Impacts of Climate Change on the Ecosystem of the Baltic Sea

Author(s):  
Markku Viitasalo

Climate change influences the Baltic Sea ecosystem via its effects on oceanography and biogeochemistry. Sea surface temperature has been projected to increase by 2 to 4 °C until 2100 due to global warming; the changes will be more significant in the northern areas and less so in the south. The warming up will also diminish the annual sea ice cover by 57% to 71%, and ice season will be one to three months shorter than in the early 21st century, depending on latitude. A significant decrease in sea surface salinity has been projected because of an increase in rainfall and decrease of saline inflows into the Baltic Sea. The increasing surface flow has, in turn, been projected to increase leaching of nutrients from the soil to the watershed and eventually into the Baltic Sea. Also, acidification of the seawater and sea-level rise have been predicted. Increasing seawater temperature speeds up metabolic processes and increases growth rates of many secondary producers. Species associated with sea ice, from salt brine microbes to seals, will suffer. Due to the specific salinity tolerances, species’ geographical ranges may shift by tens or hundreds of kilometres with decreasing salinity. A decrease in pH will slow down calcification of bivalve shells, and higher temperatures also alleviate establishment of non-indigenous species originating from more southern sea areas. Many uncertainties still remain in predicting the couplings between atmosphere, oceanography and ecosystem. Especially projections of many oceanographic parameters, such as wind speeds and directions, the mean salinity level, and density stratification, are still ambiguous. Also, the effects of simultaneous changes in multiple environmental factors on species with variable preferences to temperature, salinity, and nutrient conditions are difficult to project. There is, however, enough evidence to claim that due to increasing runoff of nutrients from land and warming up of water, primary production and sedimentation of organic matter will increase; this will probably enhance anoxia and release of phosphorus from sediments. Such changes may keep the Baltic Sea in an eutrophicated state for a long time, unless strong measures to decrease nutrient runoff from land are taken. Changes in the pelagic and benthic communities are anticipated. Benthic communities will change from marine to relatively more euryhaline communities and will suffer from hypoxic events. The projected temperature increase and salinity decline will contribute to maintain the pelagic ecosystem of the Central Baltic and the Gulf of Finland in a state dominated by cyanobacteria, flagellates, small-sized zooplankton and sprat, instead of diatoms, large marine copepods, herring, and cod. Effects vary from area to area, however. In particular the Bothnian Sea, where hypoxia is less common and rivers carry a lot of dissolved organic carbon, primary production will probably not increase as much as in the other basins. The coupled oceanography-biogeochemistry ecosystem models have greatly advanced our understanding of the effects of climate change on marine ecosystems. Also, studies on climate associated “regime shifts” and cascading effects from top predators to plankton have been fundamental for understanding of the response of the Baltic Sea ecosystem to anthropogenic and climatic stress. In the future, modeling efforts should be focusing on coupling of biogeochemical processes and lower trophic levels to the top predators. Also, fine resolution species distribution models should be developed and combined with 3-D modelling, to describe how the species and communities are responding to climate-induced changes in environmental variables.

Ocean Science ◽  
2018 ◽  
Vol 14 (3) ◽  
pp. 525-541 ◽  
Author(s):  
Ye Liu ◽  
Weiwei Fu

Abstract. We assess the impact of assimilating the satellite sea surface temperature (SST) data on the Baltic forecast, particularly on the forecast of ocean variables related to SST. For this purpose, a multivariable data assimilation (DA) system has been developed based on a Nordic version of the Nucleus for European Modelling of the Ocean (NEMO-Nordic). We use Kalman-type filtering to assimilate the observations in the coastal regions. Further, a low-rank approximation of the stationary background error covariance metrics is used at the analysis steps. High-resolution SST from the Ocean and Sea Ice Satellite Application Facility (OSISAF) is assimilated to verify the performance of the DA system. The assimilation run shows very stable improvements of the model simulation as compared with both independent and dependent observations. The SST prediction of NEMO-Nordic is significantly enhanced by the DA forecast. Temperatures are also closer to observations in the DA forecast than the model results in the water above 100 m in the Baltic Sea. In the deeper layers, salinity is also slightly improved. In addition, we find that sea level anomaly (SLA) is improved with the SST assimilation. Comparisons with independent tide gauge data show that the overall root mean square error (RMSE) is reduced by 1.8 % and the overall correlation coefficient is slightly increased. Moreover, the sea-ice concentration forecast is improved considerably in the Baltic Proper, the Gulf of Finland and the Bothnian Sea during the sea-ice formation period, respectively.


Author(s):  
Erik Kjellström ◽  
Ole Bøssing Christensen

Regional climate models (RCMs) are commonly used to provide detailed regional to local information for climate change assessments, impact studies, and work on climate change adaptation. The Baltic Sea region is well suited for RCM evaluation due to its complexity and good availability of observations. Evaluation of RCM performance over the Baltic Sea region suggests that: • Given appropriate boundary conditions, RCMs can reproduce many aspects of the climate in the Baltic Sea region. • High resolution improves the ability of RCMs to simulate significant processes in a realistic way. • When forced by global climate models (GCMs) with errors in their representation of the large-scale atmospheric circulation and/or sea surface conditions, performance of RCMs deteriorates. • Compared to GCMs, RCMs can add value on the regional scale, related to both the atmosphere and other parts of the climate system, such as the Baltic Sea, if appropriate coupled regional model systems are used. Future directions for regional climate modeling in the Baltic Sea region would involve testing and applying even more high-resolution, convection permitting, models to generally better represent climate features like heavy precipitation extremes. Also, phenomena more specific to the Baltic Sea region are expected to benefit from higher resolution (these include, for example, convective snowbands over the sea in winter). Continued work on better describing the fully coupled regional climate system involving the atmosphere and its interaction with the sea surface and land areas is also foreseen as beneficial. In this respect, atmospheric aerosols are important components that deserve more attention.


Author(s):  
Christian Möllmann

Climate change and fisheries have significantly changed the Baltic Sea ecosystem, with the demise of Eastern Baltic cod (Gadus morhua callarias) being the signature development. Cod in the Central Baltic Sea collapsed in the late 1980s as a result of low reproductive success and overfishing. Low recruitment and hence small year-classes were not able to compensate for fishing pressures far above sustainable levels. Recruitment failure can be mainly related to the absence of North Sea water inflows to the Central Baltic deep basins. These major Baltic inflows (MBIs) occurred regularly until the 1980s, when their frequency decreased to a decadal pattern, a development attributed to changes in atmospheric circulation patterns. MBIs are needed for ventilation of otherwise stagnating Baltic deep waters, and their absence caused reduced oxygen and salinity levels in cod-spawning habitats, limiting egg and larval survival. Climate change, on the other hand, has promoted a warmer environment richer in zooplanktonic food for larval Baltic sprat (Sprattus sprattus). Resulting large year-classes and low predation by the collapsed cod stock caused an outburst of the sprat stock that cascaded down to the zoo- and phytoplankton trophic levels. Furthermore, a large sprat population controlled cod recruitment and hence hindered a recovery of the stock by predation on cod eggs, limiting cod larval food supply. The change in ecosystem structure and function caused by the collapse of the cod stock was a major part and driver of an ecosystem regime shift in the Central Baltic Sea during the period 1988 to 1993. This reorganization of ecosystem structure involved all trophic levels from piscivorous and planktivorous fish to zoo- and phytoplankton. The observed large-scale ecosystem changes displayed the characteristics of a discontinuous regime shift, initiated by climate-induced changes in the abiotic environment and stabilized by feedback loops in the food web. Discontinuous changes such as regime shifts are characteristically difficult to reverse, and the Baltic ecosystem recently rather shows signs of increasing ecological novelty for which the failed recovery of the cod stock despite a reduction in fishing pressure is a clear symptom. Unusually widespread deficient oxygen conditions in major cod-spawning areas have altered the overall productivity of the population by negatively affecting growth and recruitment. Eutrophication as a consequence of intensive agriculture is the main driver for anoxia in the Baltic Sea amplified by the effects on continuing climate change and stabilized by self-enforcing feedbacks. Developing ecological novelty in the Baltic Sea hence requires true cross-sectoral ecosystem-based management approaches that truly integrate eutrophication combatment, species conservation, and living resources management.


2020 ◽  
Author(s):  
Marcello Passaro ◽  
Felix L. Müller ◽  
Adili Abulaitijiang ◽  
Ole B. Andersen ◽  
Denise Dettmering ◽  
...  

<p>The use of satellite altimetry at high latitudes and coastal regions is currently limited by the presence of seasonal sea ice coverage, and the proximity to the coast. The semi-enclosed Baltic Sea features seasonal coverage of sea-ice in the northern and coastal regions, and complex jagged coastlines with a huge number of small islands. However, as a semi-enclosed sea with a considerable extent, the Baltic Sea features a much-reduced tidal signal, both open- and coastal- waters, and an extensive multi-national network of tide-gauges. These factors maximise opportunities to drive improvements in sea-level estimations for coastal, and seasonal-ice regions.</p><p>The ESA Baltic SEAL project, launched in April 2019, aims to exploit these opportunities. It is generating and validating a suite of enhanced multi-mission sea level products. Processing is developed specifically for coastal regions, with the objective of achieving a consistent description of the sea-level variability in terms of long-term trends, seasonal variations and a mean sea-surface. These will advance knowledge on adapting processing algorithms, to account for seasonal ice, and complex coastlines. Best practice approaches will be available to update current state-of-the-art datasets.</p><p>In order to fulfill these goals, a novel altimeter re-tracking strategy has been developed. This enables the homogeneous determination of sea-surface heights for open-ocean, coastal and sea-ice conditions (ALES+). An unsupervised classification algorithm based on artificial intelligence routines has been developed and tailored to ingest data from all current and past satellite altimetry missions. This identifies radar echoes, reflected by narrow cracks within the sea-ice domain. Finally, the improved altimetry observations are gridded onto a triangulated surface mesh, featuring a spatial resolution greater than 1/4 degree. This is more suitable for utility for coastal areas, and use by coastal stakeholders.</p><p>In addition to utilizing a wide range of altimetry data (Delay-Doppler and Pulse-Limited systems), the Baltic SEAL initiative harnesses the Baltic Seas unique characteristics to test novel geophysical corrections (e.g. wet troposphere correction), use the latest generation of regional altimetry datasets, and evaluate the benefits of the newest satellite altimetry missions. This presentation outlines the methodology and results achieved to date. These include estimations of a new regional mean sea surface, and insights into the trends of the sea level along the altimetry tracks with the longest records. The transfer of advances to other regions and sea-level initiatives are also highlighted.</p>


2021 ◽  
Vol 14 (9) ◽  
pp. 5731-5749
Author(s):  
Tuomas Kärnä ◽  
Patrik Ljungemyr ◽  
Saeed Falahat ◽  
Ida Ringgaard ◽  
Lars Axell ◽  
...  

Abstract. This paper describes Nemo-Nordic 2.0, an operational marine model for the Baltic Sea. The model is used for both near-real-time forecasts and hindcast purposes. It provides estimates of sea surface height, water temperature, salinity, and velocity, as well as sea ice concentration and thickness. The model is based on the NEMO (Nucleus for European Modelling of the Ocean) circulation model and the previous Nemo-Nordic 1.0 configuration by Hordoir et al. (2019). The most notable updates include the switch from NEMO version 3.6 to 4.0, updated model bathymetry, and revised bottom friction formulation. The model domain covers the Baltic Sea and the North Sea with approximately 1 nmi resolution. Vertical grid resolution has been increased from 3 to 1 m in the surface layer. In addition, the numerical solver configuration has been revised to reduce artificial mixing to improve the representation of inflow events. Sea ice is modeled with the SI3 model instead of LIM3. The model is validated against sea level, water temperature, and salinity observations, as well as Baltic Sea ice chart data for a 2-year hindcast simulation (October 2014 to September 2016). Sea level root mean square deviation (RMSD) is typically within 10 cm throughout the Baltic basin. Seasonal sea surface temperature variation is well captured, although the model exhibits a negative bias of approximately −0.5 ∘C. Salinity RMSD is typically below 1.5 g kg−1. The model captures the 2014 major Baltic inflow event and its propagation to the Gotland Deep. The model assessment demonstrates that Nemo-Nordic 2.0 can reproduce the hydrographic features 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.


PLoS ONE ◽  
2020 ◽  
Vol 15 (1) ◽  
pp. e0227714 ◽  
Author(s):  
Sanna Majaneva ◽  
Emil Fridolfsson ◽  
Michele Casini ◽  
Catherine Legrand ◽  
Elin Lindehoff ◽  
...  

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.


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