scholarly journals Consistency between Satellite Ocean Colour Products under High Coloured Dissolved Organic Matter Absorption in the Baltic Sea

2021 ◽  
Vol 14 (1) ◽  
pp. 89
Author(s):  
Gavin H. Tilstone ◽  
Silvia Pardo ◽  
Stefan G. H. Simis ◽  
Ping Qin ◽  
Nick Selmes ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Baltic Sea ◽  
Atmospheric Correction ◽  
Relative Difference ◽  
Global Ocean ◽  
Ocean Colour ◽  
The Baltic Sea ◽  
Chl A ◽  
The Baltic

Ocean colour (OC) remote sensing is an important tool for monitoring phytoplankton in the global ocean. In optically complex waters such as the Baltic Sea, relatively efficient light absorption by substances other than phytoplankton increases product uncertainty. Sentinel-3 OLCI-A, Suomi-NPP VIIRS and MODIS-Aqua OC radiometric products were assessed using Baltic Sea in situ remote sensing reflectance (Rrs) from ferry tracks (Alg@line) and at two Aerosol Robotic Network for Ocean Colour (AERONET-OC) sites from April 2016 to September 2018. A range of atmospheric correction (AC) processors for OLCI-A were evaluated. POLYMER performed best with <23 relative % difference at 443, 490 and 560 nm compared to in situ Rrs and 28% at 665 nm, suggesting that using this AC for deriving Chl a will be the most accurate. Suomi-VIIRS and MODIS-Aqua underestimated Rrs by 35, 29, 22 and 39% and 34, 22, 17 and 33% at 442, 486, 560 and 671 nm, respectively. The consistency between different AC processors for OLCI-A and MODIS-Aqua and VIIRS products was relatively poor. Applying the POLYMER AC to OLCI-A, MODIS-Aqua and VIIRS may produce the most accurate Rrs and Chl a products and OC time series for the Baltic Sea.

scholarly journals Remote Sensing Supported Sea Surface pCO2 Estimation and Variable Analysis in the Baltic Sea

2021 ◽  
Vol 13 (2) ◽  
pp. 259
Author(s):  
Shuping Zhang ◽  
Anna Rutgersson ◽  
Petra Philipson ◽  
Marcus B. Wallin
Keyword(s):  
Remote Sensing ◽  
Baltic Sea ◽  
Mean Squared Error ◽  
Numerical Models ◽  
Mixed Layer Depth ◽  
Sea Surface ◽  
The Baltic Sea ◽  
Chl A ◽  
Marginal Seas ◽  
The Baltic

Marginal seas are a dynamic and still to large extent uncertain component of the global carbon cycle. The large temporal and spatial variations of sea-surface partial pressure of carbon dioxide (pCO2) in these areas are driven by multiple complex mechanisms. In this study, we analyzed the variable importance for the sea surface pCO2 estimation in the Baltic Sea and derived monthly pCO2 maps for the marginal sea during the period of July 2002–October 2011. We used variables obtained from remote sensing images and numerical models. The random forest algorithm was employed to construct regression models for pCO2 estimation and produce the importance of different input variables. The study found that photosynthetically available radiation (PAR) was the most important variable for the pCO2 estimation across the entire Baltic Sea, followed by sea surface temperature (SST), absorption of colored dissolved organic matter (aCDOM), and mixed layer depth (MLD). Interestingly, Chlorophyll-a concentration (Chl-a) and the diffuse attenuation coefficient for downwelling irradiance at 490 nm (Kd_490nm) showed relatively low importance for the pCO2 estimation. This was mainly attributed to the high correlation of Chl-a and Kd_490nm to other pCO2-relevant variables (e.g., aCDOM), particularly in the summer months. In addition, the variables’ importance for pCO2 estimation varied between seasons and sub-basins. For example, the importance of aCDOM were large in the Gulf of Finland but marginal in other sub-basins. The model for pCO2 estimate in the entire Baltic Sea explained 63% of the variation and had a root of mean squared error (RMSE) of 47.8 µatm. The pCO2 maps derived with this model displayed realistic seasonal variations and spatial features of sea surface pCO2 in the Baltic Sea. The spatially and seasonally varying variables’ importance for the pCO2 estimation shed light on the heterogeneities in the biogeochemical and physical processes driving the carbon cycling in the Baltic Sea and can serve as an important basis for future pCO2 estimation in marginal seas using remote sensing techniques. The pCO2 maps derived in this study provided a robust benchmark for understanding the spatiotemporal patterns of CO2 air-sea exchange in the Baltic Sea.

scholarly journals Evaluation of Sentinel-3A OLCI Products Derived Using the Case-2 Regional CoastColour Processor over the Baltic Sea

Sensors ◽  
2019 ◽  
Vol 19 (16) ◽  
pp. 3609 ◽  
Author(s):  
Kyryliuk ◽  
Kratzer
Keyword(s):  
Remote Sensing ◽  
Baltic Sea ◽  
Attenuation Coefficient ◽  
Secchi Depth ◽  
Local Algorithm ◽  
The Baltic Sea ◽  
In Situ Data ◽  
The Baltic ◽  
Level 2

In this study, the Level-2 products of the Ocean and Land Colour Instrument (OLCI) data on Sentinel-3A are derived using the Case-2 Regional CoastColour (C2RCC) processor for the SentiNel Application Platform (SNAP) whilst adjusting the specific scatter of Total Suspended Matter (TSM) for the Baltic Sea in order to improve TSM retrieval. The remote sensing product “kd_z90max” (i.e., the depth of the water column from which 90% of the water-leaving irradiance are derived) from C2RCC-SNAP showed a good correlation with in situ Secchi depth (SD). Additionally, a regional in-water algorithm was applied to derive SD from the attenuation coefficient Kd(489) using a local algorithm. Furthermore, a regional in-water relationship between particle scatter and bench turbidity was applied to generate turbidity from the remote sensing product “iop_bpart” (i.e., the scattering coefficient of marine particles at 443 nm). The spectral shape of the remote sensing reflectance (Rrs) data extracted from match-up stations was evaluated against reflectance data measured in situ by a tethered Attenuation Coefficient Sensor (TACCS) radiometer. The L2 products were evaluated against in situ data from several dedicated validation campaigns (2016–2018) in the NW Baltic proper. All derived L2 in-water products were statistically compared to in situ data and the results were also compared to results for MERIS validation from the literature and the current S3 Level-2 Water (L2W) standard processor from EUMETSAT. The Chl-a product showed a substantial improvement (MNB 21%, RMSE 88%, APD 96%, n = 27) compared to concentrations derived from the Medium Resolution Imaging Spectrometer (MERIS), with a strong underestimation of higher values. TSM performed within an error comparable to MERIS data with a mean normalized bias (MNB) 25%, root-mean square error (RMSE) 73%, average absolute percentage difference (APD) 63% n = 23). Coloured Dissolved Organic Matter (CDOM) absorption retrieval has also improved substantially when using the product “iop_adg” (i.e., the sum of organic detritus and Gelbstoff absorption at 443 nm) as a proxy (MNB 8%, RMSE 56%, APD 54%, n = 18). The local SD (MNB 6%, RMSE 62%, APD 60%, n = 35) and turbidity (MNB 3%, RMSE 35%, APD 34%, n = 29) algorithms showed very good agreement with in situ data. We recommend the use of the SNAP C2RCC with regionally adjusted TSM-specific scatter for water product retrieval as well as the regional turbidity algorithm for Baltic Sea monitoring. Besides documenting the evaluation of the C2RCC processor, this paper may also act as a handbook on the validation of Ocean Colour data.

Mapping seagrass and water depths using Sentinel-2

2020 ◽  
Author(s):  
Katja Kuhwald ◽  
Philipp Held ◽  
Florian Gausepohl ◽  
Jens Schneider von Deimling ◽  
Natascha Oppelt
Keyword(s):  
Remote Sensing ◽  
Baltic Sea ◽  
Atmospheric Correction ◽  
The Baltic Sea ◽  
Seagrass Meadows ◽  
Spatial Coverage ◽  
Acoustic Methods ◽  
The Baltic ◽  
Water Depths ◽  
Sentinel 2

&lt;p&gt;Seagrass meadows cover large benthic areas of the Baltic Sea, but eutrophication and climate change imply declining seagrass coverage. Apart from acoustic methods and traditional diver mappings, optical remote sensing techniques allow for mapping seagrass. Optical satellite analyses of seagrass mapping may supplement acoustic methods in shallow coastal waters with observations that are more frequent and have a larger spatial coverage.&lt;/p&gt;&lt;p&gt;In the clear Greek Mediterranean Sea, Sentinel-2 was already applied successfully to detect bathymetry and seagrass meadows. We are now testing whether Sentinel-2 data are also suitable for analysing the sublittoral in the turbid waters of the Baltic Sea. We focus on an extensive shallow water area near Kiel/Germany. Based on Sentinel-2 data, we analyse water depth and differentiate between seagrass covered and bare sandy ground. We derive these parameters using empirical and process-based models. First results show that Sentinel-2 allows to determine water depths up to 4 m (RMSE ~ 0.2 m). Comparisons with LiDAR water depths show that inaccuracies increase in overgrown areas. Our study also shows that the atmospheric correction algorithm influences sublittoral ground mappings with Sentinel-2 data. For instance, the absolute water depths of the process-based modelling differ up to 2.5 m on average depending on the atmospheric correction algorithm (ACOLITE, Sen2Cor, iCOR).&lt;/p&gt;&lt;p&gt;Comparing Sentinel-2 seagrass classifications with diver mappings and aerial imagery emphasises that empiric approaches provide plausible sublittoral ground classifications up to approximately 4 m water depth. Combining these results with seagrass mappings based on acoustic measurements (deeper than 4 m water) provides a synthesised sublittoral classification map of the study area up to the present growth limit of seagrass (~ 7 m in the study area).&lt;/p&gt;&lt;p&gt;The Baltic Sea is considered as a very&amp;#160;turbid environment, nevertheless we show that satellite-based remote sensing has a great potential for shedding light into the&amp;#160; &quot;white ribbon&quot;. The spatial coverage and temporal resolution of the analysed Sentinel-2 data increases the knowledge about the occurrence of seagrass and its spatio-temporal dynamics. Nevertheless, the influence of the selected atmospheric correction approach on the results shows that further research in remote sensing is necessary to assess seagrass meadows reliably.&lt;/p&gt;

scholarly journals Satellite Remote Sensing Signatures of the Major Baltic Inflows

2019 ◽  
Vol 11 (8) ◽  
pp. 954
Author(s):  
Malgorzata Stramska ◽  
Paulina Aniskiewicz
Keyword(s):  
Remote Sensing ◽  
Baltic Sea ◽  
Large Scale ◽  
Spatial Information ◽  
The Baltic Sea ◽  
Salty Water ◽  
In Situ Data ◽  
The North ◽  
The Baltic

Variability of sea level in the North and Baltic Seas, enforced by weather patterns, affects the intensity of water exchange between these seas. Transfer of salty water from the North Sea is very important for the hydrography of the Baltic Sea. The volume of inflowing salty water can occasionally increase remarkably. Such incidents, called the Major Baltic Inflows (MBIs), are unpredictable, of relatively short duration, and difficult to observe using in situ data. We have shown that remote sensing altimetry can be used as a complementary source of information about the MBI events. The advantage of using such data is that large-scale spatial information about SLA is available with daily resolution. We have described changes in SLA during several MBI events observed in 1993–2017. The net volume of water transported into the Baltic Sea varied between the events due to differences in atmospheric forcing. Based on SLA data, the largest inflow of water happened during the 2014 MBI. This is in agreement with previously published results, based on in situ data.

scholarly journals Phytoplankton Bloom Dynamics in the Baltic Sea Using a Consistently Reprocessed Time Series of Multi-Sensor Reflectance and Novel Chlorophyll-a Retrievals

2021 ◽  
Vol 13 (16) ◽  
pp. 3071
Author(s):  
Vittorio E. Brando ◽  
Michela Sammartino ◽  
Simone Colella ◽  
Marco Bracaglia ◽  
Annalisa Di Cicco ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Time Series ◽  
Baltic Sea ◽  
Chlorophyll A ◽  
Atmospheric Correction ◽  
Quantitative Description ◽  
Cyanobacterial Blooms ◽  
The Baltic Sea ◽  
Sensing Applications ◽  
The Baltic

A relevant indicator for the eutrophication status in the Baltic Sea is the Chlorophyll-a concentration ( ). Alas, ocean color remote sensing applications to estimate in this brackish basin, characterized by large gradients in salinity and dissolved organic matter, are hampered by its optical complexity and atmospheric correction limits. This study presents retrieval improvements for a fully reprocessed multi-sensor time series of remote-sensing reflectances () at ~1 km spatial resolution for the Baltic Sea. A new ensemble scheme based on multilayer perceptron neural net (MLP) bio-optical algorithms has been implemented to this end. The study documents that this approach outperforms band-ratio algorithms when compared to in situ datasets, reducing the gross overestimates of observed in the literature for this basin. The and time series were then exploited for eutrophication monitoring, providing a quantitative description of spring and summer phytoplankton blooms in the Baltic Sea over 1998–2019. The analysis of the phytoplankton dynamics enabled the identification of the latitudinal variations in the spring bloom phenology across the basin, the early blooming in spring in the last two decades, and the description of the spatiotemporal coverage of summer cyanobacterial blooms in the central and southern Baltic Sea.

scholarly journals Testing the performance of empirical remote sensing algorithms in the Baltic Sea waters with modelled and in situ reflectance data

Oceanologia ◽  
2017 ◽  
Vol 59 (1) ◽  
pp. 57-68 ◽  
Author(s):  
Martin Ligi ◽  
Tiit Kutser ◽  
Kari Kallio ◽  
Jenni Attila ◽  
Sampsa Koponen ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Baltic Sea ◽  
The Baltic Sea ◽  
The Baltic ◽  
Reflectance Data

scholarly journals In-Situ Evaluation of the Protectivity of Coatings Applied to Metal Cultural Artefacts Using Non-Destructive Electrochemical Measurements

2021 ◽  
Vol 2 (1) ◽  
pp. 120-132
Author(s):  
Douglas J. Mills ◽  
Katarzyna Schaefer ◽  
Tomasz Wityk
Keyword(s):  
Baltic Sea ◽  
Electrochemical Noise ◽  
Organic Coating ◽  
Noise Measurement ◽  
The Baltic Sea ◽  
Coating Type ◽  
The Baltic ◽  
Non Destructive ◽  
Electrolytic Resistance

Electrochemical Noise Measurement (ENM) and DC electrolytic resistance measurement (ERM) can be used to assess the level of protectiveness provided by an organic coating (paint or varnish) to the underlying metal. These techniques also have applicability to the thinner, transparent type of coatings used to protect archaeological artefacts. Two studies are presented here demonstrating how ERM and ENM techniques can be applied in artefact preservation. The similarity of the techniques, both of which are a measure of resistance, means results can be considered to be analogous. The first study investigated the use of ERM to determine the protection levels provided by typical coatings in order to develop a database of coating type and application for objects, for specific environments. The second study used ENM to evaluate coatings which had been applied to historic artefacts recovered from shipwrecks in the Baltic Sea and displayed inside the museum or kept in the museum store area. The studies showed the usefulness of both techniques for determining the level of protection of a coating and how a better performing coating can be specified if a pre-existing coating on an artefact has been found to be unsuitable.

scholarly journals Effect of ocean acidification and elevated <i>f</i>CO<sub>2</sub> on trace gas production by a Baltic Sea summer phytoplankton community

2016 ◽  
Vol 13 (15) ◽  
pp. 4595-4613 ◽  
Author(s):  
Alison L. Webb ◽  
Emma Leedham-Elvidge ◽  
Claire Hughes ◽  
Frances E. Hopkins ◽  
Gill Malin ◽  
...  
Keyword(s):  
Baltic Sea ◽  
Large Scale ◽  
Gas Production ◽  
Trace Gas ◽  
Research Station ◽  
The Baltic Sea ◽  
Chl A ◽  
The Baltic ◽  
Upwelling Event ◽  
Ambient Co2

Abstract. The Baltic Sea is a unique environment as the largest body of brackish water in the world. Acidification of the surface oceans due to absorption of anthropogenic CO2 emissions is an additional stressor facing the pelagic community of the already challenging Baltic Sea. To investigate its impact on trace gas biogeochemistry, a large-scale mesocosm experiment was performed off Tvärminne Research Station, Finland, in summer 2012. During the second half of the experiment, dimethylsulfide (DMS) concentrations in the highest-fCO2 mesocosms (1075–1333 µatm) were 34 % lower than at ambient CO2 (350 µatm). However, the net production (as measured by concentration change) of seven halocarbons analysed was not significantly affected by even the highest CO2 levels after 5 weeks' exposure. Methyl iodide (CH3I) and diiodomethane (CH2I2) showed 15 and 57 % increases in mean mesocosm concentration (3.8 ± 0.6 increasing to 4.3 ± 0.4 pmol L−1 and 87.4 ± 14.9 increasing to 134.4 ± 24.1 pmol L−1 respectively) during Phase II of the experiment, which were unrelated to CO2 and corresponded to 30 % lower Chl a concentrations compared to Phase I. No other iodocarbons increased or showed a peak, with mean chloroiodomethane (CH2ClI) concentrations measured at 5.3 (±0.9) pmol L−1 and iodoethane (C2H5I) at 0.5 (±0.1) pmol L−1. Of the concentrations of bromoform (CHBr3; mean 88.1 ± 13.2 pmol L−1), dibromomethane (CH2Br2; mean 5.3 ± 0.8 pmol L−1), and dibromochloromethane (CHBr2Cl, mean 3.0 ± 0.5 pmol L−1), only CH2Br2 showed a decrease of 17 % between Phases I and II, with CHBr3 and CHBr2Cl showing similar mean concentrations in both phases. Outside the mesocosms, an upwelling event was responsible for bringing colder, high-CO2, low-pH water to the surface starting on day t16 of the experiment; this variable CO2 system with frequent upwelling events implies that the community of the Baltic Sea is acclimated to regular significant declines in pH caused by up to 800 µatm fCO2. After this upwelling, DMS concentrations declined, but halocarbon concentrations remained similar or increased compared to measurements prior to the change in conditions. Based on our findings, with future acidification of Baltic Sea waters, biogenic halocarbon emissions are likely to remain at similar values to today; however, emissions of biogenic sulfur could significantly decrease in this region.

Sign in / Sign up

Export Citation Format

Share Document