1 | \documentclass[../main/NEMO_manual]{subfiles} |
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2 | |
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3 | \begin{document} |
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4 | % ================================================================ |
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5 | % Chapter observation operator (OBS) |
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6 | % ================================================================ |
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7 | \chapter{Observation and Model Comparison (OBS)} |
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8 | \label{chap:OBS} |
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9 | |
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10 | Authors: D. Lea, M. Martin, K. Mogensen, A. Vidard, A. Weaver, A. Ryan, ... % do we keep that ? |
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11 | |
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12 | \minitoc |
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13 | |
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14 | \newpage |
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15 | |
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16 | The observation and model comparison code (OBS) reads in observation files |
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17 | (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. |
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18 | The resulting data are saved in a ``feedback'' file (or files). |
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19 | The code was originally developed for use with the NEMOVAR data assimilation code, |
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20 | but can be used for validation or verification of the model or with any other data assimilation system. |
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21 | |
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22 | The OBS code is called from \mdl{nemogcm} for model initialisation and to calculate the model equivalent values for observations on the 0th timestep. |
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23 | The code is then called again after each timestep from \mdl{step}. |
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24 | The code is only activated if the namelist logical \np{ln\_diaobs} is set to true. |
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25 | |
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26 | For all data types a 2D horizontal interpolator or averager is needed to |
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27 | interpolate/average the model fields to the observation location. |
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28 | For {\em in situ} profiles, a 1D vertical interpolator is needed in addition to |
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29 | provide model fields at the observation depths. |
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30 | This now works in a generalised vertical coordinate system. |
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31 | |
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32 | Some profile observation types (\eg tropical moored buoys) are made available as daily averaged quantities. |
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33 | The observation operator code can be set-up to calculate the equivalent daily average model temperature fields using |
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34 | the \np{nn\_profdavtypes} namelist array. |
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35 | Some SST observations are equivalent to a night-time average value and |
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36 | the observation operator code can calculate equivalent night-time average model SST fields by |
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37 | setting the namelist value \np{ln\_sstnight} to true. |
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38 | Otherwise the model value from the nearest timestep to the observation time is used. |
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39 | |
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40 | The code is controlled by the namelist \textit{namobs}. |
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41 | See the following sections for more details on setting up the namelist. |
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42 | |
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43 | \autoref{sec:OBS_example} introduces a test example of the observation operator code including |
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44 | where to obtain data and how to setup the namelist. |
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45 | \autoref{sec:OBS_details} introduces some more technical details of the different observation types used and |
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46 | also shows a more complete namelist. |
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47 | \autoref{sec:OBS_theory} introduces some of the theoretical aspects of the observation operator including |
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48 | interpolation methods and running on multiple processors. |
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49 | \autoref{sec:OBS_ooo} describes the offline observation operator code. |
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50 | \autoref{sec:OBS_obsutils} introduces some utilities to help working with the files produced by the OBS code. |
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51 | |
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52 | % ================================================================ |
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53 | % Example |
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54 | % ================================================================ |
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55 | \section{Running the observation operator code example} |
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56 | \label{sec:OBS_example} |
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57 | |
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58 | This section describes an example of running the observation operator code using |
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59 | profile data which can be freely downloaded. |
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60 | It shows how to adapt an existing run and build of NEMO to run the observation operator. |
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61 | |
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62 | \begin{enumerate} |
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63 | \item Compile NEMO. |
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64 | |
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65 | \item Download some EN4 data from \href{http://www.metoffice.gov.uk/hadobs}{www.metoffice.gov.uk/hadobs}. |
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66 | Choose observations which are valid for the period of your test run because |
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67 | the observation operator compares the model and observations for a matching date and time. |
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68 | |
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69 | \item Compile the OBSTOOLS code using: |
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70 | \begin{cmds} |
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71 | ./maketools -n OBSTOOLS -m [ARCH]. |
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72 | \end{cmds} |
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73 | |
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74 | \item Convert the EN4 data into feedback format: |
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75 | \begin{cmds} |
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76 | enact2fb.exe profiles_01.nc EN.4.1.1.f.profiles.g10.YYYYMM.nc |
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77 | \end{cmds} |
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78 | |
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79 | \item Include the following in the NEMO namelist to run the observation operator on this data: |
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80 | \end{enumerate} |
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81 | |
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82 | Options are defined through the \ngn{namobs} namelist variables. |
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83 | The options \np{ln\_t3d} and \np{ln\_s3d} switch on the temperature and salinity profile observation operator code. |
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84 | The filename or array of filenames are specified using the \np{cn\_profbfiles} variable. |
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85 | The model grid points for a particular observation latitude and longitude are found using |
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86 | the grid searching part of the code. |
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87 | This can be expensive, particularly for large numbers of observations, |
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88 | setting \np{ln\_grid\_search\_lookup} allows the use of a lookup table which |
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89 | is saved into an ``xypos`` file (or files). |
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90 | This will need to be generated the first time if it does not exist in the run directory. |
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91 | However, once produced it will significantly speed up future grid searches. |
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92 | Setting \np{ln\_grid\_global} means that the code distributes the observations evenly between processors. |
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93 | Alternatively each processor will work with observations located within the model subdomain |
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94 | (see section~\autoref{subsec:OBS_parallel}). |
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95 | |
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96 | A number of utilities are now provided to plot the feedback files, convert and recombine the files. |
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97 | These are explained in more detail in section~\autoref{sec:OBS_obsutils}. |
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98 | Utilites to convert other input data formats into the feedback format are also described in |
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99 | section~\autoref{sec:OBS_obsutils}. |
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100 | |
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101 | \section{Technical details (feedback type observation file headers)} |
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102 | \label{sec:OBS_details} |
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103 | |
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104 | Here we show a more complete example namelist \ngn{namobs} and also show the NetCDF headers of |
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105 | the observation files that may be used with the observation operator. |
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106 | |
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107 | %------------------------------------------namobs-------------------------------------------------------- |
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108 | |
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109 | \nlst{namobs} |
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110 | %------------------------------------------------------------------------------------------------------------- |
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111 | |
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112 | The observation operator code uses the "feedback" observation file format for all data types. |
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113 | All the observation files must be in NetCDF format. |
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114 | Some example headers (produced using \mbox{\textit{ncdump~-h}}) for profile data, sea level anomaly and |
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115 | sea surface temperature are in the following subsections. |
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116 | |
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117 | \subsection{Profile feedback} |
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118 | |
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119 | \begin{clines} |
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120 | netcdf profiles_01 { |
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121 | dimensions: |
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122 | N_OBS = 603 ; |
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123 | N_LEVELS = 150 ; |
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124 | N_VARS = 2 ; |
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125 | N_QCF = 2 ; |
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126 | N_ENTRIES = 1 ; |
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127 | N_EXTRA = 1 ; |
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128 | STRINGNAM = 8 ; |
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129 | STRINGGRID = 1 ; |
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130 | STRINGWMO = 8 ; |
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131 | STRINGTYP = 4 ; |
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132 | STRINGJULD = 14 ; |
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133 | variables: |
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134 | char VARIABLES(N_VARS, STRINGNAM) ; |
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135 | VARIABLES:long_name = "List of variables in feedback files" ; |
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136 | char ENTRIES(N_ENTRIES, STRINGNAM) ; |
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137 | ENTRIES:long_name = "List of additional entries for each variable in feedback files" ; |
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138 | char EXTRA(N_EXTRA, STRINGNAM) ; |
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139 | EXTRA:long_name = "List of extra variables" ; |
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140 | char STATION_IDENTIFIER(N_OBS, STRINGWMO) ; |
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141 | STATION_IDENTIFIER:long_name = "Station identifier" ; |
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142 | char STATION_TYPE(N_OBS, STRINGTYP) ; |
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143 | STATION_TYPE:long_name = "Code instrument type" ; |
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144 | double LONGITUDE(N_OBS) ; |
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145 | LONGITUDE:long_name = "Longitude" ; |
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146 | LONGITUDE:units = "degrees_east" ; |
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147 | LONGITUDE:_Fillvalue = 99999.f ; |
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148 | double LATITUDE(N_OBS) ; |
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149 | LATITUDE:long_name = "Latitude" ; |
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150 | LATITUDE:units = "degrees_north" ; |
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151 | LATITUDE:_Fillvalue = 99999.f ; |
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152 | double DEPTH(N_OBS, N_LEVELS) ; |
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153 | DEPTH:long_name = "Depth" ; |
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154 | DEPTH:units = "metre" ; |
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155 | DEPTH:_Fillvalue = 99999.f ; |
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156 | int DEPTH_QC(N_OBS, N_LEVELS) ; |
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157 | DEPTH_QC:long_name = "Quality on depth" ; |
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158 | DEPTH_QC:Conventions = "q where q =[0,9]" ; |
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159 | DEPTH_QC:_Fillvalue = 0 ; |
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160 | int DEPTH_QC_FLAGS(N_OBS, N_LEVELS, N_QCF) ; |
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161 | DEPTH_QC_FLAGS:long_name = "Quality flags on depth" ; |
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162 | DEPTH_QC_FLAGS:Conventions = "NEMOVAR flag conventions" ; |
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163 | double JULD(N_OBS) ; |
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164 | JULD:long_name = "Julian day" ; |
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165 | JULD:units = "days since JULD_REFERENCE" ; |
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166 | JULD:Conventions = "relative julian days with decimal part (as parts of day)" ; |
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167 | JULD:_Fillvalue = 99999.f ; |
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168 | char JULD_REFERENCE(STRINGJULD) ; |
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169 | JULD_REFERENCE:long_name = "Date of reference for julian days" ; |
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170 | JULD_REFERENCE:Conventions = "YYYYMMDDHHMMSS" ; |
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171 | int OBSERVATION_QC(N_OBS) ; |
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172 | OBSERVATION_QC:long_name = "Quality on observation" ; |
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173 | OBSERVATION_QC:Conventions = "q where q =[0,9]" ; |
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174 | OBSERVATION_QC:_Fillvalue = 0 ; |
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175 | int OBSERVATION_QC_FLAGS(N_OBS, N_QCF) ; |
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176 | OBSERVATION_QC_FLAGS:long_name = "Quality flags on observation" ; |
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177 | OBSERVATION_QC_FLAGS:Conventions = "NEMOVAR flag conventions" ; |
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178 | OBSERVATION_QC_FLAGS:_Fillvalue = 0 ; |
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179 | int POSITION_QC(N_OBS) ; |
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180 | POSITION_QC:long_name = "Quality on position (latitude and longitude)" ; |
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181 | POSITION_QC:Conventions = "q where q =[0,9]" ; |
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182 | POSITION_QC:_Fillvalue = 0 ; |
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183 | int POSITION_QC_FLAGS(N_OBS, N_QCF) ; |
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184 | POSITION_QC_FLAGS:long_name = "Quality flags on position" ; |
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185 | POSITION_QC_FLAGS:Conventions = "NEMOVAR flag conventions" ; |
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186 | POSITION_QC_FLAGS:_Fillvalue = 0 ; |
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187 | int JULD_QC(N_OBS) ; |
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188 | JULD_QC:long_name = "Quality on date and time" ; |
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189 | JULD_QC:Conventions = "q where q =[0,9]" ; |
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190 | JULD_QC:_Fillvalue = 0 ; |
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191 | int JULD_QC_FLAGS(N_OBS, N_QCF) ; |
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192 | JULD_QC_FLAGS:long_name = "Quality flags on date and time" ; |
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193 | JULD_QC_FLAGS:Conventions = "NEMOVAR flag conventions" ; |
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194 | JULD_QC_FLAGS:_Fillvalue = 0 ; |
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195 | int ORIGINAL_FILE_INDEX(N_OBS) ; |
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196 | ORIGINAL_FILE_INDEX:long_name = "Index in original data file" ; |
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197 | ORIGINAL_FILE_INDEX:_Fillvalue = -99999 ; |
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198 | float POTM_OBS(N_OBS, N_LEVELS) ; |
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199 | POTM_OBS:long_name = "Potential temperature" ; |
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200 | POTM_OBS:units = "Degrees Celsius" ; |
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201 | POTM_OBS:_Fillvalue = 99999.f ; |
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202 | float POTM_Hx(N_OBS, N_LEVELS) ; |
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203 | POTM_Hx:long_name = "Model interpolated potential temperature" ; |
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204 | POTM_Hx:units = "Degrees Celsius" ; |
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205 | POTM_Hx:_Fillvalue = 99999.f ; |
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206 | int POTM_QC(N_OBS) ; |
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207 | POTM_QC:long_name = "Quality on potential temperature" ; |
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208 | POTM_QC:Conventions = "q where q =[0,9]" ; |
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209 | POTM_QC:_Fillvalue = 0 ; |
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210 | int POTM_QC_FLAGS(N_OBS, N_QCF) ; |
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211 | POTM_QC_FLAGS:long_name = "Quality flags on potential temperature" ; |
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212 | POTM_QC_FLAGS:Conventions = "NEMOVAR flag conventions" ; |
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213 | POTM_QC_FLAGS:_Fillvalue = 0 ; |
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214 | int POTM_LEVEL_QC(N_OBS, N_LEVELS) ; |
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215 | POTM_LEVEL_QC:long_name = "Quality for each level on potential temperature" ; |
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216 | POTM_LEVEL_QC:Conventions = "q where q =[0,9]" ; |
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217 | POTM_LEVEL_QC:_Fillvalue = 0 ; |
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218 | int POTM_LEVEL_QC_FLAGS(N_OBS, N_LEVELS, N_QCF) ; |
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219 | POTM_LEVEL_QC_FLAGS:long_name = "Quality flags for each level on potential temperature" ; |
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220 | POTM_LEVEL_QC_FLAGS:Conventions = "NEMOVAR flag conventions" ; |
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221 | POTM_LEVEL_QC_FLAGS:_Fillvalue = 0 ; |
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222 | int POTM_IOBSI(N_OBS) ; |
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223 | POTM_IOBSI:long_name = "ORCA grid search I coordinate" ; |
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224 | int POTM_IOBSJ(N_OBS) ; |
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225 | POTM_IOBSJ:long_name = "ORCA grid search J coordinate" ; |
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226 | int POTM_IOBSK(N_OBS, N_LEVELS) ; |
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227 | POTM_IOBSK:long_name = "ORCA grid search K coordinate" ; |
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228 | char POTM_GRID(STRINGGRID) ; |
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229 | POTM_GRID:long_name = "ORCA grid search grid (T,U,V)" ; |
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230 | float PSAL_OBS(N_OBS, N_LEVELS) ; |
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231 | PSAL_OBS:long_name = "Practical salinity" ; |
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232 | PSAL_OBS:units = "PSU" ; |
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233 | PSAL_OBS:_Fillvalue = 99999.f ; |
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234 | float PSAL_Hx(N_OBS, N_LEVELS) ; |
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235 | PSAL_Hx:long_name = "Model interpolated practical salinity" ; |
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236 | PSAL_Hx:units = "PSU" ; |
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237 | PSAL_Hx:_Fillvalue = 99999.f ; |
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238 | int PSAL_QC(N_OBS) ; |
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239 | PSAL_QC:long_name = "Quality on practical salinity" ; |
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240 | PSAL_QC:Conventions = "q where q =[0,9]" ; |
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241 | PSAL_QC:_Fillvalue = 0 ; |
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242 | int PSAL_QC_FLAGS(N_OBS, N_QCF) ; |
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243 | PSAL_QC_FLAGS:long_name = "Quality flags on practical salinity" ; |
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244 | PSAL_QC_FLAGS:Conventions = "NEMOVAR flag conventions" ; |
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245 | PSAL_QC_FLAGS:_Fillvalue = 0 ; |
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246 | int PSAL_LEVEL_QC(N_OBS, N_LEVELS) ; |
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247 | PSAL_LEVEL_QC:long_name = "Quality for each level on practical salinity" ; |
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248 | PSAL_LEVEL_QC:Conventions = "q where q =[0,9]" ; |
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249 | PSAL_LEVEL_QC:_Fillvalue = 0 ; |
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250 | int PSAL_LEVEL_QC_FLAGS(N_OBS, N_LEVELS, N_QCF) ; |
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251 | PSAL_LEVEL_QC_FLAGS:long_name = "Quality flags for each level on practical salinity" ; |
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252 | PSAL_LEVEL_QC_FLAGS:Conventions = "NEMOVAR flag conventions" ; |
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253 | PSAL_LEVEL_QC_FLAGS:_Fillvalue = 0 ; |
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254 | int PSAL_IOBSI(N_OBS) ; |
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255 | PSAL_IOBSI:long_name = "ORCA grid search I coordinate" ; |
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256 | int PSAL_IOBSJ(N_OBS) ; |
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257 | PSAL_IOBSJ:long_name = "ORCA grid search J coordinate" ; |
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258 | int PSAL_IOBSK(N_OBS, N_LEVELS) ; |
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259 | PSAL_IOBSK:long_name = "ORCA grid search K coordinate" ; |
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260 | char PSAL_GRID(STRINGGRID) ; |
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261 | PSAL_GRID:long_name = "ORCA grid search grid (T,U,V)" ; |
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262 | float TEMP(N_OBS, N_LEVELS) ; |
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263 | TEMP:long_name = "Insitu temperature" ; |
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264 | TEMP:units = "Degrees Celsius" ; |
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265 | TEMP:_Fillvalue = 99999.f ; |
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266 | |
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267 | // global attributes: |
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268 | :title = "NEMO observation operator output" ; |
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269 | :Convention = "NEMO unified observation operator output" ; |
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270 | } |
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271 | \end{clines} |
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272 | |
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273 | \subsection{Sea level anomaly feedback} |
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274 | |
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275 | \begin{clines} |
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276 | netcdf sla_01 { |
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277 | dimensions: |
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278 | N_OBS = 41301 ; |
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279 | N_LEVELS = 1 ; |
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280 | N_VARS = 1 ; |
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281 | N_QCF = 2 ; |
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282 | N_ENTRIES = 1 ; |
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283 | N_EXTRA = 1 ; |
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284 | STRINGNAM = 8 ; |
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285 | STRINGGRID = 1 ; |
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286 | STRINGWMO = 8 ; |
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287 | STRINGTYP = 4 ; |
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288 | STRINGJULD = 14 ; |
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289 | variables: |
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290 | char VARIABLES(N_VARS, STRINGNAM) ; |
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291 | VARIABLES:long_name = "List of variables in feedback files" ; |
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292 | char ENTRIES(N_ENTRIES, STRINGNAM) ; |
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293 | ENTRIES:long_name = "List of additional entries for each variable in feedback files" ; |
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294 | char EXTRA(N_EXTRA, STRINGNAM) ; |
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295 | EXTRA:long_name = "List of extra variables" ; |
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296 | char STATION_IDENTIFIER(N_OBS, STRINGWMO) ; |
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297 | STATION_IDENTIFIER:long_name = "Station identifier" ; |
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298 | char STATION_TYPE(N_OBS, STRINGTYP) ; |
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299 | STATION_TYPE:long_name = "Code instrument type" ; |
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300 | double LONGITUDE(N_OBS) ; |
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301 | LONGITUDE:long_name = "Longitude" ; |
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302 | LONGITUDE:units = "degrees_east" ; |
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303 | LONGITUDE:_Fillvalue = 99999.f ; |
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304 | double LATITUDE(N_OBS) ; |
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305 | LATITUDE:long_name = "Latitude" ; |
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306 | LATITUDE:units = "degrees_north" ; |
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307 | LATITUDE:_Fillvalue = 99999.f ; |
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308 | double DEPTH(N_OBS, N_LEVELS) ; |
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309 | DEPTH:long_name = "Depth" ; |
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310 | DEPTH:units = "metre" ; |
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311 | DEPTH:_Fillvalue = 99999.f ; |
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312 | int DEPTH_QC(N_OBS, N_LEVELS) ; |
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313 | DEPTH_QC:long_name = "Quality on depth" ; |
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314 | DEPTH_QC:Conventions = "q where q =[0,9]" ; |
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315 | DEPTH_QC:_Fillvalue = 0 ; |
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316 | int DEPTH_QC_FLAGS(N_OBS, N_LEVELS, N_QCF) ; |
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317 | DEPTH_QC_FLAGS:long_name = "Quality flags on depth" ; |
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318 | DEPTH_QC_FLAGS:Conventions = "NEMOVAR flag conventions" ; |
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319 | double JULD(N_OBS) ; |
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320 | JULD:long_name = "Julian day" ; |
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321 | JULD:units = "days since JULD_REFERENCE" ; |
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322 | JULD:Conventions = "relative julian days with decimal part (as parts of day)" ; |
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323 | JULD:_Fillvalue = 99999.f ; |
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324 | char JULD_REFERENCE(STRINGJULD) ; |
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325 | JULD_REFERENCE:long_name = "Date of reference for julian days" ; |
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326 | JULD_REFERENCE:Conventions = "YYYYMMDDHHMMSS" ; |
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327 | int OBSERVATION_QC(N_OBS) ; |
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328 | OBSERVATION_QC:long_name = "Quality on observation" ; |
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329 | OBSERVATION_QC:Conventions = "q where q =[0,9]" ; |
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330 | OBSERVATION_QC:_Fillvalue = 0 ; |
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331 | int OBSERVATION_QC_FLAGS(N_OBS, N_QCF) ; |
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332 | OBSERVATION_QC_FLAGS:long_name = "Quality flags on observation" ; |
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333 | OBSERVATION_QC_FLAGS:Conventions = "NEMOVAR flag conventions" ; |
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334 | OBSERVATION_QC_FLAGS:_Fillvalue = 0 ; |
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335 | int POSITION_QC(N_OBS) ; |
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336 | POSITION_QC:long_name = "Quality on position (latitude and longitude)" ; |
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337 | POSITION_QC:Conventions = "q where q =[0,9]" ; |
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338 | POSITION_QC:_Fillvalue = 0 ; |
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339 | int POSITION_QC_FLAGS(N_OBS, N_QCF) ; |
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340 | POSITION_QC_FLAGS:long_name = "Quality flags on position" ; |
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341 | POSITION_QC_FLAGS:Conventions = "NEMOVAR flag conventions" ; |
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342 | POSITION_QC_FLAGS:_Fillvalue = 0 ; |
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343 | int JULD_QC(N_OBS) ; |
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344 | JULD_QC:long_name = "Quality on date and time" ; |
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345 | JULD_QC:Conventions = "q where q =[0,9]" ; |
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346 | JULD_QC:_Fillvalue = 0 ; |
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347 | int JULD_QC_FLAGS(N_OBS, N_QCF) ; |
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348 | JULD_QC_FLAGS:long_name = "Quality flags on date and time" ; |
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349 | JULD_QC_FLAGS:Conventions = "NEMOVAR flag conventions" ; |
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350 | JULD_QC_FLAGS:_Fillvalue = 0 ; |
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351 | int ORIGINAL_FILE_INDEX(N_OBS) ; |
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352 | ORIGINAL_FILE_INDEX:long_name = "Index in original data file" ; |
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353 | ORIGINAL_FILE_INDEX:_Fillvalue = -99999 ; |
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354 | float SLA_OBS(N_OBS, N_LEVELS) ; |
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355 | SLA_OBS:long_name = "Sea level anomaly" ; |
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356 | SLA_OBS:units = "metre" ; |
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357 | SLA_OBS:_Fillvalue = 99999.f ; |
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358 | float SLA_Hx(N_OBS, N_LEVELS) ; |
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359 | SLA_Hx:long_name = "Model interpolated sea level anomaly" ; |
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360 | SLA_Hx:units = "metre" ; |
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361 | SLA_Hx:_Fillvalue = 99999.f ; |
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362 | int SLA_QC(N_OBS) ; |
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363 | SLA_QC:long_name = "Quality on sea level anomaly" ; |
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364 | SLA_QC:Conventions = "q where q =[0,9]" ; |
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365 | SLA_QC:_Fillvalue = 0 ; |
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366 | int SLA_QC_FLAGS(N_OBS, N_QCF) ; |
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367 | SLA_QC_FLAGS:long_name = "Quality flags on sea level anomaly" ; |
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368 | SLA_QC_FLAGS:Conventions = "NEMOVAR flag conventions" ; |
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369 | SLA_QC_FLAGS:_Fillvalue = 0 ; |
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370 | int SLA_LEVEL_QC(N_OBS, N_LEVELS) ; |
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371 | SLA_LEVEL_QC:long_name = "Quality for each level on sea level anomaly" ; |
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372 | SLA_LEVEL_QC:Conventions = "q where q =[0,9]" ; |
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373 | SLA_LEVEL_QC:_Fillvalue = 0 ; |
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374 | int SLA_LEVEL_QC_FLAGS(N_OBS, N_LEVELS, N_QCF) ; |
---|
375 | SLA_LEVEL_QC_FLAGS:long_name = "Quality flags for each level on sea level anomaly" ; |
---|
376 | SLA_LEVEL_QC_FLAGS:Conventions = "NEMOVAR flag conventions" ; |
---|
377 | SLA_LEVEL_QC_FLAGS:_Fillvalue = 0 ; |
---|
378 | int SLA_IOBSI(N_OBS) ; |
---|
379 | SLA_IOBSI:long_name = "ORCA grid search I coordinate" ; |
---|
380 | int SLA_IOBSJ(N_OBS) ; |
---|
381 | SLA_IOBSJ:long_name = "ORCA grid search J coordinate" ; |
---|
382 | int SLA_IOBSK(N_OBS, N_LEVELS) ; |
---|
383 | SLA_IOBSK:long_name = "ORCA grid search K coordinate" ; |
---|
384 | char SLA_GRID(STRINGGRID) ; |
---|
385 | SLA_GRID:long_name = "ORCA grid search grid (T,U,V)" ; |
---|
386 | float MDT(N_OBS, N_LEVELS) ; |
---|
387 | MDT:long_name = "Mean Dynamic Topography" ; |
---|
388 | MDT:units = "metre" ; |
---|
389 | MDT:_Fillvalue = 99999.f ; |
---|
390 | |
---|
391 | // global attributes: |
---|
392 | :title = "NEMO observation operator output" ; |
---|
393 | :Convention = "NEMO unified observation operator output" ; |
---|
394 | } |
---|
395 | \end{clines} |
---|
396 | |
---|
397 | The mean dynamic topography (MDT) must be provided in a separate file defined on |
---|
398 | the model grid called \ifile{slaReferenceLevel}. |
---|
399 | The MDT is required in order to produce the model equivalent sea level anomaly from the model sea surface height. |
---|
400 | Below is an example header for this file (on the ORCA025 grid). |
---|
401 | |
---|
402 | \begin{clines} |
---|
403 | dimensions: |
---|
404 | x = 1442 ; |
---|
405 | y = 1021 ; |
---|
406 | variables: |
---|
407 | float nav_lon(y, x) ; |
---|
408 | nav_lon:units = "degrees_east" ; |
---|
409 | float nav_lat(y, x) ; |
---|
410 | nav_lat:units = "degrees_north" ; |
---|
411 | float sossheig(y, x) ; |
---|
412 | sossheig:_FillValue = -1.e+30f ; |
---|
413 | sossheig:coordinates = "nav_lon nav_lat" ; |
---|
414 | sossheig:long_name = "Mean Dynamic Topography" ; |
---|
415 | sossheig:units = "metres" ; |
---|
416 | sossheig:grid = "orca025T" ; |
---|
417 | \end{clines} |
---|
418 | |
---|
419 | \subsection{Sea surface temperature feedback} |
---|
420 | |
---|
421 | \begin{clines} |
---|
422 | netcdf sst_01 { |
---|
423 | dimensions: |
---|
424 | N_OBS = 33099 ; |
---|
425 | N_LEVELS = 1 ; |
---|
426 | N_VARS = 1 ; |
---|
427 | N_QCF = 2 ; |
---|
428 | N_ENTRIES = 1 ; |
---|
429 | STRINGNAM = 8 ; |
---|
430 | STRINGGRID = 1 ; |
---|
431 | STRINGWMO = 8 ; |
---|
432 | STRINGTYP = 4 ; |
---|
433 | STRINGJULD = 14 ; |
---|
434 | variables: |
---|
435 | char VARIABLES(N_VARS, STRINGNAM) ; |
---|
436 | VARIABLES:long_name = "List of variables in feedback files" ; |
---|
437 | char ENTRIES(N_ENTRIES, STRINGNAM) ; |
---|
438 | ENTRIES:long_name = "List of additional entries for each variable in feedback files" ; |
---|
439 | char STATION_IDENTIFIER(N_OBS, STRINGWMO) ; |
---|
440 | STATION_IDENTIFIER:long_name = "Station identifier" ; |
---|
441 | char STATION_TYPE(N_OBS, STRINGTYP) ; |
---|
442 | STATION_TYPE:long_name = "Code instrument type" ; |
---|
443 | double LONGITUDE(N_OBS) ; |
---|
444 | LONGITUDE:long_name = "Longitude" ; |
---|
445 | LONGITUDE:units = "degrees_east" ; |
---|
446 | LONGITUDE:_Fillvalue = 99999.f ; |
---|
447 | double LATITUDE(N_OBS) ; |
---|
448 | LATITUDE:long_name = "Latitude" ; |
---|
449 | LATITUDE:units = "degrees_north" ; |
---|
450 | LATITUDE:_Fillvalue = 99999.f ; |
---|
451 | double DEPTH(N_OBS, N_LEVELS) ; |
---|
452 | DEPTH:long_name = "Depth" ; |
---|
453 | DEPTH:units = "metre" ; |
---|
454 | DEPTH:_Fillvalue = 99999.f ; |
---|
455 | int DEPTH_QC(N_OBS, N_LEVELS) ; |
---|
456 | DEPTH_QC:long_name = "Quality on depth" ; |
---|
457 | DEPTH_QC:Conventions = "q where q =[0,9]" ; |
---|
458 | DEPTH_QC:_Fillvalue = 0 ; |
---|
459 | int DEPTH_QC_FLAGS(N_OBS, N_LEVELS, N_QCF) ; |
---|
460 | DEPTH_QC_FLAGS:long_name = "Quality flags on depth" ; |
---|
461 | DEPTH_QC_FLAGS:Conventions = "NEMOVAR flag conventions" ; |
---|
462 | double JULD(N_OBS) ; |
---|
463 | JULD:long_name = "Julian day" ; |
---|
464 | JULD:units = "days since JULD_REFERENCE" ; |
---|
465 | JULD:Conventions = "relative julian days with decimal part (as parts of day)" ; |
---|
466 | JULD:_Fillvalue = 99999.f ; |
---|
467 | char JULD_REFERENCE(STRINGJULD) ; |
---|
468 | JULD_REFERENCE:long_name = "Date of reference for julian days" ; |
---|
469 | JULD_REFERENCE:Conventions = "YYYYMMDDHHMMSS" ; |
---|
470 | int OBSERVATION_QC(N_OBS) ; |
---|
471 | OBSERVATION_QC:long_name = "Quality on observation" ; |
---|
472 | OBSERVATION_QC:Conventions = "q where q =[0,9]" ; |
---|
473 | OBSERVATION_QC:_Fillvalue = 0 ; |
---|
474 | int OBSERVATION_QC_FLAGS(N_OBS, N_QCF) ; |
---|
475 | OBSERVATION_QC_FLAGS:long_name = "Quality flags on observation" ; |
---|
476 | OBSERVATION_QC_FLAGS:Conventions = "NEMOVAR flag conventions" ; |
---|
477 | OBSERVATION_QC_FLAGS:_Fillvalue = 0 ; |
---|
478 | int POSITION_QC(N_OBS) ; |
---|
479 | POSITION_QC:long_name = "Quality on position (latitude and longitude)" ; |
---|
480 | POSITION_QC:Conventions = "q where q =[0,9]" ; |
---|
481 | POSITION_QC:_Fillvalue = 0 ; |
---|
482 | int POSITION_QC_FLAGS(N_OBS, N_QCF) ; |
---|
483 | POSITION_QC_FLAGS:long_name = "Quality flags on position" ; |
---|
484 | POSITION_QC_FLAGS:Conventions = "NEMOVAR flag conventions" ; |
---|
485 | POSITION_QC_FLAGS:_Fillvalue = 0 ; |
---|
486 | int JULD_QC(N_OBS) ; |
---|
487 | JULD_QC:long_name = "Quality on date and time" ; |
---|
488 | JULD_QC:Conventions = "q where q =[0,9]" ; |
---|
489 | JULD_QC:_Fillvalue = 0 ; |
---|
490 | int JULD_QC_FLAGS(N_OBS, N_QCF) ; |
---|
491 | JULD_QC_FLAGS:long_name = "Quality flags on date and time" ; |
---|
492 | JULD_QC_FLAGS:Conventions = "NEMOVAR flag conventions" ; |
---|
493 | JULD_QC_FLAGS:_Fillvalue = 0 ; |
---|
494 | int ORIGINAL_FILE_INDEX(N_OBS) ; |
---|
495 | ORIGINAL_FILE_INDEX:long_name = "Index in original data file" ; |
---|
496 | ORIGINAL_FILE_INDEX:_Fillvalue = -99999 ; |
---|
497 | float SST_OBS(N_OBS, N_LEVELS) ; |
---|
498 | SST_OBS:long_name = "Sea surface temperature" ; |
---|
499 | SST_OBS:units = "Degree centigrade" ; |
---|
500 | SST_OBS:_Fillvalue = 99999.f ; |
---|
501 | float SST_Hx(N_OBS, N_LEVELS) ; |
---|
502 | SST_Hx:long_name = "Model interpolated sea surface temperature" ; |
---|
503 | SST_Hx:units = "Degree centigrade" ; |
---|
504 | SST_Hx:_Fillvalue = 99999.f ; |
---|
505 | int SST_QC(N_OBS) ; |
---|
506 | SST_QC:long_name = "Quality on sea surface temperature" ; |
---|
507 | SST_QC:Conventions = "q where q =[0,9]" ; |
---|
508 | SST_QC:_Fillvalue = 0 ; |
---|
509 | int SST_QC_FLAGS(N_OBS, N_QCF) ; |
---|
510 | SST_QC_FLAGS:long_name = "Quality flags on sea surface temperature" ; |
---|
511 | SST_QC_FLAGS:Conventions = "NEMOVAR flag conventions" ; |
---|
512 | SST_QC_FLAGS:_Fillvalue = 0 ; |
---|
513 | int SST_LEVEL_QC(N_OBS, N_LEVELS) ; |
---|
514 | SST_LEVEL_QC:long_name = "Quality for each level on sea surface temperature" ; |
---|
515 | SST_LEVEL_QC:Conventions = "q where q =[0,9]" ; |
---|
516 | SST_LEVEL_QC:_Fillvalue = 0 ; |
---|
517 | int SST_LEVEL_QC_FLAGS(N_OBS, N_LEVELS, N_QCF) ; |
---|
518 | SST_LEVEL_QC_FLAGS:long_name = "Quality flags for each level on sea surface temperature" ; |
---|
519 | SST_LEVEL_QC_FLAGS:Conventions = "NEMOVAR flag conventions" ; |
---|
520 | SST_LEVEL_QC_FLAGS:_Fillvalue = 0 ; |
---|
521 | int SST_IOBSI(N_OBS) ; |
---|
522 | SST_IOBSI:long_name = "ORCA grid search I coordinate" ; |
---|
523 | int SST_IOBSJ(N_OBS) ; |
---|
524 | SST_IOBSJ:long_name = "ORCA grid search J coordinate" ; |
---|
525 | int SST_IOBSK(N_OBS, N_LEVELS) ; |
---|
526 | SST_IOBSK:long_name = "ORCA grid search K coordinate" ; |
---|
527 | char SST_GRID(STRINGGRID) ; |
---|
528 | SST_GRID:long_name = "ORCA grid search grid (T,U,V)" ; |
---|
529 | |
---|
530 | // global attributes: |
---|
531 | :title = "NEMO observation operator output" ; |
---|
532 | :Convention = "NEMO unified observation operator output" ; |
---|
533 | } |
---|
534 | \end{clines} |
---|
535 | |
---|
536 | \section{Theoretical details} |
---|
537 | \label{sec:OBS_theory} |
---|
538 | |
---|
539 | \subsection{Horizontal interpolation and averaging methods} |
---|
540 | |
---|
541 | For most observation types, the horizontal extent of the observation is small compared to the model grid size and so |
---|
542 | the model equivalent of the observation is calculated by interpolating from |
---|
543 | the four surrounding grid points to the observation location. |
---|
544 | Some satellite observations (\eg microwave satellite SST data, or satellite SSS data) have a footprint which |
---|
545 | is similar in size or larger than the model grid size (particularly when the grid size is small). |
---|
546 | In those cases the model counterpart should be calculated by averaging the model grid points over |
---|
547 | the same size as the footprint. |
---|
548 | NEMO therefore has the capability to specify either an interpolation or an averaging |
---|
549 | (for surface observation types only). |
---|
550 | |
---|
551 | The main namelist option associated with the interpolation/averaging is \np{nn\_2dint}. |
---|
552 | This default option can be set to values from 0 to 6. |
---|
553 | Values between 0 to 4 are associated with interpolation while values 5 or 6 are associated with averaging. |
---|
554 | \begin{itemize} |
---|
555 | \item \np{nn\_2dint}\forcode{ = 0}: Distance-weighted interpolation |
---|
556 | \item \np{nn\_2dint}\forcode{ = 1}: Distance-weighted interpolation (small angle) |
---|
557 | \item \np{nn\_2dint}\forcode{ = 2}: Bilinear interpolation (geographical grid) |
---|
558 | \item \np{nn\_2dint}\forcode{ = 3}: Bilinear remapping interpolation (general grid) |
---|
559 | \item \np{nn\_2dint}\forcode{ = 4}: Polynomial interpolation |
---|
560 | \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}) |
---|
562 | \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 | \end{itemize} |
---|
566 | The ??? in the last two options indicate these options should be specified for each observation type for |
---|
567 | which the averaging is to be performed (see namelist example above). |
---|
568 | The \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. |
---|
570 | |
---|
571 | Below is some more detail on the various options for interpolation and averaging available in NEMO. |
---|
572 | |
---|
573 | \subsubsection{Horizontal interpolation} |
---|
574 | |
---|
575 | Consider an observation point ${\mathrm P}$ with with longitude and latitude $({\lambda_{}}_{\mathrm P}, \phi_{\mathrm P})$ and |
---|
576 | the four nearest neighbouring model grid points ${\mathrm A}$, ${\mathrm B}$, ${\mathrm C}$ and ${\mathrm D}$ with |
---|
577 | longitude and latitude ($\lambda_{\mathrm A}$, $\phi_{\mathrm A}$),($\lambda_{\mathrm B}$, $\phi_{\mathrm B}$) etc. |
---|
578 | All horizontal interpolation methods implemented in NEMO estimate the value of a model variable $x$ at point $P$ as |
---|
579 | a weighted linear combination of the values of the model variables at the grid points ${\mathrm A}$, ${\mathrm B}$ etc.: |
---|
580 | \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) |
---|
586 | \end{align*} |
---|
587 | where ${w_{}}_{\mathrm A}$, ${w_{}}_{\mathrm B}$ etc. are the respective weights for the model field at |
---|
588 | points ${\mathrm A}$, ${\mathrm B}$ etc., and $w = {w_{}}_{\mathrm A} + {w_{}}_{\mathrm B} + {w_{}}_{\mathrm C} + {w_{}}_{\mathrm D}$. |
---|
589 | |
---|
590 | Four different possibilities are available for computing the weights. |
---|
591 | |
---|
592 | \begin{enumerate} |
---|
593 | |
---|
594 | \item[1.] {\bfseries Great-Circle distance-weighted interpolation.} |
---|
595 | The weights are computed as a function of the great-circle distance $s(P, \cdot)$ between $P$ and |
---|
596 | the model grid points $A$, $B$ etc. |
---|
597 | For example, the weight given to the field ${x_{}}_{\mathrm A}$ is specified as the product of the distances |
---|
598 | from ${\mathrm P}$ to the other points: |
---|
599 | \begin{align*} |
---|
600 | {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\{ |
---|
607 | \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}) |
---|
610 | \right\} |
---|
611 | \end{align*} |
---|
612 | and $M$ corresponds to $B$, $C$ or $D$. |
---|
613 | A more stable form of the great-circle distance formula for small distances ($x$ near 1) |
---|
614 | 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*} |
---|
618 | 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*} |
---|
632 | |
---|
633 | \item[2.] {\bfseries Great-Circle distance-weighted interpolation with small angle approximation.} |
---|
634 | Similar to the previous interpolation but with the distance $s$ computed as |
---|
635 | \begin{align*} |
---|
636 | s\left( {\mathrm P}, {\mathrm M} \right) |
---|
637 | & \hspace{-2mm} = \hspace{-2mm} & |
---|
638 | \sqrt{ \left( {\phi_{}}_{\mathrm M} - {\phi_{}}_{\mathrm P} \right)^{2} |
---|
639 | + \left( {\lambda_{}}_{\mathrm M} - {\lambda_{}}_{\mathrm P} \right)^{2} |
---|
640 | \cos^{2} {\phi_{}}_{\mathrm M} } |
---|
641 | \end{align*} |
---|
642 | where $M$ corresponds to $A$, $B$, $C$ or $D$. |
---|
643 | |
---|
644 | \item[3.] {\bfseries Bilinear interpolation for a regular spaced grid.} |
---|
645 | The interpolation is split into two 1D interpolations in the longitude and latitude directions, respectively. |
---|
646 | |
---|
647 | \item[4.] {\bfseries Bilinear remapping interpolation for a general grid.} |
---|
648 | An iterative scheme that involves first mapping a quadrilateral cell into |
---|
649 | a cell with coordinates (0,0), (1,0), (0,1) and (1,1). |
---|
650 | This method is based on the \href{https://github.com/SCRIP-Project/SCRIP}{SCRIP interpolation package}. |
---|
651 | |
---|
652 | \end{enumerate} |
---|
653 | |
---|
654 | \subsubsection{Horizontal averaging} |
---|
655 | |
---|
656 | For each surface observation type: |
---|
657 | \begin{itemize} |
---|
658 | \item The standard grid-searching code is used to find the nearest model grid point to the observation location |
---|
659 | (see next subsection). |
---|
660 | \item The maximum number of grid points is calculated in the local grid domain for which |
---|
661 | 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 |
---|
663 | existing mpi routines. |
---|
664 | \item The weights for each grid point associated with each observation are calculated, |
---|
665 | either for radial or rectangular footprints. |
---|
666 | For grid points completely within the footprint, the weight is one; |
---|
667 | for grid points completely outside the footprint, the weight is zero. |
---|
668 | For grid points which are partly within the footprint the ratio between the area of the footprint within |
---|
669 | the grid box and the total area of the grid box is used as the weight. |
---|
670 | \item The weighted average of the model grid points associated with each observation is calculated, |
---|
671 | and this is then given as the model counterpart of the observation. |
---|
672 | \end{itemize} |
---|
673 | |
---|
674 | Examples of the weights calculated for an observation with rectangular and radial footprints are shown in |
---|
675 | Figs.~\autoref{fig:obsavgrec} and~\autoref{fig:obsavgrad}. |
---|
676 | |
---|
677 | %>>>>>>>>>>>>>>>>>>>>>>>>>>>> |
---|
678 | \begin{figure} |
---|
679 | \begin{center} |
---|
680 | \includegraphics[width=\textwidth]{Fig_OBS_avg_rec} |
---|
681 | \caption{ |
---|
682 | \protect\label{fig:obsavgrec} |
---|
683 | Weights associated with each model grid box (blue lines and numbers) |
---|
684 | for an observation at -170.5\deg{E}, 56.0\deg{N} with a rectangular footprint of 1\deg x 1\deg. |
---|
685 | } |
---|
686 | \end{center} |
---|
687 | \end{figure} |
---|
688 | %>>>>>>>>>>>>>>>>>>>>>>>>>>>> |
---|
689 | |
---|
690 | %>>>>>>>>>>>>>>>>>>>>>>>>>>>> |
---|
691 | \begin{figure} |
---|
692 | \begin{center} |
---|
693 | \includegraphics[width=\textwidth]{Fig_OBS_avg_rad} |
---|
694 | \caption{ |
---|
695 | \protect\label{fig:obsavgrad} |
---|
696 | Weights associated with each model grid box (blue lines and numbers) |
---|
697 | for an observation at -170.5\deg{E}, 56.0\deg{N} with a radial footprint with diameter 1\deg. |
---|
698 | } |
---|
699 | \end{center} |
---|
700 | \end{figure} |
---|
701 | %>>>>>>>>>>>>>>>>>>>>>>>>>>>> |
---|
702 | |
---|
703 | |
---|
704 | \subsection{Grid search} |
---|
705 | |
---|
706 | 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. |
---|
707 | Therefore, 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 |
---|
709 | the quadrilateral cell in which the observation is located. |
---|
710 | This is the most difficult and time consuming part of the 2D interpolation procedure. |
---|
711 | A robust test for determining if an observation falls within a given quadrilateral cell is as follows. |
---|
712 | Let ${\mathrm P}({\lambda_{}}_{\mathrm P} ,{\phi_{}}_{\mathrm P} )$ denote the observation point, |
---|
713 | and let ${\mathrm A}({\lambda_{}}_{\mathrm A} ,{\phi_{}}_{\mathrm A} )$, ${\mathrm B}({\lambda_{}}_{\mathrm B} ,{\phi_{}}_{\mathrm B} )$, |
---|
714 | ${\mathrm C}({\lambda_{}}_{\mathrm C} ,{\phi_{}}_{\mathrm C} )$ 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 |
---|
717 | \begin{align*} |
---|
718 | \begin{array}{lllll} |
---|
719 | {{\mathbf r}_{}}_{\mathrm PA} \times {{\mathbf r}_{}}_{\mathrm PC} |
---|
720 | & = & [({\lambda_{}}_{\mathrm A}\; -\; {\lambda_{}}_{\mathrm P} ) |
---|
721 | ({\phi_{}}_{\mathrm C} \; -\; {\phi_{}}_{\mathrm P} ) |
---|
722 | - ({\lambda_{}}_{\mathrm C}\; -\; {\lambda_{}}_{\mathrm P} ) |
---|
723 | ({\phi_{}}_{\mathrm A} \; -\; {\phi_{}}_{\mathrm P} )] \; \widehat{\mathbf k} \\ |
---|
724 | {{\mathbf r}_{}}_{\mathrm PB} \times {{\mathbf r}_{}}_{\mathrm PA} |
---|
725 | & = & [({\lambda_{}}_{\mathrm B}\; -\; {\lambda_{}}_{\mathrm P} ) |
---|
726 | ({\phi_{}}_{\mathrm A} \; -\; {\phi_{}}_{\mathrm P} ) |
---|
727 | - ({\lambda_{}}_{\mathrm A}\; -\; {\lambda_{}}_{\mathrm P} ) |
---|
728 | ({\phi_{}}_{\mathrm B} \; -\; {\phi_{}}_{\mathrm P} )] \; \widehat{\mathbf k} \\ |
---|
729 | {{\mathbf r}_{}}_{\mathrm PC} \times {{\mathbf r}_{}}_{\mathrm PD} |
---|
730 | & = & [({\lambda_{}}_{\mathrm C}\; -\; {\lambda_{}}_{\mathrm P} ) |
---|
731 | ({\phi_{}}_{\mathrm D} \; -\; {\phi_{}}_{\mathrm P} ) |
---|
732 | - ({\lambda_{}}_{\mathrm D}\; -\; {\lambda_{}}_{\mathrm P} ) |
---|
733 | ({\phi_{}}_{\mathrm C} \; -\; {\phi_{}}_{\mathrm P} )] \; \widehat{\mathbf k} \\ |
---|
734 | {{\mathbf r}_{}}_{\mathrm PD} \times {{\mathbf r}_{}}_{\mathrm PB} |
---|
735 | & = & [({\lambda_{}}_{\mathrm D}\; -\; {\lambda_{}}_{\mathrm P} ) |
---|
736 | ({\phi_{}}_{\mathrm B} \; -\; {\phi_{}}_{\mathrm P} ) |
---|
737 | - ({\lambda_{}}_{\mathrm B}\; -\; {\lambda_{}}_{\mathrm P} ) |
---|
738 | ({\phi_{}}_{\mathrm D} \; - \; {\phi_{}}_{\mathrm P} )] \; \widehat{\mathbf k} \\ |
---|
739 | \end{array} |
---|
740 | % \label{eq:cross} |
---|
741 | \end{align*} |
---|
742 | point in the opposite direction to the unit normal $\widehat{\mathbf k}$ |
---|
743 | (\ie that the coefficients of $\widehat{\mathbf k}$ are negative), |
---|
744 | where ${{\mathbf r}_{}}_{\mathrm PA}$, ${{\mathbf r}_{}}_{\mathrm PB}$, etc. correspond to |
---|
745 | the vectors between points P and A, P and B, etc.. |
---|
746 | The method used is similar to the method used in the \href{https://github.com/SCRIP-Project/SCRIP}{SCRIP interpolation package}. |
---|
747 | |
---|
748 | In order to speed up the grid search, there is the possibility to construct a lookup table for a user specified resolution. |
---|
749 | This lookup table contains the lower and upper bounds on the $i$ and $j$ indices to |
---|
750 | be searched for on a regular grid. |
---|
751 | For 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. |
---|
753 | |
---|
754 | \subsection{Parallel aspects of horizontal interpolation} |
---|
755 | \label{subsec:OBS_parallel} |
---|
756 | |
---|
757 | For horizontal interpolation, there is the basic problem that |
---|
758 | the observations are unevenly distributed on the globe. |
---|
759 | In numerical models, it is common to divide the model grid into subgrids (or domains) where |
---|
760 | each subgrid is executed on a single processing element with explicit message passing for |
---|
761 | exchange 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. |
---|
765 | Two options have been made available: |
---|
766 | 1) geographical distribution; |
---|
767 | and 2) round-robin. |
---|
768 | |
---|
769 | \subsubsection{Geographical distribution of observations among processors} |
---|
770 | |
---|
771 | %>>>>>>>>>>>>>>>>>>>>>>>>>>>> |
---|
772 | \begin{figure} |
---|
773 | \begin{center} |
---|
774 | \includegraphics[width=\textwidth]{Fig_ASM_obsdist_local} |
---|
775 | \caption{ |
---|
776 | \protect\label{fig:obslocal} |
---|
777 | Example of the distribution of observations with the geographical distribution of observational data. |
---|
778 | } |
---|
779 | \end{center} |
---|
780 | \end{figure} |
---|
781 | %>>>>>>>>>>>>>>>>>>>>>>>>>>>> |
---|
782 | |
---|
783 | This is the simplest option in which the observations are distributed according to |
---|
784 | the domain of the grid-point parallelization. |
---|
785 | \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. |
---|
787 | The grid-point domain decomposition is clearly visible on the plot. |
---|
788 | |
---|
789 | The advantage of this approach is that all information needed for horizontal interpolation is available without |
---|
790 | any MPP communication. |
---|
791 | Of course, this is under the assumption that we are only using a $2 \times 2$ grid-point stencil for |
---|
792 | the interpolation (\eg bilinear interpolation). |
---|
793 | For higher order interpolation schemes this is no longer valid. |
---|
794 | A disadvantage with the above scheme is that the number of observations on each processor can be very different. |
---|
795 | If the cost of the actual interpolation is expensive relative to the communication of data needed for interpolation, |
---|
796 | this could lead to load imbalance. |
---|
797 | |
---|
798 | \subsubsection{Round-robin distribution of observations among processors} |
---|
799 | |
---|
800 | %>>>>>>>>>>>>>>>>>>>>>>>>>>>> |
---|
801 | \begin{figure} |
---|
802 | \begin{center} |
---|
803 | \includegraphics[width=\textwidth]{Fig_ASM_obsdist_global} |
---|
804 | \caption{ |
---|
805 | \protect\label{fig:obsglobal} |
---|
806 | Example of the distribution of observations with the round-robin distribution of observational data. |
---|
807 | } |
---|
808 | \end{center} |
---|
809 | \end{figure} |
---|
810 | %>>>>>>>>>>>>>>>>>>>>>>>>>>>> |
---|
811 | |
---|
812 | An alternative approach is to distribute the observations equally among processors and |
---|
813 | use message passing in order to retrieve the stencil for interpolation. |
---|
814 | The simplest distribution of the observations is to distribute them using a round-robin scheme. |
---|
815 | \autoref{fig:obsglobal} shows the distribution of the {\em in situ} data on processors for |
---|
816 | the round-robin distribution of observations with a different colour for each observation on a given processor for |
---|
817 | a 4 $\times$ 2 decomposition with ORCA2 for the same input data as in \autoref{fig:obslocal}. |
---|
818 | The observations are now clearly randomly distributed on the globe. |
---|
819 | In order to be able to perform horizontal interpolation in this case, |
---|
820 | a subroutine has been developed that retrieves any grid points in the global space. |
---|
821 | |
---|
822 | \subsection{Vertical interpolation operator} |
---|
823 | |
---|
824 | Vertical interpolation is achieved using either a cubic spline or linear interpolation. |
---|
825 | For the cubic spline, the top and bottom boundary conditions for the second derivative of |
---|
826 | the interpolating polynomial in the spline are set to zero. |
---|
827 | At the bottom boundary, this is done using the land-ocean mask. |
---|
828 | |
---|
829 | \newpage |
---|
830 | |
---|
831 | % ================================================================ |
---|
832 | % Offline observation operator documentation |
---|
833 | % ================================================================ |
---|
834 | |
---|
835 | %\usepackage{framed} |
---|
836 | |
---|
837 | \section{Offline observation operator} |
---|
838 | \label{sec:OBS_ooo} |
---|
839 | |
---|
840 | \subsection{Concept} |
---|
841 | |
---|
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. |
---|
852 | The first is to mimic the behaviour of the online system by supplying model fields at |
---|
853 | regular intervals between the start and the end of the run. |
---|
854 | This 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. |
---|
858 | In 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. |
---|
864 | |
---|
865 | %-------------------------------------------------------------------------------------------------------- |
---|
866 | % offline_oper.exe |
---|
867 | %-------------------------------------------------------------------------------------------------------- |
---|
868 | |
---|
869 | \subsection{Using the offline observation operator} |
---|
870 | |
---|
871 | \subsubsection{Building} |
---|
872 | |
---|
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 |
---|
875 | overwrites the resultant \textbf{nemo.exe}. |
---|
876 | This is the approach taken by \emph{SAS\_SRC} and \emph{OFF\_SRC}. |
---|
877 | |
---|
878 | %-------------------------------------------------------------------------------------------------------- |
---|
879 | % Running |
---|
880 | %-------------------------------------------------------------------------------------------------------- |
---|
881 | \subsubsection{Running} |
---|
882 | |
---|
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. |
---|
893 | |
---|
894 | %-------------------------------------------------------------------------------------------------------- |
---|
895 | % Configuration section |
---|
896 | %-------------------------------------------------------------------------------------------------------- |
---|
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. |
---|
902 | |
---|
903 | \subsubsection{Single field} |
---|
904 | |
---|
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. |
---|
907 | These routines will be expanded upon in future versions to allow the specification of any model variable. |
---|
908 | As such, input files must be global versions of the model domain with |
---|
909 | \textbf{votemper}, \textbf{vosaline} and optionally \textbf{sshn} present. |
---|
910 | |
---|
911 | For each field read there must be an entry in the \textbf{namooo} namelist specifying |
---|
912 | the name of the file to read and the index along the \emph{time\_counter}. |
---|
913 | For example, to read the second time counter from a single file the namelist would be. |
---|
914 | |
---|
915 | \begin{forlines} |
---|
916 | !---------------------------------------------------------------------- |
---|
917 | ! namooo Offline obs_oper namelist |
---|
918 | !---------------------------------------------------------------------- |
---|
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 |
---|
924 | / |
---|
925 | \end{forlines} |
---|
926 | |
---|
927 | \subsubsection{Multiple fields per run} |
---|
928 | |
---|
929 | Model field iteration is controlled via \textbf{nn\_ooo\_freq} which |
---|
930 | specifies the number of model steps at which the next field gets read. |
---|
931 | For example, if 12 hourly fields are to be interpolated in a setup where 288 steps equals 24 hours. |
---|
932 | |
---|
933 | \begin{forlines} |
---|
934 | !---------------------------------------------------------------------- |
---|
935 | ! namooo Offline obs_oper namelist |
---|
936 | !---------------------------------------------------------------------- |
---|
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 |
---|
944 | / |
---|
945 | \end{forlines} |
---|
946 | |
---|
947 | The above namelist will result in feedback files whose first 12 hours contain the first field of foo.nc and |
---|
948 | the second 12 hours contain the second field. |
---|
949 | |
---|
950 | %\begin{framed} |
---|
951 | \textbf{Note} Missing files can be denoted as "nofile". |
---|
952 | %\end{framed} |
---|
953 | |
---|
954 | It is easy to see how a collection of fields taken fron a number of files at different indices can be combined at |
---|
955 | a 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. |
---|
1158 | |
---|
1159 | \newpage |
---|
1160 | |
---|
1161 | \section{Observation utilities} |
---|
1162 | \label{sec:OBS_obsutils} |
---|
1163 | |
---|
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. |
---|
1167 | They do such tasks as observation file conversion, printing of file contents, |
---|
1168 | some basic statistical analysis of feedback files. |
---|
1169 | The other tool is an IDL program called dataplot which uses a graphical interface to |
---|
1170 | visualise observations and feedback files. |
---|
1171 | OBSTOOLS and dataplot are described in more detail below. |
---|
1172 | |
---|
1173 | \subsection{Obstools} |
---|
1174 | |
---|
1175 | A 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 |
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1178 | |
---|
1179 | \subsubsection{c4comb} |
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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: |
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1184 | |
---|
1185 | |
---|
1186 | \footnotesize |
---|
1187 | \begin{cmds} |
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1188 | c4comb.exe outputfile inputfile1 inputfile2 ... |
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1189 | \end{cmds} |
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1190 | |
---|
1191 | \subsubsection{corio2fb} |
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1192 | |
---|
1193 | The program corio2fb converts profile observation files from the Coriolis format to the standard feedback format. |
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1194 | The program is called in the following way: |
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1195 | |
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1196 | \footnotesize |
---|
1197 | \begin{cmds} |
---|
1198 | corio2fb.exe outputfile inputfile1 inputfile2 ... |
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1199 | \end{cmds} |
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1200 | |
---|
1201 | \subsubsection{enact2fb} |
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1202 | |
---|
1203 | The program enact2fb converts profile observation files from the ENACT format to the standard feedback format. |
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1204 | The program is called in the following way: |
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1205 | |
---|
1206 | \footnotesize |
---|
1207 | \begin{cmds} |
---|
1208 | enact2fb.exe outputfile inputfile1 inputfile2 ... |
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1209 | \end{cmds} |
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1210 | |
---|
1211 | \subsubsection{fbcomb} |
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1212 | |
---|
1213 | The program fbcomb combines multiple feedback files produced by individual processors in |
---|
1214 | an MPI run of NEMO into a single feedback file. |
---|
1215 | The program is called in the following way: |
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1216 | |
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1217 | \footnotesize |
---|
1218 | \begin{cmds} |
---|
1219 | fbcomb.exe outputfile inputfile1 inputfile2 ... |
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1220 | \end{cmds} |
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1221 | |
---|
1222 | \subsubsection{fbmatchup} |
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1223 | |
---|
1224 | The program fbmatchup will match observations from two feedback files. |
---|
1225 | The program is called in the following way: |
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1226 | |
---|
1227 | \footnotesize |
---|
1228 | \begin{cmds} |
---|
1229 | fbmatchup.exe outputfile inputfile1 varname1 inputfile2 varname2 ... |
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1230 | \end{cmds} |
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1231 | |
---|
1232 | \subsubsection{fbprint} |
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1233 | |
---|
1234 | The program fbprint will print the contents of a feedback file or files to standard output. |
---|
1235 | Selected information can be output using optional arguments. |
---|
1236 | The program is called in the following way: |
---|
1237 | |
---|
1238 | \footnotesize |
---|
1239 | \begin{cmds} |
---|
1240 | fbprint.exe [options] inputfile |
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1241 | |
---|
1242 | options: |
---|
1243 | -b shorter output |
---|
1244 | -q Select observations based on QC flags |
---|
1245 | -Q Select observations based on QC flags |
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1246 | -B Select observations based on QC flags |
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1247 | -u unsorted |
---|
1248 | -s ID select station ID |
---|
1249 | -t TYPE select observation type |
---|
1250 | -v NUM1-NUM2 select variable range to print by number |
---|
1251 | (default all) |
---|
1252 | -a NUM1-NUM2 select additional variable range to print by number |
---|
1253 | (default all) |
---|
1254 | -e NUM1-NUM2 select extra variable range to print by number |
---|
1255 | (default all) |
---|
1256 | -d output date range |
---|
1257 | -D print depths |
---|
1258 | -z use zipped files |
---|
1259 | \end{cmds} |
---|
1260 | |
---|
1261 | \subsubsection{fbsel} |
---|
1262 | |
---|
1263 | The program fbsel will select or subsample observations. |
---|
1264 | The program is called in the following way: |
---|
1265 | |
---|
1266 | \footnotesize |
---|
1267 | \begin{cmds} |
---|
1268 | fbsel.exe <input filename> <output filename> |
---|
1269 | \end{cmds} |
---|
1270 | |
---|
1271 | \subsubsection{fbstat} |
---|
1272 | |
---|
1273 | The 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 |
---|
1277 | \begin{cmds} |
---|
1278 | fbstat.exe [-nmlev] <filenames> |
---|
1279 | \end{cmds} |
---|
1280 | |
---|
1281 | \subsubsection{fbthin} |
---|
1282 | |
---|
1283 | The program fbthin will thin the data to 1 degree resolution. |
---|
1284 | The code could easily be modified to thin to a different resolution. |
---|
1285 | The program is called in the following way: |
---|
1286 | |
---|
1287 | \footnotesize |
---|
1288 | \begin{cmds} |
---|
1289 | fbthin.exe inputfile outputfile |
---|
1290 | \end{cmds} |
---|
1291 | |
---|
1292 | \subsubsection{sla2fb} |
---|
1293 | |
---|
1294 | The program sla2fb will convert an AVISO SLA format file to feedback format. |
---|
1295 | The program is called in the following way: |
---|
1296 | |
---|
1297 | \footnotesize |
---|
1298 | \begin{cmds} |
---|
1299 | sla2fb.exe [-s type] outputfile inputfile1 inputfile2 ... |
---|
1300 | |
---|
1301 | Option: |
---|
1302 | -s Select altimeter data_source |
---|
1303 | \end{cmds} |
---|
1304 | |
---|
1305 | \subsubsection{vel2fb} |
---|
1306 | |
---|
1307 | The program vel2fb will convert TAO/PIRATA/RAMA currents files to feedback format. |
---|
1308 | The program is called in the following way: |
---|
1309 | |
---|
1310 | \footnotesize |
---|
1311 | \begin{cmds} |
---|
1312 | vel2fb.exe outputfile inputfile1 inputfile2 ... |
---|
1313 | \end{cmds} |
---|
1314 | |
---|
1315 | \subsection{Building the obstools} |
---|
1316 | |
---|
1317 | To build the obstools use in the tools directory use ./maketools -n OBSTOOLS -m [ARCH]. |
---|
1318 | |
---|
1319 | \subsection{Dataplot} |
---|
1320 | |
---|
1321 | An IDL program called dataplot is included which uses a graphical interface to |
---|
1322 | visualise observations and feedback files. |
---|
1323 | It is possible to zoom in, plot individual profiles and calculate some basic statistics. |
---|
1324 | To plot some data run IDL and then: |
---|
1325 | \footnotesize |
---|
1326 | \begin{minted}{idl} |
---|
1327 | IDL> dataplot, "filename" |
---|
1328 | \end{minted} |
---|
1329 | |
---|
1330 | To read multiple files into dataplot, |
---|
1331 | for example multiple feedback files from different processors or from different days, |
---|
1332 | the easiest method is to use the spawn command to generate a list of files which can then be passed to dataplot. |
---|
1333 | \footnotesize |
---|
1334 | \begin{minted}{idl} |
---|
1335 | IDL> spawn, 'ls profb*.nc', files |
---|
1336 | IDL> dataplot, files |
---|
1337 | \end{minted} |
---|
1338 | |
---|
1339 | \autoref{fig:obsdataplotmain} shows the main window which is launched when dataplot starts. |
---|
1340 | This is split into three parts. |
---|
1341 | At the top there is a menu bar which contains a variety of drop down menus. |
---|
1342 | Areas - zooms into prespecified regions; |
---|
1343 | plot - plots the data as a timeseries or a T-S diagram if appropriate; |
---|
1344 | Find - allows data to be searched; |
---|
1345 | Config - sets various configuration options. |
---|
1346 | |
---|
1347 | The middle part is a plot of the geographical location of the observations. |
---|
1348 | This will plot the observation value, the model background value or observation minus background value depending on |
---|
1349 | the option selected in the radio button at the bottom of the window. |
---|
1350 | The plotting colour range can be changed by clicking on the colour bar. |
---|
1351 | The title of the plot gives some basic information about the date range and depth range shown, |
---|
1352 | the extreme values, and the mean and rms values. |
---|
1353 | It is possible to zoom in using a drag-box. |
---|
1354 | You may also zoom in or out using the mouse wheel. |
---|
1355 | |
---|
1356 | The bottom part of the window controls what is visible in the plot above. |
---|
1357 | There are two bars which select the level range plotted (for profile data). |
---|
1358 | The other bars below select the date range shown. |
---|
1359 | The bottom of the figure allows the option to plot the mean, root mean square, standard deviation or |
---|
1360 | mean square values. |
---|
1361 | As mentioned above you can choose to plot the observation value, the model background value or |
---|
1362 | observation minus background value. |
---|
1363 | The next group of radio buttons selects the map projection. |
---|
1364 | This can either be regular latitude longitude grid, or north or south polar stereographic. |
---|
1365 | The next group of radio buttons will plot bad observations, switch to salinity and |
---|
1366 | plot density for profile observations. |
---|
1367 | The rightmost group of buttons will print the plot window as a postscript, save it as png, or exit from dataplot. |
---|
1368 | |
---|
1369 | %>>>>>>>>>>>>>>>>>>>>>>>>>>>> |
---|
1370 | \begin{figure} |
---|
1371 | \begin{center} |
---|
1372 | % \includegraphics[width=\textwidth]{Fig_OBS_dataplot_main} |
---|
1373 | \includegraphics[width=\textwidth]{Fig_OBS_dataplot_main} |
---|
1374 | \caption{ |
---|
1375 | \protect\label{fig:obsdataplotmain} |
---|
1376 | Main window of dataplot. |
---|
1377 | } |
---|
1378 | \end{center} |
---|
1379 | \end{figure} |
---|
1380 | %>>>>>>>>>>>>>>>>>>>>>>>>>>>> |
---|
1381 | |
---|
1382 | If a profile point is clicked with the mouse button a plot of the observation and background values as |
---|
1383 | a function of depth (\autoref{fig:obsdataplotprofile}). |
---|
1384 | |
---|
1385 | %>>>>>>>>>>>>>>>>>>>>>>>>>>>> |
---|
1386 | \begin{figure} |
---|
1387 | \begin{center} |
---|
1388 | % \includegraphics[width=\textwidth]{Fig_OBS_dataplot_prof} |
---|
1389 | \includegraphics[width=\textwidth]{Fig_OBS_dataplot_prof} |
---|
1390 | \caption{ |
---|
1391 | \protect\label{fig:obsdataplotprofile} |
---|
1392 | Profile plot from dataplot produced by right clicking on a point in the main window. |
---|
1393 | } |
---|
1394 | \end{center} |
---|
1395 | \end{figure} |
---|
1396 | %>>>>>>>>>>>>>>>>>>>>>>>>>>>> |
---|
1397 | |
---|
1398 | \biblio |
---|
1399 | |
---|
1400 | \pindex |
---|
1401 | |
---|
1402 | \end{document} |
---|