelf regions (e.g., P. boliniand G. nicholsi).DiscussionOur findings suggest that the abundance of mesopelagic fish is influenced by diel vertical migration and meso- and sub-mesoscale oceanographic features, with the Polar Front being a major delimiting feature. Our study showed contrasting patterns in community composition with higher species diversity north of the Polar Front that might be indicative of latitudinal variability in food web structure. Our spatial analysis is an important step toward resolving what determines important habitat for mesopelagic fishes, providing foundational information for understanding shifting food web dynamics into the future.

High-Resolution Model of Clew Bay—Model Set-Up and Validation Results

Clew Bay is an important aquaculture production area in Ireland. In this study, we focused on a high-resolution simulation of the Clew Bay region based on a regional ocean modeling system (ROMS). Freshwater discharges from eight rivers are included in the model and a wetting–drying scheme has been implemented. The Clew Bay model simulation was validated and calibrated with available observations (e.g., acoustic Doppler current profiler (ADCP), vertical salinity and temperature profiles, and a tide gauge) in the geographic area of the model domain. High correlations were found between the model data and observed temperature, salinity and water levels, along with small root mean square errors. This indicates that the model is able to reproduce the oceanographic phenomena in the study area. The Taylor diagram analysis showed a high correlation coefficient (R = 0.99) between the observed bottom temperature in the Inner Bay and Clew Bay model, along with a small centered root mean square error (RMSD = 0.5 °C). High correlation coefficients (R &gt; 0.80) were found between the model and the two ADCPs for the zonal current component. There was a resemblance in structure between the model and the observed salinity profiles, indicating that freshwater was correctly implemented in the model. Moreover, the correlation coefficient between the model and the tidal sea surface height (SSH) was 0.99, with an RMSD of 0.09 m. We discovered that wind direction and speed had a significant impact on the bay’s water inflow rate. The model outputs can be used to provide scientists, fishermen, and decision-makers with hydrodynamic information on ocean conditions in the bay.

Reconstruction Methods in Oceanographic Satellite Data Observation—A Survey

Oceanographic parameters, such as sea surface temperature, surface chlorophyll-a concentration, sea surface ice concentration, sea surface height, etc., are listed as Essential Climate Variables. Therefore, there is a crucial need for persistent and accurate measurements on a global scale. While in situ methods tend to be accurate and continuous, these qualities are difficult to scale spatially, leaving a significant portion of Earth’s oceans and seas unmonitored. To tackle this, various remote sensing techniques have been developed. One of the more prominent ways to measure the aforementioned parameters is via satellite spacecraft-mounted remote sensors. This way, spatial coverage is considerably increased while retaining significant accuracy and resolution. Unfortunately, due to the nature of electromagnetic signals, the atmosphere itself and its content (such as clouds, rain, etc.) frequently obstruct the signals, preventing the satellite-mounted sensors from measuring, resulting in gaps—missing data—in satellite recordings. One way to deal with these gaps is via various reconstruction methods developed through the past two decades. However, there seems to be a lack of review papers on reconstruction methods for satellite-derived oceanographic variables. To rectify the lack, this paper surveyed more than 130 articles dealing with the issue of data reconstruction. Articles were chosen according to two criteria: (a) the article has to feature satellite-derived oceanographic data (b) gaps in satellite data have to be reconstructed. As an additional result of the survey, a novel categorising system based on the type of input data and the usage of time series in reconstruction efforts is proposed.

Evaluation of the sensitivity on mesoscale eddy associated with the sea surface height anomaly forecasting in the Kuroshio Extension

The sensitivity of the sea surface height anomaly (SSHA) forecasting on the accuracy of mesoscale eddies over the Kuroshio Extension region, which was determined by the conditional non-linear optimal perturbation (CNOP) method using a two-layer quasigeostrophic model, is evaluated by adopting multiply realistic marine datasets through an advanced particle filter assimilation method. It is shown that, if additional observations are preferentially assimilated to the sensitive area of mesoscale eddies identified by the CNOP, where the eddies present a clear high- to low-velocity gradient along the eddy rotation, the forecasting skill of the SSHA can be more significantly improved. It is also demonstrated that the forecasts of the SSHA in the region where the large-scale mean flow possesses much stronger barotropic and/or baroclinic instability tend to exhibit stronger sensitivity to the accuracy of the initial field in the sensitive area of mesoscale eddies. Therefore, more attention should be preferentially paid to the assimilation of the additional observations of the mesoscale eddies for the SSHA forecast in the region with a strong velocity shear of ocean circulation. The present study verifies the sensitivity on mesoscale eddies of SSHA forecasts derived by the two-layer quasigeostrophic model using multiply sets of realistic oceanic data, especially including observation and reanalysis data, which further additionally demonstrates the importance of targeted observations of mesoscale eddies to the SSHA forecast in the regions of strong velocity shear of ocean circulation and provides a more credible scientific basis for the field campaign of the targeted observations for mesoscale eddies associated with the SSHA forecasting.