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Due to the diffuse scattering on sea surface and dynamic geometry of coastal global navigation satellite system-reflectometry, the altimetry performance is strongly dependent on elevation angle. As the elevation angle decreases, the bias in retrieved height using the peak of the derivative waveform and the fractional power point of the waveform leading edge increases. In this article, a multiparameter estimator is proposed to combine the peak of the derivative waveform and several fractional power points to obtain unbiased height. The simulated results show that the bias of the uncalibrated height using the proposed algorithm has no significant dependence on elevation angle, but the standard derivation for the low elevation angle case still is larger than that of the high elevation angle. In addition, the calibrated performance depends on the used fractional values so that proper fractional values should be chosen. The data from the Dongying experiment acquiring GPS L1 CA and L5 signal and the Qingdao experiment for BeiDou B1I signal are used to demonstrate the proposed algorithm. After calibrating using the proposed algorithm, regardless of GPS L1 CA, L5, or BeiDou B1I signal, the calibrated heights all are in agreement with in situ heights. Finally, the calibrated heights from the BeiDou B1I signal are used to retrieve sea surface height. The results show that retrieved sea surface heights from geostationary Earth orbit (GEO) and inclined geosynchronous orbit/middle Earth orbit (IGSO/MEO) satellites all appear in the same trend as that of the in situ ones; furthermore, GEO satellites can provide a better retrieved performance than IGSO/MEO satellites. Through averaging the heights from several satellites and smoothing with the half-hour span, compared to in situ sea surface height, the standard derivation of 0.67 m is obtained.

Satellite data on the sea level heights and data of Argo floats for the southwestern Bering Sea and adjacent area of the North Pacific are analyzed. Interannual variability of the thermohaline structure and water dynamics caused by the nodal (declination) tide with the period of 18.6 years is revealed. The tidal-induced 18.6-year variability is traced in variations of the sea level, water temperature and direction and velocity of the geostrophic currents. Extreme strengthening (in 2006) and weakening (in 1997 and 2015) of nodal tides led to lowering/rising of the sea level heights in the southwestern Bering Sea and in the areas southward from the Near Strait and Commander Islands. The sea level lowering was associated with increasing of salinity and water density in the layer of 50–400 m; as the result, the salinity and density at the depth of temperature minimum (~100 m) were higher in 2005–2006 than in 2015–2016 by 0.20 psu and 0.14 kg . m–3, respectively. This increasing can be explained by transformation of the Alaskan Stream waters due to intensified tidal mixing in the Aleutian Passes and in the Near Strait. No statistically significant correlation between the sea level and amplitude of the nodal tide was found in the areas remoted from the straits. Another consequence of the sea level lowering was an appearance of cyclonic circulation northward and southward from the Near Strait and weakening of the Alaskan Stream in spring of 2006, with cessation of the flow from the Near Strait to the mainland coast that caused SST decreasing in the southwestern Bering Sea. Intensification (weakening) of nodal tides was accompanied by decreasing (increasing) of sockeye salmon catches at East Kamchatka and Aleutian Islands.

A spatiotemporal empirical orthogonal function (STEOF) forecast method is proposed and used in medium- to long-term sea surface height anomaly (SSHA) forecast. This method embeds temporal information in empirical orthogonal function spatial patterns, effectively capturing the evolving spatial distribution of variables and avoiding the typical rapid accumulation of forecast errors. The forecast experiments are carried out for SSHA in the South China Sea to evaluate the proposed model. Experimental results demonstrate that the STEOF forecast method consistently outperforms the autoregressive integrated moving average (ARIMA), optimal climatic normal (OCN), and persistence prediction. The model accurately forecasts the intensity and location of ocean eddies, indicating its great potential for practical applications in medium- to long-term ocean forecasts.

As a member of the Chinese modeling groups, the coupled ocean-ice component of the Chinese Academy of Sciences’ Earth System Model, version 2.0 (CAS-ESM2.0), is taking part in the Ocean Model Intercomparison Project Phase 1 (OMIP1) experiment of phase 6 of the Coupled Model Intercomparison Project (CMIP6). The simulation was conducted, and monthly outputs have been published on the ESGF (Earth System Grid Federation) data server. In this paper, the experimental dataset is introduced, and the preliminary performances of the ocean model in simulating the global ocean temperature, salinity, sea surface temperature, sea surface salinity, sea surface height, sea ice, and Atlantic Meridional Overturning Circulation (AMOC) are evaluated. The results show that the model is at quasi-equilibrium during the integration of 372 years, and performances of the model are reasonable compared with observations. This dataset is ready to be downloaded and used by the community in related research, e.g., multi-ocean-sea-ice model performance evaluation and interannual variation in oceans driven by prescribed atmospheric forcing.

Sea state bias (SSB) is an important component of errors for the radar altimeter measurements of sea surface height (SSH). However, existing SSB estimation methods are almost all based on single-task learning (STL), where one model is built on the data from only one radar altimeter. In this paper, taking account of the data from multiple radar altimeters available, we introduced a multi-task learning method, called trace-norm regularized multi-task learning (TNR-MTL), for SSB estimation. Corresponding to each individual task, TNR-MLT involves only three parameters. Hence, it is easy to implement. More importantly, the convergence of TNR-MLT is theoretically guaranteed. Compared with the commonly used STL models, TNR-MTL can effectively utilize the shared information between data from multiple altimeters. During the training of TNR-MTL, we used the JASON-2 and JASON-3 cycle data to solve two correlated SSB estimation tasks. Then the optimal model was selected to estimate SSB on the JASON-2 and the HY-2 70–71 cycle intersection data. For the JSAON-2 cycle intersection data, the corrected variance (M) has been reduced by 0.60 cm2 compared to the geophysical data records (GDR); while for the HY-2 cycle intersection data, M has been reduced by 1.30 cm2 compared to GDR. Therefore, TNR-MTL is proved to be effective for the SSB estimation tasks.

Using data on the distribution of temperatures in the Pacific, Indian, and Atlantic Oceans, large-scale structures of spatial and temporal variations of these temperatures are investigated. A structure is found which is almost identical to the spatial and temporal sea surface temperature (SST) structure that is characteristic of the recently found Global Atmospheric Oscillation. Variations in water temperature in a near-equatorial zone of the Pacific Ocean at depths up to about 150 m behave themselves in the same way as variations in sea surface height and SST. At even greater depths, variations in water temperature reveal a “striped” structure, which is, however, overall similar to that of SST variations. Variations of water temperature at depths in all three oceans spread from east to west along the equator with a period of 14 months. This makes it possible to think that the dynamics of these temperatures are controlled by the so-called Pole tides. The surface North Pacific Pole Tide was found previously responsible for excitation of El Nino. The deep Pole tides in the Southern Atlantic and Southern Indian Ocean appear to be triggers of the Atlantic El Nino and Indian Ocean Dipole (IOD). Thus, IOD manifests itself at the depth of the thermocline more clearly than on the surface of the Indian Ocean. The out-of-phase behavior of El Nino and IOD is explained by the 180° difference in the longitudes of these phenomena.

As part of the Flow Encountering Abrupt Topography (FLEAT) program, an array of pressure-sensor equipped inverted echo sounders (PIESs) was deployed north of Palau where the westward-flowing North Equatorial Current encounters the southern end of the Kyushu–Palau Ridge in the tropical North Pacific. Capitalizing on concurrent observations from satellite altimetry, FLEAT Spray gliders, and shipboard hydrography, the PIESs’ 10-month duration hourly bottom pressure p and round-trip acoustic travel time τ records are used to examine the magnitude and predictability of sea level and pycnocline depth changes and to track signal propagations through the array. Sea level and pycnocline depth are found to vary in response to a range of ocean processes, with their magnitude and predictability strongly process dependent. Signals characterized here comprise the barotropic tides, semidiurnal and diurnal internal tides, southeastward-propagating superinertial waves, westward-propagating mesoscale eddies, and a strong signature of sea level increase and pycnocline deepening associated with the region’s relaxation from El Niño to La Niña conditions. The presence of a broad band of superinertial waves just above the inertial frequency was unexpected and the FLEAT observations and output from a numerical model suggest that these waves detected near Palau are forced by remote winds east of the Philippines. The PIES-based estimates of pycnocline displacement are found to have large uncertainties relative to overall variability in pycnocline depth, as localized deep current variations arising from interactions of the large-scale currents with the abrupt topography around Palau have significant travel time variability.

The Brazilian Earth System Model (BESM-OA2.5), while simulating the historical period proposed by the fifth phase of the Coupled Model Intercomparison Project (CMIP5), detects an increasing trend in the sea surface height (SSH) on the southern hemisphere oceans relative to that of the pre-industrial era. The increasing trend is accentuated in the CMIP5 RCP4.5 and RCP8.5 future scenarios with higher concentrations of greenhouse gases in the atmosphere. This study sheds light on the sources of such trends in these regions. The results suggest an association with the thermal expansion of the oceans in the upper 700 m due to a gradual warming inflicted by those future scenarios. BESM-OA2.5 presents a surface height increase of 0.11 m in the historical period of 1850–2005. Concerning future projections, BESM-OA2.5 projects SSH increases of 0.14 and 0.23 m (relative to the historical 2005 value) for RCP4.5 and RCP8.5, respectively, by the end of 2100. These increases are predominantly in a band of latitude within 35–60°S in the Atlantic and Indian oceans. The reproducibility of the trend signal detected in the BESM-OA2.5 simulations is confirmed by the results of three other CMIP5 models.

A new wave data set from the southern North Sea covering the period 2011–2016 and composed of wave buoy and radar measurements sampling the sea surface height at frequencies between 1.28 and 4 Hz was quality controlled and scanned for the presence of rogue waves. Here, rogue waves refer to waves whose height exceeds twice the significant wave height. Rogue wave frequencies were analyzed and compared to Rayleigh and Forristall distributions, and spatial, seasonal, and long-term variability was assessed. Rogue wave frequency appeared to be relatively constant over the course of the year and uncorrelated among the different measurement sites. While data from buoys basically correspond with expectations from the Forristall distribution, radar measurement showed some deviations in the upper tail pointing towards higher rogue wave frequencies. The amount of data available in the upper tail is, however, still too limited to allow a robust assessment. Some indications were found that the distribution of waves in samples with and without rogue waves was different in a statistical sense. However, differences were small and deemed not to be relevant as attempts to use them as a criterion for rogue wave detection were not successful in Monte Carlo experiments based on the available data.

A persisting problem in ocean modeling around coastal areas has been the adequate imposition of open boundary conditions, especially in the presence of complex bathymetric features commonly found in shelf seas. Ocean models with horizontal resolutions of O(1km) can generate submesoscale current variability not captured by coarser regional models which resolve mesoscale flows approximately in geostrophic and thermal-wind balance. In practice, higher-resolution systems will provide analyses with enhanced spatial detail but may be less skillful at predicting the evolution of mesoscale eddies. This study aims at assessing the role of open boundary conditions, tidal forcing and tide filtering techniques in a coastal ocean model using a split-explicit time marching scheme with horizontal resolutions of O(1km) and its effect in coastal sea level dynamics and ocean currents. Numerical experiments have been performed using the Regional Ocean Modeling System (ROMS) with different uniform horizontal resolution: 3.6km, 1.2km and 740m. Initial and lateral boundary conditions are derived from the U.S. Naval Oceanographic Office (NAVOCEANO) operational AmSeas model forecast, a 3.6-km resolution application of the regional Navy Coastal Ocean Model (NCOM) that encompasses the Gulf of Mexico and Caribbean Sea. Meteorological conditions are interpolated from the Navy’s Coastal Ocean-Atmosphere Mesoscale Prediction System (COAMPS) model with the exception of surface stresses, which are computed from a 2-km application of the Weather Research and Forecasting (WRF) model used by National Center for Environmental Protection’s (NCEP) National Digital Forecast Database (NDFD). Tidal variability is imposed in two ways: 1) by specifying the time evolution of sea level at the open boundaries and 2) spectrally by specifying the harmonic phases and amplitudes from the TPXO global inverse tide solutions at the boundaries. Sub-tidal low frequency conditions are imposed by filtering high frequencies out of the regional NCOM solution. A spectral analysis of the sea surface height and barotropic velocity is performed via Fourier’s transform, showing significant differences at higher frequencies. Tide signals are then reconstructed and removed from the open boundary condition’s (OBC’s) in 2 ways: 1) using Rich Pawlowicz’s t_tide package (i.e., classic harmonic analysis) (Pawlowicz, 2002 [1]) and 2) with traditional low-pass filters. The spectral analysis provides a comprehensive characterization of the response in coastal sea level dynamics, which is difficult to elucidate in the time domain. Modeled results of sea surface height and ocean currents are validated with NOAA tide gauges and Acoustic Doppler Current Profilers. The tide filtering approach with the low-pass filter yields significant improvement of water levels in coastal areas, and similar performance in the modeled currents. The grid sensitivity analysis shows significant reduction of error when increasing the resolution from 3.6km to 1.2km, but no further improvement is found at higher resolution. Power spectra shows that further increasing the resolution yields better agreement for higher frequencies but no significant reduction in error.

The mean velocity structure and variability of the Kuroshio east of Taiwan, China, were investigated using mooring observations acquired at 23°N/122°E between January 2016 and May 2017. Power spectrum analysis reveals marked intraseasonal variability in 70–95 days in the meridional Kuroshio velocity in the upper 800 m. Hybrid Coordinate Ocean Model assimilation data adequately reproduce variations of the Kuroshio. Westward propagating mesoscale eddies that originated from the Subtropical Countercurrent play an important role in intraseasonal variability in the Kuroshio velocity. Cyclonic (anticyclonic) eddies are often associated with negative (positive) sea surface height anomaly, resulting in positive (negative) potential vorticity in the subsurface layer of the eddy center, which decreases (increases) isopycnal slope and then weakens (strengthens) the Kuroshio. When anticyclonic (cyclonic) eddies are active, the Kuroshio axis moves offshore (inshore). Corresponding to the Kuroshio intraseasonal variability (ISV), the variation of the intermediate water salinity also had a significant ISV induced by the mesoscale eddies.

This paper presents global comparisons of fundamental global climate variables from a suite of four pairs of matched low- and high-resolution ocean and sea ice simulations that are obtained following the OMIP-2 protocol (Griffies et al., 2016) and integrated for one cycle (1958–2018) of the JRA55-do atmospheric state and runoff dataset (Tsujino et al., 2018). Our goal is to assess the robustness of climate-relevant improvements in ocean simulations (mean and variability) associated with moving from coarse (∼ 1∘) to eddy-resolving (∼ 0.1∘) horizontal resolutions. The models are diverse in their numerics and parameterizations, but each low-resolution and high-resolution pair of models is matched so as to isolate, to the extent possible, the effects of horizontal resolution. A variety of observational datasets are used to assess the fidelity of simulated temperature and salinity, sea surface height, kinetic energy, heat and volume transports, and sea ice distribution. This paper provides a crucial benchmark for future studies comparing and improving different schemes in any of the models used in this study or similar ones. The biases in the low-resolution simulations are familiar, and their gross features – position, strength, and variability of western boundary currents, equatorial currents, and the Antarctic Circumpolar Current – are significantly improved in the high-resolution models. However, despite the fact that the high-resolution models “resolve” most of these features, the improvements in temperature and salinity are inconsistent among the different model families, and some regions show increased bias over their low-resolution counterparts. Greatly enhanced horizontal resolution does not deliver unambiguous bias improvement in all regions for all models.

The objective of this paper is to present a new approach for forecasting NAO index (NAOi) based on predictions of sea level anomalies (SLAs). We utilize significant correlations (Pearson’s r up to 0.69) between sea surface height (SSH) calculated for the North Atlantic (15–65°N, basin-wide) and winter Hurrell NAOi, as shown by Esselborn and Eden (Geophys Res Lett 28:3473–3476, 2001). We consider the seasonal and monthly data of Hurrell NAOi, ranging from 1993 to 2017. Weekly prognoses of SLA are provided by the Prognocean Plus system which uses several data-based models to predict sea level variation. Our experiment consists of three steps: (1) we calculate correlation between the first principal component (PC1) of SSH/SLA data and NAOi, (2) we determine coefficients of a linear regression model which describes the relationship between winter NAOi and PC1 of SLA data (1993–2013), (3) we build two regression models in order to predict winter NAOi (by attaching SLA forecasts and applying coefficients of the fitted regression models). The resulting 3-month prognoses of winter NAOi are found to reveal mean absolute errors of 1.5 or less. The choice of method for preparing SLA data for principal component analysis is shown to have a stronger impact on the prediction performance than the selection of SLA prediction method itself.

Tropical storms (TS) are highly sensitive to the behavior of nearby oceans, and the only way to improve their predictability is to include all the possible factors contributing to their genesis and motion. The present study evaluates the response of air–sea coupling on TS Mora, which occurred during the pre-monsoon season of 2017. Mora is simulated using a non-hydrostatic regional atmospheric modeling system coupled to a regional ocean modeling system model. The observations show a low-level Rossby wave in the atmosphere during the storm genesis. There was also evidence of increased sea surface height simultaneously in the form of a downwelling Kelvin wave at the west coast of the Bay of Bengal. The present study emphasizes the relationship between near-surface oceanic and atmospheric circulation patterns. We have tried to elucidate the process with the help of dynamical equations and model solutions. We also analyze the pivotal role of the atmospheric Rossby wave in the formation of the coastal Kelvin wave. The Kelvin wave seems to produce a warm pool required to form a low-pressure system, which further gave rise to the tropical storm Mora. The changes in the temperature and salinity profile within the ocean subsurface layers during storm passage are further used for inferences regarding the vertical structure of the upper ocean due to wind-generated mixing. The model analysis reveals that the ocean and atmospheric counterparts responsible for storm genesis are well recorded in the coupled model when compared to the observations. It was found that air–sea coupling in the model made it possible to realistically capture ocean and atmospheric responses.

Marine gravity anomalies are essential data for determining coastal geoid, investigating tectonics and crustal structures, and offshore explorations. The objective of this study is to present a methodology for estimating marine gravity anomalies from CryoSat-2 and Saral/AltiKa satellite altimeter data for the Gulf of Tonkin of Vietnam with a high-resolution 2′ × 2′ grid. A total of 15,665 sea surface height (SSH) grid points, including derived from the Cryosat-2 (6842 grid points) and Saral/AltiKa (8823 grid points) satellite altimeter data were used. Then, the remove-restore technique and the crossover adjustment algorithm were used to remove the long-wavelength geoid height, the mean dynamic topography , and time-varying sea-surface topography . The residual geoid heights were used to determine the residual gravity anomalies using the Least-Squares Collocation method, whereas the Earth Geopotential Model was employed to restore the long-wavelength gravity anomalies . GPS/leveling and tidal gauge of 31 tidal stations were used for assessing and choosing the best Earth Geopotential Model and Mean Dynamic Topography models for the study area (EIGEN6C4 and DTU15MDT models). The accuracy of the final marine gravity anomaly result was assessed using 56,978 marine gravity points, which were distributed in the study area. The result showed that the standard deviation between the satellite-derived gravity anomalies and checked points is ± 3.36 mGal, indicating good accuracy. After improving with ship-measured gravity anomalies, the accuracy of satellite-derived marine gravity anomaly improves to ± 2.63 mGal. The results of this research are useful for geodetic and geophysical applications in the region. 2020 COSPAR. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/ by-nc-nd/4.0/)

A time series analysis of the sea surface height anomaly (SSHa) was conducted in the Kuril Basin of the Sea of Okhotsk. The mapping of the satellite-derived SSHa data was optimized to mitigate the effects of sea ice on the SSHa field during winter and early spring. Complex empirical orthogonal functions (CEOFs) were then used to analyze the SSHa field, revealing that the first three modes account for 55% of the signal variance. Mode 1 mainly represents the coherent variability trapped over the shelves all along the coastal regions and the Kuril Islands. Both seasonal and interannual variations are strongly correlated with the alongshore wind stress and can be well explained by an arrested topographic wave. Mode 3 is a propagating mode that exhibits trains of southwestward-propagating, high-amplitude anomalies. One possible mechanism for this is first-mode baroclinic Rossby waves, whose energy propagates from the Kuril Straits toward the Kuril Basin. However, mode 3 can be better interpreted as barotropic Rossby normal modes generated in the deep Kuril Basin. Mode 2 is a standing mode that may encompass the baroclinic variability in the basin. The monthly mean of the SSHa in the Kuril Basin is primarily governed by variability in mode 1, with mode 2 contributing to a lesser extent, and mode 3 being insignificant.

The air-sea interaction processes and their relation to Indian summer monsoon rainfall via dynamic and thermodynamic components are vital. The present study examined the two contrasting monsoon years 2016 (normal) and 2017 (below normal) and highlighted the significance of air-sea interaction in the understanding the rainfall over central India. We investigate the difference in the sea surface height anomaly and propagation of oceanic Kelvin and Rossby wave over the tropical Indian Ocean and other atmospheric parameters during the contrasting monsoon years. The study gives information on how equatorial and coastal Kelvin/Rossby waves cause upwelling/downwelling and modulate convection and influence rainfall during 2016 and 2017. The high (low) sea surface height anomaly, sea surface temperature, and upper ocean heat content during 2016 (2017) lead to enhanced (subdued) convection in the Bay of Bengal and thereby contributing more rainfall to central India. During 2016 (2017), high (low) tropospheric temperature draws more (less) moisture through mid-tropospheric heat flux, and net convergence (divergence) is dominated over the central India that results in enhanced (diminish) convection. Also, the velocity potential determines the strengthening (weakening) of Walker circulation through associated atmospheric circulation and upper-level divergence (convergence) that become favorable for rainfall in the year 2016 (2017). This study will help in understanding the variations in the air-sea interaction processes over the tropical Indian Ocean and the Indian subcontinent, the results of which may improve the predictability of the rainfall.

Recent marine heatwave (MHW) events in the Tasman Sea have had dramatic impacts on the ecosystems, fisheries, and aquaculture off Tasmania’s east coast. However, our understanding of the large-scale drivers (forcing) and potential predictability of MHW events in this region off southeast Australia is still in its infancy. Here, we investigate the role of oceanic Rossby waves forced in the interior South Pacific on observed MHW occurrences off southeast Australia from 1994 to 2016, including the extreme 2015/16 MHW event. First, we used an upper-ocean heat budget analysis to show that 51% of these historical Tasman Sea MHWs were primarily due to increased East Australian Current (EAC) Extension poleward transports through the region. Second, we used lagged correlation analysis to empirically connect the EAC Extension intensification to incoming westward-propagating sea surface height (SSH) anomalies from the interior South Pacific. Third, we dynamically analyzed these SSH anomalies using simple process-based baroclinic and barotropic Rossby wave models forced by wind stress curl changes across the South Pacific. Finally, we show that associated monthly SSH changes around New Zealand may be a useful index of western Tasman Sea MHW predictability, with a lead time of 2–3 years. In conclusion, our findings demonstrate that there is potential predictability of advection-dominated MHW event likelihoods in the EAC Extension region up to several years in advance, due to the deterministic contribution from baroclinic and barotropic Rossby waves in modulating the EAC Extension transports.

We present preliminary calibration results for Jason-3 and Sentinel-3A altimeters that we set up in the Wanshan Islands in Guandong Province, China. Two campaigns were carried out in 2018, from March 8 to April 16 and from November 3 to December 11, 2018. Three GPS reference stations and tide gauges were established on the islands of Zhiwan, Dangan, and Wailingding during the campaigns. The in-situ sea surface height (SSH) of the altimeter footprint was determined using the tide gauge. The tidal and geoid connection between the tide gauge locations and the altimeter footprints were computed with the NAO.99Jb tidal prediction system and the EGM 2008 geoid, respectively. The data of the tide gauges were defined using the GPS buoy and GPS reference stations during the campaigns. The results show that the waveform of the altimeters was slightly contaminated by the small islands. The bias associated with Jason-3 and Sentinel-3A amounted to approximately +20.7±49.7 mm and +30.1±39.4 mm, respectively, which agreed well with the results from other in-situ calibration fields. This indicates that the Wanshan area was very suitable as an in-situ calibration/validation field. The wet zenith delay (WZD) determined from the Microwave Radiometer (MWR) and the GPS measurements differed from each other for the Jason-3 and Sentinel-3A by -6.6±7.4 mm and 0±6.8 mm, respectively.

The Arctic Ocean and subarctic seas have been undergoing significant changes, particularly evident throughout the past few decades. In this paper, we examine the declining sea ice extent in the Arctic (− 0.0639 million km2 year−1), the increasing sea surface temperature (approximately 0.014 °C year−1 in the Arctic Ocean to 0.03 °C year−1 in the subarctic Atlantic) and sea surface height (2.2 mm year−1 in the Arctic Ocean to 2.4 mm year−1 in the subarctic Atlantic), and changing patterns of sea surface salinity using a variety of reanalysis and observational data products from 1990 to 2017. The Amerasian Basin, particularly the Beaufort Gyre, has been freshening, concurrent with a salinification of the Laptev, Barents, and Greenland Seas, all of which are due to a shift towards a more anticyclonic circulation regime, shift in freshwater storage, and ice melt. Even as this regime began to weaken in the past decade, the freshening in the Beaufort Gyre continued. When comparing these variables to climate indices, we found an important connection between the Arctic Ocean Oscillation (AOO), sea surface height, sea surface temperatures, and ocean heat content in the subarctic Atlantic region, indicating more widespread impacts of atmospheric circulation changes in the Arctic region. These connections show that changes in the cyclonicity of the Arctic Ocean can impact output to the subarctic Atlantic region, which affects the heat and sea level of the region.

This study compares the seasonal and interannual-to-decadal variability in the strength and position of the Kuroshio Extension front (KEF) using high-resolution satellite-derived sea surface temperature (SST) and sea surface height (SSH) data. Results show that the KEF strength has an obvious seasonal variation that is similar at different longitudes, with a stronger (weaker) KEF during the cold (warm) season. However, the seasonal variation in the KEF position is relatively weak and varies with longitude. In contrast, the low-frequency variation of the KEF position is more distinct than that of the KEF strength even though they are well correlated. On both seasonal and interannual-to-decadal time scales, the western part of the KEF (142°–144°E) has the greatest variability in strength, while the eastern part of the KEF (149°–155°E) has the greatest variability in position. In addition, the relationships between wind-forced Rossby waves and the low-frequency variability in the KEF strength and position are also discussed by using the statistical analysis methods and a wind-driven hindcast model. A positive (negative) North Pacific Oscillation (NPO)-like atmospheric forcing generates positive (negative) SSH anomalies over the central North Pacific. These oceanic signals then propagate westward as Rossby waves, reaching the KE region about three years later, favoring a strengthened (weakened) and northward (southward)-moving KEF.

Wanshan area has been chosen to be the specified field to calibrate and validate (Cal/Val) the HY-2 altimeter and its follow-on satellites. In March 2018, an experiment has been conducted to determine the sea surface height (SSH) under the HY-2A ground track (Pass No. 203). A GPS towing-body (GPS-TB) was designed to measure the SSH covering an area of about 6 km×28 km wide centered on the HY-2A altimeter satellite ground track. Three GPS reference stations, one tide gauge and a GPS buoy were placed in the research area, in order to process and resolve the kinematic solution and check the precision of the GPS-TB respectively. All the GPS data were calculated by the GAMIT/GLOBK software and TRACK module. The sea surface was determined by the GPS-TB solution and the tide gauge placed on Zhiwan Island. Then the sea surface of this area was interpolated by ArcGIS 10.2 with ordinary Kriging method. The results showed that the precision of the GPS-TB is about 1.10 cm compared with the tide gauge placed nearby, which has an equivalent precision with the GPS buoy. The interpolated sea surface has a bias of −1.5–4.0 cm with standard deviation of 0.2–2.4 cm compared with the checking line. The gradient of the measured sea surface is about 1.62 cm/km along the HY-2 orbit which shows a good agreement compared with the CLS11 mean sea surface (MSS). In the Cal/Val of satellites, the sea surface between the tide gauge/GPS buoy and the footprint of altimeter can be improved by this work.

Previous work has demonstrated the strong ocean response to atmospheric rivers (ARs) in the northeast Pacific including coastal currents along the west coast of North America, because of strong surface winds associated with ARs. A recent study on the global distribution of ARs also suggests that the southeast Indian Ocean is one of the areas of relatively strong AR activity. This study investigates the influence of ARs on the Leeuwin Current system, which is one of the major boundary currents in the Indian Ocean. It is demonstrated that winds associated with typical ARs in the southeast Indian Ocean can generate strong poleward coastal currents and sea level rise along the west coast of Australia using a high-resolution ocean reanalysis (0.08° HYCOM). The composite of upper ocean currents and sea surface height (SSH) associated with landfalling ARs along the west coast of Australia is constructed using the HYCOM reanalysis, long-term AR data set, and tide gauge data. The enhancement of the poleward currents generated by ARs is found in the composite, and the magnitude of the enhancement is comparable to the strength of the Leeuwin Current itself. The results also indicate that the fluctuation of SSH and coastal currents along the west coast propagates along the southern coast all the way to the southeast coast (Pacific side) of Australia. The SSH propagation along the coasts is also detected in the tide gauge data in the west and southern coasts of Australia.

Satellite altimetry data has been a backbone of global oceanography research since the early 1990s. Because a satellite altimeter measures sea surface height (SSH) at the nadir point, it produces a one-dimensional profile of SSH. Along the track, an altimeter provides SSH sampling at an interval of about 7 km. However, the distance between adjacent tracks is larger than 100 km, and satellites have repeat times of 10–30 d. These characteristics limit the usefulness of altimetry data from a single satellite for scientific analysis of the space-time structure of ocean circulation. During the past two decades, there have usually been three to four altimeters in orbit at any one time. Mapping along-track measurements from multiple altimeters onto a uniform grid has been a major research theme. A popular merged data product, known as AVISO, has been developed and extensively applied to a wide variety of ocean research. One of key properties of a merged data product is its effective resolution. The effective resolution represents the minimum spatial size of an eddy or other mesoscale circulation that the data product can resolve. The AVISO data product has an effective resolution of 300 km in equatorial regions to 100 km in high latitudes. Nowadays, there are more than five satellite altimeters in orbit, including the Chinese HY-2A that was launched in 2011, and thus the density of the tracks has been much improved. However, the effective resolution of the AVISO data product has not increased accordingly. Effective resolution of mapped data is closely related to the background error correlation coefficient scale in the mapping scheme. The effective resolution is no more than twice the correlation coefficient scale even when the amount of satellite altimeter is more than 5. As the background fields contains the correct large scale information, the meso-scale or small-scale information in the background error will play a dominant role and the background error correlation coefficient scale becomes even smaller. Therefore, The option of background determines the effective resolution of mapped data. The above theory is the basement of our new proposed mapping scheme, which effectively improved the effective resolution. Another key technique is how to deal with the observation errors: to reduce time-smoothing by introducing evolution errors in observation errors and effectively mapping multi-mission satellite altimeters from different times. In this study, a new mapping system has been developed, aiming to maximize the effective resolution of the mapped data product. The formulation is based on a variational method and optimal estimation theory. The system has been applied to the South China Sea region. The product uses a regular grid with spacing of 0.08°, in comparison to 0.25° for AVISO. The product merged data from five satellites, Sentinel-3A, Jason-3, Cryosat-2, Saral/AltiKa and HY-2A. Systematic evaluations show that this new product has an effective resolution of 125 km, whereas the AVISO data product an effective resolution of 240 km for the same region. The accuracy is also significantly improved. The new proposed mapping scheme is important in the application of satellite altimeters on the study of meso-scale ocean eddies. In addition, the option of background fields and the processing method of observation error are strictly general and can be used in other schemes of high-resolution data mapping.

Flow of barotropic tidal currents over topographic features, such as continental slopes and submarine ridges, generates internal gravity waves at tidal periods known as internal tides. Amplitude of these waves are generally large near the generation regions. Analysis of Sea Surface Height (SSH) data, derived from satellite altimeter revealed the amplification of internal tides in the semidiurnal period in the north-central Bay of Bengal (BoB) (around 89$${}^{\circ }$$∘E, 16$${}^{\circ }$$∘N), which is about 450 km away from their generation sites. SSH signals found in the north-central BoB ($$ \sim $$~3 cm) were comparable to the maximum amplitudes (2.5 to 3.5 cm) observed near their potential generation sites in the BoB such as continental slopes in the head of the bay and Andaman-Nicobar (AN) Ridge. Simulations from a high-resolution regional ocean model also confirmed the presence of large internal tide amplitude in the north-central BoB. Our study revealed that convergence of internal tides, which were generated along the concave-shaped source (continental slopes in the head of the bay and the northern parts of AN Ridge), into its focal region caused their amplification in the north-central BoB. It was also found that internal tide energy dissipation rates in this focal region were about 10 times larger than those in other open ocean regions.

This study observed the decadal variability of the sea surface height anomaly (SSHA) and identified the decadal Kelvin wave propagation along west-Sumatra and south coast of Java. SSHA data and the vertical distribution of sea temperature for 64 years from HYCOM model resulted has already used in this research. There are several methods to identify the propagation of decadal Kelvin wave. These methods were low-pass filter by cut-off 1 and 8 years, visual analytic by using Hovmӧller diagram method, and frequency-wavenumber 2D spectral analysis to identify the Kelvin wave propagation and its period. The decadal Kelvin wave could be observed in west coast of Sumatra and along south coast of Java. There are three propagations of decadal Kelvin wave and their velocities were 1.029x10-3 m/s (1974 – 1976), 0.21 m/s (1985 – 1986), and 6.86x10-4 m/s for 1998 to 2001 trough west Sumatra and southern Java. The frequency-wavenumber 2D spectral analysis produced the improvement of Kelvin wave and it has the period of 7.25 years. The occurrence of the Kelvin wave has a relation to IOD index. The average of the IOD index when the decadal Kelvin wave was occurring must be the negative value, its value was a -0.21.

The ocean and land color instrument (OLCI) and synthetic aperture radar altimeter (SRAL) installed aboard the Sentinel-3 satellite have been in orbit for operational uses. In this study, data collected from Sentinel-3 are used to investigate internal waves in the South China Sea. An internal wave is detected using an OLCI image with a resolution of 300 m, and an analysis was performed with a quasi-synchronous moderate-resolution imaging spectroradiometer (MODIS) image. The opposite characteristics of OLCI and MODIS images of the same internal wave are explained by the critical angle in brightness reversals. The unique observational geometry of the OLCI image and its influence on observations of internal waves are discussed. The distribution of σ0 and sea surface height anomalies (SSHAs) induced by internal waves are studied using SRAL records. The σ0 records of SRAL occasionally show less sensitivity to the modulation of internal waves, which may be attributed to the observational geometry, while SSHAs show obvious variations. The synchronous pairing of OLCI images and SRAL records are analyzed to extract the three-dimensional sea surface signatures induced by internal waves. The analysis demonstrates that the profile of SSHAs in the surface shows an opposite phase to the profiles of internal waves in the ocean. The opposite phase relationship, observed in the remote sensing view, is also confirmed with a laboratory experiment.

AIM: Species distribution modelling is a useful tool for determining important habitats. By accounting for specific animal behaviour in the model, it is possible to identify finer‐scale patterns of habitat use. Together with spatially explicit data on anthropogenic activities, models can be used to assess human impacts and inform conservation management. This study used observations of breeding behaviour to identify fine‐scale breeding habitats of humpback whales (Megaptera novaeangliae), as well as potential overlap of these habitats with cumulative anthropogenic impacts. LOCATION: Eastern Tropical Atlantic, West Africa. METHODS: Maxent was used to model humpback distribution using pertinent environmental predictors and an integrated dataset of humpback whale occurrences filtered for breeding‐specific behaviours. In conjunction with multiple anthropogenic activities, a subsequent cumulative utilization and impact analysis assessed the degree of overlap between predicted breeding habitat and potential anthropogenic impacts. RESULTS: Greatest habitat suitability occurred in warm coastal waters of Gabon, and other highly suitable areas occurred off Equatorial Guinea (Bioko Island), Cameroon and Angola. Sea surface temperature and height contributed most to the model. Highest overlap between humpback whales and potential impacts from anthropogenic activities occurred off Gabon, Equatorial Guinea (Bioko Island), Cameroon and Angola. Impacts associated with oil and gas development (where oil and gas platforms serve as an indicator for industry activity) appeared to contribute most to potential cumulative impact. MAIN CONCLUSIONS: Depth and sea surface temperature of predicted breeding habitats were consistent with previous studies. However, lesser known characteristics such as sea surface height and wind speed, resulting in potentially more sheltered areas for breeding whales, may also be important in delineating finer‐scale habitat suitability. Identified areas of high potential cumulative impact occurred within exclusive economic zones of multiple countries and likely represent the minimum level of impact to humpback whales in the region, highlighting the need for additional research and effective management throughout the area.

Satellite altimeters routinely supply sea surface height (SSH) measurements, which are key observations for monitoring ocean dynamics. However, below a wavelength of about 70 km, along-track altimeter measurements are often characterized by a dramatic drop in signal-to-noise ratio (SNR), making it very challenging to fully exploit the available altimeter observations to precisely analyze small mesoscale variations in SSH. Although various approaches have been proposed and applied to identify and filter noise from measurements, no distinct methodology has emerged for systematic application in operational products. To best address this unresolved issue, the Copernicus Marine Environment Monitoring Service (CMEMS) actually provides simple band-pass filtered data to mitigate noise contamination of along-track SSH signals. More innovative and suitable noise filtering methods are thus left to users seeking to unveil small-scale altimeter signals. As demonstrated here, a fully data-driven approach is developed and applied successfully to provide robust estimates of noise-free sea level anomaly (SLA) signals (Quilfen, 2021). The method combines empirical mode decomposition (EMD), used to help analyze non-stationary and non-linear processes, and an adaptive noise filtering technique inspired by discrete wavelet transform (DWT) decompositions. It is found to best resolve the distribution of SLA variability in the 30–120 km mesoscale wavelength band. A practical uncertainty variable is attached to the denoised SLA estimates that accounts for errors related to the local SNR but also for uncertainties in the denoising process, which assumes that the SLA variability results in part from a stochastic process. For the available period, measurements from the Jason-3, Sentinel-3, and SARAL/AltiKa missions are processed and analyzed, and their energy spectral and seasonal distributions are characterized in the small mesoscale domain. In anticipation of the upcoming SWOT (Surface Water and Ocean Topography) mission data, the SASSA (Satellite Altimeter Short-scale Signals Analysis, https://doi.org/10.12770/1126742b-a5da-4fe2-b687-e64d585e138c, Quilfen and Piolle, 2021) data set of denoised SLA measurements for three reference altimeter missions has already been shown to yield valuable opportunities to evaluate global small mesoscale kinetic energy distributions.

The purpleback flying squid (Ommastrephidae: Sthenoteuthis oualaniensis) is an important species at higher trophic levels of the regional marine ecosystem in the South China Sea (SCS), where it is considered to show the potential for fishery development. Accordingly, under increasing climatic and environmental changes, understanding the nature and importance of various factors that determine the spatial and temporal distribution and abundance of S. oualaniensis in the SCS is of great scientific and socio-economic interest. Using generalized additive model (GAM) methods, we analyzed the relationship between available environmental factors and catch per unit effort (CPUE) data of S. oualaniensis. The body size of S. oualaniensis in the SCS was relatively small (&lt, 19.4 cm), with a shorter lifespan than individuals in other seas. The biological characteristics indicate that S. oualaniensis in the SCS showed a positive allometric growth, and could be suitably described by the logistic growth equation. In our study, the sea areas with higher CPUE were mainly distributed at 10&deg, &ndash, 11&deg, N, with a 27&ndash, 28 &deg, C sea surface temperature (SST) range, a sea surface height anomaly (SSHA) of &minus, 0.05&ndash, 0.05 m, and chlorophyll-a concentration (Chl-a) higher than 0.18 &mu, g/L. The SST was the most important factor in the GAM analysis and the best fitting GAM model explained 67.9% of the variance. Understanding the biological characteristics and habitat status of S. oualaniensis in the SCS will benefit the management of this resource.

We present a simple smoother designed for smooth data adjustments in sequentially generated reanalysis products by utilizing knowledge of future assimilation increments. A decay time parameter is applied to the smoother increments to account for memory decay timescales in the ocean. The result is different from simply time smoothing the reanalysis itself as only the increments are smoothed so the reanalysis product can retain high frequency variability that is being internally generated by the model and the atmospheric forcing. The smoother is applied first to the Lorenz 1963 model and then to the daily Met Office GloSea5 Global ¼° ocean reanalysis during 2016. Results show significant improvement over the original reanalysis in the 3D temperature and salinity state and variability, as well as in the sea surface height (SSH). Comparisons are made directly against temperature, salinity and SSH observations, as well as independent 15m drifter velocities. The impact on the time variability of conservative quantities, particularly ocean heat and salt content, as well as Kinetic energy and the Atlantic overturning, is also demonstrated.

A growing number of studies are concluding that the resilience of the Arctic sea ice cover in a warming climate is essentially controlled by its thickness. Satellite radar and laser altimeters have allowed us to routinely monitor sea ice thickness across most of the Arctic Ocean for several decades. However, a key uncertainty remaining in the sea ice thickness retrieval is the error on the sea surface height (SSH) which is conventionally interpolated at ice floes from a limited number of lead observations along the altimeter's orbital track. Here, we use an objective mapping approach to determine sea surface height from all proximal lead samples located on the orbital track and from adjacent tracks within a neighborhood of 30–220 (mean 105) km. The patterns of the SSH signal's zonal, meridional, and temporal decorrelation length scales are obtained by analyzing the covariance of historic CryoSat-2 Arctic lead observations, which match the scales obtained from an equivalent analysis of high-resolution sea ice-ocean model fields. We use these length scales to determine an optimal SSH and error estimate for each sea ice floe location. By exploiting leads from adjacent tracks, we can increase the sea ice radar freeboard precision estimated at orbital crossovers by up to 20%. In regions of high SSH uncertainty, biases in CryoSat-2 radar freeboard can be reduced by 25% with respect to coincident airborne validation data. The new method is not restricted to a particular sensor or mode, so it can be generalized to all present and historic polar altimetry missions.

Oceanic mesoscale eddies are associated with large thermodynamic anomalies, yet so far they are most commonly studied in terms of surface temperature and in the sense of composite mean. Here we employ an objective eddy identification and tracking algorithm together with a novel matching and filling procedure to more thoroughly examine eddy-induced thermodynamic anomalies in the North Pacific, their relationship with eddy amplitude (SSH), and the percentage of variability they explain on various timescales from submonthly to interannual. The thermodynamic anomalies are investigated in terms of sea surface temperature (SST), isothermal layer depth (ITD), and upper ocean heat content (HCT). Most eddies are weak in amplitude and are associated with small thermodynamic anomalies. In the sense of composite mean, anticyclonic eddies are generally warm eddies with deeper isothermal layer and larger heat content, and the reverse is true for cyclonic eddies. A small fraction of eddies, most probably subsurface eddies, exhibits the opposite polarities. Linear relationships with eddy amplitude are found for each of the thermodynamic parameters but with different level of scatter and seasonality. HCT-amplitude relation scatters the least and has the smallest seasonal difference, ITD-amplitude relation has the largest scatter and seasonality, while SST-amplitude relation is in between. For the Kuroshio and Oyashio Extension region, the most eddy-rich region in the North Pacific, eddies are responsible for over 50% of the total SSH variability up to the intra-seasonal scale, and ITD and HCT variability up to interannual. Eddy-induced SST variability is the highest along the Oyashio Extension Front on the order of 40–60% on submonthly scales. These results highlight the role of mesoscale eddies in ocean thermodynamic variability and in air-sea interaction.

Sea surface height (SSH), a measurement widely used in marine science, can be used to compute the marine gravity field while providing underlying information on the ocean current, tide, and...

75 pages, 8 figures, 3 tables, 6 appendixes, supplement https://doi.org/10.5194/esd-12-1295-2021-supplement.-- Code and data availability: The python code that was used for the analysis and to create the plots is available at https://renkulab.io/gitlab/ACE-ASAID/spca-decomposition (last access: 29 March 2021; Volpi, 2021) and as a Renku project https://renkulab.io/projects/ACE-ASAID/spca-decomposition (last access: 29 March 2021; Volpi and Landwehr, 2021). For the availability of the data used in this study please refer to Tables B1 to B8 in Appendix B, The Southern Ocean is a critical component of Earth's climate system, but its remoteness makes it challenging to develop a holistic understanding of its processes from the small scale to the large scale. As a result, our knowledge of this vast region remains largely incomplete. The Antarctic Circumnavigation Expedition (ACE, austral summer 2016/2017) surveyed a large number of variables describing the state of the ocean and the atmosphere, the freshwater cycle, atmospheric chemistry, and ocean biogeochemistry and microbiology. This circumpolar cruise included visits to 12 remote islands, the marginal ice zone, and the Antarctic coast. Here, we use 111 of the observed variables to study the latitudinal gradients, seasonality, shorter-term variations, geographic setting of environmental processes, and interactions between them over the duration of 90 d. To reduce the dimensionality and complexity of the dataset and make the relations between variables interpretable we applied an unsupervised machine learning method, the sparse principal component analysis (sPCA), which describes environmental processes through 14 latent variables. To derive a robust statistical perspective on these processes and to estimate the uncertainty in the sPCA decomposition, we have developed a bootstrap approach. Our results provide a proof of concept that sPCA with uncertainty analysis is able to identify temporal patterns from diurnal to seasonal cycles, as well as geographical gradients and “hotspots” of interaction between environmental compartments. While confirming many well known processes, our analysis provides novel insights into the Southern Ocean water cycle (freshwater fluxes), trace gases (interplay between seasonality, sources, and sinks), and microbial communities (nutrient limitation and island mass effects at the largest scale ever reported). More specifically, we identify the important role of the oceanic circulations, frontal zones, and islands in shaping the nutrient availability that controls biological community composition and productivity; the fact that sea ice controls sea water salinity, dampens the wave field, and is associated with increased phytoplankton growth and net community productivity possibly due to iron fertilisation and reduced light limitation; and the clear regional patterns of aerosol characteristics that have emerged, stressing the role of the sea state, atmospheric chemical processing, and source processes near hotspots for the availability of cloud condensation nuclei and hence cloud formation. A set of key variables and their combinations, such as the difference between the air and sea surface temperature, atmospheric pressure, sea surface height, geostrophic currents, upper-ocean layer light intensity, surface wind speed and relative humidity played an important role in our analysis, highlighting the necessity for Earth system models to represent them adequately. In conclusion, our study highlights the use of sPCA to identify key ocean–atmosphere interactions across physical, chemical, and biological processes and their associated spatio-temporal scales. It thereby fills an important gap between simple correlation analyses and complex Earth system models. The sPCA processing code is available as open-access from the following link: https://renkulab.io/gitlab/ACE-ASAID/spca-decomposition (last access: 29 March 2021). As we show here, it can be used for an exploration of environmental data that is less prone to cognitive biases (and confirmation biases in particular) compared to traditional regression analysis that might be affected by the underlying research question, Rafel Simó, Marina Zamanillo, Pau Cortés-Greus, and Pablo Rodríguez-Ros were supported by the Spanish Ministry of Science through the BIOGAPS project (CTM2016-81008-R), With the institutional support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S)

Little is known about the ecological importance of fin whales found year-round in southwestern offshore Irish waters. Understanding their ecology is important to reduce potential harm through any spatio-temporal overlap with commercial shipping and fishing activities. This study explored the potential environmental drivers and impacts of low-frequency shipping noise on fin whale calling at Porcupine Ridge using the presence/absence of call detections as a proxy for observed changes due to possible masking. Acoustic call data was collected at a low sampling rate (2 ksps) from the end of March 2016 to June 2016 (97 days) using a bottom-moored autonomous acoustic recorder with an omni-directional hydrophone. The high zero-inflated and binary nature of the data was addressed using generalised linear models. The results of our habitat modelling predicted call detections to increase significantly during night-time (p ≤ 0.01) with sea surface height and chlorophyll-a concentration (p ≤ 0.01), implying higher prey availability may occur on Porcupine Ridge. It also indicated a significant decrease in call detections with increasing shipping noise (p ≤ 0.01). Unfortunately, the model had a type II error. To provide robust results, a longer study not limited by data on the prey, and oceanographic drivers including spatial and temporal parameters is required. This study provides the foundations on which further ecological data could be added to establish management and mitigation measures to minimize the effects of shipping noise on fin whales.

Improving the altimetric precision under the requirement of ensuring the along-track resolution is of great significance to the application of iGNSS-R satellite ocean altimetry. The results obtained by using the empirical integration time need to be improved. Optimizing the integration time can suppress the noise interference from different sources to the greatest extent, thereby improving the altimetric precision. The inverse relationship between along-track resolution and signal integration time leads to the latter not being infinite. To obtain the optimal combination of integral parameters, this study first constructs an analytical model whose precision varies with coherent integration time. Second, the model is verified using airborne experimental data. The result shows that the average deviation between the model and the measured precision is about 0.16 m. The two are consistent. Third, we apply the model to obtain the optimal coherent integration time of the airborne experimental scenario. Compared with the empirical coherent integration parameters, the measured precision is improved by about 0.1 m. Fourth, the verified model is extrapolated to different spaceborne scenarios. Then, the optimal coherent integration time and the improvement of measured precision under various conditions are estimated. It was found that the optimal coherent integration time of the spaceborne scene is shorter than that of the airborne scene. Depending on the orbital altitude and the roughness of the sea surface, its value may also vary. Moreover, the model can significantly improve the precision for low signal-to-noise ratios. The coherent integration time optimization model proposed in this paper can enhance the altimetric precision. It would provide theoretical support for the signal optimization processing and sea surface height retrieval of iGNSS-R altimetry satellites with high precision and high along-track resolution in the future.

In this paper we studied the impact of winds on Arctic sea ice through the ocean's memory by using numerical simulations. We found that the changes in halosteric height induced by wind perturbations can significantly affect the Arctic sea ice drift, thickness, concentration and deformation rates regionally even years after the wind perturbations. Changes in the Arctic liquid freshwater content and thus in halosteric height can cause changes in the sea surface height and surface geostrophic currents, which further enforce a lasting and strong impact on sea ice. The changes in both sea surface height gradient force (due to changes in sea surface height) and ice–ocean stress (due to changes in surface geostrophic currents) are found to be important in determining the overall ocean effects. The revealed ocean effects are mainly associated with changes in sea ice dynamics, not thermodynamics. Depending on the preceding atmospheric mode driving the ocean, the ocean's memory of the wind forcing can lead to changes in Arctic sea ice characteristics with very different spatial patterns. We obtained these spatial patterns associated with Arctic Oscillation, Arctic Dipole Anomaly and Beaufort High modes through dedicated numerical simulations. The dynamical impact of the ocean has strong seasonal variations, stronger in summer and weaker in winter and spring. This implies that declining trends of Arctic sea ice will very possibly allow a stronger ocean impact on the sea ice in a warming climate.

The Mediterranean is considered a hot-spot for plastic pollution, due to its semi-enclosed nature and heavily populated coastal areas. In the present study, a basin-scale coupled hydrodynamic/particle drift model was used to track the pathways and fate of plastics from major land-based sources (coastal cities and rivers), taking into account of the most important processes (advection, stokes drift, vertical and horizontal mixing, sinking, wind drag, and beaching). A hybrid ensemble Kalman filter algorithm was implemented to correct the near- surface circulation, assimilating satellite data (sea surface height, temperature) in the hydrodynamic model. Different size classes and/or types of both micro- and macroplastics were considered in the model. Biofouling induced sinking was explicitly described, as a possible mechanism of microplastics removal from the surface. A simplified parameterization of size-dependent biofilm growth has been adopted, as a function of bacterial biomass (obtained from a biogeochemical model simulation), being considered a proxy for the biofouling community. The simulated distributions for micro- and macroplastics were validated against available observations, showing reasonable agreement, both in terms of magnitude and horizontal variability. An 8-year simulation was used to identify micro- and macroplastics accumulation patterns in the surface layer, water column, seafloor and beaches. The impact of different processes (vertical mixing, biofouling, and wind/wave drift) was identified through a series of sensitivity experiments. For both micro- and macroplastics, distributions at sea surface were closely related to the adopted sources. The microplastics concentration was drastically reduced away from source areas, due to biofouling induced sinking, with their size distribution dominated by larger (>1 mm) size classes in open sea areas, in agreement with observations. High concentration patches of floating plastics were simulated in convergence areas, characterized by anticyclonic circulation. The distribution of macroplastics on beaches followed the predominant southeastward wind/wave direction. In the water column, a sub-surface maximum in microplastics abundance was simulated, with increasing contribution of smaller particles in deeper layers. Accumulation of microplastics on the seafloor was limited in relatively shallow areas (

Recent evidence shows that the variability of meridional overturning circulation (MOC) in the Indian and Pacific Oceans (PMOC) is characterized by a prominent deep cross-equatorial cell (CEC) spanning the tropics between 20S and 20N, but the mechanism responsible for this CEC is not understood. Using version 4.2 of the Estimating the Circulation and Climate of the Ocean (ECCO) state estimate, our investigation shows the mechanism responsible for CEC can be conceptualized by following mechanistic chain: 1) Anomalous winds produce equatorially antisymmetric anomalies of zonal mean sea surface temperature (SST) in the Pacific Ocean, 2) These temperature anomalies generate equatorially antisymmetric anomalies of sea surface height (SSH), 3) The SSH anomalies generate a cross-equatorial flow in the upper Pacific Ocean, and 4) This anomalous cross-equatorial flow in the upper layers drives compensating circulation in the deep Pacific.

International audience; The future wide-swath satellite altimeters, such as the upcoming Surface Water Ocean Topography (SWOT) mission, will provide instantaneous 2D measurements of sea level down to the spatial scale of O(10 km) for the first time. However, the validity of the geostrophic assumption for estimating surface currents from these instantaneous maps is not known a priori. In this study, we quantify the accuracy of geostrophy for the estimation of surface currents from a knowledge of instantaneous sea level using the hourly snapshots from a tide- and eddy-resolving global numerical simulation. Geostrophic balance is found to be the leading-order balance in frontal regions characterized by large kinetic energy, such as the western boundary currents and the Antarctic Circumpolar Current. Everywhere else, geostrophic approximation ceases to be a useful predictor of ocean velocity, which may result in significant high-frequency contamination of geostrophically computed velocities by fast variability (e.g., inertial and higher). As expected, the validity of geostrophy is shown to improve at low frequencies (typically urn:x-wiley:21699275:media:jgrc24720:jgrc24720-math-0001 0.5 cpd). Global estimates of the horizontal momentum budget reveal that the tropical and mid-latitude regions where geostrophic balance fails are dominated by fast variability and turbulent stress divergence terms rather than higher-order geostrophic terms. These findings indicate that the estimation of velocity from geostrophy applied on SWOT instantaneous sea level maps may be challenging away from energetic areas.

Bigeyes (Priacanthus spp.; Family: Priacanthidae) are among the most significant demersal fishes in northern South China Sea (nSCS). Based on the bottom trawl data of nSCS from 2009 to 2014, this study applied the SARIMA (Seasonal Autoregressive Integrated Moving Average) model and the centre of gravity movement to analyse the spatio-temporal patterns of catch per unit effort (CPUE). Combining with the corresponding environmental factors of each trawling cruise, including bottom water temperature (BWT), bottom water salinity (BWS) and sea surface height (SSH) and their relationships with the CPUE were analysed by generalised linear model (GLM). The results indicated that, the monthly CPUE varied in half a year as a period and the peak in the first half year was obviously lower than the one in the second half year. The annual temporal trend of the centre of gravity movement was similar, which was related to the monthly variation of CPUE. Among the environmental factors, SSH had the greatest impact on CPUE, especially in October, November and December, 2009 and 2012; BWS had a significant impact on CPUE in July, August and September, 2009 and October, November and December, 2012. The spatio-temporal scale of the CPUE was mainly influenced by SSH and BWS under the effect of nSCS currents. This study presents a method for spatio-temporal variation of economic fish CPUE, integrating the centre of gravity movement and the temporal variation of the CPUE with the environmental factors, which is helpful for determining the fishery management unit and closed fishing season in the nSCS. Keywords: Bigeye fish (Priacanthus spp.), Environmental factors, Generalised linear model (GLM), Northern South China Sea (nSCS), Spatio-temporal patterns

The large-scale system of ocean currents that transport warm waters in the upper 1000 m northward and return deeper cooler waters southward is known as the Atlantic meridional overturning circulation (AMOC). Variations in the AMOC have significant repercussions for the climate system; hence, there is a need for long-term monitoring of AMOC fluctuations. Currently the longest record of continuous directly measured AMOC changes is from the RAPID-MOCHA-WBTS programme, initiated in 2004. The RAPID programme and other mooring programmes have revolutionised our understanding of large-scale circulation; however, by design they are constrained to measurements at a single latitude and cannot tell us anything pre-2004. Nearly global coverage of surface ocean data from satellite altimetry has been available since the launch of the TOPEX/Poseidon satellite in 1992 and has been shown to provide reliable estimates of surface ocean transports on interannual timescales including previous studies that have investigated empirical correlations between sea surface height variability and the overturning circulation. Here we show a direct calculation of ocean circulation from satellite altimetry of the upper mid-ocean transport (UMO), the Gulf Stream transport through the Florida Straits (GS), and the AMOC using a dynamically based method that combines geostrophy with a time mean of the vertical structure of the flow from the 26∘ N RAPID moorings. The satellite-based transport captures 56 %, 49 %, and 69 % of the UMO, GS, and AMOC transport variability, respectively, from the 26∘ N RAPID array on interannual (18-month) timescales. Further investigation into the vertical structure of the horizontal transport shows that the first baroclinic mode accounts for 83 % of the interior geostrophic variability, and the combined barotropic and first baroclinic mode representation of dynamic height accounts for 98 % of the variability. Finally, the methods developed here are used to reconstruct the UMO and the AMOC for the time period pre-dating RAPID, 1993 to 2003. The effective implementation of satellite-based method for monitoring the AMOC at 26∘ N lays down the starting point for monitoring large-scale circulation at all latitudes.

Two-dimensional mapping of sea surface height (SSH) for future wide-swath satellite altimetry (WSA) is a challenge at present. So far, considering the utilization of data-driven methods is a new researching direction for SSH mapping. In general, the data-driven mapping methods rely on the spatial-temporal relationship of the observations. These methods require training in large volumes, and the time cost is high, especially for the WSA observations. This paper proposed the prediction neural networks for mapping (Mapping-PNN) method to improve the training efficiency and maintain stable data and mapping capabilities. By 10-year wide-swath satellite along track observing system simulation experiments (OSSEs) on the HYCOM data, the experiment results indicate that the method introduced in this paper can improve the training efficiency and meet the grid mapping expectations. Compared with other methods, the root mean squared error (RMSE) of the mapping-PNN method can be limited within the range of ~1.8 cm, and the new method can promote the observation of the ocean phenomena scale with < ~40 km, which reaches state of the art.

The interannual variability of rainfall caused by the El Niño Southern Oscillation (ENSO) results in significant changes in hydrologic conditions that affect entire countries’ water supply. Forecasting ENSO and its impacts are mainly based on Central Pacific Sea surface temperature (SST) anomalies which satisfactorily correlates with timing and, to a lesser extent, the intensity of drought conditions in the Philippines and the rest of the Western Pacific during the El Niño phase. Changes in sea surface height (SSH) are also brought upon by ENSO through density changes with temperature and oceanographic processes. Here, we report that the associative nature of SSH and drought as measured by surface runoff, has a stronger correlation (r > 0.693, p < 0.05) in terms of the expected timing, with 1 to 3 months lag time, and intensity compared to using traditional ENSO SST indices from the Central Pacific. Furthermore, since SSH is co-located with its corresponding forecasted decrease in runoff, a localized prediction can be made which further increases the accuracy of this predictive tool. In the wake of a changing climate, this work demonstrates the possibility of statistically forecasting the timing of precipitation, and thus the volume of surface water availability, using local SSH as an indicator. A tool which is necessary for time-sensitive management decision making in drought-prone tropical regions.

In the present study, an attempt has been made to develop a modified genesis potential index (GPI) by considering the atmospheric parameters of relative humidity (RH), thermal instability (TI), relative vorticity (RV), vertical wind shear (WS) and the ocean parameters of sea surface height (SSH) and upper ocean heat content (UOHC). The new genesis potential index (GPI) is a modified version of the currently used GPI by the India Meteorological Department (IMD), New Delhi for the North Indian Ocean which does not consider the ocean parameters. The main objective of the present study is to examine and improve our earlier GPI (Suneeta and Sadhuram 2018), during southwest monsoon (June–September) and post-monsoon (October–December) seasons for the period 1995–2018, over Bay of Bengal. In addition to UOHC and atmospheric parameters, we have introduced a new term, sea surface height (SSH) to compute the new GPI. Correlations have been computed between GPI and TNDC (total number of depressions, cyclones and severe cyclones) during both the seasons. This new index displayed very high correlation coefficient (CC) r = 0.85 (significant at a level greater than 99%) with the TNDC for the post-monsoon season. But it showed low correlation during SW monsoon season in which the GPI (Kotal et al. 2009) (which considers only atmospheric parameters) showed a correlation of 0.5 which is significant at 95% level. From this, it is inferred that the atmospheric parameters are important during southwest monsoon, while both atmospheric and ocean parameters (UOHC and SSH) appear to be playing important role during post-monsoon season. In this paper, the SSH has been included or the first time in the GPI which showed better performance during post-monsoon season.

One of the thorniest problems in altimetry community is retrieving accurate coastal sea surface height, especially in the last several kilometers offshore. It is confirmed in previous studies that decontaminating waveforms is beneficial to improve the quality of coastal SSHs. In this article, we proposed an upgraded strategy for waveform decontamination, including a novel realignment algorithm and gate-wise outlier detector. We validated the new strategy in four test regions using Jason-2 altimeter data. In the validation process, we compared retracked SSHs by 16 retrackers, which include retrackers provided in SGDR (Sensor Geophysical Data Record), ALES (Adaptive Leading Edge Subwaveform), and PISTACH (Prototype Innovant de Système de Traitement pour les Applications Côtières et l’Hydrologie) products. Comparison results verified that retracking the waveforms decontaminated using our new method can greatly improve the SSHs in the coastal region. The 20% threshold retracker (DW-TR20) and the ICE1 retracker (DW-ICE1) based on the decontaminated waveforms outperform other retrackers, especially in 0–4 km zone offshore. DW-TR20 and DW-ICE1 can provide robust SSHs with a consistent accuracy in 0–20 km coastal band and a high correlation (>0.9) with nearby gauge data. To conclude, the upgraded waveform decontamination strategy provides a promising solution for coastal altimetry, which makes it possible to extend reliable observations to the last several kilometers offshore.

Uptake of anthropogenic carbon dioxide from the atmosphere by the surface ocean is leading to global ocean acidification, but regional variations in ocean circulation and mixing can dampen or accelerate apparent acidification rates. Here we use a regional ocean model simulation for the years 1980 to 2013 and observational data to investigate how ocean fluctuations impact acidification rates in surface waters of the Gulf of Alaska. We find that large-scale atmospheric forcing influenced local winds and upwelling strength, which in turn affected ocean acidification rate. Specifically, variability in local wind stress curl depressed sea surface height in the subpolar gyre over decade-long intervals, which increased upwelling of nitrate- and dissolved inorganic carbon-rich waters and enhanced apparent ocean acidification rates. We define this sea surface height variability as the Northern Gulf of Alaska Oscillation and suggest that it can cause extreme acidification events that are detrimental to ecosystem health and fisheries. Decadal wind patterns enhance upwelling of carbon-rich waters and increase apparent surface ocean acidification rates in the Gulf of Alaska, according to a 34-year regional ocean biogeochemical hindcast model simulation.

Contemporary Universiti Teknologi Malaysia 2020 Mean Sea Surface (UTM20 MSS) and Mean Dynamic Topography (UTM20 MDT) models around Malaysian seas are introduced in this study. These regional models are computed via scrutinizing along-track sea surface height (SSH) points and specific interpolation methods. A 1.5-min resolution of UTM20 MSS is established by integrating 27 years of along-track multi-mission satellite altimetry covering 1993–2019 and considering the 19-year moving average technique. The Exact Repeat Mission (ERM) collinear analysis, reduction of sea level variability of geodetic mission (GM) data, crossover adjustment, and data gridding are presented as part of the MSS computation. The UTM20 MDT is derived using a pointwise approach from the differences between UTM20 MSS and the local gravimetric geoid. UTM20 MSS and MDT reliability are validated with the latest Technical University of Denmark (DTU) and Collecte Localisation Services (CLS) models along with coastal tide gauges. The findings presented that the UTM20, CLS15, and DTU18 MSS models exhibit good agreement. Besides, UTM20 MDT is also in good agreement with CLS18 and DTU15 MDT models with an accuracy of 5.1 and 5.5 cm, respectively. The results also indicate that UTM20 MDT statistically achieves better accuracy than global models compared to tide gauges. Meanwhile, the UTM20 MSS accuracy is within 7.5 cm. These outcomes prove that UTM20 MSS and MDT models yield significant improvement compared to the previous regional models developed by UTM, denoted as MSS1 and MSS2 in this study.