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-revision 1.1 by dimitri,
Wed Nov  7 14:35:09 2007 UTC
+revision 1.14 by dimitri,
Tue Feb 26 00:13:20 2008 UTC
 Line 1
+ % $Header$
+ % $Name$
  \documentclass[12pt]{article}
- \usepackage{epsfig}
- \usepackage{graphics}
+ \usepackage[]{graphicx}
  \usepackage{subfigure}
  \usepackage[round,comma]{natbib}
- \bibliographystyle{agu04}
+ \bibliographystyle{bib/agu04}
  \usepackage{amsmath,amssymb}
  \newcommand\bmmax{10} \newcommand\hmmax{10}
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  %\newlength{\widefigwidth}\setlength{\widefigwidth}{39pc}
  \newlength{\widefigwidth}\setlength{\widefigwidth}{\textwidth}
- \newcommand{\fpath}{.}
+ \newcommand{\fpath}{figs}
+ % commenting scheme
+ \newcommand{\ml}[1]{\textsf{\slshape #1}}
  \title{A Dynamic-Thermodynamic Sea ice Model for Ocean Climate
    Estimation on an Arakawa C-Grid}
-Line 47
+Line 52
  \maketitle
  \begin{abstract}
-   Some blabla
+ As part of ongoing efforts to obtain a best possible synthesis of most
+ available, global-scale, ocean and sea ice data, a dynamic and thermodynamic
+ sea-ice model has been coupled to the Massachusetts Institute of Technology
+ general circulation model (MITgcm).  Ice mechanics follow a viscous plastic
+ rheology and the ice momentum equations are solved numerically using either
+ line successive relaxation (LSR) 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.  This paper describes the MITgcm sea ice
+ model; it presents example Arctic and Antarctic results from a realistic,
+ eddy-permitting, global ocean and sea-ice configuration; it compares B-grid
+ and C-grid dynamic solvers in a regional Arctic configuration; and it presents
+ example results from coupled ocean and sea-ice adjoint-model integrations.
  \end{abstract}
  \section{Introduction}
  \label{sec:intro}
- more blabla
+ The availability of an adjoint model as a powerful research
+ tool complementary to an ocean model was a major design
- \section{Model}
+ requirement early on in the development of the MIT general
- \label{sec:model}
+ circulation model (MITgcm) [Marshall et al. 1997a,
+ Marotzke et al. 1999, Adcroft et al. 2002]. It was recognized
+ that the adjoint permitted very efficient computation
+ of gradients of various scalar-valued model diagnostics,
+ norms or, generally, objective functions with respect
+ to external or independent parameters. Such gradients
+ arise in at least two major contexts. If the objective function
+ is the sum of squared model vs. obervation differences
+ weighted by e.g. the inverse error covariances, the gradient
+ of the objective function can be used to optimize this measure
+ of model vs. data misfit in a least-squares sense. One
+ is then solving a problem of statistical state estimation.
+ If the objective function is a key oceanographic quantity
+ such as meridional heat or volume transport, ocean heat
+ content or mean surface temperature index, the gradient
+ provides a complete set of sensitivities of this quantity
+ with respect to all independent variables simultaneously.
+ References to existing sea-ice adjoint models, explaining that they are either
+ for simplified configurations, for ice-only studies, or for short-duration
+ studies to motivate the present work.
  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}. From the perspective of coupling a
+ kreyscher00, zhang98, hunke97}. 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
-Line 69 
 velocities points and thus needs to be i
+Line 111 
 velocities points and thus needs to be i
  sea-ice model and a C-grid ocean model. While the smoothing implicitly
  associated with this interpolation may mask grid scale noise, it may
  in two-way coupling lead to a computational mode as will be shown. By
- choosing a C-grid for the sea-ice model, we circumvene this difficulty
+ 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.
-Line 77 
 A further advantage of the C-grid formul
+Line 119 
 A further advantage of the C-grid formul
  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 counditions),
  whereas the C-grid formulation allows a flux of sea-ice through this
- passage for all types of lateral boundary conditions. We (will)
+ passage for all types of lateral boundary conditions. We
  demonstrate this effect in the Candian archipelago.
+ Talk about problems that make the sea-ice-ocean code very sensitive and
+ changes in the code that reduce these sensitivities.
+ This paper describes the MITgcm sea ice
+ model; it presents example Arctic and Antarctic results from a realistic,
+ eddy-permitting, global ocean and sea-ice configuration; it compares B-grid
+ and C-grid dynamic solvers in a regional Arctic configuration; and it presents
+ example results from coupled ocean and sea-ice adjoint-model integrations.
+ \section{Model}
+ \label{sec:model}
  \subsection{Dynamics}
  \label{sec:dynamics}
- The momentum equations of the sea-ice model are standard with
+ The momentum equation of the sea-ice model is
  \begin{equation}
    \label{eq:momseaice}
    m \frac{D\vek{u}}{Dt} = -mf\vek{k}\times\vek{u} + \vtau_{air} +
-   \vtau_{ocean} - m \nabla{\phi(0)} + \vek{F},
+   \vtau_{ocean} - mg \nabla{\phi(0)} + \vek{F},
  \end{equation}
- where $\vek{u} = u\vek{i}+v\vek{j}$ is the ice velocity vectory, $m$
+ where $m=m_{i}+m_{s}$ is the ice and snow mass per unit area;
- the ice mass per unit area, $f$ the Coriolis parameter, $g$ is the
+ $\vek{u}=u\vek{i}+v\vek{j}$ is the ice velocity vector;
- gravity accelation, $\nabla\phi$ is the gradient (tilt) of the sea
+ $\vek{i}$, $\vek{j}$, and $\vek{k}$ are unit vectors in the $x$, $y$, and $z$
- surface height potential beneath the ice. $\phi$ is the sum of
+ directions, respectively;
- atmpheric pressure $p_{a}$ and loading due to ice and snow
+ $f$ is the Coriolis parameter;
- $(m_{i}+m_{s})g$. $\vtau_{air}$ and $\vtau_{ocean}$ are the wind and
+ $\vtau_{air}$ and $\vtau_{ocean}$ are the wind-ice and ocean-ice stresses,
- ice-ocean stresses, respectively.  $\vek{F}$ is the interaction force
+ respectively;
- and $\vek{i}$, $\vek{j}$, and $\vek{k}$ are the unit vectors in the
+ $g$ is the gravity accelation;
- $x$, $y$, and $z$ directions.  Advection of sea-ice momentum is
+ $\nabla\phi(0)$ is the gradient (or tilt) of the sea surface height;
- neglected. The wind and ice-ocean stress terms are given by
+ $\phi(0)$ is the sea surface height potential in response to ocean dynamics
+ and to atmospheric pressure loading;
+ and $\vek{F}=\nabla\cdot\sigma$ is the divergence of the internal ice stress
+ tensor $\sigma_{ij}$.
+ When using the rescaled vertical coordinate system, z$^\ast$, of
+ \citet{cam08}, $\phi(0)$ also includes a term due to snow and ice loading, $mg$.
+ Advection of sea-ice momentum is neglected. The wind and ice-ocean stress
+ terms are given by
  \begin{align*}
-   \vtau_{air} =& \rho_{air} |\vek{U}_{air}|R_{air}(\vek{U}_{air}) \\
+   \vtau_{air}   = & \rho_{air}  C_{air}   |\vek{U}_{air}  -\vek{u}|
-   \vtau_{ocean} =& \rho_{ocean} |\vek{U}_{ocean}-\vek{u}|
+                    R_{air}  (\vek{U}_{air}  -\vek{u}), \\
+   \vtau_{ocean} = & \rho_{ocean}C_{ocean} |\vek{U}_{ocean}-\vek{u}|
                     R_{ocean}(\vek{U}_{ocean}-\vek{u}), \\
  \end{align*}
  where $\vek{U}_{air/ocean}$ are the surface winds of the atmosphere
- and surface currents of the ocean, respectively. $C_{air/ocean}$ are
+ and surface currents of the ocean, respectively; $C_{air/ocean}$ are
- air and ocean drag coefficients, $\rho_{air/ocean}$ reference
+ air and ocean drag coefficients; $\rho_{air/ocean}$ are reference
- densities, and $R_{air/ocean}$ rotation matrices that act on the
+ densities; and $R_{air/ocean}$ are rotation matrices that act on the
- wind/current vectors. $\vek{F} = \nabla\cdot\sigma$ is the divergence
+ wind/current vectors.
- of the interal stress tensor $\sigma_{ij}$.
  For an isotropic system this stress tensor can be related to the ice
  strain rate and strength by a nonlinear viscous-plastic (VP)
-Line 127 
 The ice strain rate is given by
+Line 188 
 The ice strain rate is given by
      \frac{\partial{u_{i}}}{\partial{x_{j}}} +
      \frac{\partial{u_{j}}}{\partial{x_{i}}}\right).
  \end{equation*}
- The pressure $P$, a measure of ice strength, depends on both thickness
+ The maximum ice pressure $P_{\max}$, a measure of ice strength, depends on
- $h$ and compactness (concentration) $c$: \[P =
+ both thickness $h$ and compactness (concentration) $c$:
- P^{*}c\,h\,e^{[C^{*}\cdot(1-c)]},\] with the constants $P^{*}$ and
+ \begin{equation}
- $C^{*}$. The nonlinear bulk and shear viscosities $\eta$ and $\zeta$
+   P_{\max} = P^{*}c\,h\,e^{[C^{*}\cdot(1-c)]},
- are functions of ice strain rate invariants and ice strength such that
+ \label{eq:icestrength}
- the principal components of the stress lie on an elliptical yield
+ \end{equation}
- curve with the ratio of major to minor axis $e$ equal to $2$; they are
+ with the constants $P^{*}$ and $C^{*}$. The nonlinear bulk and shear
- given by:
+ viscosities $\eta$ and $\zeta$ are functions of ice strain rate
+ invariants and ice strength such that the principal components of the
+ stress lie on an elliptical yield curve with the ratio of major to
+ minor axis $e$ equal to $2$; they are given by:
  \begin{align*}
-   \zeta =& \frac{P}{2\Delta} \\
+   \zeta =& \min\left(\frac{P_{\max}}{2\max(\Delta,\Delta_{\min})},
-   \eta =& \frac{P}{2\Delta{e}^2} \\
+    \zeta_{\max}\right) \\
+   \eta =& \frac{\zeta}{e^2} \\
    \intertext{with the abbreviation}
    \Delta = & \left[
      \left(\dot{\epsilon}_{11}^2+\dot{\epsilon}_{22}^2\right)
-Line 145 
 given by:
+Line 210 
 given by:
 \dot{\epsilon}_{11}\dot{\epsilon}_{22} (1-e^{-2})
    \right]^{-\frac{1}{2}}
  \end{align*}
+ The bulk viscosities are bounded above by imposing both a minimum
+ $\Delta_{\min}=10^{-11}\text{\,s}^{-1}$ (for numerical reasons) and a
+ maximum $\zeta_{\max} = P_{\max}/\Delta^*$, where
+ $\Delta^*=(5\times10^{12}/2\times10^4)\text{\,s}^{-1}$. For stress
+ tensor computation the replacement pressure $P = 2\,\Delta\zeta$
+ \citep{hibler95} is used so that the stress state always lies on the
+ elliptic yield curve by definition.
+ In the so-called truncated ellipse method the shear viscosity $\eta$
+ is capped to suppress any tensile stress \citep{hibler97, geiger98}:
+ \begin{equation}
+   \label{eq:etatem}
+   \eta = \min(\frac{\zeta}{e^2}
+   \frac{\frac{P}{2}-\zeta(\dot{\epsilon}_{11}+\dot{\epsilon}_{22})}
+   {\sqrt{(\dot{\epsilon}_{11}+\dot{\epsilon}_{22})^2
+       +4\dot{\epsilon}_{12}^2}}
+ \end{equation}
  In the current implementation, the VP-model is integrated with the
  semi-implicit line successive over relaxation (LSOR)-solver of
  \citet{zhang98}, which allows for long time steps that, in our case,
-Line 155 
 same length as in the ocean model where
+Line 238 
 same length as in the ocean model where
  treated explicitly.
  \citet{hunke97}'s introduced an elastic contribution to the strain
- rate elatic-viscous-plastic in order to regularize
+ rate elastic-viscous-plastic in order to regularize
  Eq.\refeq{vpequation} in such a way that the resulting
- elatic-viscous-plastic (EVP) and VP models are identical at steady
+ elastic-viscous-plastic (EVP) and VP models are identical at steady
  state,
  \begin{equation}
    \label{eq:evpequation}
-Line 183 
 $\sigma_{12}$. Introducing the divergenc
+Line 266 
 $\sigma_{12}$. Introducing the divergenc
  \dot{\epsilon}_{11}+\dot{\epsilon}_{22}$, and the horizontal tension
  and shearing strain rates, $D_T =
  \dot{\epsilon}_{11}-\dot{\epsilon}_{22}$ and $D_S =
-\dot{\epsilon}_{12}$, respectively and using the above abbreviations,
+\dot{\epsilon}_{12}$, respectively, and using the above abbreviations,
  the equations can be written as:
  \begin{align}
    \label{eq:evpstresstensor1}
-Line 213 
 differences and averaging is only involv
+Line 296 
 differences and averaging is only involv
  $P$ at vorticity points.
  For a general curvilinear grid, one needs in principle to take metric
- terms into account that arise in the transformation a curvilinear grid
+ terms into account that arise in the transformation of a curvilinear grid
- on the sphere. However, for now we can neglect these metric terms
+ on the sphere. For now, however, we can neglect these metric terms
  because they are very small on the cubed sphere grids used in this
  paper; in particular, only near the edges of the cubed sphere grid, we
  expect them to be non-zero, but these edges are at approximately
-Line 223 
 simulations.  Everywhere else the coordi
+Line 306 
 simulations.  Everywhere else the coordi
  cartesian.  However, for last-glacial-maximum or snowball-earth-like
  simulations the question of metric terms needs to be reconsidered.
  Either, one includes these terms as in \citet{zhang03}, or one finds a
- vector-invariant formulation fo the sea-ice internal stress term that
+ vector-invariant formulation for the sea-ice internal stress term that
  does not require any metric terms, as it is done in the ocean dynamics
  of the MITgcm \citep{adcroft04:_cubed_sphere}.
-Line 284 
 addition to ice-thickness and compactnes
+Line 367 
 addition to ice-thickness and compactnes
  state variables to be advected by ice velocities, namely enthalphy of
  the two ice layers and the thickness of the overlying snow layer.
- \section{Funnel Experiments}
- \label{sec:funnel}
- \begin{itemize}
- \item B-grid LSR no-slip
- \item C-grid LSR no-slip
- \item C-grid LSR slip
- \item C-grid EVP no-slip
- \item C-grid EVP slip
- \end{itemize}
- \subsection{B-grid vs.\ C-grid}
- Comparison between:
- \begin{itemize}
- \item B-grid, lsr, no-slip
- \item C-grid, lsr, no-slip
- \item C-grid, evp, no-slip
- \end{itemize}
- all without ice-ocean stress, because ice-ocean stress does not work
- for B-grid.
  \subsection{C-grid}
  \begin{itemize}
-Line 350 
 differences between the two main options
+Line 413 
 differences between the two main options
  \subsection{Arctic Domain with Open Boundaries}
  \label{sec:arctic}
- The Arctic domain of integration is illustrated in Fig.~\ref{???}.  It is
+ The Arctic domain of integration is illustrated in Fig.~\ref{fig:arctic1}.  It
- carved out from, and obtains open boundary conditions from, the global
+ is carved out from, and obtains open boundary conditions from, the
- cubed-sphere configuration of the Estimating the Circulation and Climate of
+ global cubed-sphere configuration of the Estimating the Circulation
- the Ocean, Phase II (ECCO2) project \cite{men05a}.  The domain size is 420 by
+ and Climate of the Ocean, Phase II (ECCO2) project
-grid boxes horizontally with mean horizontal grid spacing of 18 km.
+ \citet{menemenlis05}.  The domain size is 420 by 384 grid boxes
+ horizontally with mean horizontal grid spacing of 18 km.
+ \begin{figure}
+ %\centerline{{\includegraphics*[width=0.44\linewidth]{\fpath/arctic1.eps}}}
+ \caption{Bathymetry of Arctic Domain.\label{fig:arctic1}}
+ \end{figure}
  There are 50 vertical levels ranging in thickness from 10 m near the surface
  to approximately 450 m at a maximum model depth of 6150 m. Bathymetry is from
  the National Geophysical Data Center (NGDC) 2-minute gridded global relief
  data (ETOPO2) and the model employs the partial-cell formulation of
- \cite{adc97}, which permits accurate representation of the bathymetry. The
+ \citet{adcroft97:_shaved_cells}, which permits accurate representation of the bathymetry. The
  model is integrated in a volume-conserving configuration using a finite volume
  discretization with C-grid staggering of the prognostic variables. In the
- ocean, the non-linear equation of state of \cite{jac95}.  The ocean model is
+ ocean, the non-linear equation of state of \citet{jackett95}.  The ocean model is
  coupled to a sea-ice model described hereinabove.
- This particular ECCO2 simulation is initialized from rest using the January
+ This particular ECCO2 simulation is initialized from rest using the
- temperature and salinity distribution from the World Ocean Atlas 2001 (WOA01)
+ January temperature and salinity distribution from the World Ocean
- [Conkright et al., 2002] and it is integrated for 32 years prior to the
+ Atlas 2001 (WOA01) [Conkright et al., 2002] and it is integrated for
--2001 period discussed in the study. Surface boundary conditions are from
+years prior to the 1996--2001 period discussed in the study. Surface
- the National Centers for Environmental Prediction and the National Center for
+ boundary conditions are from the National Centers for Environmental
- Atmospheric Research (NCEP/NCAR) atmospheric reanalysis [Kistler et al.,
+ Prediction and the National Center for Atmospheric Research
-]. Six-hourly surface winds, temperature, humidity, downward short- and
+ (NCEP/NCAR) atmospheric reanalysis [Kistler et al., 2001]. Six-hourly
- long-wave radiations, and precipitation are converted to heat, freshwater, and
+ surface winds, temperature, humidity, downward short- and long-wave
- wind stress fluxes using the Large and Pond [1981, 1982] bulk
+ radiations, and precipitation are converted to heat, freshwater, and
- formulae. Shortwave radiation decays exponentially as per Paulson and Simpson
+ wind stress fluxes using the \citet{large81, large82} bulk formulae.
- [1977]. Additionally the time-mean river run-off from Large and Nurser [2001]
+ Shortwave radiation decays exponentially as per Paulson and Simpson
- is applied and there is a relaxation to the monthly-mean climatological sea
+ [1977]. Additionally the time-mean river run-off from Large and Nurser
- surface salinity values from WOA01 with a relaxation time scale of 3
+ [2001] is applied and there is a relaxation to the monthly-mean
- months. Vertical mixing follows Large et al. [1994] with background vertical
+ climatological sea surface salinity values from WOA01 with a
- diffusivity of 1.5 � 10-5 m2 s-1 and viscosity of 10-3 m2 s-1. A third order,
+ relaxation time scale of 3 months. Vertical mixing follows
- direct-space-time advection scheme with flux limiter is employed and there is
+ \citet{large94} with background vertical diffusivity of
- no explicit horizontal diffusivity. Horizontal viscosity follows Leith [1996]
+ $1.5\times10^{-5}\text{\,m$^{2}$\,s$^{-1}$}$ and viscosity of
- but modified to sense the divergent flow as per Fox-Kemper and Menemenlis [in
+ $10^{-3}\text{\,m$^{2}$\,s$^{-1}$}$. A third order, direct-space-time
- press].  Shortwave radiation decays exponentially as per Paulson and Simpson
+ advection scheme with flux limiter is employed \citep{hundsdorfer94}
- [1977].  Additionally, the time-mean runoff of Large and Nurser [2001] is
+ and there is no explicit horizontal diffusivity. Horizontal viscosity
- applied near the coastline and, where there is open water, there is a
+ follows \citet{lei96} but
- relaxation to monthly-mean WOA01 sea surface salinity with a time constant of
+ modified to sense the divergent flow as per Fox-Kemper and Menemenlis
-days.
+ [in press].  Shortwave radiation decays exponentially as per Paulson
+ and Simpson [1977].  Additionally, the time-mean runoff of Large and
+ Nurser [2001] is applied near the coastline and, where there is open
+ water, there is a relaxation to monthly-mean WOA01 sea surface
+ salinity with a time constant of 45 days.
  Open water, dry
  ice, wet ice, dry snow, and wet snow albedo are, respectively, 0.15, 0.85,
-Line 417 
 ice, wet ice, dry snow, and wet snow alb
+Line 490 
 ice, wet ice, dry snow, and wet snow alb
  \item C-grid LSR slip
  \item C-grid EVP no-slip
  \item C-grid EVP slip
+ \item C-grid LSR + TEM (truncated ellipse method, no tensile stress, new flag)
  \item C-grid LSR no-slip + Winton
  \item  speed-performance-accuracy (small)
    ice transport through Canadian Archipelago differences
-Line 428 
 We anticipate small differences between
+Line 502 
 We anticipate small differences between
  \begin{itemize}
  \item advection schemes: along the ice-edge and regions with large
    gradients
- \item C-grid: more transport through narrow straits for no slip
+ \item C-grid: less transport through narrow straits for no slip
-   conditons, less for free slip
+   conditons, more for free slip
  \item VP vs.\ EVP: speed performance, accuracy?
  \item ocean stress: different water mass properties beneath the ice
  \end{itemize}
- \section{Adjoint sensitivity experiment}
- \label{sec:adjoint}
- Adjoint sensitivity experiment on 1/2-res setup
-  Sensitivity of sea ice volume flow through Fram Strait
  \section{Adjoint sensiivities of the MITsim}
  \subsection{The adjoint of MITsim}
-Line 516 
 storing vs. recomputation of the model s
+Line 584 
 storing vs. recomputation of the model s
  checkpointing loop.
  Again, an initial code adjustment is required to support TAFs
  checkpointing capability.
- The code adjustments are sufficiently simply so as not to cause
+ The code adjustments are sufficiently simple so as not to cause
  major limitations to the full nonlinear parent model.
  Once in place, an adjoint model of a new model configuration
  may be derived in about 10 minutes.
-Line 539 
 may be derived in about 10 minutes.
+Line 607 
 may be derived in about 10 minutes.
  We demonstrate the power of the adjoint method
  in the context of investigating sea-ice export sensitivities through Fram Strait
  (for details of this study see Heimbach et al., 2007).
+ %\citep[for details of this study see][]{heimbach07}. %Heimbach et al., 2007).
  The domain chosen is a coarsened version of the Arctic face of the
  high-resolution cubed-sphere configuration of the ECCO2 project
- (see Menemenlis et al. 2005). It covers the entire Arctic,
+ \citep[see][]{menemenlis05}. It covers the entire Arctic,
  extends into the North Pacific such as to cover the entire
  ice-covered regions, and comprises parts of the North Atlantic
  down to XXN to enable analysis of remote influences of the
-Line 552 
 The adjoint models run efficiently on 80
+Line 621 
 The adjoint models run efficiently on 80
  (benchmarks have been performed both on an SGI Altix as well as an
  IBM SP5 at NASA/ARC).
- Following a 1-year spinup, the model has been integrated for four years
+ Following a 1-year spinup, the model has been integrated for four
- between 1992 and 1995.
+ years between 1992 and 1995. It is forced using realistic 6-hourly
- It is forced using realistic 6-hourly NCEP/NCAR atmospheric state variables.
+ NCEP/NCAR atmospheric state variables. Over the open ocean these are
- Over the open ocean these are converted into
+ converted into air-sea fluxes via the bulk formulae of
- air-sea fluxes via the bulk formulae of Large and Yeager (2004).
+ \citet{large04}.  Derivation of air-sea fluxes in the presence of
- Derivation of air-sea fluxes in the presence of sea-ice is handled
+ sea-ice is handled by the ice model as described in \refsec{model}.
- by the ice model as described in Section XXX.
  The objective function chosen is sea-ice export through Fram Strait
- computed for December 1995
+ computed for December 1995.  The adjoint model computes sensitivities
- The adjoint model computes sensitivities to sea-ice export back in time
+ to sea-ice export back in time from 1995 to 1992 along this
- from 1995 to 1992 along this trajectory.
+ trajectory.  In principle all adjoint model variable (i.e., Lagrange
- In principle all adjoint model variable (i.e. Lagrange multipliers)
+ multipliers) of the coupled ocean/sea-ice model are available to
- of the coupled ocean/sea-ice model
+ analyze the transient sensitivity behaviour of the ocean and sea-ice
- are available to analyze the transient sensitivity behaviour
+ state.  Over the open ocean, the adjoint of the bulk formula scheme
- of the ocean and sea-ice state.
+ computes sensitivities to the time-varying atmospheric state.  Over
- Over the open ocean, the adjoint of the bulk formula scheme
+ ice-covered parts, the sea-ice adjoint converts surface ocean
- computes sensitivities to the time-varying atmospheric state.
+ sensitivities to atmospheric sensitivities.
- Over ice-covered parts, the sea-ice adjoint converts
- surface ocean sensitivities to atmospheric sensitivities.
+ \reffig{4yradjheff}(a--d) depict sensitivities of sea-ice export
+ through Fram Strait in December 1995 to changes in sea-ice thickness
- Fig. XXX(a--d) depict sensitivities of sea-ice export through Fram Strait
+, 24, 36, 48 months back in time. Corresponding sensitivities to
- in December 1995 to changes in sea-ice thickness
+ ocean surface temperature are depicted in
-, 24, 36, 48 months back in time.
+ \reffig{4yradjthetalev1}(a--d).  The main characteristics is
- Corresponding sensitivities to ocean surface temperature are
+ consistency with expected advection of sea-ice over the relevant time
- depicted in Fig. XXX(a--d).
+ scales considered.  The general positive pattern means that an
- The main characteristics is consistency with expected advection
+ increase in sea-ice thickness at location $(x,y)$ and time $t$ will
- of sea-ice over the relevant time scales considered.
+ increase sea-ice export through Fram Strait at time $T_e$.  Largest
- The general positive pattern means that an increase in
+ distances from Fram Strait indicate fastest sea-ice advection over the
- sea-ice thickness at location $(x,y)$ and time $t$ will increase
+ time span considered.  The ice thickness sensitivities are in close
- sea-ice export through Fram Strait at time $T_e$.
+ correspondence to ocean surface sentivitites, but of opposite sign.
- Largest distances from Fram Strait indicate fastest sea-ice advection
+ An increase in temperature will incur ice melting, decrease in ice
- over the time span considered.
+ thickness, and therefore decrease in sea-ice export at time $T_e$.
- The ice thickness sensitivities are in close correspondence to
- ocean surface sentivitites, but of opposite sign.
- An increase in temperature will incur ice melting, decrease in ice thickness,
- and therefore decrease in sea-ice export at time $T_e$.
  The picture is fundamentally different and much more complex
  for sensitivities to ocean temperatures away from the surface.
- Fig. XXX (a--d) depicts ice export sensitivities to
+ \reffig{4yradjthetalev10??}(a--d) depicts ice export sensitivities to
  temperatures at roughly 400 m depth.
  Primary features are the effect of the heat transport of the North
  Atlantic current which feeds into the West Spitsbergen current,
-Line 600 
 the circulation around Svalbard, and ...
+Line 664 
 the circulation around Svalbard, and ...
  \begin{figure}[t!]
  \centerline{
  \subfigure[{\footnotesize -12 months}]
- {\includegraphics*[width=0.44\linewidth]{figs/run_4yr_ADJheff_arc_lev1_tim072_cmax2.0E+02.eps}}
+ {\includegraphics*[width=0.44\linewidth]{\fpath/run_4yr_ADJheff_arc_lev1_tim072_cmax2.0E+02.eps}}
  %\includegraphics*[width=.3\textwidth]{H_c.bin_res_100_lev1.pdf}
  %
  \subfigure[{\footnotesize -24 months}]
- {\includegraphics*[width=0.44\linewidth]{figs/run_4yr_ADJheff_arc_lev1_tim145_cmax2.0E+02.eps}}
+ {\includegraphics*[width=0.44\linewidth]{\fpath/run_4yr_ADJheff_arc_lev1_tim145_cmax2.0E+02.eps}}
  }
  \centerline{
  \subfigure[{\footnotesize
  -36 months}]
- {\includegraphics*[width=0.44\linewidth]{figs/run_4yr_ADJheff_arc_lev1_tim218_cmax2.0E+02.eps}}
+ {\includegraphics*[width=0.44\linewidth]{\fpath/run_4yr_ADJheff_arc_lev1_tim218_cmax2.0E+02.eps}}
  %
  \subfigure[{\footnotesize
  -48 months}]
- {\includegraphics*[width=0.44\linewidth]{figs/run_4yr_ADJheff_arc_lev1_tim292_cmax2.0E+02.eps}}
+ {\includegraphics*[width=0.44\linewidth]{\fpath/run_4yr_ADJheff_arc_lev1_tim292_cmax2.0E+02.eps}}
  }
  \caption{Sensitivity of sea-ice export through Fram Strait in December 2005 to
  sea-ice thickness at various prior times.
-Line 625 
 sea-ice thickness at various prior times
+Line 689 
 sea-ice thickness at various prior times
  \begin{figure}[t!]
  \centerline{
  \subfigure[{\footnotesize -12 months}]
- {\includegraphics*[width=0.44\linewidth]{figs/run_4yr_ADJtheta_arc_lev1_tim072_cmax5.0E+01.eps}}
+ {\includegraphics*[width=0.44\linewidth]{\fpath/run_4yr_ADJtheta_arc_lev1_tim072_cmax5.0E+01.eps}}
  %\includegraphics*[width=.3\textwidth]{H_c.bin_res_100_lev1.pdf}
  %
  \subfigure[{\footnotesize -24 months}]
- {\includegraphics*[width=0.44\linewidth]{figs/run_4yr_ADJtheta_arc_lev1_tim145_cmax5.0E+01.eps}}
+ {\includegraphics*[width=0.44\linewidth]{\fpath/run_4yr_ADJtheta_arc_lev1_tim145_cmax5.0E+01.eps}}
  }
  \centerline{
  \subfigure[{\footnotesize
  -36 months}]
- {\includegraphics*[width=0.44\linewidth]{figs/run_4yr_ADJtheta_arc_lev1_tim218_cmax5.0E+01.eps}}
+ {\includegraphics*[width=0.44\linewidth]{\fpath/run_4yr_ADJtheta_arc_lev1_tim218_cmax5.0E+01.eps}}
  %
  \subfigure[{\footnotesize
  -48 months}]
- {\includegraphics*[width=0.44\linewidth]{figs/run_4yr_ADJtheta_arc_lev1_tim292_cmax5.0E+01.eps}}
+ {\includegraphics*[width=0.44\linewidth]{\fpath/run_4yr_ADJtheta_arc_lev1_tim292_cmax5.0E+01.eps}}
  }
- \caption{Same as Fig. XXX but for sea surface temperature
+ \caption{Same as \reffig{4yradjheff} but for sea surface temperature
  \label{fig:4yradjthetalev1}}
  \end{figure}
-Line 666 
 parameters that we use here. What about
+Line 730 
 parameters that we use here. What about
  \paragraph{Acknowledgements}
  We thank Jinlun Zhang for providing the original B-grid code and many
- helpful discussions.
+ helpful discussions. ML thanks Elizabeth Hunke for multiple explanations.
  \bibliography{bib/journal_abrvs,bib/seaice,bib/genocean,bib/maths,bib/mitgcmuv,bib/fram}
-Line 676 
 helpful discussions.
+Line 740 
 helpful discussions.
  %%% mode: latex
  %%% TeX-master: t
  %%% End:
+ A Dynamic-Thermodynamic Sea ice Model for Ocean Climate
+   Estimation on an Arakawa C-Grid
+ Introduction
+ Ice Model:
+  Dynamics formulation.
+   B-C, LSR, EVP, no-slip, slip
+   parallellization
+  Thermodynamics formulation.
+-layer Hibler salinity + snow
+-layer Winton
+ Idealized tests
+  Funnel Experiments
+  Downstream Island tests
+   B-grid LSR no-slip
+   C-grid LSR no-slip
+   C-grid LSR slip
+   C-grid EVP no-slip
+   C-grid EVP slip
+ Arctic Setup
+  Configuration
+  OBCS from cube
+  forcing
+/2 and full resolution
+  with a few JFM figs from C-grid LSR no slip
+   ice transport through Canadian Archipelago
+   thickness distribution
+   ice velocity and transport
+ Arctic forward sensitivity experiments
+  B-grid LSR no-slip
+  C-grid LSR no-slip
+  C-grid LSR slip
+  C-grid EVP no-slip
+  C-grid EVP slip
+  C-grid LSR no-slip + Winton
+   speed-performance-accuracy (small)
+   ice transport through Canadian Archipelago differences
+   thickness distribution differences
+   ice velocity and transport differences
+ Adjoint sensitivity experiment on 1/2-res setup
+  Sensitivity of sea ice volume flow through Fram Strait
+ *** Sensitivity of sea ice volume flow through Canadian Archipelago
+ Summary and conluding remarks

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