Variability In Coastal Waters Research Articles

High-resolution study of the air-sea CO2 flux and net community oxygen production in the Ligurian Sea by a fleet of gliders

Intense glider monitoring was conducted in the Ligurian Sea for five months to capture the Net Community Production (NCP) variability in one of the most dynamic and productive regions of the Mediterranean Sea. Using the SeaExplorer glider technology, we were able to observe continuously from January to the end of May 2018 the physical and biogeochemical variables during the last period of intense convection observed in this region. High-frequency measurements from these gliders provided valuable information for determining dissolved O2 (DO) concentrations between coastal and open sea waters. Our DO balance approach provided an estimate of NCP fluxes complemented by the prediction of air-sea CO2 fluxes based on a neural network adapted to the Mediterranean Sea (CANYON-MED). Based on our NCP calculation method, our results show that the air-sea O2 flux and DO inventory have contributed largely to the NCP variability. The NCP values also suggest that heterotrophic conditions were predominant in winter and became autotrophic in spring, with strong variability in coastal waters due to the occurrence of sub-mesoscale structures. Finally, CO2 fluxes at the air-sea interface reveal that during the convection period, the central zone of the Ligurian Sea acted as a CO2 sink from January to March with little impact on NCP fluxes counterbalanced by a thermal effect of seawater.

Sensitivity simulation of sea surface temperature variability in coastal waters off East Africa in relation to the Indian Ocean Dipole

East African coastal waters in the tropical western Indian Ocean experience strong seasonality which varies yearly, leading to the establishment of a prominent interannual Indian Ocean Dipole (IOD). This has a significant influence on regional and global socio-economic, climatic and human development. Sea surface temperature (SST) variability in these waters and its association with ocean–atmosphere feedbacks and internal subsurface ocean dynamics in relation to the IOD is the subject of this study. The research used reference simulation accompanied with sensitivity simulations with forcings from higher frequency variabilities against climatological signals of ocean–atmosphere or internal subsurface ocean dynamics from 1980 to 2007. Wind forcing with higher-frequency variabilities was applied in all simulations. Cooling and warming during pure and positive IOD events leading El Niño events in the region is caused by a combination of both surface heat fluxes associated with ocean–atmosphere feedbacks, and internal subsurface ocean dynamics, from July and peaking in August and October, respectively. Such processes also dominate the warming (cooling) in the region during pure El Niño (La Niña) events from July to December (July to October) where the SST patterns extend southwards. The warmest (coolest) SST anomalies during positive (negative) IOD events co-occurring with El Niño (La Niña) events stay longer than other events, being characterised by bimodal peaking in August and December. Such SST patterns are significantly forced with ocean–atmosphere feedbacks that might be associated with Walker circulation driving links between the Indian and Pacific oceans; however, the peaking in August might be enhanced by small ocean dynamics off the Somali coast, probably owing to the existing upwelling systems during these conditions.

A baseline assessment of coastal pH variability in a temperate South African embayment: implications for biological ocean acidification research

Compared with the open ocean, knowledge of pH variability in coastal waters is rudimentary, especially in Africa. This is concerning as quantifying local pH conditions is critical when assessing the response of coastal species to future ocean acidification scenarios. The objective of this study was to capture some of the variability in pH at scales and sites relevant to coastal marine organisms in a South African temperate embayment (Algoa Bay, Indian Ocean). We used a sampling approach that captured spatial (at a resolution of ∼10 km), monthly and diel (24-hour) variability in pH and associated physical and biological parameters at offshore and shallow inshore sites in Algoa Bay. We found that pH and associated parameters (temperature, calculated pCO2, chlorophyll a) varied over space and time in Algoa Bay. The range in pH was 0.30 units at offshore sites and 0.46 at inshore sites, and the average pH was 8.10 (SD 0.06) and 8.10 (SD 0.13) at these sites, respectively, which is typical for coastal environments. Our results showed that both biological factors (at the offshore sites) and salinity (at the inshore sites) may influence temporal and spatial variability in pH. We also identified a shallow inshore site with high levels of macroalgal growth that had consistently higher average daytime pH levels (8.33 [SD 0.07]), which may serve as an ocean acidification refuge for coastal marine species. This is the first comprehensive pH-monitoring study to be implemented in a nearshore coastal area in Africa and provides recommendations for monitoring in other understudied regions.

Thermal tolerance, safety margins and vulnerability of coastal species: Projected impact of climate change induced cold water variability in a temperate African region

Anthropogenic induced climate change is predicted to increase the thermal variability in coastal waters, which can have strong physiological effects on individuals and populations of marine ectotherms. The magnitude and direction of these thermal effects varies depending on species, life stage, biogeography, habitat and season. This study aimed to compare the thermal tolerance of a range of juvenile fish and adult macro-invertebrates from intertidal and estuarine habitats in a warm-temperate, thermally variable region on the south-east coast of South Africa. Seasonal variability in thermal tolerance was compared between species, taxonomic groups, biogeographical distribution and habitat affinity and related to existing and projected water temperature data to gauge the local vulnerability of each species. Critical thermal maximum (CTmax), critical thermal minimum (CTmin), thermal breadths and scopes, and the thermal safety margins of each species were quantified. The greatest differences in thermal tolerance patterns were based on taxonomy, with macro-invertebrates having broader thermal tolerance compared to fish, with the exception of the Cape sea urchin, in both summer and winter. Relatively narrow lower breadths in tolerance and safety margin values for transient juvenile sub-tropical and temperate fish species from the intertidal rocky low-shore habitat were observed in both summer and winter. This indicates that these fish species and the Cape sea urchin may be more vulnerable to projected increases in cold temperature (upwelling in summer) than warm temperature variability in this warm-temperate region if they are unable to seek thermal habitat refuge.

Correcting in situ chlorophyll fluorescence time-series observations for nonphotochemical quenching and tidal variability reveals nonconservative phytoplankton variability in coastal waters.

Chlorophyll fluorometry is one of the most commonly implemented approaches for estimating phytoplankton biomass in situ, despite documented sources of natural variability and instrumental uncertainty in the relationship between in vivo fluorescence and chlorophyll concentration. A number of strategies are employed to minimize errors and quantify natural variability in this relationship in the open ocean. However, the assumptions underlying these approaches are unsupported in coastal waters due to the short temporal and small spatial scales of variability, as well as the optical complexity. The largest source of variability in the in situ chlorophyll fluorometric signal is nonphotochemical quenching (NPQ). Typically, unquenched nighttime observations are interpolated over the quenched daytime interval, but this assumes a spatial homogeneity not found in tidally impacted coastal waters. Here, we present a model that provides a tidally resolved correction for NPQ in moored chlorophyll fluorescence measurements. The output of the model is a time series of unquenched chlorophyll fluorescence in tidal endmembers (high and low tide extremes), and thus a time series of phytoplankton biomass growth and loss in these endmember populations. Comparison between modeled and measured unquenched time series yields quantification of nonconservative variations in phytoplankton biomass. Tidally modeled interpolation between these endmember time series yields a highly resolved time series of unquenched daytime chlorophyll fluorescence values at the location of the moored sensor. Such data sets provide a critical opportunity for validating the satellite remotely sensed ocean color chlorophyll concentration data product in coastal waters.

Atmospheric Corrections and Multi-Conditional Algorithm for Multi-Sensor Remote Sensing of Suspended Particulate Matter in Low-to-High Turbidity Levels Coastal Waters

The accurate measurement of suspended particulate matter (SPM) concentrations in coastal waters is of crucial importance for ecosystem studies, sediment transport monitoring, and assessment of anthropogenic impacts in the coastal ocean. Ocean color remote sensing is an efficient tool to monitor SPM spatio-temporal variability in coastal waters. However, near-shore satellite images are complex to correct for atmospheric effects due to the proximity of land and to the high level of reflectance caused by high SPM concentrations in the visible and near-infrared spectral regions. The water reflectance signal (ρw) tends to saturate at short visible wavelengths when the SPM concentration increases. Using a comprehensive dataset of high-resolution satellite imagery and in situ SPM and water reflectance data, this study presents (i) an assessment of existing atmospheric correction (AC) algorithms developed for turbid coastal waters; and (ii) a switching method that automatically selects the most sensitive SPM vs. ρw relationship, to avoid saturation effects when computing the SPM concentration. The approach is applied to satellite data acquired by three medium-high spatial resolution sensors (Landsat-8/Operational Land Imager, National Polar-Orbiting Partnership/Visible Infrared Imaging Radiometer Suite and Aqua/Moderate Resolution Imaging Spectrometer) to map the SPM concentration in some of the most turbid areas of the European coastal ocean, namely the Gironde and Loire estuaries as well as Bourgneuf Bay on the French Atlantic coast. For all three sensors, AC methods based on the use of short-wave infrared (SWIR) spectral bands were tested, and the consistency of the retrieved water reflectance was examined along transects from low- to high-turbidity waters. For OLI data, we also compared a SWIR-based AC (ACOLITE) with a method based on multi-temporal analyses of atmospheric constituents (MACCS). For the selected scenes, the ACOLITE-MACCS difference was lower than 7%. Despite some inaccuracies in ρw retrieval, we demonstrate that the SPM concentration can be reliably estimated using OLI, MODIS and VIIRS, regardless of their differences in spatial and spectral resolutions. Match-ups between the OLI-derived SPM concentration and autonomous field measurements from the Loire and Gironde estuaries’ monitoring networks provided satisfactory results. The multi-sensor approach together with the multi-conditional algorithm presented here can be applied to the latest generation of ocean color sensors (namely Sentinel2/MSI and Sentinel3/OLCI) to study SPM dynamics in the coastal ocean at higher spatial and temporal resolutions.

Sea surface carbon dioxide at the Georgia time series site (2006–2007): Air–sea flux and controlling processes

Carbon dioxide partial pressure (pCO2) in surface seawater was continuously recorded every three hours from 18 July 2006 through 31 October 2007 using a moored autonomous pCO2 (MAPCO2) system deployed on the Gray’s Reef buoy off the coast of Georgia, USA. Surface water pCO2 (average 373±52μatm) showed a clear seasonal pattern, undersaturated with respect to the atmosphere in cold months and generally oversaturated in warm months. High temporal resolution observations revealed important events not captured in previous ship-based observations, such as sporadically occurring biological CO2 uptake during April–June 2007. In addition to a qualitative analysis of the primary drivers of pCO2 variability based on property regressions, we quantified contributions of temperature, air–sea exchange, mixing, and biological processes to monthly pCO2 variations using a 1-D mass budget model. Although temperature played a dominant role in the annual cycle of pCO2, river inputs especially in the wet season, biological respiration in peak summer, and biological production during April–June 2007 also substantially influenced seawater pCO2. Furthermore, sea surface pCO2 was higher in September–October 2007 than in September–October 2006, associated with increased river inputs in fall 2007. On an annual basis this site was a moderate atmospheric CO2 sink, and was autotrophic as revealed by monthly mean net community production (NCP) in the mixed layer. If the sporadic short productive events during April–May 2007 were missed by the sampling schedule, one would conclude erroneously that the site is heterotrophic. While previous ship-based pCO2 data collected around this buoy site agreed with the buoy CO2 data on seasonal scales, high resolution buoy observations revealed that the cruise-based surveys undersampled temporal variability in coastal waters, which could greatly bias the estimates of air–sea CO2 fluxes or annual NCP, and even produce contradictory results.

Trace metal variability in coastal waters of San Jorge Bay, Antofagasta, Chile: An environmental evaluation and statistical approach to propose local background levels

Between 2008 and 2011, twelve metals from 384 coastal waters samples from San Jorge Bay (Antofagasta, northern Chile) were collected and analyzed. The goal was to evaluate the quality of the bay's water bodies according to the current Chilean Quality Guideline and to establish background levels for these metals.The result suggests that the coastal waters of San Jorge Bay are of very good quality suitable for recreational activities involving human body contact. The natural background thresholds established for this bay were significantly lower than primary and secondary water quality guidelines. The distribution of Cu, Zn and Pb, along the bay's coastline provides evidence of the effects of industrial activity. Both situations suggest that the threshold indicated in the environmental guidelines of the Chilean legislation may be overestimated and do not represent pollution-free environments.

Large and local-scale influences on physical and chemical characteristics of coastal waters of Western Europe during winter

There is now a strong scientific consensus that coastal marine systems of Western Europe are highly sensitive to the combined effects of natural climate variability and anthropogenic climate change. However, it still remains challenging to assess the spatial and temporal scales at which climate influence operates. While large-scale hydro-climatic indices, such as the North Atlantic Oscillation (NAO) or the East Atlantic Pattern (EAP) and the weather regimes such as the Atlantic Ridge (AR), are known to be relevant predictors of physical processes, changes in coastal waters can also be related to local hydro-meteorological and geochemical forcing. Here, we study the temporal variability of physical and chemical characteristics of coastal waters located at about 48°N over the period 1998–2013 using (1) sea surface temperature, (2) sea surface salinity and (3) nutrient concentration observations for two coastal sites located at the outlet of the Bay of Brest and off Roscoff, (4) river discharges of the major tributaries close to these two sites and (5) regional and local precipitation data over the region of interest. Focusing on the winter months, we characterize the physical and chemical variability of these coastal waters and document changes in both precipitation and river runoffs. Our study reveals that variability in coastal waters is connected to the large-scale North Atlantic atmospheric circulation but is also partly explained by local river influences. Indeed, while the NAO is strongly related to changes in sea surface temperature at the Brest and Roscoff sites, the EAP and the AR have a major influence on precipitations, which in turn modulate river discharges that impact sea surface salinity at the scale of the two coastal stations.

Coupled 1D–3D hydrodynamic modelling, with application to the Pearl River Delta

Within the hydrodynamic modelling community, it is common practice to apply different modelling systems for coastal waters and river systems. Whereas for coastal waters 3D finite difference or finite element grids are commonly used, river systems are generally modelled using 1D networks. Each of these systems is tailored towards specific applications. Three-dimensional coastal water models are designed to model the horizontal and vertical variability in coastal waters and are less well suited for representing the complex geometry and cross-sectional areas of river networks. On the other hand, 1D river network models are designed to accurately represent complex river network geometries and complex structures like weirs, barrages and dams. A disadvantage, however, is that they are unable to resolve complex spatial flow variability. In real life, however, coastal oceans and rivers interact. In deltaic estuaries, both tidal intrusion of seawater into the upstream river network and river discharge into open waters play a role. This is frequently approached by modelling the systems independently, with off-line coupling of the lateral boundary forcing. This implies that the river and the coastal model run sequentially, providing lateral discharge (1D) and water level (3D) forcing to each other without the possibility of direct feedback or interaction between these processes. An additional disadvantage is that due to the time aggregation usually applied to exchanged quantities, mass conservation is difficult to ensure. In this paper, we propose an approach that couples a 3D hydrodynamic modelling system for coastal waters (Delft3D) with a 1D modelling system for river hydraulics (SOBEK) online. This implies that contrary to off-line coupling, the hydrodynamic quantities are exchanged between the 1D and 3D domains during runtime to resolve the real-time exchange and interaction between the coastal waters and river network. This allows for accurate and mass conserving modelling of complex coastal waters and river network systems, whilst the advantages of both systems are maintained and used in an optimal and computationally efficient way. The coupled 1D–3D system is used to model the flows in the Pearl River Delta (Guangdong, China), which are determined by the interaction of the upstream network of the Pearl River and the open waters of the South China Sea. The highly complex upstream river network is modelled in 1D, simulating river discharges for the dry and wet monsoon periods. The 3D coastal model simulates the flow due to the external (ocean) periodic tidal forcing, the salinity distribution for both dry and wet seasons, as well as residual water levels (sea level anomalies) originating from the South China Sea. The model is calibrated and its performance extensively assessed against field measurements, resulting in a mean root mean square (RMS) error of below 6% for water levels over the entire Pearl River Delta. The model also represents both the discharge distribution over the river network and salinity transport processes with good accuracy, resolving the discharge distribution over the main branches of the river network within 5% of reported annual mean values and RMS errors for salinity in the range of 2 ppt (dry season) to 5 ppt (wet season).