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1% ================================================================
2% Chapter Assimilation increments (ASM)
3% ================================================================
4\chapter{Apply assimilation increments (ASM)}
5\label{ASM}
6
7Authors: D. Lea,  M. Martin, K. Mogensen, A. Weaver, ...   % do we keep
8
9\minitoc
10
11
12\newpage
13$\ $\newline    % force a new line
14
15The ASM code adds the functionality to apply increments to the model variables:
16temperature, salinity, sea surface height, velocity and sea ice concentration.
17These are read into the model from a NetCDF file which may be produced by separate data
18assimilation code.  The code can also output model background fields which are used
19as an input to data assimilation code. This is all controlled by the namelist
20\textit{\ngn{nam\_asminc} }.  There is a brief description of all the namelist options
21provided.  To build the ASM code \key{asminc} must be set.
22
23%===============================================================
24
25\section{Direct initialization}
26\label{ASM_DI}
27
28Direct initialization (DI) refers to the instantaneous correction
29of the model background state using the analysis increment.
30DI is used when \np{ln\_asmdin} is set to true.
31
32\section{Incremental Analysis Updates}
33\label{ASM_IAU}
34
35Rather than updating the model state directly with the analysis increment,
36it may be preferable to introduce the increment gradually into the ocean
37model in order to minimize spurious adjustment processes. This technique
38is referred to as Incremental Analysis Updates (IAU) \citep{Bloom_al_MWR96}.
39IAU is a common technique used with 3D assimilation methods such as 3D-Var or OI.
40IAU is used when \np{ln\_asmiau} is set to true.
41
42With IAU, the model state trajectory ${\bf x}$ in the assimilation window
43($t_{0} \leq t_{i} \leq t_{N}$)
44is corrected by adding the analysis increments for temperature, salinity, horizontal velocity and SSH
45as additional tendency terms to the prognostic equations:
46\begin{eqnarray}     \label{eq:wa_traj_iau}
47{\bf x}^{a}(t_{i}) = M(t_{i}, t_{0})[{\bf x}^{b}(t_{0})]
48\; + \; F_{i} \delta \tilde{\bf x}^{a} 
49\end{eqnarray}
50where $F_{i}$ is a weighting function for applying the increments $\delta
51\tilde{\bf x}^{a}$ defined such that $\sum_{i=1}^{N} F_{i}=1$.
52${\bf x}^b$ denotes the model initial state and ${\bf x}^a$ is the model state
53after the increments are applied.
54To control the adjustment time of the model to the increment,
55the increment can be applied over an arbitrary sub-window,
56$t_{m} \leq t_{i} \leq t_{n}$, of the main assimilation window,
57where $t_{0} \leq t_{m} \leq t_{i}$ and $t_{i} \leq t_{n} \leq t_{N}$,
58Typically the increments are spread evenly over the full window.
59In addition, two different weighting functions have been implemented.
60The first function employs constant weights,
61\begin{eqnarray}    \label{eq:F1_i}
62F^{(1)}_{i}
63=\left\{ \begin{array}{ll}
64   0     &    {\rm if} \; \; \; t_{i} < t_{m}                \\
65   1/M &    {\rm if} \; \; \; t_{m} < t_{i} \leq t_{n} \\
66   0     &    {\rm if} \; \; \; t_{i} > t_{n}
67  \end{array} \right.
68\end{eqnarray}
69where $M = m-n$.
70The second function employs peaked hat-like weights in order to give maximum
71weight in the centre of the sub-window, with the weighting reduced
72linearly to a small value at the window end-points:
73\begin{eqnarray}     \label{eq:F2_i}
74F^{(2)}_{i}
75=\left\{ \begin{array}{ll}
76   0                           &    {\rm if} \; \; \; t_{i}       <     t_{m}                        \\
77   \alpha \, i               &    {\rm if} \; \; \; t_{m}    \leq t_{i}    \leq   t_{M/2}   \\
78   \alpha \, (M - i +1) &    {\rm if} \; \; \; t_{M/2}  <    t_{i}    \leq   t_{n}       \\
79   0                            &   {\rm if} \; \; \; t_{i}        >    t_{n}
80  \end{array} \right.
81\end{eqnarray}
82where $\alpha^{-1} = \sum_{i=1}^{M/2} 2i$ and $M$ is assumed to be even.
83The weights described by \eqref{eq:F2_i} provide a
84smoother transition of the analysis trajectory from one assimilation cycle
85to the next than that described by \eqref{eq:F1_i}.
86
87%==========================================================================
88% Divergence damping description %%%
89\section{Divergence damping initialisation}
90\label{ASM_details}
91
92The velocity increments may be initialized by the iterative application of
93a divergence damping operator. In iteration step $n$ new estimates of
94velocity increments $u^{n}_I$ and $v^{n}_I$ are updated by:
95\begin{equation} \label{eq:asm_dmp}
96\left\{ \begin{aligned}
97 u^{n}_I = u^{n-1}_I + \frac{1}{e_{1u} } \delta _{i+1/2} \left( {A_D
98\;\chi^{n-1}_I } \right) \\
99\\
100 v^{n}_I = v^{n-1}_I + \frac{1}{e_{2v} } \delta _{j+1/2} \left( {A_D
101\;\chi^{n-1}_I } \right) \\
102\end{aligned} \right.,
103\end{equation}
104where
105\begin{equation} \label{eq:asm_div}
106\chi^{n-1}_I = \frac{1}{e_{1t}\,e_{2t}\,e_{3t} }
107                \left( {\delta _i \left[ {e_{2u}\,e_{3u}\,u^{n-1}_I} \right]
108                       +\delta _j \left[ {e_{1v}\,e_{3v}\,v^{n-1}_I} \right]} \right).
109\end{equation}
110By the application of \eqref{eq:asm_dmp} and \eqref{eq:asm_dmp} the divergence is filtered
111in each iteration, and the vorticity is left unchanged. In the presence of coastal boundaries
112with zero velocity increments perpendicular to the coast the divergence is strongly damped.
113This type of the initialisation reduces the vertical velocity magnitude  and alleviates the
114problem of the excessive unphysical vertical mixing in the first steps of the model
115integration \citep{Talagrand_JAS72, Dobricic_al_OS07}. Diffusion coefficients are defined as
116$A_D = \alpha e_{1t} e_{2t}$, where $\alpha = 0.2$. The divergence damping is activated by
117assigning to \np{nn\_divdmp} in the \textit{nam\_asminc} namelist a value greater than zero.
118By choosing this value to be of the order of 100 the increments in the vertical velocity will
119be significantly reduced.
120
121
122%==========================================================================
123
124\section{Implementation details}
125\label{ASM_details}
126
127Here we show an example \ngn{namasm} namelist and the header of an example assimilation
128increments file on the ORCA2 grid.
129
130%------------------------------------------namasm-----------------------------------------------------
131\namdisplay{namasm}
132%-------------------------------------------------------------------------------------------------------------
133
134The header of an assimilation increments file produced using the NetCDF tool
135\mbox{\textit{ncdump~-h}} is shown below
136
137\begin{alltt}
138\tiny
139\begin{verbatim}
140netcdf assim_background_increments {
141dimensions:
142        x = 182 ;
143        y = 149 ;
144        z = 31 ;
145        t = UNLIMITED ; // (1 currently)
146variables:
147        float nav_lon(y, x) ;
148        float nav_lat(y, x) ;
149        float nav_lev(z) ;
150        double time_counter(t) ;
151        double time ;
152        double z_inc_dateb ;
153        double z_inc_datef ;
154        double bckint(t, z, y, x) ;
155        double bckins(t, z, y, x) ;
156        double bckinu(t, z, y, x) ;
157        double bckinv(t, z, y, x) ;
158        double bckineta(t, y, x) ;
159
160// global attributes:
161                :DOMAIN_number_total = 1 ;
162                :DOMAIN_number = 0 ;
163                :DOMAIN_dimensions_ids = 1, 2 ;
164                :DOMAIN_size_global = 182, 149 ;
165                :DOMAIN_size_local = 182, 149 ;
166                :DOMAIN_position_first = 1, 1 ;
167                :DOMAIN_position_last = 182, 149 ;
168                :DOMAIN_halo_size_start = 0, 0 ;
169                :DOMAIN_halo_size_end = 0, 0 ;
170                :DOMAIN_type = "BOX" ;
171}
172\end{verbatim}
173\end{alltt}
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