ceaice_split_version/ceaice_part1/ceaice_abstract.tex

\begin{abstract}
This paper describes the MITgcm
sea ice model; it presents example Arctic and Antarctic results from a
realistic, eddying, global ocean and sea ice configuration;
and it compares B-grid and C-grid dynamic solvers and other
numerical details of the parameterized dynamics and thermodynamics in a
regional Arctic
configuration.
Ice mechanics follow a viscous-plastic rheology and the ice momentum
equations are solved numerically using either
line-successive-over-relaxation (LSOR) or elastic-viscous-plastic
(EVP) dynamic models.  Ice thermodynamics are represented using either
a zero-heat-capacity formulation or a two-layer formulation that
conserves enthalpy. The model includes prognostic variables for snow
and for sea ice salinity. The above sea ice model components were
borrowed from current-generation climate models but they were
reformulated on an Arakawa~C grid in order to match the MITgcm oceanic
grid and they were modified in many ways to permit efficient and
accurate automatic differentiation. %
Both stress tensor divergence and advective terms are discretized with
the finite-volume method. % 
The choice of the dynamic solver has a considerable
effect on the solution; this effect can be larger than, for example,
the choice of lateral boundary conditions, of ice rheology, and of
ice-ocean stress coupling. The solutions obtained with different
dynamic solvers typically differ
by 4\,cm\,s$^{-1}$ in ice drift speeds, 1\,m in ice thickness, and
order 300\,km$^3$\,yr$^{-1}$ in fresh water (ice and snow) export
out of the Arctic.

\end{abstract}

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1	heimbach	1.1	\begin{abstract}
2	cnh	1.8	This paper describes the MITgcm
3			sea ice model; it presents example Arctic and Antarctic results from a
4			realistic, eddying, global ocean and sea ice configuration;
5			and it compares B-grid and C-grid dynamic solvers and other
6			numerical details of the parameterized dynamics and thermodynamics in a
7			regional Arctic
8			configuration.
9			Ice mechanics follow a viscous-plastic rheology and the ice momentum
10	mlosch	1.2	equations are solved numerically using either
11			line-successive-over-relaxation (LSOR) or elastic-viscous-plastic
12			(EVP) dynamic models. Ice thermodynamics are represented using either
13			a zero-heat-capacity formulation or a two-layer formulation that
14	mlosch	1.9	conserves enthalpy. The model includes prognostic variables for snow
15			and for sea ice salinity. The above sea ice model components were
16	mlosch	1.2	borrowed from current-generation climate models but they were
17	mlosch	1.3	reformulated on an Arakawa~C grid in order to match the MITgcm oceanic
18	mlosch	1.2	grid and they were modified in many ways to permit efficient and
19	mlosch	1.9	accurate automatic differentiation. %
20			Both stress tensor divergence and advective terms are discretized with
21			the finite-volume method. %
22	cnh	1.8	The choice of the dynamic solver has a considerable
23	mlosch	1.3	effect on the solution; this effect can be larger than, for example,
24	dimitri	1.4	the choice of lateral boundary conditions, of ice rheology, and of
25	mlosch	1.3	ice-ocean stress coupling. The solutions obtained with different
26	mlosch	1.5	dynamic solvers typically differ
27			by 4\,cm\,s$^{-1}$ in ice drift speeds, 1\,m in ice thickness, and
28	dimitri	1.6	order 300\,km$^3$\,yr$^{-1}$ in fresh water (ice and snow) export
29	mlosch	1.3	out of the Arctic.
30	heimbach	1.1
31			\end{abstract}
32	mlosch	1.3
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