Hypoxia in the Baltic Sea and Basin-Scale Changes in Phosphorus Biogeochemistry

AbstractThe Baltic Sea is one of the fastest-warming semi-enclosed seas in the world over the last decades, yielding critical consequences on physical and biogeochemical conditions and on marine ecosystems. Although long-term trends in sea surface temperature (SST) have long been attributed to trends in air temperature, there are however, strong seasonal and sub-basin scale heterogeneities of similar magnitude than the average trend which are not fully explained. Here, using reconstructed atmospheric forcing fields for the period 1850–2008, oceanic climate simulations were performed and analyzed to identify areas of homogenous SST trends using spatial clustering. Our results show that the Baltic Sea can be divided into five different areas of homogeneous SST trends: the Bothnian Bay, the Bothnian Sea, the eastern and western Baltic proper, and the southwestern Baltic Sea. A classification tree and sensitivity experiments were carried out to analyze the main drivers behind the trends. While ice cover explains the seasonal north/south warming contrast, the changes in surface winds and air-sea temperature anomalies (along with changes in upwelling frequencies and heat fluxes) explain the SST trends differences between the sub-basins of the southern part of the Baltic Sea. To investigate future warming trends climate simulations were performed for the period 1976–2099 using two RCP scenarios. It was found that the seasonal north/south gradient of SST trends should be reduced in the future due to the vanishing of sea ice, while changes in the frequency of upwelling and heat fluxes explained the lower future east/west gradient of SST trend in fall. Finally, an ensemble of 48 climate change simulations has revealed that for a given RCP scenario the atmospheric forcing is the main source of uncertainty. Our results are useful to better understand the historical and future changes of SST in the Baltic Sea, but also in terms of marine ecosystem and public management, and could thus be used for planning sustainable coastal development.

Download Full-text

Developing benthic monitoring programmes to support precise and representative status assessments: a case study from the Baltic Sea

Environmental Monitoring and Assessment ◽

10.1007/s10661-020-08764-7 ◽

2020 ◽

Vol 192 (12) ◽

Author(s):

Henrik Nygård ◽

Mats Lindegarth ◽

Alexander Darr ◽

Grete E. Dinesen ◽

Ole R. Eigaard ◽

...

Keyword(s):

Baltic Sea ◽

Marine Ecosystem ◽

Monitoring Data ◽

Data Series ◽

Sampling Effort ◽

The Baltic Sea ◽

Basin Scale ◽

The Status ◽

The Baltic

AbstractBenthic habitats and communities are key components of the marine ecosystem. Securing their functioning is a central aim in marine environmental management, where monitoring data provide the base for assessing the state of marine ecosystems. In the Baltic Sea, a > 50-year-long tradition of zoobenthic monitoring exists. However, the monitoring programmes were designed prior to the current policies, primarily to detect long-term trends at basin-scale and are thus not optimal to fulfil recent requirements such as area-based periodic status assessments. Here, we review the current monitoring programmes and assess the precision and representativity of the monitoring data in status assessments to identify routes for improvement. At present, the monitoring is focused on soft-bottoms, not accounting for all habitat types occurring in the Baltic Sea. Evaluating the sources of variance in the assessment data revealed that the component accounting for variability among stations forms the largest proportion of the uncertainty. Furthermore, it is shown that the precision of the status estimates can be improved, with the current number of samples. Reducing sampling effort per station, but sampling more stations, is the best option to improve precision in status assessments. Furthermore, by allocating the sampling stations more evenly in the sub-basins, a better representativity of the area can be achieved. However, emphasis on securing the long-term data series is needed if changes to the monitoring programmes are planned.

Download Full-text

On the modelling of ice-thickness redistribution

Journal of Glaciology ◽

10.3189/172756500781833106 ◽

2000 ◽

Vol 46 (154) ◽

pp. 427-437 ◽

Cited By ~ 31

Author(s):

Jari Haapala

Keyword(s):

Baltic Sea ◽

Numerical Experiments ◽

Thickness Distribution ◽

Distribution Model ◽

Ice Thickness ◽

The Baltic Sea ◽

Pack Ice ◽

Basin Scale ◽

The Baltic ◽

Ice Production

AbstractAn ice-thickness distribution model based on physical ice classes is formulated. Pack ice is subdivided into open water, two different types of undeformed ice, and rafted, rubble and ridged ice. Evolution equations for each ice class are formulated and a redistribution between the ice classes is calculated according to a functional form depending on the ice compactness, thickness and velocity divergence. The ice-thickness distribution model has been included in a coupled ice–ocean model, and numerical experiments have been carried out for a simulation of the Baltic Sea ice season. The extended ice classification allows separation of thermally and mechanically produced ice. Inherent thermodynamic growth/melting rates of the ice classes can be introduced into the model, giving a more detailed seasonal evolution of the pack ice. In addition, the model provides more information about the surface properties of pack ice.Numerical experiments for the Baltic Sea show that both the sub-basin and inter-basin ice characteristics were realistically simulated by the model. Deformed-ice production was related to storm activity. Most of the deformation was produced in the coastal zone, which is also an important region for thermodynamically produced ice because of the ice growth in leads. The modelled mechanical growth rates of ice were 0.5–3 cm d−1 on a basin scale, close to the thermodynamic ice-production rates. The deformed-ice fraction was 0.2 in mid-winter and increased to 0.5–1.0 during spring.

Download Full-text

Remote sensing of chlorophyll in the Baltic Sea at basin scale from 1997 to 2012 using merged multisensor data

Ocean Science Discussions ◽

10.5194/osd-12-2283-2015 ◽

2015 ◽

Vol 12 (5) ◽

pp. 2283-2313

Author(s):

J. Pitarch ◽

G. Volpe ◽

S. Colella ◽

H. Krasemann ◽

R. Santoleri

Keyword(s):

Time Series ◽

Baltic Sea ◽

Late Winter ◽

The Baltic Sea ◽

In Situ Data ◽

Basin Scale ◽

Gulf Of Bothnia ◽

Summer Bloom ◽

The Baltic

Abstract. Fifteen-year (1997–2012) time series of chlorophyll a (CHL) in the Baltic Sea, based on merged multisensor satellite data provided by the European projects Globcolour and ESA-OC-CCI were analysed. Several available CHL algorithms were sea-truthed against a large in situ CHL dataset consisting of data by Seadatanet, HELCOM and NOAA. Matchups were calculated for three separate areas (1) Skagerrak and Kattegat, (2) Baltic Proper plus gulfs of Riga and Finland, called here "Central Baltic", (3) Gulf of Bothnia, and for the three areas as a whole. Statistics showed low linearity. The OC4v6 algorithm (R2 = 0.46, BIAS = +60 %, RMS = 79 % for the whole dataset) was linearly transformed by using the best linear fit (OC4corr). By construction, the bias was corrected, but RMS was increased instead. Despite this shortcoming, we demonstrated that errors between OC4corr and in situ data were log-normally distributed and centred at zero. Consequently, unbiased estimators of the horizontally-averaged CHL could be obtained, the error of which tends to zero when a large amount of pixels is averaged. From the basin-wide time series, the climatology and the annual anomalies were separated. The climatologies revealed completely different CHL dynamics among regions: in Skagerrak and Kattegat, CHL strongly peaks in late winter, with a minimum in summer and a secondary peak in spring. In the Central Baltic, CHL follows a dynamics of a spring CHL peak, followed by a much stronger summer bloom, with decreasing CHL towards winter. The Gulf of Bothnia shows a similar CHL dynamics as the central Baltic, although the summer bloom is absent. Across years, CHL showed great variability. Supported by auxiliary satellite sea-surface temperature (SST) data, we found that phytoplankton growth was inhibited in the central Baltic Sea in the years of colder summers or when the SST happened to increase later in the season. Extremely high CHL in spring 2008 was detected and linked to an exceptionally warm preceding winter. Sharp SST changes were found to induce CHL changes in the same direction. This phenomenon was appreciated best by overlaying the time series of the CHL and SST anomalies.

Download Full-text

Basin-scale granular ice dynamics modelling

10.5194/egusphere-egu2020-18117 ◽

2020 ◽

Author(s):

Jonni Lehtiranta

Keyword(s):

Sea Ice ◽

Baltic Sea ◽

The Baltic Sea ◽

Ice Dynamics ◽

Length Scales ◽

The North ◽

Acceleration Techniques ◽

Basin Scale ◽

Ice Floes ◽

The Baltic

Current operational sea ice models solve primitive equations on a grid and treat sea ice as a continuum with smoothly varying properties. This is the same method that is used in ocean models. The continuum assumption is unrealistic for sea ice which consists of separate rigid ice floes. The assumption works best for length scales much larger than typical floe size, and worst for very small length scales.Winter shipping in finnish ports depends on timely sea ice information on the Baltic Sea. Due to climate change, the yearly ice covered area and thermodynamic ice growth are decreasing. However, sea ice is also becoming more mobile and dynamic, especially in the Bay of Bothnia which lies in the north end of the Baltic Sea.A particle-based granular approach is more realistic in the length scales of individual ice floes. Such models have been developed (eg. by Mark Hopkins and Agnieszka Herman) and used successfully in limited scales, such as fjords. For larger horizontal scales, they have been computationally too expensive. Using modern GPU acceleration techniques, discrete element simulation of sea ice is becoming possible in the scale required for Baltic sea basins.This work presents an ongoing project for building a granular sea ice model for forecasting ice dynamics. This includes ice movement and deformation and describes ridge and lead formation and similar phenomena. Existing accelerated solvers are examined, and the most suitable is adapted for Baltic sea ice and applied for the Bay of Bothnia.

Download Full-text

Basin-scale spatio-temporal variability and control of phytoplankton photosynthesis in the Baltic Sea: The first multiwavelength fast repetition rate fluorescence study operated on a ship-of-opportunity

Journal of Marine Systems ◽

10.1016/j.jmarsys.2017.01.007 ◽

2017 ◽

Vol 169 ◽

pp. 40-51 ◽

Cited By ~ 3

Author(s):

Emilie Houliez ◽

Stefan Simis ◽

Susanna Nenonen ◽

Pasi Ylöstalo ◽

Jukka Seppälä

Keyword(s):

Baltic Sea ◽

Temporal Variability ◽

Repetition Rate ◽

Fluorescence Study ◽

The Baltic Sea ◽

Basin Scale ◽

Spatio Temporal ◽

The Baltic ◽

And Control ◽

Phytoplankton Photosynthesis

Download Full-text

Forms and Variability of Phosphorus in the Baltic Sea–-A Challenge to Ecosystem Modeling

Air Soil and Water Research ◽

10.4137/aswr.s6123 ◽

2010 ◽

Vol 3 ◽

pp. ASWR.S6123

Author(s):

O. Magnus Karlsson

Keyword(s):

Baltic Sea ◽

East Coast ◽

Inorganic Phosphorus ◽

Ecosystem Modeling ◽

Sensitivity Analyses ◽

The Baltic Sea ◽

Dissolved Phosphorus ◽

Basin Scale ◽

Key Factor ◽

The Baltic

Knowledge of the partitioning between the dissolved and particulate phases of nutrient elements is a key factor in aquatic ecosystem modeling since partitioning regulates the availability to demand ratio of the nutrient in question. This is seldom taken into account in environmental monitoring programs. In this paper, the occurrence and variability of particulate and dissolved phosphorus were studied in the coastal zone of the Baltic Sea. The particulate fraction (PF) of total phosphorus (TP) concentration in coastal waters from some forty stations along the east coast of Sweden was, on average, 0.33. Dissolved inorganic phosphorus (DIP) was a poor predictor of total dissolved phosphorus (DP) representing only 20%-30% of this fraction. Sensitivity analyses showed that the value of PF had a significant impact on modeled predictions of TP concentration in the water on a Baltic sub-basin scale, whereas an applied coastal model was insensitive to variations in PF. Hence, this study encourages further sampling efforts on the partitioning of phosphorus in the open waters of the Baltic Sea.

Download Full-text

Basin-scale distribution of harbour porpoises in the Baltic Sea provides basis for effective conservation actions

Biological Conservation ◽

10.1016/j.biocon.2018.06.031 ◽

2018 ◽

Vol 226 ◽

pp. 42-53 ◽

Cited By ~ 21

Author(s):

Ida Carlén ◽

Len Thomas ◽

Julia Carlström ◽

Mats Amundin ◽

Jonas Teilmann ◽

...

Keyword(s):

Baltic Sea ◽

The Baltic Sea ◽

Basin Scale ◽

Conservation Actions ◽

The Baltic ◽

Effective Conservation

Download Full-text

Remote sensing of chlorophyll in the Baltic Sea at basin scale from 1997 to 2012 using merged multi-sensor data

Ocean Science ◽

10.5194/os-12-379-2016 ◽

2016 ◽

Vol 12 (2) ◽

pp. 379-389 ◽

Cited By ~ 17

Author(s):

Jaime Pitarch ◽

Gianluca Volpe ◽

Simone Colella ◽

Hajo Krasemann ◽

Rosalia Santoleri

Keyword(s):

Time Series ◽

Baltic Sea ◽

Sensor Data ◽

The Baltic Sea ◽

Data Set ◽

Chl A ◽

Basin Scale ◽

Gulf Of Bothnia ◽

Summer Bloom ◽

The Baltic

Abstract. A 15-year (1997–2012) time series of chlorophyll a (Chl a) in the Baltic Sea, based on merged multi-sensor satellite data was analysed. Several available Chl a algorithms were sea-truthed against the largest in situ publicly available Chl a data set ever used for calibration and validation over the Baltic region. To account for the known biogeochemical heterogeneity of the Baltic, matchups were calculated for three separate areas: (1) the Skagerrak and Kattegat, (2) the central Baltic, including the Baltic Proper and the gulfs of Riga and Finland, and (3) the Gulf of Bothnia. Similarly, within the operational context of the Copernicus Marine Environment Monitoring Service (CMEMS) the three areas were also considered as a whole in the analysis. In general, statistics showed low linearity. However, a bootstrapping-like assessment did provide the means for removing the bias from the satellite observations, which were then used to compute basin average time series. Resulting climatologies confirmed that the three regions display completely different Chl a seasonal dynamics. The Gulf of Bothnia displays a single Chl a peak during spring, whereas in the Skagerrak and Kattegat the dynamics are less regular and composed of highs and lows during winter, progressing towards a small bloom in spring and a minimum in summer. In the central Baltic, Chl a follows a dynamics of a mild spring bloom followed by a much stronger bloom in summer. Surface temperature data are able to explain a variable fraction of the intensity of the summer bloom in the central Baltic.

Download Full-text