Remote Sensing Sea Surface Temperature Research Articles

Interannual Variations in the Summer Coastal Upwelling in the Northeastern South China Sea

This study scrutinizes interannual (2003–2023) variations in coastal upwelling along the Guangdong Province during summers (June–August) in the northeastern South China Sea (NESCS) by comprehensively applying the moderate-resolution imaging spectroradiometer (MODIS) remote sensing sea surface temperature (SST) and chlorophyll concentration (CHL) data and the model reanalysis product. The results show that SST and upwelling intensity in the sea area have significant (p < 0.05) rising trends in the last 21 years. The CHL shows an upward but insignificant trend, which is affected simultaneously by the rise in SST and the enhancement of upwelling. Further analysis reveals that the interannual variations in upwelling are robustly related to the wind fields’ variations in the coastal region. A clockwise/counter-clockwise anomaly in the wind field centered on the NESCS facilitates alongshore/onshore winds near the Guangdong coast, which can strengthen/weaken coastal upwelling. Based on the correlation between wind field variations and large-scale climate factors, long-term variations in the upwelling intensity can be primarily predicted by the Oceanic Niño Index.

Long-term warming and human-induced plankton shifts at a coastal Eastern Mediterranean site

Plankton are key ecological indicators for assessing the impacts of human-induced pressures like climate change and waste-water discharge. Here, 26 years (1988–2015) of biweekly in-situ chlorophyll-a concentration, mesozooplankton biomass and remotely-sensed sea surface temperature (SST) data are utilized to investigate long-term changes of plankton biomass and timing of growth (phenology) in relation to warming, in a coastal region of the Saronikos Gulf (Aegean Sea). A Waste-Water Treatment Plant (WWTP) was established in 1995, leading to decreased nutrient concentrations circa 2004. Overall, the results indicate an interplay between warming and changes in ecological status. During higher nutrient input (1989–2004), a temporal mismatch between zooplankton and phytoplankton, and a positive zooplankton growth—SST association, are evident. Conversely, in the warmer, less mesotrophic period 2005–2015, an earlier timing of zooplankton growth (related to copepod abundance) synchronizes with phytoplankton growth, including a secondary autumn growth period. Concurrently, an abrupt negative interannual relationship between SST and mesozooplankton, and a summer biomass decrease (linked with cladoceran abundance) are observed. This work provides evidence that current warming could alter plankton abundance and phenology in nearshore Eastern Mediterranean ecosystems, suggesting shifts in plankton community composition that could trigger potential cascading effects on higher trophic levels.

An ocean front dataset for the Mediterranean sea and southwest Indian ocean

Fronts are ubiquitous discrete features of the global ocean often associated with enhanced vertical velocities, in turn boosting primary production. Fronts thus form dynamical and ephemeral ecosystems where numerous species meet across all trophic levels. Fronts are also targeted by fisheries. Capturing ocean fronts and studying their long-term variability in relation with climate change is thus key for marine resource management and spatial planning. The Mediterranean Sea and the Southwest Indian Ocean are natural laboratories to study front-marine life interactions due to their energetic flow at sub-to-mesoscales, high biodiversity (including endemic and endangered species) and numerous conservation initiatives. Based on remotely-sensed Sea Surface Temperature and Height, we compute thermal fronts (2003–2020) and attracting Lagrangian coherent structures (1994–2020), in both regions over several decades. We advocate for the combined use of both thermal fronts and attracting Lagrangian coherent structures to study front-marine life interactions. The resulting front dataset differs from other alternatives by its high spatio-temporal resolution, long time coverage, and relevant thresholds defined for ecological provinces.

Estimating Three‐Dimensional Structures of Eddy in the South Indian Ocean From the Satellite Observations Based on the isQG Method

AbstractBy incorporating the high‐resolution satellite remote sensing sea surface temperature (SST) with low‐resolution sea level anomaly and sea surface salinity (SSS), this study explores the reconstructability of the three‐dimensional (3D) eddy structures via the “interior + surface quasigeostrophic” (isQG) method in the South Indian Ocean. We apply the incorporation of high‐resolution SST to improve the spatial resolution of the reconstruction. We also propose a correction scheme for density reconstruction within the mixed layer to offset the absence of mixed layer dynamics in the SQG framework. Comparison against the in situ observations demonstrates a satisfactory reconstructability for subsurface velocity and density anomalies. Statistically, the zonal velocity reconstructability outperforms its meridional counterpart and the corresponding velocity phase. The reconstructed shallow‐layer velocity exhibits a superior skill in eddy‐active regions, when compared with drogued drifter observations. Reconstructed subsurface velocities reproduce the spatial structures of eddy‐induced velocity anomaly along the GO‐SHIP observation transect, although present smaller magnitudes. Results demonstrate the potential applicability of the isQG method for reconstructing mesoscale eddies, particularly in the ocean at mid‐to‐high latitudes, where subsurface dynamics are strongly influenced by barotropic and the first baroclinic modes. With the upcoming high‐advanced satellite observations, the isQG framework is expected to achieve better subsurface estimations.

Cross-shelf transport off the northern Taiwan, East China Sea

Cross-shelf transport is an important material exchange process between the shelf seas and open seas. The distribution characteristics of phytoplankton, surface sediment particle size, minerals, etc., all indicate the possible existence of a cross-shelf transport conduit from the inner shelf to the outer shelf off northern Taiwan. This study confirmed cross-shelf transport off northern Taiwan based on remote sensing sea surface temperature (SST) data and heat flux data, which can be divided into two patterns: cold eddy and cold water tongue. Furthermore, combined with AVISO sea surface level data, CCMP wind field data, the dynamic formation factors of different morphological characteristics of cross-shelf transport are studied.Topographic changes mainly induce cross-shelf transport off northern Taiwan and occur at the curve of isobath to deep water. When there is a strong thermal front along the coast, cross-shelf transport is more likely to occur. Against the steady, strong northerly wind, the Zhe-Min coastal current's southward flow and Kuroshio's invasion strengthened the temperature front and facilitated cross-shelf transport. Typhoon strengthened cross-shelf transport over northern Taiwan after passing through the southern part of the study area. This research has important implications to find the channel and transporting pattern for material exchange between the East China Sea and the West Pacific, which will contribute to the study of ecological environmental protection and seabed muddy area formation.

Remote Sensing Analysis of Typhoon-Induced Storm Surges and Sea Surface Cooling in Chinese Coastal Waters

Inthis study, remote sensing measurements were utilized to examine the characteristics of storm surges and sea surface cooling in Chinese coastal waters caused by typhoons. Altimetric data from satellite altimeters were used to determine the magnitude, cross-shelf decaying scale, and propagating speed of storm surges from typhoons. The results were in agreement with estimates obtained from a theoretical model and tide gauge data, showing that the two storm surges propagated as continental shelf waves along the southeastern coast of China. The sea surface cooling, driven by Typhoons 1319Usagi and 1323Fitow, was analyzed using the remote sensing sea surface temperature product, named the global 1 km sea surface temperature (G1SST) dataset, revealing a considerable decrease in the temperature, with the largest decrease reaching 4.5 °C after the passage of 1319Usagi, in line with buoy estimates of 4.6 °C. It was found that 1323Fitow and 1324Danas jointly impacted the southeastern coast of China, resulting in a significant temperature drop of 4.0 °C. Our study shows that incorporating remotely sensed measurements into the study of oceanic responses to typhoons has significant benefits and complements the traditional tide gauge network and buoy data.

A Hybrid ENSO Prediction System Based on the FIO−CPS and XGBoost Algorithm

Accurate prediction of the El Niño–Southern Oscillation (ENSO) is crucial for climate change research and disaster prevention and mitigation. In recent decades, the prediction skill for ENSO has improved significantly; however, accurate forecasting at a lead time of more than six months remains challenging. By using a machine learning method called eXtreme Gradient Boosting (XGBoost), we corrected the ENSO predicted results from the First Institute of Oceanography Climate Prediction System version 2.0 (FIO−CPS v2.0) based on the satellite remote sensing sea surface temperature data, and then developed a dynamic and statistical hybrid prediction model, named FIO−CPS−HY. The latest 15 years (2007–2021) of independent testing results showed that the average anomaly correlation coefficient (ACC) and root mean square error (RMSE) of the Niño3.4 index from FIO−CPS v2.0 to FIO−CPS−HY for 7− to 13−month lead times could be increased by 57.80% (from 0.40 to 0.63) and reduced by 24.79% (from 0.86 °C to 0.65 °C), respectively. The real−time predictions from FIO−CPS−HY indicated that the sea surface state of the Niño3.4 area would likely be in neutral conditions in 2023. Although FIO−CPS−HY still has some biases in real−time prediction, this study provides possible ideas and methods to enhance short−term climate prediction ability and shows the potential of integration between machine learning and numerical models in climate research and applications.

Spatial and seasonal variability of horizontal temperature fronts in the Mozambique Channel for both epipelagic and mesopelagic realms

IntroductionOcean fronts are moving ephemeral biological hotspots forming at the interface of cooler and warmer waters. In the open ocean, this is where marine organisms, ranging from plankton to mesopelagic fish up to megafauna, gather and where most fishing activities concentrate. Fronts are critical ecosystems so that understanding their spatio-temporal variability is essential not only for conservation goals but also to ensure sustainable fisheries. The Mozambique Channel (MC) is an ideal laboratory to study ocean front variability due to its energetic flow at sub-to-mesoscales, its high biodiversity and the currently debated conservation initiatives. Meanwhile, fronts detection relying solely on remotely-sensed Sea Surface Temperature (SST) cannot access aspects of the subsurface frontal activity that may be relevant for understanding ecosystem dynamics.MethodIn this study, we used the Belkin and O’Reilly Algorithm on remotely-sensed SST and hindcasts of a high-resolution nested ocean model to investigate the spatial and seasonal variability of temperature fronts at different depths in the MC.ResultsWe find that the seasonally varying spatial patterns of frontal activity can be interpreted as resulting from main features of the mean circulation in the MC region. In particular, horizontally, temperature fronts are intense and frequent along continental shelves, in islands’ wakes, at the edge of eddies, and in the pathways of both North-East Madagascar Current (NEMC) and South-East Madagascar Current (SEMC). In austral summer, thermal fronts in the MC are mainly associated with the Angoche upwelling and seasonal variability of the Mozambique current. In austral winter, thermal fronts in the MC are more intense when the NEMC and the Seychelles-Chagos and South Madagascar upwelling cells intensify. Vertically, the intensity of temperature fronts peaks in the vicinity of the mean thermocline.DiscussionConsidering the marked seasonality of frontal activity evidenced here and the dynamical connections of the MC circulation with equatorial variability, our study calls for addressing longer timescales of variability to investigate how ocean ecosystem/front interactions will evolve with climate change.

Alteration of alpha and beta diversity in nekton community by extreme marine heatwave events: An example from the East China Sea

In the year of 2016 to 2017, record-breaking marine heatwave (MHW) events occurred along the Chinese coast, exerting severe impacts on coastal fishes and fisheries. However, the response of the nekton community to MHW events still remains poorly understanding. Thus, to investigate the influences of the MHW events on species composition dynamics, this study conducted a survey on nekton communities in the northern East China Sea in the summers during 2014 to 2017. The recently-developed “heatwaveR” package was adopted to describe the variation characteristics of heatwaves within the study area, based on high-resolution remote-sensing sea surface temperature products. We also compared variations in the community structures of different biological groups before (2014–2015) and during the occurrence of the MHW events (2016–2017). During the MHW events, temperature increased by approximately 2.3°C in both 2016 and 2017. Compared with those before the MHW events, the biomass and dominance of several important crustaceans decreased, and the biomass of warm water affinity species increased significantly, while their richness and diversity decreased; the biomass of warm temperature affinity species declined significantly, while their diversity increased slightly. These results show the difference in the response rates of species with different thermal preferences and different species compositions to the extreme climate change. Beta diversity analysis revealed that the inter-group variation before and during the MHW event exceeded the intra-group variation, proving that MHWs changed the community structure to a certain extent. PERMANOVA test showed that the species compositions of planktivorous fish (FG1) and small-omnivorous fish (FG2) in the feeding-functional groups were significantly different before and during the MHW event, which may be attributed to the impact of MHWs on oligotrophic fishes through thermal preference and the trophic cascade effect. There was no significant change in the species compositions of other functional groups, indicating that medium-trophic and eutrophic fishes possessed certain adaptability to MHWs. Regarding fisheries management under extreme warming events, it would be advisable to diagnose temperature anomalies in the early stage, monitor changes in species abundance in the early life cycle, and then rapidly develop suitable fishing strategies.

Simulated response of St. Joseph Bay, Florida, seagrass meadows and their belowground carbon to anthropogenic and climate impacts

Seagrass meadows are degraded globally and continue to decline in areal extent due to human pressures and climate change. This study used the bio-optical model GrassLight to explore the impact of climate change and anthropogenic stressors on seagrass extent, leaf area index (LAI) and belowground organic carbon (BGC) in St. Joseph Bay, Florida, using water quality data and remotely-sensed sea surface temperature (SST) from 2002 to 2020. Model predictions were compared with satellite-derived measurements of seagrass extent and shoot density from the Landsat images for the same period. The GrassLight-derived area of potential seagrass habitat ranged from 36.2 km2 to 39.2 km2, averaging 38.0 ± 0.8 km2 compared to an observed seagrass extent of 23.0 ± 3.0 km2 derived from Landsat (range = 17.9–27.4 km2). GrassLight predicted a mean seagrass LAI of 2.7 m2 leaf m−2 seabed, compared to a mean LAI of 1.9 m2 m−2 estimated from Landsat, indicating that seagrass density in St. Joseph Bay may have been below its light-limited ecological potential. Climate and anthropogenic change simulations using GrassLight predicted the impact of changes in temperature, pH, chlorophyll a, chromophoric dissolved organic matter and turbidity on seagrass meadows. Simulations predicted a 2–8% decline in seagrass extent with rising temperatures that was offset by a 3–11% expansion in seagrass extent in response to ocean acidification when compared to present conditions. Simulations of water quality impacts showed that a doubling of turbidity would reduce seagrass extent by 18% and total leaf area by 21%. Combining climate and water quality scenarios showed that ocean acidification may increase seagrass productivity to offset the negative effects of both thermal stress and declining water quality on the seagrasses growing in St. Joseph Bay. This research highlights the importance of considering multiple limiting factors in understanding the effects of environmental change on seagrass ecosystems.

On the Reconstruction of Missing Sea Surface Temperature Data from Himawari-8 in Adjacent Waters of Taiwan Using DINEOF Conducted with 25-h Data

Satellite remote sensing sea surface temperature (SST) data are lost due to cloud cover. Missing data often cause inconvenience in subsequent applications and thus need to be reconstructed. In this study, the Data Interpolating Empirical Orthogonal Function (DINEOF) method was used to reconstruct the hourly SST data missing from the Himawari-8 satellite in the waters near Taiwan. The SST characteristics in the waters around Taiwan are quite complex, with high SST at Kuroshio in the east of Taiwan and great variation in the SST west of Taiwan due to the influence of tides. Therefore, the analysis with DINEOF was conducted using 25-h data to match the tidal cycle. The influence of SST characteristics on the accuracy of SST reconstruction is also discussed. The results show that in the western sea area where the variation of SST is large, the average root-mean-square error of SST between the original SST and the reconstructed SST is the lowest and the average coefficient of determination is the highest. The accuracy of the reconstructed SST is positively correlated with the SST variation. Furthermore, the statistical results also show that the DINEOF method can effectively reconstruct the SST regardless of the missing data rate.

Effects of Buoyancy Flux on Upper‐Ocean Turbulent Mixing Generated by Non‐Breaking Surface Waves Observed in the South China Sea

AbstractThe surface waves are the most energetic motions, which have great contribution to the turbulent mixing in the upper ocean. In this study, a novel turbulent mixing scheme is proposed in terms of the non‐breaking wave velocity shear module with the buoyancy flux. In the scheme, the mixing coefficients can be calculated empirically from the significant wave height, the wave number, the wave frequency, the buoyancy frequency, and the turbulence Prandtl number. The buoyancy fluxes, as well as the non‐breaking wave velocity shear production, are important for the upper‐ocean turbulent mixing, and make the calculated turbulence dissipation rate closer to in situ observations, which are provided by the “Responses of Marine Hazards to Climate Change in the Western Pacific (ROSE)” Project. The effects of the buoyancy flux on the turbulent mixing are examined based on three numerical experiments using the MASNUM ocean model. In the experiments, the topography, the lateral boundaries, initialization conditions, and the surface forcing fluxes are taken from the GEBCO, HYCOM/NCODA, and ERA5 data, respectively. Comparing to the AVHRR remote sensing sea surface temperature (SST) products and in situ observations, the simulated results with the non‐breaking wave‐generated turbulent mixing gain significant improvement in the SST, upper‐ocean temperature structure, and the mixed layer compared with the classic Mellor‐Yamada scheme. The results show that the buoyancy flux is able to suppress the enhanced non‐breaking wave‐generated turbulent mixing, so that the improved model simulates the observations better than that without the buoyancy effects.

Spatiotemporal distribution of Decapterus maruadsi in spring and autumn in response to environmental variation in the northern South China Sea

Understanding relationships between the spatiotemporal variability of fishery resources and marine environmental variables forms the basis of effective development and utilization of the northern South China Sea (NSCS) fishery resources. Decapterus maruadsi is one important pelagic economic fish which inhabits the coastal warm waters of the NSCS. We examine the spatiotemporal distribution and central of gravity (CoG) of D. maruadsi in the NSCS in spring and autumn from 2015 to 2017 with generalized additive models (GAMs), using fishing trawl data, and remote sensed sea surface temperature (SST), sea surface salinity (SSS), sea surface wind (SSW), chlorophyll a concentration (Chl-a), and the sea level anomaly (SLA) data. During spring D. maruadsi occurs mainly in a small area from 110.5–111 °E and 18.25–19.25 °N, at about 72 m, SST 24.4–26.8 °C, SSS 32.9–34.0 PSU, and SLA -0.04 to 0.04 m. During autumn these ranges shift to 112.25–114 °E and 20.25–21.25 °N, 62 m, 28.5–28.8 °C, and 33.4–34.1 PSU, respectively (D. maruadsi was insensitive to SLA during autumn). Accordingly, we deem the most important variables affecting the distribution of this species to be water depth and SSS in spring and SSS in autumn. CPUE of D. maruadsi was high in autumn and low in spring, with the CoG shifting from spring to autumn northwards by 0.4 °N and eastwards by 0.7 °E. This shift is likely influenced by this species’ life habits. Higher D. maruadsi CPUE in 2016 could partly be associated with La Nina and Typhoon climate anomalies. Our results provide a basis for scientific assessment and effective conservation of NSCS fishery resources.

Assimilating In Situ and Remote Sensing Observations in a Highly Variable Estuary–Shelf Model

AbstractTo improve the forecasting performance in dynamically active coastal waters forced by winds, tides, and river discharges in a coupled estuary–shelf model off Hong Kong, a multivariable data assimilation (DA) system using the ensemble optimal interpolation method has been developed and implemented. The system assimilates the conductivity–temperature–depth (CTD) profilers, time series buoy measurement, and remote sensing sea surface temperature (SST) data into a high-resolution estuary–shelf ocean model around Hong Kong. We found that the time window selection associated with the local dynamics and the number of observation samples are two key factors in improving assimilation in the unique estuary–shelf system. DA with a varied assimilation time window that is based on the intratidal variation in the local dynamics can reduce the errors in the estimation of the innovation vector caused by the model–observation mismatch at the analysis time and improve simulation greatly in both the estuary and coastal regions. Statistically, the overall root-mean-square error (RMSE) between the DA forecasts and not-yet-assimilated observations for temperature and salinity has been reduced by 33.0% and 31.9% in the experiment period, respectively. By assimilating higher-resolution remote sensing SST data instead of lower-resolution satellite SST, the RMSE of SST is improved by ~18%. Besides, by assimilating real-time buoy mooring data, the model bias can be continuously corrected both around the buoy location and beyond. The assimilation of the combined buoy, CTD, and SST data can provide an overall improvement of the simulated three-dimensional solution. A dynamics-oriented assimilation scheme is essential for the improvement of model forecasting in the estuary–shelf system under multiple forcings.

Scrutinizing Relationships between Submarine Groundwater Discharge and Upstream Areas Using Thermal Remote Sensing: A Case Study in the Northern Persian Gulf

Nutrient input through submarine groundwater discharge (SGD) often plays a significant role in primary productivity and nutrient cycling in the coastal areas. Understanding relationships between SGD and topo-hydrological and geo-environmental characteristics of upstream zones is essential for sustainable development in these areas. However, these important relationships have not yet been completely explored using data-mining approaches, especially in arid and semi-arid coastal lands. Here, Landsat 8 thermal sensor data were used to identify potential sites of SGD at a regional scale. Relationships between the remotely-sensed sea surface temperature (SST) patterns and geo-environmental variables of upland watersheds were analyzed using logistic regression model for the first time. The accuracy of the predictions was evaluated using the area under the receiver operating characteristic curve (AUC-ROC) metric. A highly accurate model, with the AUC-ROC of 96.6%, was generated. Moreover, the results indicated that the percentage of karstic lithological formation and topographic wetness index were key variables influencing SGD phenomenon and spatial distribution in the northern coastal areas of the Persian Gulf. The adopted methodology and applied metrics can be transferred to other coastal regions as a rapid assessment procedure for SGD site detection. Moreover, the results can help planners and decision-makers to develop efficient environmental management strategies and the design of comprehensive sustainable development policies.

Using satellite remote sensing to improve the prediction of scallop condition in their natural environment: Case study for Georges Bank, Canada

The continuous, synoptical and high spatio-temporal resolution of thermal and visible satellite observations constitute an asset when characterizing and monitoring biogeochemical cycles in the oceans. In particular, they provide a unique insight into the hydrodynamics of the surface ocean and phytoplankton phenology. This information can be combined with in-situ observations of higher trophic levels to understand the functioning of the marine ecosystem, with potential use for fisheries and aquaculture. In the Gulf of Maine, off the eastern seaboard of North America, Georges Bank is one of the world's most productive natural sea scallop (Placopecten magellanicus) fisheries, which sustains economically valuable fisheries in Canada and the US. In Canada, the relationship between the scallop meat weight and its shell height (known as scallop condition) is used to obtain biomass estimates for stock assessment and thereby influences the fishing quotas. On Georges Bank, for a 100 mm shell height scallop, scallop condition has varied significantly interannually between 10.2 g and 19.5 g. Establishing a relationship between environmental factors and scallop condition would improve the forecasting of scallop biomass and reduce the uncertainty when determining the total allowable catch for the subsequent fishing season. In this study, satellite remote-sensed sea-surface temperature (SST) and chlorophyll-a concentration (Chla) coupled with in-situ measurements of scallop condition (SC) on Georges Bank were used to assess the relationship between SC and satellite-derived environmental conditions between 1985 and 2019 for SST and between 1998 and 2019 for Chla. The inter-annual variation of SC in May was found to be positively correlated (p-value <0.001) with the variation in SST in winter-spring months of the current and previous year of the SC survey. An empirical linear model for the estimation of SC was developed and validated using two independent datasets of satellite SST (r2 = 0.64, MAPD = 7%). Another model using cumulative SST in the previous year only was also provided (r2 = 0.58, MAPD = 7.7%), which could serve as an alternative choice when the SST products in the current year are not yet available for use. There was a weak relationship observed between SC and Chla; this is likely due to the influence of water-column vertical mixing on transport of phytoplankton to the benthic zone where the sea scallop resides. Our study indicates that a cost-effective satellite-derived SST product can be used to improve predictions of SC and provide useful information and decision support tools for managing scallop stocks.

China Ocean ReAnalysis (CORA) version 1.0 products and validation for 2009–18: 2009–18年西北太平洋区域海洋再分析CORA1.0产品研制及检验

China Ocean ReAnalysis (CORA) version 1.0 products for the period 2009–18 have been developed and validated. The model configuration and assimilation algorithm have both been updated compared to those of the 51-year (1958–2008) products. The assimilated observations include temperature and salinity field data, satellite remote sensing sea surface temperature, and merged sea surface height (SSH) anomaly data. The validation includes the following three aspects: (1) Temperature, salinity, and SSH anomaly root-mean-square errors (RMSEs) are computed as a primary evaluation of the reanalysis quality. The 0–2000 m domain-averaged RMSEs of temperature and salinity are 0.61°C and 0.08 psu, respectively. The SSH anomaly RMSE is less than 0.2 m in most regions. (2) The 35°N temperature section is used to evaluate the ability to reproduce the thermocline, mixing layer, and Yellow Sea cold water mass. In summer, the thermocline is reinforced, with the gradient changing from 3°C in May to 10°C in August. The mixing-layer depth reproduced by CORA is consistent with that computed from the observed climatology. The Yellow Sea cold water mass forms at a depth of 50 m. (3) The reanalysis current is examined against the tracks of some drifting buoys. The results show that the reanalysis current can capture the mesoscale eddies near the Kuroshio, which are similar to those described by the drifting buoys. Overall, the 2009–18 CORA reanalysis products are capable of reproducing major oceanic phenomena and processes in the coastal waters of China and adjacent seas.摘要在51年 (1958–2008) 西北太平洋区域海洋再分析CORA1.0产品的基础上, 改进了模式配置和同化方法, 研制了2009-18年的CORA产品并对其进行以下检验: (1) 温盐和海表高度异常均方根误差分布检验; (2) 35°N处温度断面分布检验; (3) 再分析流场和表漂浮标轨迹对比检验.结果显示, 2009–18年的CORA产品可以再现海洋要素长时间序列,时空多尺度的变化特征, 为研究特征海洋现象和过程提供背景信息.

Effect of topography on the cold water region in the east entrance area of Qiongzhou Strait

A cold water region will occur in the east entrance area of Qiongzhou Strait when upwelling develops off the northeast coast of Hainan Island. The effect of topography on this cold water region was investigated by combining satellite observations and numerical simulations. Multi-source high-resolution remote-sensed sea surface temperature images revealed that the western periphery of the cold water region frequently occurred at a quasi-fixed location with similar jagged structure. Compared with observations, the numerical model employed in this study could satisfactorily simulate the intense tidal currents in the strait, and reasonably reproduce the jagged western periphery of the cold water region. Under strong westward tidal flow, the cold upwelling water intruded deeply into the interior strait, whereas under sustained eastward tidal currents, much stronger tidal currents occurred where there were deeper waters connecting the inner strait, therefore the cold upwelling water faded towards east faster and formed the concave parts (looking in east-to-west direction) of the western periphery of the cold water region; conversely, convex parts would develop over the adjacent shallower shoals. The eastward movement of the cold water was dominated by topography-modified tidal currents, and only after sustained eastward tidal currents (usually in the second half or near the end of the eastward tidal current phase), the western periphery of the cold water region would occur at a quasi-fixed location with similar jagged shape. Moreover, the development of the upwelling off the northeast coast of Hainan Island, which was the precondition of the cold water region, was found to be mainly driven by sustained SE ~ S winds.

On the cross-shelf exchange driven by frontal eddies along a western boundary current during austral winter 2007

Western boundary currents are characterised by high mesoscale eddy activity including that of cyclonic frontal eddies (CFEs). These form frequently adjacent to the shelf-break, export coastal water and affect biological productivity. Here, we study the physical properties of eddies identified within the intensification zone of the East Australian Current (EAC) through the analysis of remotely sensed data, the application of an ocean circulation model and the evaluation of Lagrangian simulations during austral winter 2007. We examine the spatial and temporal evolution of identified eddies, investigate their formation mechanism, and quantify the contribution made to cross-shelf exchanges. The mesoscale eddies are tracked from generation to decay using an eddy detection and tracking method. In this case study, we identify two CFEs referred to as C1 and C2 with lifetimes of 11 and 38 days and radii of 45 and 70 km, respectively, and one anticyclonic eddy (ACE) with a lifetime of 62 days and a radius of 60 km. Both CFEs interact with the ACE leading to quasi-stationary dipole-eddies located in the vicinity of the shelf. This is the first time dipole-eddies are reported for the intensification zone of the EAC. The location of CFEs characterised by negative sea surface height anomaly (SSHA) and clockwise rotation coincides with remotely-sensed sea surface temperature (SST) and chlorophyll-a (Chl-a) anomalies. CFEs C1 and C2 appear to contribute in different ways to the cross-shelf transport along the shelf-break. CFE C1 drives a stronger onshore transport, while CFE C2 appears to enhance the offshore transport. The estimated export of shelf water associated with CFE C2 is estimated with about 1.23 Sv (~106 km3 day−1). It renews the regional shelf water in about 7 days. The lifetime of CFE C2 is about 38 days, thus the eddy had the potential to flush the shelf at least five times. The CFEs intensify the cross-shelf exchange that is due to the wind-driven cyclonic circulation of the Fraser Gyre. This seasonally occurring gyre dominates the local shelf during austral autumn and winter. The results from this study demonstrate the importance of CFEs in exporting cooler and Chl-a enriched shelf water into the warmer and oligotrophic waters of the southward-flowing EAC.

SST Anomalies in the Mozambique Channel Using Remote Sensing and Numerical Modeling Data

Based on both satellite remote sensing sea surface temperature (SST) data and numerical model results, SST warming differences in the Mozambique Channel (MC) west of the Madagascar Island (MI) were found with respect to the SST east of the MI along the same latitude. The mean SST west of the MI is up to about 3.0 °C warmer than that east of the MI. The SST differences exist all year round and the maximum value appears in October. The area of the highest SST is located in the northern part of the MC. Potential factors causing the SST anomalies could be sea surface wind, heat flux and oceanic flow advection. The presence of the MI results in weakening wind in the MC and in turn causes weakening of the mixing in the upper oceans, thus the surface mixed layer depth becomes shallower. There is more precipitation on the east of the MI than that inside the MC because of the orographic effects. Different precipitation patterns and types of clouds result in different solar radiant heat fluxes across both sides of the MI. Warm water advected from the equatorial area also contribute to the SST warm anomalies.