The Baltic Sea Experiment (BALTEX) started in 1993 as part of the Global Energy and Water Cycle Experiment (GEWEX). It was later organized into three programs: BALTEX I, BALTEX II, and Baltic Earth. Here, we examine in a brief overview the overall BALTEX achievements, including program goals, risks encountered during the research journey, and knowledge development when finalizing the programs. During three decades of climate and environmental studies of the Baltic Basin within the BALTEX/Baltic Earth programs, significant steps have been taken towards improved scientifically constructed knowledge and efforts to disseminate this knowledge to neighboring sciences and the public. These programs have illustrated the need to actively navigate the European research arena while remaining an independent science network. The well-organized International Baltic Earth Secretariat and many dedicated scientists made the research excursions safe and successful. The learning process relates to improved knowledge of the dynamics of the atmosphere–ocean–land climate system in the Baltic Sea region, the cycling of carbon and other substances, the region's anthropogenic climate and environmental changes, and how global warming and regional human activities can be detected outside natural variability.
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During an experiment-of-opportunity in July 2019, 27 drift bottles were released in the southern Baltic Sea. Ten of these bottles were found and reported at locations that were surprisingly widespread. In this study, we explore the chances to reproduce these findings with a numerical drift model. While trajectories may be considered as completely deterministic, in practice their prediction as well as reconstruction has a strong stochastic component, because of ubiquitous gradients on even the smallest scales. We illustrate different aspects of uncertainty including specification of leeway, random dispersion, and stretching along Lagrangian coherent structures. By and large, the results of numerical ensemble simulations seem to be in reasonable agreement with the observational evidence available. Some drift bottle findings suggest a bias in simulations, but without knowing the drift bottles’ full drift paths, a basis for more detailed model tuning is missing.
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