Oceanographic research and development
At the Oceanographic research group, research is based on oceanography, the study of the sea, and links the physics of the sea with biological, geological and chemical processes in the ocean. We are about 20 specialists in fields ranging from oceanography and marine biology to mathematics and computer programming. We increase society's knowledge of the state of the sea to facilitate sustainable management of our ocean.
”The ocean is important for everyone”
About the researchFind on this page
Much of SMHI's oceanographic research focuses on our surrounding sea areas; the Baltic Sea, Kattegat and Skagerrak, but we also conduct research for the North Sea and Arctic Ocean.
We are specialists in a number of areas related to marine research, such as marine biology, marine observations, numerical modeling and remote sensing.
We work with marine observational data, oceanographic analysis and the development of computational models and methods. The models are used to make forecasts, study processes and predict future ocean climate.
Our research results are used in products that benefit a wide range of fields, such as oil spill response, shipping, sea rescue, and warnings of algal blooms and high or low water levels.
The results are also used to plan actions needed to meet national environmental quality objectives and to support decision-making on water management, adaptation to future climate and mitigation of climate impacts.
Our oceanographic research focuses on three main research areas: Ocean Climate, Marine Environment and Operational Oceanographic Research and Model Development.
Ocean Climate
The role of the ocean in the climate system
Marine Environment
The sea as a habitat
Operational Oceanographic Research and Model Development.
Sea forecasts and warnings
SMHI's oceanographic research unit participates in many national and international projects. We develop ocean modeling and ocean observations and link them with central services and with various issues, both around historical reconstructions and climate change in the Baltic Sea, the North Sea and the Arctic.
Oxygenation – model study: Evaluate restoration of the Baltic Sea by oxygenation of anoxic bottoms
The aim with the project is to investigate if pumping oxygen rich water to the deep will decrease the re-circulation of phosphorus and speed up a permanent improvement of the environment state in the Baltic Sea.
Numerical models are the main tools in oceanographic research. At SMHI, several advanced models are developed and used to describe the physical and biogeochemical processes in the ocean. Sometimes the models can also be linked together into a multi-model system.
The various model systems are used to make forecasts and enable SMHI to issue warnings and study environmental changes in the marine ecosystem and the effects of climate change.
The main modeling systems today are EC-Earth, NEMO, PADM, SCOBI and SCM.
%20FoU-Oce_Internat%20Gbg%20v%C3%A5ren%202024.webp)
All of us at the oceanographic research unit
The unit is led by Sam Fredriksson, Elin Almroth-Rosell and Lars Axén.
We publish our research results in international peer-reviewed journals and in SMHI reports. The two most recent publications from SMHI's oceanographic research are:
Incorporating ecosystem component interactions and indirect effects in cumulative impact assessment models
Irene Wåhlstrom, Diana Perry, Sanne Bergman, Martin Dahl, Maria E. Granberg, Martin Gullstrom, Linus Hammar Perry, Kerstin Magnusson, Peter Thor
Abstract
The cumulative impact of anthropogenic pressures on coastal seas is important to consider for a strategic and sustainable management of marine ecosystems. We aim to demonstrate how, and to what extent, incorporating interactions among ecosystem components (species and habitats) and indirect effects of pressures through other ecosystem components can develop existing cumulative impact assessment (CIA) models. A Swedish case study area was selected to test a simplified version of the extended regional Symphony CIA model. Five pollution- and climate-driven pressures acting on three trophically connected ecosystem components, i.e. cod, herring and plankton species/organism groups, were used. In addition, we conducted a systematic review of the scientific literature to determine the impact weight scores for an advancement of the method. The results from the development of CIA models clearly indicate the importance of introducing ecosystem component interactions and indirect effects into CIA models. The total cumulative impact increased by 117 % in the test area, but even more importantly, the development of the model resulted in a spatially more detailed outcome with a greater spatial variability in the magnitude of the total cumulative impact. New areas were highlighted that are under pressure compared to the original model. Thus, the development of the model captures cumulative impacts that would otherwise be overlooked if ecosystem component interactions and indirect effects were ignored. These types of changes to CIA models are required to increase the predictive power and ecological relevance to accommodate solid holistic and ecosystem-based marine management.
Exploring Storm Tides Projections and Their Return Levels Around the Baltic Sea Using a Machine Learning Approach
Kevin Dubois, Erik Nilsson, Morten Drews Dahl Andreas, Martin larsen, Magnus Hieronymus, Pasha Karami, Anna Rutgersson
In: Tellus. Series A, Dynamic meteorology and oceanography, Vol. 77, No. 1
2025
Abstract
Extreme sea levels are a major global concern due to their potential to cause fatalities and significant economic losses in coastal areas. Consequently, accurate projections of these extremes for the coming century are crucial for effective coastal planning. While it is well established that relative sea level rise driven by ongoing climate change is a key factor influencing future extreme sea levels, changes in storm surges resulting from shifts in storm climatology may also play a critical role. In this study, we project future daily maximum storm tides (the combination of storm surge and tides) using a random forest machine learning approach for 59 stations around the Baltic Sea, based on atmospheric variables such as surface pressure, wind speed, and wind direction derived from climate datasets. The results suggest both positive and negative changes, with sub-regional variations, in 50-year storm tide return levels across the Baltic Sea when comparing the period of 2070-2099 to 1850-1879. Localized increases of up to 10 cm are projected along the west coast of Sweden and the northern Baltic Sea, while decreases of up to 6 cm are anticipated along the south coast of Sweden, the Gulf of Riga, and the mouth of the Gulf of Finland. Negligible levels of change are expected in other parts of the Baltic Sea. The variability in atmospheric drivers across the four climate models contributes to a high degree of uncertainty in future climate projections.
SMHI recruits Professor of Oceanography
To further strengthen and profile SMHI's expertise in oceanographic research, the position of Professor of Oceanography is now advertised. With a focus on climate effects and other anthropogenic impacts on the ocean, operational oceanography and data assimilation or biogeochemical and physical processes and their impac...SMHI's research at EGU 2023
SMHI will participate in the annual research conference European Geosciences Union General Assembly in Vienna. This year SMHI's researchers will participate in various events within our disciplines of meteorology, hydrology, oceanography and climate.On a pathway to resilient and sustainable societies
The research project ARCPATH (Arctic Climate Predictions: Pathways to Resilient, Sustainable Societies) has been completed after four years. The aim of the project has been to investigate pathways to resilient and sustainable societies by developing climate projections in the Arctic and to interpret the effects of clim...