ceaice_split_version/ceaice_part1/ceaice_model.tex

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

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; these are the most important ones:
\begin{itemize}
\item the model has been rewritten for an Arakawa~C grid, both B- and
  C-grid variants are available; the finite-volume 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{hunke01, hunke02}, have been adopted,
\item ice-ocean stress can be formulated as in \citet{hibler87} as an
  alternative to the standard method of applying ice-ocean stress
  directly,
\item ice concentration and thickness, snow, and ice salinity or enthalpy can
  be advected by sophisticated, conservative
  advection schemes with flux limiters.%, and
%ph(
% This is Ian's work, and will be reported elsewhere, I insist;
% or Ian should be co-author
%\item growth and melt parameterizations have been refined and extended
%  in order to allow for automatic differentiation of the code.
%ph)
\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, freshwater 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}

%\ml{[Sergey says: a kind of repetition; need to revise previous section]}
Sea-ice motion is driven by ice-atmosphere, ice-ocean and internal
stresses; and by the horizontal surface elevation gradient
of the ocean. 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.
Alternatively, the elastic-viscous-plastic (EVP) technique following
\citet{hunke01} relaxed the ice state towards the VP rheology by
sub-cycling the evolution equations for the internal stress tensor
components and the sea ice momentum solver within one ocean model time
step.

\ml{In the LSOR solver the bulk viscosities are bounded from
  above. The EVP solver regularizes large viscosities by introducing
  damped elastic waves. Neither solver requires limiting the
  viscosities from below.}
% 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}. 
In an alternative to the elliptic yield curve, 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).
\ml{Free-slip boundary conditions are not implemented for the B~grid.}

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 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
their effects on the sea-ice solution.

The finite-volume discretization of the momentum equation on the
Arakawa C~grid is straightforward. The stress tensor divergence, 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, see
\refapp{discretization} for details. 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 through the ice
is parameterized assuming a linear temperature profile and a constant
ice conductivity implying zero heat capacity for ice. This type of
model is often referred to as a ``zero-layer'' model
\citep{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
seawater, 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 
%ph: it doesn't improve adjoint code *generation*, it improves the smoothness
improves the smoothness of the differentiated model
%(see companion, part 2, paper).
\citep[see][for details]{fent:09}.
%\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 $z=0$
at sea-level \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 schemes 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. 
%\ml{[Sergey says: any FV scheme will do this]}

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.
%
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; we intercompare
the impact of the different formulations (all of which are widely
used in sea ice modeling today) on Arctic sea ice simulation 
\citep{proshutinsky07:_aomip}.
%% Got to here..... more later
%% Add reference to JGR special issue here.....
%\citep{prosh07:_aomipspecial}.


%%% 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	dimitri	1.10	The MITgcm sea ice model is based on a variant of the
5	mlosch	1.2	viscous-plastic (VP) dynamic-thermodynamic sea-ice model of
6	cnh	1.16	\citet{zhang97} first introduced by \citet{hibler79, hibler80}.
7			Many aspects of the original codes have been
8	mlosch	1.22	adapted; these are the most important ones:
9	heimbach	1.1	\begin{itemize}
10	mlosch	1.15	\item the model has been rewritten for an Arakawa~C grid, both B- and
11	mlosch	1.22	C-grid variants are available; the finite-volume C-grid code allows
12			for no-slip and free-slip lateral boundary conditions,
13	heimbach	1.1	\item two different solution methods for solving the nonlinear
14	dimitri	1.11	momentum equations, LSOR \citep{zhang97} and EVP
15	mlosch	1.27	\citep{hunke01, hunke02}, have been adopted,
16	mlosch	1.26	\item ice-ocean stress can be formulated as in \citet{hibler87} as an
17			alternative to the standard method of applying ice-ocean stress
18			directly,
19	dimitri	1.11	\item ice concentration and thickness, snow, and ice salinity or enthalpy can
20			be advected by sophisticated, conservative
21	mlosch	1.26	advection schemes with flux limiters.%, and
22	heimbach	1.23	%ph(
23			% This is Ian's work, and will be reported elsewhere, I insist;
24			% or Ian should be co-author
25			%\item growth and melt parameterizations have been refined and extended
26			% in order to allow for automatic differentiation of the code.
27			%ph)
28	heimbach	1.1	\end{itemize}
29	jmc	1.9	The sea ice model is tightly coupled to the ocean component of the
30	cnh	1.16	MITgcm \citep{marshall97:_hydros_quasi_hydros_nonhy,marshall97:_finit_volum_incom_navier_stokes}.
31	mlosch	1.25	Heat, freshwater fluxes and surface stresses are computed from the
32	heimbach	1.1	atmospheric state and modified by the ice model at every time step.
33	mlosch	1.2	The remainder of this section describes the model equations and
34			details of their numerical realization. Further documentation and
35			model code can be found at \url{http://mitgcm.org}.
36
37			\subsection{Dynamics}
38			\label{sec:dynamics}
39
40	mlosch	1.22	%\ml{[Sergey says: a kind of repetition; need to revise previous section]}
41	mlosch	1.2	Sea-ice motion is driven by ice-atmosphere, ice-ocean and internal
42	mlosch	1.26	stresses; and by the horizontal surface elevation gradient
43			of the ocean. The internal stresses are evaluated following a
44	mlosch	1.2	viscous-plastic (VP) constitutive law with an elliptic yield curve as
45			in \citet{hibler79}. The full momentum equations for the sea-ice model
46			and the solution by line successive over-relaxation (LSOR) are
47	mlosch	1.22	described in \citet{zhang97}. %Alternatively, the momentum equation
48			% can be solved with an elastic-viscous-plastic (EVP) solver following
49			% \citet{hunke01}. In this technique, the evolution equations for the
50			% internal stress tensor components are solved by sub-cycling the sea ice
51			% momentum solver within one ocean model time step.
52			Alternatively, the elastic-viscous-plastic (EVP) technique following
53			\citet{hunke01} relaxed the ice state towards the VP rheology by
54			sub-cycling the evolution equations for the internal stress tensor
55			components and the sea ice momentum solver within one ocean model time
56			step.
57	mlosch	1.2
58	mlosch	1.27	\ml{In the LSOR solver the bulk viscosities are bounded from
59			above. The EVP solver regularizes large viscosities by introducing
60			damped elastic waves. Neither solver requires limiting the
61			viscosities from below.}
62			% In both cases, the bulk viscosities can be bounded from above (if
63			% required for numerical reasons).
64			For stress tensor computations the
65	mlosch	1.2	replacement pressure \citep{hibler95} is used so that the stress state
66	mlosch	1.22	always lies within the elliptic yield curve by definition.
67			%Alternatively, in the so-called truncated ellipse method (TEM) the
68			%shear viscosity is capped to suppress any tensile stress
69			%\citep{hibler97, geiger98}.
70			In an alternative to the elliptic yield curve, the so-called truncated
71			ellipse method (TEM), the shear viscosity is capped to suppress any
72			tensile stress \citep{hibler97, geiger98}.
73	mlosch	1.2
74			The horizontal gradient of the ocean's surface is estimated directly
75			from ocean sea surface height and pressure loading from atmosphere,
76	dimitri	1.11	ice and snow \citep{campin08}. Ice does not float on top of the
77			ocean, instead it depresses the ocean surface according to its thickness and
78			buoyancy.
79	mlosch	1.2
80	mlosch	1.15	Lateral boundary conditions are naturally ``no-slip'' for B~grids, as
81	mlosch	1.27	the tangential velocities points lie on the boundary. For C~grids,
82			the lateral boundary condition for tangential velocities allow
83			alternatively no-slip or free-slip conditions. In ocean models
84			free-slip boundary conditions in conjunction with piecewise-constant
85			(``castellated'') coastlines have been shown to reduce to no-slip
86			boundary conditions \citep{adcroft98:_slippery_coast}; for coupled
87			ocean sea-ice models the effects of lateral boundary conditions have
88			not yet been studied (as far as we know).
89			\ml{Free-slip boundary conditions are not implemented for the B~grid.}
90	mlosch	1.2
91			Moving sea ice exerts a surface stress on the ocean. In coupling the
92	jmc	1.9	sea-ice model to the ocean model, this stress is applied directly to
93	mlosch	1.2	the surface layer of the ocean model. An alternative ocean stress
94			formulation is given by \citet{hibler87}. Rather than applying the
95			interfacial stress directly, the stress is derived from integrating
96			over the ice thickness to the bottom of the oceanic surface layer. In
97	mlosch	1.15	the resulting equation for the combined ocean-ice momentum, the
98	mlosch	1.2	interfacial stress cancels and the total stress appears as the sum of
99	dimitri	1.6	wind stress and divergence of internal ice stresses \citep[see also
100	mlosch	1.2	Eq.\,2 of][]{hibler87}. While this formulation tightly embeds the
101	mlosch	1.15	sea ice into the surface layer of the ocean, its disadvantage is that
102	dimitri	1.11	the velocity in the surface layer of the ocean that is used to
103	mlosch	1.22	advect ocean tracers is an average over the ocean surface
104	dimitri	1.11	velocity and the ice velocity, leading to an inconsistency as the ice
105	mlosch	1.2	temperature and salinity are different from the oceanic variables.
106			Both stress coupling options are available for a direct comparison of
107	mlosch	1.18	their effects on the sea-ice solution.
108	mlosch	1.2
109	mlosch	1.21	The finite-volume discretization of the momentum equation on the
110			Arakawa C~grid is straightforward. The stress tensor divergence, in
111	mlosch	1.15	particular, is discretized naturally on the C~grid with the diagonal
112	mlosch	1.2	components of the stress tensor on the center points and the
113			off-diagonal term on the corner (or vorticity) points of the grid.
114			With this choice all derivatives are discretized as central
115	mlosch	1.21	differences and very little averaging is involved, see
116			\refapp{discretization} for details. Apart from the standard C-grid
117			implementation, the original B-grid implementation of \citet{zhang97}
118			is also available as an option in the code.
119	mlosch	1.2
120			\subsection{Thermodynamics}
121			\label{sec:thermodynamics}
122
123	mlosch	1.26	Upward conductive heat flux through the ice
124	mlosch	1.2	is parameterized assuming a linear temperature profile and a constant
125	mlosch	1.26	ice conductivity implying zero heat capacity for ice. This type of
126			model is often referred to as a ``zero-layer'' model
127			\citep{semtner76}. The surface heat flux is computed in a similar
128	mlosch	1.2	way to that of \citet{parkinson79} and \citet{manabe79}.
129
130			The conductive heat flux depends strongly on the ice thickness $h$.
131			However, the ice thickness in the model represents a mean over a
132			potentially very heterogeneous thickness distribution. In order to
133			parameterize a sub-grid scale distribution for heat flux computations,
134			the mean ice thickness $h$ is split into seven thickness categories
135			$H_{n}$ that are equally distributed between $2h$ and a minimum
136			imposed ice thickness of $5\text{\,cm}$ by $H_n= \frac{2n-1}{7}\,h$
137			for $n\in[1,7]$. The heat fluxes computed for each thickness category
138			is area-averaged to give the total heat flux \citep{hibler84}.
139
140	mlosch	1.12	The atmospheric heat flux is balanced by an oceanic heat flux.
141			The oceanic flux is proportional to the difference between
142	mlosch	1.25	ocean surface temperature and the freezing point temperature of
143			seawater, which is a function of salinity.
144	cnh	1.16	This flux is not assumed to instantaneously melt
145	mlosch	1.3	or create ice, but a time scale of three days is used to relax the
146	mlosch	1.8	ocean temperature to the freezing point. While this
147	dimitri	1.11	parameterization is not new \citep[it follows the ideas of,
148	mlosch	1.3	e.g.,][]{mellor86, mcphee92, lohmann98, notz03}, it avoids a
149			discontinuity in the functional relationship between model variables,
150	heimbach	1.23	which
151			%is crucial for making the code differentiable for adjoint code generation
152			%ph: it doesn't improve adjoint code generation, it improves the smoothness
153	mlosch	1.24	improves the smoothness of the differentiated model
154	heimbach	1.23	%(see companion, part 2, paper).
155	mlosch	1.25	\citep[see][for details]{fent:09}.
156	dimitri	1.13	%\ml{[ONCE IT IS SUBMITTED, otherwise pers. communcations:]}\citep{fen09}
157	mlosch	1.2	The parameterization of lateral and vertical growth of sea ice follows
158			that of \citet{hibler79, hibler80}.
159
160			On top of the ice there is a layer of snow that modifies the heat flux
161			and the albedo as in \citet{zhang98}. If enough snow accumulates so
162			that its weight submerges the ice and the snow is flooded, a simple
163	dimitri	1.11	mass conserving parameterization of snow ice formation (a flood-freeze
164	mlosch	1.2	algorithm following Archimedes' principle) turns snow into ice until
165	jmc	1.19	the ice surface is back %at $z=0$
166	mlosch	1.20	at sea-level \citep{leppaeranta83}.
167	mlosch	1.2
168			The concentration $c$, effective ice thickness (ice volume per unit
169	dimitri	1.11	area, $c\cdot{h}$), effective snow thickness ($c\cdot{h}_{s}$), and effective
170			ice salinity (in g\,m$^{-2}$) are advected by ice velocities.
171	mlosch	1.2	%
172	mlosch	1.25	From the various advection schemes that are available in the MITgcm
173	dimitri	1.11	\citep{mitgcm02}, we choose flux-limited schemes, i.e., multidimensional 2nd
174			and 3rd-order advection schemes with flux limiters
175			\citep{roe85, hundsdorfer94}, to preserve sharp gradients and
176	mlosch	1.2	edges that are typical of sea ice distributions and to rule out
177			unphysical over- and undershoots (negative thickness or
178	mlosch	1.18	concentration). These schemes, conserve volume and horizontal area and
179			are unconditionally stable, so that no extra diffusion is required.
180			%\ml{[Sergey says: any FV scheme will do this]}
181	mlosch	1.2
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	mlosch	1.24	%
194	dimitri	1.11	The internal sea ice temperature is inferred from ice enthalpy.
195	cnh	1.16	To avoid unphysical (negative) values for ice thickness and
196	mlosch	1.12	concentration, a positive 2nd-order advection scheme with a SuperBee
197			flux limiter \citep{roe85}
198			is used in this study to advect all sea-ice-related
199	dimitri	1.11	quantities of the \citet{winton00} thermodynamic model.
200	jmc	1.9	Because of the non-linearity of the advection scheme,
201			care must be taken in advecting these quantities: when simply using
202			ice velocity to advect enthalpy, the total energy (i.e., the volume
203			integral of enthalpy) is not conserved. Alternatively, one can advect
204			the energy content (i.e., product of ice-volume and enthalpy)
205			but then false enthalpy extrema can occur,
206			which then leads to unrealistic ice temperature.
207	mlosch	1.15	In the currently implemented solution, the sea-ice mass flux is used
208	cnh	1.17	to advect the enthalpy in order to ensure conservation of enthalpy
209	mlosch	1.15	and to prevent false enthalpy extrema.
210	heimbach	1.1
211	cnh	1.16	In \refsec{globalmodel} and \ref{sec:arcticmodel}
212			we exercise and compare several
213	mlosch	1.22	of the options, which have been discussed above; we intercompare
214	cnh	1.16	the impact of the different formulations (all of which are widely
215	cnh	1.17	used in sea ice modeling today) on Arctic sea ice simulation
216	mlosch	1.18	\citep{proshutinsky07:_aomip}.
217	cnh	1.16	%% Got to here..... more later
218			%% Add reference to JGR special issue here.....
219	mlosch	1.18	%\citep{prosh07:_aomipspecial}.
220
221
222	dimitri	1.11
223	heimbach	1.1	%%% Local Variables:
224			%%% mode: latex
225	mlosch	1.2	%%% TeX-master: "ceaice_part1"
226	heimbach	1.1	%%% End: