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Timestamp:
2019-07-19T18:03:07+02:00 (14 months ago)
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djlea
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#2297 Fix a few typos

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1 edited

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

    r11307 r11311  
    1515\begin{tabular}{l||l|m{0.65\linewidth}} 
    1616    Release   & Author        & Modifications \\ 
    17     {\em 4.0} & {\em D. J. Lea} & {\em NEMO 4.0 updates}  \\ 
     17    {\em 4.0} & {\em D. J. Lea} & {\em \NEMO 4.0 updates}  \\ 
    1818    {\em 3.6} & {\em M. Martin, A. Ryan} & {\em Add averaging operator, standalone obs oper} \\ 
    1919    {\em 3.4} & {\em D. J. Lea, M. Martin, ...} & {\em Initial version}  \\ 
     
    2525 
    2626The observation and model comparison code, the observation operator (OBS), reads in observation files 
    27 (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. 
     27(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 time step. 
    2828The resulting data are saved in a ``feedback'' file (or files). 
    2929The code was originally developed for use with the NEMOVAR data assimilation code, 
    3030but can be used for validation or verification of the model or with any other data assimilation system. 
    3131 
    32 The OBS code is called from \mdl{nemogcm} for model initialisation and to calculate the model equivalent values for observations on the 0th timestep. 
    33 The code is then called again after each timestep from \mdl{step}. 
     32The OBS code is called from \mdl{nemogcm} for model initialisation and to calculate the model equivalent values for observations on the 0th time step. 
     33The code is then called again after each time step from \mdl{step}. 
    3434The code is only activated if the \ngn{namobs} namelist logical \np{ln\_diaobs} is set to true. 
    3535 
     
    4646the observation operator code can calculate equivalent night-time average model SST fields by 
    4747setting the namelist value \np{ln\_sstnight} to true. 
    48 Otherwise (by default) the model value from the nearest timestep to the observation time is used. 
     48Otherwise (by default) the model value from the nearest time step to the observation time is used. 
    4949 
    5050The code is controlled by the namelist \ngn{namobs}. 
    5151See the following sections for more details on setting up the namelist. 
    5252 
    53 \autoref{sec:OBS_example} introduces a test example of the observation operator code including 
     53In \autoref{sec:OBS_example} a test example of the observation operator code is introduced, including 
    5454where to obtain data and how to setup the namelist. 
    55 \autoref{sec:OBS_details} introduces some more technical details of the different observation types used and 
    56 also shows a more complete namelist. 
    57 \autoref{sec:OBS_theory} introduces some of the theoretical aspects of the observation operator including 
     55In \autoref{sec:OBS_details} some more technical details of the different observation types used are introduced, and we 
     56also show a more complete namelist. 
     57In \autoref{sec:OBS_theory} some of the theoretical aspects of the observation operator are described including 
    5858interpolation methods and running on multiple processors. 
    59 \autoref{sec:OBS_sao} describes the standalone observation operator code. 
    60 \autoref{sec:OBS_obsutils} introduces some utilities to help working with the files produced by the OBS code. 
     59In \autoref{sec:OBS_sao} the standalone observation operator code is described. 
     60In \autoref{sec:OBS_obsutils} we describe some utilities to help work with the files produced by the OBS code. 
    6161 
    6262% ================================================================ 
     
    6868In this section an example of running the observation operator code is described using 
    6969profile observation data which can be freely downloaded. 
    70 It 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. 
     70It 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. 
    7171 
    7272\begin{enumerate} 
     
    8989\end{cmds} 
    9090 
    91 \item Include the following in the NEMO namelist to run the observation operator on this data: 
     91\item Include the following in the \NEMO namelist to run the observation operator on this data: 
    9292\end{enumerate} 
    9393 
     
    108108A number of utilities are now provided to plot the feedback files, convert and recombine the files. 
    109109These are explained in more detail in \autoref{sec:OBS_obsutils}. 
    110 Utilites to convert other input data formats into the feedback format are also described in 
     110Utilities to convert other input data formats into the feedback format are also described in 
    111111\autoref{sec:OBS_obsutils}. 
    112112 
     
    558558In those cases the model counterpart should be calculated by averaging the model grid points over 
    559559the same size as the footprint. 
    560 NEMO therefore has the capability to specify either an interpolation or an averaging 
     560\NEMO therefore has the capability to specify either an interpolation or an averaging 
    561561(for surface observation types only). 
    562562 
     
    585585\subsubsection{Horizontal interpolation} 
    586586 
    587 Consider an observation point ${\mathrm P}$ with with longitude and latitude (${\lambda_{}}_{\mathrm P}$, $\phi_{\mathrm P}$) and 
     587Consider an observation point ${\mathrm P}$ with longitude and latitude (${\lambda_{}}_{\mathrm P}$, $\phi_{\mathrm P}$) and 
    588588the four nearest neighbouring model grid points ${\mathrm A}$, ${\mathrm B}$, ${\mathrm C}$ and ${\mathrm D}$ with 
    589589longitude and latitude ($\lambda_{\mathrm A}$, $\phi_{\mathrm A}$),($\lambda_{\mathrm B}$, $\phi_{\mathrm B}$) etc. 
    590 All horizontal interpolation methods implemented in NEMO estimate the value of a model variable $x$ at point $P$ as 
     590All horizontal interpolation methods implemented in \NEMO estimate the value of a model variable $x$ at point $P$ as 
    591591a weighted linear combination of the values of the model variables at the grid points ${\mathrm A}$, ${\mathrm B}$ etc.: 
    592592 
     
    680680  the averaging is likely need to cover. 
    681681\item The longitudes and latitudes of the grid points surrounding the nearest model grid box are extracted using 
    682   existing mpi routines. 
     682  existing MPI routines. 
    683683\item The weights for each grid point associated with each observation are calculated, 
    684684  either for radial or rectangular footprints. 
     
    723723\subsection{Grid search} 
    724724 
    725 For 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. 
     725For 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. 
    726726Therefore, it is not always straightforward to determine the grid points surrounding any given observational position. 
    727727Before the interpolation can be performed, a search algorithm is then required to determine the corner points of 
     
    845845At the bottom boundary, this is done using the land-ocean mask. 
    846846 
    847 For 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. 
     847For 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. 
    848848 
    849849\newpage 
     
    862862The 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. 
    863863During the interpolation phase the SAO populates the model arrays by 
    864 reading saved model fields from disk. The interpolation and the output phases use the same OBS code described in the preceeding sections. 
     864reading saved model fields from disk. The interpolation and the output phases use the same OBS code described in the preceding sections. 
    865865 
    866866There are two ways of exploiting the standalone capacity. 
     
    893893 
    894894The simplest way to use the executable is to edit and append the \textbf{sao.nml} namelist to 
    895 a full NEMO namelist and then to run the executable as if it were nemo.exe. 
     895a full \NEMO namelist and then to run the executable as if it were nemo.exe. 
    896896 
    897897%-------------------------------------------------------------------------------------------------------- 
     
    900900\subsection{Configuring the standalone observation operator} 
    901901The observation files and settings understood by \ngn{namobs} have been outlined in the online observation operator section. 
    902 In addition there are two further namelists wich control the operation of the SAO. 
    903 \textbf{namsao} which controls the input model fields and \textbf{namcl4} which 
    904 controls the production of class 4 files. 
     902In addition is a further namelist \ngn{namsao} which used to set the input model fields for the SAO 
    905903 
    906904\subsubsection{Single field} 
     
    912910\textbf{votemper}, \textbf{vosaline} and optionally \textbf{sshn} present. 
    913911 
    914 For each field read there must be an entry in the \textbf{namsao} namelist specifying 
     912For each field read there must be an entry in the \ngn{namsao} namelist specifying 
    915913the name of the file to read and the index along the \emph{time\_counter}. 
    916914For example, to read the second time counter from a single file the namelist would be. 
     
    959957If all that is needed is a single model counterpart at a regular interval then 
    960958the standard SAO is all that is required. 
    961 However, it is possible to extend this approach by comparing multiple forecasts, analyses, persisted analyses and 
     959However, just to note, it is possible to extend this approach by comparing multiple forecasts, analyses, persisted analyses and 
    962960climatologies with the same set of observations. 
    963 This 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. 
     961This 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. 
    964962 
    965963\newpage 
     
    969967 
    970968For convenience some tools for viewing and processing of observation and feedback files are provided in 
    971 the NEMO repository. 
     969the \NEMO repository. 
    972970These tools include OBSTOOLS which are a collection of \fortran programs which are helpful to deal with feedback files. 
    973971They do such tasks as observation file conversion, printing of file contents, 
     
    979977\subsection{Obstools} 
    980978 
    981 A series of \fortran utilities is provided with NEMO called OBSTOOLS. 
    982 This 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 
     979A series of \fortran utilities is provided with \NEMO called OBSTOOLS. 
     980This are helpful in handling observation files and the feedback file output from the observation operator. A brief description of some of the utilities follows 
    983981 
    984982\subsubsection{corio2fb} 
     
    10031001 
    10041002The program fbcomb combines multiple feedback files produced by individual processors in 
    1005 an MPI run of NEMO into a single feedback file. 
     1003an MPI run of \NEMO into a single feedback file. 
    10061004It is called in the following way: 
    10071005 
     
    11341132The plotting colour range can be changed by clicking on the colour bar. 
    11351133The title of the plot gives some basic information about the date range and depth range shown, 
    1136 the extreme values, and the mean and rms values. 
     1134the extreme values, and the mean and RMS values. 
    11371135It is possible to zoom in using a drag-box. 
    11381136You may also zoom in or out using the mouse wheel. 
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