Improving Sea Ice Forecasting by National Ice Centres

Application

National ice centres throughout the world have mandates from their respective governments to monitor and chart sea ice and iceberg conditions in their particular areas of interest. This is a significant activity and involves the manual interpretation of large volumes of satellite data for ice chart production, which is labour intensive, slow and lacks consistency between ice centres as well as inside the same ice centre.

With the large volume of Sentinel-1 SAR data expected from early 2015 onwards, a more automated and rigorous analysis method that allows the combination of SAR, microwave radiometer data, infrared data, scatterometer data and visible data, as well as state of the art numerical weather prediction data is needed.

Current effort is directed at collation of data from multiple sources and (building on the previous development of satellite data assimilation in an ice analysis system) establishing an automated ice analysis system with the aim of being able to produce a regularly updated Arctic wide ice analysis every six hours.

The data assimilation system will build on previous ESA efforts such as SAR Ice constellation (STSE), Sea-ice CCI, SMOSICE etc, since radiative transfer models and backscatter models developed in these projects will be key elements in quantitatively relating satellite observations to surface ice conditions.

[Figure 3: Greenland ice chart produced by DMI.]

Role of the Polar TEP

Development and operations of such a large scale and complex data assimilation system will depend on established access to all required datasets and a programming environment within which to develop, deploy and operate the necessary algorithms. The storage and processing requirements required for this task are significant and most readily provided in close proximity to the required data resources.

In addition production of a regular ice analysis will require regular validation using independent data, which will be more easily achieved within the established processing chain given access to the necessary observation data.

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