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1% ================================================================
2% Chapter Ñ Vertical Ocean Physics (ZDF)
3% ================================================================
4\chapter{Vertical Ocean Physics (ZDF)}
5\label{ZDF}
6\minitoc
7
8%gm% Add here a small introduction to ZDF and naming of the different physics (similar to what have been written for TRA and DYN.
9\gmcomment{Steven remark (not taken into account : problem here with turbulent vs turbulence.  I've changed "turbulent closure" to "turbulence closure", "turbulent mixing length" to "turbulence mixing length", but I've left "turbulent kinetic energy" alone - though I think it is an historical abberation!
10Gurvan :  I kept "turbulent closure etc "...}
11
12
13% ================================================================
14% Vertical Mixing
15% ================================================================
16\section{Vertical Mixing}
17\label{ZDF_zdf}
18
19The discrete form of the ocean subgrid scale physics has been presented in
20\S\ref{TRA_zdf} and \S\ref{DYN_zdf}. At the surface and bottom boundaries,
21the turbulent fluxes of momentum, heat and salt have to be defined. At the
22surface they are prescribed from the surface forcing (see Chap.~\ref{SBC}),
23while at the bottom they are set to zero for heat and salt, unless a geothermal
24flux forcing is prescribed as a bottom boundary condition ($i.e.$ \key{trabbl} 
25defined, see \S\ref{TRA_bbc}), and specified through a bottom friction
26parameterisation for momentum (see \S\ref{ZDF_bfr}).
27
28In this section we briefly discuss the various choices offered to compute
29the vertical eddy viscosity and diffusivity coefficients, $A_u^{vm}$ ,
30$A_v^{vm}$ and $A^{vT}$ ($A^{vS}$), defined at $uw$-, $vw$- and $w$-
31points, respectively (see \S\ref{TRA_zdf} and \S\ref{DYN_zdf}). These
32coefficients can be assumed to be either constant, or a function of the local
33Richardson number, or computed from a turbulent closure model (either
34TKE or KPP formulation). The computation of these coefficients is initialized
35in the \mdl{zdfini} module and performed in the \mdl{zdfric}, \mdl{zdftke} or
36\mdl{zdfkpp} modules. The trends due to the vertical momentum and tracer
37diffusion, including the surface forcing, are computed and added to the
38general trend in the \mdl{dynzdf} and \mdl{trazdf} modules, respectively.
39These trends can be computed using either a forward time stepping scheme
40(namelist parameter \np{np\_zdfexp}=true) or a backward time stepping
41scheme (\np{np\_zdfexp}=false) depending on the magnitude of the mixing
42coefficients, and thus of the formulation used (see \S\ref{DOM_nxt}).
43
44% -------------------------------------------------------------------------------------------------------------
45%        Constant
46% -------------------------------------------------------------------------------------------------------------
47\subsection{Constant (\key{zdfcst})}
48\label{ZDF_cst}
49%--------------------------------------------namzdf---------------------------------------------------------
50\namdisplay{namzdf}
51%--------------------------------------------------------------------------------------------------------------
52
53When \key{zdfcst} is defined, the momentum and tracer vertical eddy coefficients
54are set to constant values over the whole ocean. This is the crudest way to define
55the vertical ocean physics. It is recommended that this option is only used in
56process studies, not in basin scale simulations. Typical values used in this case are:
57\begin{align*} 
58A_u^{vm} = A_v^{vm} &= 1.2\ 10^{-4}~m^2.s^{-1}  \\
59\\
60A^{vT} = A^{vS} &= 1.2\ 10^{-5}~m^2.s^{-1}
61\end{align*}
62
63These values are set through the \np{avm0} and \np{avt0} namelist parameters.
64In all cases, do not use values smaller that those associated with the molecular
65viscosity and diffusivity, that is $\sim10^{-6}~m^2.s^{-1}$ for momentum,
66$\sim10^{-7}~m^2.s^{-1}$ for temperature and $\sim10^{-9}~m^2.s^{-1}$ for salinity.
67
68
69% -------------------------------------------------------------------------------------------------------------
70%        Richardson Number Dependent
71% -------------------------------------------------------------------------------------------------------------
72\subsection{Richardson Number Dependent (\key{zdfric})}
73\label{ZDF_ric}
74
75%--------------------------------------------namric---------------------------------------------------------
76\namdisplay{namric}
77%--------------------------------------------------------------------------------------------------------------
78
79When \key{zdfric} is defined, a local Richardson number dependent formulation
80for the vertical momentum and tracer eddy coefficients is set. The vertical mixing
81coefficients are diagnosed from the large scale variables computed by the model.
82\textit{In situ} measurements have been used to link vertical turbulent activity to
83large scale ocean structures. The hypothesis of a mixing mainly maintained by the
84growth of Kelvin-Helmholtz like instabilities leads to a dependency between the
85vertical eddy coefficients and the local Richardson number ($i.e.$ the
86ratio of stratification to vertical shear). Following \citet{PacPhil1981}, the following
87formulation has been implemented:
88\begin{equation} \label{Eq_zdfric}
89   \left\{      \begin{aligned}
90         A^{vT} &= \frac {A_{ric}^{vT}}{\left( 1+a \; Ri \right)^n} + A_b^{vT}       \\
91         \\
92         A^{vm} &= \frac{A^{vT}        }{\left( 1+ a \;Ri  \right)   } + A_b^{vm}
93   \end{aligned}    \right.
94\end{equation}
95where $Ri = N^2 / \left(\partial_z \textbf{U}_h \right)^2$ is the local Richardson
96number, $N$ is the local Brunt-Vais\"{a}l\"{a} frequency (see \S\ref{TRA_bn2}),
97$A_b^{vT} $ and $A_b^{vm}$ are the constant background values set as in the
98constant case (see \S\ref{ZDF_cst}), and $A_{ric}^{vT} = 10^{-4}~m^2.s^{-1}$ 
99is the maximum value that can be reached by the coefficient when $Ri\leq 0$,
100$a=5$ and $n=2$. The last three values can be modified by setting the
101\np{avmri}, \np{alp} and \np{nric} namelist parameters, respectively.
102
103% -------------------------------------------------------------------------------------------------------------
104%        TKE Turbulent Closure Scheme
105% -------------------------------------------------------------------------------------------------------------
106\subsection{TKE Turbulent Closure Scheme (\key{zdftke})}
107\label{ZDF_tke}
108
109%--------------------------------------------namtke---------------------------------------------------------
110\namdisplay{namtke}
111%--------------------------------------------------------------------------------------------------------------
112
113The vertical eddy viscosity and diffusivity coefficients are computed from a TKE
114turbulent closure model based on a prognostic equation for $\bar {e}$, the turbulent
115kinetic energy, and a closure assumption for the turbulent length scales. This
116turbulent closure model has been developed by \citet{Bougeault1989} in the
117atmospheric case, adapted by \citet{Gaspar1990} for the oceanic case, and
118embedded in OPA by \citet{Blanke1993} for equatorial Atlantic simulations. Since
119then, significant modifications have been introduced by \citet{Madec1998} in both
120the implementation and the formulation of the mixing length scale. The time
121evolution of $\bar{e}$ is the result of the production of $\bar{e}$ through vertical
122shear, its destruction through stratification, its vertical diffusion, and its dissipation
123of \citet{Kolmogorov1942} type:
124\begin{equation} \label{Eq_zdftke_e}
125\frac{\partial \bar{e}}{\partial t} =
126\frac{A^{vm}}{e_3 }\;\left[ {\left( {\frac{\partial u}{\partial k}} \right)^2
127                     +\left( {\frac{\partial v}{\partial k}} \right)^2} \right]
128-A^{vT}\,N^2
129+\frac{1}{e_3} \;\frac{\partial }{\partial k}\left[ {\frac{A^{vm}}{e_3 }
130            \;\frac{\partial \bar{e}}{\partial k}} \right]
131- c_\epsilon \;\frac{\bar {e}^{3/2}}{l_\epsilon }
132\end{equation}
133\begin{equation} \label{Eq_zdftke_kz}
134   \begin{split}
135         A^{vm} &= C_k\  l_k\  \sqrt {\bar{e}}     \\
136         A^{vT} &= A^{vm} / P_{rt}
137   \end{split}
138\end{equation}
139where $N$ is the local Brunt-Vais\"{a}l\"{a} frequency (see \S\ref{TRA_bn2}),
140$l_{\epsilon }$ and $l_{\kappa }$ are the dissipation and mixing length scales,
141$P_{rt} $ is the Prandtl number. The constants $C_k = \sqrt {2} /2$ and
142$C_\epsilon = 0.1$ are designed to deal with vertical mixing at any depth
143\citep{Gaspar1990}. They are set through namelist parameters \np{ediff} 
144and \np{ediss}. $P_{rt} $ can be set to unity or, following \citet{Blanke1993},
145be a function of the local Richardson number, $R_i $:
146\begin{align*} \label{Eq_prt}
147P_{rt} = \begin{cases}
148                    \ \ \ 1 &      \text{if $\ R_i \leq 0.2$}  \\
149                    5\,R_i &      \text{if $\ 0.2 \leq R_i \leq 2$}  \\
150                    \ \ 10 &      \text{if $\ 2 \leq R_i$} 
151            \end{cases}
152\end{align*}
153Note that a horizontal Shapiro filter can optionally be applied to $R_i$.
154However it is an obsolescent option that is not recommended. 
155The choice of $P_{rt} $ is controlled by the \np{npdl} namelist parameter.
156
157For computational efficiency, the original formulation of the turbulent length
158scales proposed by \citet{Gaspar1990} has been simplified. Four formulations
159are proposed, the choice of which is controlled by the \np{nmxl} namelist
160parameter. The first two are based on the following first order approximation
161\citep{Blanke1993}:
162\begin{equation} \label{Eq_tke_mxl0_1}
163l_k = l_\epsilon = \sqrt {2 \bar e} / N
164\end{equation}
165which is valid in a stable stratified region with constant values of the brunt-
166Vais\"{a}l\"{a} frequency. The resulting length scale is bounded by the distance
167to the surface or to the bottom (\np{nmxl}=0) or by the local vertical scale factor (\np{nmxl}=1). \citet{Blanke1993} notice that this simplification has two major
168drawbacks: it makes no sense for locally unstable stratification and the
169computation no longer uses all the information contained in the vertical density
170profile. To overcome these drawbacks, \citet{Madec1998} introduces the
171\np{nmxl}=2 or 3 cases, which add an extra assumption concerning the vertical
172gradient of the computed length scale. So, the length scales are first evaluated
173as in \eqref{Eq_tke_mxl0_1} and then bounded such that:
174\begin{equation} \label{Eq_tke_mxl_constraint}
175\frac{1}{e_3 }\left| {\frac{\partial l}{\partial k}} \right| \leq 1
176\qquad \text{with }\  l =  l_k = l_\epsilon
177\end{equation}
178\eqref{Eq_tke_mxl_constraint} means that the vertical variations of the length
179scale cannot be larger than the variations of depth. It provides a better
180approximation of the \citet{Gaspar1990} formulation while being much less
181time consuming. In particular, it allows the length scale to be limited not only
182by the distance to the surface or to the ocean bottom but also by the distance
183to a strongly stratified portion of the water column such as the thermocline
184(Fig.~\ref{Fig_mixing_length}). In order to impose the \eqref{Eq_tke_mxl_constraint} 
185constraint, we introduce two additional length scales: $l_{up}$ and $l_{dwn}$,
186the upward and downward length scales, and evaluate the dissipation and
187mixing turbulent length scales as (and note that here we use numerical
188indexing):
189%>>>>>>>>>>>>>>>>>>>>>>>>>>>>
190\begin{figure}[!t] \label{Fig_mixing_length}  \begin{center}
191\includegraphics[width=1.00\textwidth]{./TexFiles/Figures/Fig_mixing_length.pdf}
192\caption {Illustration of the mixing length computation. }
193\end{center} 
194\end{figure}
195%>>>>>>>>>>>>>>>>>>>>>>>>>>>>
196\begin{equation} \label{Eq_tke_mxl2}
197\begin{aligned}
198 l_{up\ \ }^{(k)} &= \min \left(  l^{(k)} \ , \ l_{up}^{(k+1)} + e_{3T}^{(k)}\ \ \ \;  \right)
199    \quad &\text{ from $k=1$ to $jpk$ }\ \\
200 l_{dwn}^{(k)} &= \min \left(  l^{(k)} \ , \ l_{dwn}^{(k-1)} + e_{3T}^{(k-1)}  \right)   
201    \quad &\text{ from $k=jpk$ to $1$ }\ \\
202\end{aligned}
203\end{equation}
204where $l^{(k)}$ is computed using \eqref{Eq_tke_mxl0_1},
205$i.e.$ $l^{(k)} = \sqrt {2 \bar e^{(k)} / N^{(k)} }$.
206
207In the \np{nmxl}=2 case, the dissipation and mixing length scales take the same
208value: $ l_k=  l_\epsilon = \min \left(\ l_{up} \;,\;  l_{dwn}\ \right)$, while in the
209\np{nmxl}=2 case, the dissipation and mixing length scales are give
210as in \citet{Gaspar1990}:
211\begin{equation} \label{Eq_tke_mxl_gaspar}
212\begin{aligned}
213& l_k          = \sqrt{\  l_{up} \ \ l_{dwn}\ }    \\
214& l_\epsilon = \min \left(\ l_{up} \;,\;  l_{dwn}\ \right)
215\end{aligned}
216\end{equation}
217
218At the sea surface the value of $\bar{e}$ is prescribed from the wind
219stress field: $\bar{e}=ebb\;\left| \tau \right|$ ($ebb=60$ by default)
220with a minimal threshold of $emin0=10^{-4}~m^2.s^{-2}$ (namelist
221parameters). Its value at the bottom of the ocean is assumed to be
222equal to the value of the level just above. The time integration of the
223$\bar{e}$ equation may formally lead to negative values because the
224numerical scheme does not ensure its positivity. To overcome this
225problem, a cut-off in the minimum value of $\bar{e}$ is used. Following
226\citet{Gaspar1990}, the cut-off value is set to $\sqrt{2}/2~10^{-6}~m^2.s^{-2}$.
227This allows the subsequent formulations to match that of\citet{Gargett1984} 
228for the diffusion in the thermocline and deep ocean :  $(A^{vT} = 10^{-3} / N)$.
229In addition, a cut-off is applied on $A^{vm}$ and $A^{vT}$ to avoid numerical
230instabilities associated with too weak vertical diffusion. They must be
231specified at least larger than the molecular values, and are set through
232\textit{avm0} and \textit{avt0} (\textbf{namelist} parameters).
233
234% -------------------------------------------------------------------------------------------------------------
235%        GLS Generic Length Scale Scheme
236% -------------------------------------------------------------------------------------------------------------
237\subsection{GLS Generic Length Scale (\key{zdfgls})}
238\label{ZDF_gls}
239
240%--------------------------------------------namgls---------------------------------------------------------
241\namdisplay{namgls}
242%--------------------------------------------------------------------------------------------------------------
243
244The model allows to resolve two prognostic equations for turbulent
245kinetic energy $\bar {e}$ and a generic length scale \citep{Umlauf_Burchard_2003}. Thanks to the latter, commonly
246used closures can be retrieved: $k-kl$ \citep{Mellor_Yamada_1982}, $k-{\epsilon }$ \citep{Rodi_1987} and $k-{\omega }$ 
247\citep{Wilcox_1988}. These equations could be written in a generic form with the incorporation
248of a new variable : ${\psi} = (C^{0}_{\mu})^{p} \ {\bar{e}}^{m} \ l^{n}$.
249
250\begin{equation} \label{Eq_zdfgls_e}
251\frac{\partial \bar{e}}{\partial t} =
252\frac{A^{vm}}{{\sigma_e} {e_3} }\;\left[ {\left( {\frac{\partial u}{\partial k}} \right)^2
253                                                        +\left( {\frac{\partial v}{\partial k}} \right)^2} \right]
254-A^{vT}\,N^2
255+\frac{1}{e_3}  \;\frac{\partial }{\partial k}\left[ {\frac{A^{vm}}{e_3 }
256                                \;\frac{\partial \bar{e}}{\partial k}} \right]
257- \epsilon \;
258\end{equation}
259
260\begin{equation} \label{Eq_zdfgls_psi}
261\frac{\partial \psi}{\partial t} = \frac{\psi}{\bar{e}} 
262(\frac{{C_1}A^{vm}}{{\sigma_{\psi}} {e_3} }\;\left[ {\left( {\frac{\partial u}{\partial k}} \right)^2
263                                                        +\left( {\frac{\partial v}{\partial k}} \right)^2} \right]
264-{C_3}A^{vT}\,N^2- C_2{\epsilon}Fw)
265+\frac{1}{e_3}  \;\frac{\partial }{\partial k}\left[ {\frac{A^{vm}}{e_3 }
266                                \;\frac{\partial \psi}{\partial k}} \right]\;
267\end{equation}
268
269\begin{equation} \label{Eq_zdfgls_kz}
270   \begin{split}
271         A^{vm} &= C_{\mu} \ \sqrt {\bar{e}} \ l         \\
272         A^{vT} &= C_{\mu'}\ \sqrt {\bar{e}} \ l
273   \end{split}
274\end{equation}
275
276\begin{equation} \label{Eq_zdfgls_eps}
277{\epsilon} = (C^{0}_{\mu}) \frac{\bar {e}^{3/2}}{l} \;
278\end{equation}
279where $N$ is the local Brunt-Vais\"{a}l\"{a} frequency (see \S\ref{TRA_bn2}) and $\epsilon$ the dissipation rate.
280In function of the parameters k, m and n, common turbulent closure could be retrieved.
281The constants C1, C2, C3, ${\sigma_e}$, ${\sigma_{\psi}}$ and the wall function (Fw) depends of the choice of the turbulence model.
282%>>>>>>>>>>>>>>>>>>>>>>>>>>>>
283\begin{figure}[!h]
284\centering
285\includegraphics[scale=0.7]{./TexFiles/Figures/tabgls.png}
286\caption {Values of the parameters in function of the model of turbulence.}
287\label{tabgls}
288\end{figure}
289%>>>>>>>>>>>>>>>>>>>>>>>>>>>>
290
291About the Mellor-Yamada model, the negativity of n allows to use a wall function to force
292the convergence of the mixing length towards Kzb (K: Kappa and zb: rugosity length) value
293near physical boundaries (logarithmic boundary layer law). $C_{\mu}$ and $C_{\mu'}$ are calculated from stability functions
294of \citet{Galperin_1988}, \citet{Kantha_Clayson_1994} or \citet{Canuto_2001}.
295$C^{0}_{\mu}$ depends of the choice of the stability function.
296
297The boundary condition at the surface and the bottom could be calculated thanks to Diriclet or Neumann condition.
298The wave effect on the mixing could be also being considered \citep{Craig_Banner_1994}.
299
300-------------------------------------------------------------------------------------------------------------
301%        K Profile Parametrisation (KPP)
302% -------------------------------------------------------------------------------------------------------------
303\subsection{K Profile Parametrisation (KPP) (\key{zdfkpp}) }
304\label{ZDF_kpp}
305
306%--------------------------------------------namkpp--------------------------------------------------------
307\namdisplay{namkpp}
308%--------------------------------------------------------------------------------------------------------------
309
310The K-Profile Parametrization (KKP) developed by \cite{Large_al_RG94} has been
311implemented in \NEMO by J. Chanut (PhD reference to be added here!).
312
313\colorbox{yellow}{Add a description of KPP here.}
314
315
316% ================================================================
317% Convection
318% ================================================================
319\section{Convection}
320\label{ZDF_conv}
321
322%--------------------------------------------namzdf--------------------------------------------------------
323\namdisplay{namzdf}
324%--------------------------------------------------------------------------------------------------------------
325
326Static instabilities (i.e. light potential densities under heavy ones) may
327occur at particular ocean grid points. In nature, convective processes
328quickly re-establish the static stability of the water column. These
329processes have been removed from the model via the hydrostatic
330assumption so they must be parameterized. Three parameterisations
331are available to deal with convective processes: a non-penetrative
332convective adjustment or an enhanced vertical diffusion, or/and the
333use of a turbulent closure scheme.
334
335% -------------------------------------------------------------------------------------------------------------
336%       Non-Penetrative Convective Adjustment
337% -------------------------------------------------------------------------------------------------------------
338\subsection   [Non-Penetrative Convective Adjustment (\np{ln\_tranpc}) ]
339         {Non-Penetrative Convective Adjustment (\np{ln\_tranpc}=.true.) }
340\label{ZDF_npc}
341
342%--------------------------------------------namnpc--------------------------------------------------------
343\namdisplay{namnpc}
344%--------------------------------------------------------------------------------------------------------------
345
346
347%>>>>>>>>>>>>>>>>>>>>>>>>>>>>
348\begin{figure}[!htb] \label{Fig_npc}   \begin{center}
349\includegraphics[width=0.90\textwidth]{./TexFiles/Figures/Fig_npc.pdf}
350\caption {Example of an unstable density profile treated by the non penetrative
351convective adjustment algorithm. $1^{st}$ step: the initial profile is checked from
352the surface to the bottom. It is found to be unstable between levels 3 and 4.
353They are mixed. The resulting $\rho$ is still larger than $\rho$(5): levels 3 to 5
354are mixed. The resulting $\rho$ is still larger than $\rho$(6): levels 3 to 6 are
355mixed. The $1^{st}$ step ends since the density profile is then stable below
356the level 3. $2^{nd}$ step: the new $\rho$ profile is checked following the same
357procedure as in $1^{st}$ step: levels 2 to 5 are mixed. The new density profile
358is checked. It is found stable: end of algorithm.}
359\end{center}   \end{figure}
360%>>>>>>>>>>>>>>>>>>>>>>>>>>>>
361
362The non-penetrative convective adjustment is used when \np{ln\_zdfnpc}=true.
363It is applied at each \np{nnpc1} time step and mixes downwards instantaneously
364the statically unstable portion of the water column, but only until the density
365structure becomes neutrally stable ($i.e.$ until the mixed portion of the water
366column has \textit{exactly} the density of the water just below) \citep{Madec1991a}.
367The associated algorithm is an iterative process used in the following way
368(Fig. \ref{Fig_npc}): starting from the top of the ocean, the first instability is
369found. Assume in the following that the instability is located between levels
370$k$ and $k+1$. The potential temperature and salinity in the two levels are
371vertically mixed, conserving the heat and salt contents of the water column.
372The new density is then computed by a linear approximation. If the new
373density profile is still unstable between levels $k+1$ and $k+2$, levels $k$,
374$k+1$ and $k+2$ are then mixed. This process is repeated until stability is
375established below the level $k$ (the mixing process can go down to the
376ocean bottom). The algorithm is repeated to check if the density profile
377between level $k-1$ and $k$ is unstable and/or if there is no deeper instability.
378
379This algorithm is significantly different from mixing statically unstable levels
380two by two. The latter procedure cannot converge with a finite number
381of iterations for some vertical profiles while the algorithm used in \NEMO 
382converges for any profile in a number of iterations which is less than the
383number of vertical levels. This property is of paramount importance as
384pointed out by \citet{Killworth1989}: it avoids the existence of permanent
385and unrealistic static instabilities at the sea surface. This non-penetrative
386convective algorithm has been proved successful in studies of the deep
387water formation in the north-western Mediterranean Sea
388\citep{Madec1991a, Madec1991b, Madec1991c}.
389
390Note that in the current implementation of this algorithm presents several
391limitations. First, potential density referenced to the sea surface is used to
392check whether the density profile is stable or not. This is a strong
393simplification which leads to large errors for realistic ocean simulations.
394Indeed, many water masses of the world ocean, especially Antarctic Bottom
395Water, are unstable when represented in surface-referenced potential density.
396The scheme will erroneously mix them up. Second, the mixing of potential
397density is assumed to be linear. This assures the convergence of the algorithm
398even when the equation of state is non-linear. Small static instabilities can thus
399persist due to cabbeling: they will be treated at the next time step.
400Third, temperature and salinity, and thus density, are mixed, but the
401corresponding velocity fields remain unchanged. When using a Richardson
402Number dependent eddy viscosity, the mixing of momentum is done through
403the vertical diffusion: after a static adjustment, the Richardson Number is zero
404and thus the eddy viscosity coefficient is at a maximum. When this convective
405adjustment algorithm is used with constant vertical eddy viscosity, spurious
406solutions can occur since the vertical momentum diffusion remains small even
407after a static adjustment. In that case, we recommend the addition of momentum
408mixing in a manner that mimics the mixing in temperature and salinity
409\citep{Speich1992, Speich1996}.
410
411% -------------------------------------------------------------------------------------------------------------
412%       Enhanced Vertical Diffusion
413% -------------------------------------------------------------------------------------------------------------
414\subsection   [Enhanced Vertical Diffusion (\np{ln\_zdfevd})]
415         {Enhanced Vertical Diffusion (\np{ln\_zdfevd}=.true.)}
416\label{ZDF_evd}
417
418%--------------------------------------------namzdf--------------------------------------------------------
419\namdisplay{namzdf}
420%--------------------------------------------------------------------------------------------------------------
421
422The enhanced vertical diffusion parameterisation is used when \np{ln\_zdfevd}=true.
423In this case, the vertical eddy mixing coefficients are assigned very large values
424(a typical value is $10\;m^2s^{-1})$ in regions where the stratification is unstable
425($i.e.$ when the Brunt-Vais\"{a}l\"{a} frequency is negative) \citep{Lazar1997, Lazar1999}.
426This is done either on tracers only (\np{n\_evdm}=0) or on both momentum and
427tracers (\np{n\_evdm}=1).
428
429In practice, where $N^2\leq 10^{-12}$, $A_T^{vT}$ and $A_T^{vS}$, and
430if \np{n\_evdm}=1, the four neighbouring $A_u^{vm} \;\mbox{and}\;A_v^{vm}$ 
431values also, are set equal to the namelist parameter \np{avevd}. A typical value
432for $avevd$ is between 1 and $100~m^2.s^{-1}$. This parameterisation of
433convective processes is less time consuming than the convective adjustment
434algorithm presented above when mixing both tracers and momentum in the
435case of static instabilities. It requires the use of an implicit time stepping on
436vertical diffusion terms (i.e. \np{ln\_zdfexp}=false).
437
438% -------------------------------------------------------------------------------------------------------------
439%       Turbulent Closure Scheme
440% -------------------------------------------------------------------------------------------------------------
441\subsection{Turbulent Closure Scheme (\key{zdftke})}
442\label{ZDF_tcs}
443
444The TKE turbulent closure scheme presented in \S\ref{ZDF_tke} and used
445when the \key{zdftke} is defined, in theory solves the problem of statically
446unstable density profiles. In such a case, the term corresponding to the
447destruction of turbulent kinetic energy through stratification in \eqref{Eq_zdftke_e} 
448becomes a source term, since $N^2$ is negative. It results in large values of
449$A_T^{vT}$ and  $A_T^{vT}$, and also the four neighbouring
450$A_u^{vm} {and}\;A_v^{vm}$ (up to $1\;m^2s^{-1})$. These large values
451restore the static stability of the water column in a way similar to that of the
452enhanced vertical diffusion parameterisation (\S\ref{ZDF_evd}). However,
453in the vicinity of the sea surface (first ocean layer), the eddy coefficients
454computed by the turbulent closure scheme do not usually exceed $10^{-2}m.s^{-1}$,
455because the mixing length scale is bounded by the distance to the sea surface
456(see \S\ref{ZDF_tke}). It can thus be useful to combine the enhanced vertical
457diffusion with the turbulent closure scheme, $i.e.$ setting the \np{ln\_zdfnpc} 
458namelist parameter to true and defining the \key{zdftke} CPP key all together.
459
460The KPP turbulent closure scheme already includes enhanced vertical diffusion
461in the case of convection, as governed by the variables $bvsqcon$ and $difcon$ 
462found in \mdl{zdfkpp}, therefore \np{np\_zdfevd} should not be used with the KPP
463scheme. %gm%  + one word on non local flux with KPP scheme trakpp.F90 module...
464
465% ================================================================
466% Double Diffusion Mixing
467% ================================================================
468\section  [Double Diffusion Mixing (\textit{zdfddm} - \key{zdfddm})]
469      {Double Diffusion Mixing (\mdl{zdfddm} module - \key{zdfddm})}
470\label{ZDF_ddm}
471
472%-------------------------------------------namddm--------------------------------------------------------
473\namdisplay{namddm}
474%--------------------------------------------------------------------------------------------------------------
475
476Double diffusion occurs when relatively warm, salty water overlies cooler, fresher
477water, or vice versa. The former condition leads to salt fingering and the latter
478to diffusive convection. Double-diffusive phenomena contribute to diapycnal
479mixing in extensive regions of the ocean.  \citet{Merryfield1999} include a
480parameterisation of such phenomena in a global ocean model and show that
481it leads to relatively minor changes in circulation but exerts significant regional
482influences on temperature and salinity.
483
484Diapycnal mixing of S and T are described by diapycnal diffusion coefficients
485\begin{align*} % \label{Eq_zdfddm_Kz}
486    &A^{vT} = A_o^{vT}+A_f^{vT}+A_d^{vT}  \\
487    &A^{vS} = A_o^{vS}+A_f^{vS}+A_d^{vS}
488\end{align*}
489where subscript $f$ represents mixing by salt fingering, $d$ by diffusive convection,
490and $o$ by processes other than double diffusion. The rates of double-diffusive mixing
491depend on the buoyancy ratio $R_\rho = \alpha \partial_z T / \beta \partial_z S$,
492where $\alpha$ and $\beta$ are coefficients of thermal expansion and saline
493contraction (see \S\ref{TRA_eos}). To represent mixing of $S$ and $T$ by salt
494fingering, we adopt the diapycnal diffusivities suggested by Schmitt (1981):
495\begin{align} \label{Eq_zdfddm_f}
496A_f^{vS} &=    \begin{cases}
497   \frac{A^{\ast v}}{1+(R_\rho / R_c)^n   } &\text{if  $R_\rho > 1$ and $N^2>0$ } \\
498   0                              &\text{otherwise} 
499            \end{cases}   
500\\           \label{Eq_zdfddm_f_T}
501A_f^{vT} &= 0.7 \ A_f^{vS} / R_\rho 
502\end{align}
503
504%>>>>>>>>>>>>>>>>>>>>>>>>>>>>
505\begin{figure}[!t] \label{Fig_zdfddm}  \begin{center}
506\includegraphics[width=0.99\textwidth]{./TexFiles/Figures/Fig_zdfddm.pdf}
507\caption {From \citet{Merryfield1999} : (a) Diapycnal diffusivities $A_f^{vT}$ 
508and $A_f^{vS}$ for temperature and salt in regions of salt fingering. Heavy
509curves denote $A^{\ast v} = 10^{-3}~m^2.s^{-1}$ and thin curves
510$A^{\ast v} = 10^{-4}~m^2.s^{-1}$ ; (b) diapycnal diffusivities $A_d^{vT}$ and
511$A_d^{vS}$ for temperature and salt in regions of diffusive convection. Heavy
512curves denote the Federov parameterisation and thin curves the Kelley
513parameterisation. The latter is not implemented in \NEMO. }
514\end{center}    \end{figure}
515%>>>>>>>>>>>>>>>>>>>>>>>>>>>>
516
517The factor 0.7 in \eqref{Eq_zdfddm_f_T} reflects the measured ratio
518$\alpha F_T /\beta F_S \approx  0.7$ of buoyancy flux of heat to buoyancy
519flux of salt ($e.g.$, \citet{McDougall_Taylor_JMR84}). Following  \citet{Merryfield1999},
520we adopt $R_c = 1.6$, $n = 6$, and $A^{\ast v} = 10^{-4}~m^2.s^{-1}$.
521
522To represent mixing of S and T by diffusive layering,  the diapycnal diffusivities suggested
523by Federov (1988) is used:
524\begin{align}  \label{Eq_zdfddm_d}
525A_d^{vT} &=    \begin{cases}
526   1.3635 \, \exp{\left( 4.6\, \exp{ \left[  -0.54\,( R_{\rho}^{-1} - 1 )  \right] }    \right)}
527                           &\text{if  $0<R_\rho < 1$ and $N^2>0$ } \\
528   0                       &\text{otherwise} 
529            \end{cases}   
530\\          \label{Eq_zdfddm_d_S}
531A_d^{vS} &=    \begin{cases}
532   A_d^{vT}\ \left( 1.85\,R_{\rho} - 0.85 \right)
533                           &\text{if  $0.5 \leq R_\rho<1$ and $N^2>0$ } \\
534   A_d^{vT} \ 0.15 \ R_\rho
535                           &\text{if  $\ \ 0 < R_\rho<0.5$ and $N^2>0$ } \\
536   0                       &\text{otherwise} 
537            \end{cases}   
538\end{align}
539
540The dependencies of \eqref{Eq_zdfddm_f} to \eqref{Eq_zdfddm_d_S} on $R_\rho$ 
541are illustrated in Fig.~\ref{Fig_zdfddm}. Implementing this requires computing
542$R_\rho$ at each grid point on every time step. This is done in \mdl{eosbn2} at the
543same time as $N^2$ is computed. This avoids duplication in the computation of
544$\alpha$ and $\beta$ (which is usually quite expensive).
545
546% ================================================================
547% Bottom Friction
548% ================================================================
549\section  [Bottom Friction (\textit{zdfbfr})]
550      {Bottom Friction (\mdl{zdfbfr} module)}
551\label{ZDF_bfr}
552
553%--------------------------------------------nambfr--------------------------------------------------------
554\namdisplay{nambfr}
555%--------------------------------------------------------------------------------------------------------------
556
557Both the surface momentum flux (wind stress) and the bottom momentum
558flux (bottom friction) enter the equations as a condition on the vertical
559diffusive flux. For the bottom boundary layer, one has:
560\begin{equation} \label{Eq_zdfbfr_flux}
561A^{vm} \left( \partial \textbf{U}_h / \partial z \right) = \textbf{F}_h
562\end{equation}
563where $\textbf{F}_h$ is supposed to represent the horizontal momentum flux
564outside the logarithmic turbulent boundary layer (thickness of the order of
5651~m in the ocean). How $\textbf{F}_h$ influences the interior depends on the
566vertical resolution of the model near the bottom relative to the Ekman layer
567depth. For example, in order to obtain an Ekman layer depth
568$d = \sqrt{2\;A^{vm}} / f = 50$~m, one needs a vertical diffusion coefficient
569$A^{vm} = 0.125$~m$^2$s$^{-1}$ (for a Coriolis frequency
570$f = 10^{-4}$~m$^2$s$^{-1}$). With a background diffusion coefficient
571$A^{vm} = 10^{-4}$~m$^2$s$^{-1}$, the Ekman layer depth is only 1.4~m.
572When the vertical mixing coefficient is this small, using a flux condition is
573equivalent to entering the viscous forces (either wind stress or bottom friction)
574as a body force over the depth of the top or bottom model layer. To illustrate
575this, consider the equation for $u$ at $k$, the last ocean level:
576\begin{equation} \label{Eq_zdfbfr_flux2}
577\frac{\partial u \; (k)}{\partial t} = \frac{1}{e_{3u}} \left[ A^{vm} \; (k) \frac{U \; (k-1) - U \; (k)}{e_{3uw} \; (k-1)} - F_u \right] \approx - \frac{F_u}{e_{3u}}
578\end{equation}
579For example, if the bottom layer thickness is 200~m, the Ekman transport will
580be distributed over that depth. On the other hand, if the vertical resolution
581is high (1~m or less) and a turbulent closure model is used, the turbulent
582Ekman layer will be represented explicitly by the model. However, the
583logarithmic layer is never represented in current primitive equation model
584applications: it is \emph{necessary} to parameterize the flux $\textbf{F}_h $.
585Two choices are available in \NEMO: a linear and a quadratic bottom friction.
586Note that in both cases, the rotation between the interior velocity and the
587bottom friction is neglected in the present release of \NEMO.
588
589% -------------------------------------------------------------------------------------------------------------
590%       Linear Bottom Friction
591% -------------------------------------------------------------------------------------------------------------
592\subsection{Linear Bottom Friction (\np{nbotfr} = 1) }
593\label{ZDF_bfr_linear}
594
595The linear bottom friction parameterisation assumes that the bottom friction
596is proportional to the interior velocity (i.e. the velocity of the last model level):
597\begin{equation} \label{Eq_zdfbfr_linear}
598\textbf{F}_h = \frac{A^{vm}}{e_3} \; \frac{\partial \textbf{U}_h}{\partial k} = r \; \textbf{U}_h^b
599\end{equation}
600where $\textbf{U}_h^b$ is the horizontal velocity vector of the bottom ocean
601layer and $r$ is a friction coefficient expressed in m.s$^{-1}$. This coefficient
602is generally estimated by setting a typical decay time $\tau$ in the deep ocean,
603and setting $r = H / \tau$, where $H$ is the ocean depth. Commonly accepted
604values of $\tau$ are of the order of 100 to 200 days \citep{Weatherly1984}.
605A value $\tau^{-1} = 10^{-7}$~s$^{-1}$ equivalent to 115 days, is usually used
606in quasi-geostrophic models. One may consider the linear friction as an
607approximation of quadratic friction, $r \approx 2\;C_D\;U_{av}$ (\citet{Gill1982},
608Eq. 9.6.6). For example, with a drag coefficient $C_D = 0.002$, a typical speed
609of tidal currents of $U_{av} =0.1$~m.s$^{-1}$, and assuming an ocean depth
610$H = 4000$~m, the resulting friction coefficient is $r = 4\;10^{-4}$~m.s$^{-1}$.
611This is the default value used in \NEMO. It corresponds to a decay time scale
612of 115~days. It can be changed by specifying \np{bfric1} (namelist parameter).
613
614In the code, the bottom friction is imposed by updating the value of the
615vertical eddy coefficient at the bottom level. Indeed, the discrete formulation
616of (\ref{Eq_zdfbfr_linear}) at the last ocean $T-$level, using the fact that
617$\textbf {U}_h =0$ below the ocean floor, leads to
618\begin{equation} \label{Eq_zdfbfr_linKz}
619\begin{split}
620A_u^{vm} &= r\;e_{3uw}\\
621A_v^{vm} &= r\;e_{3vw}\\
622\end{split}
623\end{equation}
624
625This update is done in \mdl{zdfbfr} when \np{nbotfr}=1. The value of $r$ 
626used is \np{bfric1}. Setting \np{nbotfr}=3 is equivalent to setting $r=0$ and
627leads to a free-slip bottom boundary condition. Setting \np{nbotfr}=0 sets
628$r=2\;A_{vb}^{\rm {\bf U}} $, where $A_{vb}^{\rm {\bf U}} $ is the background
629vertical eddy coefficient, and a no-slip boundary condition is imposed.
630Note that this latter choice generally leads to an underestimation of the
631bottom friction: for example with a deepest level thickness of $200~m$ 
632and $A_{vb}^{\rm {\bf U}} =10^{-4}$m$^2$.s$^{-1}$, the friction coefficient
633is only $r=10^{-6}$m.s$^{-1}$.
634
635% -------------------------------------------------------------------------------------------------------------
636%       Non-Linear Bottom Friction
637% -------------------------------------------------------------------------------------------------------------
638\subsection{Non-Linear Bottom Friction (\np{nbotfr} = 2)}
639\label{ZDF_bfr_nonlinear}
640
641The non-linear bottom friction parameterisation assumes that the bottom
642friction is quadratic:
643\begin{equation} \label{Eq_zdfbfr_nonlinear}
644\textbf {F}_h = \frac{A^{vm}}{e_3 }\frac{\partial \textbf {U}_h
645}{\partial k}=C_D \;\sqrt {u_b ^2+v_b ^2+e_b } \;\; \textbf {U}_h^b
646\end{equation}
647
648with $\textbf{U}_h^b = (u_b\;,\;v_b)$ the horizontal interior velocity ($i.e.$ 
649the horizontal velocity of the bottom ocean layer), $C_D$ a drag coefficient,
650and $e_b $ a bottom turbulent kinetic energy due to tides, internal waves
651breaking and other short time scale currents. A typical value of the drag
652coefficient is $C_D = 10^{-3} $. As an example, the CME experiment
653\citep{Treguier1992} uses $C_D = 10^{-3}$ and $e_b = 2.5\;10^{-3}$m$^2$.s$^{-2}$,
654while the FRAM experiment \citep{Killworth1992} uses $e_b =0$ 
655and $e_b =2.5\;\;10^{-3}$m$^2$.s$^{-2}$. The FRAM choices have been
656set as default values (\np{bfric2} and \np{bfeb2} namelist parameters).
657
658As for the linear case, the bottom friction is imposed in the code by
659updating the value of the vertical eddy coefficient at the bottom level:
660\begin{equation} \label{Eq_zdfbfr_nonlinKz}
661\begin{split}
662A_u^{vm} &=C_D\; e_{3uw} \left[ u^2 + \left(\bar{\bar{v}}^{i+1,j}\right)^2 + e_b \right]^
663{1/2}\\
664A_v^{vm} &=C_D\; e_{3uw} \left[  \left(\bar{\bar{u}}^{i,j+1}\right)^2 + v^2 + e_b \right]^{1/2}\\
665\end{split}
666\end{equation}
667
668This update is done in \mdl{zdfbfr}. The coefficients that control the strength of the
669non-linear bottom friction are initialized as namelist parameters: $C_D$= \np{bfri2},
670and $e_b$ =\np{bfeb2}.
671
672% ================================================================
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