--- MITgcm_contrib/articles/ceaice/ceaice.tex	2008/02/25 23:45:46	1.13
+++ MITgcm_contrib/articles/ceaice/ceaice.tex	2008/02/26 00:13:20	1.14
@@ -1,4 +1,4 @@
-% $Header: /home/ubuntu/mnt/e9_copy/MITgcm_contrib/articles/ceaice/ceaice.tex,v 1.13 2008/02/25 23:45:46 dimitri Exp $
+% $Header: /home/ubuntu/mnt/e9_copy/MITgcm_contrib/articles/ceaice/ceaice.tex,v 1.14 2008/02/26 00:13:20 dimitri Exp $
 % $Name:  $
 \documentclass[12pt]{article}
 
@@ -52,7 +52,6 @@
 \maketitle
 
 \begin{abstract}
-
 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
@@ -76,10 +75,35 @@
 \section{Introduction}
 \label{sec:intro}
 
+The availability of an adjoint model as a powerful research
+tool complementary to an ocean model was a major design
+requirement early on in the development of the MIT general
+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
@@ -95,9 +119,18 @@
 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}