publications

Impact of the Atlantic Multidecadal Oscillation on Baltic Sea Variability

Börgel, F., C. Frauen, T. Neumann, S. Schimanke, and H. E. M. Meier. (2018), Impact of the Atlantic Multidecadal Oscillation on Baltic Sea variability, Geophys. Res. Lett., 45. https://doi.org/10.1029/2018GL078943

Coastal seas are of great importance to society. A prominent example of such a coastal sea is the Baltic Sea, since it is strongly impacted by human activities. However, besides the human footprint there are also natural phenomena, that influence the Baltic Sea. Especially climate phenomena over the North Atlantic can have a strong impact on the Baltic Sea. One such phenomenon is the so‐called Atlantic Multidecadal Oscillation (AMO), a seesaw between warm and cold sea surface temperatures in the North Atlantic with a period of 60‐90 years. Reliable observations only exist for a period of about 150 years, which is too short to study multidecadal time scales. Therefore, we use an 850 years long model simulation. Our results show that changes in North Atlantic sea surface temperature associated with the AMO influence the atmospheric circulation, which impacts the rain and snowfall over the Baltic Sea region. This in turn enhances or decreases the river runoff into the Baltic Sea and thus impacts the Baltic Sea salinity. Thus, the AMO has a strong influence on the Baltic Sea.

Validator – a Web-Based Interactive Tool for Validation of Ocean Models at Oceanographic Stations

Radtke, H, Börgel, F, Brunnabend, S-E, Eggert, A, Kniebusch, M, Meier, H E M, Neumann, D, Neumann, T and Placke, M 2019 Validator – a Web-Based Interactive Tool for Validation of Ocean Models at Oceanographic Stations. Journal of Open Research Software, 7: 18. DOI: https://doi.org/10.5334/jors.259

Numerical ocean models, like other geoscientific models, are a strongly simplified representation of real oceans. They are used as tools to answer research questions about the real-world systems. Therefore, their thorough validation is essential to ensure that the conclusions drawn from the model experiment are valid in reality. We demonstrate a software which allows an interactive model validation through a web interface based on the R Shiny framework. At pre-defined stations, different kinds of plots can be rendered within a few seconds, according to the user’s choice, allowing a live validation of different model parameters even in model simulations which are still running. This makes it different from validation approaches which generate a pre-defined set of plots after the calculations have finished and make it particularly useful for model tuning purposes. Observation data can be read in from text files or can be extracted from a database.

Once set up, the validation tool requires no technical skills to use. It can be used for single- or multi-model validation and allows saving the generated plots as high-resolution images suitable for use in scientific publications.

A Linux operating system is required for the Validator app, but via a virtual machine, the software can run on Windows or MacOS hosts as well. A Dockerfile is supplied which allows to test the software with example data without installation.

Temperature variability of the Baltic Sea since 1850 and attribution to atmospheric forcing variables

Kniebusch, M., Meier, H. E. M., Neumann, T., & Börgel, F. (2019). Temperature variability of the Baltic Sea since 1850 and attribution to atmospheric forcing variables. Journal of Geophysical Research: Oceans, 124. https://doi.org/10.1029/2018JC013948

The Baltic Sea is highly impacted by global warming and other anthropogenic changes and is one of the fastest‐warming marginal seas in the world. To detect trends in water temperature and to attribute them to atmospheric parameters, the results of two different ocean circulation models driven by reconstructed atmospheric forcing fields for the period 1850‐2008 were analysed. The model simulations were analysed at temporal and spatial scales from seasonal to centennial and from intra‐basin to basin, respectively. The strongest 150‐year trends were found in the annual mean bottom temperature of the Bornholm Deep (0.15 K/decade) and in summer mean sea surface temperature (SST) in Bothnian Bay (0.09‐0.12 K/decade). A comparison of the time periods 1856‐2005 and 1978‐2007 revealed that the SST trends strengthened 10‐fold. An attribution analysis showed that most of the SST variability could be explained by the surface air temperature (SAT), i.e., sensible heat flux, and the latent heat flux. Wind parallel to the coast and cloudiness additionally explained SST variability in the coastal zone affected by the variations in upwelling and in offshore areas affected by the variations in solar radiation, respectively. In contrast, the high variability in stratification caused by fresh‐ and saltwater inflows does not impact the long‐term variability in the SST averaged over the Baltic Sea. The strongest SST trends since the 1980s can be explained by the superposition of global warming and a shift from the cold to the warm phase of the Atlantic Multidecadal Oscillation (AMO).