We develop and apply ocean models to understand ocean currents, temperature, salinity and biological processes in the marine environment. Our expertise covers model development, scenario analyses, data assimilation, uncertainty assessment and interpretation of model results.
This expertise is applied in aquaculture, fisheries, offshore operations, environmental management and defence, including the calculation of current conditions, the spread of disease, particles and pollution, as well as the study of climate change impacts. Ocean models are also used for a wide range of other purposes where knowledge of the state and development of the ocean is important.
Ocean models and observation systems
Mathematical modelling is a key component of modern ocean research. Ocean models are advanced tools used to simulate physical, chemical and biological processes in the marine environment. By describing the interactions between these processes, the models provide insight into how marine ecosystems function and how they are affected by changes in climate, the marine environment and human activities.
We use our expertise in ocean modelling to develop knowledge and decision support for marine industries such as aquaculture, fisheries, offshore operations, and ocean and environmental management.
Ocean modelling also makes it possible to study the consequences of global challenges such as climate change, ocean warming and increasing atmospheric CO₂ concentrations.
Model systems are important tools for understanding the effects of human-induced pressures and for developing knowledge-based solutions for the sustainable management of marine resources and ocean-based industries.
Ocean models can help answer questions such as:
- What effects do nutrient discharges and releases of organic material from the aquaculture industry have on marine ecosystems?
- How large are these discharges relative to the natural supply of nutrients?
- How do they affect plankton production and oxygen levels locally and at larger scales?
- How do they contribute to algal blooms?
- How do offshore wind farms affect ocean currents and plankton distribution?
From observations to better models
To ensure that models provide reliable results, they must be continuously tested and improved through comparison with observational data from the ocean. This process is known as model validation and is a fundamental part of model development.
To further reduce uncertainty, data assimilation is used, whereby observations are integrated directly into the models while simulations are running. This makes it possible to continuously correct model calculations and improve both the representation of current conditions and forecasts of future developments.
The observation pyramid and data assimilation
Effective data assimilation requires measurements from a wide range of sources. Data are collected using, among other things, satellites, drones, buoys, autonomous surface vessels and underwater vehicles. Together, these platforms form an observation pyramid, in which measurements at different spatial and temporal scales are combined to provide a comprehensive picture of the marine environment.
The observation pyramid is a central concept in marine research and education at NTNU (FjordLab) and SINTEF (Gemini Centre for Ocean Modelling). Through the integration of observations and models, it contributes to a deeper understanding of marine processes and provides a stronger foundation for research, management and the sustainable use of the ocean.