Changeset 11296


Ignore:
Timestamp:
2019-07-18T15:41:15+02:00 (13 months ago)
Author:
djlea
Message:

#2297 Updates to OBS and ASM documentation - first sweep.

Location:
NEMO/branches/2019/dev_r11233_obsasm_docfixes/doc
Files:
3 edited

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  • NEMO/branches/2019/dev_r11233_obsasm_docfixes/doc/latex/NEMO/subfiles/chap_ASM.tex

    r11151 r11296  
    88\label{chap:ASM} 
    99 
    10 Authors: D. Lea,  M. Martin, K. Mogensen, A. Weaver, ...   % do we keep 
     10Authors: D. Lea,  M. Martin, K. Mogensen, A. Weaver. 
    1111 
    1212\minitoc 
     
    1515 
    1616The ASM code adds the functionality to apply increments to the model variables: temperature, salinity, 
    17 sea surface height, velocity and sea ice concentration.  
     17sea surface height, velocity and sea ice concentration. 
    1818These are read into the model from a NetCDF file which may be produced by separate data assimilation code. 
    1919The code can also output model background fields which are used as an input to data assimilation code. 
     
    5656Typically the increments are spread evenly over the full window. 
    5757In addition, two different weighting functions have been implemented. 
    58 The first function employs constant weights,  
     58The first function (namelist option \np{niaufn} = 0) employs constant weights, 
    5959\begin{align} 
    6060  \label{eq:F1_i} 
     
    6666    0     &    {\mathrm if} \; \; \; t_{i} > t_{n} 
    6767  \end{array} 
    68             \right.  
     68            \right. 
    6969\end{align} 
    7070where $M = m-n$. 
    71 The second function employs peaked hat-like weights in order to give maximum weight in the centre of the sub-window, 
     71The second function (namelist option \np{niaufn} = 1) employs peaked hat-like weights in order to give maximum weight in the centre of the sub-window, 
    7272with the weighting reduced linearly to a small value at the window end-points: 
    7373\begin{align} 
     
    8383                                   \right. 
    8484\end{align} 
    85 where $\alpha^{-1} = \sum_{i=1}^{M/2} 2i$ and $M$ is assumed to be even.  
     85where $\alpha^{-1} = \sum_{i=1}^{M/2} 2i$ and $M$ is assumed to be even. 
    8686The weights described by \autoref{eq:F2_i} provide a smoother transition of the analysis trajectory from 
    8787one assimilation cycle to the next than that described by \autoref{eq:F1_i}. 
     
    105105  \right., 
    106106\end{equation} 
    107 where 
     107where the divergence is defined as 
    108108\[ 
    109109  % \label{eq:asm_div} 
     
    122122The divergence damping is activated by assigning to \np{nn\_divdmp} in the \textit{nam\_asminc} namelist 
    123123a value greater than zero. 
    124 By choosing this value to be of the order of 100 the increments in 
    125 the vertical velocity will be significantly reduced. 
     124This specifies the number of iterations of the divergence damping. Setting a value of the order of 100 will result in a significant reduction in the vertical velocity induced by the increments. 
    126125 
    127126 
     
    131130\label{sec:ASM_details} 
    132131 
    133 Here we show an example \ngn{namasm} namelist and the header of an example assimilation increments file on 
     132Here we show an example \ngn{nam\_asminc} namelist and the header of an example assimilation increments file on 
    134133the ORCA2 grid. 
    135134 
    136 %------------------------------------------namasm----------------------------------------------------- 
     135%------------------------------------------nam_asminc----------------------------------------------------- 
    137136% 
    138137\nlst{nam_asminc} 
  • NEMO/branches/2019/dev_r11233_obsasm_docfixes/doc/latex/NEMO/subfiles/chap_OBS.tex

    r11151 r11296  
    88\label{chap:OBS} 
    99 
    10 Authors: D. Lea, M. Martin, K. Mogensen, A. Vidard, A. Weaver, A. Ryan, ...   % do we keep that ? 
     10Authors: D. Lea, M. Martin, K. Mogensen, A. Vidard, A. Weaver, A. Ryan. 
    1111 
    1212\minitoc 
     
    1414\newpage 
    1515 
    16 The observation and model comparison code (OBS) reads in observation files 
     16The observation and model comparison code, the observation operator (OBS), reads in observation files 
    1717(profile temperature and salinity, sea surface temperature, sea level anomaly, sea ice concentration, and velocity) and calculates an interpolated model equivalent value at the observation location and nearest model timestep. 
    1818The resulting data are saved in a ``feedback'' file (or files). 
     
    2222The OBS code is called from \mdl{nemogcm} for model initialisation and to calculate the model equivalent values for observations on the 0th timestep. 
    2323The code is then called again after each timestep from \mdl{step}. 
    24 The code is only activated if the namelist logical \np{ln\_diaobs} is set to true. 
     24The code is only activated if the \ngn{namobs} namelist logical \np{ln\_diaobs} is set to true. 
    2525 
    2626For all data types a 2D horizontal interpolator or averager is needed to 
     
    2828For {\em in situ} profiles, a 1D vertical interpolator is needed in addition to 
    2929provide model fields at the observation depths. 
    30 This now works in a generalised vertical coordinate system.  
     30This now works in a generalised vertical coordinate system. 
    3131 
    3232Some profile observation types (\eg tropical moored buoys) are made available as daily averaged quantities. 
     
    3636the observation operator code can calculate equivalent night-time average model SST fields by 
    3737setting the namelist value \np{ln\_sstnight} to true. 
    38 Otherwise the model value from the nearest timestep to the observation time is used. 
    39  
    40 The code is controlled by the namelist \textit{namobs}. 
     38Otherwise (by default) the model value from the nearest timestep to the observation time is used. 
     39 
     40The code is controlled by the namelist \ngn{namobs}. 
    4141See the following sections for more details on setting up the namelist. 
    4242 
     
    4747\autoref{sec:OBS_theory} introduces some of the theoretical aspects of the observation operator including 
    4848interpolation methods and running on multiple processors. 
    49 \autoref{sec:OBS_ooo} describes the offline observation operator code. 
     49\autoref{sec:OBS_sao} describes the standalone observation operator code. 
    5050\autoref{sec:OBS_obsutils} introduces some utilities to help working with the files produced by the OBS code. 
    5151 
     
    5656\label{sec:OBS_example} 
    5757 
    58 This section describes an example of running the observation operator code using 
    59 profile data which can be freely downloaded. 
    60 It shows how to adapt an existing run and build of NEMO to run the observation operator. 
     58In this section an example of running the observation operator code is described using 
     59profile observation data which can be freely downloaded. 
     60It shows how to adapt an existing run and build of NEMO to run the observation operator. Note also the observation operator and the assimilation increments code are run in the \np{ORCA2\_ICE\_OBS} SETTE test. 
    6161 
    6262\begin{enumerate} 
     
    6565\item Download some EN4 data from \href{http://www.metoffice.gov.uk/hadobs}{www.metoffice.gov.uk/hadobs}. 
    6666  Choose observations which are valid for the period of your test run because 
    67   the observation operator compares the model and observations for a matching date and time.  
    68  
    69 \item Compile the OBSTOOLS code using:  
     67  the observation operator compares the model and observations for a matching date and time. 
     68 
     69\item Compile the OBSTOOLS code in the \np{tools} directory using: 
    7070\begin{cmds} 
    71 ./maketools -n OBSTOOLS -m [ARCH]. 
     71./maketools -n OBSTOOLS -m [ARCH] 
    7272\end{cmds} 
    7373 
    74 \item Convert the EN4 data into feedback format:  
     74replacing \np{[ARCH]} with the build architecture file for your machine. Note the tools are checked out from a separate repository under \np{utils/tools}. 
     75 
     76\item Convert the EN4 data into feedback format: 
    7577\begin{cmds} 
    7678enact2fb.exe profiles_01.nc EN.4.1.1.f.profiles.g10.YYYYMM.nc 
     
    8789This can be expensive, particularly for large numbers of observations, 
    8890setting \np{ln\_grid\_search\_lookup} allows the use of a lookup table which 
    89 is saved into an ``xypos`` file (or files). 
     91is saved into an \np{cn\_gridsearch} file (or files). 
    9092This will need to be generated the first time if it does not exist in the run directory. 
    9193However, once produced it will significantly speed up future grid searches. 
    9294Setting \np{ln\_grid\_global} means that the code distributes the observations evenly between processors. 
    9395Alternatively each processor will work with observations located within the model subdomain 
    94 (see section~\autoref{subsec:OBS_parallel}). 
     96(see \autoref{subsec:OBS_parallel}). 
    9597 
    9698A number of utilities are now provided to plot the feedback files, convert and recombine the files. 
    97 These are explained in more detail in section~\autoref{sec:OBS_obsutils}. 
     99These are explained in more detail in \autoref{sec:OBS_obsutils}. 
    98100Utilites to convert other input data formats into the feedback format are also described in 
    99 section~\autoref{sec:OBS_obsutils}. 
     101\autoref{sec:OBS_obsutils}. 
    100102 
    101103\section{Technical details (feedback type observation file headers)} 
     
    110112%------------------------------------------------------------------------------------------------------------- 
    111113 
    112 The observation operator code uses the "feedback" observation file format for all data types. 
     114The observation operator code uses the feedback observation file format for all data types. 
    113115All the observation files must be in NetCDF format. 
    114116Some example headers (produced using \mbox{\textit{ncdump~-h}}) for profile data, sea level anomaly and 
    115117sea surface temperature are in the following subsections. 
    116118 
    117 \subsection{Profile feedback} 
     119\subsection{Profile feedback file} 
    118120 
    119121\begin{clines} 
     
    271273\end{clines} 
    272274 
    273 \subsection{Sea level anomaly feedback} 
     275\subsection{Sea level anomaly feedback file} 
    274276 
    275277\begin{clines} 
     
    395397\end{clines} 
    396398 
    397 The mean dynamic topography (MDT) must be provided in a separate file defined on 
     399To use Sea Level Anomaly (SLA) data the mean dynamic topography (MDT) must be provided in a separate file defined on 
    398400the model grid called \ifile{slaReferenceLevel}. 
    399401The MDT is required in order to produce the model equivalent sea level anomaly from the model sea surface height. 
     
    417419\end{clines} 
    418420 
    419 \subsection{Sea surface temperature feedback} 
     421\subsection{Sea surface temperature feedback file} 
    420422 
    421423\begin{clines} 
     
    547549the same size as the footprint. 
    548550NEMO therefore has the capability to specify either an interpolation or an averaging 
    549 (for surface observation types only).  
     551(for surface observation types only). 
    550552 
    551553The main namelist option associated with the interpolation/averaging is \np{nn\_2dint}. 
     
    559561\item \np{nn\_2dint}\forcode{ = 4}: Polynomial interpolation 
    560562\item \np{nn\_2dint}\forcode{ = 5}: Radial footprint averaging with diameter specified in the namelist as 
    561   \np{rn\_???\_avglamscl} in degrees or metres (set using \np{ln\_???\_fp\_indegs}) 
     563  \np{rn\_[var]\_avglamscl} in degrees or metres (set using \np{ln\_[var]\_fp\_indegs}) 
    562564\item \np{nn\_2dint}\forcode{ = 6}: Rectangular footprint averaging with E/W and N/S size specified in 
    563   the namelist as \np{rn\_???\_avglamscl} and \np{rn\_???\_avgphiscl} in degrees or metres 
    564   (set using \np{ln\_???\_fp\_indegs}) 
     565  the namelist as \np{rn\_[var]\_avglamscl} and \np{rn\_[var]\_avgphiscl} in degrees or metres 
     566  (set using \np{ln\_[var]\_fp\_indegs}) 
    565567\end{itemize} 
    566 The ??? in the last two options indicate these options should be specified for each observation type for 
     568Replace \np{[var]} in the last two options with the observation type (sla, sst, sss or sic) for 
    567569which the averaging is to be performed (see namelist example above). 
    568570The \np{nn\_2dint} default option can be overridden for surface observation types using 
    569 namelist values \np{nn\_2dint\_???} where ??? is one of sla,sst,sss,sic. 
     571namelist values \np{nn\_2dint\_[var]} where \np{[var]} is the observation type. 
    570572 
    571573Below is some more detail on the various options for interpolation and averaging available in NEMO. 
     
    573575\subsubsection{Horizontal interpolation} 
    574576 
    575 Consider an observation point ${\mathrm P}$ with with longitude and latitude $({\lambda_{}}_{\mathrm P}, \phi_{\mathrm P})$ and 
     577Consider an observation point ${\mathrm P}$ with with longitude and latitude (${\lambda_{}}_{\mathrm P}$, $\phi_{\mathrm P}$) and 
    576578the four nearest neighbouring model grid points ${\mathrm A}$, ${\mathrm B}$, ${\mathrm C}$ and ${\mathrm D}$ with 
    577579longitude and latitude ($\lambda_{\mathrm A}$, $\phi_{\mathrm A}$),($\lambda_{\mathrm B}$, $\phi_{\mathrm B}$) etc. 
    578580All horizontal interpolation methods implemented in NEMO estimate the value of a model variable $x$ at point $P$ as 
    579581a weighted linear combination of the values of the model variables at the grid points ${\mathrm A}$, ${\mathrm B}$ etc.: 
     582 
    580583\begin{align*} 
    581   {x_{}}_{\mathrm P} & \hspace{-2mm} = \hspace{-2mm} & 
    582                                                    \frac{1}{w} \left( {w_{}}_{\mathrm A} {x_{}}_{\mathrm A} + 
    583                                                    {w_{}}_{\mathrm B} {x_{}}_{\mathrm B} + 
    584                                                    {w_{}}_{\mathrm C} {x_{}}_{\mathrm C} + 
    585                                                    {w_{}}_{\mathrm D} {x_{}}_{\mathrm D} \right) 
     584  {x_{}}_{\mathrm P} = 
     585\frac{1}{w} \left( {w_{}}_{\mathrm A} {x_{}}_{\mathrm A} + 
     586{w_{}}_{\mathrm B} {x_{}}_{\mathrm B} + 
     587{w_{}}_{\mathrm C} {x_{}}_{\mathrm C} + 
     588{w_{}}_{\mathrm D} {x_{}}_{\mathrm D} \right) 
    586589\end{align*} 
     590 
    587591where ${w_{}}_{\mathrm A}$, ${w_{}}_{\mathrm B}$ etc. are the respective weights for the model field at 
    588592points ${\mathrm A}$, ${\mathrm B}$ etc., and $w = {w_{}}_{\mathrm A} + {w_{}}_{\mathrm B} + {w_{}}_{\mathrm C} + {w_{}}_{\mathrm D}$. 
     
    597601  For example, the weight given to the field ${x_{}}_{\mathrm A}$ is specified as the product of the distances 
    598602  from ${\mathrm P}$ to the other points: 
    599   \begin{align*} 
     603 
     604  \begin{alignat*}{2} 
    600605    {w_{}}_{\mathrm A} = s({\mathrm P}, {\mathrm B}) \, s({\mathrm P}, {\mathrm C}) \, s({\mathrm P}, {\mathrm D}) 
    601   \end{align*} 
    602   where  
    603   \begin{align*} 
    604     s\left ({\mathrm P}, {\mathrm M} \right )  
    605      & \hspace{-2mm} = \hspace{-2mm} &  
    606       \cos^{-1} \! \left\{  
     606  \end{alignat*} 
     607 
     608  where 
     609 
     610  \begin{alignat*}{2} 
     611    s\left({\mathrm P}, {\mathrm M} \right) & = & \hspace{0.25em} \cos^{-1} \! \left\{ 
    607612               \sin {\phi_{}}_{\mathrm P} \sin {\phi_{}}_{\mathrm M} 
    608              + \cos {\phi_{}}_{\mathrm P} \cos {\phi_{}}_{\mathrm M}  
    609                \cos ({\lambda_{}}_{\mathrm M} - {\lambda_{}}_{\mathrm P})  
     613             + \cos {\phi_{}}_{\mathrm P} \cos {\phi_{}}_{\mathrm M} 
     614               \cos ({\lambda_{}}_{\mathrm M} - {\lambda_{}}_{\mathrm P}) 
    610615                   \right\} 
    611    \end{align*} 
     616   \end{alignat*} 
     617 
    612618   and $M$ corresponds to $B$, $C$ or $D$. 
    613619   A more stable form of the great-circle distance formula for small distances ($x$ near 1) 
    614620   involves the arcsine function (\eg see p.~101 of \citet{daley.barker_bk01}: 
    615    \begin{align*} 
    616      s\left( {\mathrm P}, {\mathrm M} \right) & \hspace{-2mm} = \hspace{-2mm} & \sin^{-1} \! \left\{ \sqrt{ 1 - x^2 } \right\} 
    617    \end{align*} 
     621 
     622   \begin{alignat*}{2} 
     623     s\left( {\mathrm P}, {\mathrm M} \right) = \sin^{-1} \! \left\{ \sqrt{ 1 - x^2 } \right\} 
     624   \end{alignat*} 
     625 
    618626   where 
    619    \begin{align*} 
    620      x & \hspace{-2mm} = \hspace{-2mm} & 
    621                                          {a_{}}_{\mathrm M} {a_{}}_{\mathrm P} + {b_{}}_{\mathrm M} {b_{}}_{\mathrm P} + {c_{}}_{\mathrm M} {c_{}}_{\mathrm P} 
    622    \end{align*} 
    623    and  
    624    \begin{align*} 
    625       {a_{}}_{\mathrm M} & \hspace{-2mm} = \hspace{-2mm} & \sin {\phi_{}}_{\mathrm M}, \\ 
    626       {a_{}}_{\mathrm P} & \hspace{-2mm} = \hspace{-2mm} & \sin {\phi_{}}_{\mathrm P}, \\ 
    627       {b_{}}_{\mathrm M} & \hspace{-2mm} = \hspace{-2mm} & \cos {\phi_{}}_{\mathrm M} \cos {\phi_{}}_{\mathrm M}, \\ 
    628       {b_{}}_{\mathrm P} & \hspace{-2mm} = \hspace{-2mm} & \cos {\phi_{}}_{\mathrm P} \cos {\phi_{}}_{\mathrm P}, \\ 
    629       {c_{}}_{\mathrm M} & \hspace{-2mm} = \hspace{-2mm} & \cos {\phi_{}}_{\mathrm M} \sin {\phi_{}}_{\mathrm M}, \\ 
    630       {c_{}}_{\mathrm P} & \hspace{-2mm} = \hspace{-2mm} & \cos {\phi_{}}_{\mathrm P} \sin {\phi_{}}_{\mathrm P}. 
    631   \end{align*} 
     627 
     628   \begin{alignat*}{2} 
     629     x = {a_{}}_{\mathrm M} {a_{}}_{\mathrm P} + {b_{}}_{\mathrm M} {b_{}}_{\mathrm P} + {c_{}}_{\mathrm M} {c_{}}_{\mathrm P} 
     630   \end{alignat*} 
     631 
     632   and 
     633 
     634   \begin{alignat*}{3} 
     635   & {a_{}}_{\mathrm M} & = && \quad \sin {\phi_{}}_{\mathrm M}, \\ 
     636   & {a_{}}_{\mathrm P} & = && \quad \sin {\phi_{}}_{\mathrm P}, \\ 
     637   & {b_{}}_{\mathrm M} & = && \quad \cos {\phi_{}}_{\mathrm M} \cos {\phi_{}}_{\mathrm M}, \\ 
     638   & {b_{}}_{\mathrm P} & = && \quad \cos {\phi_{}}_{\mathrm P} \cos {\phi_{}}_{\mathrm P}, \\ 
     639   & {c_{}}_{\mathrm M} & = && \quad \cos {\phi_{}}_{\mathrm M} \sin {\phi_{}}_{\mathrm M}, \\ 
     640   & {c_{}}_{\mathrm P} & = && \quad \cos {\phi_{}}_{\mathrm P} \sin {\phi_{}}_{\mathrm P}. 
     641   \end{alignat*} 
    632642 
    633643\item[2.] {\bfseries Great-Circle distance-weighted interpolation with small angle approximation.} 
    634644  Similar to the previous interpolation but with the distance $s$ computed as 
    635   \begin{align*} 
     645  \begin{alignat*}{2} 
    636646    s\left( {\mathrm P}, {\mathrm M} \right) 
    637     & \hspace{-2mm} = \hspace{-2mm} & 
    638                                       \sqrt{ \left( {\phi_{}}_{\mathrm M} - {\phi_{}}_{\mathrm P} \right)^{2} 
     647    & = & \sqrt{ \left( {\phi_{}}_{\mathrm M} - {\phi_{}}_{\mathrm P} \right)^{2} 
    639648                                      + \left( {\lambda_{}}_{\mathrm M} - {\lambda_{}}_{\mathrm P} \right)^{2} 
    640649                                      \cos^{2} {\phi_{}}_{\mathrm M} } 
    641   \end{align*} 
     650  \end{alignat*} 
    642651  where $M$ corresponds to $A$, $B$, $C$ or $D$. 
    643652 
     
    649658  a cell with coordinates (0,0), (1,0), (0,1) and (1,1). 
    650659  This method is based on the \href{https://github.com/SCRIP-Project/SCRIP}{SCRIP interpolation package}. 
    651    
     660 
    652661\end{enumerate} 
    653662 
     
    660669\item The maximum number of grid points is calculated in the local grid domain for which 
    661670  the averaging is likely need to cover. 
    662 \item The lats/longs of the grid points surrounding the nearest model grid box are extracted using 
     671\item The longitudes and latitudes of the grid points surrounding the nearest model grid box are extracted using 
    663672  existing mpi routines. 
    664673\item The weights for each grid point associated with each observation are calculated, 
     
    673682 
    674683Examples of the weights calculated for an observation with rectangular and radial footprints are shown in 
    675 Figs.~\autoref{fig:obsavgrec} and~\autoref{fig:obsavgrad}. 
     684\autoref{fig:obsavgrec} and~\autoref{fig:obsavgrad}. 
    676685 
    677686%>>>>>>>>>>>>>>>>>>>>>>>>>>>> 
     
    696705      Weights associated with each model grid box (blue lines and numbers) 
    697706      for an observation at -170.5\deg{E}, 56.0\deg{N} with a radial footprint with diameter 1\deg. 
    698     }  
     707    } 
    699708  \end{center} 
    700709\end{figure} 
     
    706715For many grids used by the NEMO model, such as the ORCA family, the horizontal grid coordinates $i$ and $j$ are not simple functions of latitude and longitude. 
    707716Therefore, it is not always straightforward to determine the grid points surrounding any given observational position. 
    708 Before the interpolation can be performed, a search algorithm is then required to determine the corner points of  
     717Before the interpolation can be performed, a search algorithm is then required to determine the corner points of 
    709718the quadrilateral cell in which the observation is located. 
    710 This is the most difficult and time consuming part of the 2D interpolation procedure.  
     719This is the most difficult and time consuming part of the 2D interpolation procedure. 
    711720A robust test for determining if an observation falls within a given quadrilateral cell is as follows. 
    712721Let ${\mathrm P}({\lambda_{}}_{\mathrm P} ,{\phi_{}}_{\mathrm P} )$ denote the observation point, 
    713722and let ${\mathrm A}({\lambda_{}}_{\mathrm A} ,{\phi_{}}_{\mathrm A} )$, ${\mathrm B}({\lambda_{}}_{\mathrm B} ,{\phi_{}}_{\mathrm B} )$, 
    714723${\mathrm C}({\lambda_{}}_{\mathrm C} ,{\phi_{}}_{\mathrm C} )$ and ${\mathrm D}({\lambda_{}}_{\mathrm D} ,{\phi_{}}_{\mathrm D} )$ 
    715 denote the bottom left, bottom right, top left and top right corner points of the cell, respectively.  
    716 To determine if P is inside the cell, we verify that the cross-products  
     724denote the bottom left, bottom right, top left and top right corner points of the cell, respectively. 
     725To determine if P is inside the cell, we verify that the cross-products 
    717726\begin{align*} 
    718727  \begin{array}{lllll} 
     
    750759be searched for on a regular grid. 
    751760For each observation position, the closest point on the regular grid of this position is computed and 
    752 the $i$ and $j$ ranges of this point searched to determine the precise four points surrounding the observation.  
     761the $i$ and $j$ ranges of this point searched to determine the precise four points surrounding the observation. 
    753762 
    754763\subsection{Parallel aspects of horizontal interpolation} 
     
    757766For horizontal interpolation, there is the basic problem that 
    758767the observations are unevenly distributed on the globe. 
    759 In numerical models, it is common to divide the model grid into subgrids (or domains) where 
     768In \NEMO the model grid is divided into subgrids (or domains) where 
    760769each subgrid is executed on a single processing element with explicit message passing for 
    761770exchange of information along the domain boundaries when running on a massively parallel processor (MPP) system. 
    762 This approach is used by \NEMO. 
    763  
    764 For observations there is no natural distribution since the observations are not equally distributed on the globe.  
     771 
     772For observations there is no natural distribution since the observations are not equally distributed on the globe. 
    765773Two options have been made available: 
    7667741) geographical distribution; 
     
    784792the domain of the grid-point parallelization. 
    785793\autoref{fig:obslocal} shows an example of the distribution of the {\em in situ} data on processors with 
    786 a different colour for each observation on a given processor for a 4 $\times$ 2 decomposition with ORCA2.  
     794a different colour for each observation on a given processor for a 4 $\times$ 2 decomposition with ORCA2. 
    787795The grid-point domain decomposition is clearly visible on the plot. 
    788796 
    789797The advantage of this approach is that all information needed for horizontal interpolation is available without 
    790798any MPP communication. 
    791 Of course, this is under the assumption that we are only using a $2 \times 2$ grid-point stencil for 
     799This is under the assumption that we are dealing with point observations and only using a $2 \times 2$ grid-point stencil for 
    792800the interpolation (\eg bilinear interpolation). 
    793801For higher order interpolation schemes this is no longer valid. 
     
    827835At the bottom boundary, this is done using the land-ocean mask. 
    828836 
     837For profile observation types we do both vertical and horizontal interpolation. NEMO has a generalised vertical coordinate system this means the vertical level depths can vary with location. Therefore, it is necessary first to perform vertical interpolation of the model value to the observation depths for each of the four surrounding grid points. After this the model values, at these points, at the observation depth, are horizontally interpolated to the observation location. 
     838 
    829839\newpage 
    830840 
    831841% ================================================================ 
    832 % Offline observation operator documentation 
     842% Standalone observation operator documentation 
    833843% ================================================================ 
    834844 
    835845%\usepackage{framed} 
    836846 
    837 \section{Offline observation operator} 
    838 \label{sec:OBS_ooo} 
     847\section{Standalone observation operator} 
     848\label{sec:OBS_sao} 
    839849 
    840850\subsection{Concept} 
    841851 
    842 The obs oper maps model variables to observation space. 
    843 It is possible to apply this mapping without running the model. 
    844 The software which performs this functionality is known as the \textbf{offline obs oper}. 
    845 The obs oper is divided into three stages. 
    846 An initialisation phase, an interpolation phase and an output phase. 
    847 The implementation of which is outlined in the previous sections. 
    848 During the interpolation phase the offline obs oper populates the model arrays by 
    849 reading saved model fields from disk. 
    850  
    851 There are two ways of exploiting this offline capacity. 
     852The observation operator maps model variables to observation space. This is normally done while the model is running, i.e. online, it is possible to apply this mapping offline without running the model with the \textbf{standalone observation operator} (SAO). The process is divided into an initialisation phase, an interpolation phase and an output phase. 
     853During the interpolation phase the SAO populates the model arrays by 
     854reading saved model fields from disk. The interpolation and the output phases use the same OBS code described in the preceeding sections. 
     855 
     856There are two ways of exploiting the standalone capacity. 
    852857The first is to mimic the behaviour of the online system by supplying model fields at 
    853858regular intervals between the start and the end of the run. 
    854859This approach results in a single model counterpart per observation. 
    855 This kind of usage produces feedback files the same file format as the online obs oper. 
    856 The second is to take advantage of the offline setting in which 
    857 multiple model counterparts can be calculated per observation. 
     860This kind of usage produces feedback files the same file format as the online observation operator. 
     861The second is to take advantage of the ability to run offline by calculating 
     862multiple model counterparts for each observation. 
    858863In this case it is possible to consider all forecasts verifying at the same time. 
    859 By forecast, I mean any method which produces an estimate of physical reality which is not an observed value. 
    860 In the case of class 4 files this means forecasts, analyses, persisted analyses and 
    861 climatological values verifying at the same time. 
    862 Although the class 4 file format doesn't account for multiple ensemble members or 
    863 multiple experiments per observation, it is possible to include these components in the same or multiple files. 
     864By forecast, we mean any method which produces an estimate of physical reality which is not an observed value. 
    864865 
    865866%-------------------------------------------------------------------------------------------------------- 
    866 % offline_oper.exe  
     867% sao.exe 
    867868%-------------------------------------------------------------------------------------------------------- 
    868869 
    869 \subsection{Using the offline observation operator} 
     870\subsection{Using the standalone observation operator} 
    870871 
    871872\subsubsection{Building} 
    872873 
    873 In addition to \emph{OPA\_SRC} the offline obs oper requires the inclusion of the \emph{OOO\_SRC} directory. 
    874 \emph{OOO\_SRC} contains a replacement \mdl{nemo} and \mdl{nemogcm} which 
     874In addition to \emph{OPA\_SRC} the SAO requires the inclusion of the \emph{SAO\_SRC} directory. 
     875\emph{SAO\_SRC} contains a replacement \mdl{nemo} and \mdl{nemogcm} which 
    875876overwrites the resultant \textbf{nemo.exe}. 
    876 This is the approach taken by \emph{SAS\_SRC} and \emph{OFF\_SRC}. 
     877Note this a similar approach to that taken by the standalone surface scheme \emph{SAS\_SRC} and the offline TOP model \emph{OFF\_SRC}. 
    877878 
    878879%-------------------------------------------------------------------------------------------------------- 
    879 % Running  
     880% Running 
    880881%-------------------------------------------------------------------------------------------------------- 
    881882\subsubsection{Running} 
    882883 
    883 The simplest way to use the executable is to edit and append the \textbf{ooo.nml} namelist to 
    884 a full NEMO namelist and then to run the executable as if it were nemo.exe.  
    885  
    886 \subsubsection{Quick script} 
    887  
    888 A useful Python utility to control the namelist options can be found in \textbf{OBSTOOLS/OOO}. 
    889 The functions which locate model fields and observation files can be manually specified. 
    890 The package can be installed by appropriate use of the included setup.py script. 
    891  
    892 Documentation can be auto-generated by Sphinx by running \emph{make html} in the \textbf{doc} directory. 
     884The simplest way to use the executable is to edit and append the \textbf{sao.nml} namelist to 
     885a full NEMO namelist and then to run the executable as if it were nemo.exe. 
    893886 
    894887%-------------------------------------------------------------------------------------------------------- 
    895888% Configuration section 
    896889%-------------------------------------------------------------------------------------------------------- 
    897 \subsection{Configuring the offline observation operator} 
    898 The observation files and settings understood by \textbf{namobs} have been outlined in the online obs oper section. 
    899 In addition there are two further namelists wich control the operation of the offline obs oper. 
    900 \textbf{namooo} which controls the input model fields and \textbf{namcl4} which 
    901 controls the production of class 4 files.  
     890\subsection{Configuring the standalone observation operator} 
     891The observation files and settings understood by \ngn{namobs} have been outlined in the online observation operator section. 
     892In addition there are two further namelists wich control the operation of the SAO. 
     893\textbf{namsao} which controls the input model fields and \textbf{namcl4} which 
     894controls the production of class 4 files. 
    902895 
    903896\subsubsection{Single field} 
    904897 
    905 In offline mode model arrays are populated at appropriate time steps via input files. 
    906 At present, \textbf{tsn} and \textbf{sshn} are populated by the default read routines.  
     898In the SAO the model arrays are populated at appropriate time steps via input files. 
     899At present, \textbf{tsn} and \textbf{sshn} are populated by the default read routines. 
    907900These routines will be expanded upon in future versions to allow the specification of any model variable. 
    908901As such, input files must be global versions of the model domain with 
    909902\textbf{votemper}, \textbf{vosaline} and optionally \textbf{sshn} present. 
    910903 
    911 For each field read there must be an entry in the \textbf{namooo} namelist specifying 
     904For each field read there must be an entry in the \textbf{namsao} namelist specifying 
    912905the name of the file to read and the index along the \emph{time\_counter}. 
    913906For example, to read the second time counter from a single file the namelist would be. 
     
    915908\begin{forlines} 
    916909!---------------------------------------------------------------------- 
    917 !       namooo Offline obs_oper namelist 
     910!       namsao Standalone obs_oper namelist 
    918911!---------------------------------------------------------------------- 
    919 !   ooo_files    specifies the files containing the model counterpart 
    920 !   nn_ooo_idx   specifies the time_counter index within the model file 
    921 &namooo 
    922    ooo_files = "foo.nc" 
    923    nn_ooo_idx = 2 
     912!   sao_files    specifies the files containing the model counterpart 
     913!   nn_sao_idx   specifies the time_counter index within the model file 
     914&namsao 
     915   sao_files = "foo.nc" 
     916   nn_sao_idx = 2 
    924917/ 
    925918\end{forlines} 
     
    927920\subsubsection{Multiple fields per run} 
    928921 
    929 Model field iteration is controlled via \textbf{nn\_ooo\_freq} which 
     922Model field iteration is controlled via \textbf{nn\_sao\_freq} which 
    930923specifies the number of model steps at which the next field gets read. 
    931924For example, if 12 hourly fields are to be interpolated in a setup where 288 steps equals 24 hours. 
     
    933926\begin{forlines} 
    934927!---------------------------------------------------------------------- 
    935 !       namooo Offline obs_oper namelist 
     928!       namsao Standalone obs_oper namelist 
    936929!---------------------------------------------------------------------- 
    937 !   ooo_files    specifies the files containing the model counterpart 
    938 !   nn_ooo_idx   specifies the time_counter index within the model file 
    939 !   nn_ooo_freq  specifies number of time steps between read operations 
    940 &namooo 
    941    ooo_files = "foo.nc" "foo.nc" 
    942    nn_ooo_idx = 1 2 
    943    nn_ooo_freq = 144 
     930!   sao_files    specifies the files containing the model counterpart 
     931!   nn_sao_idx   specifies the time_counter index within the model file 
     932!   nn_sao_freq  specifies number of time steps between read operations 
     933&namsao 
     934   sao_files = "foo.nc" "foo.nc" 
     935   nn_sao_idx = 1 2 
     936   nn_sao_freq = 144 
    944937/ 
    945938\end{forlines} 
     
    952945%\end{framed} 
    953946 
    954 It is easy to see how a collection of fields taken fron a number of files at different indices can be combined at 
     947A collection of fields taken from a number of files at different indices can be combined at 
    955948a particular frequency in time to generate a pseudo model evolution. 
    956 As long as all that is needed is a single model counterpart at a regular interval then 
    957 namooo is all that needs to be edited. 
    958 However, a far more interesting approach can be taken in which multiple forecasts, analyses, persisted analyses and 
    959 climatologies are considered against the same set of observations. 
    960 For this a slightly more complicated approach is needed. 
    961 It is referred to as \emph{Class 4} since it is the fourth metric defined by the GODAE intercomparison project. 
    962  
    963 %-------------------------------------------------------------------------------------------------------- 
    964 % Class 4 file section 
    965 %-------------------------------------------------------------------------------------------------------- 
    966 \subsubsection{Multiple model counterparts per observation a.k.a Class 4} 
    967  
    968 A generalisation of feedback files to allow multiple model components per observation. 
    969 For a single observation, as well as previous forecasts verifying at the same time 
    970 there are also analyses, persisted analyses and climatologies.  
    971  
    972  
    973 The above namelist performs two basic functions. 
    974 It organises the fields given in \textbf{namooo} into groups so that observations can be matched up multiple times. 
    975 It also controls the metadata and the output variable of the class 4 file when a write routine is called. 
    976  
    977 %\begin{framed} 
    978 \textbf{Note: ln\_cl4} must be set to \forcode{.true.} in \textbf{namobs} to use class 4 outputs. 
    979 %\end{framed} 
    980  
    981 \subsubsection{Class 4 naming convention} 
    982  
    983 The standard class 4 file naming convention is as follows. 
    984  
    985 \noindent 
    986 \linebreak 
    987 \textbf{\$\{prefix\}\_\$\{yyyymmdd\}\_\$\{sys\}\_\$\{cfg\}\_\$\{vn\}\_\$\{kind\}\_\$\{nproc\}}.nc 
    988  
    989 \noindent 
    990 \linebreak 
    991 Much of the namelist is devoted to specifying this convention. 
    992 The following namelist settings control the elements of the output file names. 
    993 Each should be specified as a single string of character data. 
    994  
    995 \begin{description} 
    996 \item[cl4\_prefix] 
    997   Prefix for class 4 files \eg class4 
    998 \item[cl4\_date] 
    999   YYYYMMDD validity date 
    1000 \item[cl4\_sys] 
    1001   The name of the class 4 model system \eg FOAM 
    1002 \item[cl4\_cfg] 
    1003   The name of the class 4 model configuration \eg orca025 
    1004 \item[cl4\_vn] 
    1005   The name of the class 4 model version \eg 12.0 
    1006 \end{description} 
    1007  
    1008 \noindent 
    1009 The kind is specified by the observation type internally to the obs oper. 
    1010 The processor number is specified internally in NEMO.  
    1011  
    1012 \subsubsection{Class 4 file global attributes} 
    1013  
    1014 Global attributes necessary to fulfill the class 4 file definition. 
    1015 These are also useful pieces of information when collaborating with external partners. 
    1016  
    1017 \begin{description} 
    1018 \item[cl4\_contact] 
    1019   Contact email for class 4 files. 
    1020 \item[cl4\_inst] 
    1021   The name of the producers institution. 
    1022 \item[cl4\_cfg] 
    1023   The name of the class 4 model configuration \eg orca025 
    1024 \item[cl4\_vn] 
    1025   The name of the class 4 model version \eg 12.0 
    1026 \end{description} 
    1027  
    1028 \noindent 
    1029 The obs\_type, creation date and validity time are specified internally to the obs oper. 
    1030  
    1031 \subsubsection{Class 4 model counterpart configuration} 
    1032  
    1033 As seen previously it is possible to perform a single sweep of the obs oper and 
    1034 specify a collection of model fields equally spaced along that sweep. 
    1035 In the class 4 case the single sweep is replaced with multiple sweeps and 
    1036 a certain ammount of book keeping is needed to ensure each model counterpart makes its way to 
    1037 the correct piece of memory in the output files. 
    1038  
    1039 \noindent 
    1040 \linebreak 
    1041 In terms of book keeping, the offline obs oper needs to know how many full sweeps need to be performed. 
    1042 This is specified via the \textbf{cl4\_match\_len} variable and 
    1043 is the total number of model counterparts per observation. 
    1044 For example, a 3 forecasts plus 3 persistence fields plus an analysis field would be 7 counterparts per observation. 
    1045  
    1046 \begin{forlines} 
    1047    cl4_match_len = 7 
    1048 \end{forlines} 
    1049  
    1050 Then to correctly allocate a class 4 file the forecast axis must be defined. 
    1051 This is controlled via \textbf{cl4\_fcst\_len}, which in out above example would be 3. 
    1052  
    1053 \begin{forlines} 
    1054    cl4_fcst_len = 3 
    1055 \end{forlines} 
    1056  
    1057 Then for each model field it is necessary to designate what class 4 variable and index along 
    1058 the forecast dimension the model counterpart should be stored in the output file. 
    1059 As well as a value for that lead time in hours, this will be useful when interpreting the data afterwards.  
    1060  
    1061 \begin{forlines} 
    1062    cl4_vars = "forecast" "forecast" "forecast" "persistence" "persistence" 
    1063               "persistence" "best_estimate" 
    1064    cl4_fcst_idx = 1 2 3 1 2 3 1 
    1065    cl4_leadtime = 12 36 60  
    1066 \end{forlines} 
    1067  
    1068 In terms of files and indices of fields inside each file the class 4 approach makes use of 
    1069 the \textbf{namooo} namelist. 
    1070 If our fields are in separate files with a single field per file our example inputs will be specified. 
    1071  
    1072 \begin{forlines} 
    1073    ooo_files = "F.1.nc" "F.2.nc" "F.3.nc" "P.1.nc" "P.2.nc" "P.3.nc" "A.1.nc" 
    1074    nn_ooo_idx = 1 1 1 1 1 1 1 
    1075 \end{forlines} 
    1076  
    1077 When we combine all of the naming conventions, global attributes and i/o instructions the class 4 namelist becomes. 
    1078  
    1079 \begin{forlines} 
    1080 !---------------------------------------------------------------------- 
    1081 !       namooo Offline obs_oper namelist 
    1082 !---------------------------------------------------------------------- 
    1083 !   ooo_files    specifies the files containing the model counterpart 
    1084 !   nn_ooo_idx   specifies the time_counter index within the model file 
    1085 !   nn_ooo_freq  specifies number of time steps between read operations 
    1086 &namooo 
    1087    ooo_files = "F.1.nc" "F.2.nc" "F.3.nc" "P.1.nc" "P.2.nc" "P.3.nc" "A.1.nc" 
    1088    nn_ooo_idx = 1 1 1 1 1 1 1 
    1089 / 
    1090 !---------------------------------------------------------------------- 
    1091 !       namcl4 Offline obs_oper class 4 namelist 
    1092 !---------------------------------------------------------------------- 
    1093 ! 
    1094 !  Naming convention 
    1095 !  ----------------- 
    1096 !  cl4_prefix    specifies the output file prefix 
    1097 !  cl4_date      specifies the output file validity date 
    1098 !  cl4_sys       specifies the model counterpart system 
    1099 !  cl4_cfg       specifies the model counterpart configuration 
    1100 !  cl4_vn        specifies the model counterpart version 
    1101 !  cl4_inst      specifies the model counterpart institute 
    1102 !  cl4_contact   specifies the file producers contact details 
    1103 ! 
    1104 !  I/O specification 
    1105 !  ----------------- 
    1106 !  cl4_vars      specifies the names of the output file netcdf variable 
    1107 !  cl4_fcst_idx  specifies output file forecast index 
    1108 !  cl4_fcst_len  specifies forecast axis length 
    1109 !  cl4_match_len specifies number of unique matches per observation 
    1110 !  cl4_leadtime  specifies the forecast axis lead time  
    1111 ! 
    1112 &namcl4 
    1113    cl4_match_len = 7 
    1114    cl4_fcst_len = 3 
    1115    cl4_fcst_idx = 1 2 3 1 2 3 1 
    1116    cl4_vars = "forecast" "forecast" "forecast" "persistence" "persistence" 
    1117               "persistence" "best_estimate" 
    1118    cl4_leadtime = 12 36 60 
    1119    cl4_prefix = "class4" 
    1120    cl4_date = "20130101" 
    1121    cl4_vn = "12.0" 
    1122    cl4_sys = "FOAM" 
    1123    cl4_cfg = "AMM7" 
    1124    cl4_contact = "example@example.com" 
    1125    cl4_inst = "UK Met Office" 
    1126 / 
    1127 \end{forlines} 
    1128  
    1129 \subsubsection{Climatology interpolation} 
    1130  
    1131 The climatological counterpart is generated at the start of the run by 
    1132 restarting the model from climatology through appropriate use of \textbf{namtsd}. 
    1133 To override the offline observation operator read routine and to take advantage of the restart settings, 
    1134 specify the first entry in \textbf{cl4\_vars} as "climatology". 
    1135 This will then pipe the restart from climatology into the output class 4 file. 
    1136 As in every other class 4 matchup the input file, input index and output index must be specified. 
    1137 These can be replaced with dummy data since they are not used but 
    1138 they must be present to cycle through the matchups correctly.  
    1139  
    1140 \subsection{Advanced usage} 
    1141  
    1142 In certain cases it may be desirable to include both multiple model fields per observation window with 
    1143 multiple match ups per observation. 
    1144 This can be achieved by specifying \textbf{nn\_ooo\_freq} as well as the class 4 settings. 
    1145 Care must be taken in generating the ooo\_files list such that the files are arranged into 
    1146 consecutive blocks of single match ups. 
    1147 For example, 2 forecast fields of 12 hourly data would result in 4 separate read operations but 
    1148 only 2 write operations, 1 per forecast. 
    1149  
    1150 \begin{forlines} 
    1151    ooo_files = "F1.nc" "F1.nc" "F2.nc" "F2.nc" 
    1152 ... 
    1153    cl4_fcst_idx = 1 2 
    1154 \end{forlines} 
    1155  
    1156 The above notation reveals the internal split between match up iterators and file iterators. 
    1157 This technique has not been used before so experimentation is needed before results can be trusted. 
     949If all that is needed is a single model counterpart at a regular interval then 
     950the standard SAO is all that is required. 
     951However, it is possible to extend this approach by comparing multiple forecasts, analyses, persisted analyses and 
     952climatologies with the same set of observations. 
     953This approach is referred to as \emph{Class 4} since it is the fourth metric defined by the GODAE intercomparison project. This requires multiple runs of the SAO and running an additional utility (not currently in the NEMO repository) to combine the feedback files into one class 4 file. 
    1158954 
    1159955\newpage 
     
    1162958\label{sec:OBS_obsutils} 
    1163959 
    1164 Some tools for viewing and processing of observation and feedback files are provided in 
    1165 the NEMO repository for convenience. 
    1166 These include OBSTOOLS which are a collection of \fortran programs which are helpful to deal with feedback files. 
     960For convenience some tools for viewing and processing of observation and feedback files are provided in 
     961the NEMO repository. 
     962These tools include OBSTOOLS which are a collection of \fortran programs which are helpful to deal with feedback files. 
    1167963They do such tasks as observation file conversion, printing of file contents, 
    1168964some basic statistical analysis of feedback files. 
    1169 The other tool is an IDL program called dataplot which uses a graphical interface to 
     965The other main tool is an IDL program called dataplot which uses a graphical interface to 
    1170966visualise observations and feedback files. 
    1171967OBSTOOLS and dataplot are described in more detail below. 
     
    1174970 
    1175971A series of \fortran utilities is provided with NEMO called OBSTOOLS. 
    1176 This are helpful in handling observation files and the feedback file output from the NEMO observation operator. 
    1177 The utilities are as follows 
    1178  
    1179 \subsubsection{c4comb} 
    1180  
    1181 The program c4comb combines multiple class 4 files produced by individual processors in 
    1182 an MPI run of NEMO offline obs\_oper into a single class 4 file. 
    1183 The program is called in the following way: 
    1184  
    1185  
    1186 \footnotesize 
    1187 \begin{cmds} 
    1188 c4comb.exe outputfile inputfile1 inputfile2 ... 
    1189 \end{cmds} 
     972This are helpful in handling observation files and the feedback file output from the NEMO observation operator. A brief description of some of the utilities follows 
    1190973 
    1191974\subsubsection{corio2fb} 
    1192975 
    1193976The program corio2fb converts profile observation files from the Coriolis format to the standard feedback format. 
    1194 The program is called in the following way: 
    1195  
    1196 \footnotesize 
     977It is called in the following way: 
     978 
    1197979\begin{cmds} 
    1198980corio2fb.exe outputfile inputfile1 inputfile2 ... 
     
    1202984 
    1203985The program enact2fb converts profile observation files from the ENACT format to the standard feedback format. 
    1204 The program is called in the following way: 
    1205  
    1206 \footnotesize 
     986It is called in the following way: 
     987 
    1207988\begin{cmds} 
    1208989enact2fb.exe outputfile inputfile1 inputfile2 ... 
     
    1213994The program fbcomb combines multiple feedback files produced by individual processors in 
    1214995an MPI run of NEMO into a single feedback file. 
    1215 The program is called in the following way: 
    1216  
    1217 \footnotesize 
     996It is called in the following way: 
     997 
    1218998\begin{cmds} 
    1219999fbcomb.exe outputfile inputfile1 inputfile2 ... 
     
    12231003 
    12241004The program fbmatchup will match observations from two feedback files. 
    1225 The program is called in the following way: 
    1226  
    1227 \footnotesize 
     1005It is called in the following way: 
     1006 
    12281007\begin{cmds} 
    12291008fbmatchup.exe outputfile inputfile1 varname1 inputfile2 varname2 ... 
     
    12341013The program fbprint will print the contents of a feedback file or files to standard output. 
    12351014Selected information can be output using optional arguments. 
    1236 The program is called in the following way: 
    1237  
    1238 \footnotesize 
     1015It is called in the following way: 
     1016 
    12391017\begin{cmds} 
    12401018fbprint.exe [options] inputfile 
     
    12461024     -B            Select observations based on QC flags 
    12471025     -u            unsorted 
    1248      -s ID         select station ID   
     1026     -s ID         select station ID 
    12491027     -t TYPE       select observation type 
    1250      -v NUM1-NUM2  select variable range to print by number  
     1028     -v NUM1-NUM2  select variable range to print by number 
    12511029                      (default all) 
    1252      -a NUM1-NUM2  select additional variable range to print by number  
     1030     -a NUM1-NUM2  select additional variable range to print by number 
    12531031                      (default all) 
    1254      -e NUM1-NUM2  select extra variable range to print by number  
     1032     -e NUM1-NUM2  select extra variable range to print by number 
    12551033                      (default all) 
    12561034     -d            output date range 
     
    12621040 
    12631041The program fbsel will select or subsample observations. 
    1264 The program is called in the following way: 
    1265  
    1266 \footnotesize 
     1042It is called in the following way: 
     1043 
    12671044\begin{cmds} 
    12681045fbsel.exe <input filename> <output filename> 
     
    12721049 
    12731050The program fbstat will output summary statistics in different global areas into a number of files. 
    1274 The program is called in the following way: 
    1275  
    1276 \footnotesize 
     1051It is called in the following way: 
     1052 
    12771053\begin{cmds} 
    12781054fbstat.exe [-nmlev] <filenames> 
     
    12831059The program fbthin will thin the data to 1 degree resolution. 
    12841060The code could easily be modified to thin to a different resolution. 
    1285 The program is called in the following way: 
    1286  
    1287 \footnotesize 
     1061It is called in the following way: 
     1062 
    12881063\begin{cmds} 
    12891064fbthin.exe inputfile outputfile 
     
    12931068 
    12941069The program sla2fb will convert an AVISO SLA format file to feedback format. 
    1295 The program is called in the following way: 
    1296  
    1297 \footnotesize 
     1070It is called in the following way: 
     1071 
    12981072\begin{cmds} 
    12991073sla2fb.exe [-s type] outputfile inputfile1 inputfile2 ... 
     
    13061080 
    13071081The program vel2fb will convert TAO/PIRATA/RAMA currents files to feedback format. 
    1308 The program is called in the following way: 
    1309  
    1310 \footnotesize 
     1082It is called in the following way: 
     1083 
    13111084\begin{cmds} 
    13121085vel2fb.exe outputfile inputfile1 inputfile2 ... 
     
    13201093 
    13211094An IDL program called dataplot is included which uses a graphical interface to 
    1322 visualise observations and feedback files. 
     1095visualise observations and feedback files. Note a similar package has recently developed in python (also called dataplot) which does some of the same things that the IDL dataplot does. Please contact the authors of the this chapter if you are interested in this. 
     1096 
    13231097It is possible to zoom in, plot individual profiles and calculate some basic statistics. 
    13241098To plot some data run IDL and then: 
    1325 \footnotesize 
     1099 
    13261100\begin{minted}{idl} 
    13271101IDL> dataplot, "filename" 
     
    13311105for example multiple feedback files from different processors or from different days, 
    13321106the easiest method is to use the spawn command to generate a list of files which can then be passed to dataplot. 
    1333 \footnotesize 
     1107 
    13341108\begin{minted}{idl} 
    13351109IDL> spawn, 'ls profb*.nc', files 
     
    13621136observation minus background value. 
    13631137The next group of radio buttons selects the map projection. 
    1364 This can either be regular latitude longitude grid, or north or south polar stereographic. 
     1138This can either be regular longitude latitude grid, or north or south polar stereographic. 
    13651139The next group of radio buttons will plot bad observations, switch to salinity and 
    13661140plot density for profile observations. 
  • NEMO/branches/2019/dev_r11233_obsasm_docfixes/doc/namelists/namobs

    r11005 r11296  
    88   ln_sla      = .false.             ! Logical switch for SLA observations 
    99   ln_sst      = .false.             ! Logical switch for SST observations 
    10    ln_sss      = .false.             ! Logical swithc for SSS observations 
     10   ln_sss      = .false.             ! Logical switch for SSS observations 
    1111   ln_sic      = .false.             ! Logical switch for Sea Ice observations 
    1212   ln_vel3d    = .false.             ! Logical switch for velocity observations 
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