Lagrangian Assimilation of Satellite Data for Climate Studies in the Arctic

• Main Authors: Stern, Harry, Lindsay, Ronald W., Zhang, Jin-Lun
• Language: unknown
• Published: 2004
• Subjects: Meteorology and Climatology; Arctic; Sea ice
• Online Access: http://hdl.handle.net/2060/20040086560

Under this grant we have developed and tested a new Lagrangian model of sea ice. A Lagrangian model keeps track of material parcels as they drift in the model domain. Besides providing a natural framework for the assimilation of Lagrangian data, it has other advantages: 1) a model that follows material elements is well suited for a medium such as sea ice in which an element retains its identity for a long period of time; 2) model cells can be added or dropped as needed, allowing the spatial resolution to be increased in areas of high variability or dense observations; 3) ice from particular regions, such as the marginal seas, can be marked and traced for a long time; and 4) slip lines in the ice motion are accommodated more naturally because there is no internal grid. Our work makes use of these strengths of the Lagrangian formulation.