Ongoing projects

ARCA

The project "Biocultural Heritage in Arctic Cities: Resource for Climate Adaptation?" aims to understand how traditional ecological knowledge and Indigenous knowledge, and human-environment relationships that form the core of biocultural heritage can contribute to climate change adaptation in urban areas and surrounding landscapes. The focus lies on Fairbanks and Nome (USA), and Kirkenes and Tromsø (Norway).  

ObsSea4Clim

Ocean observing is executed and financed by nations according to their national interest and needs, but aligned with European and international agreements and directives. To improve sustained and multipurpose observations vital to European and global climate requirements, the project "Ocean Observations and Indicators for Climate and Assessments" brings together key European actors within ocean observing science, climate assessment, Earth System modelling, data sharing and standards, with users of oceanographic products and services to deliver an improved observation framework based on essential ocean variables.

FOCCUS

The main ambition of the project "Forecasting and observing the open-to-coastal ocean for Copernicus users" is to improve and advance the coastal dimension of the Copernicus Marine Environment Monitoring Service by enhancing existing capability, developing innovative coastal products.

DynAMIC

The project "Detecting episodes of Arctic sea ice Mass Imbalance" will combine existing satellites to detect 3D sea-ice mass balance snapshots. The project will use machine learning to optimise the sea ice ridging scheme in models and build Norwegian capacity in sea-ice observation-model integration.

C3-eKerala

In the project "Climate change impact on the marine coastal ecosystem of Kerala", researchers from the Nansen Center and India investigate how climate change, through sea-level rise and waves, affects the coasts and ecosystems along the coast in the state of Kerala in India. They want to find out more about the changes so that authorities and societal actors can better plan climate adaptation measures.

NorHAB-ML

Harmful algae blooms happen when specific algae produce toxins. They have impacts on both human health and on the economy of aquacultures. The project “Machine learning for prediction and projection of harmful algae blooms hazards” aims to enhance the accuracy of predicting harmful algae blooms (HABs). In particular, the project will develop a new algorithm for improving the accuracy of remote sensing on the Norwegian shelf and using coastal modelling products. NorHAB-ML aims to predict HABs harmful for aquaculture accurately, as well as high biomass bloom that can be harmful to fisheries. The geographic focus lies on the Norwegian coastal and shelf waters.

SuperIce

High resolution of sea-ice thickness is instrumental to provide better seasonal forecasts over the Arctic and to better understand energy fluxes between ocean and atmosphere. The "SuperIce" project will leverage artificial intelligence techniques and physical simulation of the sea-ice model neXtSIM to enhance the spatial resolution of current satellite observations of the Arctic sea ice.

AOOS

The project "Technologies and collaboration for sustained Arctic Ocean Observing System" aims to draw up an international collaboration agreement for the establishment and operation phase of an Arctic ocean observation system based on in-situ measurement systems, and will contribute to positioning Norway in the management of the system where Norwegian industry is engaged.

SCOPE

Carbon in the sea is of great importance for the carbon cycle and thus the climate. How the amount and distribution of carbon changes over time is something that the researchers in the project "Satellite-based observations of Carbon in the Ocean: Pools, fluxes and Exchanges" study with the help of satellites.

APASIP

In order to produce automated ice maps over the entire Arctic region, the researchers in the project "Automatic pan-Arctic Sea Ice Product from high-resolution satellite data" are developing automatic algorithms to retrieve sea ice concentration and ice type from satellite data using artificial intelligence.