Description
of
The
Global Ice-Ocean Modeling
and Assimilation System (GIOMAS)
The global
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.
The TED
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
and
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).
Satellite sea
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.
The
configuration of the finite-difference grid of GIOMAS is
shown below.
The
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 reanalysis data.
References
Thorndike, A.
S.,
D. A. Rothrock, G. A. Maykut, and R. Colony, 1975:
The thickness distribution of sea ice. J. Geophys. Res., 80,
4501-4513.
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, 18,611-18,626.
Winton,
M.,
2000: A reformulated three-layer sea ice model. J.
Atmos. Ocean. Tech., 17, 525-531.