# Changeset 11608

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Timestamp:
2019-09-27T12:24:49+02:00 (22 months ago)
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Review of "Model Basics" chapter

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1 edited

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 r11598 Release & Author(s) & Modifications \\ \hline {\em   4.0} & {\em ...} & {\em ...} \\ {\em   3.6} & {\em ...} & {\em ...} \\ {\em   3.4} & {\em ...} & {\em ...} \\ {\em <=3.4} & {\em ...} & {\em ...} {\em   4.0} & {\em Mike Bell                       } & {\em Update       } \\ {\em   3.6} & {\em Gurvan Madec                    } & {\em Minor changes} \\ {\em <=3.4} & {\em Gurvan Madec and Steven Alderson} & {\em First version} \\ \end{tabularx} } plus the following additional assumptions made from scale considerations: \begin{enumerate} \item \textit{spherical Earth approximation}: the geopotential surfaces are assumed to be oblate spheriods that follow the Earth's bulge; these spheroids are approximated by spheres with gravity locally vertical (parallel to the Earth's radius) and independent of latitude \begin{labeling}{Neglect of additional Coriolis terms} \item [\textit{Spherical Earth approximation}] The geopotential surfaces are assumed to be oblate spheroids that follow the Earth's bulge; these spheroids are approximated by spheres with gravity locally vertical (parallel to the Earth's radius) and independent of latitude \citep[][section 2]{white.hoskins.ea_QJRMS05}. \item \textit{thin-shell approximation}: the ocean depth is neglected compared to the earth's radius \item \textit{turbulent closure hypothesis}: the turbulent fluxes \item [\textit{Thin-shell approximation}] The ocean depth is neglected compared to the earth's radius \item [\textit{Turbulent closure hypothesis}] The turbulent fluxes (which represent the effect of small scale processes on the large-scale) are expressed in terms of large-scale features \item \textit{Boussinesq hypothesis}: density variations are neglected except in their contribution to the buoyancy force \item [\textit{Boussinesq hypothesis}] Density variations are neglected except in their contribution to the buoyancy force \begin{equation} \label{eq:MB_PE_eos} \rho = \rho \ (T,S,p) \end{equation} \item \textit{Hydrostatic hypothesis}: the vertical momentum equation is reduced to a balance between the vertical pressure gradient and the buoyancy force \item [\textit{Hydrostatic hypothesis}] The vertical momentum equation is reduced to a balance between the vertical pressure gradient and the buoyancy force (this removes convective processes from the initial Navier-Stokes equations and so convective processes must be parameterized instead) \pd[p]{z} = - \rho \ g \end{equation} \item \textit{Incompressibility hypothesis}: the three dimensional divergence of the velocity vector $\vect U$ is assumed to be zero. \item [\textit{Incompressibility hypothesis}] The three dimensional divergence of the velocity vector $\vect U$ is assumed to be zero. \begin{equation} \label{eq:MB_PE_continuity} \nabla \cdot \vect U = 0 \end{equation} \item \textit{Neglect of additional Coriolis terms}: the Coriolis terms that vary with the cosine of latitude are neglected. These terms may be non-negligible where the Brunt-Vaisala frequency $N$ is small, either in the deep ocean or in the sub-mesoscale motions of the mixed layer, or near the equator \citep[][section 1]{white.hoskins.ea_QJRMS05}. They can be consistently included as part of the ocean dynamics \citep[][section 3(d)]{white.hoskins.ea_QJRMS05} and are retained in the MIT ocean model. \end{enumerate} \item [\textit{Neglect of additional Coriolis terms}] The Coriolis terms that vary with the cosine of latitude are neglected. These terms may be non-negligible where the Brunt-V\"{a}is\"{a}l\"{a} frequency $N$ is small, either in the deep ocean or in the sub-mesoscale motions of the mixed layer, or near the equator \citep[][section 1]{white.hoskins.ea_QJRMS05}. They can be consistently included as part of the ocean dynamics \citep[][section 3(d)]{white.hoskins.ea_QJRMS05} and are retained in the MIT ocean model. \end{labeling} Because the gravitational force is so dominant in the equations of large-scale motions, $k$ is the local upward vector and $(i,j)$ are two vectors orthogonal to $k$, \ie\ tangent to the geopotential surfaces. Let us define the following variables: $\vect U$ the vector velocity, $\vect U = \vect U_h + w \, \vect k$ Let us define the following variables: $\vect U$ the vector velocity, $\vect U = \vect U_h + w \, \vect k$ (the subscript $h$ denotes the local horizontal vector, \ie\ over the $(i,j)$ plane), $T$ the potential temperature, $S$ the salinity, $\rho$ the \textit{in situ} density. \label{eq:MB_PE} \begin{gather} \intertext{$-$ the momentum balance} \shortintertext{$-$ the momentum balance} \label{eq:MB_PE_dyn} \pd[\vect U_h]{t} = - \lt[ (\nabla \times \vect U) \times \vect U + \frac{1}{2} \nabla \lt( \vect U^2 \rt) \rt]_h - f \; k \times \vect U_h - \frac{1}{\rho_o} \nabla_h p + \vect D^{\vect U} + \vect F^{\vect U} \\ \intertext{$-$ the heat and salt conservation equations} \pd[\vect U_h]{t} = - \lt[ (\nabla \times \vect U) \times \vect U + \frac{1}{2} \nabla \lt( \vect U^2 \rt) \rt]_h - f \; k \times \vect U_h - \frac{1}{\rho_o} \nabla_h p + \vect D^{\vect U} + \vect F^{\vect U} \shortintertext{$-$ the heat and salt conservation equations} \label{eq:MB_PE_tra_T} \pd[T]{t} = - \nabla \cdot (T \ \vect U) + D^T + F^T \\ (\autoref{eq:MB_PE_eos}), $\rho_o$ is a reference density, $p$ the pressure, $f = 2 \vect \Omega \cdot k$ is the Coriolis acceleration (where $\vect \Omega$ is the Earth's angular velocity vector), and $g$ is the gravitational acceleration. (where $\vect \Omega$ is the Earth's angular velocity vector), and $g$ is the gravitational acceleration. $\vect D^{\vect U}$, $D^T$ and $D^S$ are the parameterisations of small-scale physics for momentum, temperature and salinity, and $\vect F^{\vect U}$, $F^T$ and $F^S$ surface forcing terms. Their nature and formulation are discussed in \autoref{sec:MB_zdf_ldf} and \autoref{subsec:MB_boundary_condition}. Their nature and formulation are discussed in \autoref{sec:MB_zdf_ldf} and \autoref{subsec:MB_boundary_condition}. %% ================================================================================================= where $H$ is the depth of the ocean bottom and $\eta$ is the height of the sea surface (discretisation can introduce additional artificial side-wall'' boundaries). Both $H$ and $\eta$ are referenced to a surface of constant geopotential (\ie\ a mean sea surface height) on which $z = 0$. (\autoref{fig:MB_ocean_bc}). Through these two boundaries, the ocean can exchange fluxes of heat, fresh water, salt, and momentum with the solid earth, the continental margins, the sea ice and the atmosphere. However, some of these fluxes are so weak that even on climatic time scales of thousands of years they can be neglected. Both $H$ and $\eta$ are referenced to a surface of constant geopotential (\ie\ a mean sea surface height) on which $z = 0$ (\autoref{fig:MB_ocean_bc}). Through these two boundaries, the ocean can exchange fluxes of heat, fresh water, salt, and momentum with the solid earth, the continental margins, the sea ice and the atmosphere. However, some of these fluxes are so weak that even on climatic time scales of thousands of years they can be neglected. In the following, we briefly review the fluxes exchanged at the interfaces between the ocean and the other components of the earth system. \begin{figure}[!ht] \begin{figure} \centering \includegraphics[width=0.66\textwidth]{Fig_I_ocean_bc} \begin{description} \item [Land - ocean interface:]  the major flux between continental margins and the ocean is a mass exchange of fresh water through river runoff. \item [Land - ocean] The major flux between continental margins and the ocean is a mass exchange of fresh water through river runoff. Such an exchange modifies the sea surface salinity especially in the vicinity of major river mouths. It can be neglected for short range integrations but has to be taken into account for long term integrations as It can be neglected for short range integrations but has to be taken into account for long term integrations as it influences the characteristics of water masses formed (especially at high latitudes). It is required in order to close the water cycle of the climate system. It is usually specified as a fresh water flux at the air-sea interface in the vicinity of river mouths. \item [Solid earth - ocean interface:]  heat and salt fluxes through the sea floor are small, except in special areas of little extent. They are usually neglected in the model \footnote{ It is usually specified as a fresh water flux at the air-sea interface in the vicinity of river mouths. \item [Solid earth - ocean] Heat and salt fluxes through the sea floor are small, except in special areas of little extent. They are usually neglected in the model \footnote{ In fact, it has been shown that the heat flux associated with the solid Earth cooling (\ie\ the geothermal heating) is not negligible for the thermohaline circulation of the world ocean (see \autoref{subsec:TRA_bbc}). (\ie\ the geothermal heating) is not negligible for the thermohaline circulation of the world ocean (see \autoref{subsec:TRA_bbc}). }. The boundary condition is thus set to no flux of heat and salt across solid boundaries. For momentum, the situation is different. There is no flow across solid boundaries, \ie\ the velocity normal to the ocean bottom and coastlines is zero (in other words, the bottom velocity is parallel to solid boundaries). This kinematic boundary condition can be expressed as: For momentum, the situation is different. There is no flow across solid boundaries, \ie\ the velocity normal to the ocean bottom and coastlines is zero (in other words, the bottom velocity is parallel to solid boundaries). This kinematic boundary condition can be expressed as: \begin{equation} \label{eq:MB_w_bbc} In addition, the ocean exchanges momentum with the earth through frictional processes. Such momentum transfer occurs at small scales in a boundary layer. It must be parameterized in terms of turbulent fluxes using bottom and/or lateral boundary conditions. It must be parameterized in terms of turbulent fluxes using bottom and/or lateral boundary conditions. Its specification depends on the nature of the physical parameterisation used for $\vect D^{\vect U}$ in \autoref{eq:MB_PE_dyn}. It is discussed in \autoref{eq:MB_zdf}.% and Chap. III.6 to 9. \item [Atmosphere - ocean interface:]  the kinematic surface condition plus the mass flux of fresh water PE (the precipitation minus evaporation budget) leads to: It is discussed in \autoref{eq:MB_zdf}. % and Chap. III.6 to 9. \item [Atmosphere - ocean] The kinematic surface condition plus the mass flux of fresh water PE (the precipitation minus evaporation budget) leads to: $% \label{eq:MB_w_sbc} w = \pd[\eta]{t} + \lt. \vect U_h \rt|_{z = \eta} \cdot \nabla_h (\eta) + P - E$ The dynamic boundary condition, neglecting the surface tension (which removes capillary waves from the system) leads to the continuity of pressure across the interface $z = \eta$. The dynamic boundary condition, neglecting the surface tension (which removes capillary waves from the system) leads to the continuity of pressure across the interface $z = \eta$. The atmosphere and ocean also exchange horizontal momentum (wind stress), and heat. \item [Sea ice - ocean interface:]  the ocean and sea ice exchange heat, salt, fresh water and momentum. \item [Sea ice - ocean] The ocean and sea ice exchange heat, salt, fresh water and momentum. The sea surface temperature is constrained to be at the freezing point at the interface. Sea ice salinity is very low ($\sim4-6 \, psu$) compared to those of the ocean ($\sim34 \, psu$). The cycle of freezing/melting is associated with fresh water and salt fluxes that cannot be neglected. The cycle of freezing/melting is associated with fresh water and salt fluxes that cannot be neglected. \end{description} \] Two strategies can be considered for the surface pressure term: $(a)$ introduce of a  new variable $\eta$, the free-surface elevation, \begin{enumerate*}[label={(\alph*)}] \item introduce of a new variable $\eta$, the free-surface elevation, for which a prognostic equation can be established and solved; $(b)$ assume that the ocean surface is a rigid lid, \item assume that the ocean surface is a rigid lid, on which the pressure (or its horizontal gradient) can be diagnosed. \end{enumerate*} When the former strategy is used, one solution of the free-surface elevation consists of the excitation of external gravity waves. modifies certain other longwave dynamics (\eg\ barotropic Rossby or planetary waves). The rigid-lid hypothesis is an obsolescent feature in modern OGCMs. It has been available until the release 3.1 of \NEMO, and it has been removed in release 3.2 and followings. It has been available until the release 3.1 of \NEMO, and it has been removed in release 3.2 and followings. Only the free surface formulation is now described in this document (see the next sub-section). In the free surface formulation, a variable $\eta$, the sea-surface height, is introduced which describes the shape of the air-sea interface. This variable is solution of a prognostic equation which is established by forming the vertical average of the kinematic surface condition (\autoref{eq:MB_w_bbc}): This variable is solution of a prognostic equation which is established by forming the vertical average of the kinematic surface condition (\autoref{eq:MB_w_bbc}): \begin{equation} \label{eq:MB_ssh} \pd[\eta]{t} = - D + P - E \quad \text{where} \quad D = \nabla \cdot \lt[ (H + \eta) \; \overline{U}_h \, \rt] \end{equation} and using (\autoref{eq:MB_PE_hydrostatic}) the surface pressure is given by: $p_s = \rho \, g \, \eta$. Allowing the air-sea interface to move introduces the external gravity waves (EGWs) as and using (\autoref{eq:MB_PE_hydrostatic}) the surface pressure is given by: $p_s = \rho \, g \, \eta$. Allowing the air-sea interface to move introduces the \textbf{E}xternal \textbf{G}ravity \textbf{W}aves (EGWs) as a class of solution of the primitive equations. These waves are barotropic (\ie\ nearly independent of depth) and their phase speed is quite high. Two choices can be made regarding the implementation of the free surface in the model, depending on the physical processes of interest. $\bullet$ If one is interested in EGWs, in particular the tides and their interaction with the baroclinic structure of the ocean (internal waves) possibly in shallow seas, then a non linear free surface is the most appropriate. This means that no approximation is made in \autoref{eq:MB_ssh} and that the variation of the ocean volume is fully taken into account. Note that in order to study the fast time scales associated with EGWs it is necessary to minimize time filtering effects (use an explicit time scheme with very small time step, or a split-explicit scheme with reasonably small time step, see \autoref{subsec:DYN_spg_exp} or \autoref{subsec:DYN_spg_ts}). $\bullet$ If one is not interested in EGW but rather sees them as high frequency noise, it is possible to apply an explicit filter to slow down the fastest waves while not altering the slow barotropic Rossby waves. If further, an approximative conservation of heat and salt contents is sufficient for the problem solved, then it is sufficient to solve a linearized version of \autoref{eq:MB_ssh}, which still allows to take into account freshwater fluxes applied at the ocean surface \citep{roullet.madec_JGR00}. Nevertheless, with the linearization, an exact conservation of heat and salt contents is lost. The filtering of EGWs in models with a free surface is usually a matter of discretisation of the temporal derivatives, \begin{itemize} \item If one is interested in EGWs, in particular the tides and their interaction with the baroclinic structure of the ocean (internal waves) possibly in shallow seas, then a non linear free surface is the most appropriate. This means that no approximation is made in \autoref{eq:MB_ssh} and that the variation of the ocean volume is fully taken into account. Note that in order to study the fast time scales associated with EGWs it is necessary to minimize time filtering effects (use an explicit time scheme with very small time step, or a split-explicit scheme with reasonably small time step, see \autoref{subsec:DYN_spg_exp} or \autoref{subsec:DYN_spg_ts}). \item If one is not interested in EGWs but rather sees them as high frequency noise, it is possible to apply an explicit filter to slow down the fastest waves while not altering the slow barotropic Rossby waves. If further, an approximative conservation of heat and salt contents is sufficient for the problem solved, then it is sufficient to solve a linearized version of \autoref{eq:MB_ssh}, which still allows to take into account freshwater fluxes applied at the ocean surface \citep{roullet.madec_JGR00}. Nevertheless, with the linearization, an exact conservation of heat and salt contents is lost. \end{itemize} The filtering of EGWs in models with a free surface is usually a matter of discretisation of the temporal derivatives, using a split-explicit method \citep{killworth.webb.ea_JPO91, zhang.endoh_JGR92} or the implicit scheme \citep{dukowicz.smith_JGR94} or the addition of a filtering force in the momentum equation \citep{roullet.madec_JGR00}. With the present release, \NEMO\  offers the choice between an explicit free surface (see \autoref{subsec:DYN_spg_exp}) or a split-explicit scheme strongly inspired the one proposed by \citet{shchepetkin.mcwilliams_OM05} (see \autoref{subsec:DYN_spg_ts}). %% ================================================================================================= \section{Curvilinear \textit{z-}coordinate system} the implicit scheme \citep{dukowicz.smith_JGR94} or the addition of a filtering force in the momentum equation \citep{roullet.madec_JGR00}. With the present release, \NEMO\ offers the choice between an explicit free surface (see \autoref{subsec:DYN_spg_exp}) or a split-explicit scheme strongly inspired the one proposed by \citet{shchepetkin.mcwilliams_OM05} (see \autoref{subsec:DYN_spg_ts}). %% ================================================================================================= \section{Curvilinear \textit{z}-coordinate system} \label{sec:MB_zco} A solution consists of introducing an appropriate coordinate transformation that shifts the singular point onto land \citep{madec.imbard_CD96, murray_JCP96}. As a consequence, it is important to solve the primitive equations in various curvilinear coordinate systems. An efficient way of introducing an appropriate coordinate transform can be found when using a tensorial formalism. As a consequence, it is important to solve the primitive equations in various curvilinear coordinate systems. An efficient way of introducing an appropriate coordinate transform can be found when using a tensorial formalism. This formalism is suited to any multidimensional curvilinear coordinate system. Ocean modellers mainly use three-dimensional orthogonal grids on the sphere (spherical earth approximation), with preservation of the local vertical. Here we give the simplified equations for this particular case. The general case is detailed by \citet{eiseman.stone_SR80} in their survey of the conservation laws of fluid dynamics. Ocean modellers mainly use three-dimensional orthogonal grids on the sphere (spherical earth approximation), with preservation of the local vertical. Here we give the simplified equations for this particular case. The general case is detailed by \citet{eiseman.stone_SR80} in their survey of the conservation laws of fluid dynamics. Let $(i,j,k)$ be a set of orthogonal curvilinear coordinates on \begin{equation} \label{eq:MB_scale_factors} \begin{aligned} e_1 &= (a + z) \lt[ \lt( \pd[\lambda]{i} \cos \varphi \rt)^2 + \lt( \pd[\varphi]{i} \rt)^2 \rt]^{1/2} \\ e_2 &= (a + z) \lt[ \lt( \pd[\lambda]{j} \cos \varphi \rt)^2 + \lt( \pd[\varphi]{j} \rt)^2 \rt]^{1/2} \\ e_3 &= \lt( \pd[z]{k} \rt) \end{aligned} e_1 = (a + z) \lt[ \lt( \pd[\lambda]{i} \cos \varphi \rt)^2 + \lt( \pd[\varphi]{i} \rt)^2 \rt]^{1/2} \quad e_2 = (a + z) \lt[ \lt( \pd[\lambda]{j} \cos \varphi \rt)^2 + \lt( \pd[\varphi]{j} \rt)^2 \rt]^{1/2} \quad e_3 = \lt( \pd[z]{k} \rt) \end{equation} \begin{figure}[!tb] \begin{figure} \centering \includegraphics[width=0.66\textwidth]{Fig_I_earth_referential} \includegraphics[width=0.33\textwidth]{Fig_I_earth_referential} \caption[Geographical and curvilinear coordinate systems]{ the geographical coordinate system $(\lambda,\varphi,z)$ and the curvilinear \begin{subequations} % \label{eq:MB_discrete_operators} \begin{gather} \begin{align} \label{eq:MB_grad} \nabla q =   \frac{1}{e_1} \pd[q]{i} \; \vect i + \frac{1}{e_2} \pd[q]{j} \; \vect j + \frac{1}{e_3} \pd[q]{k} \; \vect k \\ \nabla q &=   \frac{1}{e_1} \pd[q]{i} \; \vect i + \frac{1}{e_2} \pd[q]{j} \; \vect j + \frac{1}{e_3} \pd[q]{k} \; \vect k \\ \label{eq:MB_div} \nabla \cdot \vect A =   \frac{1}{e_1 \; e_2} \lt[ \pd[(e_2 \; a_1)]{\partial i} + \pd[(e_1 \; a_2)]{j} \rt] + \frac{1}{e_3} \lt[ \pd[a_3]{k} \rt] \end{gather} \begin{multline} \nabla \cdot \vect A &=   \frac{1}{e_1 \; e_2} \lt[ \pd[(e_2 \; a_1)]{\partial i} + \pd[(e_1 \; a_2)]{j} \rt] + \frac{1}{e_3} \lt[ \pd[a_3]{k} \rt] \\ \label{eq:MB_curl} \nabla \times \vect{A} =   \lt[ \frac{1}{e_2} \pd[a_3]{j} - \frac{1}{e_3} \pd[a_2]{k}   \rt] \vect i \\ + \lt[ \frac{1}{e_3} \pd[a_1]{k} - \frac{1}{e_1} \pd[a_3]{i}   \rt] \vect j \\ + \frac{1}{e_1 e_2} \lt[ \pd[(e_2 a_2)]{i} - \pd[(e_1 a_1)]{j} \rt] \vect k \end{multline} \begin{gather} \nabla \times \vect{A} &=   \lt[ \frac{1}{e_2} \pd[a_3]{j} - \frac{1}{e_3} \pd[a_2]{k}   \rt] \vect i + \lt[ \frac{1}{e_3} \pd[a_1]{k} - \frac{1}{e_1} \pd[a_3]{i}   \rt] \vect j + \frac{1}{e_1 e_2} \lt[ \pd[(e_2 a_2)]{i} - \pd[(e_1 a_1)]{j} \rt] \vect k \\ \label{eq:MB_lap} \Delta q = \nabla \cdot (\nabla q) \\ \Delta q &= \nabla \cdot (\nabla q) \\ \label{eq:MB_lap_vector} \Delta \vect A = \nabla (\nabla \cdot \vect A) - \nabla \times (\nabla \times \vect A) \end{gather} \Delta \vect A &= \nabla (\nabla \cdot \vect A) - \nabla \times (\nabla \times \vect A) \end{align} \end{subequations} where $q$ is a scalar quantity and $\vect A = (a_1,a_2,a_3)$ a vector in the $(i,j,k)$ coordinates system. where $q$ is a scalar quantity and $\vect A = (a_1,a_2,a_3)$ a vector in the $(i,j,k)$ coordinates system. %% ================================================================================================= In order to express the Primitive Equations in tensorial formalism, it is necessary to compute the horizontal component of the non-linear and viscous terms of the equation using \autoref{eq:MB_grad}) to \autoref{eq:MB_lap_vector}. Let us set $\vect U = (u,v,w) = \vect U_h + w \; \vect k$, the velocity in the $(i,j,k)$ coordinates system and define the relative vorticity $\zeta$ and the divergence of the horizontal velocity field $\chi$, by: it is necessary to compute the horizontal component of the non-linear and viscous terms of the equation using \autoref{eq:MB_grad}) to \autoref{eq:MB_lap_vector}. Let us set $\vect U = (u,v,w) = \vect U_h + w \; \vect k$, the velocity in the $(i,j,k)$ coordinates system, and define the relative vorticity $\zeta$ and the divergence of the horizontal velocity field $\chi$, by: \begin{gather} \label{eq:MB_curl_Uh} $e_3$  is a function of the single variable $k$, $NLT$ the nonlinear term of \autoref{eq:MB_PE_dyn} can be transformed as follows: \begin{alignat*}{2} &NLT &=   &\lt[ (\nabla \times {\vect U}) \times {\vect U} + \frac{1}{2} \nabla \lt( {\vect U}^2 \rt) \rt]_h \\ &    &=   &\lt( \begin{array}{*{20}c} \lt[ \frac{1}{e_3} \pd[u]{k} - \frac{1}{e_1} \pd[w]{i} \rt] w - \zeta \; v   \\ \zeta \; u - \lt[ \frac{1}{e_2} \pd[w]{j} - \frac{1}{e_3} \pd[v]{k} \rt] \ w \end{array} \rt) + \frac{1}{2} \lt( \begin{array}{*{20}c} \frac{1}{e_1} \pd[(u^2 + v^2 + w^2)]{i} \\ \frac{1}{e_2} \pd[(u^2 + v^2 + w^2)]{j} \end{array} \rt) \\ &    &=   &\lt( \begin{array}{*{20}c} -\zeta \; v \\ \zeta \; u \end{array} \rt) + \frac{1}{2} \lt( \begin{array}{*{20}c} \frac{1}{e_1} \pd[(u^2 + v^2)]{i} \\ \frac{1}{e_2} \pd[(u^2 + v^2)]{j} \end{array} \rt) \\ &    &  &+ \frac{1}{e_3} \lt( \begin{array}{*{20}c} w \; \pd[u]{k} \\ w \; \pd[v]{k} \end{array} \rt) - \lt( \begin{array}{*{20}c} \frac{w}{e_1} \pd[w]{i} - \frac{1}{2 e_1} \pd[w^2]{i} \\ \frac{w}{e_2} \pd[w]{j} - \frac{1}{2 e_2} \pd[w^2]{j} \end{array} \rt) \end{alignat*} The last term of the right hand side is obviously zero, and thus the nonlinear term of \autoref{eq:MB_PE_dyn} is written in the $(i,j,k)$ coordinate system: \begin{align*} NLT &= \lt[ (\nabla \times {\vect U}) \times {\vect U} + \frac{1}{2} \nabla \lt( {\vect U}^2 \rt) \rt]_h \\ &= \lt( \begin{array}{*{20}c} \lt[ \frac{1}{e_3} \pd[u]{k} - \frac{1}{e_1} \pd[w]{i} \rt] w - \zeta \; v   \\ \zeta \; u - \lt[ \frac{1}{e_2} \pd[w]{j} - \frac{1}{e_3} \pd[v]{k} \rt] \ w \end{array} \rt) + \frac{1}{2} \lt( \begin{array}{*{20}c} \frac{1}{e_1} \pd[(u^2 + v^2 + w^2)]{i} \\ \frac{1}{e_2} \pd[(u^2 + v^2 + w^2)]{j} \end{array} \rt) \\ &= \lt( \begin{array}{*{20}c} -\zeta \; v \\ \zeta \; u \end{array} \rt) + \frac{1}{2} \lt( \begin{array}{*{20}c} \frac{1}{e_1} \pd[(u^2 + v^2)]{i} \\ \frac{1}{e_2} \pd[(u^2 + v^2)]{j} \end{array} \rt) + \frac{1}{e_3} \lt( \begin{array}{*{20}c} w \; \pd[u]{k} \\ w \; \pd[v]{k} \end{array} \rt) - \lt( \begin{array}{*{20}c} \frac{w}{e_1} \pd[w]{i} - \frac{1}{2 e_1} \pd[w^2]{i} \\ \frac{w}{e_2} \pd[w]{j} - \frac{1}{2 e_2} \pd[w^2]{j} \end{array} \rt) \end{align*} The last term of the right hand side is obviously zero, and thus the \textbf{N}on\textbf{L}inear \textbf{T}erm ($NLT$) of \autoref{eq:MB_PE_dyn} is written in the $(i,j,k)$ coordinate system: \begin{equation} \label{eq:MB_vector_form} NLT =   \zeta \; \vect k \times \vect U_h + \frac{1}{2} \nabla_h \lt( \vect U_h^2 \rt) + \frac{1}{e_3} w \pd[\vect U_h]{k} NLT = \zeta \; \vect k \times \vect U_h + \frac{1}{2} \nabla_h \lt( \vect U_h^2 \rt) + \frac{1}{e_3} w \pd[\vect U_h]{k} \end{equation} For some purposes, it can be advantageous to write this term in the so-called flux form, \ie\ to write it as the divergence of fluxes. For example, the first component of \autoref{eq:MB_vector_form} (the $i$-component) is transformed as follows: \begin{alignat*}{2} For example, the first component of \autoref{eq:MB_vector_form} (the $i$-component) is transformed as follows: \begin{alignat*}{3} &NLT_i &= &- \zeta \; v + \frac{1}{2 \; e_1} \pd[ (u^2 + v^2) ]{i} + \frac{1}{e_3} w \ \pd[u]{k} \\ &      &=  &\frac{1}{e_1 \; e_2} \lt( -v \pd[(e_2 \, v)]{i} + v \pd[(e_1 \, u)]{j} \rt) + \frac{1}{e_1 e_2} \lt( e_2 \; u \pd[u]{i} + e_2 \; v \pd[v]{i} \rt) \\ &      & &+ \frac{1}{e_3} \lt( w \; \pd[u]{k} \rt) \\ &      &=  &\frac{1}{e_1 \; e_2} \lt[ - \lt( v^2 \pd[e_2]{i} + e_2 \, v \pd[v]{i} \rt) + \lt( \pd[ \lt( e_1 \, u \, v \rt)]{j} -         e_1 \, u \pd[v]{j} \rt) \rt. \\ &      &                       &\lt. + \lt( \pd[ \lt( e_2 \, u \, u \rt)]{i} - u \pd[ \lt( e_2 u \rt)]{i} \rt) + e_2 v \pd[v]{i}                                                         \rt] \\ &      &= &\frac{1}{e_1 \; e_2} \lt( -v \pd[(e_2 \, v)]{i} + v \pd[(e_1 \, u)]{j} \rt) + \frac{1}{e_1 e_2} \lt( e_2 \; u \pd[u]{i} + e_2 \; v \pd[v]{i} \rt) + \frac{1}{e_3} \lt( w \; \pd[u]{k} \rt) \\ &      &= &\frac{1}{e_1 \; e_2} \lt[ - \lt( v^2 \pd[e_2]{i} + e_2 \, v \pd[v]{i} \rt) + \lt( \pd[ \lt( e_1 \, u \, v \rt)]{j} - e_1 \, u \pd[v]{j} \rt) \rt. \lt. + \lt( \pd[ \lt( e_2 \, u \, u \rt)]{i} - u \pd[ \lt( e_2 u \rt)]{i} \rt) + e_2 v \pd[v]{i} \rt] \\ &      & &+ \frac{1}{e_3} \lt( \pd[(w \, u)]{k} - u \pd[w]{k} \rt) \\ &      &=  &\frac{1}{e_1 \; e_2} \lt( \pd[(e_2 \, u \, u)]{i} + \pd[(e_1 \, u \, v)]{j} \rt) + \frac{1}{e_3} \pd[(w \, u)]{k} \\ &      & &+ \frac{1}{e_1 e_2} \lt[ - u \lt( \pd[(e_1 v)]{j} - v \, \pd[e_1]{j} \rt) - u \pd[(e_2 u)]{i}                              \rt] - \frac{1}{e_3} \pd[w]{k} u \\ &      &= &\frac{1}{e_1 \; e_2} \lt( \pd[(e_2 \, u \, u)]{i} + \pd[(e_1 \, u \, v)]{j} \rt) + \frac{1}{e_3} \pd[(w \, u)]{k} + \frac{1}{e_1 e_2} \lt[ - u \lt( \pd[(e_1 v)]{j} - v \, \pd[e_1]{j} \rt) - u \pd[(e_2 u)]{i} \rt] - \frac{1}{e_3} \pd[w]{k} u \\ &      & &+ \frac{1}{e_1 e_2} \lt( - v^2 \pd[e_2]{i} \rt) \\ &      &= &\nabla \cdot (\vect U \, u) - (\nabla \cdot \vect U) \ u + \frac{1}{e_1 e_2} \lt( -v^2 \pd[e_2]{i} + u v \, \pd[e_1]{j} \rt) \\ \intertext{as $\nabla \cdot {\vect U} \; = 0$ (incompressibility) it becomes:} &      &= &\nabla \cdot (\vect U \, u) - (\nabla \cdot \vect U) \ u + \frac{1}{e_1 e_2} \lt( -v^2 \pd[e_2]{i} + u v \, \pd[e_1]{j} \rt) \\ \shortintertext{as $\nabla \cdot {\vect U} \; = 0$ (incompressibility) it becomes:} &      &= &\, \nabla \cdot (\vect U \, u) + \frac{1}{e_1 e_2} \lt( v \; \pd[e_2]{i} - u \; \pd[e_1]{j} \rt) (-v) \end{alignat*} \begin{equation} \label{eq:MB_flux_form} NLT =   \nabla \cdot \lt( \begin{array}{*{20}c} \vect U \, u \\ \vect U \, v \end{array} \rt) + \frac{1}{e_1 e_2} \lt( v \pd[e_2]{i} - u \pd[e_1]{j} \rt) \vect k \times \vect U_h NLT = \nabla \cdot \lt( \begin{array}{*{20}c} \vect U \, u \\ \vect U \, v \end{array} \rt) + \frac{1}{e_1 e_2} \lt( v \pd[e_2]{i} - u \pd[e_1]{j} \rt) \vect k \times \vect U_h \end{equation} The flux form has two terms, the first one is expressed as the divergence of momentum fluxes (hence the flux form name given to this formulation) and the second one is due to the curvilinear nature of the coordinate system used. The latter is called the \textit{metric} term and can be viewed as a modification of the Coriolis parameter: the first one is expressed as the divergence of momentum fluxes (hence the flux form name given to this formulation) and the second one is due to the curvilinear nature of the coordinate system used. The latter is called the \textit{metric} term and can be viewed as a modification of the Coriolis parameter: $% \label{eq:MB_cor+metric} the following tensorial formalism: \begin{itemize} \item \textbf{Vector invariant form of the momentum equations}: \begin{description} \item [Vector invariant form of the momentum equations] \begin{equation} \label{eq:MB_dyn_vect} \begin{split} \begin{gathered} % \label{eq:MB_dyn_vect_u} \pd[u]{t} = &+ (\zeta + f) \, v - \frac{1}{2 e_1} \pd[]{i} (u^2 + v^2) - \frac{1}{e_3} w \pd[u]{k} - \frac{1}{e_1} \pd[]{i} \lt( \frac{p_s + p_h}{\rho_o} \rt) \\ &+ D_u^{\vect U} + F_u^{\vect U} \\ \pd[v]{t} = &- (\zeta + f) \, u - \frac{1}{2 e_2} \pd[]{j} (u^2 + v^2) - \frac{1}{e_3} w \pd[v]{k} - \frac{1}{e_2} \pd[]{j} \lt( \frac{p_s + p_h}{\rho_o} \rt) \\ &+ D_v^{\vect U} + F_v^{\vect U} \end{split} \pd[u]{t} = + (\zeta + f) \, v - \frac{1}{2 e_1} \pd[]{i} (u^2 + v^2) - \frac{1}{e_3} w \pd[u]{k} - \frac{1}{e_1} \pd[]{i} \lt( \frac{p_s + p_h}{\rho_o} \rt) + D_u^{\vect U} + F_u^{\vect U} \\ \pd[v]{t} = - (\zeta + f) \, u - \frac{1}{2 e_2} \pd[]{j} (u^2 + v^2) - \frac{1}{e_3} w \pd[v]{k} - \frac{1}{e_2} \pd[]{j} \lt( \frac{p_s + p_h}{\rho_o} \rt) + D_v^{\vect U} + F_v^{\vect U} \end{gathered} \end{equation} \item \textbf{flux form of the momentum equations}: \item [Flux form of the momentum equations] % \label{eq:MB_dyn_flux} \begin{multline*} % \label{eq:MB_dyn_flux_u} \pd[u]{t} = + \lt[ f + \frac{1}{e_1 \; e_2} \lt( v \pd[e_2]{i} - u \pd[e_1]{j} \rt) \rt] \, v \\ - \frac{1}{e_1 \; e_2} \lt( \pd[(e_2 \, u \, u)]{i} + \pd[(e_1 \, v \, u)]{j} \rt) \\ - \frac{1}{e_3} \pd[(w \, u)]{k} - \frac{1}{e_1} \pd[]{i} \lt( \frac{p_s + p_h}{\rho_o} \rt) + D_u^{\vect U} + F_u^{\vect U} \pd[u]{t} = + \lt[ f + \frac{1}{e_1 \; e_2} \lt( v \pd[e_2]{i} - u \pd[e_1]{j} \rt) \rt] \, v - \frac{1}{e_1 \; e_2} \lt( \pd[(e_2 \, u \, u)]{i} + \pd[(e_1 \, v \, u)]{j} \rt) \\ - \frac{1}{e_3} \pd[(w \, u)]{k} - \frac{1}{e_1} \pd[]{i} \lt( \frac{p_s + p_h}{\rho_o} \rt) + D_u^{\vect U} + F_u^{\vect U} \end{multline*} \begin{multline*} % \label{eq:MB_dyn_flux_v} \pd[v]{t} = - \lt[ f + \frac{1}{e_1 \; e_2} \lt( v \pd[e_2]{i} - u \pd[e_1]{j} \rt) \rt] \, u \\ - \frac{1}{e_1 \; e_2} \lt( \pd[(e_2 \, u \, v)]{i} + \pd[(e_1 \, v \, v)]{j} \rt) \\ - \frac{1}{e_3} \pd[(w \, v)]{k} - \frac{1}{e_2} \pd[]{j} \lt( \frac{p_s + p_h}{\rho_o} \rt) + D_v^{\vect U} + F_v^{\vect U} \pd[v]{t} = - \lt[ f + \frac{1}{e_1 \; e_2} \lt( v \pd[e_2]{i} - u \pd[e_1]{j} \rt) \rt] \, u - \frac{1}{e_1 \; e_2} \lt( \pd[(e_2 \, u \, v)]{i} + \pd[(e_1 \, v \, v)]{j} \rt) \\ - \frac{1}{e_3} \pd[(w \, v)]{k} - \frac{1}{e_2} \pd[]{j} \lt( \frac{p_s + p_h}{\rho_o} \rt) + D_v^{\vect U} + F_v^{\vect U} \end{multline*} where \zeta, the relative vorticity, is given by \autoref{eq:MB_curl_Uh} and p_s, the surface pressure, is given by: where \zeta, the relative vorticity, is given by \autoref{eq:MB_curl_Uh} and p_s, the surface pressure, is given by: \[ % \label{eq:MB_spg}$ where the divergence of the horizontal velocity, $\chi$ is given by \autoref{eq:MB_div_Uh}. \item \textbf{tracer equations}: \begin{equation} \begin{split} \pd[T]{t} = & - \frac{1}{e_1 e_2} \lt[ \pd[(e_2 T \, u)]{i} + \pd[(e_1 T \, v)]{j} \rt] - \frac{1}{e_3} \pd[(T \, w)]{k} + D^T + F^T \\ \pd[S]{t} = & - \frac{1}{e_1 e_2} \lt[ \pd[(e_2 S \, u)]{i} + \pd[(e_1 S \, v)]{j} \rt] - \frac{1}{e_3} \pd[(S \, w)]{k} + D^S + F^S \\ \rho = & \rho \big( T,S,z(k) \big) \end{split} \end{equation} \end{itemize} The expression of $\vect D^{U}$, $D^{S}$ and $D^{T}$ depends on the subgrid scale parameterisation used. \item [Tracer equations] \begin{gather*} \pd[T]{t} = - \frac{1}{e_1 e_2} \lt[ \pd[(e_2 T \, u)]{i} + \pd[(e_1 T \, v)]{j} \rt] - \frac{1}{e_3} \pd[(T \, w)]{k} + D^T + F^T \\ \pd[S]{t} = - \frac{1}{e_1 e_2} \lt[ \pd[(e_2 S \, u)]{i} + \pd[(e_1 S \, v)]{j} \rt] - \frac{1}{e_3} \pd[(S \, w)]{k} + D^S + F^S \\ \rho = \rho \big( T,S,z(k) \big) \end{gather*} \end{description} The expression of $\vect D^{U}$, $D^{S}$ and $D^{T}$ depends on the subgrid scale parameterisation used. It will be defined in \autoref{eq:MB_zdf}. The nature and formulation of $\vect F^{\vect U}$, $F^T$ and $F^S$, the surface forcing terms, varying from more than 6,000 meters in abyssal trenches to zero at the coast. Last but not least, the ocean stratification exerts a strong barrier to vertical motions and mixing. Therefore, in order to represent the ocean with respect to the first point a space and time dependent vertical coordinate that follows the variation of the sea surface height Therefore, in order to represent the ocean with respect to the first point a space and time dependent vertical coordinate that follows the variation of the sea surface height \eg\ an \zstar-coordinate; for the second point, a space variation to fit the change of bottom topography for the second point, a space variation to fit the change of bottom topography \eg\ a terrain-following or $\sigma$-coordinate; and for the third point, one will be tempted to use a space and time dependent coordinate that follows the isopycnal surfaces, \eg\ an isopycnic coordinate. In order to satisfy two or more constraints one can even be tempted to mixed these coordinate systems, as in HYCOM (mixture of $z$-coordinate at the surface, isopycnic coordinate in the ocean interior and $\sigma$ at the ocean bottom) \citep{chassignet.smith.ea_JPO03} or OPA (mixture of $z$-coordinate in vicinity the surface and steep topography areas and $\sigma$-coordinate elsewhere) \citep{madec.delecluse.ea_JPO96} among others. and for the third point, one will be tempted to use a space and time dependent coordinate that follows the isopycnal surfaces, \eg\ an isopycnic coordinate. In order to satisfy two or more constraints one can even be tempted to mixed these coordinate systems, as in HYCOM (mixture of $z$-coordinate at the surface, isopycnic coordinate in the ocean interior and $\sigma$ at the ocean bottom) \citep{chassignet.smith.ea_JPO03} or OPA (mixture of $z$-coordinate in vicinity the surface and steep topography areas and $\sigma$-coordinate elsewhere) \citep{madec.delecluse.ea_JPO96} among others. In fact one is totally free to choose any space and time vertical coordinate by s = s(i,j,k,t) \end{equation} with the restriction that the above equation gives a single-valued monotonic relationship between $s$ and $k$, when $i$, $j$ and $t$ are held fixed. \autoref{eq:MB_s} is a transformation from the $(i,j,k,t)$ coordinate system with independent variables into with the restriction that the above equation gives a single-valued monotonic relationship between $s$ and $k$, when $i$, $j$ and $t$ are held fixed. \autoref{eq:MB_s} is a transformation from the $(i,j,k,t)$ coordinate system with independent variables into the $(i,j,s,t)$ generalised coordinate system with $s$ depending on the other three variables through \autoref{eq:MB_s}. This so-called \textit{generalised vertical coordinate} \citep{kasahara_MWR74} is in fact an Arbitrary Lagrangian--Eulerian (ALE) coordinate. Indeed, one has a great deal of freedom in the choice of expression for $s$. The choice determines which part of the vertical velocity (defined from a fixed referential) will cross the levels (Eulerian part) and which part will be used to move them (Lagrangian part). The coordinate is also sometime referenced as an adaptive coordinate \citep{hofmeister.burchard.ea_OM10}, since the coordinate system is adapted in the course of the simulation. an \textbf{A}rbitrary \textbf{L}agrangian--\textbf{E}ulerian (ALE) coordinate. Indeed, one has a great deal of freedom in the choice of expression for $s$. The choice determines which part of the vertical velocity (defined from a fixed referential) will cross the levels (Eulerian part) and which part will be used to move them (Lagrangian part). The coordinate is also sometimes referenced as an adaptive coordinate \citep{hofmeister.burchard.ea_OM10}, since the coordinate system is adapted in the course of the simulation. Its most often used implementation is via an ALE algorithm, in which a pure lagrangian step is followed by regridding and remapping steps, The horizontal velocity in ocean models measures motions in the horizontal plane, perpendicular to the local gravitational field. That is, horizontal velocity is mathematically the same regardless of the vertical coordinate, be it geopotential, isopycnal, pressure, or terrain following. That is, horizontal velocity is mathematically the same regardless of the vertical coordinate, be it geopotential, isopycnal, pressure, or terrain following. The key motivation for maintaining the same horizontal velocity component is that the hydrostatic and geostrophic balances are dominant in the large-scale ocean. Use of an alternative quasi -horizontal velocity, for example one oriented parallel to the generalized surface, Use of an alternative quasi -horizontal velocity, for example one oriented parallel to the generalized surface, would lead to unacceptable numerical errors. Correspondingly, the vertical direction is anti -parallel to the gravitational force in the surface of a constant generalized vertical coordinate. It is the method used to measure transport across the generalized vertical coordinate surfaces which differs between the vertical coordinate choices. That is, computation of the dia-surface velocity component represents the fundamental distinction between It is the method used to measure transport across the generalized vertical coordinate surfaces which differs between the vertical coordinate choices. That is, computation of the dia-surface velocity component represents the fundamental distinction between the various coordinates. In some models, such as geopotential, pressure, and terrain following, this transport is typically diagnosed from volume or mass conservation. In other models, such as isopycnal layered models, this transport is prescribed based on assumptions about the physical processes producing a flux across the layer interfaces. In some models, such as geopotential, pressure, and terrain following, this transport is typically diagnosed from volume or mass conservation. In other models, such as isopycnal layered models, this transport is prescribed based on assumptions about the physical processes producing a flux across the layer interfaces. In this section we first establish the PE in the generalised vertical $s$-coordinate, \subsection{\textit{S}-coordinate formulation} Starting from the set of equations established in \autoref{sec:MB_zco} for the special case $k = z$ and thus $e_3 = 1$, we introduce an arbitrary vertical coordinate $s = s(i,j,k,t)$, Starting from the set of equations established in \autoref{sec:MB_zco} for the special case $k = z$ and thus $e_3 = 1$, we introduce an arbitrary vertical coordinate $s = s(i,j,k,t)$, which includes $z$-, \zstar- and $\sigma$-coordinates as special cases ($s = z$, $s = \zstar$, and $s = \sigma = z / H$ or $= z / \lt( H + \eta \rt)$, resp.). A formal derivation of the transformed equations is given in \autoref{apdx:SCOORD}. Let us define the vertical scale factor by $e_3 = \partial_s z$  ($e_3$ is now a function of $(i,j,k,t)$ ), Let us define the vertical scale factor by $e_3 = \partial_s z$ ($e_3$ is now a function of $(i,j,k,t)$ ), and the slopes in the $(i,j)$ directions between $s$- and $z$-surfaces by: \begin{equation} \sigma_2 = \frac{1}{e_2} \; \lt. \pd[z]{j} \rt|_s \end{equation} We also introduce $\omega$, a dia-surface velocity component, defined as the velocity relative to the moving $s$-surfaces and normal to them: We also introduce $\omega$, a dia-surface velocity component, defined as the velocity relative to the moving $s$-surfaces and normal to them: $% \label{eq:MB_sco_w} (see \autoref{sec:SCOORD_momentum}): \begin{itemize} \item \textbf{Vector invariant form of the momentum equation}: \begin{description} \item [Vector invariant form of the momentum equation] \begin{gather*} % \label{eq:MB_sco_u_vector} \pd[u]{t} = + (\zeta + f) \, v - \frac{1}{2 \, e_1} \pd[]{i} (u^2 + v^2) - \frac{1}{e_3} \omega \pd[u]{k} - \frac{1}{e_1} \pd[]{i} \lt( \frac{p_s + p_h}{\rho_o} \rt) - g \frac{\rho}{\rho_o} \sigma_1 + D_u^{\vect U} + F_u^{\vect U} \\ % \label{eq:MB_sco_v_vector} \pd[v]{t} = - (\zeta + f) \, u - \frac{1}{2 \, e_2} \pd[]{j} (u^2 + v^2) - \frac{1}{e_3} \omega \pd[v]{k} - \frac{1}{e_2} \pd[]{j} \lt( \frac{p_s + p_h}{\rho_o} \rt) - g \frac{\rho}{\rho_o} \sigma_2 + D_v^{\vect U} + F_v^{\vect U} \end{gather*} \item [Flux form of the momentum equation] \begin{multline*} % \label{eq:MB_sco_u_vector} \pd[u]{t} = + (\zeta + f) \, v - \frac{1}{2 \, e_1} \pd[]{i} (u^2 + v^2) - \frac{1}{e_3} \omega \pd[u]{k} \\ - \frac{1}{e_1} \pd[]{i} \lt( \frac{p_s + p_h}{\rho_o} \rt) - g \frac{\rho}{\rho_o} \sigma_1 + D_u^{\vect U} + F_u^{\vect U} \end{multline*} \begin{multline*} % \label{eq:MB_sco_v_vector} \pd[v]{t} = - (\zeta + f) \, u - \frac{1}{2 \, e_2} \pd[]{j}(u^2 + v^2) - \frac{1}{e_3} \omega \pd[v]{k} \\ - \frac{1}{e_2} \pd[]{j} \lt( \frac{p_s + p_h}{\rho_o} \rt) - g \frac{\rho}{\rho_o} \sigma_2 + D_v^{\vect U} + F_v^{\vect U} \end{multline*} \item \textbf{Flux form of the momentum equation}: \begin{multline*} % \label{eq:MB_sco_u_flux} \frac{1}{e_3} \pd[(e_3 \, u)]{t} = + \lt[ f + \frac{1}{e_1 \; e_2} \lt( v \pd[e_2]{i} - u \pd[e_1]{j} \rt) \rt] \, v \\ - \frac{1}{e_1 \; e_2 \; e_3} \lt( \pd[(e_2 \, e_3 \, u \, u)]{i} + \pd[(e_1 \, e_3 \, v \, u)]{j} \rt) \\ - \frac{1}{e_3} \pd[(\omega \, u)]{k} - \frac{1}{e_1} \pd[]{i} \lt( \frac{p_s + p_h}{\rho_o} \rt) - g \frac{\rho}{\rho_o} \sigma_1 + D_u^{\vect U} + F_u^{\vect U} % \label{eq:MB_sco_u_flux} \frac{1}{e_3} \pd[(e_3 \, u)]{t} = + \lt[ f + \frac{1}{e_1 \; e_2} \lt( v \pd[e_2]{i} - u \pd[e_1]{j} \rt) \rt] \, v - \frac{1}{e_1 \; e_2 \; e_3} \lt( \pd[(e_2 \, e_3 \, u \, u)]{i} + \pd[(e_1 \, e_3 \, v \, u)]{j} \rt) \\ - \frac{1}{e_3} \pd[(\omega \, u)]{k} - \frac{1}{e_1} \pd[]{i} \lt( \frac{p_s + p_h}{\rho_o} \rt) - g \frac{\rho}{\rho_o} \sigma_1 + D_u^{\vect U} + F_u^{\vect U} \end{multline*} \begin{multline*} % \label{eq:MB_sco_v_flux} \frac{1}{e_3} \pd[(e_3 \, v)]{t} = - \lt[ f + \frac{1}{e_1 \; e_2} \lt( v \pd[e_2]{i} - u \pd[e_1]{j} \rt) \rt] \, u \\ - \frac{1}{e_1 \; e_2 \; e_3} \lt( \pd[( e_2 \; e_3 \, u \, v)]{i} + \pd[(e_1 \; e_3 \, v \, v)]{j} \rt) \\ - \frac{1}{e_3} \pd[(\omega \, v)]{k} - \frac{1}{e_2} \pd[]{j} \lt( \frac{p_s + p_h}{\rho_o} \rt) - g \frac{\rho}{\rho_o}\sigma_2 + D_v^{\vect U} + F_v^{\vect U} \frac{1}{e_3} \pd[(e_3 \, v)]{t} = - \lt[ f + \frac{1}{e_1 \; e_2} \lt( v \pd[e_2]{i} - u \pd[e_1]{j} \rt) \rt] \, u - \frac{1}{e_1 \; e_2 \; e_3} \lt( \pd[( e_2 \; e_3 \, u \, v)]{i} + \pd[(e_1 \; e_3 \, v \, v)]{j} \rt) \\ - \frac{1}{e_3} \pd[(\omega \, v)]{k} - \frac{1}{e_2} \pd[]{j} \lt( \frac{p_s + p_h}{\rho_o} \rt) - g \frac{\rho}{\rho_o}\sigma_2 + D_v^{\vect U} + F_v^{\vect U} \end{multline*} where the relative vorticity, \zeta, the surface pressure gradient, \chi = \frac{1}{e_1 e_2 e_3} \lt( \pd[(e_2 e_3 \, u)]{i} + \pd[(e_1 e_3 \, v)]{j} \rt)$ \item \textit{tracer equations}: \begin{multline*} % \label{eq:MB_sco_t} \frac{1}{e_3} \pd[(e_3 \, T)]{t} = - \frac{1}{e_1 e_2 e_3} \lt(   \pd[(e_2 e_3 \, u \, T)]{i} + \pd[(e_1 e_3 \, v \, T)]{j} \rt) \\ - \frac{1}{e_3} \pd[(T \, \omega)]{k} + D^T + F^S \end{multline*} \begin{multline} % \label{eq:MB_sco_s} \frac{1}{e_3} \pd[(e_3 \, S)]{t} = - \frac{1}{e_1 e_2 e_3} \lt(   \pd[(e_2 e_3 \, u \, S)]{i} + \pd[(e_1 e_3 \, v \, S)]{j} \rt) \\ - \frac{1}{e_3} \pd[(S \, \omega)]{k} + D^S + F^S \end{multline} \end{itemize} \item [Tracer equations] \begin{gather*} % \label{eq:MB_sco_t} \frac{1}{e_3} \pd[(e_3 \, T)]{t} = - \frac{1}{e_1 e_2 e_3} \lt(   \pd[(e_2 e_3 \, u \, T)]{i} + \pd[(e_1 e_3 \, v \, T)]{j} \rt) - \frac{1}{e_3} \pd[(T \, \omega)]{k} + D^T + F^S \\ % \label{eq:MB_sco_s} \frac{1}{e_3} \pd[(e_3 \, S)]{t} = - \frac{1}{e_1 e_2 e_3} \lt(   \pd[(e_2 e_3 \, u \, S)]{i} + \pd[(e_1 e_3 \, v \, S)]{j} \rt) - \frac{1}{e_3} \pd[(S \, \omega)]{k} + D^S + F^S \end{gather*} \end{description} The equation of state has the same expression as in $z$-coordinate, and similar expressions are used for mixing and forcing terms. \label{subsec:MB_zco_star} \begin{figure}[!b] \begin{figure} \centering \includegraphics[width=0.66\textwidth]{Fig_z_zstar} \caption[Curvilinear z-coordinate systems (\{non-\}linear free-surface cases and re-scaled \zstar)]{ (a) $z$-coordinate in linear free-surface case ; (b) $z$-coordinate in non-linear free surface case ; (c) re-scaled height coordinate (become popular as the \zstar-coordinate \citep{adcroft.campin_OM04}).} \begin{enumerate*}[label={(\alph*)}] \item $z$-coordinate in linear free-surface case; \item $z$-coordinate in non-linear free surface case; \item re-scaled height coordinate (become popular as the \zstar-coordinate \citep{adcroft.campin_OM04}). \end{enumerate*} } \label{fig:MB_z_zstar} \end{figure} In this case, the free surface equation is nonlinear, and the variations of volume are fully taken into account. These coordinates systems is presented in a report \citep{levier.treguier.ea_rpt07} available on the \NEMO\ web site. The \zstar coordinate approach is an unapproximated, non-linear free surface implementation which allows one to deal with large amplitude free-surface variations relative to the vertical resolution \citep{adcroft.campin_OM04}. In the \zstar formulation, the variation of the column thickness due to sea-surface undulations is not concentrated in the surface level, as in the $z$-coordinate formulation, but is equally distributed over the full water column. In this case, the free surface equation is nonlinear, and the variations of volume are fully taken into account. These coordinates systems is presented in a report \citep{levier.treguier.ea_rpt07} available on the \NEMO\ web site. The \zstar\ coordinate approach is an unapproximated, non-linear free surface implementation which allows one to deal with large amplitude free-surface variations relative to the vertical resolution \citep{adcroft.campin_OM04}. In the \zstar\ formulation, the variation of the column thickness due to sea-surface undulations is not concentrated in the surface level, as in the $z$-coordinate formulation, but is equally distributed over the full water column. Thus vertical levels naturally follow sea-surface variations, with a linear attenuation with depth, as illustrated by \autoref{fig:MB_z_zstar}. Note that with a flat bottom, such as in \autoref{fig:MB_z_zstar}, the bottom-following $z$ coordinate and \zstar are equivalent. Note that with a flat bottom, such as in \autoref{fig:MB_z_zstar}, the bottom-following $z$ coordinate and \zstar\ are equivalent. The definition and modified oceanic equations for the rescaled vertical coordinate \zstar, including the treatment of fresh-water flux at the surface, are detailed in Adcroft and Campin (2004). The major points are summarized here. The position (\zstar) and vertical discretization (\zstar) are expressed as: The position (\zstar) and vertical discretization ($\delta \zstar$) are expressed as: $% \label{eq:MB_z-star} H + \zstar = (H + z) / r \quad \text{and} \quad \delta \zstar = \delta z / r \quad \text{with} \quad r = \frac{H + \eta}{H} . H + \zstar = (H + z) / r \quad \text{and} \quad \delta \zstar = \delta z / r \quad \text{with} \quad r = \frac{H + \eta}{H}$ Simple re-organisation of the above expressions gives $% \label{eq:MB_zstar_2} \zstar = H \lt( \frac{z - \eta}{H + \eta} \rt) . \zstar = H \lt( \frac{z - \eta}{H + \eta} \rt)$ Since the vertical displacement of the free surface is incorporated in the vertical coordinate \zstar, the upper and lower boundaries are at fixed  \zstar position, the upper and lower boundaries are at fixed \zstar\ position, $\zstar = 0$ and $\zstar = -H$ respectively. Also the divergence of the flow field is no longer zero as shown by the continuity equation: $\pd[r]{t} = \nabla_{\zstar} \cdot \lt( r \; \vect U_h \rt) + \pd[r \; w^*]{\zstar} = 0 . \pd[r]{t} = \nabla_{\zstar} \cdot \lt( r \; \vect U_h \rt) + \pd[r \; w^*]{\zstar} = 0$ This \zstar coordinate is closely related to the "eta" coordinate used in many atmospheric models (see Black (1994) for a review of eta coordinate atmospheric models). This \zstar\ coordinate is closely related to the $\eta$ coordinate used in many atmospheric models (see Black (1994) for a review of $\eta$ coordinate atmospheric models). It was originally used in ocean models by Stacey et al. (1995) for studies of tides next to shelves, and it has been recently promoted by Adcroft and Campin (2004) for global climate modelling. The surfaces of constant \zstar are quasi -horizontal. Indeed, the \zstar coordinate reduces to $z$ when $\eta$ is zero. The surfaces of constant \zstar\ are quasi-horizontal. Indeed, the \zstar\ coordinate reduces to $z$ when $\eta$ is zero. In general, when noting the large differences between undulations of the bottom topography versus undulations in the surface height, it is clear that surfaces constant \zstar are very similar to the depth surfaces. it is clear that surfaces constant \zstar\ are very similar to the depth surfaces. These properties greatly reduce difficulties of computing the horizontal pressure gradient relative to terrain following sigma models discussed in \autoref{subsec:MB_sco}. Additionally, since $\zstar = z$ when $\eta = 0$, no flow is spontaneously generated in an unforced ocean starting from rest, regardless the bottom topography. This behaviour is in contrast to the case with "s"-models, where pressure gradient errors in the presence of nontrivial topographic variations can generate nontrivial spontaneous flow from a resting state, no flow is spontaneously generated in an unforced ocean starting from rest, regardless the bottom topography. This behaviour is in contrast to the case with s''-models, where pressure gradient errors in the presence of nontrivial topographic variations can generate nontrivial spontaneous flow from a resting state, depending on the sophistication of the pressure gradient solver. The quasi -horizontal nature of the coordinate surfaces also facilitates the implementation of neutral physics parameterizations in \zstar  models using the same techniques as in $z$-models The quasi-horizontal nature of the coordinate surfaces also facilitates the implementation of neutral physics parameterizations in \zstar\ models using the same techniques as in $z$-models (see Chapters 13-16 of \cite{griffies_bk04}) for a discussion of neutral physics in $z$-models, as well as \autoref{sec:LDF_slp} in this document for treatment in \NEMO). The range over which \zstar  varies is time independent $-H \leq \zstar \leq 0$. The range over which \zstar\ varies is time independent $-H \leq \zstar \leq 0$. Hence, all cells remain nonvanishing, so long as the surface height maintains $\eta > -H$. This is a minor constraint relative to that encountered on the surface height when using $s = z$ or $s = z - \eta$. Because \zstar  has a time independent range, all grid cells have static increments ds, This is a minor constraint relative to that encountered on the surface height when using $s = z$ or $s = z - \eta$. Because \zstar\ has a time independent range, all grid cells have static increments ds, and the sum of the vertical increments yields the time independent ocean depth. %k ds = H. The \zstar coordinate is therefore invisible to undulations of the free surface, The \zstar\ coordinate is therefore invisible to undulations of the free surface, since it moves along with the free surface. This property means that no spurious vertical transport is induced across surfaces of constant \zstar  by the motion of external gravity waves. This property means that no spurious vertical transport is induced across surfaces of constant \zstar\  by the motion of external gravity waves. Such spurious transport can be a problem in z-models, especially those with tidal forcing. Quite generally, the time independent range for the \zstar  coordinate is a very convenient property that allows for a nearly arbitrary vertical resolution even in the presence of large amplitude fluctuations of the surface height, again so long as $\eta > -H$. Quite generally, the time independent range for the \zstar\ coordinate is a very convenient property that allows for a nearly arbitrary vertical resolution even in the presence of large amplitude fluctuations of the surface height, again so long as $\eta > -H$. %end MOM doc %%% \label{subsec:MB_sco} %% ================================================================================================= \subsubsection{Introduction} Several important aspects of the ocean circulation are influenced by bottom topography. Of course, the most important is that bottom topography determines deep ocean sub-basins, barriers, sills and channels that strongly constrain the path of water masses, but more subtle effects exist. For example, the topographic $\beta$-effect is usually larger than the planetary one along continental slopes. Of course, the most important is that bottom topography determines deep ocean sub-basins, barriers, sills and channels that strongly constrain the path of water masses, but more subtle effects exist. For example, the topographic $\beta$-effect is usually larger than the planetary one along continental slopes. Topographic Rossby waves can be excited and can interact with the mean current. In the $z$-coordinate system presented in the previous section (\autoref{sec:MB_zco}), large localized depth gradients associated with large localized vertical velocities. The response to such a velocity field often leads to numerical dispersion effects. One solution to strongly reduce this error is to use a partial step representation of bottom topography instead of a full step one \cite{pacanowski.gnanadesikan_MWR98}. One solution to strongly reduce this error is to use a partial step representation of bottom topography instead of a full step one \cite{pacanowski.gnanadesikan_MWR98}. Another solution is to introduce a terrain-following coordinate system (hereafter $s$-coordinate). The $s$-coordinate avoids the discretisation error in the depth field since the layers of computation are gradually adjusted with depth to the ocean bottom. Relatively small topographic features as well as  gentle, large-scale slopes of the sea floor in the deep ocean, which would be ignored in typical $z$-model applications with the largest grid spacing at greatest depths, The $s$-coordinate avoids the discretisation error in the depth field since the layers of computation are gradually adjusted with depth to the ocean bottom. Relatively small topographic features as well as gentle, large-scale slopes of the sea floor in the deep ocean, which would be ignored in typical $z$-model applications with the largest grid spacing at greatest depths, can easily be represented (with relatively low vertical resolution). A terrain-following model (hereafter $s$-model) also facilitates the modelling of the boundary layer flows over a large depth range, which in the framework of the $z$-model would require high vertical resolution over A terrain-following model (hereafter $s$-model) also facilitates the modelling of the boundary layer flows over a large depth range, which in the framework of the $z$-model would require high vertical resolution over the whole depth range. Moreover, with a $s$-coordinate it is possible, at least in principle, to have the bottom and the sea surface as Moreover, with a $s$-coordinate it is possible, at least in principle, to have the bottom and the sea surface as the only boundaries of the domain (no more lateral boundary condition to specify). Nevertheless, a $s$-coordinate also has its drawbacks. Perfectly adapted to a homogeneous ocean, Nevertheless, a $s$-coordinate also has its drawbacks. Perfectly adapted to a homogeneous ocean, it has strong limitations as soon as stratification is introduced. The main two problems come from the truncation error in the horizontal pressure gradient and a possibly increased diapycnal diffusion. The horizontal pressure force in $s$-coordinate consists of two terms (see \autoref{apdx:SCOORD}), \begin{equation} \label{eq:MB_p_sco} The second term in \autoref{eq:MB_p_sco} depends on the tilt of the coordinate surface and leads to a truncation error that is not present in a $z$-model. In the special case of a $\sigma$-coordinate (i.e. a depth-normalised coordinate system $\sigma = z/H$), \citet{haney_JPO91} and \citet{beckmann.haidvogel_JPO93} have given estimates of the magnitude of this truncation error. It depends on topographic slope, stratification, horizontal and vertical resolution, the equation of state, and the finite difference scheme. In the special case of a $\sigma$-coordinate (i.e. a depth-normalised coordinate system $\sigma = z/H$), \citet{haney_JPO91} and \citet{beckmann.haidvogel_JPO93} have given estimates of the magnitude of this truncation error. It depends on topographic slope, stratification, horizontal and vertical resolution, the equation of state, and the finite difference scheme. This error limits the possible topographic slopes that a model can handle at a given horizontal and vertical resolution. This is a severe restriction for large-scale applications using realistic bottom topography. The large-scale slopes require high horizontal resolution, and the computational cost becomes prohibitive. The large-scale slopes require high horizontal resolution, and the computational cost becomes prohibitive. This problem can be at least partially overcome by mixing $s$-coordinate and step-like representation of bottom topography \citep{gerdes_JGR93*a,gerdes_JGR93*b,madec.delecluse.ea_JPO96}. step-like representation of bottom topography \citep{gerdes_JGR93*a,gerdes_JGR93*b,madec.delecluse.ea_JPO96}. However, the definition of the model domain vertical coordinate becomes then a non-trivial thing for a realistic bottom topography: an envelope topography is defined in $s$-coordinate on which a full or partial step bottom topography is then applied in order to adjust the model depth to the observed one (see \autoref{subsec:DOM_zgr}. For numerical reasons a minimum of diffusion is required along the coordinate surfaces of any finite difference model. an envelope topography is defined in $s$-coordinate on which a full or partial step bottom topography is then applied in order to adjust the model depth to the observed one (see \autoref{subsec:DOM_zgr}). For numerical reasons a minimum of diffusion is required along the coordinate surfaces of any finite difference model. It causes spurious diapycnal mixing when coordinate surfaces do not coincide with isoneutral surfaces. This is the case for a $z$-model as well as for a $s$-model. However, density varies more strongly on $s$-surfaces than on horizontal surfaces in regions of large topographic slopes, implying larger diapycnal diffusion in a $s$-model than in a $z$-model. Whereas such a diapycnal diffusion in a $z$-model tends to weaken horizontal density (pressure) gradients and thus the horizontal circulation, it usually reinforces these gradients in a $s$-model, creating spurious circulation. For example, imagine an isolated bump of topography in an ocean at rest with a horizontally uniform stratification. However, density varies more strongly on $s$-surfaces than on horizontal surfaces in regions of large topographic slopes, implying larger diapycnal diffusion in a $s$-model than in a $z$-model. Whereas such a diapycnal diffusion in a $z$-model tends to weaken horizontal density (pressure) gradients and thus the horizontal circulation, it usually reinforces these gradients in a $s$-model, creating spurious circulation. For example, imagine an isolated bump of topography in an ocean at rest with a horizontally uniform stratification. Spurious diffusion along $s$-surfaces will induce a bump of isoneutral surfaces over the topography, and thus will generate there a baroclinic eddy. In contrast, the ocean will stay at rest in a $z$-model. As for the truncation error, the problem can be reduced by introducing the terrain-following coordinate below the strongly stratified portion of the water column (\ie\ the main thermocline) \citep{madec.delecluse.ea_JPO96}. An alternate solution consists of rotating the lateral diffusive tensor to geopotential or to isoneutral surfaces (see \autoref{subsec:MB_ldf}). As for the truncation error, the problem can be reduced by introducing the terrain-following coordinate below the strongly stratified portion of the water column (\ie\ the main thermocline) \citep{madec.delecluse.ea_JPO96}. An alternate solution consists of rotating the lateral diffusive tensor to geopotential or to isoneutral surfaces (see \autoref{subsec:MB_ldf}). Unfortunately, the slope of isoneutral surfaces relative to the $s$-surfaces can very large, strongly exceeding the stability limit of such a operator when it is discretized (see \autoref{chap:LDF}). The $s$-coordinates introduced here \citep{lott.madec.ea_OM90,madec.delecluse.ea_JPO96} differ mainly in two aspects from similar models: it allows a representation of bottom topography with mixed full or partial step-like/terrain following topography; strongly exceeding the stability limit of such a operator when it is discretized (see \autoref{chap:LDF}). The $s$-coordinates introduced here \citep{lott.madec.ea_OM90,madec.delecluse.ea_JPO96} differ mainly in two aspects from similar models: it allows a representation of bottom topography with mixed full or partial step-like/terrain following topography; It also offers a completely general transformation, $s=s(i,j,z)$ for the vertical coordinate. %% ================================================================================================= \subsection{\texorpdfstring{Curvilinear \ztilde-coordinate}{}} \subsection{Curvilinear \ztilde-coordinate} \label{subsec:MB_zco_tilde} The \ztilde -coordinate has been developed by \citet{leclair.madec_OM11}. The \ztilde-coordinate has been developed by \citet{leclair.madec_OM11}. It is available in \NEMO\ since the version 3.4 and is more robust in version 4.0 than previously. Nevertheless, it is currently not robust enough to be used in all possible configurations. \label{sec:MB_zdf_ldf} The hydrostatic primitive equations describe the behaviour of a geophysical fluid at space and time scales larger than a few kilometres in the horizontal, a few meters in the vertical and a few minutes. They are usually solved at larger scales: the specified grid spacing and time step of the numerical model. The hydrostatic primitive equations describe the behaviour of a geophysical fluid at space and time scales larger than a few kilometres in the horizontal, a few meters in the vertical and a few minutes. They are usually solved at larger scales: the specified grid spacing and time step of the numerical model. The effects of smaller scale motions (coming from the advective terms in the Navier-Stokes equations) must be represented entirely in terms of large-scale patterns to close the equations. small scale processes \textit{in fine} balance the surface input of kinetic energy and heat. The control exerted by gravity on the flow induces a strong anisotropy between the lateral and vertical motions. The control exerted by gravity on the flow induces a strong anisotropy between the lateral and vertical motions. Therefore subgrid-scale physics \textbf{D}$^{\vect U}$, $D^{S}$ and $D^{T}$  in \autoref{eq:MB_PE_dyn}, \autoref{eq:MB_PE_tra_T} and \autoref{eq:MB_PE_tra_S} are divided into a lateral part \textbf{D}$^{l \vect U}$, $D^{l S}$ and $D^{l T}$ and a  lateral part \textbf{D}$^{l \vect U}$, $D^{l S}$ and $D^{l T}$ and a vertical part \textbf{D}$^{v \vect U}$, $D^{v S}$ and $D^{v T}$. The formulation of these terms and their underlying physics are briefly discussed in the next two subsections. The formulation of these terms and their underlying physics are briefly discussed in the next two subsections. %% ================================================================================================= \label{subsec:MB_zdf} The model resolution is always larger than the scale at which the major sources of vertical turbulence occur (shear instability, internal wave breaking...). The model resolution is always larger than the scale at which the major sources of vertical turbulence occur (shear instability, internal wave breaking...). Turbulent motions are thus never explicitly solved, even partially, but always parameterized. The vertical turbulent fluxes are assumed to depend linearly on the gradients of large-scale quantities (for example, the turbulent heat flux is given by $\overline{T' w'} = -A^{v T} \partial_z \overline T$, The vertical turbulent fluxes are assumed to depend linearly on the gradients of large-scale quantities (for example, the turbulent heat flux is given by $\overline{T' w'} = -A^{v T} \partial_z \overline T$, where $A^{v T}$ is an eddy coefficient). This formulation is analogous to that of molecular diffusion and dissipation. \label{eq:MB_zdf} \begin{gathered} \vect D^{v \vect U} = \pd[]{z} \lt( A^{vm} \pd[\vect U_h]{z} \rt) \ , \\ D^{vT}       = \pd[]{z} \lt( A^{vT} \pd[T]{z}         \rt) \quad \text{and} \quad \vect D^{v \vect U} = \pd[]{z} \lt( A^{vm} \pd[\vect U_h]{z} \rt) \text{,} \ D^{vT}       = \pd[]{z} \lt( A^{vT} \pd[T]{z}         \rt) \ \text{and} \ D^{vS}       = \pd[]{z} \lt( A^{vT} \pd[S]{z}         \rt) \end{gathered} \end{equation} where $A^{vm}$ and $A^{vT}$ are the vertical eddy viscosity and diffusivity coefficients, respectively. where $A^{vm}$ and $A^{vT}$ are the vertical eddy viscosity and diffusivity coefficients, respectively. At the sea surface and at the bottom, turbulent fluxes of momentum, heat and salt must be specified (see \autoref{chap:SBC} and \autoref{chap:ZDF} and \autoref{sec:TRA_bbl}). All the vertical physics is embedded in the specification of the eddy coefficients. They can be assumed to be either constant, or function of the local fluid properties (\eg\ Richardson number, Brunt-Vais\"{a}l\"{a} frequency, distance from the boundary ...), (\eg\ Richardson number, Brunt-V\"{a}is\"{a}l\"{a} frequency, distance from the boundary ...), or computed from a turbulent closure model. The choices available in \NEMO\ are discussed in \autoref{chap:ZDF}). (which can be solved explicitly if the resolution is sufficient since their underlying physics are included in the primitive equations), and a sub mesoscale turbulence which is never explicitly solved even partially, but always parameterized. The formulation of lateral eddy fluxes depends on whether the mesoscale is below or above the grid-spacing (\ie\ the model is eddy-resolving or not). and a sub mesoscale turbulence which is never explicitly solved even partially, but always parameterized. The formulation of lateral eddy fluxes depends on whether the mesoscale is below or above the grid-spacing (\ie\ the model is eddy-resolving or not). In non-eddy-resolving configurations, the closure is similar to that used for the vertical physics. The lateral turbulent fluxes are assumed to depend linearly on the lateral gradients of large-scale quantities. The lateral turbulent fluxes are assumed to depend linearly on the lateral gradients of large-scale quantities. The resulting lateral diffusive and dissipative operators are of second order. Observations show that lateral mixing induced by mesoscale turbulence tends to be along isopycnal surfaces Observations show that lateral mixing induced by mesoscale turbulence tends to be along isopycnal surfaces (or more precisely neutral surfaces \cite{mcdougall_JPO87}) rather than across them. As the slope of neutral surfaces is small in the ocean, a common approximation is to assume that the lateral' direction is the horizontal, \ie\ the lateral mixing is performed along geopotential surfaces. As the slope of neutral surfaces is small in the ocean, a common approximation is to assume that the `lateral'' direction is the horizontal, \ie\ the lateral mixing is performed along geopotential surfaces. This leads to a geopotential second order operator for lateral subgrid scale physics. This assumption can be relaxed: the eddy-induced turbulent fluxes can be better approached by assuming that This assumption can be relaxed: the eddy-induced turbulent fluxes can be better approached by assuming that they depend linearly on the gradients of large-scale quantities computed along neutral surfaces. In such a case, the diffusive operator is an isoneutral second order operator and it has components in the three space directions. However, both horizontal and isoneutral operators have no effect on mean (\ie\ large scale) potential energy whereas However, both horizontal and isoneutral operators have no effect on mean (\ie\ large scale) potential energy whereas potential energy is a main source of turbulence (through baroclinic instabilities). \citet{gent.mcwilliams_JPO90} proposed a parameterisation of mesoscale eddy-induced turbulence which associates an eddy-induced velocity to the isoneutral diffusion. Its mean effect is to reduce the mean potential energy of the ocean. This leads to a formulation of lateral subgrid-scale physics made up of an isoneutral second order operator and an eddy induced advective part. This leads to a formulation of lateral subgrid-scale physics made up of an isoneutral second order operator and an eddy induced advective part. In all these lateral diffusive formulations, the specification of the lateral eddy coefficients remains the problematic point as there is no really satisfactory formulation of these coefficients as a function of large-scale features. there is no really satisfactory formulation of these coefficients as a function of large-scale features. In eddy-resolving configurations, a second order operator can be used, not interfering with the resolved mesoscale activity. Another approach is becoming more and more popular: instead of specifying explicitly a sub-grid scale term in the momentum and tracer time evolution equations, instead of specifying explicitly a sub-grid scale term in the momentum and tracer time evolution equations, one uses an advective scheme which is diffusive enough to maintain the model stability. It must be emphasised that then, all the sub-grid scale physics is included in the formulation of the advection scheme. It must be emphasised that then, all the sub-grid scale physics is included in the formulation of the advection scheme. All these parameterisations of subgrid scale physics have advantages and drawbacks. They are not all available in \NEMO. For active tracers (temperature and salinity) the main ones are: They are not all available in \NEMO. For active tracers (temperature and salinity) the main ones are: Laplacian and bilaplacian operators acting along geopotential or iso-neutral surfaces, \citet{gent.mcwilliams_JPO90} parameterisation, and various slightly diffusive advection schemes. For momentum, the main ones are: Laplacian and bilaplacian operators acting along geopotential surfaces, For momentum, the main ones are: Laplacian and bilaplacian operators acting along geopotential surfaces, and UBS advection schemes when flux form is chosen for the momentum advection. \begin{equation} \label{eq:MB_iso_tensor} D^{lT} = \nabla \vect . \lt( A^{lT} \; \Re \; \nabla T \rt) \quad \text{with} \quad \Re = \begin{pmatrix} 1    & 0    & -r_1          \\ 0    & 1    & -r_2          \\ -r_1 & -r_2 & r_1^2 + r_2^2 \\ \end{pmatrix} D^{lT} = \nabla \vect . \lt( A^{lT} \; \Re \; \nabla T \rt) \quad \text{with} \quad \Re = \begin{pmatrix} 1    & 0    & -r_1          \\ 0    & 1    & -r_2          \\ -r_1 & -r_2 & r_1^2 + r_2^2 \\ \end{pmatrix} \end{equation} where $r_1$ and $r_2$ are the slopes between the surface along which the diffusive operator acts and the rotation between geopotential and $s$-surfaces, while it is only an approximation for the rotation between isoneutral and $z$- or $s$-surfaces. Indeed, in the latter case, two assumptions are made to simplify \autoref{eq:MB_iso_tensor} \citep{cox_OM87}. First, the horizontal contribution of the dianeutral mixing is neglected since the ratio between iso and dia-neutral diffusive coefficients is known to be several orders of magnitude smaller than unity. Indeed, in the latter case, two assumptions are made to simplify \autoref{eq:MB_iso_tensor} \citep{cox_OM87}. First, the horizontal contribution of the dianeutral mixing is neglected since the ratio between iso and dia-neutral diffusive coefficients is known to be several orders of magnitude smaller than unity. Second, the two isoneutral directions of diffusion are assumed to be independent since the slopes are generally less than $10^{-2}$ in the ocean (see \autoref{apdx:DIFFOPERS}). they are equal to $\sigma_1$ and $\sigma_2$, respectively (see \autoref{eq:MB_sco_slope}). For \textit{isoneutral} diffusion $r_1$ and $r_2$ are the slopes between the isoneutral and computational surfaces. For \textit{isoneutral} diffusion $r_1$ and $r_2$ are the slopes between the isoneutral and computational surfaces. Therefore, they are different quantities, but have similar expressions in $z$- and $s$-coordinates. In $z$-coordinates: where $\vect U^\ast = \lt( u^\ast,v^\ast,w^\ast \rt)$ is a non-divergent, eddy-induced transport velocity. This velocity field is defined by: \begin{gather} \begin{gather*} % \label{eq:MB_eiv} u^\ast =   \frac{1}{e_3}            \pd[]{k} \lt( A^{eiv} \;        \tilde{r}_1 \rt) \\ u^\ast =   \frac{1}{e_3}            \pd[]{k} \lt( A^{eiv} \;        \tilde{r}_1 \rt) \quad v^\ast =   \frac{1}{e_3}            \pd[]{k} \lt( A^{eiv} \;        \tilde{r}_2 \rt) \\ w^\ast = - \frac{1}{e_1 e_2} \lt[   \pd[]{i} \lt( A^{eiv} \; e_2 \, \tilde{r}_1 \rt) + \pd[]{j} \lt( A^{eiv} \; e_1 \, \tilde{r}_2 \rt) \rt] \end{gather} \end{gather*} where $A^{eiv}$ is the eddy induced velocity coefficient (or equivalently the isoneutral thickness diffusivity coefficient), and $\tilde r_1$ and $\tilde r_2$ are the slopes between isoneutral and \textit{geopotential} surfaces. Their values are thus independent of the vertical coordinate, but their expression depends on the coordinate: \begin{align} and $\tilde r_1$ and $\tilde r_2$ are the slopes between isoneutral and \textit{geopotential} surfaces. Their values are thus independent of the vertical coordinate, but their expression depends on the coordinate: \begin{equation} \label{eq:MB_slopes_eiv} \tilde{r}_n = \end{cases} \quad \text{where~} n = 1, 2 \end{align} \end{equation} The normal component of the eddy induced velocity is zero at all the boundaries. This can be achieved in a model by tapering either the eddy coefficient or the slopes to zero in the vicinity of the boundaries. This can be achieved in a model by tapering either the eddy coefficient or the slopes to zero in the vicinity of the boundaries. The latter strategy is used in \NEMO\ (cf. \autoref{chap:LDF}). \end{align*} Such a formulation ensures a complete separation between the vorticity and horizontal divergence fields (see \autoref{apdx:INVARIANTS}). Such a formulation ensures a complete separation between the vorticity and horizontal divergence fields (see \autoref{apdx:INVARIANTS}). Unfortunately, it is only available in \textit{iso-level} direction. When a rotation is required (\ie\ geopotential diffusion in $s$-coordinates or isoneutral diffusion in both $z$- and $s$-coordinates), the $u$ and $v$-fields are considered as independent scalar fields, so that the diffusive operator is given by: (\ie\ geopotential diffusion in $s$-coordinates or isoneutral diffusion in both $z$- and $s$-coordinates), the $u$ and $v$-fields are considered as independent scalar fields, so that the diffusive operator is given by: \begin{gather*} % \label{eq:MB_lapU_iso} \subsubsection{Lateral bilaplacian momentum diffusive operator} As for tracers, the bilaplacian order momentum diffusive operator is a re-entering Laplacian operator with As for tracers, the bilaplacian order momentum diffusive operator is a re-entering Laplacian operator with the harmonic eddy diffusion coefficient set to the square root of the biharmonic one. Nevertheless it is currently not available in the iso-neutral case.