Surface Chlorophyll-A Fronts in the Yellow and Bohai Seas Based on Satellite Data

Chlorophyll fronts are important to monitor and map the oceanic front, especially in the season when sea surface temperature (SST) fronts weaken. In this study, surface chlorophyll-a (chl-a) fronts in the Yellow and Bohai seas were characterized for the first time using satellite data. Five distinct chl-a fronts (i.e., the Bohai Strait, Shandong Peninsula, Jiangsu, Liaodong Peninsula, and Korean Peninsula fronts) were observed in summer along the 40 m isobaths and faded in other seasons. Notably, these fronts coincided with SST fronts. Strong chl-a fronts emerged during summer due to chl-a blooms in eutrophic coastal waters paired with surface chl-a fading in strongly stratified offshore waters and coastal physical fronts. Although SST fronts were strong during winter, light limitation and strong vertical mixing in offshore waters led to low chl-a in both coastal and offshore waters, suppressing chl-a front formation. Both chl-a and SST fronts coincided with steep seabed slopes (slope ratio > 1), suggesting that seabed slope may be an indicator of oceanic front location.

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Spatiotemporal Variability of Surface Phytoplankton Carbon and Carbon-to-Chlorophyll a Ratio in the South China Sea Based on Satellite Data

Remote Sensing ◽

10.3390/rs13010030 ◽

2020 ◽

Vol 13 (1) ◽

pp. 30

Author(s):

Wenlong Xu ◽

Guifen Wang ◽

Long Jiang ◽

Xuhua Cheng ◽

Wen Zhou ◽

...

Keyword(s):

South China Sea ◽

Chlorophyll A ◽

South China ◽

Satellite Data ◽

Phytoplankton Biomass ◽

The South China Sea ◽

Spatiotemporal Variability ◽

The South ◽

Chl A ◽

China Sea

The spatiotemporal variability of phytoplankton biomass has been widely studied because of its importance in biogeochemical cycles. Chlorophyll a (Chl-a)—an essential pigment present in photoautotrophic organisms—is widely used as an indicator for oceanic phytoplankton biomass because it could be easily measured with calibrated optical sensors. However, the intracellular Chl-a content varies with light, nutrient levels, and temperature and could misrepresent phytoplankton biomass. In this study, we estimated the concentration of phytoplankton carbon—a more suitable indicator for phytoplankton biomass—using a regionally adjusted bio-optical algorithm with satellite data in the South China Sea (SCS). Phytoplankton carbon and the carbon-to-Chl-a ratio (θ) exhibited considerable variability spatially and seasonally. Generally, phytoplankton carbon in the northern SCS was higher than that in the western and central parts. The regional monthly mean phytoplankton carbon in the northern SCS showed a prominent peak during December and January. A similar pattern was shown in the central part of SCS, but its peak was weaker. Besides the winter peak, the western part of SCS had a secondary maximum of phytoplankton carbon during summer. θ exhibited significant seasonal variability in the northern SCS, but a relatively weak seasonal change in the western and central parts. θ had a peak in September and a trough in January in the northern and central parts of SCS, whereas in the western SCS the minimum and maximum θ was found in August and during October–April of the following year, respectively. Overall, θ ranged from 26.06 to 123.99 in the SCS, which implies that the carbon content could vary up to four times given a specific Chl-a value. The variations in θ were found to be related to changing phytoplankton community composition, as well as dynamic phytoplankton physiological activities in response to environmental influences; which also exhibit much spatial differences in the SCS. Our results imply that the spatiotemporal variability of θ should be considered, rather than simply used a single value when converting Chl-a to phytoplankton carbon biomass in the SCS, especially, when verifying the simulation results of biogeochemical models.

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SPATIAL-TEMPORAL DISTRIBUTION OF CHLOROPHYLL-A IN SOUTHERN PART OF THE MAKASSAR STRAIT

Jurnal Ilmu Kelautan SPERMONDE ◽

10.20956/jiks.v4i1.3804 ◽

2018 ◽

Vol 4 (1) ◽

Author(s):

Wasir Samad Daming ◽

Muhammad Anshar Amran ◽

Amir Hamzah Muhiddin ◽

Rahmadi Tambaru

Keyword(s):

Chlorophyll A ◽

Satellite Data ◽

Chlorophyll Concentration ◽

Temporal Distribution ◽

Fishing Ground ◽

Landsat 8 ◽

Trade Winds ◽

Chl A ◽

June July ◽

Potential Area

Surface chlorophyll-a (Chl-a) distribution have been analyzed with seasonal variation during southeast monsoon in southern part of Makassar Strait and Flores Sea. Satellite data of Landsat-8 is applied to this study to formulate the distribution of chlorophyll concentration during monsoonal wind period. The distribution of chlorophyll concentration was normally peaked condition in August during southeast monsoon. Satellite data showed that a slowdown in the rise of the distribution of chlorophyll in September with a lower concentration than normal is likely due to a weakening the strength of southeast trade winds during June – July – August 2016. Further analysis shows that the southern part of the Makassar strait is likely occurrence of upwelling characterized by increase in surface chlorophyll concentrations were identified as the potential area of fishing ground.

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Chlorophyll-a Variability during Upwelling Events in the South-Eastern Baltic Sea and in the Curonian Lagoon from Satellite Observations

Remote Sensing ◽

10.3390/rs12213661 ◽

2020 ◽

Vol 12 (21) ◽

pp. 3661

Author(s):

Toma Dabuleviciene ◽

Diana Vaiciute ◽

Igor E. Kozlov

Keyword(s):

Baltic Sea ◽

Chlorophyll A ◽

Satellite Data ◽

Coastal Upwelling ◽

Curonian Lagoon ◽

The Baltic Sea ◽

Chl A ◽

Resolution Imaging ◽

The Baltic ◽

Eastern Baltic

Based on the analysis of multispectral satellite data, this work demonstrates the influence of coastal upwelling on the variability of chlorophyll-a (Chl-a) concentration in the south-eastern Baltic (SEB) Sea and in the Curonian Lagoon. The analysis of sea surface temperature (SST) data acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard Aqua/Terra satellites, together with Chl-a maps from Medium Resolution Imaging Spectrometer (MERIS) onboard Envisat, shows a significant decrease of up to 40–50% in Chl-a concentration in the upwelling zone. This results from the offshore Ekman transport of more productive surface waters, which are replaced by cold and less-productive waters from deeper layers. Due to an active interaction between the Baltic Sea and the Curonian Lagoon which are connected through the Klaipeda Strait, coastal upwelling in the SEB also influences the hydrobiological conditions of the adjacent lagoon. During upwelling inflows, SST drops by approximately 2–8 °C, while Chl-a concentration becomes 2–4 times lower than in pre-upwelling conditions. The joint analysis of remotely sensed Chl-a and SST data reveals that the upwelling-driven reduction in Chl-a concentration leads to the temporary improvement of water quality in terms of Chl-a in the coastal zone and in the hyper-eutrophic Curonian Lagoon. This study demonstrates the benefits of multi-spectral satellite data for upscaling coastal processes and monitoring the environmental status of the Baltic Sea and its largest estuarine lagoon.

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Spatio-Temporal Variability of Chlorophyll-A and Environmental Variables in the Panama Bight

Remote Sensing ◽

10.3390/rs12132150 ◽

2020 ◽

Vol 12 (13) ◽

pp. 2150

Author(s):

Andrea Corredor-Acosta ◽

Náyade Cortés-Chong ◽

Alberto Acosta ◽

Matias Pizarro-Koch ◽

Andrés Vargas ◽

...

Keyword(s):

Surface Temperature ◽

Sea Surface Temperature ◽

Chlorophyll A ◽

Satellite Data ◽

Temporal Variability ◽

Phytoplankton Growth ◽

Sea Surface ◽

Chl A ◽

Physical Variables ◽

Spatio Temporal

The analysis of synoptic satellite data of total chlorophyll-a (Chl-a) and the environmental drivers that influence nutrient and light availability for phytoplankton growth allows us to understand the spatio-temporal variability of phytoplankton biomass. In the Panama Bight Tropical region (PB; 1–9°N, 79–84°W), the spatial distribution of Chl-a is mostly related to the seasonal wind patterns and the intensity of localized upwelling centers. However, the association between the Chl-a and different physical variables and nutrient availability is still not fully assessed. In this study, we evaluate the relationship between the Chl-a and multiple physical (wind, Ekman pumping, geostrophic circulation, mixed layer depth, sea level anomalies, river discharges, sea surface temperature, and photosynthetically available radiation) and chemical (nutrients) drivers in order to explain the spatio-temporal Chl-a variability in the PB. We used satellite data of Chl-a and physical variables, and a re-analysis of a biogeochemical product for nutrients (2002–2016). Our results show that at the regional scale, the Chl-a varies seasonally in response to the wind forcing and sea surface temperature. However, in the coastal areas (mainly Gulf of Panama and off central-southern Colombia), the maximum non-seasonal Chl-a values are found in association with the availability of nutrients by river discharges, localized upwelling centers and the geostrophic circulation field. From this study, we infer that the interplay among these physical-chemical drivers is crucial for supporting the phytoplankton growth and the high biodiversity of the PB region.

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Comparison of In-Situ Chlorophyll-a Time Series and Sentinel-3 Ocean and Land Color Instrument Data in Slovenian National Waters (Gulf of Trieste, Adriatic Sea)

Water ◽

10.3390/w13141903 ◽

2021 ◽

Vol 13 (14) ◽

pp. 1903

Author(s):

El Khalil Cherif ◽

Patricija Mozetič ◽

Janja Francé ◽

Vesna Flander-Putrle ◽

Jana Faganeli-Pucer ◽

...

Keyword(s):

Machine Learning ◽

Chlorophyll A ◽

Satellite Data ◽

Adriatic Sea ◽

Global Ocean ◽

Learning Approach ◽

Chl A ◽

Gulf Of Trieste ◽

Machine Learning Approach

While satellite remote sensing of ocean color is a viable tool for estimating large-scale patterns of chlorophyll-a (Chl-a) and global ocean primary production, its application in coastal waters is limited by the complex optical properties. An exploratory study was conducted in the Gulf of Trieste (Adriatic Sea) to assess the usefulness of Sentinel-3 satellite data in the Slovenian national waters. OLCI (Ocean and Land Colour Instrument) Chl-a level 2 products (OC4Me and NN) were compared to monthly Chl-a in-situ measurements at fixed sites from 2017 to 2019. In addition, eight other methods for estimating Chl-a concentration based on reflectance in different spectral bands were tested (OC3M, OC4E, MedOC4, ADOC4, AD4, 3B-OLCI, 2B-OLCI and G2B). For some of these methods, calibration was performed on in-situ data to achieve a better agreement. Finally, L1-regularized regression and random forest were trained on the available dataset to test the capabilities of the machine learning approach. The results show rather poor performance of the two originally available products. The same is true for the other eight methods and the fits to the measured values also show only marginal improvement. The best results are obtained with the blue-green methods (OC3, OC4 and AD4), especially the AD4SI (a designated fit of AD4) with R = 0.56 and RMSE = 0.4 mg/m³, while the near infrared (NIR) methods show underwhelming performance. The machine learning approach can only explain 30% of the variability and the RMSE is of the same order as for the blue-green methods. We conclude that due to the low Chl-a concentration and the moderate turbidity of the seawater, the reflectance provided by the Sentinel-3 OLCI spectrometer carries little information about Chl-a in the Slovenian national waters within the Gulf of Trieste and is therefore of limited use for our purposes. This requires that we continue to improve satellite products for use in those marine waters that have not yet proven suitable. In this way, satellite data could be effectively integrated into a comprehensive network that would allow a reliable assessment of ecological status, taking into account environmental regulations.

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Assessment of chlorophyll-a and sea surface temperature variability around the Mascarene Plateau, Nazareth Bank (Mauritius) using satellite data

Indian Journal of Fisheries ◽

10.21077/ijf.2017.64.4.71978-01 ◽

2017 ◽

Vol 64 (4) ◽

Cited By ~ 1

Author(s):

V. Ramchandur ◽

Soonil D. D. V. Rughooputh ◽

R. Boojawon ◽

B. A. Motah

Keyword(s):

Surface Temperature ◽

Sea Surface Temperature ◽

Chlorophyll A ◽

Satellite Data ◽

Phytoplankton Biomass ◽

Winter Season ◽

Sea Surface ◽

Chl A ◽

The Past ◽

Western Side

The Mascarene Plateau is characterised by shallow banks namely Saya de Malha and Nazareth which are known to harbour high phytoplankton biomass along the slope down to the ridge. Correlation between sea surface temperature (SST) and Chlorophyll-a (Chl-a) distribution surrounding the plateau was investigated. Higher Chl-a concentration was observed during the period July to September, indicating higher productivity due to upwelling. The regions east (61-630E) and west (57-590E) of the Mascarene Plateau were also studied along latitudes 130S up to 180S in the exclusive economic zone of Mauritius, where most of the fishing activities are concentrated. In general, 2008 was observed to be less warm during the past 14 years registering a drop with respect to the maximum monthly mean records, whilst 2006 was the most productive during winter season in the region of study. Chl-a bloom was observed after cyclone Imelda in April 2013 showing Chl-a concentration above 0.3 mg m-3 along latitude 130S and longitude 570E. The study reveals that the western side of the plateau is more productive with relatively warmer surface temperature compared to the eastern side of the plateau.

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Mapping Chlorophyll-a Concentrations in the Kaštela Bay and Brač Channel Using Ridge Regression and Sentinel-2 Satellite Images

Electronics ◽

10.3390/electronics10233004 ◽

2021 ◽

Vol 10 (23) ◽

pp. 3004

Author(s):

Antonia Ivanda ◽

Ljiljana Šerić ◽

Marin Bugarić ◽

Maja Braović

Keyword(s):

Remote Sensing ◽

Chlorophyll A ◽

Satellite Data ◽

Coastal Waters ◽

Optical Parameter ◽

Data Set ◽

Chl A ◽

Sentinel 2

In this paper, we describe a method for the prediction of concentration of chlorophyll-a (Chl-a) from satellite data in the coastal waters of Kaštela Bay and the Brač Channel (our case study areas) in the Republic of Croatia. Chl-a is one of the parameters that indicates water quality and that can be measured by in situ measurements or approximated as an optical parameter with remote sensing. Remote sensing products for monitoring Chl-a are mostly based on the ocean and open sea monitoring and are not accurate for coastal waters. In this paper, we propose a method for remote sensing monitoring that is locally tailored to suit the focused area. This method is based on a data set constructed by merging Sentinel 2 Level-2A satellite data with in situ Chl-a measurements. We augmented the data set horizontally by transforming the original feature set, and vertically by adding synthesized zero measurements for locations without Chl-a. By transforming features, we were able to achieve a sophisticated model that predicts Chl-a from combinations of features representing transformed bands. Multiple Linear Regression equation was derived to calculate Chl-a concentration and evaluated quantitatively and qualitatively. Quantitative evaluation resulted in R2 scores 0.685 and 0.659 for train and test part of data set, respectively. A map of Chl-a of the case study area was generated with our model for the dates of the known incidents of algae blooms. The results that we obtained are discussed in this paper.

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Chlorophyll content of Thalassia hemprichii (Ehrenberg) Ascherson leaves in some coastal areas of Cebu Island, Central Philippines

Annals of Tropical Research ◽

10.32945/atr4023.2018 ◽

2018 ◽

pp. 35-44

Author(s):

Lorenzo Halasan ◽

Danilo Dy

Keyword(s):

Chlorophyll Content ◽

Chlorophyll A ◽

Biomass Productivity ◽

Nonparametric Tests ◽

Coastal Areas ◽

Light Limitation ◽

Thalassia Hemprichii ◽

Chl A ◽

Pigment Extraction ◽

Significant Difference

Variations in the chlorophyll concentrations in seagrass leaves can be used to indicate biomass, productivity and overall ecosystem condition in coastal areas. In this study, we determined the chlorophyll content (ie chl a and b) of Thalassia hemprichii from selected coastal areas in Cebu Island, Central Philippines to determine if there were spatial variations between intertidal (0m) and subtidal (1.5m) sections, and in the five geographically separate coastal areas of the island. Pigment extraction was done using 95% acetone, the solution analyzed via spectrophotometry and quantified using the equation of Ritchie (2006). The values were statistically compared using nonparametric tests. Mean chlorophyll content and chlorophyll a/b ratio of T. hemprichii showed no significant variations between intertidal and subtidal sections: F(4,45)=27.75, p=0.192 for mean chlorophyll content and F(4,45)=18.28, p=0.116 for chlorophyll a/b ratio. However, there was significant difference between geographic areas (p=0.000). Although T. hemprichii tend to display a physiological response to shading and light limitation, the difference in depth (≈ 1.5m) between intertidal and subtidal sections did not produce a statistically meaningful difference. However, the significant differences between sites for the chlorophyll content and chlorophyll a/b ratio of T. hemprichii could guide future decision in seagrass transplantation of specific localities.

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SEASONAL CHANGES OF VERTICAL PROFILES OF CHLOROPHYLL A IN THE AMUR BAY (JAPAN SEA)

Izvestiya TINRO ◽

10.26428/1606-9919-2018-193-183-189 ◽

2018 ◽

Vol 193 ◽

pp. 183-189

Author(s):

A. D. Zharova ◽

Yu. I. Zuenko

Keyword(s):

Chlorophyll A ◽

Satellite Data ◽

Seasonal Changes ◽

Subsurface Layer ◽

Peter The Great Bay ◽

Japan Sea ◽

Vertical Profiles ◽

Amur Bay ◽

Chl A ◽

External Part

Seasonal changes of chlorophyll a profiles are traced over the Amur Bay (Peter the Great Bay, Japan Sea) in May-October, 2017 by means of oceanographic sonde-profiler equipped with fluorometer. Two principally different types of the vertical profiles are revealed, which were formed by different mechanisms of productivity: i) Chl a concentration had the maximum at the sea surface and decreased with the depth in the internal part of the bay occupied by the estuarine waters, and ii) Chl a concentration had the maximum below the seasonal pycnocline in the external part of the bay connected with the open sea. The highest Chl a concentration was observed in July-August for the estuarine type because of summer monsoon flood on the rivers, but in September for the marine type because of the coastal upwelling induced by monsoon winds change. Comparing these results with estimations of Chl a concentration made with the satellite data, insufficient correspondence is concluded for the external part of the bay, outside the estuarine zone, because the satellite data don’t reflect well the chlorophyll a in the subsurface layer and its seasonal variations. Thus, underestimation of real productivity and feeding ability of marine areas is available with the satellite data on chlorophyll a.

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