|Projections of an
- Retrospection and Future Projection
Jinlun Zhang, D.
Andrew Rothrock, and Michael Steele
Polar Science Center, Applied
Physics Laboratory, University of Washington
Funded by The National Science Foundation Office
of Polar Programs
A Pan-Arctic Ice-Ocean
Modeling and Assimilation System (PIOMAS) is used for this project.
PIOMAS is a coupled Parallel Ocean and sea Ice Model
and Rothrock 2003) with capabilities of assimilating ice
concentration and velocity data. It is formulated in a generalized
coordinate (GOCC) system and designed to run on computers with a single
processor or massively parallel processors. PIOMAS 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 12 categories each for ice thickness,
ice enthalpy, and snow ((Zhang et al., 2000).
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
Rothrock, 2003). The heat equation is solved over each ice
thickness category using a modified three-layer thermodynamic model
(Winton, 2000). The configuration of the finite-difference grid of
model grid is a stretched GOCC grid with the northern grid pole
displaced into Greenland. This causes the model to have its highest
resolution in the Greenland Sea, Baffin Bay, and the eastern Canadian
Archipelago. This lets the model have a
reasonably good connection between the Arctic Ocean and the Atlantic
Ocean via the Greenland-Iceland-Norwegian (GIN) Sea and the Labrador
horizontal resolution is 22 km for the Arctic, Barents, and GIN
(Greenland-Iceland-Norwegian) seas, and Baffin Bay.
is one-way nested to a global
(GIOMAS) by imposing open
boundary conditions along the southern boundaries (~ 43oN).
Monthly output from GIOMAS is used for the open boundary conditions.
The model was driven by the NCEP/NCAR reanalysis data.
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.