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1 \section{Model Formulation}
2 \label{sec:model}
3
4 The MITgcm sea ice model (MITsim) is based on a variant of the
5 viscous-plastic (VP) dynamic-thermodynamic sea ice model
6 \citep{zhang97} first introduced by \citet{hibler79, hibler80}. In
7 order to adapt this model to the requirements of coupled
8 ice-ocean simulations, many important aspects of the original code have
9 been modified and improved:
10 \begin{itemize}
11 \item the code has been rewritten for an Arakawa C-grid, both B- and
12 C-grid variants are available; the C-grid code allows for no-slip
13 and free-slip lateral boundary conditions;
14 \item two different solution methods for solving the nonlinear
15 momentum equations have been adopted: LSOR \citep{zhang97}, EVP
16 \citep{hunke97};
17 \item ice-ocean stress can be formulated as in \citet{hibler87};
18 \item ice variables are advected by sophisticated advection schemes;
19 \item growth and melt parameterization have been refined and extended
20 in order to allow for automatic differentiation of the code.
21 \end{itemize}
22 The model equations and their numerical realization are summarized
23 below.
24
25 \subsection{Dynamics}
26 \label{sec:dynamics}
27
28 The momentum equation of the sea-ice model is
29 \begin{equation}
30 \label{eq:momseaice}
31 m \frac{D\vek{u}}{Dt} = -mf\vek{k}\times\vek{u} + \vtau_{air} +
32 \vtau_{ocean} - m \nabla{\phi(0)} + \vek{F},
33 \end{equation}
34 where $m=m_{i}+m_{s}$ is the ice and snow mass per unit area;
35 $\vek{u}=u\vek{i}+v\vek{j}$ is the ice velocity vector;
36 $\vek{i}$, $\vek{j}$, and $\vek{k}$ are unit vectors in the $x$, $y$, and $z$
37 directions, respectively;
38 $f$ is the Coriolis parameter;
39 $\vtau_{air}$ and $\vtau_{ocean}$ are the wind-ice and ocean-ice stresses,
40 respectively;
41 $g$ is the gravity accelation;
42 $\nabla\phi(0)$ is the gradient (or tilt) of the sea surface height;
43 $\phi(0) = g\eta + p_{a}/\rho_{0}$ is the sea surface height potential
44 in response to ocean dynamics ($g\eta$) and to atmospheric pressure
45 loading ($p_{a}/\rho_{0}$, where $\rho_{0}$ is a reference density);
46 and $\vek{F}=\nabla\cdot\sigma$ is the divergence of the internal ice stress
47 tensor $\sigma_{ij}$.
48 When using the rescaled vertical coordinate system, z$^\ast$, of
49 \citet{cam08}, $\phi(0)$ also includes a term due to snow and ice
50 loading, $mg/\rho_{0}$.
51 Advection of sea-ice momentum is neglected. The wind and ice-ocean stress
52 terms are given by
53 \begin{align*}
54 \vtau_{air} = & \rho_{air} C_{air} |\vek{U}_{air} -\vek{u}|
55 R_{air} (\vek{U}_{air} -\vek{u}), \\
56 \vtau_{ocean} = & \rho_{ocean}C_{ocean} |\vek{U}_{ocean}-\vek{u}|
57 R_{ocean}(\vek{U}_{ocean}-\vek{u}), \\
58 \end{align*}
59 where $\vek{U}_{air/ocean}$ are the surface winds of the atmosphere
60 and surface currents of the ocean, respectively; $C_{air/ocean}$ are
61 air and ocean drag coefficients; $\rho_{air/ocean}$ are reference
62 densities; and $R_{air/ocean}$ are rotation matrices that act on the
63 wind/current vectors.
64
65 For an isotropic system the stress tensor $\sigma_{ij}$ ($i,j=1,2$) can
66 be related to the ice strain rate and strength by a nonlinear
67 viscous-plastic (VP) constitutive law \citep{hibler79, zhang97}:
68 \begin{equation}
69 \label{eq:vpequation}
70 \sigma_{ij}=2\eta(\dot{\epsilon}_{ij},P)\dot{\epsilon}_{ij}
71 + \left[\zeta(\dot{\epsilon}_{ij},P) -
72 \eta(\dot{\epsilon}_{ij},P)\right]\dot{\epsilon}_{kk}\delta_{ij}
73 - \frac{P}{2}\delta_{ij}.
74 \end{equation}
75 The ice strain rate is given by
76 \begin{equation*}
77 \dot{\epsilon}_{ij} = \frac{1}{2}\left(
78 \frac{\partial{u_{i}}}{\partial{x_{j}}} +
79 \frac{\partial{u_{j}}}{\partial{x_{i}}}\right).
80 \end{equation*}
81 The maximum ice pressure $P_{\max}$, a measure of ice strength, depends on
82 both thickness $h$ and compactness (concentration) $c$:
83 \begin{equation}
84 P_{\max} = P^{*}c\,h\,e^{[C^{*}\cdot(1-c)]},
85 \label{eq:icestrength}
86 \end{equation}
87 with the constants $P^{*}$ and $C^{*}$. The nonlinear bulk and shear
88 viscosities $\eta$ and $\zeta$ are functions of ice strain rate
89 invariants and ice strength such that the principal components of the
90 stress lie on an elliptical yield curve with the ratio of major to
91 minor axis $e$ equal to $2$; they are given by:
92 \begin{align*}
93 \zeta =& \min\left(\frac{P_{\max}}{2\max(\Delta,\Delta_{\min})},
94 \zeta_{\max}\right) \\
95 \eta =& \frac{\zeta}{e^2} \\
96 \intertext{with the abbreviation}
97 \Delta = & \left[
98 \left(\dot{\epsilon}_{11}^2+\dot{\epsilon}_{22}^2\right)
99 (1+e^{-2}) + 4e^{-2}\dot{\epsilon}_{12}^2 +
100 2\dot{\epsilon}_{11}\dot{\epsilon}_{22} (1-e^{-2})
101 \right]^{\frac{1}{2}}
102 \end{align*}
103 The bulk viscosities are bounded above by imposing both a minimum
104 $\Delta_{\min}=10^{-11}\text{\,s}^{-1}$ (for numerical reasons) and a
105 maximum $\zeta_{\max} = P_{\max}/\Delta^*$, where
106 $\Delta^*=(5\times10^{12}/2\times10^4)\text{\,s}^{-1}$. For stress
107 tensor computation the replacement pressure $P = 2\,\Delta\zeta$
108 \citep{hibler95} is used so that the stress state always lies on the
109 elliptic yield curve by definition.
110
111 In the so-called truncated ellipse method the shear viscosity $\eta$
112 is capped to suppress any tensile stress \citep{hibler97, geiger98}:
113 \begin{equation}
114 \label{eq:etatem}
115 \eta = \min\left(\frac{\zeta}{e^2},
116 \frac{\frac{P}{2}-\zeta(\dot{\epsilon}_{11}+\dot{\epsilon}_{22})}
117 {\sqrt{(\dot{\epsilon}_{11}+\dot{\epsilon}_{22})^2
118 +4\dot{\epsilon}_{12}^2}}\right).
119 \end{equation}
120
121 In the current implementation, the VP-model is integrated with the
122 semi-implicit line successive over relaxation (LSOR)-solver of
123 \citet{zhang98}, which allows for long time steps that, in our case,
124 are limited by the explicit treatment of the Coriolis term. The
125 explicit treatment of the Coriolis term does not represent a severe
126 limitation because it restricts the time step to approximately the
127 same length as in the ocean model where the Coriolis term is also
128 treated explicitly.
129
130 \citet{hunke97}'s introduced an elastic contribution to the strain
131 rate in order to regularize Eq.\refeq{vpequation} in such a way that
132 the resulting elastic-viscous-plastic (EVP) and VP models are
133 identical at steady state,
134 \begin{equation}
135 \label{eq:evpequation}
136 \frac{1}{E}\frac{\partial\sigma_{ij}}{\partial{t}} +
137 \frac{1}{2\eta}\sigma_{ij}
138 + \frac{\eta - \zeta}{4\zeta\eta}\sigma_{kk}\delta_{ij}
139 + \frac{P}{4\zeta}\delta_{ij}
140 = \dot{\epsilon}_{ij}.
141 \end{equation}
142 %In the EVP model, equations for the components of the stress tensor
143 %$\sigma_{ij}$ are solved explicitly. Both model formulations will be
144 %used and compared the present sea-ice model study.
145 The EVP-model uses an explicit time stepping scheme with a short
146 timestep. According to the recommendation of \citet{hunke97}, the
147 EVP-model is stepped forward in time 120 times within the physical
148 ocean model time step (although this parameter is under debate), to
149 allow for elastic waves to disappear. Because the scheme does not
150 require a matrix inversion it is fast in spite of the small internal
151 timestep and simple to implement on parallel computers
152 \citep{hunke97}. For completeness, we repeat the equations for the
153 components of the stress tensor $\sigma_{1} =
154 \sigma_{11}+\sigma_{22}$, $\sigma_{2}= \sigma_{11}-\sigma_{22}$, and
155 $\sigma_{12}$. Introducing the divergence $D_D =
156 \dot{\epsilon}_{11}+\dot{\epsilon}_{22}$, and the horizontal tension
157 and shearing strain rates, $D_T =
158 \dot{\epsilon}_{11}-\dot{\epsilon}_{22}$ and $D_S =
159 2\dot{\epsilon}_{12}$, respectively, and using the above
160 abbreviations, the equations\refeq{evpequation} can be written as:
161 \begin{align}
162 \label{eq:evpstresstensor1}
163 \frac{\partial\sigma_{1}}{\partial{t}} + \frac{\sigma_{1}}{2T} +
164 \frac{P}{2T} &= \frac{P}{2T\Delta} D_D \\
165 \label{eq:evpstresstensor2}
166 \frac{\partial\sigma_{2}}{\partial{t}} + \frac{\sigma_{2} e^{2}}{2T}
167 &= \frac{P}{2T\Delta} D_T \\
168 \label{eq:evpstresstensor12}
169 \frac{\partial\sigma_{12}}{\partial{t}} + \frac{\sigma_{12} e^{2}}{2T}
170 &= \frac{P}{4T\Delta} D_S
171 \end{align}
172 Here, the elastic parameter $E$ is redefined in terms of a damping timescale
173 $T$ for elastic waves \[E=\frac{\zeta}{T}.\]
174 $T=E_{0}\Delta{t}$ with the tunable parameter $E_0<1$ and
175 the external (long) timestep $\Delta{t}$. \citet{hunke97} recommend
176 $E_{0} = \frac{1}{3}$.
177
178 For details of the spatial discretization, the reader is referred to
179 \citet{zhang98, zhang03}. Our discretization differs only (but
180 importantly) in the underlying grid, namely the Arakawa C-grid, but is
181 otherwise straightforward. The EVP model, in particular, is discretized
182 naturally on the C-grid with $\sigma_{1}$ and $\sigma_{2}$ on the
183 center points and $\sigma_{12}$ on the corner (or vorticity) points of
184 the grid. With this choice all derivatives are discretized as central
185 differences and averaging is only involved in computing $\Delta$ and
186 $P$ at vorticity points.
187
188 For a general curvilinear grid, one needs in principle to take metric
189 terms into account that arise in the transformation of a curvilinear
190 grid on the sphere. For now, however, we can neglect these metric
191 terms because they are very small on the \ml{[modify following
192 section3:] cubed sphere grids used in this paper; in particular,
193 only near the edges of the cubed sphere grid, we expect them to be
194 non-zero, but these edges are at approximately 35\degS\ or 35\degN\
195 which are never covered by sea-ice in our simulations. Everywhere
196 else the coordinate system is locally nearly cartesian.} However, for
197 last-glacial-maximum or snowball-earth-like simulations the question
198 of metric terms needs to be reconsidered. Either, one includes these
199 terms as in \citet{zhang03}, or one finds a vector-invariant
200 formulation for the sea-ice internal stress term that does not require
201 any metric terms, as it is done in the ocean dynamics of the MITgcm
202 \citep{adcroft04:_cubed_sphere}.
203
204 Lateral boundary conditions are naturally ``no-slip'' for B-grids, as
205 the tangential velocities points lie on the boundary. For C-grids, the
206 lateral boundary condition for tangential velocities is realized via
207 ``ghost points'', allowing alternatively no-slip or free-slip
208 conditions. In ocean models free-slip boundary conditions in
209 conjunction with piecewise-constant (``castellated'') coastlines have
210 been shown to reduce in effect to no-slip boundary conditions
211 \citep{adcroft98:_slippery_coast}; for sea-ice models the effects of
212 lateral boundary conditions have not yet been studied.
213
214 Moving sea ice exerts a stress on the ocean which is the opposite of
215 the stress $\vtau_{ocean}$ in Eq.\refeq{momseaice}. This stess is
216 applied directly to the surface layer of the ocean model. An
217 alternative ocean stress formulation is given by \citet{hibler87}.
218 Rather than applying $\vtau_{ocean}$ directly, the stress is derived
219 from integrating over the ice thickness to the bottom of the oceanic
220 surface layer. In the resulting equation for the \emph{combined}
221 ocean-ice momentum, the interfacial stress cancels and the total
222 stress appears as the sum of windstress and divergence of internal ice
223 stresses: $\delta(z) (\vtau_{air} + \vek{F})/\rho_0$, \citep[see also
224 Eq.\,2 of][]{hibler87}. The disadvantage of this formulation is that
225 now the velocity in the surface layer of the ocean that is used to
226 advect tracers, is really an average over the ocean surface
227 velocity and the ice velocity leading to an inconsistency as the ice
228 temperature and salinity are different from the oceanic variables.
229
230 %\subparagraph{boundary conditions: no-slip, free-slip, half-slip}
231 %\begin{itemize}
232 %\item transition from existing B-Grid to C-Grid
233 %\item boundary conditions: no-slip, free-slip, half-slip
234 %\item fancy (multi dimensional) advection schemes
235 %\item VP vs.\ EVP \citep{hunke97}
236 %\item ocean stress formulation \citep{hibler87}
237 %\end{itemize}
238
239 \subsection{Thermodynamics}
240 \label{sec:thermodynamics}
241
242 In the original formulation the sea ice model \citep{menemenlis05}
243 uses simple thermodynamics following the appendix of
244 \citet{semtner76}. This formulation does not allow storage of heat
245 (heat capacity of ice is zero, and this type of model is often refered
246 to as a ``zero-layer'' model). Upward conductive heat flux is parameterized
247 assuming a linear temperature profile and together with a constant ice
248 conductivity. It is expressed as $(K/h)(T_{w}-T_{0})$, where $K$ is
249 the ice conductivity, $h$ the ice thickness, and $T_{w}-T_{0}$ the
250 difference between water and ice surface temperatures. The surface
251 heat flux is computed in a similar way to that of \citet{parkinson79}
252 and \citet{manabe79}.
253
254 The conductive heat flux depends strongly on the ice thickness $h$.
255 However, the ice thickness in the model represents a mean over a
256 potentially very heterogeneous thickness distribution. In order to
257 parameterize this sub-grid scale distribution for heat flux
258 computations, the mean ice thickness $h$ is split into seven thickness
259 categories $H_{n}$ that are equally distributed between $2h$ and
260 a minimum imposed ice thickness of $5\text{\,cm}$ by $H_n=
261 \frac{2n-1}{7}\,h$ for $n\in[1,7]$. The heat fluxes computed for each
262 thickness category area averaged to give the total heat flux. \ml{[I
263 don't have citation for that, anyone?]}
264
265 The atmospheric heat flux is balanced by an oceanic heat flux from
266 below. The oceanic flux is proportional to
267 $\rho\,c_{p}\left(T_{w}-T_{fr}\right)$ where $\rho$ and $c_{p}$ are
268 the density and heat capacity of sea water and $T_{fr}$ is the local
269 freezing point temperature that is a function of salinity. Contrary to
270 \citet{menemenlis05}, this flux is not assumed to instantaneously melt
271 or create ice, but a time scale of three days is used to relax $T_{w}$
272 to the freezing point.
273
274 The parameterization of lateral and vertical growth of sea ice follows
275 that of \citet{hibler79, hibler80}.
276
277 On top of the ice there is a layer of snow that modifies the heat flux
278 and the albedo \citep{zhang98}. If enough snow accumulates so that its
279 weight submerges the ice and the snow is flooded, a simple mass
280 conserving parameterization of snowice formation (a flood-freeze
281 algorithm following Archimedes' principle) turns snow into ice until
282 the ice surface is back at $z=0$ \citep{leppaeranta83}.
283
284 Effective ice thickness (ice volume per unit area,
285 $c\cdot{h}$), concentration $c$ and effective snow thickness
286 ($c\cdot{h}_{s}$) are advected by ice velocities:
287 \begin{equation}
288 \label{eq:advection}
289 \frac{\partial{X}}{\partial{t}} = - \nabla\cdot\left(\vek{u}\,X\right) +
290 \Gamma_{X} + D_{X}
291 \end{equation}
292 where $\Gamma_X$ are the thermodynamic source terms and $D_{X}$ the
293 diffusive terms for quantities $X=(c\cdot{h}), c, (c\cdot{h}_{s})$.
294 %
295 From the various advection scheme that are available in the MITgcm
296 \citep{mitgcm02}, we choose flux-limited schemes
297 \citep[multidimensional 2nd and 3rd-order advection scheme with flux
298 limiter][]{roe85, hundsdorfer94} to preserve sharp gradients and edges
299 that are typical of sea ice distributions and to rule out unphysical
300 over- and undershoots (negative thickness or concentration). These
301 scheme conserve volume and horizontal area and are unconditionally
302 stable, so that we can set $D_{X}=0$. \ml{[do we need to proove that?
303 can we proove that? citation?]}
304
305 There is considerable doubt about the reliability of such a simple
306 thermodynamic model---\citet{semtner84} found significant errors in
307 phase (one month lead) and amplitude ($\approx$50\%\,overestimate) in
308 such models---, so that today many sea ice models employ more complex
309 thermodynamics. A popular thermodynamics model of \citet{winton00} is
310 based on the 3-layer model of \citet{semtner76} and treats brine
311 content by means of enthalphy conservation. This model requires in
312 addition to ice-thickness and compactness (fractional area) additional
313 state variables to be advected by ice velocities, namely enthalphy of
314 the two ice layers and the thickness of the overlying snow layer.
315 \ml{[Jean-Michel, your turf: ]Care must be taken in advecting these
316 quantities in order to ensure conservation of enthalphy. Currently
317 this can only be accomplished with a 2nd-order advection scheme with
318 flux limiter \citep{roe85}.}
319
320
321 %\subsection{C-grid}
322 %\begin{itemize}
323 %\item no-slip vs. free-slip for both lsr and evp;
324 % "diagnostics" to look at and use for comparison
325 % \begin{itemize}
326 % \item ice transport through Fram Strait/Denmark Strait/Davis
327 % Strait/Bering strait (these are general)
328 % \item ice transport through narrow passages, e.g.\ Nares-Strait
329 % \end{itemize}
330 %\item compare different advection schemes (if lsr turns out to be more
331 % effective, then with lsr otherwise I prefer evp), eg.
332 % \begin{itemize}
333 % \item default 2nd-order with diff1=0.002
334 % \item 1st-order upwind with diff1=0.
335 % \item DST3FL (SEAICEadvScheme=33 with diff1=0., should work, works for me)
336 % \item 2nd-order wit flux limiter (SEAICEadvScheme=77 with diff1=0.)
337 % \end{itemize}
338 % That should be enough. Here, total ice mass and location of ice edge
339 % is interesting. However, this comparison can be done in an idealized
340 % domain, may not require full Arctic Domain?
341 %\item
342 %Do a little study on the parameters of LSR and EVP
343 %\begin{enumerate}
344 %\item convergence of LSR, how many iterations do you need to get a
345 % true elliptic yield curve
346 %\item vary deltaTevp and the relaxation parameter for EVP and see when
347 % the EVP solution breaks down (relative to the forcing time scale).
348 % For this, it is essential that the evp solver gives use "stripeless"
349 % solutions, that is your dtevp = 1sec solutions/or 10sec solutions
350 % with SEAICE\_evpDampC = 615.
351 %\end{enumerate}
352
353 %\end{itemize}
354
355 %%% Local Variables:
356 %%% mode: latex
357 %%% TeX-master: "ceaice"
358 %%% End:

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