Search

Abstract The extreme conditions of the deep-sea environment, including limited light, low oxygen levels, high pressure, and nutrient scarcity, create a natural habitat for deep-sea bacteria. These remarkable microorganisms have developed unique strategies to survive and adapt to their surroundings. However, research on the diversity of deep-sea bacteria, both culture-dependent and culture-independent, in Indonesian waters remains insufficient. This study focused on exploring the biodiversity of deep-sea bacteria, specifically in the Makassar and Lombok Strait, the main Indonesian throughflow pathway characterized by relatively fertile water, which serves as an important deep-sea region. High-throughput DNA sequencing of full-length 16S rRNA was employed to construct a genomic database. The results of the bioinformatic analysis revealed that two stations, 48 and 50 (Makassar Strait), exhibited a more similar community structure of deep-sea bacteria than did station 33 (Lombok Strait). Among the predominant phyla found at a depth of 1000 m, the top ten were Proteobacteria, Firmicutes, Bacteroidetes, Actinobacteria, Planctomycetes, Acidobacteria, Nitrospinae, Verrucomicrobia, Candidatus Melainabacteria, and Cyanobacteria. Furthermore, the genera Colwellia, Moritella, Candidatus Pelagibacter, Alteromonas, and Psychrobacter consistently appeared at all three stations, albeit with varying relative abundance values. These bacterial genera share common characteristics, such as psychrophilic, halophilic, and piezophilic tendencies, and are commonly found in deep-sea ecosystem. The environmental conditions at a depth of 1000 m were relatively stable, with an average pressure 10 MPa, temperature 4.68 °C, salinity 34.58 PSU, pH 8.06, chlorophyll-a 0.29 µg/L, nitrate 3.19 µmol/L, phosphate 6.32 µmol/L and dissolved oxygen (DO) 2.90 mg/L. The bacterial community structures at the three sampling stations located at the same depth (1000 m) exhibited similarities, as indicated by the closely aligned similarity index values.

This paper examines the intraseasonal variabilities (ISVs) of the Wyrtki Jet in boreal spring and fall and their impacts on the oceanic ISVs along the southern coast of Sumatra-Java Island. The results reveal that the Wyrtki Jet ISVs in spring are significantly stronger than those in fall, with the standard deviation of the 0-30m-averaged zonal current reaching up to 0.25 m/s in spring, while the highest value in fall is only 0.2 m/s. The Wyrtki Jet ISVs are significantly correlated with surface zonal wind anomalies and sea level anomalies (SLAs) in the equatorial Indian Ocean (EIO) at intraseasonal timescale, and are modulated by the propagation of equatorial Kelvin waves. The intraseasonal SLAs along the southern coast of the Sumatra-Java Island are significantly correlated with the Wyrtki Jet ISVs, exhibiting similar seasonal fluctuation characteristics. In spring, the Wyrtki Jet intraseasonal signals initially appear near 75°E at the equator, approximately 10 days before the positive peaks of the intraseasonal SLAs, while in fall, the Wyrtki Jet intraseasonal signals first appear about 15 days before the peaks near 60°E at the equator, which is relatively further west compared to signals in spring. In addition, the composite Wyrtki Jet ISVs in spring are approximately 0.2 m/s stronger than those in fall. The enhanced ISVs of sea surface zonal wind forcing and Wyrtki Jet in spring, relative to those in fall, indicate that the seasonality in the intraseasonal SLAs along the southern coast of Sumatra-Java is attributable to the combined effects of surface wind forcing and current fields.

Abstract The Indonesian seas, with their complex passages and vigorous mixing, constitute the only route and are critical in regulating Pacific–Indian Ocean interchange, air–sea interaction, and global climate events. Previous research employing remote sensing and numerical simulations strongly suggested that this mixing is tidally driven and localized in narrow channels and straits, with only a few direct observations to validate it. The current study offers the first comprehensive temporal microstructure observations in the south of Lombok Strait with a radius of 0.05° and centered on 115.54oE and 9.02oS. Fifteen days of tidal mixing observations measured potential temperature and density, salinity, and turbulent energy dissipation rate. The results revealed significant mixing and verified the remotely sensed technique. The south Lombok temporal and depth averaged of the turbulent kinetic energy dissipation rate, and the diapycnal diffusivity from 20 to 250 m are $$\varepsilon$$ ε = 4.15 ± 15.9) × 10–6 W kg–1 and $$K\rho$$ K ρ = (1.44 ± 10.7) × 10–2 m2s–1, respectively. This $$K\rho$$ K ρ is up to 104 times larger than the Banda Sea [ $$K\rho$$ K ρ = (9.2 ± 0.55) × 10–6 m2s–1] (Alford et al. Geophys Res Lett 26:2741–2744, 1999) or the “open ocean” $$K\rho$$ K ρ = 0.03 × 10–4 m2s−1 within 2° of the equator to (0.4–0.5) × 10–4 m2s−1 at 50°–70° (Kunze et al. J Phys Oceanogr 36:1553–1576, 2006). Therefore, nonlinear interactions between internal tides, tidally induced mixing, and ITF plays a critical role regulating water mass transformation and have strong implications to longer-term variations and change of Pacific–Indian Ocean water circulation and climate.

Abstract In the nearshore area, ocean current display intricate complexities due to interactions among tide, river, and coastline, which makes accurate current modeling challenging. Continuous in situ observation with high spatial and temporal resolution helps to better understand the dynamics of these currents. In this study, we used a 10‐km long submarine fiber‐optic cable with distributed acoustic sensing technology to record seismic signals associated with ocean waves. The current velocity and water depth were obtained from the velocity dispersion using frequency‐wave number analysis matched against theoretical ocean wave propagation equations. The results show remarkable agreement with observation of a nearby current meter, confirming the dominance of tidal currents as well as a small‐scale residual current. The temporal variation of water depth is consistent with observation by a nearby tidal gauge. This study demonstrates the potential of using submarine fiber‐optic cable for long‐term, high‐resolution, near real‐time nearshore current monitoring.

Abstract The Brazil Current Overshoot regions feature the strongest sea surface temperature variations over the global ocean but forecast skill for these extreme variations is limited. Here we investigate the drivers of marine heatwaves and cold spells in this region and find that ocean flows and sea surface heat fluxes are the primary drivers. We also find that sea surface temperature extremes driven by air-sea heat fluxes produce consistent changes in sea surface temperature and related atmospheric variables over a wide horizontal area, whereas ocean flow-driven sea surface temperature extremes exhibit low consistency in air variables and limited consistency in the spatial extent of sea variables across most sea surface temperature extreme events. These differing air-sea characteristics associated with extremes driven by different drivers offer potential avenues for improving prediction skills and advancing the understanding of three-dimensional air-sea impacts associated with extreme events.

Abstract The offshore ocean heat supplied to the Antarctic continental shelves by warm eddies has the potential to greatly impact the melting rates of ice shelves and subsequent global sea level rise. While featured in modeling and some observational studies, the processes around how these warm eddies form and overcome the dynamic sub-surface barrier of the Antarctic Slope Front over the upper continental slope has not yet been clarified. Here we report on the detailed observations of persistent eddies carrying warm modified Circumpolar Deep Water (CDW) onto the continental shelf of Prydz Bay, East Antarctica, using subsurface mooring and hydrographic section data from 2013-2015. We show the warm-eddy transport is most active when the summer westerlies strengthen, which promotes the upwelling of CDW and initiates eddy formation and intrusions. Our study highlights the important role of warm eddies in the melting of Antarctica’s ice shelves, both now and into the future.

Abstract The mid-depth ocean circulation is critically linked to actual changes in the long-term global climate system. However, in the past few decades, predictions based on ocean circulation models highlight the lack of data, knowledge, and long-term implications in climate change assessment. Here, using 842,421 observations produced by Argo floats from 2001-2020, and Lagrangian simulations, we show that only 3.8% of the mid-depth oceans, including part of the equatorial Pacific Ocean and the Antarctic Circumpolar Current, can be regarded as accurately modelled, while other regions exhibit significant underestimations in mean current velocity. Knowledge of ocean circulation is generally more complete in the low-latitude oceans but is especially poor in high latitude regions. Accordingly, we propose improvements in forecasting, model representation of stochasticity, and enhancement of observations of ocean currents. The study demonstrates that knowledge and model representations of global circulation are substantially compromised by inaccuracies of significant magnitude and direction, with important implications for modelled predictions of currents, temperature, carbon dioxide sequestration, and sea-level rise trends.

Sea surface temperature (SST) is an important element in studying the global ocean-atmospheric system, as well as its simulation and projection in climate models. In this study, we evaluate the simulation skill of the Coupled Model Intercomparison Project Phase 6 (CMIP6) models in simulating the climatological SST in the Asian Marginal Seas (AMS), known as the most rapidly warming region over the global ocean. The results show that the spatial patterns and seasonal variability of Asian Marginal Seas (AMS) climatological SST simulated by the CMIP6 models are generally in good agreement with the observations, but there are simulation biases in the values. In boreal winter, the simulated climatological SST tends to be overestimated in the Japan/East Sea and the East China Seas (ECSs) by up to 2°C, while being underestimated in the Sea of Okhotsk by up to 2°C. In boreal summer, the simulated climatological SSTs are overestimated in the Indonesian seas and western Arabian Sea, while being underestimated in the Sea of Okhotsk and the northern ECSs by 1.2–1.5 and 2°C, respectively. Furthermore, we calculate the projected sea surface warming trends in the AMS under different future scenarios in the CMIP6 models. The results show warming trends of 0.8–1.8, 1.7–3.4, and 3.8–6.5°C/century for the Shared Socio-Economic Pathway (SSP) of low- (global radiative forcing of 2.6 W/m² by the year 2100), medium- (global radiative forcing of 4.5 W/m² by 2100) and high-end (8.5 W/m² by 2100) pathways, respectively. In addition, the middle and high latitudes of the AMS are found to have faster warming trends than the low latitudes, with the most rapidly warming occurring in the Sea of Okhotsk, which is around 2 times larger than the global mean SST warming trend. The SST warming trends are relatively slow in the South China Sea and the Indonesian seas, roughly equal to the global mean SST warming trend.

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

Abstract Nonstationary internal tides (ITs) are formed from their interactions with background currents. Harmonic analysis (HA), which cannot be used to estimate the incoherent component, is almost exclusively used method to predict ITs from observations. This remains ITs prediction challenge. In this study, we establish a deep learning framework to predict semidiurnal ITs. The model is established and trained with observed semidiurnal internal tidal currents that are 172 days long, and then ITs over the next 42 days are forecasted. The prediction accuracy is greatly improved using the deep learning framework. The magnitudes of errors using the deep learning framework are approximately 35% of those obtained using HA. Most temporal and spatial variations in baroclinic currents can successfully be forecasted using deep learning. In addition, the kinetic energy and incoherent components of ITs can be accurately predicted. Moreover, the relatively high adoptability of the established deep learning model is shown.

The cold wake caused by a tropical cyclone (TC) extends for hundreds of kilometers and persists for several weeks, thus influencing the surface response for any subsequent TCs that might pass over it. It is commonly accepted that sea-surface temperature (SST) cooling, as produced by a single TC, occurs primarily through vertical mixing. However, when there are sequential TCs, the earlier TC can dramatically change the thermal structure of the upper ocean, which may influence the subsequent development of a latter-occurring TC (LTC). Therefore, the contribution of horizontal advection and vertical mixing to SST-cooling during the passage of LTCs is of great interest. Using a 19-year-long observational dataset and the heat budget analysis of an idealized numerical simulation, the SST change during the passage of sequential TCs is investigated. The results demonstrate that, on average, the SST cooling caused by the LTC shows an overall decreasing trend with enhanced lingering wakes. Budget analysis of the model simulations suggests that an earlier TC can suppress the vertical mixing induced by an LTC mainly through an alteration of dynamics within the deepened mixed layer and that the contribution of vertical mixing to the SST cooling is weaker due to the intensification of the earlier TC. The weakened vertical mixing dominates the decreased SST cooling induced by an LTC. In contrast, the cold wake generated by an earlier TC can produce more cold water on the right side of the TC’s track, which contributes to stronger horizontal advection upon the arrival of the LTC. In general, the effects of the earlier TC can suppress the sea-surface thermal response to an LTC. If the contribution of the horizontal advection to SST cooling is neglected, the SST cooling induced by an LTC could be reduced by about 40%. As for the response of the sub-surface water to the passage of an LTC, the weakened warm anomaly induced by vertical mixing and the enhanced cooling anomaly caused by the vertical advection explain the reduced tendency for the mixed layer to deepen. As a result, the tendency for the mixed layer depth (MLD) to increase is suppressed during the passage of an LTC. These results highlight the importance of optimally depicting cold wakes in numerical simulations to improve the prediction of the upper ocean’s response to sequential TCs.

Exact knowledge on the seasonal variations of main tidal constituents is beneficial for improving tidal prediction. The semi-annual cycles in K1 and S2 tides are abnormally exaggerated by astronomical P1 and K2 tides, which interferes with our understanding on tidal seasonality. The widely-used tidal inference method in previous studies cannot fully separate astronomical P1 and K2 tides from seasonal P1 and K2 tides due to inaccurate inference relationship. In this study, on the basis of the ‘credo of smoothness’ which indicates that tidal admittances are smooth functions of tidal frequencies, we develop a novel but simple method to address this intractable issue and applied this method to explore the seasonality of tidal currents observed in the deep Timor Passage at the depth of 1800m. We find that the timing and range of seasonal modulations of M2, S2, K1, and O1 tides are distinct. Annual variations in tidal currents are much stronger than semi-annual variations in tidal currents. The annual and semi-annual ranges of M2 tide can reach 2.69 cm/s and 1.51 cm/s, which are largest among main constituents. Although the annual range of K1 tide is only 1.85 cm/s, considering the relatively small amplitude of time-averaged K1 tide (2.87cm/s), K1 the most affected tide by the annual cycle. The seasonal cycles of semi-diurnal tides (M2 and S2) are basically synchronous while those of diurnal tides (K1 and O1) are generally out-of-phase. As a general method, the proposed method can be widely applied to other sea areas to explore local tidal seasonality.

The Karimata Strait (KS) throughflow between the South China Sea (SCS) and Java Sea plays an essential role in heat and freshwater budget in the SCS and dual roles in strengthening/reducing the primary Indonesian throughflow (ITF) in the Makassar Strait. A sustained long-term monitoring of the ITF is logistically challenging and expensive; therefore, proxies are needed. Here, we use a combination of in situ measurement of the KS throughflow and satellite-derived sea surface height (SSH) and sea surface wind (SSW) to determine the interannual and decadal modulations in seasonal amplitude of the KS throughflow associated with El Niño-Southern Oscillation (ENSO), Indian Ocean dipole (IOD), Pacific Decadal Oscillation (PDO). Linear regression, correlation, harmonic and power spectrum analyses are used. The results manifest that there are significant interannual to decadal modulations in the seasonal amplitude of the KS throughflow. The modulations of the seasonal amplitude in the volume and heat transports range 1.36-1.92 Sv (1 Sv = 106 m3 s-1) and 126.41-173.36 TW (1 TW = 1012 W), respectively, with a significant cycle of ~9 years. From 1994 to 2020, the seasonal amplitude of volume transport through the KS shows an increasing trend of 37.75 ± 15.69 mSv decade-1 (1 mSv = 103 m3 s-1). The seasonal amplitude of the heat transport also increases, at a rate of 4.78 ± 1.52 TW decade-1. The KS volume transport is positively correlated with PDO and ENSO indices (r2 = 0.69 and r2 = 0.58), with a lag of 12 and 10 months, respectively. The results of composite analysis suggest that the interannual variability of the KS transport is related to the interannual anomalies of the SSH gradient and the local SSW fields in boreal winter.

The Japan/East Sea (JES) is known as a mid-latitude “Miniature Ocean” that features multiscale oceanic dynamical processes. Using principal component analysis (PCA), we investigate the variability of the sea surface chlorophyll-a concentration (SSC) and its bloom timing in the JES based on satellite remote sensing products spanning 1998–2019. The JES SSC exhibits strong seasonal variability and blooms twice annually. The spring bloom is induced under combined factors of increased photosynthetically active radiation (PAR), weakened wind speeds and sea ice melting, and terminated by the enhanced stratification. The fall bloom is induced by destratification and active dynamic processes (such as upwelling and front), and terminated by decreased PAR. The interannual variability of spring and fall bloom occur along the northwestern coast of the JES and in the deep Japan Basin, respectively. The positive SSC anomalies along the northwestern coast of the JES in spring is associated with more sea ice in the previous winter, weaker wind speed, and stronger stratification induced by the El Niño events. No significant relationship has been found between the fall bloom and the El Niño events. The bloom timing is controlled by the critical depth hypothesis. The initiation/termination timing of spring blooms has shifted earlier by 0.37/0.45 days, and the counterpart of fall blooms has shifted 0.49/1.28 days earlier per year. The duration and magnitude are independent with each other for spring bloom at interannual time scale. In contrast, they are positively correlated for fall bloom, because of both bloom timing and magnitude are dominated by active oceanic dynamical processes in fall.

This study presents the development and testing of a global navigation satellite system (GNSS) buoy designed for measuring the sea surface elevation and tide level. The precision-point-positioning (PPP) technology is adopted for precise observation. The design of the buoy body is optimized by stability and hydrodynamic calculations. A high-performance embedded data acquisition system with big storage and high-frequency sampling is developed for long-term observation. The GNSS buoy is deployed in a wind farm approximately 70 km offshore of China, and undergoes a 60-day ocean test. A comparison of the sea level elevations obtained from the GNSS buoy and the pressure sensor shows that there is a strong correlation between them, with a correlation coefficient of 0.99. A harmonic analysis is applied to derive the harmonic constants for four key tidal components (M2, S2, O1, and K1). The amplitude differences are −1.2 cm, 1.4 cm, −0.6 cm, and −1.2 cm, respectively, and the phase differences are 1.8°, 2.2°, −1.3°, and −2.9°, respectively. The strong correlation between the measurements of the GNSS buoy and the pressure sensor and the relatively small differences of the amplitude and phase of the main tidal components indicate that the compact GNSS buoy demonstrates a capability to continuously measure the sea surface elevation and tide level with an elevation reference in the open sea.

Air–sea heat flux is one of the most important factors that affects ocean circulation, weather, and climate. Satellite remote sensing could serve as an important supplement to the sparse in situ observations for heat flux estimations. In this study, we analyze the uncertainty of the turbulent heat fluxes derived from wind speed measured by the Cyclone Global Navigation Satellite System (CYGNSS) over the global tropical oceans at different time scales. In terms of spatial distribution, there is large uncertainty (approximately 50 to 85 W·m−2 in the RMSE) near the equator in the western Pacific Ocean, the Arabian Sea, the Bay of Bengal, and near the Gulf of Guinea. The turbulent heat fluxes are in agreement with the buoys in representing the intraseasonal and seasonal variability, but more specific regional validations are needed for revealing the synoptic and sub-synoptic phenomena and the diurnal cycle. The uncertainty of the CYGNSS wind speed contributes approximately 50–57% to the uncertainty of the estimation of turbulent heat fluxes at the frequency band with a typical period of 3–7 days. In addition, the input sea surface temperature, rather than the wind speed, results in differences in the estimation of the monthly mean turbulent heat fluxes in the tropical Atlantic Ocean based on the COARE 3.5 algorithm. In conclusion, although the CYGNSS-derived turbulent heat fluxes are basically in good agreement with the in situ observations, our analysis highlights the importance of considering the limitations of these datasets, particularly in high wind speed conditions and for higher-frequency variations, including at synoptic, sub-synoptic, and diurnal time scales.

The accurate estimation of ocean tide loading displacements is essential and necessary for geodesy, oceanic and geophysical studies. It is common knowledge that K1 and K2 tidal constituents estimated from Global Positioning System (GPS) observations are unsatisfactory because their tidal periods are nearly same to the revisit cycle or orbital period of GPS constellation. To date, this troublesome problem is not fully solved. In this paper, we revisit this important issue and develop a novel method based on the unique characteristic of tidal waves to separate GPS-system errors from astronomical K1/K2 tides. The well-known credo of smoothness indicates that tidal admittances of astronomical constituents in a narrow band can be expressed as smooth functions of tidal frequencies, while the interference of GPS-system errors seriously damages the smooth nature of observed tidal admittances. Via quadratic fitting, smooth functions of tidal frequencies for tidal admittances can be determined, thus, astronomical K1 and K2 tides can be interpolated using fitted quadratic functions. Three GPS stations are selected to demonstrate our method because of their typicality in terms of poor estimates of K1/K2 tidal parameters related to GPS-system errors. After removing GPS-systematical contributions based on our method, corrected K1/K2 tides at three GPS stations are much closer to the modeled K1/K2 tides from FES2014, which is one of the most accurate tide models. Furthermore, the proposed method can be easily applied to other areas to correct GPS-system errors because their smooth nature is valid for global tidal signals.

Ship type identification is an important basis for ship management and monitoring. The paper proposed a new method of ship type identification by combining characteristic parameters from the energy difference between high and low frequencies and the sensitive IMF variance mean value based on the modal decomposition of the underwater radiated noise signals using the Ensemble Empirical Mode Decomposition (EEMD) method. The comparison shows that the characteristic parameters of different types of ship, underwater radiated noises are different, whereas those of the same types of ship, underwater radiated noises fall in close range. Validation experiments based on randomly selected ship underwater radiated noise samples manifest that the method is of good separability for the four types of ship underwater radiated noises in the Deepship dataset. It has a higher identification rate than other methods within the distance range of ship underwater radiated noise detection in the dataset. The accuracy of this method tends to decrease with distance in the classification experiments of the ship underwater radiated noises at different distances.

Marine heatwaves (MHWs) and low sea surface salinity (SSS) events can significantly impact marine ecosystems and dynamic systems, respectively. Compound marine extreme events can cause more significant damage than individual extreme events. However, the spatiotemporal patterns of compound MHW-low SSS extremes are not well understood. Daily reanalysis data were used to identify the basic patterns of compound extreme events and their drivers. These events mainly occur over the central tropical Pacific Ocean during record-breaking El Niño events. This analysis revealed that extreme sea surface warming associated with El Niño drives increased convection, which subsequently leads to increased rainfall. It ultimately causes extreme sea surface freshening. This analysis highlights the significance of air-sea interactions and low-frequency climate variability in shaping compound extreme events.

Sea surface salinity (SSS) extremes, characterized as events surpassing a certain threshold percentile, pose a threat to stenohaline organisms worldwide. This study presents the first global mapping of SSS extreme metrics and investigates their underlying drivers using daily reanalysis data. Our key findings have revealed that mesoscale eddies drive SSS extremes over most of the global ocean with peaks in duration ranging from 5 to 10 d and peaks in intensity ranging from 0.2 to 0.3 g kg ^−1 . Freshwater fluxes (FWFs) and mean currents are generally associated with the occurrence of prolonged and intense SSS extremes in tropical and extratropical oceans, respectively. FWFs related to interannual climate modes contribute to the asymmetric distribution of high and low SSS extremes in the central Pacific Ocean and the western Indian Ocean. These results highlight the distinct impacts of different local drivers on the mean states of SSS extremes.

Exploring multi-timescale tidal variability is fundamental and necessary for numerous practical purposes, such as flood protection, marine cultivation, and ocean transport. It is well known that tides show significant seasonal, inter-annual, and 18.61-year nodal variability. Less known and less discussed is the subseasonal tidal variability (i.e., ter-annual, quarter-annual, and penta-annual cycles) in the coastal ocean. In this study, we explore subseasonal tidal modulations in the Gulf of Tonkin via the combination of four tide gauges and 27-year multi-satellite altimeter observations. Both tide gauges and satellite altimeters indicate that tidal subseasonality is significant in the Gulf of Tokin, although the amplitudes of subseasonal variations are much smaller than those of seasonal variations. Compared to spatially limited tide gauges, satellite altimeters successfully derive the basin-scale tidal subseasonality in the Gulf of Tonkin. The largest amplitude of subseasonal tidal constituents originated from the subseasonality of main tidal constituents, and can reach as high as 31.8 mm. It is suggested that subseasonal variations in ocean environments (e.g., sea levels and ocean stratification) induce tidal subseasonality through changing tidal propagation and dissipation. Although powerful, satellite altimeters also have some defects. Due to tidal aliasing related to long-period sampling intervals, some subseasonal tidal constituents are indistinguishable in satellite altimeter records.

The North Brazil Undercurrent (NBUC) is a narrow (16 Sv) and plays an important role in the Atlantic Meridional Overturning Circulation and the South Atlantic Subtropical Cell. Strong salinity and temperature fronts occur over the NBUC region. The role of temperature and salinity gradients on the genesis of NBUC variability has never been explored. This study uses three high-resolution (≤0.1°) and one low-resolution (=0.25°) model outputs to explore the linear trend of NBUC transport and its variability on annual and interannual time scales. We find that the linear trend and interannual variability of the geostrophic NBUC transport show large discrepancies among the datasets. Thus, the linear trend and variability of the geostrophic NBUC are associated with model configuration. We also find that the relative contributions of salinity and temperature gradients to the geostrophic shear of the NBUC are not model dependent. Salinity-based and temperature-based geostrophic NBUC transports tend to be opposite-signed on all time scales. Despite the limited salinity and temperature profiles, the model results are consistent with the in-situ observations on the annual cycle and interannual time scales. This study shows the relationship of salinity-based and temperature-based geostrophic NBUC variations in the annual and interannual variability and trend among different models and highlights the equal important roles of temperature and salinity in driving the variability of NBUC transport.

The 9th Chinese National Arctic Research Expedition was carried out from 20 July to 26 September 2018. The expedition was successful in undertaking multidisciplinary comprehensive surveys in the fields of physical oceanography, marine meteorology, sea ice, marine chemistry, marine biology, marine ecology, geology, and geophysics in the Bering Sea, Chukchi Sea, Chukchi Plateau, Mendeleev Ridge, and Canada Basin. This paper gives an overview of the main achievements of this expedition and highlights the scientific achievements.

Understanding nodal tidal characteristics is essential for accurate long-term tidal prediction. Observational nodal evolution of tides is mainly based on tide gauge records in coastal areas which are limited in time and space, thus impeding coherent determinations of basin-wide patterns of tidal variability. In this paper, we indicate the potential of satellite altimeter data to investigate 18.61-year nodal modulations of main constituents in the Gulf of Tonkin. Three tide gauges and multi-source satellite altimeter observations (TOPEX/Poseidon, Jason1, Jason2, and Jason3) revealed that 18.61-year nodal cycles in tidal amplitudes have noticeable deviations from the equilibrium tidal theory in the Gulf of Tonkin. In general, M2 and N2 nodal modulations are anomalously larger than theoretical values while K2, K1, and O1 nodal modulations are noticeably smaller than theoretical values. Compared to point-based tide gauges, satellite altimeter records can provide basin-wide features of nodal modulations of main constituents. Although overlapping geographical blocks are applied to eliminate the effect of tidal alias originated from long-period sampling intervals, the estimation of nodal cycles of minor constituents are still questionable. Nevertheless, the methods described here provide a strong foundation for future research on time-varying tidal dynamics using the combination of tide gauges and satellite altimeter data.

As a ubiquitous movement in the ocean, tides are vital for marine life and numerous marine activities such as fishing and ocean engineering. Tidal dynamics are complicated in the East Asian marginal seas (EAMS) due to changing complex topography and coastlines related to human activities (e.g., land reclamation and channel deepening) and natural variability (e.g., seasonal variations of ocean stratification and river flow). As an important tool, numerical models are widely used because they can provide basin-scale patterns of tidal dynamics compared to point-based tide gauges. This paper aims to overview the development history of the numerical simulation of tides in the EAMS, including the Bohai Sea, the Yellow Sea, the East China Sea, the East/Japan Sea, and the South China Sea, provide comprehensive understanding of tidal dynamics, and address contemporary research challenges. The basic features of major tidal constituents obtained by tidal models are reviewed, and the progress in the inversion of spatially and temporally changing model parameters via the adjoint method are presented. We review numerical research on how a changing ocean environment induces tidal evolution and how tides and tidal mixing influence ocean environment in turn. The generation, propagation, and dissipation of internal tides in the EAMS are also reviewed. Although remarkable progresses in tidal dynamics have been made, nonstationary tidal variations are not fully explained yet, and further efforts are needed. In addition, tidal influences on ocean environment still receive limited attention, which deserves special attention.

Exploring the relationship between evaporation (E)-minus-precipitation (P) and sea surface salinity (SSS) is vital for understanding global hydrological cycle changes and investigating the salinity budget. This study quantifies the uncertainty in the relationship between E−P and SSS based on satellite data over the 50°S–50°N ocean from 2012 to 2017 in 140 sets of combinations of E, P and SSS. We find that the uncertainty (10%) in the variability of freshwater flux (FWF) over 2012–2017 is smaller than that in SSS (15%). The difference in the combination of sets of “E-P-SSS” products can lead to the 10% difference in RMSD and 25% difference in area-weighted mean correlation coefficients between SSS tendency and FWF. There is a 24.1~58% area over the global ocean with a significant (p value < 0.05) positive correlation between the FWF and SSS tendency derived from satellite products. The seasonal EMP and SSS tendencies show larger correlation coefficients and lower RMSDs over most sets compared with those on nonseasonal time scales. Large uncertainty in the FWF-SSS tendency relation associated with spread among products prevents the use of one combination of E, P and SSS from satellite-based products for salinity budget analysis.

We report the direct and quantitative measurement of five significant near-inertial waves (NIWs) events observed by Lander at water depths of 600 m to 1100 m at 119°17′ E and 22°06′ N in the northern South China Sea from July to November 2017. We found that these five NIWs events lead to strong shearing, which plays an important role in deep water mixing. Each event corresponds to several different NIWs generation mechanisms. The results show that the NIWs events generated by typhoons were the most regular. This was caused by dispersive NIWs propagation over long periods of time and over long distances. NIWs formed by spontaneous generation do not have this feature. The strongest NIWs events during the observation period were caused by a combination of shelf wave attenuation and monsoon. This time, the signal was transmitted to the seabed, and the upward signal reflected in the meridional direction was found. The reflected signal was anisotropically affected by the seabed topography. A horizontally propagated NIWs event with relatively weak dispersion was also found in this study. Based on the topography, we suspect it was formed by the Lee wave, but we cannot provide any more useful evidence.

Marine heatwaves (MHWs) are prolonged discrete events of anomalously warm seawater observed around the world. The occurrence of MHWs in the Japan/East Sea (JES), a middle latitude marginal sea with abundant aquatic resources, has severe impacts on marine ecosystems and human society. We used satellite remote sensing products spanning 1982–2020 to investigate the mean states and variations of JES MHWs. The results show that the JES MHWs occurred twice per year. More than 40% of the MHWs were shorter than the mean duration of 12.6 days and weaker than the mean intensity of 2.4 °C. Frequent MHWs were observed in August, while high mean intensities were observed in winter and spring in the western JES. In recent years, the area’s averaged yearly sum of MHW intensity in the JES has increased dramatically, with a positive trend of 29.62 °C days per decade—over twice the average global trend (12.37 °C days per decade), which is further confirmed by its first empirical orthogonal function mode. The strengthening trend in MHWs may be explained by oceanic dynamics rather than atmospheric forcing, and may result in increased surface latent heat flux from the ocean to the atmosphere.

The southern coast of Java is known as one of the most productive fishing grounds for tuna, feeding by nutrient-rich water along the coast caused by the subsurface water upwelling. This primary productivity can be evidenced by the high sea surface chlorophyll-a concentration (SSC). Based on satellite remote sensing products, we investigate the multi-scale variability in SSC along the Sumatra-Java coast. The results show that seasonal variability of SSCs is primarily due to monsoon-driven upwelling and rainfall in the Indian Ocean and Indonesian seas sides of the Sumatra and Java Islands, respectively. Local Ekman pumping plays a secondary role, while rainfall input to the ocean has little effect. Coastally trapped Kelvin waves and mesoscale eddies are responsible for the intraseasonal SSC anomalies in regions along the south coast of Java and off the Sunda and Lombok Straits, respectively. The interannual variability in SSC is caused by the anomalous upwelling related to the Indian Ocean Dipole. There was a weak increasing trend of ~0.1–0.2 mg/m3 per decade, above the global averaged trend, which may be related to enhanced local Ekman pumping. These analyses provide an overall description of SSC variations based on satellite observations; however, further investigations based on in situ observations are needed to achieve better quantification.

The variability in sea surface salinity (SSS) on different time scales plays an important role in associated oceanic or climate processes. In this study, we compare the SSS on sub-annual, annual, and interannual time scales among ten datasets, including in situ-based and satellite-based SSS products over 2011–2018. Furthermore, the dominant mode on different time scales is compared using the empirical orthogonal function (EOF). Our results show that the largest spread of ten products occurs on the sub-annual time scale. High correlation coefficients (0.6~0.95) are found in the global mean annual and interannual SSSs between individual products and the ensemble mean. Furthermore, this study shows good agreement among the ten datasets in representing the dominant mode of SSS on the annual and interannual time scales. This analysis provides information on the consistency and discrepancy of datasets to guide future use, such as improvements to ocean data assimilation and the quality of satellite-based data.

Using in situ observations collected by a drifting air-sea interface buoy (DrIB) in the northern South China Sea from August 30 to September 13, 2018, the extreme air-sea turbulent fluxes that occurred from September 8 to 13 during tropical cyclone (TC) Barijat were investigated. The most striking features were substantial increases in momentum and heat fluxes, with maximum increases of 10.8 m s-1 in the wind speed (WS), 0.73 N m-2 in the wind stress, 68.1 W m-2 in the sensible heat fluxes (SH) and 258.8 W m-2 in the latent heat fluxes (LH). The maximum WS, wind stress, SH and LH values amounted to 15.3 m s-1, 0.8 N m-2, 70.9 W m-2 and 329.9 W m-2, respectively. Using these new DrIB observations, the performance of two state-of-the-art, high-resolution reanalysis products, ERA5 and MERRA2, was assessed. The consistency of the observed values with ERA5 was slightly better than with MERRA2, reflected in higher correlations but both products underestimated the WS during TC conditions. In calm weather conditions, the turbulent heat fluxes were overestimated, because they simulated a too dry and cold atmospheric state, enhancing the air-sea differences in temperature and humidity. Considering that an accurate representation of the air-sea turbulent and momentum fluxes is essential for understanding and predicting ocean and atmospheric variability, our findings indicate that more high-quality temperature and relative humidity observations are required to evaluate and improve existing reanalysis products. [ABSTRACT FROM AUTHOR]