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Observational surface data are utilized to reconstruct the subsurface density and geostrophic velocity fields via the “interior + surface quasigeostrophic” (isQG) method in a subdomain of the Antarctic Circumpolar Current (ACC). The input variables include the satellite-derived sea surface height (SSH), satellite-derived sea surface temperature (SST), satellite-derived or Argo-based sea surface salinity (SSS), and a monthly estimate of the stratification. The density reconstruction is assessed against a newly released high-resolution in situ dataset that is collected by a southern elephant seal. The results show that the observed mesoscale structures are reasonably reconstructed. In the Argo-SSS-based experiment, pattern correlations between the reconstructed and observed density mostly exceed 0.8 in the upper 300 m. Uncertainties in the SSS products notably influence the isQG performance, and the Argo-SSS-based experiment yields better density reconstruction than the satellite-SSS-based one. Through the two-dimensional (2D) omega equation, we further employ the isQG reconstructions to diagnose the upper-ocean vertical velocities (denoted wisQG2D), which are then compared against the seal-data-based 2D diagnosis of wseal. Notable discrepancies are found between wisQG2D and wseal, primarily because the density reconstruction does not capture the seal-observed smaller-scale signals. Within several subtransects, the Argo-SSS-based wisQG2D reasonably reproduce the spatial structures of wseal, but present smaller magnitude. We also apply the isQG reconstructions to the 3D omega equation, and the 3D diagnosis of wisQG3D is very different from wisQG2D, indicating the limitations of the 2D diagnostic equation. With reduced uncertainties in satellite-derived products in the future, we expect the isQG framework to achieve better subsurface estimations.

Strong subinertial variability near a seamount at the Xisha Islands in the South China Sea was revealed by mooring observations from January 2017 to January 2018. The intraseasonal deep flows presented two significant frequency bands, with periods of 9–20 and 30–120 days, corresponding to topographic Rossby waves (TRWs) and deep eddies, respectively. The TRW and deep eddy signals explained approximately 60% of the kinetic energy of the deep subinertial currents. The TRWs at the Ma, Mb, and Mc moorings had 297, 262, and 274 m vertical trapping lengths, and ∼43, 38, and 55 km wavelengths, respectively. Deep eddies were independent from the upper layer, with the largest temperature anomaly being >0.4°C. The generation of the TRWs was induced by mesoscale perturbations in the upper layer. The interaction between the cyclonic–anticyclonic eddy pair and the seamount topography contributed to the generation of deep eddies. Owing to the potential vorticity conservation, the westward-propagating tilted interface across the eddy pair squeezed the deep-water column, thereby giving rise to negative vorticity west of the seamount. The strong front between the eddy pair induced a northward deep flow, thereby generating a strong horizontal velocity shear because of lateral friction and enhanced negative vorticity. Approximately 4 years of observations further confirmed the high occurrence of TRWs and deep eddies. TRWs and deep eddies might be crucial for deep mixing near rough topographies by transferring mesoscale energy to small scales.

Species distribution models predict a poleward migration for marine ectotherms with ocean warming. However, a key limitation in current species distribution models (SDM) is that they do not account for population-specific heterogeneity in physiological responses to temperature change resulting from local adaptations and acclimatization. To address this gap, we developed a novel, Physiology Integrated BioClimate Model (PIBCM) that combines habitat-specific metabolic thermal physiological tolerance of a species into a bioclimate envelope model. Using a downscaling approach, we also established a fine-resolution coastal sea-surface temperature data set for 2050–2080, that showed a high degree of location-specific variability in future thermal regimes. Combining predicted temperature data with the PIBCM model, we estimated habitat distribution for a highly eurythermal intertidal minnow, the Atlantic killifish (Fundulus heteroclitus), a species that likely presents a best-case-scenario for coastal vertebrates. We show that the killifish northern boundary shifts southwards, while distinct habitat fragmentation occurs in the southern sub-population (due to migration of adjacent fish populations to the nearest metabolically optimal thermal habitat). When compared to current SDMs (e.g., AquaMaps), our results emphasize the need for thermal physiology integrated range shift models and indicate that habitat fragmentation for coastal fishes may reshape nursery habitats for many commercially and ecologically important species.

Using the extended “interior + surface quasigeostrophic” method from the 2019 study by Liu et al. (hereafter L19), subsurface density and horizontal velocities can be reconstructed from sea surface buoyancy and surface height. This study explores the potential of L19 for diagnosing the upper-ocean vertical velocity w field from high-resolution surface information, employing the 1/30° horizontal resolution OFES model output. Specifically, we employ the L19-reconstructed density and horizontal velocity fields in a diabatic version of the omega equation that incorporates a simplified parameterization for turbulent vertical mixing. The w diagnosis is evaluated against OFES output in the Kuroshio Extension region of the North Pacific, and the result indicates that the L19 method constitutes an effective framework. Statistically, the OFES-simulated and L19-diagnosed w fields have a 2-yr-averaged spatial correlation of 0.42–0.51 within the mixed layer and 0.51–0.67 throughout the 1000-m upper ocean below the mixed layer. Including the diabatic turbulent mixing effect has improved the w diagnoses inside the mixed layer, particularly for the cold-season days with the largest correlation improvement reaching 0.31. Our encouraging results suggest that the L19 method can be applied to the high-resolution sea surface height data from the forthcoming Surface Water and Ocean Topography (SWOT) satellite mission for reconstructing 3D hydrodynamic conditions of the upper ocean.

Typhoons are assumed to stimulate primary ocean production through the upward mixing of nutrients into the ocean surface. This assumption is based largely on observations of increased surface chlorophyll concentrations following the passage of typhoons. This surface chlorophyll enhancement, occasionally detected by satellites, is often undetected due to intense cloud coverage. Daily data from a BGC-Argo profiling float revealed the upper-ocean response to Typhoon Trami in the northwest Pacific Ocean. Temperature and chlorophyll changed rapidly, with a significant drop in sea surface temperature and a surge in surface chlorophyll associated with strong vertical mixing, which was only partially captured by satellite observations. However, no net increase in vertically integrated chlorophyll was observed during Typhoon Trami or in its wake. In contrast to the prevailing dogma, the result shows that typhoons likely have a limited effect on net primary ocean production. Observed surface chlorophyll enhancements during and immediately following typhoons in tropical and subtropical waters are more likely to be associated with surface entrainment of deep chlorophyll maxima. Moreover, the findings demonstrate that remote sensing data alone can overestimate the impact of storms on primary production in all oceans. Full understanding of the impact of storms on upper-ocean productivity can only be achieved with ocean-observing robots dedicated to high-resolution temporal sampling in the path of storms.

The northern South China Sea (NSCS) is a dynamically complex region whose shelf and slope currents are driven by different mechanisms. In this study, we used field measurements to identify clear interannual variations in the circulation related to the El Nino-Southern Oscillation cycle. To investigate the modulation mechanisms, we used a high-resolution numerical model that covers the shelf and slope regions of the NSCS. The results indicate that the stronger southwestward slope current during La Nina and stronger northeastward shelf current during El Nino in summer and winter are largely related to changes in wind forcing. The Kuroshio intrusion into the NSCS does not appear to significantly affect the circulation in the southwestern shelf region.

San Francisco Bay (SFB) is a complex ecosystem that has been heavily impacted by human activities. It has experienced strong year-to-year variations in physical, chemical, and biological conditions, due to both natural climate variation and human activities. There is a need to investigate this long-term variation, with a focus on management practices and needs. The study aims to construct a coupled hydrodynamic and ecosystem model SCHISM/CoSiNE, to investigate interannual variability of chlorophyll and nutrient dynamics in SFB over the 10-year period of 2005–2014. The coupled SCHISM/CoSiNE model captures the long-term observations well. It shows that high chlorophyll concentrations in South Bay persist during warm months, while chlorophyll in North Bay is low and has strong interannual variation. Nutrient concentrations are higher in North Bay where large river outflow influences their distribution and interannual variation, and in lower South Bay. The model results show that phytoplankton blooms in Suisun Bay tend to occur when flow rates are between 100 and 250 m3/s and ammonium concentration is in the range of 1–2 mmol/m3. Model sensitivity experiments show that benthic grazing can potentially reduce phytoplankton biomass, and its effect on chlorophyll concentration is modulated by river outflow. We demonstrate the potential of this open-source model for exploring water quality conditions and options for river flow management of SFB.

The Gulf Stream (GS) transports a massive amount of heat northward to high latitudes and releases sensible and latent heat to the atmosphere, playing an important role in the North Atlantic and European climate change. The change trends of the GS transport and pathway are still uncertain to date. Our analyses of altimeter observations from 1993 to 2016 indicate that the linear trends in surface maximum speed, transport, and latitudinal location of the GS are significant east of 61° W at the 95% level while they are small and not significant between 72° W and 61° W. The weakening trend of the GS during the period from 1993 to 2016 is accompanied with a southward-shifting path, which is associated with the decline of the North Atlantic Oscillation (NAO) and possibly reduction in the Atlantic meridional overturning circulation (AMOC).

Previous studies suggest importance of wind forcing on salt intrusion length and salt flux in river-dominated microtidal estuaries (with tidal range < 2 m). In this study, we investigate the role of wind forcing on salt intrusion in a mesotidal estuary, San Francisco Bay (SFB), with tidal ranges between 2 m and 4 m, through an open-source model of high transferability, the Semi-implicit Cross-scale Hydroscience Integrated System Model (SCHISM). Meanwhile, we investigate circulation and salinity variation of San Francisco Bay. The model’s performance in hydrodynamics at tidal, spring/neap and seasonal time scales is validated through model-observation comparisons. Through realistically forced and process-oriented experiments, we demonstrate that spring/neap tides can cause fortnightly variations in salinity and currents by modulating vertical mixing and stratification; and seasonal variability of circulation in North Bay is determined by change of river discharge and modified by winds, while in South Bay it is dominated by wind-driven flows. Furthermore, we revealed the role of wind on X2 (the distance from the Golden Gate Bridge to the 2-PSU isohaline at the bottom). The model results show that X2 is primarily influenced by river flow and proportional to river flow to the ¼ power. Meanwhile, wind plays a secondary role in modifying X2 by increasing X2 from 0 to 5 km during low discharge period, while spring/neap tide modulation on X2 is negligible but important for salt balance in sub-regions downstream of X2.

By parameterizing the abyssal mixing as the exchange velocity (entrainment/detrainment) between the middle and deep layers of the South China Sea (SCS), its effects on the multilayer circulation are examined. Results indicate that the cyclonic circulation in the deep SCS appears only when the mixing induces an entrainment of at least 0.72 Sv (1 Sv ≡ 106 m3 s−1) from the deep to the middle layer, which is equivalent to a diapycnal diffusivity of 0.65 × 10−3 m2 s−1 or a net input rate of gravitational potential energy (GPE) of 6.89 GW, respectively. It is also found that tidal mixing in the SCS is stronger than the threshold for the generation of the cyclonic abyssal circulation, but the pattern and evolution of the deep circulation and meridional overturning circulation also depend on the spatiotemporal variability of the mixing. Moreover, the abyssal mixing is able to intensify the anticyclonic circulation in the middle layer but weaken the cyclonic circulation in the upper layer. Vorticity analysis suggests that the upward net flux induced by the abyssal mixing leads to vortex stretching (squeezing) and modulates the pressure gradient by redistributing the layer thickness, hence affects the pattern and strength of the circulation in the middle (deep) layer of the SCS, respectively. The depth-integrated effect of the thickness variation can modulate the pressure gradient across all layers and hence influence the upper-layer circulation.

When evaluated against the 1/30°-resolution, submesoscale-resolving OFES model outputs, the previously published “interior + surface quasigeostrophic” method (from the 2013 study by Wang et al., denoted W13) for reconstructing the ocean interior from sea surface information is found to perform improperly in depicting smaller-scale oceanic motions (associated with horizontal scales smaller than about 150 km). This could be attributed to the fact that the W13 method uses only the barotropic and first baroclinic modes for the downward projection of sea surface height (SSH), while SSH at smaller scales significantly reflects other higher-order modes. To overcome this limitation of W13, an extended method (denoted L19) is proposed by employing a scale-dependent vertical projection of SSH. Specifically, the L19 method makes the projection via two gravest modes as proposed in the W13 method only for larger-scale (>150 km) signals, but for smaller scales (≤150 km) it exploits the framework of the “effective” surface quasigeostrophic (eSQG) method. Evaluation of the W13, eSQG, and L19 methods shows that the proposed L19 method can achieve the most satisfactory subsurface reconstruction in terms of both the flow and density fields in the upper 1000 m. Our encouraging results highlight the potential applicability of L19 method to the high-resolution SSH data from the upcoming Surface Water and Ocean Topography (SWOT) satellite mission.

The South China Sea (SCS) is a large marginal sea connecting the Indian and Pacific oceans. Under the factors of monsoons, strait transport, and varied bathymetry, the SCS presents a three-layer structure and strong diapycnal mixing which is far greater than that in the open ocean. Theoretical analysis and observations reveal that internal tides, internal solitary waves, and strong winds are the sources of the strong mixing in the northern SCS. A major consequence of the strong mixing is an active mid-deep circulation system. This system promotes exchange of water between the SCS and adjacent oceans, and also regulates the upper layer of wind-driven circulation, making the 3 dimensional SCS circulation clearly different from that in other tropical and subtropical marginal seas. The mass transport capacity of the mid-deep circulation has a substantial impact on marine sedimentation, the biogeochemical cycle, and other processes in the SCS. This paper summarizes the recent advances in mid-deep sea circulation dynamics of the SCS, and discusses the opportunities and challenges in this area.

As climate change threatens species' persistence, predicting the potential for species to adapt to rapidly changing environments is imperative for the development of effective conservation strategies. Eco-evolutionary individual-based models (IBMs) can be useful tools for achieving this objective. We performed a literature review to identify studies that apply these tools in marine systems. Our survey suggested that this is an emerging area of research fuelled in part by developments in modelling frameworks that allow simulation of increasingly complex ecological, genetic and demographic processes. The studies we identified illustrate the promise of this approach and advance our understanding of the capacity for adaptation to outpace climate change. These studies also identify limitations of current models and opportunities for further development. We discuss three main topics that emerged across studies: (i) effects of genetic architecture and non-genetic responses on adaptive potential; (ii) capacity for gene flow to facilitate rapid adaptation; and (iii) impacts of multiple stressors on persistence. Finally, we demonstrate the approach using simple simulations and provide a framework for users to explore eco-evolutionary IBMs as tools for understanding adaptation in changing seas.

The high-precision prediction of Earth orientation parameters (EOPs) is essential for astro-geodynamics, high-precision space navigation and positioning, on-board autonomous orbits determination and deep space exploration. However, the prediction accuracy of existing models is much lower than the estimation accuracy of geodetic technical solutions, which affects certain high-precision real-time users. To improve the prediction accuracy of EOP in short- and long-term period, we propose a hybrid model by combining the singular spectrum analysis (SSA), least squares (LSs) and support vector machine (SVM) in the study. Through SSA algorithm, the deterministic time-varying signal of EOP time series can be more precisely and reasonably detected and modeled. Based on the optimization theory, we reconstruct the EOP sequences using SSA and establish the LS extrapolation model based on the reconstructed series. Then, the residuals from SSA reconstruction and those from the LS model, are used for SVM training and prediction. The results of two-year prediction experiments based on the EOP 14 C04 series show that the proposed hybrid model has significant improvements in polar motion (PM) and length of day (LOD) for different prediction intervals (1–360 d) compared with the LS + autoregression (AR) model. The prediction error for x-component of polar motion (PMX) is reduced by 40.2%, 31.0% and 51.4% while that for y-component of polar motion (PMY) is 22.1%, 23.3% and 55.6% for prediction period of 30, 90 and 180 d respectively. For LOD, the maximum prediction improvement can reach to 53.8% during the predicted 360 d. In addition, the proposed method has better accuracy in mid- and long-term PM(x, y) predictions compared to the Bulletin A, with a 360 d prediction error of 27.273 and 21.741 mas.

An unprecedented devastating forest fire occurred in Australia from September 2019 to March 2020. Satellite observations revealed that this rare fire event in Australia destroyed a record amount of more than 202,387 km2 of forest, including 56,471 km2 in eastern Australia, which is mostly composed of evergreen forest. The released aerosols contained essential nutrients for the growth of marine phytoplankton and were transported by westerly winds over the Southern Ocean, with rainfall-induced deposition to the ocean beneath. Here, we show that a prominent oceanic bloom, indicated by the rapid growth of phytoplankton, took place in the Southern Ocean along the trajectory of fire-born aerosols in response to atmospheric deposition. Calculations of carbon released during the fire versus carbon absorbed by the oceanic phytoplankton bloom suggest that they were nearly equal. This finding illustrates the critical role of the oceans in mitigating natural and anthropogenic carbon dioxide releases to the atmosphere, which are a primary driver of climate change.

In San Francisco Bay (SFB), light availability is largely determined by the concentration of suspended particulate matter (SPM) in the water column. SPM exhibits substantial variation with time, depth, and location. To study how SPM influences light and phytoplankton growth, we coupled a sediment transport model with a hydrodynamic model and a biogeochemical model. The coupled models were used to simulate conditions for the year of 2011 with a focus on northern SFB. For comparison, two simulations were conducted with ecosystem processes driven by SPM concentrations supplied by the sediment transport model and by applying a constant SPM concentration of 20 mg l–1. The sediment transport model successfully reproduced the general pattern of SPM variation in northern SFB, which improved the chlorophyll-a simulation resulting from the biogeochemical model, with vertically integrated primary productivity varying greatly, from 40 g[C] m–2year–1over shoals to 160 g[C] m–2year–1in the deep channel. Primary productivity in northern SFB is influenced by euphotic zone depth (Ze). Our results show thatZein shallow water regions (Zein deep water regions is controlled by SPM concentration. As a result,Zehas low (high) values in shallow (deep) water regions. Large (small) differences in primary productivity exist between the two simulations in deep (shallow) water regions. Furthermore, we defined a new parameterFlightfor “averaged light limitation” in the euphotic zone. The averaged chlorophyll-a concentration in the euphotic zone andFlightshare a similar distribution such that both have high (low) values in shallow (deep) water regions. Our study demonstrates that light is a critical factor in regulating the phytoplankton growth in northern SFB, and a sediment transport model improves simulation of light availability in the water column.

The role of the Mindoro Strait-Sibutu passage pathway in influencing the Luzon Strait inflow to the South China Sea (SCS) and the SCS multi-layer circulation is investigated with a high-resolution (0.1° × 0.1°) regional ocean model. Significant changes are evident in the SCS upper layer circulation (250-900 m) by closing the Mindoro-Sibutu pathway in sensitivity experiments, as Luzon Strait transport is reduced by 75%, from −4.4 Sv to −1.2 Sv. Because of the vertical coupling between the upper and middle layers, closing the Mindoro-Sibutu pathway also weakens clockwise circulation in the middle layer (900–2150 m), but there is no significant change in the deep layer (below 2150 m). The Mindoro-Sibutu pathway is an important branch of the SCS throughflow into the Indonesian Seas. It is also the gateway for oceanic waves propagating clockwise around the Philippines Archipelago from the western Pacific Ocean into the eastern SCS, projecting El Niño-Southern Oscillation sea level signals to the SCS, impacting its interannual variations and multi-layer circulation. The results provide insights into the dynamics of how upstream and downstream passage throughflows are coupled to affect the general circulation in marginal seas.

The sea surface salinity (SSS) varies largely as a result of the evaporation–precipitation difference, indicating the source or sink of regional/global water vapor. This study identifies a relationship between the spring SSS in the tropical northwest Pacific (TNWP) and the summer rainfall of the East Asian monsoon region (EAMR) during 1980–2017. Analysis suggests that the SSS–rainfall link involves the coupled ocean–atmosphere–land processes with a multifacet evolution. In spring, evaporation and water vapor flux divergence were enhanced in some years over the TNWP where an anomalous atmospheric anticyclone was established and a high SSS was well observed. As a result, the convergence of water vapor flux and soil moisture over the EAMR was strengthened. This ocean-to-land water vapor transport pattern was sustained from spring to summer and played a leading role in the EAMR rainfall. Moreover, the change in local spring soil moisture helped to amplify the summer rainfall by modifying surface thermal conditions and precipitation systems over the EAMR. As the multifacet evolution is closely related to the large-scale ocean-to-land water vapor transport, it can be well represented by the spring SSS in the TNWP. A random forest regression algorithm was used to further evaluate the relative importance of spring SSS in predicting summer rainfall compared to other climate indices. As the SSS is now monitored routinely by satellite and the global Argo float array, it can serve as a good metric for measuring the water cycle and as a precursor for predicting the EAMR rainfall.

A novel predictive model was built for eddy propagation trajectory using the multiple linear regression method. This simple model relates various oceanic parameters to eddy propagation position changes in the northern South China Sea (NSCS). These oceanic parameters mainly represent the effects of β and mean flow advection on the eddy propagation. The performance of the proposed model has been examined in the NSCS based on five years of satellite altimeter data and demonstrates its significant forecasting skills over a 4-week forecast window compared to the traditional persistence method. It was also found that the model forecasting accuracy is sensitive to eddy polarity and the forecast season.

The “Panda”-type polarization-maintaining quartz optical fiber was respectively annealed at 25℃ and 90℃ after electron irradiation with energy of 160 keV and fluence of 5 × 1015 electrons/cm2. It is found that the attenuation coefficient shows an exponential decrease with increasing annealing duration, while the attenuation coefficient has sharper change and lower maximum value under higher annealing temperature. Based on the theory of defects generating and annihilating, an annealing model of the irradiated quartz fiber was established to describe the evolution of defects and attenuation coefficient during annealing. The proposed model can be used to calculate the annealing process of the irradiated fiber under different temperature.

Data from satellite altimetry and in situ observations together with the Hybrid Coordinate Ocean Model (HYCOM) reanalysis data were used to investigate the mechanism and formation of an anticyclonic eddy in the northeastern South China Sea (SCS). Analysis of water mass using cruise data indicated that the water captured in the eddy differs from those in the SCS, the Kuroshio intrusion, and the eddy-forming region. Data from sea surface height (SSH) and sea level anomaly (SLA) indicate that the eddy formed due both to the Kuroshio intrusion and the local circulation in the SCS. The Kuroshio intrusion is present at the start of the eddy growth (March 5–9) before Kuroshio leaps the Luzon Strait. The eddy then becomes larger and stronger in the absence of the Kuroshio intrusion. From the eddy budget of the HYCOM reanalysis data, the formation of the eddy goes in three steps. By the third step, the eddy had become affected by variations of local SCS circulation, which is more strongly than in the first step in which it is affected more by the Kuroshio intrusion. The variability of the temperature and salinity inside the eddy provide a support to this conclusion. The water in the SCS intruded into the eddy from the southeast, which decrease the salinity gradually in the southern part of the eddy during the growth period.

Storm surge inundation model based on FVCOM is developed to capture minor to significant flooding near the shallow coastal areas of Saco-Casco Bay, harbor entrance and river banks using NOAA's integrated Portland data of 1/3 arc-second MHW Digital Elevation Model. The study aims to develop a novel high-resolution framework to accurately predict the capability of the coastal inundation, the depth of inundation and its vulnerability to potential sea level rise due to winter storms (WS) in these Bays for ungauged areas to map the flood zones. The model runs (MNEC and MNAM) were driven by NECOFS/WRF and NOAA's NAM forcing respectively to analyse the five classic WS in 2014-2015. The study reveals that WS-III produces a maximum surge of ∼0.7m and WS-II cause a minimum surge of ∼0.3m. In all cases, southward wind-driven coastal current flowing across the Saco River mouth harbor entrance gets intensified but strength varies.