scholarly journals Upwelling-induced trace gas dynamics in the Baltic Sea inferred from 8 years of autonomous measurements on a ship of opportunity

2021 ◽  
Vol 18 (8) ◽  
pp. 2679-2709
Author(s):  
Erik Jacobs ◽  
Henry C. Bittig ◽  
Ulf Gräwe ◽  
Carolyn A. Graves ◽  
Michael Glockzin ◽  
...  
Keyword(s):  
Baltic Sea ◽  
Gas Dynamics ◽  
Coastal Upwelling ◽  
Regional Distribution ◽  
Trace Gas ◽  
Data Sets ◽  
The Baltic Sea ◽  
Spatial And Temporal Scales ◽  
In Situ Data ◽  
The Baltic

Abstract. Autonomous measurements aboard ships of opportunity (SOOP) provide in situ data sets with high spatial and temporal coverage. In this study, we use 8 years of carbon dioxide (CO2) and methane (CH4) observations from SOOP Finnmaid to study the influence of upwelling on trace gas dynamics in the Baltic Sea. Between spring and autumn, coastal upwelling transports water masses enriched with CO2 and CH4 to the surface of the Baltic Sea. We study the seasonality, regional distribution, relaxation, and interannual variability in this process. We use reanalysed wind and modelled sea surface temperature (SST) data in a newly established statistical upwelling detection method to identify major upwelling areas and time periods. Large upwelling-induced SST decrease and trace gas concentration increase are most frequently detected around August after a long period of thermal stratification, i.e. limited exchange between surface and underlying waters. We found that these upwelling events with large SST excursions shape local trace gas dynamics and often lead to near-linear relationships between increasing trace gas levels and decreasing temperature. Upwelling relaxation is mainly driven by mixing, modulated by air–sea gas exchange, and possibly primary production. Subsequent warming through air–sea heat exchange has the potential to enhance trace gas saturation. In 2015, quasi-continuous upwelling over several months led to weak summer stratification, which directly impacted the observed trace gas and SST dynamics in several upwelling-prone areas. Trend analysis is still prevented by the observed high variability, uncertainties from data coverage, and long water residence times of 10–30 years. We introduce an extrapolation method based on trace gas–SST relationships that allows us to estimate upwelling-induced trace gas fluxes in upwelling-affected regions. In general, the surface water reverses from CO2 sink to source, and CH4 outgassing is intensified as a consequence of upwelling. We conclude that SOOP data, especially when combined with other data sets, enable flux quantification and process studies addressing the process of upwelling on large spatial and temporal scales.

scholarly journals Upwelling-induced trace gas dynamics in the Baltic Sea inferred from 8 years of autonomous measurements on a ship of opportunity

2020 ◽  
Author(s):  
Erik Jacobs ◽  
Henry C. Bittig ◽  
Ulf Gräwe ◽  
Carolyn A. Graves ◽  
Michael Glockzin ◽  
...  
Keyword(s):  
Baltic Sea ◽  
Gas Dynamics ◽  
Coastal Upwelling ◽  
Regional Distribution ◽  
Trace Gas ◽  
Data Sets ◽  
The Baltic Sea ◽  
Spatial And Temporal Scales ◽  
In Situ Data ◽  
The Baltic

Abstract. Autonomous measurements aboard ships of opportunity (SOOP) provide in situ data sets with high spatial and temporal coverage. In this study, we use 8 years of carbon dioxide (CO2) and methane (CH4) observations from SOOP Finnmaid to study the influence of upwelling on trace gas dynamics in the Baltic Sea. Between spring and autumn, coastal upwelling transports water masses enriched with CO2 and CH4 to the surface of the Baltic Sea. We study the seasonality, regional distribution, relaxation, and interannual variability of this process. We use reanalysed wind and modelled sea surface temperature (SST) data in a newly established statistical upwelling detection method to identify major upwelling areas and time periods. Strong upwelling events are most frequently detected around August after a long period of thermal stratification, i.e. limited exchange between surface and underlying waters. We found that these strong upwelling events with large SST excursions shape local trace gas dynamics and often lead to near-linear relationships between increasing trace gas levels and decreasing temperature. Upwelling relaxation is mainly driven by mixing and modulated by air–sea gas exchange and possibly primary production. Subsequent warming through air–sea heat exchange has the potential to enhance trace gas saturation. In 2015, quasi-continuous upwelling over several months led to weak summer stratification, which directly impacted the observed trace gas and SST dynamics in several upwelling-prone areas. We introduce an extrapolation method based on trace gas – SST relationships that allows us to estimate upwelling-induced trace gas fluxes in upwelling-affected regions. In general, the surface water reverses from CO2 sink to source and CH4 outgassing is intensified as a consequence of upwelling. We conclude that upwelling is an important and relevant process controlling trace gas dynamics in near-coastal environments in the Baltic Sea, and that SOOP data, especially when combined with other data sets, enable flux quantification and process studies on larger spatial and temporal scales.

scholarly journals Comparisons of Satellite and Modeled Surface Temperature and Chlorophyll Concentrations in the Baltic Sea with In Situ Data

2021 ◽  
Vol 13 (15) ◽  
pp. 3049
Author(s):  
Malgorzata Stramska ◽  
Marta Konik ◽  
Paulina Aniskiewicz ◽  
Jaromir Jakacki ◽  
Miroslaw Darecki
Keyword(s):  
Baltic Sea ◽  
Satellite Data ◽  
In Situ Measurements ◽  
Data Sets ◽  
The Baltic Sea ◽  
Data Set ◽  
In Situ Data ◽  
The Baltic ◽  
Good Agreement

Among the most frequently used satellite data are surface chlorophyll concentration (Chl) and temperature (SST). These data can be degraded in some coastal areas, for example, in the Baltic Sea. Other popular sources of data are reanalysis models. Before satellite or model data can be used effectively, they should be extensively compared with in situ measurements. Herein, we present results of such comparisons. We used SST and Chl from model reanalysis and satellites, and in situ data measured at eight open Baltic Sea stations. The data cover time interval from 1 January 1998 to 31 December 2019, but some satellite data were not always available. Both the model and the satellite SST data had good agreement with in situ measurements. In contrast, satellite and model estimates of Chl concentrations presented large errors. Modeled Chl presented the lowest bias and the best correlation with in situ data from all Chl data sets evaluated. Chl estimates from a regionally tuned algorithm (SatBaltic) had smaller errors in comparison with other satellite data sets and good agreement with in situ data in summer. Statistics were not as good for the full data set. High uncertainties found in chlorophyll satellite algorithms for the Baltic Sea highlight the importance of continuous regional validation of such algorithms with in situ data.

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.

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.

scholarly journals Mechanisms of variability in decadal sea-level trends in the Baltic Sea over the 20th century

2017 ◽  
Vol 8 (4) ◽  
pp. 1031-1046 ◽  
Author(s):  
Sitar Karabil ◽  
Eduardo Zorita ◽  
Birgit Hünicke
Keyword(s):  
Regression Model ◽  
Baltic Sea ◽  
Sea Level ◽  
Atmospheric Circulation ◽  
Data Sets ◽  
Climatic Data ◽  
The Baltic Sea ◽  
Underlying Factor ◽  
Coastal Sea ◽  
The Baltic

Abstract. Coastal sea-level trends in the Baltic Sea display decadal-scale variations around a long-term centennial trend. In this study, we analyse the spatial and temporal characteristics of the decadal trend variations and investigate the links between coastal sea-level trends and atmospheric forcing on a decadal timescale. For this analysis, we use monthly means of sea-level and climatic data sets. The sea-level data set is composed of long tide gauge records and gridded sea surface height (SSH) reconstructions. Climatic data sets are composed of sea-level pressure, air temperature, precipitation, evaporation, and climatic variability indices. The analysis indicates that atmospheric forcing is a driving factor of decadal sea-level trends. However, its effect is geographically heterogeneous. This impact is large in the northern and eastern regions of the Baltic Sea. In the southern Baltic Sea area, the impacts of atmospheric circulation on decadal sea-level trends are smaller. To identify the influence of the large-scale factors other than the effect of atmospheric circulation in the same season on Baltic Sea sea-level trends, we filter out the direct signature of atmospheric circulation for each season separately on the Baltic Sea level through a multivariate linear regression model and analyse the residuals of this regression model. These residuals hint at a common underlying factor that coherently drives the decadal sea-level trends in the whole Baltic Sea. We found that this underlying effect is partly a consequence of decadal precipitation trends in the Baltic Sea basin in the previous season. The investigation of the relation between the AMO index and sea-level trends implies that this detected underlying factor is not connected to oceanic forcing driven from the North Atlantic region.

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.

Wind conditions over the Baltic Sea – comparing reanalysis data sets with observations

2020 ◽  
Author(s):  
Christoffer Hallgren ◽  
Erik Sahlée ◽  
Stefan Ivanell ◽  
Heiner Körnich ◽  
Ville Vakkari
Keyword(s):  
Baltic Sea ◽  
Wind Power ◽  
Reanalysis Data ◽  
Data Sets ◽  
The Baltic Sea ◽  
Data Set ◽  
Low Level ◽  
Seasonal And Diurnal Variations ◽  
Low Level Jets ◽  
The Baltic

&lt;p&gt;The potential of increasing the amount of offshore wind energy production in the Baltic Sea has been of great interest for many countries and wind power companies for a long time. From a meteorological point of view, there are several special wind characteristics that are observed in this area that needs to be taken into consideration when planning for a wind farm. For example, as the Baltic Sea is a semi-enclosed basin surrounded by coastlines in all directions, phenomenon such as low-level jets occur frequently.&lt;/p&gt;&lt;p&gt;In order to create a climatology of the wind conditions over the Baltic Sea, with wind power applications in mind, four different state-of-the-art reanalysis data sets (MERRA2, ERA5, UERRA and NEWA) have been compared with measurements from LIDAR systems and high meteorological towers (Anholt, Finnish Ut&amp;#246;, FINO2 and &amp;#214;stergarnsholm). The performance of the data sets has been analyzed in terms of stability and governing synoptic weather conditions as well as seasonal and diurnal variations. By selecting the most suitable reanalysis data set and using the observations to make corrections, a climatology for wind conditions over the Baltic Sea, focusing on the low-level jets, has then been constructed.&lt;/p&gt;

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