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Seawater Bio-Optical Characteristics from Satellite Ocean Color Data II
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Seawater Bio-Optical Characteristics from Satellite Ocean Color Data II

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Ocean Remote Sensing".

Deadline for manuscript submissions: closed (15 February 2024) | Viewed by 11685

Special Issue Editor

Dr. Dmitry Glukhovets

E-Mail Website
Guest Editor
Shirshov Institute of Oceanology, Russian Academy of Sciences, 117997 Moscow, Russia
Interests: ocean optics; satellite ocean color; seawater fluorescence; absorption coefficient; dissolved organic matter; chlorophyll; arctic seas; surface layer
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Satellite ocean color data make it possible to track changes in the state of marine ecosystems effectively and quickly. The values of seawater bio-optical characteristics, obtained as a result of processing these data, depend on the quantitative and qualitative composition of the dissolved and suspended matter. This composition is extremely variable and diverse: suspended particles carried into the sea by rivers and wind, colored organic matter, phytoplankton, bacteria and detritus. The content and variability of these seawater components, obtained from the satellite ocean color data, allow us to quickly assess the state of the ecosystem and monitor water areas on a wide spatial and temporal scale.

This Special Issue is a continuation of the first part, which was successfully completed in November 2022. It also aims at presenting the results of studies on seawater bio-optical characteristics from satellite ocean color data. An important section in this area is the development and improvement of regional satellite algorithms that take into account the characteristics of specific water areas and allow us to obtain more accurate values of bio-optical characteristics compared to standard algorithms.

The authors consider various aspects of the seawater bio-optical properties: spectral, angular, and polarization characteristics, relation to the absolute content and composition of the seawater optically active components, the inverse problems, the spatial and temporal variability of the characteristics, including both the inherent and apparent ones (for example, the diffuse attenuation coefficient). The modeling and measured results are welcomed; the presentation of new ideas and their realization, particularly applications for the investigation and monitoring of the ocean and seas are encouraged. The particular topics of interest include, but are not limited with:

  • Development and application of regional algorithms for retrieval of the seawater bio-optical characteristics from satellite ocean color data;
  • Results of processing, analysis and application of the data from the multisensor data sets;
  • Modeling of the seawater bio-optical characteristics and their components;
  • Inverse problems in application to the bio-optical characteristics of seawater
  • Bio-optical characteristics of the arctic waters;
  • Variability of the seawater optical characteristics depending on the hydro-physical processes.

Original papers and thematic reviews are accepted.

Dr. Dmitry Glukhovets
Guest Editor

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Keywords

  • seawater bio-optical characteristics
  • satellite ocean color data
  • regional algorithms
  • multi-sensor data sets
  • new approaches, methods and algorithms
  • new data on variability including polar regions

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Published Papers (7 papers)

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22 pages, 9627 KiB  
Article
Regional Models for Sentinel-2/MSI Imagery of Chlorophyll a and TSS, Obtained for Oligotrophic Issyk-Kul Lake Using High-Resolution LIF LiDAR Data
by Vadim Pelevin, Ekaterina Koltsova, Aleksandr Molkov, Sergei Fedorov, Salmor Alymkulov, Boris Konovalov, Mairam Alymkulova and Kubanychbek Jumaliev
Remote Sens. 2023, 15(18), 4443; https://doi.org/10.3390/rs15184443 - 9 Sep 2023
Cited by 1 | Viewed by 1370
Abstract
The development of regional satellite bio-optical models for natural waters with high temporal and spatial variability, such as inland seas, reservoirs, and coastal ocean waters, requires the implementation of an intermediate measuring link in the chain, “water sampling—bio-optical models”, and this link must [...] Read more.
The development of regional satellite bio-optical models for natural waters with high temporal and spatial variability, such as inland seas, reservoirs, and coastal ocean waters, requires the implementation of an intermediate measuring link in the chain, “water sampling—bio-optical models”, and this link must have certain intermediate characteristics. The most crucial of them are the high-precision measurements of the main water quality parameters, such as the concentration of chlorophyll a (Chl a), colored dissolved organic matter (CDOM), and total suspended sediments (TSS) in the upper water layer, together with a high operational rate and the ability to cover a large water area in a short time, which corresponds to a satellite overpass. A possible solution is to utilize laser-induced fluorescence (LIF) of water constituents measured by a marine LiDAR in situ with a high sampling rate from a high-speed vessel. This allows obtaining a large ground-truth dataset of the main water quality parameters simultaneously with the satellite overpass within the time interval determined by NASA protocols. This method was successfully applied to the oligotrophic Issyk-Kul Lake in Kyrgyzstan, where we obtained more than 4000 and 1000 matchups for the Chl a and TSS, respectively. New preliminary regional bio-optical models were developed on the basis of a one-day survey and tested for archive Sentinel-2A data for 2022. This approach can be applied for regular monitoring and further correction in accordance with seasonal variability. The obtained results, together with previously published similar studies for eutrophic coastal and productive inland waters, emphasize the applicability of the presented method for the development or adjustment of regional bio-optical models for water bodies of a wide trophic range. Full article
(This article belongs to the Special Issue Seawater Bio-Optical Characteristics from Satellite Ocean Color Data II)
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24 pages, 20267 KiB  
Article
Accumulation and Cross-Shelf Transport of Coastal Waters by Submesoscale Cyclones in the Black Sea
by Arseny Kubryakov, Anna Aleskerova, Evgeniy Plotnikov, Artem Mizyuk, Alesya Medvedeva and Sergey Stanichny
Remote Sens. 2023, 15(18), 4386; https://doi.org/10.3390/rs15184386 - 6 Sep 2023
Cited by 3 | Viewed by 1231
Abstract
High- and medium-resolution satellite optical imagery show that submesoscale cyclonic eddies (SCEs) trap coastal waters and induce their rapid cross-shelf transport. Due to the presence of a rigid boundary, the convergence is observed in the coastal part of SCEs. It causes accumulation of [...] Read more.
High- and medium-resolution satellite optical imagery show that submesoscale cyclonic eddies (SCEs) trap coastal waters and induce their rapid cross-shelf transport. Due to the presence of a rigid boundary, the convergence is observed in the coastal part of SCEs. It causes accumulation of suspended matter, which spins inward in a spiral motion toward the SCE core. Small SCEs with a radius of 1–10 km transport waters with local anomalies in the concentration of chlorophyll, total suspended matter and temperature to a distance of up to 150 km and are observed for more than 10 days. Lagrangian calculations based on realistic NEMO numerical model are used to estimate the fate of the coastal waters in such SCEs. The eddy entrains the largest number of particles during its separation from the coast when its vorticity reaches the maximum. Then, the SCE weakens, which is accompanied by the flattening of initially risen isopycnals and deepening of the trapped coastal waters. The described mechanism shows that coastal SCEs may cause intense short-period cross-shelf transport of the biological and chemical characteristics, and is another process affecting the functioning of the marine ecosystems. Full article
(This article belongs to the Special Issue Seawater Bio-Optical Characteristics from Satellite Ocean Color Data II)
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21 pages, 3539 KiB  
Article
Light Absorption by Optically Active Components in the Arctic Region (August 2020) and the Possibility of Application to Satellite Products for Water Quality Assessment
by Tatiana Efimova, Tatiana Churilova, Elena Skorokhod, Vyacheslav Suslin, Anatoly S. Buchelnikov, Dmitry Glukhovets, Aleksandr Khrapko and Natalia Moiseeva
Remote Sens. 2023, 15(17), 4346; https://doi.org/10.3390/rs15174346 - 4 Sep 2023
Cited by 1 | Viewed by 1526
Abstract
In August 2020, during the 80th cruise of the R/V “Akademik Mstislav Keldysh”, the chlorophyll a concentration (Chl-a) and spectral coefficients of light absorption by phytoplankton pigments, non-algal particles (NAP) and colored dissolved organic matter (CDOM) were measured in the Norwegian [...] Read more.
In August 2020, during the 80th cruise of the R/V “Akademik Mstislav Keldysh”, the chlorophyll a concentration (Chl-a) and spectral coefficients of light absorption by phytoplankton pigments, non-algal particles (NAP) and colored dissolved organic matter (CDOM) were measured in the Norwegian Sea, the Barents Sea and the adjacent area of the Arctic Ocean. It was shown that the spatial distribution of the three light-absorbing components in the explored Arctic region was non-homogenous. It was revealed that CDOM contributed largely to the total non-water light absorption (atot(λ) = aph(λ) + aNAP(λ) + aCDOM(λ)) in the blue spectral range in the Arctic Ocean and the Barents Sea. The fraction of NAP in the total non-water absorption was low (less than 20%). The depth of the euphotic zone depended on atot(λ) in the surface water layer, which was described by a power equation. The Arctic Ocean, the Norwegian Sea and the Barents Sea did not differ in the Chl-a-specific light absorption coefficients of phytoplankton. In the blue maximum of phytoplankton absorption spectra, Chl-a-specific light absorption coefficients of phytoplankton in the upper mixed layer (UML) were higher than those below the UML. Relationships between phytoplankton absorption coefficients and Chl-a were derived by least squares fitting to power functions for the whole visible domain with a 1 nm interval. The OCI, OC3 and GIOP algorithms were validated using a database of co-located results (day-to-day) of in situ measurements (n = 63) and the ocean color scanner data: the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Terra (EOS AM) and Aqua (EOS PM) satellites, the Visible and Infrared Imager/Radiometer Suite (VIIRS) onboard the Suomi National Polar-orbiting Partnership (S-NPP) and JPSS-1 satellites (also known as NOAA-20), and the Ocean and the Land Color Imager (OLCI) onboard the Sentinel-3A and Sentinel-3B satellites. The comparison showed that despite the technological progress in optical scanners and the algorithms refinement, the considered standard products (chlor_a, chl_ocx, aph_443, adg_443) carried little information about inherent optical properties in Arctic waters. Based on the statistic metrics (Bias, MdAD, MAE and RMSE), it was concluded that refinement of the algorithm for retrieval of water bio-optical properties based on remote sensing data was required for the Arctic region. Full article
(This article belongs to the Special Issue Seawater Bio-Optical Characteristics from Satellite Ocean Color Data II)
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20 pages, 2147 KiB  
Article
Blue Color Indices as a Reference for Remote Sensing of Black Sea Water
by Evgeny Shybanov, Anna Papkova, Elena Korchemkina and Vyacheslav Suslin
Remote Sens. 2023, 15(14), 3658; https://doi.org/10.3390/rs15143658 - 22 Jul 2023
Cited by 4 | Viewed by 1639
Abstract
In this paper, we propose to analyze the values of the “blue” color index for further use in additional atmospheric correction of Level 2 remote sensing reflectance data for the waters of the Black Sea. Regardless of seasonal phenomena, atmospheric conditions, and the [...] Read more.
In this paper, we propose to analyze the values of the “blue” color index for further use in additional atmospheric correction of Level 2 remote sensing reflectance data for the waters of the Black Sea. Regardless of seasonal phenomena, atmospheric conditions, and the type of water, the average color index in the short-wave region, according to in situ measurements CI(412/443), varies from 0.77 to 0.83. The most frequently observed value is 0.8. In turn, the values of the “blue” color index CI(412/443) according to the satellite data of MODIS Aqua/Terra, VIIRS SNPP, and OLCI Sentinel 3A scanners showed a large scatter in values based on the standard deviation of the sample. The paper proposes to introduce the value of the minimum allowable threshold CI(412/443) > 0.59 based on the small variance found from in situ measurements, as well as on the basis of a theoretical estimate of the possible values of the index CI(412/443) when varying the backscattering exponent and the exponent for the absorption approximation. The quality check of the remote sensing data showed that, according to this selection criterion, 15% of data are physically incorrect for MODIS Aqua, 30% for MODIS Terra, 20% for Sentinel 3A, and 26% for VIIRS SNPP. In the course of the work, it was shown that the MODIS Aqua satellite provides the most high-quality and reliable information about the optical characteristics of the Black Sea. Full article
(This article belongs to the Special Issue Seawater Bio-Optical Characteristics from Satellite Ocean Color Data II)
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22 pages, 7944 KiB  
Article
Regional Algorithm for Estimating High Coccolithophore Concentration in the Northeastern Part of the Black Sea
by Svetlana Vazyulya, Dmitriy Deryagin, Dmitry Glukhovets, Vladimir Silkin and Larisa Pautova
Remote Sens. 2023, 15(9), 2219; https://doi.org/10.3390/rs15092219 - 22 Apr 2023
Cited by 5 | Viewed by 1754
Abstract
A modified regional algorithm to quantify the coccolithophore concentration in the northeastern part of the Black Sea under conditions of intense bloom is presented. To modify the algorithm, the data of in situ measurements of coccolithophore Emiliania huxleyi abundance performed in June 2017 [...] Read more.
A modified regional algorithm to quantify the coccolithophore concentration in the northeastern part of the Black Sea under conditions of intense bloom is presented. To modify the algorithm, the data of in situ measurements of coccolithophore Emiliania huxleyi abundance performed in June 2017 and 2022 (when the maximum values were 9 × 106 and 13 × 106 Cells L−1, respectively), as well as the data from hydro-optical and satellite measurements, were used. In addition, the ratio between the number of detached coccoliths and coccolithophore cells was taken into account. Based on the expanded array of in situ data, the optimal values of the regional algorithm parameters were obtained. The modified algorithm makes it possible to obtain more accurate results in areas of high coccolithophore concentrations and takes into account the contribution of coccoliths. To test the sensitivity of the algorithm to variations in bio-optical characteristics, model calculations were performed using Hydrolight software. The updated algorithm is significantly less sensitive to variations in chlorophyll concentration and CDOM absorption coefficient than its previous version. Full article
(This article belongs to the Special Issue Seawater Bio-Optical Characteristics from Satellite Ocean Color Data II)
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24 pages, 10876 KiB  
Article
Parameterization of Light Absorption of Phytoplankton, Non-Algal Particles and Coloured Dissolved Organic Matter in the Atlantic Region of the Southern Ocean (Austral Summer of 2020)
by Tatiana Churilova, Natalia Moiseeva, Elena Skorokhod, Tatiana Efimova, Anatoly Buchelnikov, Vladimir Artemiev and Pavel Salyuk
Remote Sens. 2023, 15(3), 634; https://doi.org/10.3390/rs15030634 - 20 Jan 2023
Cited by 5 | Viewed by 2262
Abstract
Climate affects the characteristics of the Southern Ocean ecosystem, including bio-optical properties. Remote sensing is a suitable approach for monitoring a rapidly changing ecosystem. Correct remote assessment can be implemented based on a regional satellite algorithm, which requires parameterization of light absorption by [...] Read more.
Climate affects the characteristics of the Southern Ocean ecosystem, including bio-optical properties. Remote sensing is a suitable approach for monitoring a rapidly changing ecosystem. Correct remote assessment can be implemented based on a regional satellite algorithm, which requires parameterization of light absorption by all optically active components. The aim of this study is to analyse variability in total chlorophyll a concentration (TChl-a), light absorption by phytoplankton, non-algal particles (NAP), coloured dissolved organic matter (CDOM), and coloured detrital matter (CDM = CDOM+NAP), to parameterize absorption by all components. Bio-optical properties were measured in the austral summer of 2020 according to NASA Protocols (2018). High variability (1–2 orders of magnitude) in TChl-a, absorption of phytoplankton, NAP, CDOM, and CDM was revealed. High variability in both CDOM absorption (uncorrelated with TChl-a) and CDOM share in total non-water absorption, resulting in a shift from phytoplankton to CDOM dominance, caused approximately twofold chlorophyll underestimation by global bio-optical algorithms. The light absorption of phytoplankton (for the visible domain in 1 nm steps), NAP, CDOM, and CDM were parametrized. Relationships between the spectral slope coefficient (SCDOM/SCDM) and CDOM (CDM) absorption were revealed. These results can be useful for the development of regional algorithms for Chl-a, CDM, and CDOM monitoring in the Southern Ocean. Full article
(This article belongs to the Special Issue Seawater Bio-Optical Characteristics from Satellite Ocean Color Data II)
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13 pages, 6883 KiB  
Technical Note
Spatio-Temporal Variability of the Aerosol Optical Depth over the Gorky and Cheboksary Reservoirs in 2022–2023
by Darya Kalinskaya and Aleksandr Molkov
Remote Sens. 2023, 15(23), 5455; https://doi.org/10.3390/rs15235455 - 22 Nov 2023
Viewed by 984
Abstract
The present study aimed to investigate atmospheric optical characteristics over the Gorky and Cheboksary Reservoirs and their multi-scale temporal variations to obtain the background characteristics and to identify events involving the transfer of absorbing aerosol to the studied region in 2022–2023. The region [...] Read more.
The present study aimed to investigate atmospheric optical characteristics over the Gorky and Cheboksary Reservoirs and their multi-scale temporal variations to obtain the background characteristics and to identify events involving the transfer of absorbing aerosol to the studied region in 2022–2023. The region is located at a considerable distance (500 km) from the nearest AERONET station; therefore, previous atmospheric data were not available. As a solution, the in situ self-measured aerosol optical depth (AOD) and Angström exponent, as well as satellite products (MAIAC and CALIPSO) for MODIS data, were used. This allowed us to set background values of an AOD of 0.11 at a wavelength of 500 nm and an Angström exponent of 1.2, against their maximum values of 0.38 and 2.5, respectively. To explain these variations, the registered conditions and the microstructure of the dust aerosol over the studied region are presented. For days with background values, the analysis of the particle size distribution data did not show a predominance of any particle size. The optical properties of a smoke aerosol in an atmospheric column are described, and an analysis of the dynamics of particle size variability is presented. A comparative analysis of the optical characteristics of atmospheric aerosol over the Gorky and Cheboksary Reservoirs using in situ and MODIS products was carried out. Full article
(This article belongs to the Special Issue Seawater Bio-Optical Characteristics from Satellite Ocean Color Data II)
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