💎 Idea

Having information on the forces of sea ice is of pivotal importance for advances in forecasting and insights to Arctic conditions for ice navigation, regional outlook forecasting and general atmospheric and ocean climate interactions.   Information on these processes can be obtained through combination of satellite, atmospheric and ocean model data.

🚀 EU space technologies

The past, present and future radar satellite data of the Sentinel Earth Observation programs have detailed information on fractures and deformations in the ice that have information on the forces that are related to the action of winds and sea surface tilt.  These data are available through the WEkEO program and can be combined for innovation of Earth Observation Analytics for new insights.

❄️ Connecting the Arctic

The forces in sea ice make huge impact on navigability and risk associated with ice navigation and the breakup and opening and closing in the ice cover and the risk of hazardous conditions from different ice. The life on land in the Arctic depends on travel over ice for hunting and for transport of appliances.  Once the forces are capable of initiating breakup the conditions for life on land changes drastically.  

The most remarkable sites of vigorous wildlife in the Arctic is associated with open polynyas in straits and coastal impact on the ice drift such as in the Nares Strait and around North East Greenland. The vulnerability of these sites under future climate change scenarios depends on conditions for forces and can be studied and better understood through applying this new method.

We have proposed a solution that involves local indigenous people that may play a significant role in the value added chain of the data and information processing and enhance the product quality on site. 

Overview on the concept is in the attachment FASIF-hackathon.pdf and demonstration on how the value added process of making enhanced resolution and information content by combining high resolution imagery with lower resolution data fields.


Björn Erlingsson Arctic Research Scientist that has developed a method that is applied.   He has been involved in environmental forecasting since the '90.

Lampros Mouselimis, is a  self taught programmer (R, Python, C++) and data analyst. Besides using R, Python for data processing and analysis, he is capable of working with satellite imagery (Sentinel, MODIS, VIIRS). 

Ewen Jamet is a student of physical oceanography and has experience and background in processing of Copernicus data resources on Arctic ocean and sea ice parameters. (python, Matlab, C++)