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POLARPROG-Polarforskningsprogram

Multi-scale integration and digitalization of Arctic sea ice observations and prediction models

Alternative title: Multiskala integrasjon og digitalisering av Arktiske sjøisobservasjoner og prognosemodeller

Awarded: NOK 10.0 mill.

Project Manager:

Project Number:

328960

Project Period:

2022 - 2025

Funding received from:

Partner countries:

DigitalSeaIce – Chinese-Norwegian research collaboration on precise forecasting of ice conditions in the Arctic. A strong research collaboration between the universities NTNU, Jiangsu, and Dalian and the Ice Service at MET will give better insight in polar Earth systems that can be useful both in predicting ice conditions and improving maritime safety in the Arctic Ocean. The primary objective is to build a multiscale digital infrastructure that connects sea ice forecasting models on a regional scale with local and more detailed ice-ice and ice-structure discrete element models. These models are then updated by in-situ and shipboard measurements locally and regionally by satellite measurements. This will enable improved spatial and temporal resolution in our models, to achieve more precise forecasting of ice conditions in the Arctic – including better understanding of long-term variations in the polar ice cover. Novel methods for use of artificial intelligence (AI)-based analytics of synthetic aperture radar (SAR) and optical imagery from satellites, marine radars, visual and infrared cameras, and other enabling technologies will be developed in the project. The secondary objectives are to accurately map the sea ice flow in high resolution and generate quality-controlled sea ice drift forecasting. Novel methods for monitoring and analysis of sea ice dynamics and fracturing processes based on data from heterogenous sources will be developed. This will be used to update the multiscale model from the real observations. The expected impact is novel methods and a digital infrastructure for improved spatial and temporal forecasting and decision support in an increasingly dynamic Arctic environment due to climate changes. Such infrastructure will enable more accurate data and information to be produced, thus resulting in better insight on polar Earth systems. A biproduct is improved decision support for maritime safety.

The Norwegian partners will collaborate with Chinese partners on the project “Multiscale integration and digitalization of Arctic sea ice observations and prediction models”. The main objective is to build a multiscale digital infrastructure that integrates regional sea ice forecasting models and local ice-ice/ice-structure numerical models (based on discrete elements) with in-situ, shipboard, and satellite-based Arctic sea ice and environmental observations. The aim is to enable improved spatial and temporal resolution to achieve more precise forecasting of ice conditions in the Arctic – including better understanding of long-term variations in polar ice cover. A common methodology to achieve this is the use of AI-based analytics of synthetic aperture radar (SAR) and optical imagery from satellites, marine radars, and visual and infrared cameras. The Norwegian partners will mainly focus on technology research, particular on intelligent regional and local sea ice observations and corresponding ice model integration (WP1, WP2), and multi-scale integration in a digital infrastructure (WP4). The Chinese partners will mainly be responsible for sea ice data in regions of relevance and development of analytics and model development (WP3), and exploitation of results to maritime safety (WP5). All partners will collaborate on tasks in the work packages. The project activities and responsibilities of tasks are summarized below: WP1: Intelligent regional observations and large-scale ice drift model integration WP2: Intelligent local-scale observations and analytics WP3: In-situ measurements, data analytics, and multiscale modeling WP4: Multiscale integration of ice dynamics models WP5: Exploitation of results

Publications from Cristin

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Funding scheme:

POLARPROG-Polarforskningsprogram