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3%% Custom aliases
4\newcommand{\cf}{\ensuremath{C\kern-0.14em f}}
8\chapter{Vertical Ocean Physics (ZDF)}
15\paragraph{Changes record} ~\\
18  \begin{tabularx}{\textwidth}{l||X|X}
19    Release & Author(s) & Modifications \\
20    \hline
21    {\em   4.0} & {\em ...} & {\em ...} \\
22    {\em   3.6} & {\em ...} & {\em ...} \\
23    {\em   3.4} & {\em ...} & {\em ...} \\
24    {\em <=3.4} & {\em ...} & {\em ...}
25  \end{tabularx}
30%gm% Add here a small introduction to ZDF and naming of the different physics (similar to what have been written for TRA and DYN.
32%% =================================================================================================
33\section{Vertical mixing}
36The discrete form of the ocean subgrid scale physics has been presented in
37\autoref{sec:TRA_zdf} and \autoref{sec:DYN_zdf}.
38At the surface and bottom boundaries, the turbulent fluxes of momentum, heat and salt have to be defined.
39At the surface they are prescribed from the surface forcing (see \autoref{chap:SBC}),
40while at the bottom they are set to zero for heat and salt,
41unless a geothermal flux forcing is prescribed as a bottom boundary condition (\ie\ \np{ln_trabbc}{ln\_trabbc} defined,
42see \autoref{subsec:TRA_bbc}), and specified through a bottom friction parameterisation for momentum
43(see \autoref{sec:ZDF_drg}).
45In this section we briefly discuss the various choices offered to compute the vertical eddy viscosity and
46diffusivity coefficients, $A_u^{vm}$ , $A_v^{vm}$ and $A^{vT}$ ($A^{vS}$), defined at $uw$-, $vw$- and $w$- points,
47respectively (see \autoref{sec:TRA_zdf} and \autoref{sec:DYN_zdf}).
48These coefficients can be assumed to be either constant, or a function of the local Richardson number,
49or computed from a turbulent closure model (either TKE or GLS or OSMOSIS formulation).
50The computation of these coefficients is initialized in the \mdl{zdfphy} module and performed in
51the \mdl{zdfric}, \mdl{zdftke} or \mdl{zdfgls} or \mdl{zdfosm} modules.
52The trends due to the vertical momentum and tracer diffusion, including the surface forcing,
53are computed and added to the general trend in the \mdl{dynzdf} and \mdl{trazdf} modules, respectively.
54%These trends can be computed using either a forward time stepping scheme
55%(namelist parameter \np[=.true.]{ln_zdfexp}{ln\_zdfexp}) or a backward time stepping scheme
56%(\np[=.false.]{ln_zdfexp}{ln\_zdfexp}) depending on the magnitude of the mixing coefficients,
57%and thus of the formulation used (see \autoref{chap:TD}).
60  \nlst{namzdf}
61  \caption{\forcode{&namzdf}}
62  \label{lst:namzdf}
65%% =================================================================================================
66\subsection[Constant (\forcode{ln_zdfcst})]{Constant (\protect\np{ln_zdfcst}{ln\_zdfcst})}
69Options are defined through the \nam{zdf}{zdf} namelist variables.
70When \np{ln_zdfcst}{ln\_zdfcst} is defined, the momentum and tracer vertical eddy coefficients are set to
71constant values over the whole ocean.
72This is the crudest way to define the vertical ocean physics.
73It is recommended to use this option only in process studies, not in basin scale simulations.
74Typical values used in this case are:
76  A_u^{vm} = A_v^{vm} &= 1.2\ 10^{-4}~m^2.s^{-1}   \\
77  A^{vT} = A^{vS} &= 1.2\ 10^{-5}~m^2.s^{-1}
80These values are set through the \np{rn_avm0}{rn\_avm0} and \np{rn_avt0}{rn\_avt0} namelist parameters.
81In all cases, do not use values smaller that those associated with the molecular viscosity and diffusivity,
82that is $\sim10^{-6}~m^2.s^{-1}$ for momentum, $\sim10^{-7}~m^2.s^{-1}$ for temperature and
83$\sim10^{-9}~m^2.s^{-1}$ for salinity.
85%% =================================================================================================
86\subsection[Richardson number dependent (\forcode{ln_zdfric})]{Richardson number dependent (\protect\np{ln_zdfric}{ln\_zdfric})}
90  \nlst{namzdf_ric}
91  \caption{\forcode{&namzdf_ric}}
92  \label{lst:namzdf_ric}
95When \np[=.true.]{ln_zdfric}{ln\_zdfric}, a local Richardson number dependent formulation for the vertical momentum and
96tracer eddy coefficients is set through the \nam{zdf_ric}{zdf\_ric} namelist variables.
97The vertical mixing coefficients are diagnosed from the large scale variables computed by the model.
98\textit{In situ} measurements have been used to link vertical turbulent activity to large scale ocean structures.
99The hypothesis of a mixing mainly maintained by the growth of Kelvin-Helmholtz like instabilities leads to
100a dependency between the vertical eddy coefficients and the local Richardson number
101(\ie\ the ratio of stratification to vertical shear).
102Following \citet{pacanowski.philander_JPO81}, the following formulation has been implemented:
104  % \label{eq:ZDF_ric}
105  \left\{
106    \begin{aligned}
107      A^{vT} &= \frac {A_{ric}^{vT}}{\left( 1+a \; Ri \right)^n} + A_b^{vT}       \\
108      A^{vm} &= \frac{A^{vT}        }{\left( 1+ a \;Ri  \right)   } + A_b^{vm}
109    \end{aligned}
110  \right.
112where $Ri = N^2 / \left(\partial_z \textbf{U}_h \right)^2$ is the local Richardson number,
113$N$ is the local Brunt-Vais\"{a}l\"{a} frequency (see \autoref{subsec:TRA_bn2}),
114$A_b^{vT} $ and $A_b^{vm}$ are the constant background values set as in the constant case
115(see \autoref{subsec:ZDF_cst}), and $A_{ric}^{vT} = 10^{-4}~m^2.s^{-1}$ is the maximum value that
116can be reached by the coefficient when $Ri\leq 0$, $a=5$ and $n=2$.
117The last three values can be modified by setting the \np{rn_avmri}{rn\_avmri}, \np{rn_alp}{rn\_alp} and
118\np{nn_ric}{nn\_ric} namelist parameters, respectively.
120A simple mixing-layer model to transfer and dissipate the atmospheric forcings
121(wind-stress and buoyancy fluxes) can be activated setting the \np[=.true.]{ln_mldw}{ln\_mldw} in the namelist.
123In this case, the local depth of turbulent wind-mixing or "Ekman depth" $h_{e}(x,y,t)$ is evaluated and
124the vertical eddy coefficients prescribed within this layer.
126This depth is assumed proportional to the "depth of frictional influence" that is limited by rotation:
128  h_{e} = Ek \frac {u^{*}} {f_{0}}
130where, $Ek$ is an empirical parameter, $u^{*}$ is the friction velocity and $f_{0}$ is the Coriolis parameter.
132In this similarity height relationship, the turbulent friction velocity:
134  u^{*} = \sqrt \frac {|\tau|} {\rho_o}
136is computed from the wind stress vector $|\tau|$ and the reference density $ \rho_o$.
137The final $h_{e}$ is further constrained by the adjustable bounds \np{rn_mldmin}{rn\_mldmin} and \np{rn_mldmax}{rn\_mldmax}.
138Once $h_{e}$ is computed, the vertical eddy coefficients within $h_{e}$ are set to
139the empirical values \np{rn_wtmix}{rn\_wtmix} and \np{rn_wvmix}{rn\_wvmix} \citep{lermusiaux_JMS01}.
141%% =================================================================================================
142\subsection[TKE turbulent closure scheme (\forcode{ln_zdftke})]{TKE turbulent closure scheme (\protect\np{ln_zdftke}{ln\_zdftke})}
146  \nlst{namzdf_tke}
147  \caption{\forcode{&namzdf_tke}}
148  \label{lst:namzdf_tke}
151The vertical eddy viscosity and diffusivity coefficients are computed from a TKE turbulent closure model based on
152a prognostic equation for $\bar{e}$, the turbulent kinetic energy,
153and a closure assumption for the turbulent length scales.
154This turbulent closure model has been developed by \citet{bougeault.lacarrere_MWR89} in the atmospheric case,
155adapted by \citet{gaspar.gregoris.ea_JGR90} for the oceanic case, and embedded in OPA, the ancestor of \NEMO,
156by \citet{blanke.delecluse_JPO93} for equatorial Atlantic simulations.
157Since then, significant modifications have been introduced by \citet{madec.delecluse.ea_NPM98} in both the implementation and
158the formulation of the mixing length scale.
159The time evolution of $\bar{e}$ is the result of the production of $\bar{e}$ through vertical shear,
160its destruction through stratification, its vertical diffusion, and its dissipation of \citet{kolmogorov_IANS42} type:
162  \label{eq:ZDF_tke_e}
163  \frac{\partial \bar{e}}{\partial t} =
164  \frac{K_m}{{e_3}^2 }\;\left[ {\left( {\frac{\partial u}{\partial k}} \right)^2
165      +\left( {\frac{\partial v}{\partial k}} \right)^2} \right]
166  -K_\rho\,N^2
167  +\frac{1}{e_3}  \;\frac{\partial }{\partial k}\left[ {\frac{A^{vm}}{e_3 }
168      \;\frac{\partial \bar{e}}{\partial k}} \right]
169  - c_\epsilon \;\frac{\bar {e}^{3/2}}{l_\epsilon }
172  % \label{eq:ZDF_tke_kz}
173  \begin{split}
174    K_m &= C_k\  l_k\  \sqrt {\bar{e}\; }    \\
175    K_\rho &= A^{vm} / P_{rt}
176  \end{split}
178where $N$ is the local Brunt-Vais\"{a}l\"{a} frequency (see \autoref{subsec:TRA_bn2}),
179$l_{\epsilon }$ and $l_{\kappa }$ are the dissipation and mixing length scales,
180$P_{rt}$ is the Prandtl number, $K_m$ and $K_\rho$ are the vertical eddy viscosity and diffusivity coefficients.
181The constants $C_k =  0.1$ and $C_\epsilon = \sqrt {2} /2$ $\approx 0.7$ are designed to deal with
182vertical mixing at any depth \citep{gaspar.gregoris.ea_JGR90}.
183They are set through namelist parameters \np{nn_ediff}{nn\_ediff} and \np{nn_ediss}{nn\_ediss}.
184$P_{rt}$ can be set to unity or, following \citet{blanke.delecluse_JPO93}, be a function of the local Richardson number, $R_i$:
186  % \label{eq:ZDF_prt}
187  P_{rt} =
188  \begin{cases}
189    \ \ \ 1 &      \text{if $\ R_i \leq 0.2$}   \\
190    5\,R_i &      \text{if $\ 0.2 \leq R_i \leq 2$}   \\
191    \ \ 10 &      \text{if $\ 2 \leq R_i$}
192  \end{cases}
194The choice of $P_{rt}$ is controlled by the \np{nn_pdl}{nn\_pdl} namelist variable.
196At the sea surface, the value of $\bar{e}$ is prescribed from the wind stress field as
197$\bar{e}_o = e_{bb} |\tau| / \rho_o$, with $e_{bb}$ the \np{rn_ebb}{rn\_ebb} namelist parameter.
198The default value of $e_{bb}$ is 3.75. \citep{gaspar.gregoris.ea_JGR90}), however a much larger value can be used when
199taking into account the surface wave breaking (see below Eq. \autoref{eq:ZDF_Esbc}).
200The bottom value of TKE is assumed to be equal to the value of the level just above.
201The time integration of the $\bar{e}$ equation may formally lead to negative values because
202the numerical scheme does not ensure its positivity.
203To overcome this problem, a cut-off in the minimum value of $\bar{e}$ is used (\np{rn_emin}{rn\_emin} namelist parameter).
204Following \citet{gaspar.gregoris.ea_JGR90}, the cut-off value is set to $\sqrt{2}/2~10^{-6}~m^2.s^{-2}$.
205This allows the subsequent formulations to match that of \citet{gargett_JMR84} for the diffusion in
206the thermocline and deep ocean :  $K_\rho = 10^{-3} / N$.
207In addition, a cut-off is applied on $K_m$ and $K_\rho$ to avoid numerical instabilities associated with
208too weak vertical diffusion.
209They must be specified at least larger than the molecular values, and are set through \np{rn_avm0}{rn\_avm0} and
210\np{rn_avt0}{rn\_avt0} (\nam{zdf}{zdf} namelist, see \autoref{subsec:ZDF_cst}).
212%% =================================================================================================
213\subsubsection{Turbulent length scale}
215For computational efficiency, the original formulation of the turbulent length scales proposed by
216\citet{gaspar.gregoris.ea_JGR90} has been simplified.
217Four formulations are proposed, the choice of which is controlled by the \np{nn_mxl}{nn\_mxl} namelist parameter.
218The first two are based on the following first order approximation \citep{blanke.delecluse_JPO93}:
220  \label{eq:ZDF_tke_mxl0_1}
221  l_k = l_\epsilon = \sqrt {2 \bar{e}\; } / N
223which is valid in a stable stratified region with constant values of the Brunt-Vais\"{a}l\"{a} frequency.
224The resulting length scale is bounded by the distance to the surface or to the bottom
225(\np[=0]{nn_mxl}{nn\_mxl}) or by the local vertical scale factor (\np[=1]{nn_mxl}{nn\_mxl}).
226\citet{blanke.delecluse_JPO93} notice that this simplification has two major drawbacks:
227it makes no sense for locally unstable stratification and the computation no longer uses all
228the information contained in the vertical density profile.
229To overcome these drawbacks, \citet{madec.delecluse.ea_NPM98} introduces the \np[=2, 3]{nn_mxl}{nn\_mxl} cases,
230which add an extra assumption concerning the vertical gradient of the computed length scale.
231So, the length scales are first evaluated as in \autoref{eq:ZDF_tke_mxl0_1} and then bounded such that:
233  \label{eq:ZDF_tke_mxl_constraint}
234  \frac{1}{e_3 }\left| {\frac{\partial l}{\partial k}} \right| \leq 1
235  \qquad \text{with }\  l =  l_k = l_\epsilon
237\autoref{eq:ZDF_tke_mxl_constraint} means that the vertical variations of the length scale cannot be larger than
238the variations of depth.
239It provides a better approximation of the \citet{gaspar.gregoris.ea_JGR90} formulation while being much less
240time consuming.
241In particular, it allows the length scale to be limited not only by the distance to the surface or
242to the ocean bottom but also by the distance to a strongly stratified portion of the water column such as
243the thermocline (\autoref{fig:ZDF_mixing_length}).
244In order to impose the \autoref{eq:ZDF_tke_mxl_constraint} constraint, we introduce two additional length scales:
245$l_{up}$ and $l_{dwn}$, the upward and downward length scales, and
246evaluate the dissipation and mixing length scales as
247(and note that here we use numerical indexing):
249  \centering
250  \includegraphics[width=0.66\textwidth]{Fig_mixing_length}
251  \caption[Mixing length computation]{Illustration of the mixing length computation}
252  \label{fig:ZDF_mixing_length}
255  % \label{eq:ZDF_tke_mxl2}
256  \begin{aligned}
257    l_{up\ \ }^{(k)} &= \min \left(  l^{(k)} \ , \ l_{up}^{(k+1)} + e_{3t}^{(k)}\ \ \ \;  \right)
258    \quad &\text{ from $k=1$ to $jpk$ }\ \\
259    l_{dwn}^{(k)} &= \min \left(  l^{(k)} \ , \ l_{dwn}^{(k-1)} + e_{3t}^{(k-1)\right)
260    \quad &\text{ from $k=jpk$ to $1$ }\ \\
261  \end{aligned}
263where $l^{(k)}$ is computed using \autoref{eq:ZDF_tke_mxl0_1}, \ie\ $l^{(k)} = \sqrt {2 {\bar e}^{(k)} / {N^2}^{(k)} }$.
265In the \np[=2]{nn_mxl}{nn\_mxl} case, the dissipation and mixing length scales take the same value:
266$ l_k=  l_\epsilon = \min \left(\ l_{up} \;,\;  l_{dwn}\ \right)$, while in the \np[=3]{nn_mxl}{nn\_mxl} case,
267the dissipation and mixing turbulent length scales are give as in \citet{gaspar.gregoris.ea_JGR90}:
269  % \label{eq:ZDF_tke_mxl_gaspar}
270  \begin{aligned}
271    & l_k          = \sqrt{\  l_{up} \ \ l_{dwn}\ }   \\
272    & l_\epsilon = \min \left(\ l_{up} \;,\;  l_{dwn}\ \right)
273  \end{aligned}
276At the ocean surface, a non zero length scale is set through the  \np{rn_mxl0}{rn\_mxl0} namelist parameter.
277Usually the surface scale is given by $l_o = \kappa \,z_o$ where $\kappa = 0.4$ is von Karman's constant and
278$z_o$ the roughness parameter of the surface.
279Assuming $z_o=0.1$~m \citep{craig.banner_JPO94} leads to a 0.04~m, the default value of \np{rn_mxl0}{rn\_mxl0}.
280In the ocean interior a minimum length scale is set to recover the molecular viscosity when
281$\bar{e}$ reach its minimum value ($1.10^{-6}= C_k\, l_{min} \,\sqrt{\bar{e}_{min}}$ ).
283%% =================================================================================================
284\subsubsection{Surface wave breaking parameterization}
286Following \citet{mellor.blumberg_JPO04}, the TKE turbulence closure model has been modified to
287include the effect of surface wave breaking energetics.
288This results in a reduction of summertime surface temperature when the mixed layer is relatively shallow.
289The \citet{mellor.blumberg_JPO04} modifications acts on surface length scale and TKE values and
290air-sea drag coefficient.
291The latter concerns the bulk formulae and is not discussed here.
293Following \citet{craig.banner_JPO94}, the boundary condition on surface TKE value is :
295  \label{eq:ZDF_Esbc}
296  \bar{e}_o = \frac{1}{2}\,\left(  15.8\,\alpha_{CB} \right)^{2/3} \,\frac{|\tau|}{\rho_o}
298where $\alpha_{CB}$ is the \citet{craig.banner_JPO94} constant of proportionality which depends on the ''wave age'',
299ranging from 57 for mature waves to 146 for younger waves \citep{mellor.blumberg_JPO04}.
300The boundary condition on the turbulent length scale follows the Charnock's relation:
302  \label{eq:ZDF_Lsbc}
303  l_o = \kappa \beta \,\frac{|\tau|}{g\,\rho_o}
305where $\kappa=0.40$ is the von Karman constant, and $\beta$ is the Charnock's constant.
306\citet{mellor.blumberg_JPO04} suggest $\beta = 2.10^{5}$ the value chosen by
307\citet{stacey_JPO99} citing observation evidence, and
308$\alpha_{CB} = 100$ the Craig and Banner's value.
309As the surface boundary condition on TKE is prescribed through $\bar{e}_o = e_{bb} |\tau| / \rho_o$,
310with $e_{bb}$ the \np{rn_ebb}{rn\_ebb} namelist parameter, setting \np[=67.83]{rn_ebb}{rn\_ebb} corresponds
311to $\alpha_{CB} = 100$.
312Further setting  \np[=.true.]{ln_mxl0}{ln\_mxl0},  applies \autoref{eq:ZDF_Lsbc} as the surface boundary condition on the length scale,
313with $\beta$ hard coded to the Stacey's value.
314Note that a minimal threshold of \np{rn_emin0}{rn\_emin0}$=10^{-4}~m^2.s^{-2}$ (namelist parameters) is applied on the
315surface $\bar{e}$ value.
317%% =================================================================================================
318\subsubsection{Langmuir cells}
320Langmuir circulations (LC) can be described as ordered large-scale vertical motions in
321the surface layer of the oceans.
322Although LC have nothing to do with convection, the circulation pattern is rather similar to
323so-called convective rolls in the atmospheric boundary layer.
324The detailed physics behind LC is described in, for example, \citet{craik.leibovich_JFM76}.
325The prevailing explanation is that LC arise from a nonlinear interaction between the Stokes drift and
326wind drift currents.
328Here we introduced in the TKE turbulent closure the simple parameterization of Langmuir circulations proposed by
329\citep{axell_JGR02} for a $k-\epsilon$ turbulent closure.
330The parameterization, tuned against large-eddy simulation, includes the whole effect of LC in
331an extra source term of TKE, $P_{LC}$.
332The presence of $P_{LC}$ in \autoref{eq:ZDF_tke_e}, the TKE equation, is controlled by setting \np{ln_lc}{ln\_lc} to
333\forcode{.true.} in the \nam{zdf_tke}{zdf\_tke} namelist.
335By making an analogy with the characteristic convective velocity scale (\eg, \citet{dalessio.abdella.ea_JPO98}),
336$P_{LC}$ is assumed to be :
338P_{LC}(z) = \frac{w_{LC}^3(z)}{H_{LC}}
340where $w_{LC}(z)$ is the vertical velocity profile of LC, and $H_{LC}$ is the LC depth.
341With no information about the wave field, $w_{LC}$ is assumed to be proportional to
342the Stokes drift $u_s = 0.377\,\,|\tau|^{1/2}$, where $|\tau|$ is the surface wind stress module
343\footnote{Following \citet{li.garrett_JMR93}, the surface Stoke drift velocity may be expressed as
344  $u_s =  0.016 \,|U_{10m}|$.
345  Assuming an air density of $\rho_a=1.22 \,Kg/m^3$ and a drag coefficient of
346  $1.5~10^{-3}$ give the expression used of $u_s$ as a function of the module of surface stress
348For the vertical variation, $w_{LC}$ is assumed to be zero at the surface as well as at
349a finite depth $H_{LC}$ (which is often close to the mixed layer depth),
350and simply varies as a sine function in between (a first-order profile for the Langmuir cell structures).
351The resulting expression for $w_{LC}$ is :
353  w_{LC}  =
354  \begin{cases}
355    c_{LC} \,u_s \,\sin(- \pi\,z / H_{LC} )    &      \text{if $-z \leq H_{LC}$}    \\
356    0                             &      \text{otherwise}
357  \end{cases}
359where $c_{LC} = 0.15$ has been chosen by \citep{axell_JGR02} as a good compromise to fit LES data.
360The chosen value yields maximum vertical velocities $w_{LC}$ of the order of a few centimeters per second.
361The value of $c_{LC}$ is set through the \np{rn_lc}{rn\_lc} namelist parameter,
362having in mind that it should stay between 0.15 and 0.54 \citep{axell_JGR02}.
364The $H_{LC}$ is estimated in a similar way as the turbulent length scale of TKE equations:
365$H_{LC}$ is the depth to which a water parcel with kinetic energy due to Stoke drift can reach on its own by
366converting its kinetic energy to potential energy, according to
368- \int_{-H_{LC}}^0 { N^2\;\;dz} = \frac{1}{2} u_s^2
371%% =================================================================================================
372\subsubsection{Mixing just below the mixed layer}
374Vertical mixing parameterizations commonly used in ocean general circulation models tend to
375produce mixed-layer depths that are too shallow during summer months and windy conditions.
376This bias is particularly acute over the Southern Ocean.
377To overcome this systematic bias, an ad hoc parameterization is introduced into the TKE scheme \cite{rodgers.aumont.ea_B14}.
378The parameterization is an empirical one, \ie\ not derived from theoretical considerations,
379but rather is meant to account for observed processes that affect the density structure of
380the ocean’s planetary boundary layer that are not explicitly captured by default in the TKE scheme
381(\ie\ near-inertial oscillations and ocean swells and waves).
383When using this parameterization (\ie\ when \np[=1]{nn_etau}{nn\_etau}),
384the TKE input to the ocean ($S$) imposed by the winds in the form of near-inertial oscillations,
385swell and waves is parameterized by \autoref{eq:ZDF_Esbc} the standard TKE surface boundary condition,
386plus a depth depend one given by:
388  \label{eq:ZDF_Ehtau}
389  S = (1-f_i) \; f_r \; e_s \; e^{-z / h_\tau}
391where $z$ is the depth, $e_s$ is TKE surface boundary condition, $f_r$ is the fraction of the surface TKE that
392penetrates in the ocean, $h_\tau$ is a vertical mixing length scale that controls exponential shape of
393the penetration, and $f_i$ is the ice concentration
394(no penetration if $f_i=1$, \ie\ if the ocean is entirely covered by sea-ice).
395The value of $f_r$, usually a few percents, is specified through \np{rn_efr}{rn\_efr} namelist parameter.
396The vertical mixing length scale, $h_\tau$, can be set as a 10~m uniform value (\np[=0]{nn_etau}{nn\_etau}) or
397a latitude dependent value (varying from 0.5~m at the Equator to a maximum value of 30~m at high latitudes
400Note that two other option exist, \np[=2, 3]{nn_etau}{nn\_etau}.
401They correspond to applying \autoref{eq:ZDF_Ehtau} only at the base of the mixed layer,
402or to using the high frequency part of the stress to evaluate the fraction of TKE that penetrates the ocean.
403Those two options are obsolescent features introduced for test purposes.
404They will be removed in the next release.
406% This should be explain better below what this rn_eice parameter is meant for:
407In presence of Sea Ice, the value of this mixing can be modulated by the \np{rn_eice}{rn\_eice} namelist parameter.
408This parameter varies from \forcode{0} for no effect to \forcode{4} to suppress the TKE input into the ocean when Sea Ice concentration
409is greater than 25\%.
411% from Burchard et al OM 2008 :
412% the most critical process not reproduced by statistical turbulence models is the activity of
413% internal waves and their interaction with turbulence. After the Reynolds decomposition,
414% internal waves are in principle included in the RANS equations, but later partially
415% excluded by the hydrostatic assumption and the model resolution.
416% Thus far, the representation of internal wave mixing in ocean models has been relatively crude
417% (\eg\ Mellor, 1989; Large et al., 1994; Meier, 2001; Axell, 2002; St. Laurent and Garrett, 2002).
419%% =================================================================================================
420\subsection[GLS: Generic Length Scale (\forcode{ln_zdfgls})]{GLS: Generic Length Scale (\protect\np{ln_zdfgls}{ln\_zdfgls})}
424  \nlst{namzdf_gls}
425  \caption{\forcode{&namzdf_gls}}
426  \label{lst:namzdf_gls}
429The Generic Length Scale (GLS) scheme is a turbulent closure scheme based on two prognostic equations:
430one for the turbulent kinetic energy $\bar {e}$, and another for the generic length scale,
431$\psi$ \citep{umlauf.burchard_JMR03, umlauf.burchard_CSR05}.
432This later variable is defined as: $\psi = {C_{0\mu}}^{p} \ {\bar{e}}^{m} \ l^{n}$,
433where the triplet $(p, m, n)$ value given in Tab.\autoref{tab:ZDF_GLS} allows to recover a number of
434well-known turbulent closures ($k$-$kl$ \citep{mellor.yamada_RG82}, $k$-$\epsilon$ \citep{rodi_JGR87},
435$k$-$\omega$ \citep{wilcox_AJ88} among others \citep{umlauf.burchard_JMR03,kantha.carniel_JMR03}).
436The GLS scheme is given by the following set of equations:
438  \label{eq:ZDF_gls_e}
439  \frac{\partial \bar{e}}{\partial t} =
440  \frac{K_m}{\sigma_e e_3 }\;\left[ {\left( \frac{\partial u}{\partial k} \right)^2
441      +\left( \frac{\partial v}{\partial k} \right)^2} \right]
442  -K_\rho \,N^2
443  +\frac{1}{e_3}\,\frac{\partial}{\partial k} \left[ \frac{K_m}{e_3}\,\frac{\partial \bar{e}}{\partial k} \right]
444  - \epsilon
448  % \label{eq:ZDF_gls_psi}
449  \begin{split}
450    \frac{\partial \psi}{\partial t} =& \frac{\psi}{\bar{e}} \left\{
451      \frac{C_1\,K_m}{\sigma_{\psi} {e_3}}\;\left[ {\left( \frac{\partial u}{\partial k} \right)^2
452          +\left( \frac{\partial v}{\partial k} \right)^2} \right]
453      - C_3 \,K_\rho\,N^2   - C_2 \,\epsilon \,Fw   \right\}             \\
454    &+\frac{1}{e_3\;\frac{\partial }{\partial k}\left[ {\frac{K_m}{e_3 }
455        \;\frac{\partial \psi}{\partial k}} \right]\;
456  \end{split}
460  % \label{eq:ZDF_gls_kz}
461  \begin{split}
462    K_m    &= C_{\mu} \ \sqrt {\bar{e}} \ l         \\
463    K_\rho &= C_{\mu'}\ \sqrt {\bar{e}} \ l
464  \end{split}
468  % \label{eq:ZDF_gls_eps}
469  {\epsilon} = C_{0\mu} \,\frac{\bar {e}^{3/2}}{l} \;
471where $N$ is the local Brunt-Vais\"{a}l\"{a} frequency (see \autoref{subsec:TRA_bn2}) and
472$\epsilon$ the dissipation rate.
473The constants $C_1$, $C_2$, $C_3$, ${\sigma_e}$, ${\sigma_{\psi}}$ and the wall function ($Fw$) depends of
474the choice of the turbulence model.
475Four different turbulent models are pre-defined (\autoref{tab:ZDF_GLS}).
476They are made available through the \np{nn_clo}{nn\_clo} namelist parameter.
479  \centering
480  % \begin{tabular}{cp{70pt}cp{70pt}cp{70pt}cp{70pt}cp{70pt}cp{70pt}c}
481  \begin{tabular}{ccccc}
482    &   $k-kl$   & $k-\epsilon$ & $k-\omega$ &   generic   \\
483    % & \citep{mellor.yamada_RG82} &  \citep{rodi_JGR87}       & \citep{wilcox_AJ88} &                 \\
484    \hline
485    \hline
486    \np{nn_clo}{nn\_clo}     & \textbf{0} &   \textbf{1}  &   \textbf{2}   &    \textbf{3}   \\
487    \hline
488    $( p , n , m )$         &   ( 0 , 1 , 1 )   & ( 3 , 1.5 , -1 )   & ( -1 , 0.5 , -1 )    &  ( 2 , 1 , -0.67 )  \\
489    $\sigma_k$      &    2.44         &     1.              &      2.                &      0.8          \\
490    $\sigma_\psi$  &    2.44         &     1.3            &      2.                 &       1.07       \\
491    $C_1$              &      0.9         &     1.44          &      0.555          &       1.           \\
492    $C_2$              &      0.5         &     1.92          &      0.833          &       1.22       \\
493    $C_3$              &      1.           &     1.              &      1.                &       1.           \\
494    $F_{wall}$        &      Yes        &       --             &     --                  &      --          \\
495    \hline
496    \hline
497  \end{tabular}
498  \caption[Set of predefined GLS parameters or equivalently predefined turbulence models available]{
499    Set of predefined GLS parameters, or equivalently predefined turbulence models available with
500    \protect\np[=.true.]{ln_zdfgls}{ln\_zdfgls} and controlled by
501    the \protect\np{nn_clos}{nn\_clos} namelist variable in \protect\nam{zdf_gls}{zdf\_gls}.}
502  \label{tab:ZDF_GLS}
505In the Mellor-Yamada model, the negativity of $n$ allows to use a wall function to force the convergence of
506the mixing length towards $\kappa z_b$ ($\kappa$ is the Von Karman constant and $z_b$ the rugosity length scale) value near physical boundaries
507(logarithmic boundary layer law).
508$C_{\mu}$ and $C_{\mu'}$ are calculated from stability function proposed by \citet{galperin.kantha.ea_JAS88},
509or by \citet{kantha.clayson_JGR94} or one of the two functions suggested by \citet{canuto.howard.ea_JPO01}
510(\np[=0, 3]{nn_stab_func}{nn\_stab\_func}, resp.).
511The value of $C_{0\mu}$ depends on the choice of the stability function.
513The surface and bottom boundary condition on both $\bar{e}$ and $\psi$ can be calculated thanks to Dirichlet or
514Neumann condition through \np{nn_bc_surf}{nn\_bc\_surf} and \np{nn_bc_bot}{nn\_bc\_bot}, resp.
515As for TKE closure, the wave effect on the mixing is considered when
516\np[ > 0.]{rn_crban}{rn\_crban} \citep{craig.banner_JPO94, mellor.blumberg_JPO04}.
517The \np{rn_crban}{rn\_crban} namelist parameter is $\alpha_{CB}$ in \autoref{eq:ZDF_Esbc} and
518\np{rn_charn}{rn\_charn} provides the value of $\beta$ in \autoref{eq:ZDF_Lsbc}.
520The $\psi$ equation is known to fail in stably stratified flows, and for this reason
521almost all authors apply a clipping of the length scale as an \textit{ad hoc} remedy.
522With this clipping, the maximum permissible length scale is determined by $l_{max} = c_{lim} \sqrt{2\bar{e}}/ N$.
523A value of $c_{lim} = 0.53$ is often used \citep{galperin.kantha.ea_JAS88}.
524\cite{umlauf.burchard_CSR05} show that the value of the clipping factor is of crucial importance for
525the entrainment depth predicted in stably stratified situations,
526and that its value has to be chosen in accordance with the algebraic model for the turbulent fluxes.
527The clipping is only activated if \np[=.true.]{ln_length_lim}{ln\_length\_lim},
528and the $c_{lim}$ is set to the \np{rn_clim_galp}{rn\_clim\_galp} value.
530The time and space discretization of the GLS equations follows the same energetic consideration as for
531the TKE case described in \autoref{subsec:ZDF_tke_ene} \citep{burchard_OM02}.
532Evaluation of the 4 GLS turbulent closure schemes can be found in \citet{warner.sherwood.ea_OM05} in ROMS model and
533 in \citet{reffray.guillaume.ea_GMD15} for the \NEMO\ model.
535% -------------------------------------------------------------------------------------------------------------
536%        OSM OSMOSIS BL Scheme
537% -------------------------------------------------------------------------------------------------------------
538\subsection[OSM: OSMOSIS boundary layer scheme (\forcode{ln_zdfosm = .true.})]
539{OSM: OSMOSIS boundary layer scheme (\protect\np{ln\_zdfosm}\forcode{ = .true.})}
543  \nlst{namzdf_osm}
544  \caption{\forcode{&namzdf_osm}}
545  \label{lst:namzdf_osm}
548Much of the time the turbulent motions in the ocean surface boundary
549layer (OSBL) are not given by
550classical shear turbulence. Instead they are in a regime known as
551`Langmuir turbulence',  dominated by an
552interaction between the currents and the Stokes drift of the surface waves \citep[e.g.][]{mcwilliams.ea_JFM97}.
553This regime is characterised by strong vertical turbulent motion, and appears when the surface Stokes drift $u_{s0}$ is much greater than the friction velocity $u_{\ast}$. More specifically Langmuir turbulence is thought to be crucial where the turbulent Langmuir number $\mathrm{La}_{t}=(u_{\ast}/u_{s0}) > 0.4$.
555The OSMOSIS model is fundamentally based on results of Large Eddy
556Simulations (LES) of Langmuir turbulence and aims to fully describe
557this Langmuir regime. The description in this section is of necessity incomplete and further details are available in the manuscript ``The OSMOSIS scheme'', Grant. A (2019); in prep.
559The OSMOSIS turbulent closure scheme is a similarity-scale scheme in
560the same spirit as the K-profile
561parameterization (KPP) scheme of \citet{large.ea_RG97}.
562A specified shape of diffusivity, scaled by the (OSBL) depth
563$h_{\mathrm{BL}}$ and a turbulent velocity scale, is imposed throughout the
564boundary layer
565$-h_{\mathrm{BL}}<z<\eta$. The turbulent closure model
566also includes fluxes of tracers and momentum that are``non-local'' (independent of the local property gradient).
568Rather than the OSBL
569depth being diagnosed in terms of a bulk Richardson number criterion,
570as in KPP, it is set by a prognostic equation that is informed by
571energy budget considerations reminiscent of the classical mixed layer
572models of \citet{kraus.turner_tellus67}.
573The model also includes an explicit parametrization of the structure
574of the pycnocline (the stratified region at the bottom of the OSBL).
576Presently, mixing below the OSBL is handled by the Richardson
577number-dependent mixing scheme used in \citet{large.ea_RG97}.
579Convective parameterizations such as described in \ref{sec:ZDF_conv}
580below should not be used with the OSMOSIS-OBL model: instabilities
581within the OSBL are part of the model, while instabilities below the
582ML are handled by the Ri # dependent scheme.
584\subsubsection{Depth and velocity scales}
585The model supposes a boundary layer of thickness $h_{\mathrm{bl}}$ enclosing a well-mixed layer of thickness $h_{\mathrm{ml}}$ and a relatively thin pycnocline at the base of thickness $\Delta h$; Fig.~\ref{fig: OSBL_structure} shows typical (a) buoyancy structure and (b) turbulent buoyancy flux profile for the unstable boundary layer (losing buoyancy at the surface; e.g.\ cooling).
587  \begin{center}
588    \includegraphics[width=0.7\textwidth]{Fig_ZDF_OSM_structure_of_OSBL}
589    \caption{
590      \protect\label{fig: OSBL_structure}
591     The structure of the entraining  boundary layer. (a) Mean buoyancy profile. (b) Profile of the buoyancy flux.
592    }
593  \end{center}
595The pycnocline in the OSMOSIS scheme is assumed to have a finite thickness, and may include a number of model levels. This means that the OSMOSIS scheme must parametrize both the thickness of the pycnocline, and the turbulent fluxes within the pycnocline.
597Consideration of the power input by wind acting on the Stokes drift suggests that the Langmuir turbulence has velocity scale:
599w_{*L}= \left(u_*^2 u_{s\,0}\right)^{1/3};
601but at times the Stokes drift may be weak due to e.g.\ ice cover, short fetch, misalignment with the surface stress, etc.\ so  a composite velocity scale is assumed for the stable (warming) boundary layer:
603  \nu_{\ast}= \left\{ u_*^3 \left[1-\exp(-1.5 \mathrm{La}_t^2})\right]+w_{*L}^3\right\}^{1/3}.
605For the unstable boundary layer this is merged with the standard convective velocity scale $w_{*C}=\left(\overline{w^\prime b^\prime}_0 \,h_\mathrm{ml}\right)^{1/3}$, where $\overline{w^\prime b^\prime}_0$ is the upwards surface buoyancy flux to give:
607\omega_* = \left(\nu_*^3 + 0.5 w_{*C}^3\right)^{1/3}.
610\subsubsection{The flux gradient model}
611The flux-gradient relationships used in the OSMOSIS scheme take the form:
614\overline{w^\prime\chi^\prime}=-K\frac{\partial\overline{\chi}}{\partial z} + N_{\chi,s} +N_{\chi,b} +N_{\chi,t},
617where $\chi$ is a general variable and $N_{\chi,s}, N_{\chi,b} \mathrm{and} N_{\chi,t}$  are the non-gradient terms, and represent the effects of the different terms in the turbulent flux-budget on the transport of $\chi$. $N_{\chi,s}$ represents the effects that the Stokes shear has on the transport of $\chi$, $N_{\chi,b}$  the effect of buoyancy, and $N_{\chi,t}$ the effect of the turbulent transport.  The same general form for the flux-gradient relationship is used to parametrize the transports of momentum, heat and salinity.
619In terms of the non-dimensionalized depth variables
622\sigma_{\mathrm{ml}}= -z/h_{\mathrm{ml}}; \;\sigma_{\mathrm{bl}}= -z/h_{\mathrm{bl}},
625in unstable conditions the eddy diffusivity ($K_d$) and eddy viscosity ($K_\nu$) profiles are parametrized as:
628K_d=&0.8\, \omega_*\, h_{\mathrm{ml}} \, \sigma_{\mathrm{ml}} \left(1-\beta_d \sigma_{\mathrm{ml}}\right)^{3/2}
630K_\nu =& 0.3\, \omega_* \,h_{\mathrm{ml}}\, \sigma_{\mathrm{ml}} \left(1-\beta_\nu \sigma_{\mathrm{ml}}\right)\left(1-\tfrac{1}{2}\sigma_{\mathrm{ml}}^2\right)
633where $\beta_d$ and $\beta_\nu$ are parameters that are determined by matching Eqs \ref{eq:diff-unstable} and \ref{eq:visc-unstable} to the eddy diffusivity and viscosity at the base of the well-mixed layer, given by
636K_{d,\mathrm{ml}}=K_{\nu,\mathrm{ml}}=\,0.16\,\omega_* \Delta h.
639For stable conditions the eddy diffusivity/viscosity profiles are given by:
642K_d= & 0.75\,\, \nu_*\, h_{\mathrm{ml}}\,\,  \exp\left[-2.8 \left(h_{\mathrm{bl}}/L_L\right)^2\right]\sigma_{\mathrm{ml}} \left(1-\sigma_{\mathrm{ml}}\right)^{3/2} \\\label{eq:visc-stable}
643K_\nu = & 0.375\,\,  \nu_*\, h_{\mathrm{ml}} \,\, \exp\left[-2.8 \left(h_{\mathrm{bl}}/L_L\right)^2\right] \sigma_{\mathrm{ml}} \left(1-\sigma_{\mathrm{ml}}\right)\left(1-\tfrac{1}{2}\sigma_{\mathrm{ml}}^2\right).
646The shape of the eddy viscosity and diffusivity profiles is the same as the shape in the unstable OSBL. The eddy diffusivity/viscosity depends on the stability parameter $h_{\mathrm{bl}}/{L_L}$ where $ L_L$ is analogous to the Obukhov length, but for Langmuir turbulence:
648  L_L=-w_{*L}^3/\left<\overline{w^\prime b^\prime}\right>_L,
650with the mean turbulent buoyancy flux averaged over the boundary layer given in terms of its surface value $\overline{w^\prime b^\prime}}_0$ and (downwards) )solar irradiance $I(z)$ by
651\begin{equation} \label{eq:stable-av-buoy-flux}
652\left<\overline{w^\prime b^\prime}\right>_L = \tfrac{1}{2} {\overline{w^\prime b^\prime}}_0-g\alpha_E\left[\tfrac{1}{2}(I(0)+I(-h))-\left<I\right>\right].
655In unstable conditions the eddy diffusivity and viscosity depend on stability through the velocity scale $\omega_*$, which depends on the two velocity scales $\nu_*$ and $w_{*C}$.
657Details of the non-gradient terms in \eqref{eq:flux-grad-gen} and of the fluxes within the pycnocline $-h_{\mathrm{bl}}<z<h_{\mathrm{ml}}$ can be found in Grant (2019).
659\subsubsection{Evolution of the boundary layer depth}
660The prognostic equation for the depth of the neutral/unstable boundary layer is given by \citep{grant+etal18},
662\begin{equation} \label{eq:dhdt-unstable}
663%\frac{\partial h_\mathrm{bl}}{\partial t} + \mathbf{U}_b\cdot\nabla h_\mathrm{bl}= W_b - \frac{{\overline{w^\prime b^\prime}}_\mathrm{ent}}{\Delta B_\mathrm{bl}}
664\frac{\partial h_\mathrm{bl}}{\partial t} = W_b - \frac{{\overline{w^\prime b^\prime}}_\mathrm{ent}}{\Delta B_\mathrm{bl}}
666where $h_\mathrm{bl}$ is the horizontally-varying depth of the OSBL, $\mathbf{U}_b$ and $W_b$ are the mean horizontal and vertical velocities at the base of the OSBL, ${\overline{w^\prime b^\prime}}_\mathrm{ent}$ is the buoyancy flux due to entrainment and $\Delta B_\mathrm{bl}$ is the difference between the buoyancy averaged over the depth of the OSBL (i.e.\ including the ML and pycnocline) and the buoyancy just below the base of the OSBL. This equation for the case when the pycnocline has a finite thickness, based on the potential energy budget of the OSBL, is the leading term \citep{grant+etal18} of a generalization of that used in mixed-layer models \citet[e.g.][]{kraus.turner_tellus67}, in which the thickness of the pycnocline is taken to be zero.
668The entrainment flux for the combination of convective and Langmuir turbulence is given by
669\begin{equation} \label{eq:entrain-flux}
670  {\overline{w^\prime b^\prime}}_\mathrm{ent} = -\alpha_{\mathrm{B}} {\overline{w^\prime b^\prime}}_0 - \alpha_{\mathrm{S}} \frac{u_*^3}{h_{\mathrm{ml}}}
671  + G\left(\delta/h_{\mathrm{ml}} \right)\left[\alpha_{\mathrm{S}}e^{-1.5\, \mathrm{La}_t}-\alpha_{\mathrm{L}} \frac{w_{\mathrm{*L}}^3}{h_{\mathrm{ml}}}\right]
673where the factor $G\equiv 1 - \exp (-25\delta/h_{\mathrm{bl}})(1-4\delta/h_{\mathrm{bl}})$ takes care of the lesser efficiency of Langmuir mixing when the mboundary-layer depth is much greater than the Stokes depth, and $\alpha_{\mathrm{B}}$, $\alpha_{S}$  and $\alpha_{\mathrm{L}}$ depend on the ratio of the appropriate eddy turnover time to the inertial timescale $f^{-1}$. Results from the LES suggest $\alpha_{\mathrm{B}}=0.18 F(fh_{\mathrm{bl}}/w_{*C})$, $\alpha_{S}=0.15 F(fh_{\mathrm{bl}}/u_*}$  and $\alpha_{\mathrm{L}}=0.035 F(fh_{\mathrm{bl}}/u_{*L})$, where $F(x)\equiv\tanh(x^{-1}))^{0.69}$.
676%% =================================================================================================
677\subsection[ Discrete energy conservation for TKE and GLS schemes]{Discrete energy conservation for TKE and GLS schemes}
681  \centering
682  \includegraphics[width=0.66\textwidth]{Fig_ZDF_TKE_time_scheme}
683  \caption[Subgrid kinetic energy integration in GLS and TKE schemes]{
684    Illustration of the subgrid kinetic energy integration in GLS and TKE schemes and
685    its links to the momentum and tracer time integration.}
686  \label{fig:ZDF_TKE_time_scheme}
689The production of turbulence by vertical shear (the first term of the right hand side of
690\autoref{eq:ZDF_tke_e}) and  \autoref{eq:ZDF_gls_e}) should balance the loss of kinetic energy associated with the vertical momentum diffusion
691(first line in \autoref{eq:MB_zdf}).
692To do so a special care has to be taken for both the time and space discretization of
693the kinetic energy equation \citep{burchard_OM02,marsaleix.auclair.ea_OM08}.
695Let us first address the time stepping issue. \autoref{fig:ZDF_TKE_time_scheme} shows how
696the two-level Leap-Frog time stepping of the momentum and tracer equations interplays with
697the one-level forward time stepping of the equation for $\bar{e}$.
698With this framework, the total loss of kinetic energy (in 1D for the demonstration) due to
699the vertical momentum diffusion is obtained by multiplying this quantity by $u^t$ and
700summing the result vertically:
702  \label{eq:ZDF_energ1}
703  \begin{split}
704    \int_{-H}^{\eta}  u^t \,\partial_z &\left( {K_m}^t \,(\partial_z u)^{t+\rdt}  \right) \,dz   \\
705    &= \Bigl[  u^t \,{K_m}^t \,(\partial_z u)^{t+\rdt} \Bigr]_{-H}^{\eta}
706    - \int_{-H}^{\eta}{ {K_m}^t \,\partial_z{u^t} \,\partial_z u^{t+\rdt} \,dz }
707  \end{split}
709Here, the vertical diffusion of momentum is discretized backward in time with a coefficient, $K_m$,
710known at time $t$ (\autoref{fig:ZDF_TKE_time_scheme}), as it is required when using the TKE scheme
711(see \autoref{sec:TD_forward_imp}).
712The first term of the right hand side of \autoref{eq:ZDF_energ1} represents the kinetic energy transfer at
713the surface (atmospheric forcing) and at the bottom (friction effect).
714The second term is always negative.
715It is the dissipation rate of kinetic energy, and thus minus the shear production rate of $\bar{e}$.
716\autoref{eq:ZDF_energ1} implies that, to be energetically consistent,
717the production rate of $\bar{e}$ used to compute $(\bar{e})^t$ (and thus ${K_m}^t$) should be expressed as
718${K_m}^{t-\rdt}\,(\partial_z u)^{t-\rdt} \,(\partial_z u)^t$
719(and not by the more straightforward $K_m \left( \partial_z u \right)^2$ expression taken at time $t$ or $t-\rdt$).
721A similar consideration applies on the destruction rate of $\bar{e}$ due to stratification
722(second term of the right hand side of \autoref{eq:ZDF_tke_e} and \autoref{eq:ZDF_gls_e}).
723This term must balance the input of potential energy resulting from vertical mixing.
724The rate of change of potential energy (in 1D for the demonstration) due to vertical mixing is obtained by
725multiplying the vertical density diffusion tendency by $g\,z$ and and summing the result vertically:
727  \label{eq:ZDF_energ2}
728  \begin{split}
729    \int_{-H}^{\eta} g\,z\,\partial_z &\left( {K_\rho}^t \,(\partial_k \rho)^{t+\rdt}   \right) \,dz    \\
730    &= \Bigl[  g\,z \,{K_\rho}^t \,(\partial_z \rho)^{t+\rdt} \Bigr]_{-H}^{\eta}
731    - \int_{-H}^{\eta}{ g \,{K_\rho}^t \,(\partial_k \rho)^{t+\rdt} } \,dz   \\
732    &= - \Bigl[  z\,{K_\rho}^t \,(N^2)^{t+\rdt} \Bigr]_{-H}^{\eta}
733    + \int_{-H}^{\eta}{  \rho^{t+\rdt} \, {K_\rho}^t \,(N^2)^{t+\rdt} \,dz  }
734  \end{split}
736where we use $N^2 = -g \,\partial_k \rho / (e_3 \rho)$.
737The first term of the right hand side of \autoref{eq:ZDF_energ2} is always zero because
738there is no diffusive flux through the ocean surface and bottom).
739The second term is minus the destruction rate of  $\bar{e}$ due to stratification.
740Therefore \autoref{eq:ZDF_energ1} implies that, to be energetically consistent,
741the product ${K_\rho}^{t-\rdt}\,(N^2)^t$ should be used in \autoref{eq:ZDF_tke_e} and  \autoref{eq:ZDF_gls_e}.
743Let us now address the space discretization issue.
744The vertical eddy coefficients are defined at $w$-point whereas the horizontal velocity components are in
745the centre of the side faces of a $t$-box in staggered C-grid (\autoref{fig:DOM_cell}).
746A space averaging is thus required to obtain the shear TKE production term.
747By redoing the \autoref{eq:ZDF_energ1} in the 3D case, it can be shown that the product of eddy coefficient by
748the shear at $t$ and $t-\rdt$ must be performed prior to the averaging.
749Furthermore, the time variation of $e_3$ has be taken into account.
751The above energetic considerations leads to the following final discrete form for the TKE equation:
753  \label{eq:ZDF_tke_ene}
754  \begin{split}
755    \frac { (\bar{e})^t - (\bar{e})^{t-\rdt} } {\rdt}  \equiv
756    \Biggl\{ \Biggr.
757    &\overline{ \left( \left(\overline{K_m}^{\,i+1/2}\right)^{t-\rdt} \,\frac{\delta_{k+1/2}[u^{t+\rdt}]}{{e_3u}^{t+\rdt} }
758        \ \frac{\delta_{k+1/2}[u^ t         ]}{{e_3u}^ t          }  \right) }^{\,i} \\
759    +&\overline{  \left( \left(\overline{K_m}^{\,j+1/2}\right)^{t-\rdt} \,\frac{\delta_{k+1/2}[v^{t+\rdt}]}{{e_3v}^{t+\rdt} }
760        \ \frac{\delta_{k+1/2}[v^ t         ]}{{e_3v}^ t          }  \right) }^{\,j}
761    \Biggr. \Biggr\}   \\
762    %
763    - &{K_\rho}^{t-\rdt}\,{(N^2)^t}    \\
764    %
765    +&\frac{1}{{e_3w}^{t+\rdt}}  \;\delta_{k+1/2} \left[   {K_m}^{t-\rdt} \,\frac{\delta_{k}[(\bar{e})^{t+\rdt}]} {{e_3w}^{t+\rdt}}   \right]   \\
766    %
767    - &c_\epsilon \; \left( \frac{\sqrt{\bar {e}}}{l_\epsilon}\right)^{t-\rdt}\,(\bar {e})^{t+\rdt}
768  \end{split}
770where the last two terms in \autoref{eq:ZDF_tke_ene} (vertical diffusion and Kolmogorov dissipation)
771are time stepped using a backward scheme (see\autoref{sec:TD_forward_imp}).
772Note that the Kolmogorov term has been linearized in time in order to render the implicit computation possible.
773%The restart of the TKE scheme requires the storage of $\bar {e}$, $K_m$, $K_\rho$ and $l_\epsilon$ as
774%they all appear in the right hand side of \autoref{eq:ZDF_tke_ene}.
775%For the latter, it is in fact the ratio $\sqrt{\bar{e}}/l_\epsilon$ which is stored.
777%% =================================================================================================
781Static instabilities (\ie\ light potential densities under heavy ones) may occur at particular ocean grid points.
782In nature, convective processes quickly re-establish the static stability of the water column.
783These processes have been removed from the model via the hydrostatic assumption so they must be parameterized.
784Three parameterisations are available to deal with convective processes:
785a non-penetrative convective adjustment or an enhanced vertical diffusion,
786or/and the use of a turbulent closure scheme.
788%% =================================================================================================
789\subsection[Non-penetrative convective adjustment (\forcode{ln_tranpc})]{Non-penetrative convective adjustment (\protect\np{ln_tranpc}{ln\_tranpc})}
793  \centering
794  \includegraphics[width=0.66\textwidth]{Fig_npc}
795  \caption[Unstable density profile treated by the non penetrative convective adjustment algorithm]{
796    Example of an unstable density profile treated by
797    the non penetrative convective adjustment algorithm.
798    $1^{st}$ step: the initial profile is checked from the surface to the bottom.
799    It is found to be unstable between levels 3 and 4.
800    They are mixed.
801    The resulting $\rho$ is still larger than $\rho$(5): levels 3 to 5 are mixed.
802    The resulting $\rho$ is still larger than $\rho$(6): levels 3 to 6 are mixed.
803    The $1^{st}$ step ends since the density profile is then stable below the level 3.
804    $2^{nd}$ step: the new $\rho$ profile is checked following the same procedure as in $1^{st}$ step:
805    levels 2 to 5 are mixed.
806    The new density profile is checked.
807    It is found stable: end of algorithm.}
808  \label{fig:ZDF_npc}
811Options are defined through the \nam{zdf}{zdf} namelist variables.
812The non-penetrative convective adjustment is used when \np[=.true.]{ln_zdfnpc}{ln\_zdfnpc}.
813It is applied at each \np{nn_npc}{nn\_npc} time step and mixes downwards instantaneously the statically unstable portion of
814the water column, but only until the density structure becomes neutrally stable
815(\ie\ until the mixed portion of the water column has \textit{exactly} the density of the water just below)
817The associated algorithm is an iterative process used in the following way (\autoref{fig:ZDF_npc}):
818starting from the top of the ocean, the first instability is found.
819Assume in the following that the instability is located between levels $k$ and $k+1$.
820The temperature and salinity in the two levels are vertically mixed, conserving the heat and salt contents of
821the water column.
822The new density is then computed by a linear approximation.
823If the new density profile is still unstable between levels $k+1$ and $k+2$,
824levels $k$, $k+1$ and $k+2$ are then mixed.
825This process is repeated until stability is established below the level $k$
826(the mixing process can go down to the ocean bottom).
827The algorithm is repeated to check if the density profile between level $k-1$ and $k$ is unstable and/or
828if there is no deeper instability.
830This algorithm is significantly different from mixing statically unstable levels two by two.
831The latter procedure cannot converge with a finite number of iterations for some vertical profiles while
832the algorithm used in \NEMO\ converges for any profile in a number of iterations which is less than
833the number of vertical levels.
834This property is of paramount importance as pointed out by \citet{killworth_iprc89}:
835it avoids the existence of permanent and unrealistic static instabilities at the sea surface.
836This non-penetrative convective algorithm has been proved successful in studies of the deep water formation in
837the north-western Mediterranean Sea \citep{madec.delecluse.ea_JPO91, madec.chartier.ea_DAO91, madec.crepon_iprc91}.
839The current implementation has been modified in order to deal with any non linear equation of seawater
840(L. Brodeau, personnal communication).
841Two main differences have been introduced compared to the original algorithm:
842$(i)$ the stability is now checked using the Brunt-V\"{a}is\"{a}l\"{a} frequency
843(not the difference in potential density);
844$(ii)$ when two levels are found unstable, their thermal and haline expansion coefficients are vertically mixed in
845the same way their temperature and salinity has been mixed.
846These two modifications allow the algorithm to perform properly and accurately with TEOS10 or EOS-80 without
847having to recompute the expansion coefficients at each mixing iteration.
849%% =================================================================================================
850\subsection[Enhanced vertical diffusion (\forcode{ln_zdfevd})]{Enhanced vertical diffusion (\protect\np{ln_zdfevd}{ln\_zdfevd})}
853Options are defined through the  \nam{zdf}{zdf} namelist variables.
854The enhanced vertical diffusion parameterisation is used when \np[=.true.]{ln_zdfevd}{ln\_zdfevd}.
855In this case, the vertical eddy mixing coefficients are assigned very large values
856in regions where the stratification is unstable
857(\ie\ when $N^2$ the Brunt-Vais\"{a}l\"{a} frequency is negative) \citep{lazar_phd97, lazar.madec.ea_JPO99}.
858This is done either on tracers only (\np[=0]{nn_evdm}{nn\_evdm}) or
859on both momentum and tracers (\np[=1]{nn_evdm}{nn\_evdm}).
861In practice, where $N^2\leq 10^{-12}$, $A_T^{vT}$ and $A_T^{vS}$, and if \np[=1]{nn_evdm}{nn\_evdm},
862the four neighbouring $A_u^{vm} \;\mbox{and}\;A_v^{vm}$ values also, are set equal to
863the namelist parameter \np{rn_avevd}{rn\_avevd}.
864A typical value for $rn\_avevd$ is between 1 and $100~m^2.s^{-1}$.
865This parameterisation of convective processes is less time consuming than
866the convective adjustment algorithm presented above when mixing both tracers and
867momentum in the case of static instabilities.
869Note that the stability test is performed on both \textit{before} and \textit{now} values of $N^2$.
870This removes a potential source of divergence of odd and even time step in
871a leapfrog environment \citep{leclair_phd10} (see \autoref{sec:TD_mLF}).
873%% =================================================================================================
874\subsection[Handling convection with turbulent closure schemes (\forcode{ln_zdf_}\{\forcode{tke,gls,osm}\})]{Handling convection with turbulent closure schemes (\forcode{ln_zdf{tke,gls,osm}})}
877The turbulent closure schemes presented in \autoref{subsec:ZDF_tke}, \autoref{subsec:ZDF_gls} and
878\autoref{subsec:ZDF_osm} (\ie\ \np{ln_zdftke}{ln\_zdftke} or \np{ln_zdfgls}{ln\_zdfgls} or \np{ln_zdfosm}{ln\_zdfosm} defined) deal, in theory,
879with statically unstable density profiles.
880In such a case, the term corresponding to the destruction of turbulent kinetic energy through stratification in
881\autoref{eq:ZDF_tke_e} or \autoref{eq:ZDF_gls_e} becomes a source term, since $N^2$ is negative.
882It results in large values of $A_T^{vT}$ and  $A_T^{vT}$, and also of the four neighboring values at
883velocity points $A_u^{vm} {and}\;A_v^{vm}$ (up to $1\;m^2s^{-1}$).
884These large values restore the static stability of the water column in a way similar to that of
885the enhanced vertical diffusion parameterisation (\autoref{subsec:ZDF_evd}).
886However, in the vicinity of the sea surface (first ocean layer), the eddy coefficients computed by
887the turbulent closure scheme do not usually exceed $10^{-2}m.s^{-1}$,
888because the mixing length scale is bounded by the distance to the sea surface.
889It can thus be useful to combine the enhanced vertical diffusion with the turbulent closure scheme,
890\ie\ setting the \np{ln_zdfnpc}{ln\_zdfnpc} namelist parameter to true and
891defining the turbulent closure (\np{ln_zdftke}{ln\_zdftke} or \np{ln_zdfgls}{ln\_zdfgls} = \forcode{.true.}) all together.
893The OSMOSIS turbulent closure scheme already includes enhanced vertical diffusion in the case of convection,
894%as governed by the variables $bvsqcon$ and $difcon$ found in \mdl{zdfkpp},
895therefore \np[=.false.]{ln_zdfevd}{ln\_zdfevd} should be used with the OSMOSIS scheme.
896% gm%  + one word on non local flux with KPP scheme trakpp.F90 module...
898%% =================================================================================================
899\section[Double diffusion mixing (\forcode{ln_zdfddm})]{Double diffusion mixing (\protect\np{ln_zdfddm}{ln\_zdfddm})}
904This parameterisation has been introduced in \mdl{zdfddm} module and is controlled by the namelist parameter
905\np{ln_zdfddm}{ln\_zdfddm} in \nam{zdf}{zdf}.
906Double diffusion occurs when relatively warm, salty water overlies cooler, fresher water, or vice versa.
907The former condition leads to salt fingering and the latter to diffusive convection.
908Double-diffusive phenomena contribute to diapycnal mixing in extensive regions of the ocean.
909\citet{merryfield.holloway.ea_JPO99} include a parameterisation of such phenomena in a global ocean model and show that
910it leads to relatively minor changes in circulation but exerts significant regional influences on
911temperature and salinity.
913Diapycnal mixing of S and T are described by diapycnal diffusion coefficients
915  % \label{eq:ZDF_ddm_Kz}
916  &A^{vT} = A_o^{vT}+A_f^{vT}+A_d^{vT} \\
917  &A^{vS} = A_o^{vS}+A_f^{vS}+A_d^{vS}
919where subscript $f$ represents mixing by salt fingering, $d$ by diffusive convection,
920and $o$ by processes other than double diffusion.
921The rates of double-diffusive mixing depend on the buoyancy ratio
922$R_\rho = \alpha \partial_z T / \beta \partial_z S$, where $\alpha$ and $\beta$ are coefficients of
923thermal expansion and saline contraction (see \autoref{subsec:TRA_eos}).
924To represent mixing of $S$ and $T$ by salt fingering, we adopt the diapycnal diffusivities suggested by Schmitt
927  \label{eq:ZDF_ddm_f}
928  A_f^{vS} &=
929             \begin{cases}
930               \frac{A^{\ast v}}{1+(R_\rho / R_c)^n   } &\text{if  $R_\rho > 1$ and $N^2>0$ } \\
931               0                              &\text{otherwise}
932             \end{cases}
933  \\         \label{eq:ZDF_ddm_f_T}
934  A_f^{vT} &= 0.7 \ A_f^{vS} / R_\rho
938  \centering
939  \includegraphics[width=0.66\textwidth]{Fig_zdfddm}
940  \caption[Diapycnal diffusivities for temperature and salt in regions of salt fingering and
941  diffusive convection]{
942    From \citet{merryfield.holloway.ea_JPO99}:
943    (a) Diapycnal diffusivities $A_f^{vT}$ and $A_f^{vS}$ for temperature and salt in
944    regions of salt fingering.
945    Heavy curves denote $A^{\ast v} = 10^{-3}~m^2.s^{-1}$ and
946    thin curves $A^{\ast v} = 10^{-4}~m^2.s^{-1}$;
947    (b) diapycnal diffusivities $A_d^{vT}$ and $A_d^{vS}$ for temperature and salt in
948    regions of diffusive convection.
949    Heavy curves denote the Federov parameterisation and thin curves the Kelley parameterisation.
950    The latter is not implemented in \NEMO.}
951  \label{fig:ZDF_ddm}
954The factor 0.7 in \autoref{eq:ZDF_ddm_f_T} reflects the measured ratio $\alpha F_T /\beta F_S \approx  0.7$ of
955buoyancy flux of heat to buoyancy flux of salt (\eg, \citet{mcdougall.taylor_JMR84}).
956Following  \citet{merryfield.holloway.ea_JPO99}, we adopt $R_c = 1.6$, $n = 6$, and $A^{\ast v} = 10^{-4}~m^2.s^{-1}$.
958To represent mixing of S and T by diffusive layering,  the diapycnal diffusivities suggested by
959Federov (1988) is used:
961  % \label{eq:ZDF_ddm_d}
962  A_d^{vT} &=
963             \begin{cases}
964               1.3635 \, \exp{\left( 4.6\, \exp{ \left[  -0.54\,( R_{\rho}^{-1} - 1 )  \right] }    \right)}
965               &\text{if  $0<R_\rho < 1$ and $N^2>0$ } \\
966               0                       &\text{otherwise}
967             \end{cases}
968                                       \nonumber \\
969  \label{eq:ZDF_ddm_d_S}
970  A_d^{vS} &=
971             \begin{cases}
972               A_d^{vT}\ \left( 1.85\,R_{\rho} - 0.85 \right) &\text{if  $0.5 \leq R_\rho<1$ and $N^2>0$ } \\
973               A_d^{vT} \ 0.15 \ R_\rho               &\text{if  $\ \ 0 < R_\rho<0.5$ and $N^2>0$ } \\
974               0                       &\text{otherwise}
975             \end{cases}
978The dependencies of \autoref{eq:ZDF_ddm_f} to \autoref{eq:ZDF_ddm_d_S} on $R_\rho$ are illustrated in
980Implementing this requires computing $R_\rho$ at each grid point on every time step.
981This is done in \mdl{eosbn2} at the same time as $N^2$ is computed.
982This avoids duplication in the computation of $\alpha$ and $\beta$ (which is usually quite expensive).
984%% =================================================================================================
985\section[Bottom and top friction (\textit{zdfdrg.F90})]{Bottom and top friction (\protect\mdl{zdfdrg})}
989  \nlst{namdrg}
990  \caption{\forcode{&namdrg}}
991  \label{lst:namdrg}
994  \nlst{namdrg_top}
995  \caption{\forcode{&namdrg_top}}
996  \label{lst:namdrg_top}
999  \nlst{namdrg_bot}
1000  \caption{\forcode{&namdrg_bot}}
1001  \label{lst:namdrg_bot}
1004Options to define the top and bottom friction are defined through the \nam{drg}{drg} namelist variables.
1005The bottom friction represents the friction generated by the bathymetry.
1006The top friction represents the friction generated by the ice shelf/ocean interface.
1007As the friction processes at the top and the bottom are treated in and identical way,
1008the description below considers mostly the bottom friction case, if not stated otherwise.
1010Both the surface momentum flux (wind stress) and the bottom momentum flux (bottom friction) enter the equations as
1011a condition on the vertical diffusive flux.
1012For the bottom boundary layer, one has:
1013 \[
1014   % \label{eq:ZDF_bfr_flux}
1015   A^{vm} \left( \partial {\textbf U}_h / \partial z \right) = {{\cal F}}_h^{\textbf U}
1016 \]
1017where ${\cal F}_h^{\textbf U}$ is represents the downward flux of horizontal momentum outside
1018the logarithmic turbulent boundary layer (thickness of the order of 1~m in the ocean).
1019How ${\cal F}_h^{\textbf U}$ influences the interior depends on the vertical resolution of the model near
1020the bottom relative to the Ekman layer depth.
1021For example, in order to obtain an Ekman layer depth $d = \sqrt{2\;A^{vm}} / f = 50$~m,
1022one needs a vertical diffusion coefficient $A^{vm} = 0.125$~m$^2$s$^{-1}$
1023(for a Coriolis frequency $f = 10^{-4}$~m$^2$s$^{-1}$).
1024With a background diffusion coefficient $A^{vm} = 10^{-4}$~m$^2$s$^{-1}$, the Ekman layer depth is only 1.4~m.
1025When the vertical mixing coefficient is this small, using a flux condition is equivalent to
1026entering the viscous forces (either wind stress or bottom friction) as a body force over the depth of the top or
1027bottom model layer.
1028To illustrate this, consider the equation for $u$ at $k$, the last ocean level:
1030  \label{eq:ZDF_drg_flux2}
1031  \frac{\partial u_k}{\partial t} = \frac{1}{e_{3u}} \left[ \frac{A_{uw}^{vm}}{e_{3uw}} \delta_{k+1/2}\;[u] - {\cal F}^u_h \right] \approx - \frac{{\cal F}^u_{h}}{e_{3u}}
1033If the bottom layer thickness is 200~m, the Ekman transport will be distributed over that depth.
1034On the other hand, if the vertical resolution is high (1~m or less) and a turbulent closure model is used,
1035the turbulent Ekman layer will be represented explicitly by the model.
1036However, the logarithmic layer is never represented in current primitive equation model applications:
1037it is \emph{necessary} to parameterize the flux ${\cal F}^u_h $.
1038Two choices are available in \NEMO: a linear and a quadratic bottom friction.
1039Note that in both cases, the rotation between the interior velocity and the bottom friction is neglected in
1040the present release of \NEMO.
1042In the code, the bottom friction is imposed by adding the trend due to the bottom friction to
1043 the general momentum trend in \mdl{dynzdf}.
1044For the time-split surface pressure gradient algorithm, the momentum trend due to
1045the barotropic component needs to be handled separately.
1046For this purpose it is convenient to compute and store coefficients which can be simply combined with
1047bottom velocities and geometric values to provide the momentum trend due to bottom friction.
1048 These coefficients are computed in \mdl{zdfdrg} and generally take the form $c_b^{\textbf U}$ where:
1050  \label{eq:ZDF_bfr_bdef}
1051  \frac{\partial {\textbf U_h}}{\partial t} =
1052  - \frac{{\cal F}^{\textbf U}_{h}}{e_{3u}} = \frac{c_b^{\textbf U}}{e_{3u}} \;{\textbf U}_h^b
1054where $\textbf{U}_h^b = (u_b\;,\;v_b)$ is the near-bottom, horizontal, ocean velocity.
1055Note than from \NEMO\ 4.0, drag coefficients are only computed at cell centers (\ie\ at T-points) and refer to as $c_b^T$ in the following. These are then linearly interpolated in space to get $c_b^\textbf{U}$ at velocity points.
1057%% =================================================================================================
1058\subsection[Linear top/bottom friction (\forcode{ln_lin})]{Linear top/bottom friction (\protect\np{ln_lin}{ln\_lin})}
1061The linear friction parameterisation (including the special case of a free-slip condition) assumes that
1062the friction is proportional to the interior velocity (\ie\ the velocity of the first/last model level):
1064  % \label{eq:ZDF_bfr_linear}
1065  {\cal F}_h^\textbf{U} = \frac{A^{vm}}{e_3} \; \frac{\partial \textbf{U}_h}{\partial k} = r \; \textbf{U}_h^b
1067where $r$ is a friction coefficient expressed in $m s^{-1}$.
1068This coefficient is generally estimated by setting a typical decay time $\tau$ in the deep ocean,
1069and setting $r = H / \tau$, where $H$ is the ocean depth.
1070Commonly accepted values of $\tau$ are of the order of 100 to 200 days \citep{weatherly_JMR84}.
1071A value $\tau^{-1} = 10^{-7}$~s$^{-1}$ equivalent to 115 days, is usually used in quasi-geostrophic models.
1072One may consider the linear friction as an approximation of quadratic friction, $r \approx 2\;C_D\;U_{av}$
1073(\citet{gill_bk82}, Eq. 9.6.6).
1074For example, with a drag coefficient $C_D = 0.002$, a typical speed of tidal currents of $U_{av} =0.1$~m\;s$^{-1}$,
1075and assuming an ocean depth $H = 4000$~m, the resulting friction coefficient is $r = 4\;10^{-4}$~m\;s$^{-1}$.
1076This is the default value used in \NEMO. It corresponds to a decay time scale of 115~days.
1077It can be changed by specifying \np{rn_Uc0}{rn\_Uc0} (namelist parameter).
1079 For the linear friction case the drag coefficient used in the general expression \autoref{eq:ZDF_bfr_bdef} is:
1081  % \label{eq:ZDF_bfr_linbfr_b}
1082    c_b^T = - r
1084When \np[=.true.]{ln_lin}{ln\_lin}, the value of $r$ used is \np{rn_Uc0}{rn\_Uc0}*\np{rn_Cd0}{rn\_Cd0}.
1085Setting \np[=.true.]{ln_OFF}{ln\_OFF} (and \forcode{ln_lin=.true.}) is equivalent to setting $r=0$ and leads to a free-slip boundary condition.
1087These values are assigned in \mdl{zdfdrg}.
1088Note that there is support for local enhancement of these values via an externally defined 2D mask array
1089(\np[=.true.]{ln_boost}{ln\_boost}) given in the \ifile{bfr\_coef} input NetCDF file.
1090The mask values should vary from 0 to 1.
1091Locations with a non-zero mask value will have the friction coefficient increased by
1092$mask\_value$ * \np{rn_boost}{rn\_boost} * \np{rn_Cd0}{rn\_Cd0}.
1094%% =================================================================================================
1095\subsection[Non-linear top/bottom friction (\forcode{ln_non_lin})]{Non-linear top/bottom friction (\protect\np{ln_non_lin}{ln\_non\_lin})}
1098The non-linear bottom friction parameterisation assumes that the top/bottom friction is quadratic:
1100  % \label{eq:ZDF_drg_nonlinear}
1101  {\cal F}_h^\textbf{U} = \frac{A^{vm}}{e_3 }\frac{\partial \textbf {U}_h
1102  }{\partial k}=C_D \;\sqrt {u_b ^2+v_b ^2+e_b } \;\; \textbf {U}_h^b
1104where $C_D$ is a drag coefficient, and $e_b $ a top/bottom turbulent kinetic energy due to tides,
1105internal waves breaking and other short time scale currents.
1106A typical value of the drag coefficient is $C_D = 10^{-3} $.
1107As an example, the CME experiment \citep{treguier_JGR92} uses $C_D = 10^{-3}$ and
1108$e_b = 2.5\;10^{-3}$m$^2$\;s$^{-2}$, while the FRAM experiment \citep{killworth_JPO92} uses $C_D = 1.4\;10^{-3}$ and
1109$e_b =2.5\;\;10^{-3}$m$^2$\;s$^{-2}$.
1110The CME choices have been set as default values (\np{rn_Cd0}{rn\_Cd0} and \np{rn_ke0}{rn\_ke0} namelist parameters).
1112As for the linear case, the friction is imposed in the code by adding the trend due to
1113the friction to the general momentum trend in \mdl{dynzdf}.
1114For the non-linear friction case the term computed in \mdl{zdfdrg} is:
1116  % \label{eq:ZDF_drg_nonlinbfr}
1117    c_b^T = - \; C_D\;\left[ \left(\bar{u_b}^{i}\right)^2 + \left(\bar{v_b}^{j}\right)^2 + e_b \right]^{1/2}
1120The coefficients that control the strength of the non-linear friction are initialised as namelist parameters:
1121$C_D$= \np{rn_Cd0}{rn\_Cd0}, and $e_b$ =\np{rn_bfeb2}{rn\_bfeb2}.
1122Note that for applications which consider tides explicitly, a low or even zero value of \np{rn_bfeb2}{rn\_bfeb2} is recommended. A local enhancement of $C_D$ is again possible via an externally defined 2D mask array
1124This works in the same way as for the linear friction case with non-zero masked locations increased by
1125$mask\_value$ * \np{rn_boost}{rn\_boost} * \np{rn_Cd0}{rn\_Cd0}.
1127%% =================================================================================================
1128\subsection[Log-layer top/bottom friction (\forcode{ln_loglayer})]{Log-layer top/bottom friction (\protect\np{ln_loglayer}{ln\_loglayer})}
1131In the non-linear friction case, the drag coefficient, $C_D$, can be optionally enhanced using
1132a "law of the wall" scaling. This assumes that the model vertical resolution can capture the logarithmic layer which typically occur for layers thinner than 1 m or so.
1133If  \np[=.true.]{ln_loglayer}{ln\_loglayer}, $C_D$ is no longer constant but is related to the distance to the wall (or equivalently to the half of the top/bottom layer thickness):
1135  C_D = \left ( {\kappa \over {\mathrm log}\left ( 0.5 \; e_{3b} / rn\_{z0} \right ) } \right )^2
1138\noindent where $\kappa$ is the von-Karman constant and \np{rn_z0}{rn\_z0} is a roughness length provided via the namelist.
1140The drag coefficient is bounded such that it is kept greater or equal to
1141the base \np{rn_Cd0}{rn\_Cd0} value which occurs where layer thicknesses become large and presumably logarithmic layers are not resolved at all. For stability reason, it is also not allowed to exceed the value of an additional namelist parameter:
1142\np{rn_Cdmax}{rn\_Cdmax}, \ie
1144  rn\_Cd0 \leq C_D \leq rn\_Cdmax
1147\noindent The log-layer enhancement can also be applied to the top boundary friction if
1148under ice-shelf cavities are activated (\np[=.true.]{ln_isfcav}{ln\_isfcav}).
1149%In this case, the relevant namelist parameters are \np{rn_tfrz0}{rn\_tfrz0}, \np{rn_tfri2}{rn\_tfri2} and \np{rn_tfri2_max}{rn\_tfri2\_max}.
1151%% =================================================================================================
1152\subsection[Explicit top/bottom friction (\forcode{ln_drgimp=.false.})]{Explicit top/bottom friction (\protect\np[=.false.]{ln_drgimp}{ln\_drgimp})}
1155Setting \np[=.false.]{ln_drgimp}{ln\_drgimp} means that bottom friction is treated explicitly in time, which has the advantage of simplifying the interaction with the split-explicit free surface (see \autoref{subsec:ZDF_drg_ts}). The latter does indeed require the knowledge of bottom stresses in the course of the barotropic sub-iteration, which becomes less straightforward in the implicit case. In the explicit case, top/bottom stresses can be computed using \textit{before} velocities and inserted in the overall momentum tendency budget. This reads:
1157At the top (below an ice shelf cavity):
1159  \left.{\left( {\frac{A^{vm} }{e_3 }\ \frac{\partial \textbf{U}_h}{\partial k}} \right)} \right|_{t}
1160  = c_{t}^{\textbf{U}}\textbf{u}^{n-1}_{t}
1163At the bottom (above the sea floor):
1165  \left.{\left( {\frac{A^{vm} }{e_3 }\ \frac{\partial \textbf{U}_h}{\partial k}} \right)} \right|_{b}
1166  = c_{b}^{\textbf{U}}\textbf{u}^{n-1}_{b}
1169Since this is conditionally stable, some care needs to exercised over the choice of parameters to ensure that the implementation of explicit top/bottom friction does not induce numerical instability.
1170For the purposes of stability analysis, an approximation to \autoref{eq:ZDF_drg_flux2} is:
1172  \label{eq:ZDF_Eqn_drgstab}
1173  \begin{split}
1174    \Delta u &= -\frac{{{\cal F}_h}^u}{e_{3u}}\;2 \rdt    \\
1175    &= -\frac{ru}{e_{3u}}\;2\rdt\\
1176  \end{split}
1178\noindent where linear friction and a leapfrog timestep have been assumed.
1179To ensure that the friction cannot reverse the direction of flow it is necessary to have:
1181  |\Delta u| < \;|u|
1183\noindent which, using \autoref{eq:ZDF_Eqn_drgstab}, gives:
1185  r\frac{2\rdt}{e_{3u}} < 1 \qquad  \Rightarrow \qquad r < \frac{e_{3u}}{2\rdt}\\
1187This same inequality can also be derived in the non-linear bottom friction case if
1188a velocity of 1 m.s$^{-1}$ is assumed.
1189Alternatively, this criterion can be rearranged to suggest a minimum bottom box thickness to ensure stability:
1191  e_{3u} > 2\;r\;\rdt
1193\noindent which it may be necessary to impose if partial steps are being used.
1194For example, if $|u| = 1$ m.s$^{-1}$, $rdt = 1800$ s, $r = 10^{-3}$ then $e_{3u}$ should be greater than 3.6 m.
1195For most applications, with physically sensible parameters these restrictions should not be of concern.
1196But caution may be necessary if attempts are made to locally enhance the bottom friction parameters.
1197To ensure stability limits are imposed on the top/bottom friction coefficients both
1198during initialisation and at each time step.
1199Checks at initialisation are made in \mdl{zdfdrg} (assuming a 1 m.s$^{-1}$ velocity in the non-linear case).
1200The number of breaches of the stability criterion are reported as well as
1201the minimum and maximum values that have been set.
1202The criterion is also checked at each time step, using the actual velocity, in \mdl{dynzdf}.
1203Values of the friction coefficient are reduced as necessary to ensure stability;
1204these changes are not reported.
1206Limits on the top/bottom friction coefficient are not imposed if the user has elected to
1207handle the friction implicitly (see \autoref{subsec:ZDF_drg_imp}).
1208The number of potential breaches of the explicit stability criterion are still reported for information purposes.
1210%% =================================================================================================
1211\subsection[Implicit top/bottom friction (\forcode{ln_drgimp=.true.})]{Implicit top/bottom friction (\protect\np[=.true.]{ln_drgimp}{ln\_drgimp})}
1214An optional implicit form of bottom friction has been implemented to improve model stability.
1215We recommend this option for shelf sea and coastal ocean applications. %, especially for split-explicit time splitting.
1216This option can be invoked by setting \np{ln_drgimp}{ln\_drgimp} to \forcode{.true.} in the \nam{drg}{drg} namelist.
1217%This option requires \np{ln_zdfexp}{ln\_zdfexp} to be \forcode{.false.} in the \nam{zdf}{zdf} namelist.
1219This implementation is performed in \mdl{dynzdf} where the following boundary conditions are set while solving the fully implicit diffusion step:
1221At the top (below an ice shelf cavity):
1223  % \label{eq:ZDF_dynZDF__drg_top}
1224  \left.{\left( {\frac{A^{vm} }{e_3 }\ \frac{\partial \textbf{U}_h}{\partial k}} \right)} \right|_{t}
1225  = c_{t}^{\textbf{U}}\textbf{u}^{n+1}_{t}
1228At the bottom (above the sea floor):
1230  % \label{eq:ZDF_dynZDF__drg_bot}
1231  \left.{\left( {\frac{A^{vm} }{e_3 }\ \frac{\partial \textbf{U}_h}{\partial k}} \right)} \right|_{b}
1232  = c_{b}^{\textbf{U}}\textbf{u}^{n+1}_{b}
1235where $t$ and $b$ refers to top and bottom layers respectively.
1236Superscript $n+1$ means the velocity used in the friction formula is to be calculated, so it is implicit.
1238%% =================================================================================================
1239\subsection[Bottom friction with split-explicit free surface]{Bottom friction with split-explicit free surface}
1242With split-explicit free surface, the sub-stepping of barotropic equations needs the knowledge of top/bottom stresses. An obvious way to satisfy this is to take them as constant over the course of the barotropic integration and equal to the value used to update the baroclinic momentum trend. Provided \np[=.false.]{ln_drgimp}{ln\_drgimp} and a centred or \textit{leap-frog} like integration of barotropic equations is used (\ie\ \forcode{ln_bt_fw=.false.}, cf \autoref{subsec:DYN_spg_ts}), this does ensure that barotropic and baroclinic dynamics feel the same stresses during one leapfrog time step. However, if \np[=.true.]{ln_drgimp}{ln\_drgimp},  stresses depend on the \textit{after} value of the velocities which themselves depend on the barotropic iteration result. This cyclic dependency makes difficult obtaining consistent stresses in 2d and 3d dynamics. Part of this mismatch is then removed when setting the final barotropic component of 3d velocities to the time splitting estimate. This last step can be seen as a necessary evil but should be minimized since it interferes with the adjustment to the boundary conditions.
1244The strategy to handle top/bottom stresses with split-explicit free surface in \NEMO\ is as follows:
1246\item To extend the stability of the barotropic sub-stepping, bottom stresses are refreshed at each sub-iteration. The baroclinic part of the flow entering the stresses is frozen at the initial time of the barotropic iteration. In case of non-linear friction, the drag coefficient is also constant.
1247\item In case of an implicit drag, specific computations are performed in \mdl{dynzdf} which renders the overall scheme mixed explicit/implicit: the barotropic components of 3d velocities are removed before seeking for the implicit vertical diffusion result. Top/bottom stresses due to the barotropic components are explicitly accounted for thanks to the updated values of barotropic velocities. Then the implicit solution of 3d velocities is obtained. Lastly, the residual barotropic component is replaced by the time split estimate.
1250Note that other strategies are possible, like considering vertical diffusion step in advance, \ie\ prior barotropic integration.
1252%% =================================================================================================
1253\section[Internal wave-driven mixing (\forcode{ln_zdfiwm})]{Internal wave-driven mixing (\protect\np{ln_zdfiwm}{ln\_zdfiwm})}
1257  \nlst{namzdf_iwm}
1258  \caption{\forcode{&namzdf_iwm}}
1259  \label{lst:namzdf_iwm}
1262The parameterization of mixing induced by breaking internal waves is a generalization of
1263the approach originally proposed by \citet{st-laurent.simmons.ea_GRL02}.
1264A three-dimensional field of internal wave energy dissipation $\epsilon(x,y,z)$ is first constructed,
1265and the resulting diffusivity is obtained as
1267  % \label{eq:ZDF_Kwave}
1268  A^{vT}_{wave} =  R_f \,\frac{ \epsilon }{ \rho \, N^2 }
1270where $R_f$ is the mixing efficiency and $\epsilon$ is a specified three dimensional distribution of
1271the energy available for mixing.
1272If the \np{ln_mevar}{ln\_mevar} namelist parameter is set to \forcode{.false.}, the mixing efficiency is taken as constant and
1273equal to 1/6 \citep{osborn_JPO80}.
1274In the opposite (recommended) case, $R_f$ is instead a function of
1275the turbulence intensity parameter $Re_b = \frac{ \epsilon}{\nu \, N^2}$,
1276with $\nu$ the molecular viscosity of seawater, following the model of \cite{bouffard.boegman_DAO13} and
1277the implementation of \cite{de-lavergne.madec.ea_JPO16}.
1278Note that $A^{vT}_{wave}$ is bounded by $10^{-2}\,m^2/s$, a limit that is often reached when
1279the mixing efficiency is constant.
1281In addition to the mixing efficiency, the ratio of salt to heat diffusivities can chosen to vary
1282as a function of $Re_b$ by setting the \np{ln_tsdiff}{ln\_tsdiff} parameter to \forcode{.true.}, a recommended choice.
1283This parameterization of differential mixing, due to \cite{jackson.rehmann_JPO14},
1284is implemented as in \cite{de-lavergne.madec.ea_JPO16}.
1286The three-dimensional distribution of the energy available for mixing, $\epsilon(i,j,k)$,
1287is constructed from three static maps of column-integrated internal wave energy dissipation,
1288$E_{cri}(i,j)$, $E_{pyc}(i,j)$, and $E_{bot}(i,j)$, combined to three corresponding vertical structures:
1291  F_{cri}(i,j,k) &\propto e^{-h_{ab} / h_{cri} }\\
1292  F_{pyc}(i,j,k) &\propto N^{n_p}\\
1293  F_{bot}(i,j,k) &\propto N^2 \, e^{- h_{wkb} / h_{bot} }
1295In the above formula, $h_{ab}$ denotes the height above bottom,
1296$h_{wkb}$ denotes the WKB-stretched height above bottom, defined by
1298  h_{wkb} = H \, \frac{ \int_{-H}^{z} N \, dz' } { \int_{-H}^{\eta} N \, dz'  } \; ,
1300The $n_p$ parameter (given by \np{nn_zpyc}{nn\_zpyc} in \nam{zdf_iwm}{zdf\_iwm} namelist)
1301controls the stratification-dependence of the pycnocline-intensified dissipation.
1302It can take values of $1$ (recommended) or $2$.
1303Finally, the vertical structures $F_{cri}$ and $F_{bot}$ require the specification of
1304the decay scales $h_{cri}(i,j)$ and $h_{bot}(i,j)$, which are defined by two additional input maps.
1305$h_{cri}$ is related to the large-scale topography of the ocean (etopo2) and
1306$h_{bot}$ is a function of the energy flux $E_{bot}$, the characteristic horizontal scale of
1307the abyssal hill topography \citep{goff_JGR10} and the latitude.
1308% Jc: input files names ?
1310%% =================================================================================================
1311\section[Surface wave-induced mixing (\forcode{ln_zdfswm})]{Surface wave-induced mixing (\protect\np{ln_zdfswm}{ln\_zdfswm})}
1314Surface waves produce an enhanced mixing through wave-turbulence interaction.
1315In addition to breaking waves induced turbulence (\autoref{subsec:ZDF_tke}),
1316the influence of non-breaking waves can be accounted introducing
1317wave-induced viscosity and diffusivity as a function of the wave number spectrum.
1318Following \citet{qiao.yuan.ea_OD10}, a formulation of wave-induced mixing coefficient
1319is provided  as a function of wave amplitude, Stokes Drift and wave-number:
1322  \label{eq:ZDF_Bv}
1323  B_{v} = \alpha {A} {U}_{st} {exp(3kz)}
1326Where $B_{v}$ is the wave-induced mixing coefficient, $A$ is the wave amplitude,
1327${U}_{st}$ is the Stokes Drift velocity, $k$ is the wave number and $\alpha$
1328is a constant which should be determined by observations or
1329numerical experiments and is set to be 1.
1331The coefficient $B_{v}$ is then directly added to the vertical viscosity
1332and diffusivity coefficients.
1334In order to account for this contribution set: \forcode{ln_zdfswm=.true.},
1335then wave interaction has to be activated through \forcode{ln_wave=.true.},
1336the Stokes Drift can be evaluated by setting \forcode{ln_sdw=.true.}
1337(see \autoref{subsec:SBC_wave_sdw})
1338and the needed wave fields can be provided either in forcing or coupled mode
1339(for more information on wave parameters and settings see \autoref{sec:SBC_wave})
1341%% =================================================================================================
1342\section[Adaptive-implicit vertical advection (\forcode{ln_zad_Aimp})]{Adaptive-implicit vertical advection(\protect\np{ln_zad_Aimp}{ln\_zad\_Aimp})}
1345The adaptive-implicit vertical advection option in NEMO is based on the work of
1346\citep{shchepetkin_OM15}.  In common with most ocean models, the timestep used with NEMO
1347needs to satisfy multiple criteria associated with different physical processes in order
1348to maintain numerical stability. \citep{shchepetkin_OM15} pointed out that the vertical
1349CFL criterion is commonly the most limiting. \citep{lemarie.debreu.ea_OM15} examined the
1350constraints for a range of time and space discretizations and provide the CFL stability
1351criteria for a range of advection schemes. The values for the Leap-Frog with Robert
1352asselin filter time-stepping (as used in NEMO) are reproduced in
1353\autoref{tab:ZDF_zad_Aimp_CFLcrit}. Treating the vertical advection implicitly can avoid these
1354restrictions but at the cost of large dispersive errors and, possibly, large numerical
1355viscosity. The adaptive-implicit vertical advection option provides a targetted use of the
1356implicit scheme only when and where potential breaches of the vertical CFL condition
1357occur. In many practical applications these events may occur remote from the main area of
1358interest or due to short-lived conditions such that the extra numerical diffusion or
1359viscosity does not greatly affect the overall solution. With such applications, setting:
1360\forcode{ln_zad_Aimp=.true.} should allow much longer model timesteps to be used whilst
1361retaining the accuracy of the high order explicit schemes over most of the domain.
1364  \centering
1365  % \begin{tabular}{cp{70pt}cp{70pt}cp{70pt}cp{70pt}}
1366  \begin{tabular}{r|ccc}
1367    \hline
1368    spatial discretization  & 2$^nd$ order centered & 3$^rd$ order upwind & 4$^th$ order compact \\
1369    advective CFL criterion &                 0.904 &              0.472  &                0.522 \\
1370    \hline
1371  \end{tabular}
1372  \caption[Advective CFL criteria for the leapfrog with Robert Asselin filter time-stepping]{
1373    The advective CFL criteria for a range of spatial discretizations for
1374    the leapfrog with Robert Asselin filter time-stepping
1375    ($\nu=0.1$) as given in \citep{lemarie.debreu.ea_OM15}.}
1376  \label{tab:ZDF_zad_Aimp_CFLcrit}
1379In particular, the advection scheme remains explicit everywhere except where and when
1380local vertical velocities exceed a threshold set just below the explicit stability limit.
1381Once the threshold is reached a tapered transition towards an implicit scheme is used by
1382partitioning the vertical velocity into a part that can be treated explicitly and any
1383excess that must be treated implicitly. The partitioning is achieved via a Courant-number
1384dependent weighting algorithm as described in \citep{shchepetkin_OM15}.
1386The local cell Courant number ($Cu$) used for this partitioning is:
1389  \label{eq:ZDF_Eqn_zad_Aimp_Courant}
1390  \begin{split}
1391    Cu &= {2 \rdt \over e^n_{3t_{ijk}}} \bigg (\big [ \texttt{Max}(w^n_{ijk},0.0) - \texttt{Min}(w^n_{ijk+1},0.0) \big ]    \\
1392       &\phantom{=} +\big [ \texttt{Max}(e_{{2_u}ij}e^n_{{3_{u}}ijk}u^n_{ijk},0.0) - \texttt{Min}(e_{{2_u}i-1j}e^n_{{3_{u}}i-1jk}u^n_{i-1jk},0.0) \big ]
1393                     \big / e_{{1_t}ij}e_{{2_t}ij}            \\
1394       &\phantom{=} +\big [ \texttt{Max}(e_{{1_v}ij}e^n_{{3_{v}}ijk}v^n_{ijk},0.0) - \texttt{Min}(e_{{1_v}ij-1}e^n_{{3_{v}}ij-1k}v^n_{ij-1k},0.0) \big ]
1395                     \big / e_{{1_t}ij}e_{{2_t}ij} \bigg )    \\
1396  \end{split}
1399\noindent and the tapering algorithm follows \citep{shchepetkin_OM15} as:
1402  \label{eq:ZDF_Eqn_zad_Aimp_partition}
1403Cu_{min} &= 0.15 \nonumber \\
1404Cu_{max} &= 0.3  \nonumber \\
1405Cu_{cut} &= 2Cu_{max} - Cu_{min} \nonumber \\
1406Fcu    &= 4Cu_{max}*(Cu_{max}-Cu_{min}) \nonumber \\
1407\cf &=
1408     \begin{cases}
1409        0.0                                                        &\text{if $Cu \leq Cu_{min}$} \\
1410        (Cu - Cu_{min})^2 / (Fcu +  (Cu - Cu_{min})^2)             &\text{else if $Cu < Cu_{cut}$} \\
1411        (Cu - Cu_{max}) / Cu                                       &\text{else}
1412     \end{cases}
1416  \centering
1417  \includegraphics[width=0.66\textwidth]{Fig_ZDF_zad_Aimp_coeff}
1418  \caption[Partitioning coefficient used to partition vertical velocities into parts]{
1419    The value of the partitioning coefficient (\cf) used to partition vertical velocities into
1420    parts to be treated implicitly and explicitly for a range of typical Courant numbers
1421    (\forcode{ln_zad_Aimp=.true.}).}
1422  \label{fig:ZDF_zad_Aimp_coeff}
1425\noindent The partitioning coefficient is used to determine the part of the vertical
1426velocity that must be handled implicitly ($w_i$) and to subtract this from the total
1427vertical velocity ($w_n$) to leave that which can continue to be handled explicitly:
1430  \label{eq:ZDF_Eqn_zad_Aimp_partition2}
1431    w_{i_{ijk}} &= \cf_{ijk} w_{n_{ijk}}     \nonumber \\
1432    w_{n_{ijk}} &= (1-\cf_{ijk}) w_{n_{ijk}}
1435\noindent Note that the coefficient is such that the treatment is never fully implicit;
1436the three cases from \autoref{eq:ZDF_Eqn_zad_Aimp_partition} can be considered as:
1437fully-explicit; mixed explicit/implicit and mostly-implicit.  With the settings shown the
1438coefficient (\cf) varies as shown in \autoref{fig:ZDF_zad_Aimp_coeff}. Note with these values
1439the $Cu_{cut}$ boundary between the mixed implicit-explicit treatment and 'mostly
1440implicit' is 0.45 which is just below the stability limited given in
1441\autoref{tab:ZDF_zad_Aimp_CFLcrit}  for a 3rd order scheme.
1443The $w_i$ component is added to the implicit solvers for the vertical mixing in
1444\mdl{dynzdf} and \mdl{trazdf} in a similar way to \citep{shchepetkin_OM15}.  This is
1445sufficient for the flux-limited advection scheme (\forcode{ln_traadv_mus}) but further
1446intervention is required when using the flux-corrected scheme (\forcode{ln_traadv_fct}).
1447For these schemes the implicit upstream fluxes must be added to both the monotonic guess
1448and to the higher order solution when calculating the antidiffusive fluxes. The implicit
1449vertical fluxes are then removed since they are added by the implicit solver later on.
1451The adaptive-implicit vertical advection option is new to NEMO at v4.0 and has yet to be
1452used in a wide range of simulations. The following test simulation, however, does illustrate
1453the potential benefits and will hopefully encourage further testing and feedback from users:
1456  \centering
1457  \includegraphics[width=0.66\textwidth]{Fig_ZDF_zad_Aimp_overflow_frames}
1458  \caption[OVERFLOW: time-series of temperature vertical cross-sections]{
1459    A time-series of temperature vertical cross-sections for the OVERFLOW test case.
1460    These results are for the default settings with \forcode{nn_rdt=10.0} and
1461    without adaptive implicit vertical advection (\forcode{ln_zad_Aimp=.false.}).}
1462  \label{fig:ZDF_zad_Aimp_overflow_frames}
1465%% =================================================================================================
1466\subsection{Adaptive-implicit vertical advection in the OVERFLOW test-case}
1468The \href{\_cases.html\#overflow}{OVERFLOW test case}
1469provides a simple illustration of the adaptive-implicit advection in action. The example here differs from the basic test case
1470by only a few extra physics choices namely:
1473     ln_dynldf_OFF = .false.
1474     ln_dynldf_lap = .true.
1475     ln_dynldf_hor = .true.
1476     ln_zdfnpc     = .true.
1477     ln_traadv_fct = .true.
1478        nn_fct_h   =  2
1479        nn_fct_v   =  2
1482\noindent which were chosen to provide a slightly more stable and less noisy solution. The
1483result when using the default value of \forcode{nn_rdt=10.} without adaptive-implicit
1484vertical velocity is illustrated in \autoref{fig:ZDF_zad_Aimp_overflow_frames}. The mass of
1485cold water, initially sitting on the shelf, moves down the slope and forms a
1486bottom-trapped, dense plume. Even with these extra physics choices the model is close to
1487stability limits and attempts with \forcode{nn_rdt=30.} will fail after about 5.5 hours
1488with excessively high horizontal velocities. This time-scale corresponds with the time the
1489plume reaches the steepest part of the topography and, although detected as a horizontal
1490CFL breach, the instability originates from a breach of the vertical CFL limit. This is a good
1491candidate, therefore, for use of the adaptive-implicit vertical advection scheme.
1493The results with \forcode{ln_zad_Aimp=.true.} and a variety of model timesteps
1494are shown in \autoref{fig:ZDF_zad_Aimp_overflow_all_rdt} (together with the equivalent
1495frames from the base run).  In this simple example the use of the adaptive-implicit
1496vertcal advection scheme has enabled a 12x increase in the model timestep without
1497significantly altering the solution (although at this extreme the plume is more diffuse
1498and has not travelled so far).  Notably, the solution with and without the scheme is
1499slightly different even with \forcode{nn_rdt=10.}; suggesting that the base run was
1500close enough to instability to trigger the scheme despite completing successfully.
1501To assist in diagnosing how active the scheme is, in both location and time, the 3D
1502implicit and explicit components of the vertical velocity are available via XIOS as
1503\texttt{wimp} and \texttt{wexp} respectively.  Likewise, the partitioning coefficient
1504(\cf) is also available as \texttt{wi\_cff}. For a quick oversight of
1505the schemes activity the global maximum values of the absolute implicit component
1506of the vertical velocity and the partitioning coefficient are written to the netCDF
1507version of the run statistics file (\texttt{}) if this is active (see
1508\autoref{sec:MISC_opt} for activation details).
1510\autoref{fig:ZDF_zad_Aimp_maxCf} shows examples of the maximum partitioning coefficient for
1511the various overflow tests.  Note that the adaptive-implicit vertical advection scheme is
1512active even in the base run with \forcode{nn_rdt=10.0s} adding to the evidence that the
1513test case is close to stability limits even with this value. At the larger timesteps, the
1514vertical velocity is treated mostly implicitly at some location throughout the run. The
1515oscillatory nature of this measure appears to be linked to the progress of the plume front
1516as each cusp is associated with the location of the maximum shifting to the adjacent cell.
1517This is illustrated in \autoref{fig:ZDF_zad_Aimp_maxCf_loc} where the i- and k- locations of the
1518maximum have been overlaid for the base run case.
1521\noindent Only limited tests have been performed in more realistic configurations. In the
1522ORCA2\_ICE\_PISCES reference configuration the scheme does activate and passes
1523restartability and reproducibility tests but it is unable to improve the model's stability
1524enough to allow an increase in the model time-step. A view of the time-series of maximum
1525partitioning coefficient (not shown here)  suggests that the default time-step of 5400s is
1526already pushing at stability limits, especially in the initial start-up phase. The
1527time-series does not, however, exhibit any of the 'cuspiness' found with the overflow
1531\noindent A short test with an eORCA1 configuration promises more since a test using a
1532time-step of 3600s remains stable with \forcode{ln_zad_Aimp=.true.} whereas the
1533time-step is limited to 2700s without.
1536  \centering
1537  \includegraphics[width=0.66\textwidth]{Fig_ZDF_zad_Aimp_overflow_all_rdt}
1538  \caption[OVERFLOW: sample temperature vertical cross-sections from mid- and end-run]{
1539    Sample temperature vertical cross-sections from mid- and end-run using
1540    different values for \forcode{nn_rdt} and with or without adaptive implicit vertical advection.
1541    Without the adaptive implicit vertical advection
1542    only the run with the shortest timestep is able to run to completion.
1543    Note also that the colour-scale has been chosen to confirm that
1544    temperatures remain within the original range of 10$^o$ to 20$^o$.}
1545  \label{fig:ZDF_zad_Aimp_overflow_all_rdt}
1549  \centering
1550  \includegraphics[width=0.66\textwidth]{Fig_ZDF_zad_Aimp_maxCf}
1551  \caption[OVERFLOW: maximum partitioning coefficient during a series of test runs]{
1552    The maximum partitioning coefficient during a series of test runs with
1553    increasing model timestep length.
1554    At the larger timesteps,
1555    the vertical velocity is treated mostly implicitly at some location throughout the run.}
1556  \label{fig:ZDF_zad_Aimp_maxCf}
1560  \centering
1561  \includegraphics[width=0.66\textwidth]{Fig_ZDF_zad_Aimp_maxCf_loc}
1562  \caption[OVERFLOW: maximum partitioning coefficient for the case overlaid]{
1563    The maximum partitioning coefficient for the \forcode{nn_rdt=10.0} case overlaid with
1564    information on the gridcell i- and k-locations of the maximum value.}
1565  \label{fig:ZDF_zad_Aimp_maxCf_loc}
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