During the 2023/2024 ice season, a high-resolution dataset of ice thickness was collected in the Bothnian Bay. The analysis of data revealed a significant frequency of thick deformed ice such that about 60 % was thicker than 1 m. Among the 5500 individually identified ice keels, 20 % had a keel depth larger than 5 m and 2 % a depth larger than 10 m. This type of high-resolution ice data can be of vital importance for design of offshore structures and evaluation of computer ice models.

Climate change influences estuaries and their ecosystems not only by rising temperatures but also by salinity changes. This modeling study highlights the magnitude and causes of the Baltic Sea salinity sensitivity to fresh water forcing and changed ocean salinity. The large sensitivity to increased fresh water forcing is shown to be caused by dilution of fresh water within the estuary, recirculation of much of the outflow water back into the estuary, as well as decreasing inflows of ocean water.

This review explains how weather patterns, guided by the polar jet stream, influence the Baltic Sea’s climate and ecosystem. It covers the NAO, blocking events and other processes and discusses how they affect temperature, rainfall, and storms from days to decades. These shifts then impact oxygen levels, productivity, and acidification in the Baltic Sea. Physical links are fairly well known, but biogeochemical pathways remain uncertain.

Mesoscale ocean eddies (10–100 km) are crucial for transporting heat and salt in global circulation. While traditionally parameterized in ocean models, advances in computational power allow them to be partly resolved, questioning whether parameterizations should be used in this regime. We examine implications for Atlantic water circulation and heat transport to the Arctic, highlighting challenges in using – or omitting – mesoscale eddy parameterizations.

We studied the annual maximum sea levels for the coastal regions in the Baltic Sea and parts of the North Sea. The study aimed to reduce the quantified uncertainty and produce estimates at locations with no tide gauges data. Comparing four statistical models and a baseline model, we concluded that the spatial hierarchical models, which leverages spatial dependency, reduced the uncertainty for higher/lower probability events compared to the other models for locations with or without observations.