Sjøsprøyt-ising er fortsatt en stor utfordring for sikre og bærekraftige operasjoner i Arktiske og kalde havområder. Når kraftig vind og bølger kaster sjøvann på fartøy og offshore-konstruksjoner, fryser dråpene raskt i temperaturer under frysepunktet, noe som fører til tung isdannelse. Denne prosessen utgjør en alvorlig risiko for fiskeri, havbruk, skipsfart, offshore vindkraft og oljevernoperasjoner ved å redusere stabilitet, begrense funksjonalitet og skape betydelige sikkerhetsfarer.
Prosjektet tar for seg denne utfordringen gjennom en tverrfaglig tilnærming som kombinerer modellering, simulering, feltobservasjoner og risikobasert beslutningsstøtte. Hovedmålet er å forbedre forståelsen av sjøsprøyt-ising og utvikle praktiske verktøy for aktører som må håndtere de tilhørende risikoene.
På modelleringsnivå bygger prosjektet videre på og forbedrer eksisterende isingsmodeller for å bedre kunne forutsi forekomst, hastighet og alvorlighetsgrad av ising. Disse forbedringene vil danne grunnlaget for en probabilistisk rammeverk som kan produsere langtids-klimatologi for sjøsprøyt-ising. Slike prognoser er avgjørende i en tid med raskt klimaendring og tilbaketrekking av havis, hvor maritim aktivitet i Arktis øker.
Utover modelleringen innhenter prosjektet kunnskap fra feltet. Data samles inn om mengde sjøsprøyt, meteorologiske og oseanografiske forhold samt isingshendelser gjennom lokal deltakelse fra fartøy og marine installasjoner. Dette empiriske materialet vil bidra til å teste og videreutvikle nye formuleringer for sprøyt-fluks og forbedre nøyaktigheten til modellene.
Beslutningstaking under usikkerhet er et annet hovedtema i prosjektet. Det undersøkes hvordan fiskerioperasjoner i Barentshavet håndterer isingsrisiko, blant annet gjennom intervjuer for å identifisere dagens praksis og utfordringer.
En viktig nyvinning er utviklingen av en interaktiv digital plattform. Denne plattformen vil samle inn feltobservasjoner gjennom folkeforskning (crowd sourcing), slik at sjøfolk, oppdrettere og andre aktører kan dele isingshendelser og miljøforhold i sanntid. Plattformen vil også kommunisere isingsrisikovurderinger og dermed skape en toveis utveksling mellom vitenskap og praksis.
Prosjektet er finansiert av Norges forskningsråd (MAROFF-programmet, 2021–2025) og gjennomføres av UiT Norges arktiske universitet (prosjekteier) i samarbeid med SINTEF Nord AS, Meteorologisk institutt, Gratanglaks AS, Kystverket og Hermes AS. Sammen bringer disse partnerne inn kompetanse fra forskning, industri og forvaltning for å sikre at prosjektets resultater blir relevante, praktiske og bredt anvendbare.
The SPRICE project has transformed anticipated outcomes into tangible results. New equipment for spray flux measurement was successfully developed and deployed at Arctic field sites, alongside instruments for collecting detailed meteorological and oceanographic data. Together, these provided a unique dataset that has improved understanding of icing processes and created a strong foundation for testing, calibrating, and refining icing models.
Building on these data, enhanced icing models and data-driven approaches were developed to better predict the occurrence, growth, and severity of spray icing. A probabilistic framework for long-term climatology was introduced, and benchmarking of modern machine learning methods demonstrated promising potential for improving extended forecasts. These advances directly support safer and more sustainable decision-making for Arctic maritime operations.
The project has also delivered important capacity-building. A PhD thesis completed under SPRICE developed new measurement instruments, collected unique field data, and applied both statistical and machine learning techniques to improve marine icing models. This contribution strengthens long-term scientific expertise and capacity in Arctic safety research.
In addition to scientific advances, practical decision-making tools were created. Icing forecasts were linked with risk-informed decision support. An interactive digital platform is also under development, enabling stakeholders to crowdsource field observations and share icing risk assessments in real time. This creates a direct channel between science and practice.
The outcomes of the project have broad impacts. For industry, improved icing forecasts enable earlier and more efficient de-icing, reduce downtime, and lower operational costs. For society, safer operations at sea mean fewer accidents and less risk for those working in harsh Arctic conditions. For the environment, more targeted use of energy-intensive de-icing methods reduces unnecessary energy consumption and CO2 emissions, aligning with sustainability goals. On a broader level, the project also contributes to climate adaptation strategies by linking icing forecasts to long-term changes in sea ice and climate.
Looking ahead, ongoing publications, continued development of the digital platform, and close collaboration with industry partners will ensure that these outcomes are not only scientifically recognised but also widely applied. In this way, SPRICE will continue to strengthen Arctic maritime safety, sustainability, and resilience beyond the project’s completion.
Sea spray icing is a unique issue to marine operations in the Arctic offshore water and in cold water. Understanding this phenomenon is important in such regions as it imposes limitations and contributes to increased risk in a wide range of marine sectors including, fishing, fish farms, offshore wind farms, tourism, oil and gas, and shipping. Beyond operational risks, spray icing poses safety hazards for the crew and the vessel stability.
By developing models and simulation frameworks for prediction of spray-icing evens, this project helps decision-makers in technology and social science-related fields in the Norwegian maritime sector be equipped with better tools that support spray icing-related decision-making, risk perception, and operational safety, particularly due to operator error and interaction failure. The information and products developed in this project will help to also support the design and operation of anti-/de-icing measures as well as potentially reduce energy consumption and CO2 emissions from such measures. Moreover, we will develop a platform as part of this project to share data and information with a variety of end users about icing events. Importantly, we will collect and integrate end user feedback to co-produce this platform. This end user feedback will also ultimately improve the spray icing models and decision support models developed in this project. A feedback loop with end users is established over the course of the project via three separate workshops where end user, marine industry, and research community representatives will discuss various elements of our developed models and frameworks. This process of knowledge creation, knowledge exchange, and building competence concerning spray icing in the Arctic will consequently help to create an information landscape that supports holistic and informed decision-making in spray icing emergency contexts.
