ceaice_split_version/ceaice_part1/ceaice_model.tex

\section{Sea ice model formulation}
\label{sec:model}

%Traditionally, probably for historical reasons and the ease of
%treating the Coriolis term, most standard sea-ice models are
%discretized on Arakawa~B grids \citep[e.g.,][]{hibler79, harder99,
%  kreyscher00, zhang98, hunke97}, although there are sea ice models
%discretized on a C~grid \citep[e.g.,][]{ip91, tremblay97,
%  lemieux08}. %
%\ml{[there is also MI-IM, but I only found this as a reference:
%  \url{http://retro.met.no/english/r_and_d_activities/method/num_mod/MI-IM-Documentation.pdf}]}
%From the perspective of coupling a sea ice-model to a C-grid ocean
%model, the exchange of fluxes of heat and fresh-water pose no
%difficulty for a B-grid sea-ice model \citep[e.g.,][]{timmermann02a}.
%However, surface stress is defined at velocity points and thus needs
%to be interpolated between a B-grid sea-ice model and a C-grid ocean
%model. Smoothing implicitly associated with this interpolation may
%mask grid scale noise and may contribute to stabilizing the solution.
%On the other hand, by smoothing the stress signals are damped which
%could lead to reduced variability of the system. By choosing a C-grid
%for the sea-ice model, we circumvent this difficulty altogether and
%render the stress coupling as consistent as the buoyancy coupling.

%A further advantage of the C-grid formulation is apparent in narrow
%straits. In the limit of only one grid cell between coasts there is no
%flux allowed for a B-grid (with no-slip lateral boundary conditions),
%and models have used topographies with artificially widened straits to
%avoid this problem \citep{holloway07}. The C-grid formulation on the
%other hand allows a flux of sea-ice through narrow passages if
%free-slip along the boundaries is allowed. We demonstrate this effect
%in the Canadian Arctic Archipelago (CAA).

The MITgcm sea ice model is based on a variant of the
viscous-plastic (VP) dynamic-thermodynamic sea-ice model of
\citet{zhang97} first introduced by \citet{hibler79, hibler80}.
Many aspects of the original codes have been
adapted 
\begin{itemize}
\item the model has been rewritten for an Arakawa~C grid, both B- and
  C-grid variants are available; the C-grid code allows for no-slip
  and free-slip lateral boundary conditions,
\item two different solution methods for solving the nonlinear
  momentum equations, LSOR \citep{zhang97} and EVP
  \citep{hunke97, hunke01}, have been adopted,
\item ice-ocean stress can be formulated as in \citet{hibler87},
\item ice concentration and thickness, snow, and ice salinity or enthalpy can
  be advected by sophisticated, conservative
  advection schemes with flux limiters, and
\item growth and melt parameterizations have been refined and extended
  in order to allow for automatic differentiation of the code.
\end{itemize}
The sea ice model is tightly coupled to the ocean component of the
MITgcm \citep{marshall97:_hydros_quasi_hydros_nonhy,marshall97:_finit_volum_incom_navier_stokes}.
Heat, fresh water fluxes and surface stresses are computed from the
atmospheric state and modified by the ice model at every time step.
The remainder of this section describes the model equations and
details of their numerical realization. Further documentation and
model code can be found at \url{http://mitgcm.org}.

\subsection{Dynamics}
\label{sec:dynamics}

Sea-ice motion is driven by ice-atmosphere, ice-ocean and internal
stresses. The internal stresses are evaluated following a
viscous-plastic (VP) constitutive law with an elliptic yield curve as
in \citet{hibler79}. The full momentum equations for the sea-ice model
and the solution by line successive over-relaxation (LSOR) are
described in \citet{zhang97}.  Alternatively, the momentum equation
can be solved with an elastic-viscous-plastic (EVP) solver following
\citet{hunke01}. In this technique, the evolution equations for the
internal stress tensor components are solved by sub-cycling the sea ice
momentum solver within one ocean model time step.

In both cases, the bulk viscosities can be bounded from above (if
required for numerical reasons). For stress tensor computations the
replacement pressure \citep{hibler95} is used so that the stress state
always lies within the elliptic yield curve by definition. Alternatively,
in the so-called truncated ellipse method (TEM) the shear viscosity is
capped to suppress any tensile stress \citep{hibler97, geiger98}.

The horizontal gradient of the ocean's surface is estimated directly
from ocean sea surface height and pressure loading from atmosphere,
ice and snow \citep{campin08}.  Ice does not float on top of the
ocean, instead it depresses the ocean surface according to its thickness and
buoyancy.

Lateral boundary conditions are naturally ``no-slip'' for B~grids, as
the tangential velocities points lie on the boundary. For C~grids, the
lateral boundary condition for tangential velocities
allow alternatively no-slip or free-slip
conditions. In ocean models free-slip boundary conditions in
conjunction with piecewise-constant (``castellated'') coastlines have
been shown to reduce to no-slip boundary conditions
\citep{adcroft98:_slippery_coast}; for coupled ocean sea-ice models the effects of
lateral boundary conditions have not yet been studied (as far as we
know).

Moving sea ice exerts a surface stress on the ocean. In coupling the
sea-ice model to the ocean model, this stress is applied directly to
the surface layer of the ocean model. An alternative ocean stress
formulation is given by \citet{hibler87}. Rather than applying the
interfacial stress directly, the stress is derived from integrating
over the ice thickness to the bottom of the oceanic surface layer. In
the resulting equation for the combined ocean-ice momentum, the
interfacial stress cancels and the total stress appears as the sum of
wind stress and divergence of internal ice stresses \citep[see also
Eq.\,2 of][]{hibler87}. While this formulation tightly embeds the
sea ice into the surface layer of the ocean, its disadvantage is that
the velocity in the surface layer of the ocean that is used to
advect ocean tracers is really an average over the ocean surface
velocity and the ice velocity, leading to an inconsistency as the ice
temperature and salinity are different from the oceanic variables.
Both stress coupling options are available for a direct comparison of
the their effects on the sea-ice solution.

The discretization of the momentum equation is straightforward. It is
similar to that of \citet{zhang98, zhang03}, but differs fundamentally
in the underlying grid, namely the Arakawa~C grid. The EVP model, in
particular, is discretized naturally on the C~grid with the diagonal
components of the stress tensor on the center points and the
off-diagonal term on the corner (or vorticity) points of the grid.
With this choice all derivatives are discretized as central
differences and very little averaging is involved. Apart from the
standard C-grid implementation, the original B-grid implementation of
\citet{zhang97} is also available as an option in the code.

\subsection{Thermodynamics}
\label{sec:thermodynamics}

Upward conductive heat flux
is parameterized assuming a linear temperature profile and a constant
ice conductivity. This type of model is often referred to as a
``zero-layer'' model \citet{semtner76}. The surface heat flux is computed in a similar
way to that of \citet{parkinson79} and \citet{manabe79}.

The conductive heat flux depends strongly on the ice thickness $h$.
However, the ice thickness in the model represents a mean over a
potentially very heterogeneous thickness distribution.  In order to
parameterize a sub-grid scale distribution for heat flux computations,
the mean ice thickness $h$ is split into seven thickness categories
$H_{n}$ that are equally distributed between $2h$ and a minimum
imposed ice thickness of $5\text{\,cm}$ by $H_n= \frac{2n-1}{7}\,h$
for $n\in[1,7]$. The heat fluxes computed for each thickness category
is area-averaged to give the total heat flux \citep{hibler84}.

The atmospheric heat flux is balanced by an oceanic heat flux.
The oceanic flux is proportional to the difference between
ocean surface temperature and the freezing point temperature of sea
water, which is a function of salinity.
This flux is not assumed to instantaneously melt
or create ice, but a time scale of three days is used to relax the
ocean temperature to the freezing point. While this
parameterization is not new \citep[it follows the ideas of,
e.g.,][]{mellor86, mcphee92, lohmann98, notz03}, it avoids a
discontinuity in the functional relationship between model variables,
which is crucial for making the code differentiable for adjoint code
generation (see companion, part 2, paper).
%\ml{[ONCE IT IS SUBMITTED, otherwise pers. communcations:]}\citep{fen09}
The parameterization of lateral and vertical growth of sea ice follows
that of \citet{hibler79, hibler80}.

On top of the ice there is a layer of snow that modifies the heat flux
and the albedo as in \citet{zhang98}.  If enough snow accumulates so
that its weight submerges the ice and the snow is flooded, a simple
mass conserving parameterization of snow ice formation (a flood-freeze
algorithm following Archimedes' principle) turns snow into ice until
the ice surface is back at $z=0$ \citep{leppaeranta83}.

The concentration $c$, effective ice thickness (ice volume per unit
area, $c\cdot{h}$), effective snow thickness ($c\cdot{h}_{s}$), and effective
ice salinity (in g\,m$^{-2}$) are advected by ice velocities.
%
From the various advection scheme that are available in the MITgcm
\citep{mitgcm02}, we choose flux-limited schemes, i.e., multidimensional 2nd
and 3rd-order advection schemes with flux limiters
\citep{roe85, hundsdorfer94}, to preserve sharp gradients and
edges that are typical of sea ice distributions and to rule out
unphysical over- and undershoots (negative thickness or
concentration). These schemes conserve volume and horizontal area and
are unconditionally stable, so that no extra diffusion is required.

There is considerable doubt about the reliability of a
``zero-layer'' thermodynamic model --- \citet{semtner84} found
significant errors in phase (one month lead) and amplitude
($\approx$50\%\,overestimate) in such models --- so that today many
sea ice models employ more complex thermodynamics. The MITgcm
sea ice model provides the option to use the thermodynamics model of
\citet{winton00}, which in turn
is based on the 3-layer model of \citet{semtner76} and which treats brine
content by means of enthalpy conservation. This scheme requires
additional state variables, namely the enthalpy of the two ice
layers (instead of effective ice salinity), to be advected by ice velocities.
%  \ml{[Jean-Michel, your
%  turf: ]Care must be taken in advecting these quantities in order to
%  ensure conservation of enthalpy. Currently this can only be
%  accomplished with a 2nd-order advection scheme with flux limiter
%  \citep{roe85}.}
The internal sea ice temperature is inferred from ice enthalpy.
To avoid unphysical (negative) values for ice thickness and
concentration, a positive 2nd-order advection scheme with a SuperBee
flux limiter \citep{roe85}
is used in this study to advect all sea-ice-related
quantities of the \citet{winton00} thermodynamic model.
Because of the non-linearity of the advection scheme,
care must be taken in advecting these quantities: when simply using 
ice velocity to advect enthalpy, the total energy (i.e., the volume
integral of enthalpy) is not conserved. Alternatively, one can advect 
the energy content (i.e., product of ice-volume and enthalpy)
but then false enthalpy extrema can occur,
which then leads to unrealistic ice temperature.
In the currently implemented solution, the sea-ice mass flux is used
to advect the enthalpy in order to ensure conservation of enthalpy
and to prevent false enthalpy extrema.

In \refsec{globalmodel} and \ref{sec:arcticmodel}
we exercise and compare several
of the options, which have been discussed above, intercompare
the impact of the different formulations (all of which are widely
used in sea ice modeling today) on Arctic sea ice simulation 
\citep{prosh07:_aomipspecial}.
%% Got to here..... more later
%% Add reference to JGR special issue here.....

%%% Local Variables: 
%%% mode: latex
%%% TeX-master: "ceaice_part1"
%%% End: 
1	cnh	1.16	\section{Sea ice model formulation}
2	heimbach	1.1	\label{sec:model}
3
4	mlosch	1.2	%Traditionally, probably for historical reasons and the ease of
5			%treating the Coriolis term, most standard sea-ice models are
6	mlosch	1.15	%discretized on Arakawa~B grids \citep[e.g.,][]{hibler79, harder99,
7	mlosch	1.2	% kreyscher00, zhang98, hunke97}, although there are sea ice models
8	mlosch	1.15	%discretized on a C~grid \citep[e.g.,][]{ip91, tremblay97,
9	mlosch	1.5	% lemieux08}. %
10	mlosch	1.2	%\ml{[there is also MI-IM, but I only found this as a reference:
11			% \url{http://retro.met.no/english/r_and_d_activities/method/num_mod/MI-IM-Documentation.pdf}]}
12			%From the perspective of coupling a sea ice-model to a C-grid ocean
13			%model, the exchange of fluxes of heat and fresh-water pose no
14			%difficulty for a B-grid sea-ice model \citep[e.g.,][]{timmermann02a}.
15			%However, surface stress is defined at velocity points and thus needs
16			%to be interpolated between a B-grid sea-ice model and a C-grid ocean
17			%model. Smoothing implicitly associated with this interpolation may
18			%mask grid scale noise and may contribute to stabilizing the solution.
19			%On the other hand, by smoothing the stress signals are damped which
20			%could lead to reduced variability of the system. By choosing a C-grid
21			%for the sea-ice model, we circumvent this difficulty altogether and
22			%render the stress coupling as consistent as the buoyancy coupling.
23
24			%A further advantage of the C-grid formulation is apparent in narrow
25			%straits. In the limit of only one grid cell between coasts there is no
26	jmc	1.9	%flux allowed for a B-grid (with no-slip lateral boundary conditions),
27	mlosch	1.2	%and models have used topographies with artificially widened straits to
28			%avoid this problem \citep{holloway07}. The C-grid formulation on the
29			%other hand allows a flux of sea-ice through narrow passages if
30			%free-slip along the boundaries is allowed. We demonstrate this effect
31	jmc	1.9	%in the Canadian Arctic Archipelago (CAA).
32	heimbach	1.1
33	dimitri	1.10	The MITgcm sea ice model is based on a variant of the
34	mlosch	1.2	viscous-plastic (VP) dynamic-thermodynamic sea-ice model of
35	cnh	1.16	\citet{zhang97} first introduced by \citet{hibler79, hibler80}.
36			Many aspects of the original codes have been
37			adapted
38	heimbach	1.1	\begin{itemize}
39	mlosch	1.15	\item the model has been rewritten for an Arakawa~C grid, both B- and
40	heimbach	1.1	C-grid variants are available; the C-grid code allows for no-slip
41	dimitri	1.11	and free-slip lateral boundary conditions,
42	heimbach	1.1	\item two different solution methods for solving the nonlinear
43	dimitri	1.11	momentum equations, LSOR \citep{zhang97} and EVP
44			\citep{hunke97, hunke01}, have been adopted,
45			\item ice-ocean stress can be formulated as in \citet{hibler87},
46			\item ice concentration and thickness, snow, and ice salinity or enthalpy can
47			be advected by sophisticated, conservative
48			advection schemes with flux limiters, and
49	heimbach	1.1	\item growth and melt parameterizations have been refined and extended
50			in order to allow for automatic differentiation of the code.
51			\end{itemize}
52	jmc	1.9	The sea ice model is tightly coupled to the ocean component of the
53	cnh	1.16	MITgcm \citep{marshall97:_hydros_quasi_hydros_nonhy,marshall97:_finit_volum_incom_navier_stokes}.
54	heimbach	1.1	Heat, fresh water fluxes and surface stresses are computed from the
55			atmospheric state and modified by the ice model at every time step.
56	mlosch	1.2	The remainder of this section describes the model equations and
57			details of their numerical realization. Further documentation and
58			model code can be found at \url{http://mitgcm.org}.
59
60			\subsection{Dynamics}
61			\label{sec:dynamics}
62
63			Sea-ice motion is driven by ice-atmosphere, ice-ocean and internal
64			stresses. The internal stresses are evaluated following a
65			viscous-plastic (VP) constitutive law with an elliptic yield curve as
66			in \citet{hibler79}. The full momentum equations for the sea-ice model
67			and the solution by line successive over-relaxation (LSOR) are
68			described in \citet{zhang97}. Alternatively, the momentum equation
69			can be solved with an elastic-viscous-plastic (EVP) solver following
70	mlosch	1.12	\citet{hunke01}. In this technique, the evolution equations for the
71	dimitri	1.6	internal stress tensor components are solved by sub-cycling the sea ice
72			momentum solver within one ocean model time step.
73	mlosch	1.2
74			In both cases, the bulk viscosities can be bounded from above (if
75			required for numerical reasons). For stress tensor computations the
76			replacement pressure \citep{hibler95} is used so that the stress state
77	cnh	1.16	always lies within the elliptic yield curve by definition. Alternatively,
78	mlosch	1.2	in the so-called truncated ellipse method (TEM) the shear viscosity is
79			capped to suppress any tensile stress \citep{hibler97, geiger98}.
80
81			The horizontal gradient of the ocean's surface is estimated directly
82			from ocean sea surface height and pressure loading from atmosphere,
83	dimitri	1.11	ice and snow \citep{campin08}. Ice does not float on top of the
84			ocean, instead it depresses the ocean surface according to its thickness and
85			buoyancy.
86	mlosch	1.2
87	mlosch	1.15	Lateral boundary conditions are naturally ``no-slip'' for B~grids, as
88			the tangential velocities points lie on the boundary. For C~grids, the
89	cnh	1.16	lateral boundary condition for tangential velocities
90			allow alternatively no-slip or free-slip
91	mlosch	1.2	conditions. In ocean models free-slip boundary conditions in
92			conjunction with piecewise-constant (``castellated'') coastlines have
93			been shown to reduce to no-slip boundary conditions
94	cnh	1.16	\citep{adcroft98:_slippery_coast}; for coupled ocean sea-ice models the effects of
95	mlosch	1.2	lateral boundary conditions have not yet been studied (as far as we
96			know).
97
98			Moving sea ice exerts a surface stress on the ocean. In coupling the
99	jmc	1.9	sea-ice model to the ocean model, this stress is applied directly to
100	mlosch	1.2	the surface layer of the ocean model. An alternative ocean stress
101			formulation is given by \citet{hibler87}. Rather than applying the
102			interfacial stress directly, the stress is derived from integrating
103			over the ice thickness to the bottom of the oceanic surface layer. In
104	mlosch	1.15	the resulting equation for the combined ocean-ice momentum, the
105	mlosch	1.2	interfacial stress cancels and the total stress appears as the sum of
106	dimitri	1.6	wind stress and divergence of internal ice stresses \citep[see also
107	mlosch	1.2	Eq.\,2 of][]{hibler87}. While this formulation tightly embeds the
108	mlosch	1.15	sea ice into the surface layer of the ocean, its disadvantage is that
109	dimitri	1.11	the velocity in the surface layer of the ocean that is used to
110			advect ocean tracers is really an average over the ocean surface
111			velocity and the ice velocity, leading to an inconsistency as the ice
112	mlosch	1.2	temperature and salinity are different from the oceanic variables.
113			Both stress coupling options are available for a direct comparison of
114			the their effects on the sea-ice solution.
115
116	dimitri	1.6	The discretization of the momentum equation is straightforward. It is
117	mlosch	1.2	similar to that of \citet{zhang98, zhang03}, but differs fundamentally
118	mlosch	1.15	in the underlying grid, namely the Arakawa~C grid. The EVP model, in
119			particular, is discretized naturally on the C~grid with the diagonal
120	mlosch	1.2	components of the stress tensor on the center points and the
121			off-diagonal term on the corner (or vorticity) points of the grid.
122			With this choice all derivatives are discretized as central
123			differences and very little averaging is involved. Apart from the
124			standard C-grid implementation, the original B-grid implementation of
125			\citet{zhang97} is also available as an option in the code.
126
127			\subsection{Thermodynamics}
128			\label{sec:thermodynamics}
129
130	cnh	1.16	Upward conductive heat flux
131	mlosch	1.2	is parameterized assuming a linear temperature profile and a constant
132	jmc	1.9	ice conductivity. This type of model is often referred to as a
133	cnh	1.16	``zero-layer'' model \citet{semtner76}. The surface heat flux is computed in a similar
134	mlosch	1.2	way to that of \citet{parkinson79} and \citet{manabe79}.
135
136			The conductive heat flux depends strongly on the ice thickness $h$.
137			However, the ice thickness in the model represents a mean over a
138			potentially very heterogeneous thickness distribution. In order to
139			parameterize a sub-grid scale distribution for heat flux computations,
140			the mean ice thickness $h$ is split into seven thickness categories
141			$H_{n}$ that are equally distributed between $2h$ and a minimum
142			imposed ice thickness of $5\text{\,cm}$ by $H_n= \frac{2n-1}{7}\,h$
143			for $n\in[1,7]$. The heat fluxes computed for each thickness category
144			is area-averaged to give the total heat flux \citep{hibler84}.
145
146	mlosch	1.12	The atmospheric heat flux is balanced by an oceanic heat flux.
147			The oceanic flux is proportional to the difference between
148	mlosch	1.3	ocean surface temperature and the freezing point temperature of sea
149	cnh	1.16	water, which is a function of salinity.
150			This flux is not assumed to instantaneously melt
151	mlosch	1.3	or create ice, but a time scale of three days is used to relax the
152	mlosch	1.8	ocean temperature to the freezing point. While this
153	dimitri	1.11	parameterization is not new \citep[it follows the ideas of,
154	mlosch	1.3	e.g.,][]{mellor86, mcphee92, lohmann98, notz03}, it avoids a
155			discontinuity in the functional relationship between model variables,
156	dimitri	1.6	which is crucial for making the code differentiable for adjoint code
157	cnh	1.16	generation (see companion, part 2, paper).
158	dimitri	1.13	%\ml{[ONCE IT IS SUBMITTED, otherwise pers. communcations:]}\citep{fen09}
159	mlosch	1.2	The parameterization of lateral and vertical growth of sea ice follows
160			that of \citet{hibler79, hibler80}.
161
162			On top of the ice there is a layer of snow that modifies the heat flux
163			and the albedo as in \citet{zhang98}. If enough snow accumulates so
164			that its weight submerges the ice and the snow is flooded, a simple
165	dimitri	1.11	mass conserving parameterization of snow ice formation (a flood-freeze
166	mlosch	1.2	algorithm following Archimedes' principle) turns snow into ice until
167			the ice surface is back at $z=0$ \citep{leppaeranta83}.
168
169			The concentration $c$, effective ice thickness (ice volume per unit
170	dimitri	1.11	area, $c\cdot{h}$), effective snow thickness ($c\cdot{h}_{s}$), and effective
171			ice salinity (in g\,m$^{-2}$) are advected by ice velocities.
172	mlosch	1.2	%
173			From the various advection scheme that are available in the MITgcm
174	dimitri	1.11	\citep{mitgcm02}, we choose flux-limited schemes, i.e., multidimensional 2nd
175			and 3rd-order advection schemes with flux limiters
176			\citep{roe85, hundsdorfer94}, to preserve sharp gradients and
177	mlosch	1.2	edges that are typical of sea ice distributions and to rule out
178			unphysical over- and undershoots (negative thickness or
179	dimitri	1.6	concentration). These schemes conserve volume and horizontal area and
180	mlosch	1.2	are unconditionally stable, so that no extra diffusion is required.
181
182	cnh	1.16	There is considerable doubt about the reliability of a
183	dimitri	1.11	``zero-layer'' thermodynamic model --- \citet{semtner84} found
184	mlosch	1.2	significant errors in phase (one month lead) and amplitude
185	dimitri	1.11	($\approx$50\%\,overestimate) in such models --- so that today many
186			sea ice models employ more complex thermodynamics. The MITgcm
187			sea ice model provides the option to use the thermodynamics model of
188			\citet{winton00}, which in turn
189			is based on the 3-layer model of \citet{semtner76} and which treats brine
190	cnh	1.16	content by means of enthalpy conservation. This scheme requires
191	jmc	1.9	additional state variables, namely the enthalpy of the two ice
192	dimitri	1.11	layers (instead of effective ice salinity), to be advected by ice velocities.
193	jmc	1.9	% \ml{[Jean-Michel, your
194			% turf: ]Care must be taken in advecting these quantities in order to
195			% ensure conservation of enthalpy. Currently this can only be
196			% accomplished with a 2nd-order advection scheme with flux limiter
197			% \citep{roe85}.}
198	dimitri	1.11	The internal sea ice temperature is inferred from ice enthalpy.
199	cnh	1.16	To avoid unphysical (negative) values for ice thickness and
200	mlosch	1.12	concentration, a positive 2nd-order advection scheme with a SuperBee
201			flux limiter \citep{roe85}
202			is used in this study to advect all sea-ice-related
203	dimitri	1.11	quantities of the \citet{winton00} thermodynamic model.
204	jmc	1.9	Because of the non-linearity of the advection scheme,
205			care must be taken in advecting these quantities: when simply using
206			ice velocity to advect enthalpy, the total energy (i.e., the volume
207			integral of enthalpy) is not conserved. Alternatively, one can advect
208			the energy content (i.e., product of ice-volume and enthalpy)
209			but then false enthalpy extrema can occur,
210			which then leads to unrealistic ice temperature.
211	mlosch	1.15	In the currently implemented solution, the sea-ice mass flux is used
212	cnh	1.17	to advect the enthalpy in order to ensure conservation of enthalpy
213	mlosch	1.15	and to prevent false enthalpy extrema.
214	heimbach	1.1
215	cnh	1.16	In \refsec{globalmodel} and \ref{sec:arcticmodel}
216			we exercise and compare several
217			of the options, which have been discussed above, intercompare
218			the impact of the different formulations (all of which are widely
219	cnh	1.17	used in sea ice modeling today) on Arctic sea ice simulation
220			\citep{prosh07:_aomipspecial}.
221	cnh	1.16	%% Got to here..... more later
222			%% Add reference to JGR special issue here.....
223	dimitri	1.11
224	heimbach	1.1	%%% Local Variables:
225			%%% mode: latex
226	mlosch	1.2	%%% TeX-master: "ceaice_part1"
227	heimbach	1.1	%%% End: