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revision 1.4 by mlosch, Thu Jan 10 15:47:32 2008 UTC revision 1.12 by dimitri, Mon Feb 25 22:06:17 2008 UTC
# Line 1  Line 1 
1    % $Header$
2    % $Name$
3  \documentclass[12pt]{article}  \documentclass[12pt]{article}
4    
5  \usepackage{graphicx,subfigure}  \usepackage[]{graphicx}
6    \usepackage{subfigure}
7    
8  \usepackage[round,comma]{natbib}  \usepackage[round,comma]{natbib}
9  \bibliographystyle{bib/agu04}  \bibliographystyle{bib/agu04}
# Line 49  Line 52 
52  \maketitle  \maketitle
53    
54  \begin{abstract}  \begin{abstract}
55    Some blabla  
56    As part of ongoing efforts to obtain a best possible synthesis of most
57    available, global-scale, ocean and sea ice data, a dynamic and thermodynamic
58    sea-ice model has been coupled to the Massachusetts Institute of Technology
59    general circulation model (MITgcm).  Ice mechanics follow a viscous plastic
60    rheology and the ice momentum equations are solved numerically using either
61    line successive relaxation (LSR) or elastic-viscous-plastic (EVP) dynamic
62    models.  Ice thermodynamics are represented using either a zero-heat-capacity
63    formulation or a two-layer formulation that conserves enthalpy.  The model
64    includes prognostic variables for snow and for sea-ice salinity.  The above
65    sea ice model components were borrowed from current-generation climate models
66    but they were reformulated on an Arakawa C-grid in order to match the MITgcm
67    oceanic grid and they were modified in many ways to permit efficient and
68    accurate automatic differentiation.  This paper describes the MITgcm sea ice
69    model; it presents example Arctic and Antarctic results from a realistic,
70    eddy-permitting, global ocean and sea-ice configuration; it compares B-grid
71    and C-grid dynamic solvers in a regional Arctic configuration; and it presents
72    example results from coupled ocean and sea-ice adjoint-model integrations.
73    
74  \end{abstract}  \end{abstract}
75    
76  \section{Introduction}  \section{Introduction}
77  \label{sec:intro}  \label{sec:intro}
78    
 more blabla  
   
79  \section{Model}  \section{Model}
80  \label{sec:model}  \label{sec:model}
81    
# Line 129  The ice strain rate is given by Line 148  The ice strain rate is given by
148      \frac{\partial{u_{i}}}{\partial{x_{j}}} +      \frac{\partial{u_{i}}}{\partial{x_{j}}} +
149      \frac{\partial{u_{j}}}{\partial{x_{i}}}\right).      \frac{\partial{u_{j}}}{\partial{x_{i}}}\right).
150  \end{equation*}  \end{equation*}
151  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
152  $h$ and compactness (concentration) $c$:  both thickness $h$ and compactness (concentration) $c$:
153  \begin{equation}  \begin{equation}
154    P = P^{*}c\,h\,e^{[C^{*}\cdot(1-c)]},    P_{\max} = P^{*}c\,h\,e^{[C^{*}\cdot(1-c)]},
155  \label{icestrength}  \label{eq:icestrength}
156  \end{equation}  \end{equation}
157  with the constants $P^{*}$ and $C^{*}$. The nonlinear bulk and shear  with the constants $P^{*}$ and $C^{*}$. The nonlinear bulk and shear
158  viscosities $\eta$ and $\zeta$ are functions of ice strain rate  viscosities $\eta$ and $\zeta$ are functions of ice strain rate
# Line 141  invariants and ice strength such that th Line 160  invariants and ice strength such that th
160  stress lie on an elliptical yield curve with the ratio of major to  stress lie on an elliptical yield curve with the ratio of major to
161  minor axis $e$ equal to $2$; they are given by:  minor axis $e$ equal to $2$; they are given by:
162  \begin{align*}  \begin{align*}
163    \zeta =& \frac{P}{2\Delta} \\    \zeta =& \min\left(\frac{P_{\max}}{2\max(\Delta,\Delta_{\min})},
164    \eta =& \frac{P}{2\Delta{e}^2} \\     \zeta_{\max}\right) \\
165      \eta =& \frac{\zeta}{e^2} \\
166    \intertext{with the abbreviation}    \intertext{with the abbreviation}
167    \Delta = & \left[    \Delta = & \left[
168      \left(\dot{\epsilon}_{11}^2+\dot{\epsilon}_{22}^2\right)      \left(\dot{\epsilon}_{11}^2+\dot{\epsilon}_{22}^2\right)
# Line 150  minor axis $e$ equal to $2$; they are gi Line 170  minor axis $e$ equal to $2$; they are gi
170      2\dot{\epsilon}_{11}\dot{\epsilon}_{22} (1-e^{-2})      2\dot{\epsilon}_{11}\dot{\epsilon}_{22} (1-e^{-2})
171    \right]^{-\frac{1}{2}}    \right]^{-\frac{1}{2}}
172  \end{align*}  \end{align*}
173    The bulk viscosities are bounded above by imposing both a minimum
174    $\Delta_{\min}=10^{-11}\text{\,s}^{-1}$ (for numerical reasons) and a
175    maximum $\zeta_{\max} = P_{\max}/\Delta^*$, where
176    $\Delta^*=(5\times10^{12}/2\times10^4)\text{\,s}^{-1}$. For stress
177    tensor compuation the replacement pressure $P = 2\,\Delta\zeta$
178    \citep{hibler95} is used so that the stress state always lies on the
179    elliptic yield curve by definition.
180    
181    In the so-called truncated ellipse method the shear viscosity $\eta$
182    is capped to suppress any tensile stress \citep{hibler97, geiger98}:
183    \begin{equation}
184      \label{eq:etatem}
185      \eta = \min(\frac{\zeta}{e^2}
186      \frac{\frac{P}{2}-\zeta(\dot{\epsilon}_{11}+\dot{\epsilon}_{22})}
187      {\sqrt{(\dot{\epsilon}_{11}+\dot{\epsilon}_{22})^2
188          +4\dot{\epsilon}_{12}^2}}
189    \end{equation}
190    
191  In the current implementation, the VP-model is integrated with the  In the current implementation, the VP-model is integrated with the
192  semi-implicit line successive over relaxation (LSOR)-solver of  semi-implicit line successive over relaxation (LSOR)-solver of
193  \citet{zhang98}, which allows for long time steps that, in our case,  \citet{zhang98}, which allows for long time steps that, in our case,
# Line 289  addition to ice-thickness and compactnes Line 327  addition to ice-thickness and compactnes
327  state variables to be advected by ice velocities, namely enthalphy of  state variables to be advected by ice velocities, namely enthalphy of
328  the two ice layers and the thickness of the overlying snow layer.  the two ice layers and the thickness of the overlying snow layer.
329    
 \section{Funnel Experiments}  
 \label{sec:funnel}  
   
 For a first/detailed comparison between the different variants of the  
 MIT sea ice model an idealized geometry of a periodic channel,  
 1000\,km long and 500\,m wide on a non-rotating plane, with converging  
 walls forming a symmetric funnel and a narrow strait of 40\,km width  
 is used. The horizontal resolution is 5\,km throughout the domain  
 making the narrow strait 8 grid points wide. The ice model is  
 initialized with a complete ice cover of 50\,cm uniform thickness. The  
 ice model is driven by a constant along channel eastward ocean current  
 of 25\,cm/s that does not see the walls in the domain. All other  
 ice-ocean-atmosphere interactions are turned off, in particular there  
 is no feedback of ice dynamics on the ocean current. All thermodynamic  
 processes are turned off so that ice thickness variations are only  
 caused by convergent or divergent ice flow. Ice volume (effective  
 thickness) and concentration are advected with a third-order scheme  
 with a flux limiter \citep{hundsdorfer94} to avoid undershoots. This  
 scheme is unconditionally stable and does not require additional  
 diffusion. The time step used here is 1\,h.  
   
 \reffig{funnelf0} compares the dynamic fields ice concentration $c$,  
 effective thickness $h_{eff} = h\cdot{c}$, and velocities $(u,v)$ for  
 five different cases at steady state (after 10\,years of integration):  
 \begin{description}  
 \item[B-LSRns:] LSR solver with no-slip boundary conditions on a B-grid,  
 \item[C-LSRns:] LSR solver with no-slip boundary conditions on a C-grid,  
 \item[C-LSRfs:] LSR solver with free-slip boundary conditions on a C-grid,  
 \item[C-EVPns:] EVP solver with no-slip boundary conditions on a C-grid,  
 \item[C-EVPfs:] EVP solver with free-slip boundary conditions on a C-grid,  
 \end{description}  
 \ml{[We have not implemented the EVP solver on a B-grid.]}  
 \begin{figure*}[htbp]  
   \includegraphics[width=\widefigwidth]{\fpath/all_086280}  
   \caption{Ice concentration, effective thickness [m], and ice  
     velocities [m/s]  
     for 5 different numerical solutions.}  
   \label{fig:funnelf0}  
 \end{figure*}  
 At a first glance, the solutions look similar. This is encouraging as  
 the details of discretization and numerics should not affect the  
 solutions to first order. In all cases the ice-ocean stress pushes the  
 ice cover eastwards, where it converges in the funnel. In the narrow  
 channel the ice moves quickly (nearly free drift) and leaves the  
 channel as narrow band.  
   
 A close look reveals interesting differences between the B- and C-grid  
 results. The zonal velocity in the narrow channel is nearly the free  
 drift velocity ( = ocean velocity) of 25\,cm/s for the C-grid  
 solutions, regardless of the boundary conditions, while it is just  
 above 20\,cm/s for the B-grid solution. The ice accelerates to  
 25\,cm/s after it exits the channel. Concentrating on the solutions  
 B-LSRns and C-LSRns, the ice volume (effective thickness) along the  
 boundaries in the narrow channel is larger in the B-grid case although  
 the ice concentration is reduces in the C-grid case. The combined  
 effect leads to a larger actual ice thickness at smaller  
 concentrations in the C-grid case. However, since the effective  
 thickness determines the ice strength $P$ in Eq\refeq{icestrength},  
 the ice strength and thus the bulk and shear viscosities are larger in  
 the B-grid case leading to more horizontal friction. This circumstance  
 might explain why the no-slip boundary conditions in the B-grid case  
 appear to be more effective in reducing the flow within the narrow  
 channel, than in the C-grid case. Further, the viscosities are also  
 sensitive to details of the velocity gradients. Via $\Delta$, these  
 gradients enter the viscosities in the denominator so that large  
 gradients tend to reduce the viscosities. This again favors more flow  
 along the boundaries in the C-grid case: larger velocities  
 (\reffig{funnelf0}) on grid points that are closer to the boundary by  
 a factor $\frac{1}{2}$ than in the B-grid case because of the stagger  
 nature of the C-grid lead numerically to larger tangential gradients  
 across the boundary; these in turn make the viscosities smaller for  
 less tangential friction and allow more tangential flow along the  
 boundaries.  
   
 The above argument can also be invoked to explain the small  
 differences between the free-slip and no-slip solutions on the C-grid.  
 Because of the non-linearities in the ice viscosities, in particular  
 along the boundaries, the no-slip boundary conditions has only a small  
 impact on the solution.  
   
 The difference between LSR and EVP solutions is largest in the  
 effective thickness and meridional velocity fields. The velocity field  
 appears to be a little noisy. This noise has been address by  
 \citet{hunke01}. It can be dealt with by reducing EVP's internal time  
 step (increasing the number of iterations) or by regularizing the bulk  
 and shear viscosities. We revisit the latter option by reproducing the  
 results of \citet{hunke01} for the C-grid no-slip cases.  
 \begin{figure*}[htbp]  
   \includegraphics[width=\widefigwidth]{\fpath/hun12days}  
   \caption{Hunke's test case.}  
   \label{fig:hunke01}  
 \end{figure*}  
   
 \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.  
330    
331  \subsection{C-grid}  \subsection{C-grid}
332  \begin{itemize}  \begin{itemize}
# Line 445  differences between the two main options Line 373  differences between the two main options
373  \subsection{Arctic Domain with Open Boundaries}  \subsection{Arctic Domain with Open Boundaries}
374  \label{sec:arctic}  \label{sec:arctic}
375    
376  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
377  carved out from, and obtains open boundary conditions from, the global  is carved out from, and obtains open boundary conditions from, the
378  cubed-sphere configuration of the Estimating the Circulation and Climate of  global cubed-sphere configuration of the Estimating the Circulation
379  the Ocean, Phase II (ECCO2) project \cite{men05a}.  The domain size is 420 by  and Climate of the Ocean, Phase II (ECCO2) project
380  384 grid boxes horizontally with mean horizontal grid spacing of 18 km.    \citet{menemenlis05}.  The domain size is 420 by 384 grid boxes
381    horizontally with mean horizontal grid spacing of 18 km.
382    
383    \begin{figure}
384    %\centerline{{\includegraphics*[width=0.44\linewidth]{\fpath/arctic1.eps}}}
385    \caption{Bathymetry of Arctic Domain.\label{fig:arctic1}}
386    \end{figure}
387    
388  There are 50 vertical levels ranging in thickness from 10 m near the surface  There are 50 vertical levels ranging in thickness from 10 m near the surface
389  to approximately 450 m at a maximum model depth of 6150 m. Bathymetry is from  to approximately 450 m at a maximum model depth of 6150 m. Bathymetry is from
390  the National Geophysical Data Center (NGDC) 2-minute gridded global relief  the National Geophysical Data Center (NGDC) 2-minute gridded global relief
391  data (ETOPO2) and the model employs the partial-cell formulation of  data (ETOPO2) and the model employs the partial-cell formulation of
392  \cite{adc97}, which permits accurate representation of the bathymetry. The  \citet{adcroft97:_shaved_cells}, which permits accurate representation of the bathymetry. The
393  model is integrated in a volume-conserving configuration using a finite volume  model is integrated in a volume-conserving configuration using a finite volume
394  discretization with C-grid staggering of the prognostic variables. In the  discretization with C-grid staggering of the prognostic variables. In the
395  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
396  coupled to a sea-ice model described hereinabove.    coupled to a sea-ice model described hereinabove.  
397    
398  This particular ECCO2 simulation is initialized from rest using the January  This particular ECCO2 simulation is initialized from rest using the
399  temperature and salinity distribution from the World Ocean Atlas 2001 (WOA01)  January temperature and salinity distribution from the World Ocean
400  [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
401  1996-2001 period discussed in the study. Surface boundary conditions are from  32 years prior to the 1996--2001 period discussed in the study. Surface
402  the National Centers for Environmental Prediction and the National Center for  boundary conditions are from the National Centers for Environmental
403  Atmospheric Research (NCEP/NCAR) atmospheric reanalysis [Kistler et al.,  Prediction and the National Center for Atmospheric Research
404  2001]. Six-hourly surface winds, temperature, humidity, downward short- and  (NCEP/NCAR) atmospheric reanalysis [Kistler et al., 2001]. Six-hourly
405  long-wave radiations, and precipitation are converted to heat, freshwater, and  surface winds, temperature, humidity, downward short- and long-wave
406  wind stress fluxes using the Large and Pond [1981, 1982] bulk  radiations, and precipitation are converted to heat, freshwater, and
407  formulae. Shortwave radiation decays exponentially as per Paulson and Simpson  wind stress fluxes using the \citet{large81, large82} bulk formulae.
408  [1977]. Additionally the time-mean river run-off from Large and Nurser [2001]  Shortwave radiation decays exponentially as per Paulson and Simpson
409  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
410  surface salinity values from WOA01 with a relaxation time scale of 3  [2001] is applied and there is a relaxation to the monthly-mean
411  months. Vertical mixing follows Large et al. [1994] with background vertical  climatological sea surface salinity values from WOA01 with a
412  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
413  direct-space-time advection scheme with flux limiter is employed and there is  \citet{large94} with background vertical diffusivity of
414  no explicit horizontal diffusivity. Horizontal viscosity follows Leith [1996]  $1.5\times10^{-5}\text{\,m$^{2}$\,s$^{-1}$}$ and viscosity of
415  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
416  press].  Shortwave radiation decays exponentially as per Paulson and Simpson  advection scheme with flux limiter is employed \citep{hundsdorfer94}
417  [1977].  Additionally, the time-mean runoff of Large and Nurser [2001] is  and there is no explicit horizontal diffusivity. Horizontal viscosity
418  applied near the coastline and, where there is open water, there is a  follows \citet{lei96} but
419  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
420  45 days.  [in press].  Shortwave radiation decays exponentially as per Paulson
421    and Simpson [1977].  Additionally, the time-mean runoff of Large and
422    Nurser [2001] is applied near the coastline and, where there is open
423    water, there is a relaxation to monthly-mean WOA01 sea surface
424    salinity with a time constant of 45 days.
425    
426  Open water, dry  Open water, dry
427  ice, wet ice, dry snow, and wet snow albedo are, respectively, 0.15, 0.85,  ice, wet ice, dry snow, and wet snow albedo are, respectively, 0.15, 0.85,
# Line 512  ice, wet ice, dry snow, and wet snow alb Line 450  ice, wet ice, dry snow, and wet snow alb
450  \item C-grid LSR slip  \item C-grid LSR slip
451  \item C-grid EVP no-slip  \item C-grid EVP no-slip
452  \item C-grid EVP slip  \item C-grid EVP slip
453    \item C-grid LSR + TEM (truncated ellipse method, no tensile stress, new flag)
454  \item C-grid LSR no-slip + Winton  \item C-grid LSR no-slip + Winton
455  \item  speed-performance-accuracy (small)  \item  speed-performance-accuracy (small)
456    ice transport through Canadian Archipelago differences    ice transport through Canadian Archipelago differences
# Line 523  We anticipate small differences between Line 462  We anticipate small differences between
462  \begin{itemize}  \begin{itemize}
463  \item advection schemes: along the ice-edge and regions with large  \item advection schemes: along the ice-edge and regions with large
464    gradients    gradients
465  \item C-grid: more transport through narrow straits for no slip  \item C-grid: less transport through narrow straits for no slip
466    conditons, less for free slip    conditons, more for free slip
467  \item VP vs.\ EVP: speed performance, accuracy?  \item VP vs.\ EVP: speed performance, accuracy?
468  \item ocean stress: different water mass properties beneath the ice  \item ocean stress: different water mass properties beneath the ice
469  \end{itemize}  \end{itemize}
# Line 605  storing vs. recomputation of the model s Line 544  storing vs. recomputation of the model s
544  checkpointing loop.  checkpointing loop.
545  Again, an initial code adjustment is required to support TAFs  Again, an initial code adjustment is required to support TAFs
546  checkpointing capability.  checkpointing capability.
547  The code adjustments are sufficiently simply so as not to cause  The code adjustments are sufficiently simple so as not to cause
548  major limitations to the full nonlinear parent model.  major limitations to the full nonlinear parent model.
549  Once in place, an adjoint model of a new model configuration  Once in place, an adjoint model of a new model configuration
550  may be derived in about 10 minutes.  may be derived in about 10 minutes.
# Line 628  may be derived in about 10 minutes. Line 567  may be derived in about 10 minutes.
567  We demonstrate the power of the adjoint method  We demonstrate the power of the adjoint method
568  in the context of investigating sea-ice export sensitivities through Fram Strait  in the context of investigating sea-ice export sensitivities through Fram Strait
569  (for details of this study see Heimbach et al., 2007).  (for details of this study see Heimbach et al., 2007).
570    %\citep[for details of this study see][]{heimbach07}. %Heimbach et al., 2007).
571  The domain chosen is a coarsened version of the Arctic face of the  The domain chosen is a coarsened version of the Arctic face of the
572  high-resolution cubed-sphere configuration of the ECCO2 project  high-resolution cubed-sphere configuration of the ECCO2 project
573  (see Menemenlis et al. 2005). It covers the entire Arctic,  \citep[see][]{menemenlis05}. It covers the entire Arctic,
574  extends into the North Pacific such as to cover the entire  extends into the North Pacific such as to cover the entire
575  ice-covered regions, and comprises parts of the North Atlantic  ice-covered regions, and comprises parts of the North Atlantic
576  down to XXN to enable analysis of remote influences of the  down to XXN to enable analysis of remote influences of the
# Line 641  The adjoint models run efficiently on 80 Line 581  The adjoint models run efficiently on 80
581  (benchmarks have been performed both on an SGI Altix as well as an  (benchmarks have been performed both on an SGI Altix as well as an
582  IBM SP5 at NASA/ARC).  IBM SP5 at NASA/ARC).
583    
584  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
585  between 1992 and 1995.  years between 1992 and 1995. It is forced using realistic 6-hourly
586  It is forced using realistic 6-hourly NCEP/NCAR atmospheric state variables.  NCEP/NCAR atmospheric state variables. Over the open ocean these are
587  Over the open ocean these are converted into  converted into air-sea fluxes via the bulk formulae of
588  air-sea fluxes via the bulk formulae of Large and Yeager (2004).  \citet{large04}.  Derivation of air-sea fluxes in the presence of
589  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.  
590  The objective function chosen is sea-ice export through Fram Strait  The objective function chosen is sea-ice export through Fram Strait
591  computed for December 1995  computed for December 1995.  The adjoint model computes sensitivities
592  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
593  from 1995 to 1992 along this trajectory.  trajectory.  In principle all adjoint model variable (i.e., Lagrange
594  In principle all adjoint model variable (i.e. Lagrange multipliers)  multipliers) of the coupled ocean/sea-ice model are available to
595  of the coupled ocean/sea-ice model  analyze the transient sensitivity behaviour of the ocean and sea-ice
596  are available to analyze the transient sensitivity behaviour  state.  Over the open ocean, the adjoint of the bulk formula scheme
597  of the ocean and sea-ice state.  computes sensitivities to the time-varying atmospheric state.  Over
598  Over the open ocean, the adjoint of the bulk formula scheme  ice-covered parts, the sea-ice adjoint converts surface ocean
599  computes sensitivities to the time-varying atmospheric state.  sensitivities to atmospheric sensitivities.
600  Over ice-covered parts, the sea-ice adjoint converts  
601  surface ocean sensitivities to atmospheric sensitivities.  \reffig{4yradjheff}(a--d) depict sensitivities of sea-ice export
602    through Fram Strait in December 1995 to changes in sea-ice thickness
603  Fig. XXX(a--d) depict sensitivities of sea-ice export through Fram Strait  12, 24, 36, 48 months back in time. Corresponding sensitivities to
604  in December 1995 to changes in sea-ice thickness  ocean surface temperature are depicted in
605  12, 24, 36, 48 months back in time.  \reffig{4yradjthetalev1}(a--d).  The main characteristics is
606  Corresponding sensitivities to ocean surface temperature are  consistency with expected advection of sea-ice over the relevant time
607  depicted in Fig. XXX(a--d).  scales considered.  The general positive pattern means that an
608  The main characteristics is consistency with expected advection  increase in sea-ice thickness at location $(x,y)$ and time $t$ will
609  of sea-ice over the relevant time scales considered.  increase sea-ice export through Fram Strait at time $T_e$.  Largest
610  The general positive pattern means that an increase in  distances from Fram Strait indicate fastest sea-ice advection over the
611  sea-ice thickness at location $(x,y)$ and time $t$ will increase  time span considered.  The ice thickness sensitivities are in close
612  sea-ice export through Fram Strait at time $T_e$.  correspondence to ocean surface sentivitites, but of opposite sign.
613  Largest distances from Fram Strait indicate fastest sea-ice advection  An increase in temperature will incur ice melting, decrease in ice
614  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 $T_e$.  
615    
616  The picture is fundamentally different and much more complex  The picture is fundamentally different and much more complex
617  for sensitivities to ocean temperatures away from the surface.  for sensitivities to ocean temperatures away from the surface.
618  Fig. XXX (a--d) depicts ice export sensitivities to  \reffig{4yradjthetalev10??}(a--d) depicts ice export sensitivities to
619  temperatures at roughly 400 m depth.  temperatures at roughly 400 m depth.
620  Primary features are the effect of the heat transport of the North  Primary features are the effect of the heat transport of the North
621  Atlantic current which feeds into the West Spitsbergen current,  Atlantic current which feeds into the West Spitsbergen current,
# Line 730  sea-ice thickness at various prior times Line 665  sea-ice thickness at various prior times
665  -48 months}]  -48 months}]
666  {\includegraphics*[width=0.44\linewidth]{\fpath/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}}
667  }  }
668  \caption{Same as Fig. XXX but for sea surface temperature  \caption{Same as \reffig{4yradjheff} but for sea surface temperature
669  \label{fig:4yradjthetalev1}}  \label{fig:4yradjthetalev1}}
670  \end{figure}  \end{figure}
671    
# Line 755  parameters that we use here. What about Line 690  parameters that we use here. What about
690    
691  \paragraph{Acknowledgements}  \paragraph{Acknowledgements}
692  We thank Jinlun Zhang for providing the original B-grid code and many  We thank Jinlun Zhang for providing the original B-grid code and many
693  helpful discussions.  helpful discussions. ML thanks Elizabeth Hunke for multiple explanations.
694    
695  \bibliography{bib/journal_abrvs,bib/seaice,bib/genocean,bib/maths,bib/mitgcmuv,bib/fram}  \bibliography{bib/journal_abrvs,bib/seaice,bib/genocean,bib/maths,bib/mitgcmuv,bib/fram}
696    

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