An attempt to use measurements of sun-induced chlorophyll fluorescence to estimate chlorophyll a concentration in the Baltic Sea

1997 ◽  
Author(s):  
Miroslawa Ostrowska ◽  
Miroslaw Darecki ◽  
Bogdan Wozniak
Keyword(s):  
Chlorophyll Fluorescence ◽  
Baltic Sea ◽  
Chlorophyll A ◽  
The Baltic Sea ◽  
Chlorophyll A Concentration ◽  
The Baltic

scholarly journals Parameterization of the light absorption properties of chromophoric dissolved organic matter in the Baltic Sea and Pomeranian lakes

Ocean Science ◽  
2016 ◽  
Vol 12 (4) ◽  
pp. 1013-1032 ◽  
Author(s):  
Justyna Meler ◽  
Piotr Kowalczuk ◽  
Mirosława Ostrowska ◽  
Dariusz Ficek ◽  
Monika Zabłocka ◽  
...  
Keyword(s):  
Organic Matter ◽  
Dissolved Organic Matter ◽  
Absorption Coefficient ◽  
Baltic Sea ◽  
Chlorophyll A ◽  
Chromophoric Dissolved Organic Matter ◽  
The Baltic Sea ◽  
Absorption Properties ◽  
Chlorophyll A Concentration ◽  
The Baltic

Abstract. This study presents three alternative models for estimating the absorption properties of chromophoric dissolved organic matter aCDOM(λ). For this analysis we used a database containing 556 absorption spectra measured in 2006–2009 in different regions of the Baltic Sea (open and coastal waters, the Gulf of Gdańsk and the Pomeranian Bay), at river mouths, in the Szczecin Lagoon and also in three lakes in Pomerania (Poland) – Obłęskie, Łebsko and Chotkowskie. The variability range of the chromophoric dissolved organic matter (CDOM) absorption coefficient at 400 nm, aCDOM(400), lay within 0.15–8.85 m−1. The variability in aCDOM(λ) was parameterized with respect to the variability over 3 orders of magnitude in the chlorophyll a concentration Chl a (0.7–119 mg m−3). The chlorophyll a concentration and aCDOM(400) were correlated, and a statistically significant, nonlinear empirical relationship between these parameters was derived (R2 =  0.83). On the basis of the covariance between these parameters, we derived two empirical mathematical models that enabled us to design the CDOM absorption coefficient dynamics in natural waters and reconstruct the complete CDOM absorption spectrum in the UV and visible spectral domains. The input variable in the first model was the chlorophyll a concentration, and in the second one it was aCDOM(400). Both models were fitted to a power function, and a second-order polynomial function was used as the exponent. Regression coefficients for these formulas were determined for wavelengths from 240 to 700 nm at 5 nm intervals. Both approximations reflected the real shape of the absorption spectra with a low level of uncertainty. Comparison of these approximations with other models of light absorption by CDOM demonstrated that our parameterizations were superior (bias from −1.45 to 62 %, RSME from 22 to 220 %) for estimating CDOM absorption in the optically complex waters of the Baltic Sea and Pomeranian lakes.

scholarly journals Parameterization of the light absorption properties of chromophoric dissolved organic matter in the Baltic Sea and Pomeranian Lakes

2016 ◽  
Author(s):  
Justyna Meler ◽  
Piotr Kowalczuk ◽  
Mirosława Ostrowska ◽  
Dariusz Ficek ◽  
Monika Zabłocka ◽  
...  
Keyword(s):  
Organic Matter ◽  
Absorption Coefficient ◽  
Baltic Sea ◽  
Chlorophyll A ◽  
Light Absorption ◽  
Chromophoric Dissolved Organic Matter ◽  
The Baltic Sea ◽  
Absorption Properties ◽  
Chlorophyll A Concentration ◽  
The Baltic

Abstract. This study presents three alternative models for estimation of absorption properties of Chromophoric Dissolved Organic Matter, aCDOM(l). For this analysis we used a database containing 556 absorption spectra measured in 2006–2009 in different regions of the Baltic Sea (open and coastal waters, the Gulf of Gdańsk and the Pomeranian Bay), at river mouths, in the Szczecin Lagoon and also in three Pomeranian lakes in Poland – Lakes Obłęskie, Łebsko and Chotkowskie. Observed variability range of the CDOM absorption coefficient at 400 nm, aCDOM(400), contained within 0.15–8.85 m−1. The variability in aCDOM(l) was parameterized with respect to three orders of magnitude variability in the chlorophyll a concentration Chla (0.7–119 mg m−3). Chlorophyll a concentration and CDOM absorption coefficient, aCDOM(400) were correlated, and statistically significant, non-linear empirical relationship between those parameters was derived (R2 = 0.83). Based on observed co-variance between these parameters, we derived two empirical mathematical models that enabled to project the CDOM absorption coefficient dynamics in natural waters and reconstruct the completed CDOM absorption spectrum in the UV and visible spectral domains. The first model used the chlorophyll a concentration as the input variable. The second model used the aCDOM(400), as the input variable. Both models were fitted to power function and the second order polynomial function was used as the exponent. Regression coefficients for derived formulas were determined for wavelengths from 240 to 700 nm at 5 nm intervals . Both approximation reflected the real shape of the absorption spectra with low uncertainty. Comparison of these approximation with other models of light absorption by CDOM proved that proposed parameterizations were better (bias from −1.45 % to 62 %, RSME from 22 % to 220 %) for estimation CDOM absorption in optically complex waters of the Baltic Sea and lakes.

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

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.

scholarly journals Evaluation of atmospheric nitrogen inputs into marine ecosystems of the North Sea and Baltic Sea – part B: contribution by shipping and agricultural emissions

2018 ◽  
Author(s):  
Daniel Neumann ◽  
Hagen Radtke ◽  
Matthias Karl ◽  
Thomas Neumann
Keyword(s):  
Baltic Sea ◽  
Nitrogen Deposition ◽  
Chlorophyll A ◽  
North Sea ◽  
Atmospheric Nitrogen Deposition ◽  
Atmospheric Nitrogen ◽  
The Baltic Sea ◽  
The North ◽  
The North Sea ◽  
The Baltic

Abstract. Atmospheric nitrogen deposition constitutes 20 % to 40 % of the nitrogen input into the North Sea and the Baltic Sea contributing to phytoplankton growth and inducing eutrophication. Major contributors to the atmospheric nitrogen emissions in the vicinity of marine water bodies are shipping and agricultural activities. The contribution of individual emission sectors to the biogeochemical nitrogen cycle needs to be evaluated in order to assess improvement of marine water quality through emission reductions of these sectors. Hence, one focus of this modeling study was to evaluate the contribution of total, shipping-related, and agricultural-related nitrogen deposition to dissolved inorganic nitrogen (DIN), particulate organic nitrogen (PON), chlorophyll-a. A second focus of this study was to compare both water bodies with respect to the accumulation and processing of nitrogen from the mentioned sources. These two research questions were evaluated by a modeling study with the coupled physical-biogeochemical model HBM-ERGOM. The fate of atmospheric deposition in total and of atmospheric nitrogen deposition from two individual sources – shipping and agricultural activities – was traced in the marine ecosystem by a tagging method. In the Baltic Sea it was found that the atmospheric nitrogen deposition contributes up to 50 % to the DIN pool at individual locations during summer. On annual average, 13 % are contributed. Approximately 5 % of DIN originated from agricultural activities and 2 % from the shipping sector. In the western and central Baltic Sea, the shipping sector contributed nearly 5 %. The pattern was similar for the agricultural share indicating that these two sources have a higher relevance in these regions. In the Baltic Sea, the atmospheric nitrogen shares of chlorophyll-a and bioavailable PON were 19 % and 18 %, respectively, and, hence, higher than of DIN. In contrast in offshore regions only, atmospheric nitrogen shares to DIN, PON, and chlorophyll-a were on a similar level compared to each other (20 % to 35 %). This difference is caused by high DIN loads and phosphorus limitation in coastal regions of the Baltic Sea. In the North Sea, the atmospheric contribution to DIN was on a similar level but showed considerable spatial variability caused by a north-south gradient. The shipping contribution to DIN was slightly lower (approximately 1.4 %) and the agricultural contribution higher (6 %) compared to the Baltic Sea. The atmospheric contribution to chlorophyll-a and bioavailable PON was considerably lower than in the Baltic Sea and on the level of the atmospheric DIN shares, which is a result of short residence times of nutrients in the North Sea compared to the Baltic Sea. The shipping and agricultural contributions to PON and chlorophyll-a were also lower.

scholarly journals Multidecadal time series of satellite-detected accumulations of cyanobacteria in the Baltic Sea

2014 ◽  
Vol 11 (13) ◽  
pp. 3619-3633 ◽  
Author(s):  
M. Kahru ◽  
R. Elmgren
Keyword(s):  
Time Series ◽  
Baltic Sea ◽  
Chlorophyll A ◽  
Interannual Variations ◽  
The Baltic Sea ◽  
Decadal Scale ◽  
Long Time ◽  
Areal Fraction ◽  
Extensive Surface ◽  
The Baltic

Abstract. Cyanobacteria, primarily of the species \\textit{Nodularia spumigena}, form extensive surface accumulations in the Baltic Sea in July and August, ranging from diffuse flakes to dense surface scums. The area of these accumulations can reach ~ 200 000 km2. We describe the compilation of a 35-year-long time series (1979–2013) of cyanobacteria surface accumulations in the Baltic Sea using multiple satellite sensors. This appears to be one of the longest satellite-based time series in biological oceanography. The satellite algorithm is based on remote sensing reflectance of the water in the red band, a measure of turbidity. Validation of the satellite algorithm using horizontal transects from a ship of opportunity showed the strongest relationship with phycocyanin fluorescence (an indicator of cyanobacteria), followed by turbidity and then by chlorophyll a fluorescence. The areal fraction with cyanobacteria accumulations (FCA) and the total accumulated area affected (TA) were used to characterize the intensity and extent of the accumulations. The fraction with cyanobacteria accumulations was calculated as the ratio of the number of detected accumulations to the number of cloud-free sea-surface views per pixel during the season (July–August). The total accumulated area affected was calculated by adding the area of pixels where accumulations were detected at least once during the season. The fraction with cyanobacteria accumulations and TA were correlated (R2 = 0.55) and both showed large interannual and decadal-scale variations. The average FCA was significantly higher for the second half of the time series (13.8%, 1997–2013) than for the first half (8.6%, 1979–1996). However, that does not seem to represent a long-term trend but decadal-scale oscillations. Cyanobacteria accumulations were common in the 1970s and early 1980s (FCA between 11–17%), but rare (FCA below 4%) during 1985–1990; they increased again starting in 1991 and particularly in 1999, reaching maxima in FCA (~ 25%) and TA (~ 210 000 km2) in 2005 and 2008. After 2008, FCA declined to more moderate levels (6–17%). The timing of the accumulations has become earlier in the season, at a mean rate of 0.6 days per year, resulting in approximately 20 days advancement during the study period. The interannual variations in FCA are positively correlated with the concentration of chlorophyll a during July–August sampled at the depth of ~ 5 m by a ship of opportunity, but interannual variations in FCA are more pronounced as the coefficient of variation is over 5 times higher.

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 Satellite detection of multi-decadal time series of cyanobacteria accumulations in the Baltic Sea

2014 ◽  
Vol 11 (2) ◽  
pp. 3319-3364 ◽  
Author(s):  
M. Kahru ◽  
R. Elmgren
Keyword(s):  
Time Series ◽  
Baltic Sea ◽  
Chlorophyll A ◽  
Interannual Variations ◽  
The Baltic Sea ◽  
Decadal Scale ◽  
Long Time ◽  
Areal Fraction ◽  
Extensive Surface ◽  
The Baltic

Abstract. Cyanobacteria, primarily of the species Nodularia spumigena, form extensive surface accumulations in the Baltic Sea in July and August, ranging from diffuse flakes to dense surface scum. We describe the compilation of a 35 year (1979–2013) long time series of cyanobacteria surface accumulations in the Baltic Sea using multiple satellite sensors. This appears to be one of the longest satellite-based time series in biological oceanography. The satellite algorithm is based on increased remote sensing reflectance of the water in the red band, a measure of turbidity. Validation of the satellite algorithm using horizontal transects from a ship of opportunity showed the strongest relationship with phycocyanin fluorescence (an indicator of cyanobacteria), followed by turbidity and then by chlorophyll a fluorescence. The areal fraction with cyanobacteria accumulations (FCA) and the total accumulated area affected (TA) were used to characterize the intensity and extent of the accumulations. FCA was calculated as the ratio of the number of detected accumulations to the number of cloud free sea-surface views per pixel during the season (July–August). TA was calculated by adding the area of pixels where accumulations were detected at least once during the season. FCA and TA were correlated (R2 = 0.55) and both showed large interannual and decadal-scale variations. The average FCA was significantly higher for the 2nd half of the time series (13.8%, 1997–2013) than for the first half (8.6%, 1979–1996). However, that does not seem to represent a long-term trend but decadal-scale oscillations. Cyanobacteria accumulations were common in the 1970s and early 1980s (FCA between 11–17%), but rare (FCA below 4%) from 1985 to 1990; they increased again from 1991 and particularly from 1999, reaching maxima in FCA (~ 25%) and TA (~ 210 000 km2) in 2005 and 2008. After 2008 FCA declined to more moderate levels (6–17%). The timing of the accumulations has become earlier in the season, at a~mean rate of 0.6 days per year, resulting in approximately 20 days advancement during the study period. The interannual variations in FCA are positively correlated with the concentration of chlorophyll a in July–August sampled at the depth of ~ 5 m by a ship of opportunity program, but interannual variations in FCA are more pronounced.

scholarly journals Comparison of satellite chlorophyll a algorithms for the Baltic Sea

2014 ◽  
Vol 8 (1) ◽  
pp. 083605 ◽  
Author(s):  
Monika Wozniak ◽  
Katarzyna M. Bradtke ◽  
Adam Krezel
Keyword(s):  
Baltic Sea ◽  
Chlorophyll A ◽  
The Baltic Sea ◽  
The Baltic ◽  
Satellite Chlorophyll
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