|Antarctic and Arctic
Sea Ice Data
|- From GIOMAS
(Global Ice-Ocean Modeling and
Description of The Global Ice-Ocean
Modeling and Assimilation System (GIOMAS)
sea ice data are produced by GIOMAS, which consists of a global Parallel Ocean and sea Ice Model (POIM,
Zhang and Rothrock 2003) with data assimilation
capabilities. The POIM is formulated in a generalized orthogonal
curvilinear coordinate (GOCC) system and designed to run on
computers with a single processor or massively parallel
processors. The POIM couples the Parallel Ocean
Program (POP) with a thickness and enthalpy
distribution (TED) sea-ice model.
The POP model is developed at the Los Alamos National Laboratory.
sea-ice model is a dynamic thermodynamic model that also
explicitly simulates sea-ice ridging. The model originates from
the Thorndike et al. (1975) thickness distribution theory and is
recently enriched by enthalpy distribution theory (Zhang
and Rothrock, 2001). It has 8 categories each for ice
thickness, ice enthalpy, and snow. This multicategory TED model
consists of seven main components: a viscous-plastic ice rheology
that determines the relationship between ice internal stress and
ice deformation (Hibler 1979), a mechanical redistribution
function that determines ice ridging (Thorndike et al. 1975;
Rothrock, 1975; Hibler, 1980), a momentum equation that determines
ice motion, a heat equation that determines ice growth/decay and
ice temperature, an ice thickness distribution equation that
conserves ice mass (Thorndike et al. 1975; Hibler, 1980), an ice
enthalpy distribution equation that conserves ice thermal energy (Zhang
and Rothrock, 2001), and a snow thickness distribution
equation that conserves snow mass (Flato and Hibler, 1995). The
ice momentum equation is solved using Zhang
Hibler's (1997) ice dynamics model that employs a
line successive relaxation technique with a tridiagonal matrix
solver, which has been found to be particularly useful for
parallel computing (Zhang and
Rothrock, 2003). The heat equation is solved over
each ice thickness category using a modified three-layer
thermodynamic model (Winton, 2000).
ice concentration data are assimilated in GIOMAS using the Lindsay
and Zhang (2005) assimilation procedure. The procedure is based on “nudging”
the model estimate of ice concentration toward the observed
concentration in a manner that emphasizes the ice extent and
minimizes the effect of observational errors in the interior of
the ice pack.
configuration of the finite-difference grid of GIOMAS is shown
horizontal dimension of the model is 360×276. In the southern
hemisphere the model grid is based on a spherical coordinate
system. In the northern hemisphere the model grid is a stretched
GOCC grid with the northern grid pole displaced into Greenland.
This allows the model to have its highest resolution in the
Greenland Sea, Baffin Bay, and the eastern Canadian Archipelago,
and therefore a good connection between the Arctic Ocean and
the Atlantic Ocean via the Greenland-Iceland-Norwegian (GIN) Sea
and the Labrador Sea. The model was driven by the NCEP/NCAR
S., D. A. Rothrock, G. A. Maykut, and R. Colony, 1975: The
thickness distribution of sea ice. J. Geophys. Res., 80,
Hibler, W. D.
III, 1979: A dynamic thermodynamic sea ice model. J. Phys.
Oceanogr., 9, 815-846.
Hibler, W. D.
III, 1980: Modeling a variable thickness sea ice cover. Mon. Wea.
Rev., 108, 1943-1973.
Flato, G. M.,
and W. D. Hibler, III, 1995: Ridging and strength in modeling the
thickness distribution of Arctic sea ice. J. Geophys. Res., 100,
M., 2000: A reformulated three-layer sea ice model. J. Atmos.
Ocean. Tech., 17, 525-531.
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