Diatom-based estimation of sea surface salinity in the south Baltic Sea and Kattegat

A new diatom-based sea surface salinity (SSS) estimation has been applied to a collection of 27 taxa in 48 present-day sediment and surface water samples recovered in the Baltic Sea and Kattegat. The sediment core 303610-12 (2005) from the Eastern Gotland was chosen for study of Holocene sequence, ranging the last 8160 yrs BP. The Artificial Neuronal Network (ANN) method allows the estimation of spring SSS (March-April) values ranging between 7.04 ‰ and 8.25 ‰ at an averaged Root Mean Squared Error (RMSE) of 0.49 ‰. The rather low amplitude of salinity change might be caused by mixing of fresh water with upper surface layer of the Baltic Sea due to high precipitation and riverine input. The estimates of spring SSS from core 303610-12 were compared with independent geochemical proxies for salinity (K, Ti and S) derived from XRF Core Scanner record. Conspicuous correlation between salinity and sulphur records and reverse-correlation to K and Ti demonstrates that the ANN method combined with quantitative and qualitative analyses of diatoms provides a useful tool for palaeosalinity reconstructions in the Holocene sediments of the Baltic Sea

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First regional SMOS Sea Surface Salinity products over the Baltic Sea and its oceanographic added-value

10.5194/egusphere-egu2020-16939 ◽

2020 ◽

Author(s):

Veronica Gonzalez-Gambau ◽

Estrella Olmedo ◽

Cristina Gonzalez-Haro ◽

Antono Turiel ◽

Justino Martinez ◽

...

Keyword(s):

Baltic Sea ◽

Numerical Models ◽

Sea Surface ◽

Sea Surface Salinity ◽

Added Value ◽

The Baltic Sea ◽

Surface Salinity ◽

Validation Data ◽

The Baltic

Accurate satellite-based sea surface salinity (SSS) fields would address some gaps of knowledge and benefit the understanding of Baltic Sea salinity dynamics. &#160;In particular, these fields can contribute to the monitoring of long-term salinity changes and to the detection of periods with anomalous salinity. These products can also be very useful as initial fields and validation data for improving the existing numerical models. The Baltic Sea is one of the most challenging regions for the retrieval of SSS from L-band satellite measurements. Nowadays, available EO-based SSS products are quite limited over this region both in terms of spatio-temporal coverage and quality. This is mainly due to several technical limitations that strongly affect the SMOS TB particularly over semi-enclosed seas, such as the high contamination by Radio-Frequency Interference (RFI) sources and the contamination close to land and ice edges. Besides, the sensitivity of TB to SSS changes is very low in cold waters and much larger errors are expected compared to temperate oceans. Salinity and temperature values are very low in this basin, which implies that dielectric constant models are not fully tested in such conditions. In the recent years, the Barcelona Expert Center team has been working on the development of innovative algorithms for improving the quality of SMOS TB and SSS retrievals dealing with the main processing issues.&#160; In the context of the ESA Baltic+ Salinity Dynamics project (https://balticsalinity.argans.co.uk/), these methodologies have been adapted and consolidated towards the generation of the first &#160;regional SMOS SSS product (2011-2020) that would suit to the needs of the Baltic research community. Very recently, the first version of the Baltic+ SSS product has been produced (3-year series) and is currently under validation against in-situ measurements. The quality assessment of the SSS product in the Baltic Sea is also an issue and its representativeness must be carefully assessed. The basin is strongly stratified and then, the differences between SMOS measurements (first centimeters) and in-situ observations (few meters depth) can be noticeable. Differences are more probable during ice melting and high runoff events in spring where there might be a freshwater layer at the top shallow surface. Feedback from the users will help identifying the limitations of the product. Additional technical developments will be addressed to meet the requirements of the communities working in the study of Baltic processes.&#160; We will present at the conference the Baltic+ SSS v1 product and its added-value with respect to other existing EO-based datasets. The potential scientific impact of this satellite SSS product in advancing on-going regional research initiatives like the Baltic Earth Working Group on Salinity dynamics will be discussed.

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First SMOS Sea Surface Salinity dedicated products over the Baltic Sea

10.5194/essd-2021-461 ◽

2022 ◽

Author(s):

Verónica González-Gambau ◽

Estrella Olmedo ◽

Antonio Turiel ◽

Cristina González-Haro ◽

Aina García-Espriu ◽

...

Keyword(s):

Baltic Sea ◽

Numerical Models ◽

Sea Surface ◽

Sea Surface Salinity ◽

The Baltic Sea ◽

Surface Salinity ◽

L Band ◽

The Baltic ◽

The Impact

Abstract. This paper presents the first Soil Moisture and Ocean Salinity (SMOS) Sea Surface Salinity (SSS) dedicated products over the Baltic Sea. The SSS retrieval from L-band brightess temperature (TB) measurements over this basin is really challenging due to important technical issues, such as the land-sea and ice-sea contamination, the high contamination by Radio-Frequency Interferences (RFI) sources, the low sensitivity of L-band TB at SSS changes in cold waters and the poor characterization of dielectric constant models for the low SSS and SST ranges in the basin. For these reasons, exploratory research in the algorithms used from the level 0 up to level 4 has been required to develop these dedicated products. This work has been performed in the framework of the European Space Agency regional initiative Baltic+ Salinity Dynamics. Two Baltic+ SSS products have been generated for the period 2011–2019 and are freely distributed: the Level 3 (L3) product (daily generated 9-day maps in a 0.25° grid, https://doi.org/10.20350/digitalCSIC/13859) (González-Gambau et al., 2021a) and the Level 4 (L4) product (daily maps in a 0.05° grid, https://doi.org/10.20350/digitalCSIC/13860) (González-Gambau et al., 2021b)), that are computed by applying multifractal fusion to L3 SSS with Sea Surface Temperature (SST) maps. The accuracy of L3 SSS products is typically around 0.7–0.8 psu. The L4 product has an improved spatio-temporal resolution with respect to the L3 and the accuracy is typically around 0.4 psu. Regions with the highest errors and limited coverage are located in Arkona and Bornholm basins and Gulfs of Finland and Riga. The impact assessment of Baltic+ SSS products has shown that they can help in the understanding of salinity dynamics in the basin. They complement the temporally and spatially very sparse in situ measurements, covering data gaps in the region and they can also be useful for the validation of numerical models, particularly in areas where in situ data are very sparse.

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First regional SMOS Sea Surface Salinity products over the Baltic Sea: quality assessment and oceanographic added-value

10.5194/egusphere-egu21-15254 ◽

2021 ◽

Author(s):

Veronica Gonzalez Gambau ◽

Estrella Olmedo ◽

Cristina Gonzalez Haro ◽

Antonio Turiel ◽

Aina Garcia ◽

...

Keyword(s):

Baltic Sea ◽

Water Exchange ◽

Sea Surface ◽

Sea Surface Salinity ◽

The Baltic Sea ◽

Surface Salinity ◽

Model Simulations ◽

The North ◽

The Baltic

The Baltic Sea is a strongly stratified semi-enclosed sea with a large freshwater supply from rivers, net precipitation and water exchange and high-saline water from the North Sea through the Kattegat Strait. In the Danish Straits the water exchange is hampered by bathymetric constraints , such as narrow and shallow sills, and by hydrodynamic restrictions, such as fronts and mixing. The shallow depth of the Baltic Sea (i.e. 54 m in average) yields to highly variable ocean dynamics controlled mainly by local atmospheric forcing. The water exchange between the Baltic Sea and the North Atlantic Ocean is restricted by the narrows and sills of the Danish Straits (i.e. via Kattergat Strait at the East of the Baltic Sea) and by different river outflows distributed across the Baltic Sea. The bottom water in the deep sub-basins is ventilated mainly by large perturbations, so-called major Baltic saltwater inflows. The occurrence of these events needs still further investigation. The description of the complex oceanographic conditions within the Baltic Sea in current model simulations could also be developed. Furthermore, model simulations of the Baltic Sea are constrained to the initialization of the model (i.e. parametrization of the initial surface atmospheric and ocean conditions).For this, the Earth Observation salinity measurements have a great potential to help in the understanding of the dynamics in the basin and to improve the regional models there. However, the Baltic Sea is one of the most challenging regions for the sea surface salinity (SSS) retrieval from satellite measurements. The available EO-based SSS products are quite limited over this region both in terms of spatio-temporal coverage and quality. This is mainly due to several technical limitations that strongly affect the satellite brightness temperatures (TB) measurements, particularly over semi-enclosed seas, such as the high contamination by Radio-Frequency Interferences (RFI) and the contamination close to land and ice edges. Besides, the sensitivity of TB to SSS changes is very low in cold waters and much larger errors are expected compared to temperate oceans.As a main result of the ESA Baltic+ Salinity Dynamics project (), a new regional SSS product derived from the measurements provided by the European Soil Moisture and Ocean Salinity (SMOS) mission has been developed. In this work, first, we describe briefly the enhanced algorithms used in the generation of SMOS SSS fields. Second, we show a complete quality assessment by comparing the satellite and the in situ salinity measurements. For this, we use in situ measurements provided by SeaDataNet and Helcom and Ferry box lines. Finally, we compare the satellite salinity measurements with the salinity fields provided by a model. We focus our analysis in two aspects: i) the description of the freswater fluxes coming from continental discharge and sea-ice melting; and ii) the capability of describing the dynamics of the saltier Atlantic water that enters into the basin through the Kattegat strait.&#160;

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Remote Sensing Supported Sea Surface pCO2 Estimation and Variable Analysis in the Baltic Sea

Remote Sensing ◽

10.3390/rs13020259 ◽

2021 ◽

Vol 13 (2) ◽

pp. 259

Author(s):

Shuping Zhang ◽

Anna Rutgersson ◽

Petra Philipson ◽

Marcus B. Wallin

Keyword(s):

Remote Sensing ◽

Baltic Sea ◽

Mean Squared Error ◽

Numerical Models ◽

Mixed Layer Depth ◽

Sea Surface ◽

The Baltic Sea ◽

Chl A ◽

Marginal Seas ◽

The Baltic

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.

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Towards operational NEMO model for the Baltic Sea

10.5194/egusphere-egu2020-16587 ◽

2020 ◽

Author(s):

Tuomas Kärnä ◽

Jonni Lehtiranta ◽

Laura Tuomi

Keyword(s):

Sea Ice ◽

Baltic Sea ◽

Model Development ◽

Circulation Model ◽

Water Levels ◽

Sea Surface Salinity ◽

The Baltic Sea ◽

Surface Salinity ◽

Ice Coverage ◽

The Baltic

We are developing a new operational circulation model for the Baltic Sea using NEMO v4.0. The model configuration is derived from the NEMO v3.6 1 nmi NemoNordic setup (Hordoir et al., Geoscientific Model Development, 2019). A pre-operational version of the model has been implemented to produce daily forecasts of water level, temperature, salinity, and currents, as well as sea ice coverage. In this poster we present model validation for a two-year hindcast simulation. The results indicate that daily and seasonal variability of water levels and sea surface salinity are well captured. Sea ice coverage is well represented, although slightly over-estimated. Comparisons at several mooring locations show realistic vertical salinity structure, and verify that the model can simulate Baltic inflow events. Overall, the model skill has significantly improved compared to previous operational models.

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Variational assimilation of observation data in the mathematical model of the Baltic Sea dynamics

Russian Journal of Numerical Analysis and Mathematical Modelling ◽

10.1515/rnam-2015-0018 ◽

2015 ◽

Vol 30 (4) ◽

Cited By ~ 5

Author(s):

Valeriy I. Agoshkov ◽

Eugene I. Parmuzin ◽

Vladimir B. Zalesny ◽

Victor P. Shutyaev ◽

Natalia B. Zakharova ◽

...

Keyword(s):

Mathematical Model ◽

Heat Flux ◽

Baltic Sea ◽

Satellite Observation ◽

Sea Surface ◽

Observation Data ◽

The Baltic Sea ◽

Variational Assimilation ◽

The Baltic ◽

The Mathematical Model

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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Changing seasonality of the Baltic Sea

Biogeosciences ◽

10.5194/bg-13-1009-2016 ◽

2016 ◽

Vol 13 (4) ◽

pp. 1009-1018 ◽

Cited By ~ 34

Author(s):

Mati Kahru ◽

Ragnar Elmgren ◽

Oleg P. Savchuk

Keyword(s):

Baltic Sea ◽

Chlorophyll Concentration ◽

Ecological Status ◽

Sea Surface ◽

Seasonal Cycles ◽

The Baltic Sea ◽

Several Variables ◽

Satellite Sensors ◽

The Baltic ◽

Increasing Trends

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.

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Nemo-Nordic 2.0: Updated Baltic Sea model based on NEMO 4.0

10.5194/egusphere-egu21-8728 ◽

2021 ◽

Author(s):

Tuomas Kärnä ◽

Ida Ringgaard ◽

Vasily Korabel ◽

Adam Nord ◽

Patrik Ljungemyr ◽

...

Keyword(s):

Baltic Sea ◽

Horizontal Resolution ◽

Sea Surface ◽

Small Scale ◽

The Baltic Sea ◽

Inflow Event ◽

Arkona Basin ◽

The Baltic ◽

Marine Environment Monitoring ◽

Monitoring Service

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&#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.

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