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Satellite remote sensing of ocean colour properties allows observation of the ocean with high temporal and spatial coverage, facilitating the better assessment of changes in marine primary production. Ocean productivity is often assessed using satellite-derived chlorophyll a concentrations, a commonly used proxy for phytoplankton concentration. We used the Copernicus GlobColour remote sensing chlorophyll a surface concentration to investigate seasonal and non-seasonal variability, temporal trends, and changes in spring bloom chlorophyll a magnitude. Complementary, we analysed the chlorophyll a relationship with sea surface temperature and mixed-layer depth in the German Bight from 1998 to 2020. Empirical orthogonal functions were employed in order to investigate dominant spatial and temporal patterns (modes) related to the main processes of chlorophyll a variability. Multi covariance analysis was used to extract the dominant structures that maximize the covariance between chlorophyll a and sea surface temperature mixed-layer depth fields. High levels of chlorophyll a were found near the coast, showing a decreasing gradient towards offshore waters. A significant chlorophyll a positive trend was observed close to the Elbe estuary and adjacent area, while 55 % of the German Bight was characterized by a significant chlorophyll a negative trend. The chlorophyll a non-seasonal variability showed that the first four modes explained around 45 %, with the first and second modes related to inter- and intra-annual variability, respectively, observed in the temporal principal components spectral analyses. Monthly chlorophyll a concentration anomalies co-varied by 45 % with sea surface temperature anomalies and 23 % with mixed-layer depth anomalies. The monthly averages of chlorophyll a anomaly fields were suitable to investigate long-term trends and variability. The rising water temperature, combined with its indirect effects on other variables, can partially explain the observed trends in chlorophyll a. [ABSTRACT FROM AUTHOR]

Dynamic monitoring of water environment is the basis of maintaining urban security and promoting urban sustainable development. To effectively solve the problems caused by the large-scale flooding of floating aquatic invasive plants, such as water environment destruction, clogging river, water quality pollution, water ecological balance destruction, etc., a satellite and ground multi-sensor collaborative sensing method for floating plants is proposed in this paper. For the monitoring of floating plants in macro watershed, the vegetation index and chlorophyll concentration were used to extract floating plants, analyzing, and calculating the distribution and coverage area of floating plants based on 4-band high-resolution satellite images. For the monitoring of floating plants in small watershed, combined with visible light video, multispectral images, and LiDAR data, optimized spectral feature variable processing, semantic segmentation network, and symmetric function neural network are utilized to obtain real-time information on the invasion location, distribution pattern, and coverage area of floating plants. In this paper, the upstream basin of the Huangpu River in Shanghai in 2023 was selected as the experimental area. The distribution of floating plants in different watercourse and different periods was successfully obtained by this method, and the coverage area was accurately calculated with an identification rate of more than 90%, which provided technical support for cross-regional management and efficient cleaning of floating plants. [ABSTRACT FROM AUTHOR]

The Chlorophyll-a (Chla) concentration is an important parameter characterizing the water quality of rivers and lakes. Satellite remote sensing provides new opportunities for the quantitative monitoring of Chla concentration in large-scale water bodies. In this study, Sentinel-2 satellite remote sensing data integrated on the Google Earth Engine (GEE) remote sensing big data platform are employed, along with hourly measured water quality site data, to establish a quantitative inversion model for Chla concentration water quality parameters in Jiujiang City within Jiangxi Province, China. The Chla concentration is estimated for each quarter from 2020 to 2022, and the spatial distribution is analyzed, revealing the changing trend of Chla concentration over the past three years. The key findings are as follows: (1) The quantitative inversion model for Chla concentration has been validated with measured data, achieving a model accuracy of 0.53; (2) The spatial inversion results of Chla concentration exhibit an increasing trend that is consistent with actual measurement site results; (3) Owing to the influence of human activities and the peak-low water level of rivers and lakes, Chla concentration shows a discernible seasonal variation pattern. This methodology offers a new perspective for analyzing the seasonal variation characteristics of Chla concentration in rivers and lakes, providing valuable insights for the sustainable management of river and lake water quality. [ABSTRACT FROM AUTHOR]

Data assimilation (DA) in marine and freshwater systems combines numerical models and observations to deliver the best possible characterisation of a water body's physical and biogeochemical state. This underpins the widely used 3D ocean state reanalyses and forecasts produced operationally by e.g. the Copernicus Marine Service. The use of DA in natural waters is an active field of research, but testing new developments in realistic setting can be challenging, as operational DA systems are demanding in terms of computational resources and technical skill. There is a need for testbeds that sufficiently realistic but also efficient to run and easy to operate. Here, we present the Ensemble and Assimilation Tool (EAT): a flexible and extensible software package that enables data assimilation of physical and biogeochemical variables in a onedimensional water column. EAT builds on established open-source components for hydrodynamics (GOTM), biogeochemistry (FABM) and data assimilation (PDAF). It is easy to install and operate, and flexible through support for user-written plugins. EAT is well suited to explore and advance the state-of-the-art in DA in natural waters thanks to its support for (1) strongly and weakly coupled data assimilation, (2) observations describing any prognostic and diagnostic element of the physical-biogeochemical model, and (3) estimation of biogeochemical parameters. Its range of capabilities is demonstrated with three applications: ensemble-based coupled physical-biogeochemical assimilation, the use of variational methods (3D-Var) to assimilate sea surface chlorophyll, and the estimation of biogeochemical parameters. [ABSTRACT FROM AUTHOR]

The North Sea and the Baltic Sea still experience eutrophication and deoxygenation in spite of large international efforts to mitigate such environmental problems. Due to the highly different oceanographic frameworks of the two seas, modelling efforts so far mainly focused either on one or the other Sea making it difficult to study inter-basin exchange of mass and energy. Here, we present an ocean model (NEMO-Nordic) coupled to the Swedish Coastal and Ocean Biogeochemical model SCOBI), which covers the North Sea, the Skagerrak-Kattegat transition zone and the Baltic Sea. We address its validity to further investigate biogeochemical changes in the North Sea-Baltic Sea system. The model reproduces the long-term temporal trends, the temporal variability, the yearly averages and the general spatial distribution of all assessed biogeochemical parameters. It is particularly suitable to be used in future multi-stressor studies such as to evaluate combined climate and nutrient forcing scenarios. In particular, the model performance is best for oxygen and phosphate concentrations. However, important seasonal and spatial differences for chlorophyll-a and nitrate are seen between model results and observations in coastal areas of the southeastern North Sea, the Skagerrak-Kattegat transition zone, the Gulf of Riga, the Gulf of Finland and the Gulf of Bothnia. These are partially linked to different local processes and biogeochemical forcing that lead to a general overestimation of nitrate. The validation of our model results for individual areas are in agreement with policy management assessment areas, which gives an added value to better contribute to international programs aiming to reduce eutrophication in the Baltic Sea-North Sea system. [ABSTRACT FROM AUTHOR]

Chromophoric dissolved organic matter (CDOM) significantly contributes to the non-water absorption budget in the Mediterranean Sea. The absorption coefficient of CDOM, aCDOM(λ), is measurable in situ and remotely from different platforms and can be used as an indicator of the concentration of other relevant biogeochemical variables, e.g., dissolved organic carbon. However, our ability to model the biogeochemical processes that determine CDOM concentrations is still limited. Here we propose a novel parametrisation of the CDOM cycle that accounts for the interplay between the light- and nutrient-dependent dynamics of local CDOM production and degradation, as well as its vertical transport. The parameterization is included in a one-dimensional (1D) configuration of the Biogeochemical Flux Model (BFM), which is here coupled to the General Ocean Turbulence Model (GOTM) through the Framework for Aquatic Biogeochemical Models (FABM). Here BFM is augmented with a bio-optical component that revolves spectrally the underwater light transmission. We did run this new GOTM-FABM-BFM configuration to simulate the seasonal aCDOM(λ) cycle at the deep-water site of the BOUSSOLE project in the North-Western Mediterranean Sea. Our results show that accounting for both nutrient and light dependence of CDOM production improves the simulation of the seasonal and vertical dynamics of aCDOM(λ), including a subsurface maximum that forms in spring and progressively intensifies in summer. Furthermore, the model consistently reproduces the higher-than30 average concentrations of CDOM per unit chlorophyll concentration observed at BOUSSOLE. The configuration, outputs and sensitivity analyses from this 1D model application will be instrumental for future applications of BFM to the entire Mediterranean Sea in a 3D configuration. [ABSTRACT FROM AUTHOR]

The study of extreme weather events and their impact on ocean physics and biogeochemistry is challenging due to the difficulty involved with collecting in situ data. However, recent research has pointed out the major influence of such physical forcing events on microbiological organisms. Moreover, the occurrence of such intense events may increase in the future in the context of global change. In May 2019, an intense storm occurred in the Ligurian Sea (north-western Mediterranean Sea) and was captured during the FUMSECK (Facilities for Updating the Mediterranean Submesoscale – Ecosystem Coupling Knowledge) cruise. In situ multi-platform (vessel-mounted acoustic Doppler current profiler, thermosalinometer, fluorometer, flow cytometer, a moving vessel profiler equipped with a multi-sensor towed vehicle, and a glider) measurements along with satellite data and a 3D atmospheric model were used to characterise the fine-scale dynamics occurring in the impacted oceanic zone. The most affected area was marked by a lower water temperature (1 ∘C colder), a factor of 2 increase in surface chlorophyll a , and a factor of 7 increase in the nitrate concentration, exhibiting strong gradients with respect to the surrounding waters. Our results show that this storm led to a deepening of the mixed-layer depth from 15 to 50 m and a dilution of the deep chlorophyll maximum. As a result, the surface biomass of most phytoplankton groups identified by automated flow cytometry increased by up to a factor of 2. Conversely, the carbon / chlorophyll ratio of most phytoplankton groups decreased by a factor of 2, evidencing significant changes in the phytoplankton cell composition. These results suggest that the role of storms on the biogeochemistry and ecology of the Mediterranean Sea may be underestimated and highlight the need for high-resolution measurements during these events coupling physics and biology. [ABSTRACT FROM AUTHOR]

Understanding the variations in past ocean carbonate chemistry is critical in elucidating the role of the oceans in balancing the global carbon cycle. The fossil shells from marine calcifiers present in the sedimentary record are widely applied as past ocean carbon cycle proxies. However, the interpretation of these records can be challenging due to the complexity physiological and ecological response to the carbonate system during organisms' life cycle, as well as the potential for preservation at the sea-floor. Here we present a new dissolution proxy based on the morphological attributes of coccolithophores from the Noëlaerhabdaceae family (Emiliania huxleyi and Gephyrocapsa spp., > 2 µm). To evaluate the influences of coccolithophore calcification and coccolith preservation on fossil morphology, we measured morphological attributes, mass, length, thickness, and shape factor (ks), of coccoliths in a laboratory dissolution experiment and surface sediment samples in the South China Sea. The coccolith morphological data in surface sediment were also analyzed with environment settings, namely surface temperature, nutrients, pH, chlorophyll-a concentration, and carbonate saturation of bottom water by a redundancy analysis. Statistical analysis indicate that carbonate saturation of the deep ocean explains the highest proportion of variation in the morphological data instead of the environmental variables of the surface ocean. Moreover, the dissolution trajectory in the ks vs length of coccoliths is comparable between natural samples and laboratory dissolution experiments, emphasizing the importance of carbonate saturation on fossil coccolith morphology. However, the mean ks alone cannot fully explain all variations observed in our work. We propose that the mean ks and standard deviation of ks (σ) over the mean ks (σ/ks) could reflect different degrees of dissolution and size-selective dissolution, influenced by the assemblage composition. By applying together with the σ/ks ratio, the ks factor of fossil coccoliths in deep ocean sediments could be a potential proxy for a quantitative reconstruction of past carbonate dissolution dynamics. [ABSTRACT FROM AUTHOR]

The change of the global climate is most pronounced in the Arctic, where the air temperature increases 2 to 3 times faster than the global average. This process is associated with an increase in the concentration of greenhouse gases in the atmosphere. There are publications predicting the sharp increase in methane emissions into the atmosphere due to permafrost thawing. Therefore, it is important to study how the air composition in the Arctic changes in the changing climate. In the Russian sector of the Arctic, the air composition was measured only in the surface atmospheric layer at the coastal stations or earlier at the drifting stations. Vertical distributions of gas constituents of the atmosphere and aerosol were determined only in a few small regions. That is why the integrated experiment was carried out to measure the composition of the troposphere in the entire Russian sector of the Arctic from on board the Optik Tu-134 aircraft laboratory in the period of ​​​​​​​4 to 17 September of 2020. The aircraft laboratory was equipped with contact and remote measurement facilities. The contact facilities were capable of measuring the concentrations of CO 2 , CH 4 , O 3 , CO, NO x ​​​​​​​, and SO 2 , as well as the disperse composition of particles in the size range from 3 nm to 32 µ m, black carbon, and organic and inorganic components of atmospheric aerosol. The remote facilities were operated to measure the water transparency in the upper layer of the ocean, the chlorophyll content in water, and spectral characteristics of the underlying surface. The measured data have shown that the ocean continues absorbing CO 2. This process is most intense over the Barents and Kara seas. The recorded methane concentration was increased over all the Arctic seas, reaching 2090 ppb in the near-water layer over the Kara Sea. The contents of other gas components and black carbon were close to the background level. In bioaerosol, bacteria predominated among the identified microorganisms. In most samples, they were represented by coccal forms, less often spore-forming and non-spore-bearing rod-shaped bacteria. No dependence of the representation of various bacterial genera on the height and the sampling site was revealed. The most turbid during the experiment was the upper layer of the Chukchi and Bering seas. The Barents Sea turned out to be the most transparent. The differences in extinction varied by more than a factor of 1.5. In all measurements, except for the Barents Sea, the tendency of an increase in chlorophyll fluorescence in more transparent waters was observed. [ABSTRACT FROM AUTHOR]

Because of the large diversity of case 2 waters ranging from extremely absorbing to extremely scattering waters and the complexity of light transfer due to external terrestrial inputs, retrieving main biogeochemical parameters such as chlorophyll- a or suspended particulate matter concentration in these waters is still challenging. By providing optical and biogeochemical parameters for 180 sampling stations with turbidity and chlorophyll- a concentration ranging from 1 to 700 FNU and from 0.9 to 180 mg m -3 respectively, the HYPERMAQ dataset will contribute to a better description of marine optics in optically complex water bodies and can help the scientific community to develop algorithms. The HYPERMAQ dataset provides biogeochemical parameters (i.e. turbidity, pigment and chlorophyll- a concentration, suspended particulate matter), apparent optical properties (i.e. water reflectance from above water measurements) and inherent optical properties (i.e. absorption and attenuation coefficients) from six different study areas. These study areas include large estuaries (i.e. the Rio de la Plata in Argentina, the Yangtze estuary in China, and the Gironde estuary in France), inland (i.e. the Spuikom in Belgium and Chascomùs lake in Argentina), and coastal waters (Belgium). The dataset is available from Lavigne et al. (2022) at 10.1594/PANGAEA.944313. [ABSTRACT FROM AUTHOR]

Optical water type (OWT) classification provides a way to delineate surface waters according to spectral properties caused by optically active constituents. This classification is useful in mapping out spatial variability and describing changes in water quality over time as it uses inherent optical properties to discriminate areas of a water body. We used Sentinel-3 OLCI images from July 2017 to December 2020 to classify OWT in Manila Bay and to generate chlorophyll-a and total suspended matter (TSM) concentration layers using C2RCC algorithm. Nine coastal OWT classes for Manila Bay having consistent presence and spatial distribution seasonally were identified. The most dominant class, OWT 6, (3.50 µg/cm3 chlorophyll-a; 4.93 g/m3 TSM) was concentrated around the central area of the bay, covering as much as 79% of it. Chlorophyll-a and TSM concentrations were higher in the nearshore areas and were decreasing offshore. The class with the second highest concentrations, OWT 7, (9.11 µg/cm3 chlorophyll-a; 26.80 g/m3 TSM) were found near river outlets, where high nutrient and sediment loadings coming from the watershed enter the bay. Lowest concentrations (0.26–0.70 µg/cm3 chlorophyll-a; 0.64–1.10 g/m3 TSM) were found in OWT 1, OWT 2, and OWT 3, all located farthest from the shore, such as the mouth of the bay leading to the open sea. Validation using in situ observations showed that C2RCC produced relatively good estimates for chlorophyll-a concentrations of up to 12 µg/cm3 (RMSE=1.71 µg/cm3). No conclusion was drawn for TSM due to insufficient data. [ABSTRACT FROM AUTHOR]

Because of the large diversity of case 2 waters ranging from extremely absorbing to extremely scattering waters and the complexity of light transfer due to external terrestrial inputs, retrieving main biogeochemical parameters such as chlorophyll-a or suspended particulate matter concentration in these waters is still challenging. By providing optical and biogeochemical parameters for 180 sampling stations with turbidity and chlorophyll-a concentration ranging from 1 to 700 FNU and from 0.9 to 180 mg m-3 respectively, the HYPERMAQ dataset will contribute to a better description of marine optics in optically complex water bodies and can help the scientific community to develop algorithms. The HYPERMAQ dataset provides biogeochemical parameters (i.e. turbidity, pigment and chlorophyll-a concentration, suspended particulate matter), apparent optical properties (i.e. water reflectance from above water measurements) and inherent optical properties (i.e. absorption and attenuation coefficients) from six different study areas. These study areas include large estuaries (i.e. the Rio de la Plata in Argentina, the Yangtze Estuary in China and the Gironde Estuary in France), inland (i.e. the Spuikom in Belgium and Chascomùs lake in Argentina) and coastal waters (Belgium). The dataset is available from Lavigne et al (2022), [ABSTRACT FROM AUTHOR]

With the repetition of mucilage event, which is triggered by many different anthropogenic, climatic and microbiological factors, in the Marmara Sea in 2021, the importance of water quality in the seas has come to the fore again. To present the spatial distribution of the mucilage, a feasibility study has been carried out with point-based water quality measurements and remote sensing data. In-situ measurements are collected routinely within the scope of the Integrated Marine Pollution Monitoring Program (DEN-IZ) which was conducted in cooperation with the Ministry of Environment, Urbanisation and Climate Change and the Scientific and Technological Research Council of Turkey - Marmara Research Center (TUBITAK-MAM). In this preliminary study, 16 in-situ measurements, 5 of which were taken from water containing mucilage, on 29 April 2021 in the Gulf of Gemlik were used. Then, univariate regression analyzes were performed in two different scenarios (i.e. 5 mucilage points and all in-situ points) with Sentinel-2 satellite imagery and in-situ water quality measurements for 2 different parameters (i.e. chlorophyll-a – Chl-a) and turbidity). According to R2 and accuracy assessment measures (f- and t- statistics etc.), the most suitable models were determined for two scenarios and two parameters. Finally, the performances of the selected models were tested with 2 different in-situ measurements and satellite images (dated 22 and 27 April) taken from dates close to the data set used; and it was concluded that the models created with 16 points were successful for both Chl-a and turbidity estimation for this preliminary study. [ABSTRACT FROM AUTHOR]

A global compilation of in situ data is useful to evaluate the quality of ocean-colour satellite data records. Here we describe the data compiled for the validation of the ocean-colour products from the ESA Ocean Colour Climate Change Initiative (OC-CCI). The data were acquired from several sources (including, inter alia, MOBY, BOUSSOLE, AERONET-OC, SeaBASS, NOMAD, MERMAID, AMT, ICES, HOT and GeP&CO) and span the period from 1997 to 2018. Observations of the following variables were compiled: spectral remote-sensing reflectances, concentrations of chlorophyll a, spectral inherent optical properties, spectral diffuse attenuation coefficients and total suspended matter. The data were from multi-project archives acquired via open internet services or from individual projects, acquired directly from data providers. Methodologies were implemented for homogenization, quality control and merging of all data. No changes were made to the original data, other than averaging of observations that were close in time and space, elimination of some points after quality control and conversion to a standard format. The final result is a merged table designed for validation of satellite-derived ocean-colour products and available in text format. Metadata of each in situ measurement (original source, cruise or experiment, principal investigator) was propagated throughout the work and made available in the final table. By making the metadata available, provenance is better documented, and it is also possible to analyse each set of data separately. This paper also describes the changes that were made to the compilation in relation to the previous version (Valente et al., 2016). [ABSTRACT FROM AUTHOR]

Primary production dynamics are strongly associated with vertical density profiles, which dictate the depth of stratification and mixed layers. Climate change and artificial structures (e.g. windfarms) are likely to modify the strength of stratification and vertical distribution of nutrient fluxes, especially in shelf seas where fine scale processes are important drivers, affecting the vertical distribution of phytoplankton. To understand the effect of physical changes on primary production, identifying the linkage between density and phytoplankton profiles is essential. Here, the ecological relevance of eight density layers (DLs) obtained by multiple methods that define three different portions of the pycnocline (above, centre, below) was evaluated to identify a valuable proxy for subsurface Chlorophyll-a (Chl-a mg m-3) concentrations. The associations of subsurface Chl-a with surface and deep mixing were investigated by hypothesizing the occurrence at the same depth of any DL and the maximum Chl-a layer (DMC) using Spearman correlation, linear regression, and a Major Axis analysis. Out of 1237 observations of the water column exhibiting a pycnocline, 78% reported DMCs above the bottom mixed layer depth (BMLD). This suggests that the BMLD is a boundary trapping Chl-a in shallow waters (≤ 120 m). BMLD constantly described Chl-a vertical distribution despite surface mixing indicators, suggesting a significant contribution of deep mixing processes in supporting subsurface production under specific conditions (e.g. prolonged stratification, tidal cycle, and bathymetry). Using BMLD for defining subsurface Chl-a could be a valuable tool for understanding the spatiotemporal variability of Chl-a in shelf seas, representing a potential variable for ecological assessments. [ABSTRACT FROM AUTHOR]

Lakes are key ecosystems within the global biogeosphere. However, the bottom-up controls on the biological productivity of lakes, including surface temperature, ice phenology, nutrient loads and mixing regime, are increasingly altered by climate warming and land-use changes. To better understand the environmental drivers of lake productivity, we assembled a dataset on chlorophyll-a concentrations, as well as associated water quality parameters and surface solar irradiance, for temperate and cold-temperate lakes experiencing seasonal ice cover. We developed a method to identify periods of rapid algal growth from in situ chlorophyll-a time series data and applied it to measurements performed between 1964 and 2019 across 357 lakes, predominantly located north of 40°. Long-term trends show that the algal growth windows have been occurring earlier in the year, thus potentially extending the growing season and increasing the annual productivity of northern lakes. The dataset is also used to analyze the relationship between chlorophyll-a growth rates and solar irradiance. Lakes of higher trophic status exhibit a higher sensitivity to solar radiation, especially at moderate irradiance values during spring. The lower sensitivity of chlorophyll-a growth rates to solar irradiance in oligotrophic lakes likely reflects the dominant role of nutrient limitation. Chlorophyll-a growth rates are significantly influenced by light availability in spring but not in summer and fall, consistent with a switch to top-down control of summer and fall algal communities. The growth window dataset can be used to analyze trends in lake productivity across the northern hemisphere or at smaller, regional scales. We present some general trends in the data and encourage other researchers to use the open dataset for their own research questions. [ABSTRACT FROM AUTHOR]

Elevated surface chlorophyll- a (chl- a) concentration ([chl- a ]), an index of phytoplankton biomass, has been previously observed and documented by remote sensing in the waters to the southwest of Sable Island (SI) on the Scotian Shelf in eastern Canada. Here, we present an analysis of this phenomenon using a 21-year time series of satellite-derived [chl- a ], paired with information on the particle backscattering coefficient at 443 nm (bbp(443) , a proxy for particle suspension) and the detritus/gelbstoff absorption coefficient at 443 nm (adg(443) , a proxy to differentiate water masses and presence of dissolved organic matter) in an attempt to explain some possible mechanisms that lead to the increase in surface biomass in the surroundings of SI. We compared the seasonal cycle, 8 d climatology and seasonal trends of surface waters near SI to two control regions located both upstream and downstream of the island, away from terrigenous inputs. Application of the self-organising map (SOM) approach to the time series of satellite-derived [chl- a ] over the Scotian Shelf revealed the annual spatio-temporal patterns around SI and, in particular, persistently high phytoplankton biomass during winter and spring in the leeward side of SI, a phenomenon that was not observed in the control boxes. In the vicinity of SI, a significant increase in [chl- a ] and adg(443) during the winter months occurred at a rate twice that of the ones observed in the control boxes, while no significant trends were found for the other seasons. In addition to the increase in [chl- a ] and adg(443) within the plume southwest of SI, the surface area of the plume itself expanded by a factor of 5 over the last 21 years. While the island mass effect (IME) explained the enhanced biomass around SI, we hypothesised that the large increase in [chl- a ] over the last 21 years was partly due to an injection of nutrients by the island's grey seal colony, which has increased by 200 % during the same period. This contribution of nutrients from seals may sustain high phytoplankton biomass at a time of year when it is usually low following the fall bloom. A conceptual model was developed to estimate the standing stock of chl- a that can be sustained by the release of nitrogen (N) by seals. Comparison between satellite observations and model simulations showed a good temporal agreement between the increased abundance of seal on SI during the breeding season and the phytoplankton biomass increase during the winter. We found that about 20 % of chl- a standing stock increase over the last 21 years could be due to seal N fertilisation, the remaining being explained by climate forcing and oceanographic processes. Although without in situ measurements for ground truthing, the satellite data analysis provided evidence of the impact of marine mammals on lower trophic levels through a fertilisation mechanism that is coupled with the IME with potential implications for conservation and fisheries. [ABSTRACT FROM AUTHOR]

Water quality monitoring is important in maintaining the cleanliness and health of water bodies. It enables us to identify sources of pollutions and study trends. While modern methods include the use of satellite images to estimate water quality parameters, commonly used satellite systems, such as Landsat and Sentinel, only generate images with temporal resolution of 2 to 16 days on the average. Himawari-8 satellite system, on the other hand, generates full-disk images every 10-minutes, making it possible to generate water quality parameters concentration maps more frequently. This paper presents the preliminary analysis of the generation of yearly and seasonal Chlorophyll-a (Chl-a) and Total Suspended Matter (TSM) estimation models using Himawari-8 satellite images and linear regression. Correlation analysis shows that the single spectral bands and band ratios involving Red band have the strongest relationship with Chl-a and TSM. Generated linear regression yearly and seasonal models resulted to R2 values of 0.4 to 0.5 with RMSE values around 3 micrograms/cm3 for Chl-a and 9.5 grams/m3 for TSM. Results also indicate that the seasonal models are better than the yearly models in terms of fit and error. Results from the preliminary investigation will be used to generate a more robust global model in future studies. [ABSTRACT FROM AUTHOR]

Light is an important regulator of photo-chemical and photo-biological processes in coastal areas. However, understanding how the atmosphere-ocean interaction drives changes in the amount of light entering coastal waters and how changes in the underwater light environment influence the biological characteristic of coastal water can be challenging due to the complex oceanographic dynamic of these areas. Here, we empirically describe the seasonal relationships between meteorological and oceanographic variables over a three year period and quantify the effect light have on the productivity of a coastal area off the Otago coast, New Zealand, through the application of an oceanographic-biological model. The model quantifies changes in the production-biomass ratio (PP / B) (i.e. rate of production of organic matter from phytoplankton produced per unit of total organic biomass) using measurements of the underwater attenuation coefficient, particulate organic carbon, chlorophyll-a and sea temperature. The sensitivity of the model to input data was estimated by comparing the PP / B ratio predicted from Chl a concentrations derived from field measurements of the attenuation coefficients of PAR light Kd (m-1) and Chl a concentrations derived from remote sensing data of Kd (m-1). The results presented here indicate a mild increment in solar radiation partially driven by increased wind speeds and reduction of cloud cover, ultimately producing small increments in the amount of solar radiation penetrating the water column, especially during summer. The model formulated, predict important seasonal shifts in the PP/B ratio. These shifts are driven by the rate at which light decays and likely modulated by the frequency of wind speeds that favour increments of the thermoclines depth and an increment of sea surface temperatures in the area. [ABSTRACT FROM AUTHOR]

Two feature-based verification methods, thus far only used for the diagnostic evaluation of atmospheric models, have been applied to compare ∼7 km resolution pre-operational analyses of chlorophyll- a (Chl- a) concentrations to a 1 km gridded satellite-derived Chl- a concentration product. The aim of this study was to assess the value of applying such methods to ocean models. Chl- a bloom objects were identified in both data sets for the 2019 bloom season (1 March to 31 July). These bloom objects were analysed as discrete (2-D) spatial features, but also as space–time (3-D) features, providing the means of defining the onset, duration and demise of distinct bloom episodes and the season as a whole. The new feature-based verification methods help reveal that the model analyses are not able to represent small coastal bloom objects, given the coarser definition of the coastline, also wrongly producing more bloom objects in deeper Atlantic waters. Model analyses' concentrations are somewhat higher overall. The bias manifests itself in the size of the model analysis bloom objects, which tend to be larger than the satellite-derived bloom objects. The onset of the bloom season is delayed by 26 d in the model analyses, but the season also persists for another month beyond the diagnosed end. The season was diagnosed to be 119 d long in the model analyses, compared to 117 d from the satellite product. Geographically, the model analyses and satellite-derived bloom objects do not necessarily exist in a specific location at the same time and only overlap occasionally. [ABSTRACT FROM AUTHOR]

Water is an essential natural source for human being and environment. To conserve water sources, monitoring them by using remote sensing data and technologies is an efficient way. In this study, water quality of the Sea of Marmara (Turkey), which has lots of currents, was examined. The main aim of the study was developing a common model to monitor chlorophyll-a concentration in time by using satellite data. After, the coefficients of the OC2 (ocean chlorophyll 2) model were detected by curve fitting, it was applied to Landsat images. The bias and RMSE (Root Mean Square Error) were found as 0.73 µg/l and 5.80 µg/l, respectively. The high RMSE was stemmed from dynamic structure of the sea. Thus, the temporal resolution has a profound impact on the accuracy of estimations. The developed model was applied to the HLS (Harmonized Landsat Sentinel-2) data, which has high temporal resolution. The results of the HLS and Landsat images were compared, and HLS is found as proper to monitor the water quality. The combined data (SST (Sea Surface Temperature) daily data from 1981 to present derived from satellite observations Level-4 product) was used for the secondary aim of the study which was monitoring SST. The bias and RMSE of the data, which was acquired on 19.07.2017, were found as 0.33 °C and 1.12 °C, respectively. The bias and RMSE of the data, which was acquired on 18.07.2018, were found as −0.02 °C and 1.03 °C, respectively. The combined data is found appropriate to monitor the SST. [ABSTRACT FROM AUTHOR]

To understand oceanic restratification in the subtropical northwestern Pacific and its influence on biogeochemical (BGC) processes, we examined post-storm restratification events observed from February to April 2018 by BGC-Argo floats, the BGC data from which were stoichiometrically analyzed by Sukigara et al. (2021; this issue). We found that during these events, restratification of the mixed layer (ML) was driven by geostrophic adjustment or ML eddy formation related to surface cooling during February to March. At the end of March, high surface chlorophyll a concentrations were observed within submesoscale eddies and at the edge of a mesoscale cyclonic feature observed from satellite data. Our results indicate that primary production in the subtropical northwestern Pacific is enhanced by the combined effects of mesoscale upwelling, storm-driven formation of a deep ML, subsequent formation of ML eddies, weak cooling, and the length of intervals between storms. [ABSTRACT FROM AUTHOR]

The Peruvian Upwelling System hosts an extremely high productive marine ecosystem. Observations show that the Peruvian Upwelling System is the only Eastern Boundary Upwelling Systems (EBUS) with an out-of-phase relationship of seasonal surface chlorophyll concentrations and upwelling intensity. This "seasonal paradox" triggers the questions: (1) what is the uniqueness of the Peruvian Upwelling System compared with other EBUS that leads to the out of phase relationship; (2) how does this uniqueness lead to low phytoplankton biomass in austral winter despite strong upwelling and ample nutrients? Using observational climatologies for four EBUS we diagnose that the Peruvian Upwelling System is unique in that intense upwelling coincides with deep mixed layers. We then apply a coupled regional ocean circulation-biogeochemical model (CROCO-BioEBUS) to assess how the interplay between mixed layer and upwelling is regulating the seasonality of surface chlorophyll in the Peruvian Upwelling System. The model recreates the "seasonal paradox" within 200 km off the Peruvian coast. We confirm previous findings that deep mixed layers, which cause vertical dilution and stronger light limitation, mostly drive the diametrical seasonality of chlorophyll relative to upwelling. In contrast to previous studies, reduced phytoplankton growth due to enhanced upwelling of cold waters and lateral advection are second-order drivers of low surface chlorophyll concentrations. This impact of deep mixed layers and upwelling propagates up the ecosystem, from primary production to export efficiency. Our findings emphasize the crucial role of the interplay of the mixed layer and upwelling and suggest that surface chlorophyll may increase along with a weakened seasonal paradox in response to shoaling mixed layers under climate change. [ABSTRACT FROM AUTHOR]

The Gulf of Lion shelf (NW Mediterranean) is one of the most productive areas in the Mediterranean Sea. A 3D coupled hydrodynamic-biogeochemical model is used to study the mechanisms that drive the particulate organic carbon (POC) budget over the shelf. A set of observations, including temporal series from a coastal station, remote sensing of surface chlorophyll-a, and a glider deployment, is used to validate the distribution of physical and biogeochemical variables from the model. The model reproduces well the time and spatial evolution of temperature, chlorophyll, and nitrate concentrations and shows a clear annual cycle of gross primary production and respiration. Knowing the physical and biogeochemical inputs and outputs terms, the annual budget of the POC in the Gulf of Lion is estimated and discussed. We estimate an annual net primary production of ~200 104 tC yr-1 at the scale of the shelf. The primary production is marked by a coast-slope increase with maximal values in the eastern region. Our results show that the primary production is favored by the inputs of nutrients imported from offshore waters, representing 3 and 15 times the inputs of the Rhône in terms of nitrate and phosphate. Besides, the EOFs decomposition highlights the role of solar radiation anomalies and continental winds that favor upwellings, and inputs of the Rhône River, on annual changes in the net primary production. Annual POC deposition (19 104 tC yr-1) represents 10 % of the net primary production. The delivery of terrestrial POC favored the deposition in front of the Rhône mouth and the mean cyclonic circulation increases the deposition between 30 and 50 m depth from the Rhône prodelta to the west. Mechanisms responsible for POC export (24 104 tC yr-1) to the open sea are discussed. The export off the shelf in the western part, from the Cap de Creus to the Lacaze-Duthiers canyon, represented 37 % of the total POC export. Maximum values were obtained during shelf dense water cascading events and marine winds. Considering surface waters only, the POC was mainly exported in the eastern part of the shelf through shelf waters and Rhône inputs, which spread to the Northern Current during favorable continental wind conditions. The Gulf of Lion shelf appears as an autotrophic ecosystem with a positive Net Ecosystem Production and as a source of POC for the adjacent NW Mediterranean basin. The undergoing and future increase in temperature and stratification induced by climate change could impact the trophic status of the GoL shelf and the carbon export towards the deep basin. It is crucial to develop models to predict and assess these future evolutions. [ABSTRACT FROM AUTHOR]

We document the development and public release of a new dataset (1997–2018), consisting of global maps of the Forel–Ule index, hue angle and Secchi disk depth. Source data come from the European Space Agency (ESA) Ocean Colour (OC) Climate Change Initiative (CCI), which is providing merged multi-sensor data from the mid-resolution sensors in operation at a specific time from 1997 to the present day. Multi-sensor satellite datasets are advantageous tools for ecological studies because they increase the probabilities of cloud-free data over a given region as data from multiple satellites whose overpass times differ by a few hours are combined. Moreover, data-merging from heritage and present satellites can expand the duration of the time series indefinitely, which allows the calculation of significant trends. Additionally, data are remapped consistently and analysis-ready for scientists. Also, the products described in this article have the exclusive advantage of being linkable to in situ historic observations and thus enabling the construction of very long time series. Monthly data are presented at a spatial resolution of ∼4km at the Equator and are available at PANGAEA (10.1594/PANGAEA.904266; Pitarch et al., 2019a). Two smaller and easier-to-handle test datasets have been produced from the former: a global dataset at 1 ∘ spatial resolution and another one for the North Atlantic at 0.25 ∘ resolution. The computer code for the generation of the Forel–Ule index, hue angle and Secchi disk depth from a given remote-sensing reflectance is also shared at 10.5281/zenodo.4439646 (Pitarch et al., 2021) and can be easily set in loop mode for batch calculations. [ABSTRACT FROM AUTHOR]

The deep chlorophyll maximum (DCM) is a ubiquitous feature of phytoplankton vertical distribution in stratified waters that is relevant to our understanding of the mechanisms that underpin the variability in photoautotroph ecophysiology across environmental gradients and has implications for remote sensing of aquatic productivity. During the PEACETIME (Process studies at the air-sea interface after dust deposition in the Mediterranean Sea) cruise, carried out from 10 May to 11 June 2017, we obtained 23 concurrent vertical profiles of phytoplankton chlorophyll a , carbon biomass and primary production, as well as heterotrophic prokaryotic production, in the western and central Mediterranean basins. Our main aims were to quantify the relative role of photoacclimation and enhanced growth as underlying mechanisms of the DCM and to assess the trophic coupling between phytoplankton and heterotrophic prokaryotic production. We found that the DCM coincided with a maximum in both the biomass and primary production but not in the growth rate of phytoplankton, which averaged 0.3 d-1 and was relatively constant across the euphotic layer. Photoacclimation explained most of the increased chlorophyll a at the DCM, as the ratio of carbon to chlorophyll a (C:Chl a) decreased from ca. 90–100 (g:g) at the surface to 20–30 at the base of the euphotic layer, while phytoplankton carbon biomass increased from ca. 6 mgCm-3 at the surface to 10–15 mgCm-3 at the DCM. As a result of photoacclimation, there was an uncoupling between chlorophyll a -specific and carbon-specific productivity across the euphotic layer. The ratio of fucoxanthin to total chlorophyll a increased markedly with depth, suggesting an increased contribution of diatoms at the DCM. The increased biomass and carbon fixation at the base of the euphotic zone was associated with enhanced rates of heterotrophic prokaryotic activity, which also showed a surface peak linked with warmer temperatures. Considering the phytoplankton biomass and turnover rates measured at the DCM, nutrient diffusive fluxes across the nutricline were able to supply only a minor fraction of the photoautotroph nitrogen and phosphorus requirements. Thus the deep maxima in biomass and primary production were not fuelled by new nutrients but likely resulted from cell sinking from the upper layers in combination with the high photosynthetic efficiency of a diatom-rich, low-light acclimated community largely sustained by regenerated nutrients. Further studies with increased temporal and spatial resolution will be required to ascertain if the peaks of deep primary production associated with the DCM persist across the western and central Mediterranean Sea throughout the stratification season. [ABSTRACT FROM AUTHOR]

Numerical models of ocean biogeochemistry are becoming a major tool to detect and predict the impact of climate change on marine resources and ocean health. Classically, validation of such models relies on comparison with surface quantities from satellite (such as chlorophyll-a concentrations), climatologies, or sparse in situ data (such as cruises observations, and permanent fixed oceanic stations). However, these datasets are not fully suitable to assess how models represent many climate-relevant biogeochemical processes. These limitations now begin to be overcome with the availability of a large number of vertical profiles of light, pH, oxygen, nitrate, chlorophyll- a concentrations and particulate backscattering acquired by the Biogeochemical-Argo (BGC-Argo) floats network. Additionally, other key biogeochemical variables such as dissolved inorganic carbon and alkalinity, not measured by floats, can be predicted by machine learning-based methods applied to float oxygen concentrations. Here, we demonstrate the use of the global array of BGC-Argo floats for the validation of biogeochemical models at the global scale. We first present 18 key metrics of ocean health and biogeochemical functioning to quantify the success of BGC model simulations. These metrics are associated with the air-sea CO2 flux, the biological carbon pump, oceanic pH, oxygen levels and Oxygen Minimum Zones (OMZs). The metrics are either a depth-averaged quantity or correspond to the depth of a particular feature. We also suggest four diagnostic plots for displaying such metrics. [ABSTRACT FROM AUTHOR]

Surface chlorophyll concentrations inferred from satellite images suggest a strong influence of the mesoscale activity on biogeochemical variability within the oligotrophic regions of the Gulf of Mexico (GoM). More specifically, long-living anticyclonic Loop Current Eddies (LCEs) are shed episodically from the Yucatan Channel and propagate westward. This study addresses the biogeochemical response of the LCEs to seasonal forcing and show their role in driving phytoplankton biomass distribution in the GoM. Using an eddy resolving (1/12°) interannual regional simulation based on the coupled physical-biogeochemical model NEMO-PISCES that yields a realistic representation of the surface chlorophyll distribution, it is shown that the LCEs foster a large biomass increase in winter in the upper ocean. The primary production in the LCEs is larger than the average rate in the surrounding open waters of the GoM. This behavior cannot be directly identified from surface chlorophyll distribution alone since LCEs are associated with a negative surface chlorophyll anomaly all year long. This anomalous biomass increase in the LCEs is explained by the mixed-layer response to winter convective mixing that reaches deeper and nutrient-richer waters. [ABSTRACT FROM AUTHOR]

We introduced a sediment-induced light attenuation algorithm into a biogeochemical model of the Coupled Ocean–Atmosphere–Wave–Sediment Transport (COAWST) modeling system. A fully coupled ocean–atmospheric–sediment–biogeochemical simulation was carried out to assess the impact of sediment-induced light attenuation on primary production in the northern Gulf of Mexico during the passage of Hurricane Gustav in 2008. When compared with model results without sediment-induced light attenuation, our new model showed a better agreement with satellite data on both the magnitude of nearshore chlorophyll concentration and the spatial distribution of offshore bloom. When Hurricane Gustav approached, resuspended sediment shifted the inner shelf ecosystem from a nutrient-limited one to a light-limited one. Only 1 week after Hurricane Gustav's landfall, accumulated nutrients and a favorable optical environment induced a posthurricane algal bloom in the top 20 m of the water column, while the productivity in the lower water column was still light-limited due to slow-settling sediment. Corresponding with the elevated offshore NO3 flux (38.71 mmol N m -1 s -1) and decreased chlorophyll flux (43.10 mg m -1 s -1), the outer shelf posthurricane bloom should have resulted from the cross-shelf nutrient supply instead of the lateral dispersed chlorophyll. Sensitivity tests indicated that sediment light attenuation efficiency affected primary production when sediment concentration was moderately high. Model uncertainties due to colored dissolved organic matter and parameterization of sediment-induced light attenuation are also discussed. [ABSTRACT FROM AUTHOR]

As the primary energy and carbon source in aquatic food webs, phytoplankton generally display spatial heterogeneity due to complicated biotic and abiotic controls; however our understanding of the causes of this spatial heterogeneity is challenging, as it involves multiple regulatory mechanisms. We applied a combination of field observation, numerical modeling, and remote sensing to display and interpret the spatial gradient of phytoplankton biomass in a Dutch tidal bay (the Eastern Scheldt) on the east coast of the North Sea. The 19 years (1995–2013) of monitoring data reveal a seaward increasing trend in chlorophyll- a (chl a) concentrations during the spring bloom. Using a calibrated and validated three-dimensional hydrodynamic–biogeochemical model, two idealized model scenarios were run: switching off the suspension feeders and halving the open-boundary nutrient and phytoplankton loading. Results reveal that bivalve grazing exerts a dominant control on phytoplankton in the bay and that the tidal import mainly influences algal biomass near the mouth. Satellite data captured a post-bloom snapshot that indicated the temporally variable phytoplankton distribution. Based on a literature review, we found five common spatial phytoplankton patterns in global estuarine–coastal ecosystems for comparison with the Eastern Scheldt case: seaward increasing, seaward decreasing, concave with a chlorophyll maximum, weak spatial gradients, and irregular patterns. We highlight the temporal variability of these spatial patterns and the importance of anthropogenic and environmental influences. [ABSTRACT FROM AUTHOR]

Biogeochemical ocean models are useful tools but subject to uncertainties arising from simplifications, inaccurate parameterization of processes, and poorly known model parameters. Parameter optimization is a standard method for addressing the latter but typically cannot constrain all biogeochemical parameters because of insufficient observations. Here we assess the trade-offs between satellite observations of ocean color and biogeochemical (BGC) Argo profiles and the benefits of combining both observation types for optimizing biogeochemical parameters in a model of the Gulf of Mexico. A suite of optimization experiments is carried out using different combinations of satellite chlorophyll and profile measurements of chlorophyll, phytoplankton biomass, and particulate organic carbon (POC) from autonomous floats. As parameter optimization in 3D models is computationally expensive, we optimize the parameters in a 1D model version and then perform 3D simulations using these parameters. We show first that the use of optimal 1D parameters, with a few modifications, improves the skill of the 3D model. Parameters that are only optimized with respect to surface chlorophyll cannot reproduce subsurface distributions of biological fields. Adding profiles of chlorophyll in the parameter optimization yields significant improvements for surface and subsurface chlorophyll but does not accurately capture subsurface phytoplankton and POC distributions because the parameter for the maximum ratio of chlorophyll to phytoplankton carbon is not well constrained in that case. Using all available observations leads to significant improvements of both observed (chlorophyll, phytoplankton, and POC) and unobserved (e.g., primary production) variables. Our results highlight the significant benefits of BGC-Argo measurements for biogeochemical parameter optimization and model calibration. [ABSTRACT FROM AUTHOR]

fThe deep chlorophyll maximum (DCM) is a ubiquitous feature of phytoplankton vertical distribution in stratified waters that is relevant for our understanding of the mechanisms that underpin the variability in photoautotroph ecophysiology across environmental gradients and has implications for remote sensing of aquatic productivity. During the PEACETIME (Process studies at the air-sea interface after dust deposition in the Mediterranean Sea) cruise, carried out from 10 May to 11 June 2017, we obtained 23 concurrent vertical profiles of phytoplankton chlorophyll a, carbon biomass and primary production, as well as heterotrophic prokaryotic production, in the western and central Mediterranean basins. Our main aims were to quantify the relative role of photoacclimation and enhanced growth as underlying mechanisms of the DCM and to assess the trophic coupling between phytoplankton and heterotrophic prokaryotic production. We found that the DCM coincided with a maximum in both biomass and primary production but not in growth rate of phytoplankton, which averaged 0.3 d-1 and was relatively constant across the euphotic layer. Photoacclimation explained most of the increased chlorophyll a at the DCM, as the carbon to chlorophyll a ratio (C:Chl a) decreased from ca. 90-100 (g:g) at the surface to 20-30 at the base of the euphotic layer, while phytoplankton carbon biomass increased from ca. 6 mgC m-3 at the surface to 10-15 mgC m-3 at the DCM. As a result of photoacclimation, there was an uncoupling between chlorophyll a--specific and carbon-specific productivity across the euphotic layer. The fucoxanthin to total chlorophyll a ratio increased markedly with depth, as did the biomass contribution of large cells, suggesting a dominance of diatoms at the DCM. The increased biomass and carbon fixation at the base of the euphotic zone was associated with enhanced rates of heterotrophic prokaryotic activity, which also showed a surface peak linked with warmer temperatures. Considering the phytoplankton biomass and turnover rates measured at the DCM, nutrient diffusive fluxes across the nutricline were able to supply only a minor fraction of the photoautotroph nitrogen and phosphorus requirements. Thus the deep maxima in biomass and primary production were not fueled by new nutrients, but likely resulted from cell sinking from the upper layers in combination with the high photosynthetic efficiency of a diatom-rich, low-light acclimated community largely sustained by regenerated nutrients. Further studies with increased temporal and spatial resolution will be required to ascertain if the deep primary production peaks associated with the DCM persist across the western and central Mediterranean Sea throughout the stratification season. [ABSTRACT FROM AUTHOR]

As part of the European Space Agency's Climate Change Initiative, new sets of satellite observation products have been produced for essential climate variables including ocean colour, sea surface temperature, sea level, and sea ice. These new products have been assimilated into a global physical–biogeochemical ocean model to create a set of 13-year reanalyses at 1 ∘ resolution and 3-year reanalyses at 1/4 ∘ resolution. In a series of experiments, the variables were assimilated individually and in combination in order to assess their consistency from a data assimilation perspective. The satellite products, and the reanalyses assimilating them, were found to be consistent in their representation of spatial features such as fronts, sea ice extent, and bloom activity. Assimilating multiple variables together often resulted in larger mean increments for a variable than assimilating it individually, providing information about model biases and compensating errors which could be addressed in the future development of the model and assimilation scheme. Sea surface fugacity of carbon dioxide had lower errors against independent observations in the higher-resolution simulations and was improved by assimilating ocean colour or sea ice concentration, but it was degraded by assimilating sea surface temperature or sea level anomaly. Phytoplankton biomass correlated more strongly with net air–sea heat fluxes in the reanalyses than chlorophyll concentration did, and the correlation was weakened by assimilating ocean colour data, suggesting that studies of phytoplankton bloom initiation based solely on chlorophyll data may not provide a full understanding of the underlying processes. [ABSTRACT FROM AUTHOR]

Methane (CH4) emissions from reservoirs are responsible for most of the atmospheric climatic forcing of these aquatic ecosystems, comparable to emissions from paddies or biomass burning. Primarily, CH4 is produced during the anaerobic mineralization of organic carbon in anoxic sediments by methanogenic archaea. However, the origin of the recurrent and ubiquitous CH4 supersaturation in oxic waters (i.e., the methane paradox) is still controversial. Here, we determined the dissolved CH4 concentration in the water column of 12 reservoirs during summer stratification and winter mixing to explore CH4 sources in oxic waters. Reservoir sizes ranged from 1.18 to 26.13 km 2. We found that dissolved CH4 in the water column varied by up to 4 orders of magnitude (0.02–213.64 µ mol L -1), and all oxic depths were consistently supersaturated in both periods. Phytoplanktonic sources appear to determine the concentration of CH4 in these reservoirs primarily. In anoxic waters, the depth-cumulative chlorophyll a concentration, a proxy for the phytoplanktonic biomass exported to sediments, was correlated to CH4 concentration. In oxic waters, the photosynthetic picoeukaryotes' abundance was significantly correlated to the dissolved CH4 concentration during both the stratification and the mixing. The mean depth of the reservoirs, as a surrogate of the vertical CH4 transport from sediment to the oxic waters, also contributed notably to the CH4 concentration in oxic waters. Our findings suggest that photosynthetic picoeukaryotes can play a significant role in determining CH4 concentration in oxic waters, although their role as CH4 sources to explain the methane paradox has been poorly explored. [ABSTRACT FROM AUTHOR]

Tidal flats provide valuable ecosystem services such as flood protection and carbon sequestration. Erosion and accretion processes govern the eco-geomorphic evolution of intertidal ecosystems (marshes and bare flats), and hence substantially affect their valuable ecosystem services. To understand the intertidal ecosystem development, high-frequency bed-level change data are thus needed. However, such datasets are scarce due to the lack of suitable methods that do not involve excessive labour and/or instrument cost. By applying newly-developed Surface Elevation Dynamics sensors (SED-sensors), we obtained unique high-resolution daily bed-level change data sets in the period 2013-2017 from 10 salt marsh sites situated in the Netherlands, Belgium and Britain in contrasting physical and biological settings. At each site, multiple sensors were deployed for 9-20 months to ensure sufficient spatial and temporal coverage of highly variable bed level change processes. The bed level change data are provided with synchronized hydrodynamic data, i.e. water level, wave height, tidal current velocity, and medium grain size (D50) as well as (for some sites) chlorophyll-a level and organic matter content of the surface sediment. This dataset has revealed diverse spatial morphodynamic patterns over daily to seasonal scales, which are valuable to theoretical and model development. On the daily scale, this dataset is particularly instructive as it includes a number of storm events, the response to which can be detected in the bed level change observations. Such data are rare but useful to study tidal flat response to highly energetic conditions. [ABSTRACT FROM AUTHOR]

We present the first ambient measurements of a new marine emission methane sulfonamide (MSAM: CH5NO2S), along with dimethyl sulfide (DMS) and dimethyl sulfone (DMSO2) over the Arabian Sea. Two shipborne transects (W → E, E → W) were made during the AQABA (Air Quality and Climate Change in the Arabian Basin) measurement campaign. Molar mixing ratios in picomole of species per mole of air (throughout this paper abbreviated as ppt) of DMS were in the range of 300–500 ppt during the first traverse of the Arabian Sea (first leg) and 100–300 ppt on the second leg. On the first leg DMSO2 was always below 40 ppt and MSAM was close to the limit of detection. During the second leg DMSO2 was between 40 and 120 ppt and MSAM was mostly in the range of 20–50 ppt with maximum values of 60 ppt. An analysis of HYSPLIT back trajectories combined with calculations of the exposure of these trajectories to underlying chlorophyll in the surface water revealed that most MSAM originates from the Somalia upwelling region, known for its high biological activity. MSAM emissions can be as high as one-third of DMS emissions over the upwelling region. This new marine emission is of particular interest as it contains both sulfur and nitrogen, making it potentially relevant to marine nutrient cycling and marine atmospheric particle formation. [ABSTRACT FROM AUTHOR]

Zooplankton play an important role in global biogeochemistry and their secondary production supports valuable fisheries of the world's oceans. Currently, zooplankton abundances cannot be estimated using remote sensing techniques. Hence, coupled physical-biogeochemical models (PBMs) provide an important tool for studying zooplankton on regional and global scales. However, evaluating the accuracy of zooplankton abundance estimates from PBMs has been a major challenge as a result of sparse observations. In this study, we configure a PBM for the Gulf of Mexico (GoM) from 1993-2012 and validate the model against an extensive combination of in situ biomass and rate measurements including total mesozooplankton biomass, size-fractionated mesozooplankton biomass and grazing rates, microzooplankton specific grazing rates, surface chlorophyll, deep chlorophyll maximum depth, phytoplankton specific growth rates, and net primary production. Spatial variability in mesozooplankton biomass climatology observed in a multi-decadal database for the northern GoM is well resolved by the model with a statistically significant (p < 0.01) correlation of 0.90. Mesozooplankton secondary production for the region averaged 66 + 8 mt C yr-1 equivalent to approximately 10% of NPP and ranged from 51 to 82 mt C yr-1. In terms of diet, model results from the shelf regions suggest that herbivory is the dominant feeding mode for small mesozooplankton (< 1-mm) whereas larger mesozooplankton are primarily carnivorous. However, in open-ocean, oligotrophic regions, both groups of mesozooplankton have proportionally greater reliance on heterotrophic protists as a food source. This highlights the important role of microbial and protistan food webs in sustaining mesozooplankton biomass in the GoM which serves as the primary food source for early life stages of many commercially-important fish species, including tuna. [ABSTRACT FROM AUTHOR]

The dynamics of the Loop Current (LC) and the detached Loop Current eddies (LCEs) dominate the surface circulation of the Gulf of Mexico (GoM) and transport Caribbean Water (CW) into the gulf. In this work, 25 years (1993–2017) of daily satellite data are used to investigate the variability of these physical processes and their effect on chlorophyll a (Chl a) concentrations from 1998 to 2017, including temporal changes, mean differences, and regional concentration tendencies. The physical variables analyzed are absolute dynamic topography (ADT) and oceanic currents. From the ADT and oceanic current monthly climatologies, it is shown that there is an annual intrusion of CW with an inward incursion that starts in spring, peaks in the summer, reaches to 28 ∘ N and 90.45 ∘ W, and then retreats in winter to approximately 26.5 ∘ N and 88.3 ∘ W. Minimum surface Chl a concentrations (< 0.08 mg m -3) are found during the summer–autumn period inside the region of maximum incursion of CW; the opposite is observed during the winter period when Chl a concentrations were at a maximum, e.g., > 0.14 mg m -3. The 3-year running averages of the ADT 40 cm isoline qualitatively reproduce the climatological pattern of 25 years showing that before 2002 CW was less intrusive. This suggests that from 2003 onward, larger volumes of oligotrophic waters from the Caribbean Sea have invaded the western GoM and reduced mean surface Chl a concentrations. A direct comparison between the 1998–2002 and 2009–2014 periods indicates that in the latter time interval, the Chl a concentration above waters deeper than 250 m has decreased significantly. [ABSTRACT FROM AUTHOR]

Nutrient rich water upwells offshore of Northwest Africa and is subsequently advected westwards. There it forms eddies and filaments with a rich spatial structure of physical and biological/biogeochemical properties. Here we present a high resolution (2.5 km) section through upwelling filaments and an eddy obtained in May 2018 with a Triaxus towed vehicle equipped with various oceanographic sensors. Physical processes at the mesoscale and submesoscale such as symmetric instability, trapping of fluid in eddies, and subduction of low potential vorticity (which we use as a water mass tracer) water can explain the observed distribution of biological production and export. We found a nitrate excess (higher nitrate concentrations than would be expected from oxygen values if only influenced by production and remineralization processes) core of an anti-cyclonic mode water eddy. We also found a high nitrate concentration region of ~5 km width in the mixed layer where symmetric instability appears to have injected nutrients from below into the euphotic zone. A similar region a little further south had high chlorophyll-a concentrations suggesting that nutrients had been injected there a few days earlier. Considering that such interactions of physics and biology are ubiquitous in the world's upwelling regions, we assume that they have strong influences on the productivity of such systems and their role in CO2 uptake. The intricate interplay of different parameters at kilometer scale needs to be taken into account when interpreting single profile and/or bottle data in dynamically active regions of the ocean. [ABSTRACT FROM AUTHOR]

https://doi.org/10.5194/bg-2019-337 © Author(s) 2019. This work is distributed under the Creative Commons Attribution 4.0 License. Discussion papers Abstract Discussion Metrics Submitted as: research article 04 Sep 2019 Review status This discussion paper is a preprint. It is a manuscript under review for the journal Biogeosciences (BG). Diel quenching of Southern Ocean phytoplankton fluorescence is related to iron limitation Christina Schallenberg1, Robert F. Strzepek1, Nina Schuback1,2, Lesley A. Clementson3, Philip W. Boyd1,4, and Thomas W. Trull1,3 1Antarctic Climate and Ecosystems Cooperative Research Centre, University of Tasmania, Hobart, Tasmania, Australia 2Swiss Polar Institute, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland 3Commonwealth Scientific and Industrial Research Organisation Oceans and Atmospheres, Hobart, Tasmania, Australia 4Institute for Marine and Antarctic Studies, University of Tasmania, Hobart, Tasmania, Australia Received: 26 Aug 2019 – Accepted for review: 02 Sep 2019 – Discussion started: 04 Sep 2019 Abstract. Evaluation of photosynthetic competency in time and space is critical for better estimates and models of oceanic primary productivity. This is especially true for areas where the lack of iron limits phytoplankton productivity, such as the Southern Ocean. Assessment of photosynthetic competency on large scales remains challenging, but phytoplankton chlorophyll-a fluorescence (ChlF) is a signal that holds promise in this respect as it is affected by, and consequently provides information about, the photosynthetic efficiency of the organism. A second process affecting the ChlF signal is heat dissipation of absorbed light energy, referred to as non-photochemical quenching (NPQ). NPQ is triggered when excess energy is absorbed; i.e., when more light is absorbed than can be used directly for photosynthetic carbon fixation. The effect of NPQ on the ChlF signal complicates its interpretation in terms of photosynthetic efficiency, and therefore most approaches relating ChlF parameters to photosynthetic efficiency seek to minimize the influence of NPQ by working under conditions of sub-saturating irradiance. Here, we propose that NPQ itself holds potential as an easily acquired optical signal indicative of phytoplankton physiological state with respect to iron (Fe) limitation. We present data from a research voyage to the Subantarctic Zone south of Australia. Incubation experiments confirmed that resident phytoplankton were Fe-limited, as the maximum quantum yield of primary photochemistry, Fv/Fm, measured with a Fast Repetition Rate fluorometer (FRRf), increased significantly with Fe addition. The NPQ "capacity" of the phytoplankton also showed sensitivity to Fe addition, decreasing with increased Fe availability, confirming previous work. The fortuitous presence of a remnant warm-core eddy in the vicinity of the study area allowed comparison of fluorescence behaviour between two distinct water masses, with the colder water showing significantly lower Fv/Fm than the warmer eddy waters, suggesting a difference in Fe limitation status between the two water masses. Again, NPQ capacity measured with the FRRf mirrored the behaviour observed in Fv/Fm, decreasing as Fv/Fm increased in the warmer water mass. We also analysed the diel quenching of underway fluorescence measured with a standard fluorometer, such as is frequently used to monitor ambient chlorophyll-a concentrations, and found a significant difference in behaviour between the two water masses. This difference was quantified by defining an NPQ parameter akin to the Stern-Volmer parameterization of NPQ, exploiting the fluorescence quenching induced by diel fluctuations in incident irradiance. We propose that monitoring of this novel NPQ parameter may enable assessment of phytoplankton physiological status (related to Fe availability) based on measurements made with standard fluorometers, as ubiquitously used on moorings, ships, floats and gliders. [ABSTRACT FROM AUTHOR]

Ocean color remote sensing is a challenging task over coastal waters due to the complex optical properties of aerosols and hydrosols. In order to conduct accurate atmospheric correction, we previously implemented a joint retrieval algorithm, hereafter referred to as the Multi-Angular Polarimetric Ocean coLor (MAPOL) algorithm, to obtain the aerosol and water-leaving signal simultaneously. The MAPOL algorithm has been validated with synthetic data generated by a vector radiative transfer model, and good retrieval performance has been demonstrated in terms of both aerosol and ocean water optical properties (Gao et al., 2018). In this work we applied the algorithm to airborne polarimetric measurements from the Research Scanning Polarimeter (RSP) over both open and coastal ocean waters acquired in two field campaigns: the Ship-Aircraft Bio-Optical Research (SABOR) in 2014 and the North Atlantic Aerosols and Marine Ecosystems Study (NAAMES) in 2015 and 2016. Two different yet related bio-optical models are designed for ocean water properties. One model aligns with traditional open ocean water bio-optical models that parameterize the ocean optical properties in terms of the concentration of chlorophyll a. The other is a generalized bio-optical model for coastal waters that includes seven free parameters to describe the absorption and scattering by phytoplankton, colored dissolved organic matter, and nonalgal particles. The retrieval errors of both aerosol optical depth and the water-leaving radiance are evaluated. Through the comparisons with ocean color data products from both in situ measurements and the Moderate Resolution Imaging Spectroradiometer (MODIS), and the aerosol product from both the High Spectral Resolution Lidar (HSRL) and the Aerosol Robotic Network (AERONET), the MAPOL algorithm demonstrates both flexibility and accuracy in retrieving aerosol and water-leaving radiance properties under various aerosol and ocean water conditions. [ABSTRACT FROM AUTHOR]

A global compilation of in situ data is useful to evaluate the quality of ocean-colour satellite data records. Here we describe the data compiled for the validation of the ocean-colour products from the ESA Ocean Colour Climate Change Initiative (OC-CCI). The data were acquired from several sources (including, inter alia, MOBY, BOUSSOLE, AERONET-OC, SeaBASS, NOMAD, MERMAID, AMT, ICES, HOT and GeP&CO) and span the period from 1997 to 2018. Observations of the following variables were compiled: spectral remote-sensing reflectances, concentrations of chlorophyll a , spectral inherent optical properties, spectral diffuse attenuation coefficients and total suspended matter. The data were from multi-project archives acquired via open internet services or from individual projects, acquired directly from data providers. Methodologies were implemented for homogenization, quality control and merging of all data. No changes were made to the original data, other than averaging of observations that were close in time and space, elimination of some points after quality control and conversion to a standard format. The final result is a merged table designed for validation of satellite-derived ocean-colour products and available in text format. Metadata of each in situ measurement (original source, cruise or experiment, principal investigator) was propagated throughout the work and made available in the final table. By making the metadata available, provenance is better documented, and it is also possible to analyse each set of data separately. This paper also describes the changes that were made to the compilation in relation to the previous version (Valente et al., 2016). The compiled data are available at 10.1594/PANGAEA.898188 (Valente et al., 2019). [ABSTRACT FROM AUTHOR]

Since the mid 1990s, Australia's Commonwealth Science Industry and Research Organisation (CSIRO) has developed a biogeochemical (BGC) model for coupling with a hydrodynamic and sediment model for application in estuaries, coastal waters and shelf seas. The suite of coupled models is referred to as the CSIRO Environmental Modelling Suite (EMS) and has been applied at tens of locations around the Australian continent. At a mature point in the BGC model's development, this paper presents a full mathematical description, as well as links to the freely available code and User Guide. The mathematical description is structured into processes so that the details of new parameterisations can be easily identified, along with their derivation. The EMS BGC model cycles carbon, nitrogen, phosphorous and oxygen through multiple phytoplankton, zooplankton, detritus and dissolved organic and inorganic forms in multiple water column and sediment layers. The underwater light field is simulated by a spectrally-resolved optical model that includes the calculation of water-leaving reflectance for validation with remote sensing. The water column is dynamically coupled to the sediment to resolve deposition, resuspension and benthic-pelagic biogeochemical fluxes. With a focus on shallow waters, the model also includes particularly-detailed representations of benthic plants such as seagrass, macroalgae and coral polyps. A second focus has been on, where possible, the use of geometric derivations of physical limits to constrain ecological rates, which generally requires population-based rates to be derived from initially considering the size and shape of individuals. For example, zooplankton grazing considers encounter rates of one predator on a prey field based on summing relative motion of the predator with the prey individuals and the search area, chlorophyll synthesis includes a geometrically-derived self-shading term, and the bottom coverage of benthic plants is generically-related to their biomass using an exponential form derived from geometric arguments. This geometric approach has led to a more algebraically-complicated set of equations when compared to more empirical biogeochemical model formulations. But while being algebraically-complicated, the model has fewer unconstrained parameters and is therefore simpler to move between applications than it would otherwise be. The version of the biogeochemistry described here is implemented in the eReefs project that is delivering a near real time coupled hydrodynamic, sediment and biogeochemical simulation of the Great Barrier Reef, northeast Australia, and its formulation provides an example of the application of geometric reasoning in the formulation of aquatic ecological processes. [ABSTRACT FROM AUTHOR]

This study highlights recent advances and challenges of applying coupled physical-biogeochemical modeling for investigating the distribution of the key phytoplankton groups in the Southern Ocean, an area of strong interest for understanding biogeochemical cycling and ecosystem functioning under present climate change. Our simulations of the phenology of various Phytoplankton Functional Types (PFTs) are based on a version of the Darwin biogeochemical model coupled to the Massachusetts Institute of Technology (MIT) general circulation model (Darwin-MITgcm). The ecological module version was adapted for the Southern Ocean by: 1) improving coccolithophores abundance relative to the original model by introducing a high affinity for nutrients and an ability to escape grazing control for coccolithophores; 2) including two different (small vs. large) size classes of diatoms; and 3) accounting for two distinct life stages for Phaeocystis (single cell vs. colonial). This new model configuration describes best the competition and co-occurrence of the PFTs in the Southern Ocean. It improves significantly relative to an older version the agreement of the simulated abundance of the coccolithophores and diatoms with in situ scanning electron microscopy observations in the Subantarctic Zone as well as with in situ diatoms and haptophytes (including coccolithophores and Phaeocystis) chlorophyll a concentrations within the Patagonian Shelf and along the Western Antarctic Peninsula obtained by diagnostic pigment analysis. The modeled Southern Ocean PFT dominance also agrees well with satellite-based PFT information. [ABSTRACT FROM AUTHOR]

The sea level (SL) variations at the coastal ocean result from multiscale processes and are substantially contributed by the SL changes due to the meteorological forcing. In this study, a new methodology, named as IBR, is developed to estimate the response of the coastal ocean to meteorological forcing. The response is taken as the combination of the static ocean response calculated using the inverted barometer formula and the dynamic ocean response estimated using the multivariable linear regression involving atmospheric pressure and wind component at the dominant wind orientation. The dominant wind orientation is determined based on the averaged values of the magnitude squared coherences between the adjusted SL and wind at every wind orientation. The IBR is implemented to estimate the response of the coastal ocean at two stations, E1 and E2 in the Bohai Bay, China. The analysed results indicate that at both E1 and E2, the adjusted SLs are related more to the regional wind, which is the averaged value in the Bohai Bay of the 10 m wind in the ERA-Interim data, than to the local wind; the dominant regional wind orientation is 75°. The estimated response using IBR with the regional meteorological forcing is much closer to the observed values than other methods, including the classical inverted barometer correction, the dynamic atmospheric correction, the multivariable linear regression and the IBR with local forcing, demonstrating that IBR with regional forcing have the best skill in estimating the response. The large deviations between the observed values and the estimated values using IBR with the regional meteorological forcing are mainly due to the remote wind, which is not considered in the IBR. This case study indicates that the IBR is a feasible and relatively effective method to estimate the response of the coastal ocean to the meteorological forcing. [ABSTRACT FROM AUTHOR]

The evolution of eutrophication parameters (i.e., nutrients and phytoplankton biomass) during recent decades was examined in coastal waters of the Vilaine Bay (VB, France) in relation to changes in the Loire and Vilaine rivers. Dynamic linear models were used to study long-term trends and seasonality of dissolved inorganic nutrient and chlorophyll a concentrations (Chl a) in rivers and coastal waters. For the period 1997–2013, the reduction in dissolved riverine inorganic phosphorus (DIP) concentrations led to the decrease in their Chl a levels. However, while dissolved inorganic nitrogen (DIN) concentrations decreased only slightly in the Vilaine, they increased in the Loire, specifically in summer. Simultaneously, phytoplankton in the VB underwent profound changes with increase in biomass and change in the timing of the annual peak from spring to summer. The increase in phytoplankton biomass in the VB, manifested particularly by increased summer diatom abundances, was due to enhanced summer DIN loads from the Loire, sustained by internal regeneration of DIP and dissolved silicate (DSi) from sediments. The long-term trajectories of this case study evidence that significant reduction of P inputs without simultaneous N abatement was not yet sufficient to control eutrophication all along the Loire–Vilaine–VB continuum. Upstream rivers reveal indices of recoveries following the significant diminution of P, while eutrophication continues to increase downstream, especially when N is the limiting factor. More N input reduction, paying particular attention to diffuse N sources, is required to control eutrophication in receiving VB coastal waters. Internal benthic DIP and DSi recycling appears to have contributed to the worsening of summer VB water quality, augmenting the effects of anthropogenic DIN inputs. For this coastal ecosystem, nutrient management strategies should consider the role played by internal nutrient loads to tackle eutrophication processes. [ABSTRACT FROM AUTHOR]

Ocean color remote sensing is a challenging task over coastal waters due to the complex optical properties of aerosols and hydrosols. In order to conduct accurate atmospheric correction, we previously implemented a joint retrieval algorithm to obtain the aerosol and water leaving signal simultaneously. The algorithm has been validated with synthetic data generated by a vector radiative transfer model and good retrieval performance has been demonstrated in terms of both aerosol and ocean water optical properties (Gao et al., 2018). In this work we applied the algorithm to airborne polarimetric measurements from the Research Scanning Polarimeter (RSP) over both open and coastal ocean waters acquired in two field campaigns: the Ship-Aircraft Bio-Optical Research (SABOR) in 2014 and the North Atlantic Aerosols and Marine Ecosystems Study (NAAMES) in 2015 and 2016. Two different yet related bio-optical models are designed for ocean water properties. One model aligns with traditional open ocean water bio-optical models that parameterize the ocean optical properties in terms of the concentration of chlorophyll a. The other is a generalized bio-optical model for coastal waters that includes seven free parameters to describe the absorption and scattering by phytoplankton, colored dissolved organic matter and non-algal particles. The retrieval errors of both aerosol optical depth and the water leaving radiance are evaluated. Through the comparisons with ocean color data products from both in situ measurements and the Moderate Resolution Imaging Spectroradiometer (MODIS), and the aerosol product from both the High Spectral Resolution Lidar (HSRL) and the Aerosol Robotic Network (AERONET), our algorithm demonstrates both flexibility and accuracy in retrieving aerosol and water leaving radiance properties under various aerosol and ocean water conditions. [ABSTRACT FROM AUTHOR]

Chlorophyll-a is an optically active compound (OAC) commonly used as a proxy for phytoplankton biomass in an aquatic environment. Retrieving the concentration of chlorophyll-a remains a challenge due to the presence of several OAC particularly in water bodies which are in proximity to the land-based activities. In this study, an effort has been made to estimate the chlorophyll-a concentration of both the freshwater Lake Biwa and the coastal water of Wakasa Bay in Japan. A spectral decomposition algorithm was used to determine the chlorophyll-a using the satellite images. The algorithm was applied to the satellite images from two different sensors namely Landsat-8/OLI and Sentinel-2A/MSI. The satellite-derived chlorophyll-a concentration for the lake and coastal water from two different sensors were compared to assess the performance of both the sensors. The accuracy of the chlorophyll-a results derived from the images was evaluated with the in-situ measurement data of the chlorophyll-a for the Lake Biwa and the coastal water of Wakasa Bay. Both satellite sensors appear to give the best results for the coastal water (R2 > 0.80) with an RMSE < 0.3 μg/L. However, slight underestimation of chlorophyll-a noted for the Landsat-8 image with an increase in chlorophyll-a concentration. For the lake water, Sentinel-2A results were relatively better (R2 > 0.70) than Landsat-8, with an RMSE of < 1.0 μg/L. The obtained results will be useful to evaluate the primary productivity of both freshwater and coastal water body. [ABSTRACT FROM AUTHOR]