scholarly journals Cyanobacteria net community production in the Baltic Sea as inferred from profiling <i>p</i>CO<sub>2</sub> measurements

2021 ◽  
Vol 18 (17) ◽  
pp. 4889-4917
Author(s):  
Jens Daniel Müller ◽  
Bernd Schneider ◽  
Ulf Gräwe ◽  
Peer Fietzek ◽  
Marcus Bo Wallin ◽  
...  

Abstract. Organic matter production by cyanobacteria blooms is a major environmental concern for the Baltic Sea, as it promotes the spread of anoxic zones. Partial pressure of carbon dioxide (pCO2) measurements carried out on Ships of Opportunity (SOOP) since 2003 have proven to be a powerful tool to resolve the carbon dynamics of the blooms in space and time. However, SOOP measurements lack the possibility to directly constrain depth-integrated net community production (NCP) in moles of carbon per surface area due to their restriction to the sea surface. This study tackles the knowledge gap through (1) providing an NCP best guess for an individual cyanobacteria bloom based on repeated profiling measurements of pCO2 and (2) establishing an algorithm to accurately reconstruct depth-integrated NCP from surface pCO2 observations in combination with modelled temperature profiles. Goal (1) was achieved by deploying state-of-the-art sensor technology from a small-scale sailing vessel. The low-cost and flexible platform enabled observations covering an entire bloom event that occurred in July–August 2018 in the Eastern Gotland Sea. For the biogeochemical interpretation, recorded pCO2 profiles were converted to CT*, which is the dissolved inorganic carbon concentration normalised to alkalinity. We found that the investigated bloom event was dominated by Nodularia and had many biogeochemical characteristics in common with blooms in previous years. In particular, it lasted for about 3 weeks, caused a CT* drawdown of 90 µmol kg−1, and was accompanied by a sea surface temperature increase of 10 ∘C. The novel finding of this study is the vertical extension of the CT* drawdown up to the compensation depth located at around 12 m. Integration of the CT* drawdown across this depth and correction for vertical fluxes leads to an NCP best guess of ∼1.2 mol m−2 over the productive period. Addressing goal (2), we combined modelled hydrographical profiles with surface pCO2 observations recorded by SOOP Finnmaid within the study area. Introducing the temperature penetration depth (TPD) as a new parameter to integrate SOOP observations across depth, we achieve an NCP reconstruction that agrees to the best guess within 10 %, which is considerably better than the reconstruction based on a classical mixed-layer depth constraint. Applying the TPD approach to almost 2 decades of surface pCO2 observations available for the Baltic Sea bears the potential to provide new insights into the control and long-term trends of cyanobacteria NCP. This understanding is key for an effective design and monitoring of conservation measures aiming at a Good Environmental Status of the Baltic Sea.

2021 ◽  
Author(s):  
Jens Daniel Müller ◽  
Bernd Schneider ◽  
Ulf Gräwe ◽  
Peer Fietzek ◽  
Marcus Bo Wallin ◽  
...  

Abstract. Organic matter production by cyanobacteria blooms is a major environmental concern for the Baltic Sea as it promotes thespread of anoxic zones. Partial pressure of carbon dioxide (pCO2) measurements carried out on Ships of Opportunity (SOOP) since 2003 have proven to be a powerful tool to resolve the carbon dynamics of the blooms in space and time. However, SOOP measurements lack the possibility to directly constrain the depth–integrated net community production (NCP) due to their restriction to the sea surface. This study tackles the resulting knowledge gap through (1) providing a best–guess NCP estimatefor an individual cyanobacteria bloom based on repeated profiling measurements of pCO2 and (2) establishing an algorithm to accurately reconstruct depth–integrated NCP from surface pCO2 observations in combination with modelled temperature profiles. Goal (1) was achieved by deploying state–of–the–art sensor technology from a small–scale sailing vessel. The low–cost and flexible platform enabled observations covering an entire bloom event that occurred in July and August 2018 in the Eastern Gotland Sea. For the biogeochemical interpretation, recorded pCO2 profiles were converted to CT*, which is the dissolved inorganic carbon concentration normalised to alkalinity. We found that the investigated Nodularia–dominated bloom event had many biogeochemical characteristics in common with blooms in previous years. In particular, it lasted for about three weeks, caused a CT* drawdown of 80 μmol kg−1, and was accompanied by a sea surface temperature increase of 10 °C. The novel finding of this study is the vertical extension of the CT* drawdown up to 12 m water depth. Integration of the CT* drawdown across this depth and correction for vertical fluxes permit a best–guess NCP estimate of ~1.2 mol–C m−2. Addressing goal (2), we combined modelled hydrographical profiles with surface pCO2 observations recorded by SOOP Finnmaid within the study area. Introducing the temperature penetration depth (TPD) as a new parameter to integrate SOOP observations across depth, we achieve a reconstructed NCP estimate that agrees to the best–guess within 10 %. Applying the TPD approach to almost two decades of surface pCO2 observations available for the Baltic Sea bears the potential to provide new insights into the control and long–term trends of cyanobacteria NCP. This understanding is key for an effective design and monitoring of conservation measures aiming at a Good Environmental Status of the Baltic Sea.


2021 ◽  
Vol 13 (2) ◽  
pp. 259
Author(s):  
Shuping Zhang ◽  
Anna Rutgersson ◽  
Petra Philipson ◽  
Marcus B. Wallin

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.


2021 ◽  
Author(s):  
Tuomas Kärnä ◽  
Ida Ringgaard ◽  
Vasily Korabel ◽  
Adam Nord ◽  
Patrik Ljungemyr ◽  
...  

&lt;p&gt;We present Nemo-Nordic 2.0, the latest version of the operational marine forecasting model for the Baltic Sea used and developed in the Baltic Monitoring Forecasting Centre (BAL MFC) under the Copernicus Marine Environment Monitoring Service (CMEMS). The most notable differences between Nemo-Nordic 2.0 and its predecessor Nemo-Nordic 1.0 are the switch from NEMO 3.6 to NEMO 4.0 and an increase in horizontal resolution from 2 to 1 nautical mile. In addition, the model's bathymetry and bottom friction formulation have been updated. The model configuration was specially tuned to represent Major Baltic Inflow events. Focusing on a 2-year validation period from October 1, 2014, covering one Major Baltic Inflow event, Nemo-Nordic 2.0 simulates Sea Surface Height (SSH) well: centralized Root-Mean-Square Deviation (CRMSD) is within 10 cm for most stations outside the Inner Danish Waters. CRMSD is higher at some stations where small-scale topographical features cannot be correctly resolved. SSH variability tends to be overestimated in the Baltic Sea and underestimated in the Inner Danish Waters. Nemo-Nordic 2.0 represents Sea Surface Temperature (SST) and Salinity (SSS) well, although there is a negative bias around -0.5&amp;#176;C in SST. The 2014 Major Baltic Inflow event is well reproduced. The simulated salt pulse agrees well with observations in the Arkona basin and progresses into the Gotland basin in 3 to 4 months.&lt;/p&gt;


Author(s):  
Valeriy I. Agoshkov ◽  
Eugene I. Parmuzin ◽  
Vladimir B. Zalesny ◽  
Victor P. Shutyaev ◽  
Natalia B. Zakharova ◽  
...  

AbstractA mathematical model of the dynamics of the Baltic Sea is considered. A problem of variational assimilation of sea surface temperature (SST) data is formulated and studied. Based on variational assimilation of satellite observation data, an algorithm solving the inverse problem of heat flux restoration on the interface of two media is proposed. The results of numerical experiments reconstructing the heat flux functions in the problem of variational assimilation of SST observation data are presented. The influence of SST assimilation on other hydrodynamic parameters of the model is considered.


2016 ◽  
Vol 13 (4) ◽  
pp. 1009-1018 ◽  
Author(s):  
Mati Kahru ◽  
Ragnar Elmgren ◽  
Oleg P. Savchuk

Abstract. Changes in the phenology of physical and ecological variables associated with climate change are likely to have significant effect on many aspects of the Baltic ecosystem. We apply a set of phenological indicators to multiple environmental variables measured by satellite sensors for 17–36 years to detect possible changes in the seasonality in the Baltic Sea environment. We detect significant temporal changes, such as earlier start of the summer season and prolongation of the productive season, in several variables ranging from basic physical drivers to ecological status indicators. While increasing trends in the absolute values of variables like sea-surface temperature (SST), diffuse attenuation of light (Ked490) and satellite-detected chlorophyll concentration (CHL) are detectable, the corresponding changes in their seasonal cycles are more dramatic. For example, the cumulative sum of 30 000 W m−2 of surface incoming shortwave irradiance (SIS) was reached 23 days earlier in 2014 compared to the beginning of the time series in 1983. The period of the year with SST of at least 17 °C has almost doubled (from 29 days in 1982 to 56 days in 2014), and the period with Ked490 over 0.4 m−1 has increased from about 60 days in 1998 to 240 days in 2013 – i.e., quadrupled. The period with satellite-estimated CHL of at least 3 mg m−3 has doubled from approximately 110 days in 1998 to 220 days in 2013. While the timing of both the phytoplankton spring and summer blooms have advanced, the annual CHL maximum that in the 1980s corresponded to the spring diatom bloom in May has now shifted to the summer cyanobacteria bloom in July.


2009 ◽  
Vol 29 (7) ◽  
pp. 870-885 ◽  
Author(s):  
Anders Omstedt ◽  
Erik Gustafsson ◽  
Karin Wesslander

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