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Bathymetry, the underwater topography, is a fundamental property of oceans, seas, and lakes. As such it is important for a wide range of applications, like physical oceanography, marine geology, geophysics and biology or the administration of marine resources. The exact requirements users may have regarding bathymetric data are, however, unclear. Here, the results of a questionnaire survey and a literature review are presented, concerning the use of Baltic Sea bathymetric data in research and for societal needs. It is demonstrated that there is a great need for detailed bathymetric data. Despite the abundance of high-quality bathymetric data that are produced for safety of navigation purposes, the digital bathymetric models publicly available to date cannot satisfy this need. Our study shows that DBMs based on data collected for safety of navigation could substantially improve the base data for administrative decision making as well as the possibilities for marine research in the Baltic Sea.

A hindcast wave database and a wave database based on future climate scenarios for the Baltic Sea, Kattegat and Skagerrak is under development. The wind force used for the wave simulation is coming form the RCA model and the future wind from RCA is based on global climate model ECHAM4 for one emission scenario (IPCC SRES A2)The phase averaged spectral model SWAN (Simulated WAves Nearshore) model is used for simulating the wave field. The model is driven by atmospheric forcing and it simulates waves generated by the wind and their propagation both in deep water and near shore areas. When realistic winds are provided the model has an outstanding performance.Winds from the Mesan reanalysis and the RCA model were used as forcing for the SWAN model simulating short hindcast storms for the validation of the wave model in connection with the winds. RCA results appeared to underestimate extreme winds. A correction was introduced which used an empirical relation between 3-second gust and the wind velocity.The model data were compared with observational data. Statistical parameters like scatter index, bias and symmetric slope were used to judge the quality of the data. The performance of the wave model with Mesan is very good. Model and observed data appear to have a good correlation. The performance with RCA is worse and it underestimates the wave height during extreme wind events. The performance when using corrected RCA winds is improved and data give better statistical values when they are compared with observations. The reason for using RCA forcing was the length of RCA data, 40 years of hindcast, and the 50 years of future winds based on global climate scenarios. The corrected coefficient was applied to the RCA and used to force SWAN. Only one year of hindcast has been performed initially while the 40 year run is planned to be performed in the near future. Moreover, a run based on future scenario has been performed. Six month is 1970 were run as control period and 6 months in 2020 as a future projection, giving insight to some of the possible changes in the future wave climate. Thirty years of control run and thirty years of future projection are in progress.

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