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The role of Near Real Time Envisat ASAR Global Monitoring mode data in Arctic and Antarctic operational ice services

Nick Walker(1) , David Simonin(1) , Kim Partington(1) , Towanda Street(2) , Pablo Clemente-Colon(2) , Sean Helfrich(2) , and Tommy Skagemo-Andreassen(3)

(1) Vexcel UK, 3, Great Farm Offices, Berkshire, RG20 0BP, United Kingdom
(2) National Ice Center, 4251 Suitland Road, Washington, D.C. 20395, United States
(3) Norwegian Meteorological Institute, PO Box 43 Blindern, 0313 Oslo, Norway


In this paper we describe and assess the role that Near Real Time Envisat ASAR Global Monitoring (GM) mode data has had as a source of information for the derivation of ice products within two leading operational ice services: (i) The U.S. National Ice Center (NIC), who have a global mandate to provide the strategic and tactical ice services. (ii) The Norwegian Meteorological Institute, who provide regular ice charts issued 5 days a week covering the area between Greenland and the Kara Sea.

ASAR GM mode data can be thought of as filling a “data gap” between low resolution (but high temporal acquisition frequency) sensors such as passive microwave and scatterometers and high resolution sensors (but low temporal acquisition frequency) such as Envisat and RadarSAT’s Wide Swath and Image modes. As such ASAR GM mode data has allowed a range of medium scale key ice features to be viewed with a frequency that was not previously possible.

Vexcel UK have been working in collaboration with the NIC and the Norwegian Meteorological Institute to develop new techniques for the provision of sea ice products and have played a key role in integrating ASAR GM mode data as a source of data used by ice analysts.

In this paper we describe and evaluate the role of ASAR GM mode within the context of an operational ice service. Specifically we examine: (a) In which Arctic and Antarctic geographic regions is ASAR GM mode most useful, i.e. where does it give the greatest added value in comparison with other available sensors? (b) What ice feature information (e.g. ice edge, leads, fractures, and polynyas, young ice, texture, multi-year versus first year discrimination) can be extracted that previously was not available? (c) How useful is ASAR GM data as a source of information for monitoring ice motion and ice tracking. (d) Data quality and timeliness. (e) And lessons learned for future mission concepts.


Full paper


  Higher level                 Last modified: 07.10.03