Configuring MATLAB
DART uses MATLAB’s own netCDF reading and writing capability and does not useany MATLAB or third-party toolboxes.
To allow your environment to seamlessly use the DART MATLAB functions, yourMATLAB path must be set to include two of the directories in the DARTrepository. In the MATLAB command prompt enter the following, using the realpath to your DART installation:
addpath('DART/diagnostics/matlab','-BEGIN')addpath('DART/guide/DART_LAB/matlab','-BEGIN')
It is convenient to put these commands in your ~/matlab/startup.m so theyget run every time MATLAB starts up. You can use the example startup.m filelocated at DART/diagnostics/matlab/startup.m. This example startup filecontains instructions for using it.
Summary of MATLAB functions
Once you have processed the obs_seq.final files into a singleobs_diag_output.nc, you can use that as input to your own plotting routinesor use the following DART MATLAB® routines:
plot_evolution.mplots the temporal evolution of any of the quantities above for each variablefor specified levels. The number of observations possible and used are plottedon the same axis.
fname = 'POP11/obs_diag_output.nc'; % netcdf file produced by 'obs_diag'copystring = 'rmse'; % 'copy' string == quantity of interestplotdat = plot_evolution(fname,copystring); % -- OR --plotdat = plot_evolution(fname,copystring,'obsname','RADIOSONDE_TEMPERATURE');
plot_profile.mplots the spatial and temporal average of any specified quantity as a functionof height. The number of observations possible and used are plotted on the sameaxis.
fname = 'POP11/obs_diag_output.nc'; % netcdf file produced by 'obs_diag'copystring = 'rmse'; % 'copy' string == quantity of interestplotdat = plot_profile(fname,copystring);
plot_rmse_xxx_evolution.msame as plot_evolution.m but will overlay rmse on the same axis.
plot_rmse_xxx_profile.msame as plot_profile.m with an overlay of rmse.
plot_bias_xxx_profile.msame as plot_profile.m with an overlay of bias.
two_experiments_evolution.msame as plot_evolution.m but will overlay multiple (more than two, actually)experiments (i.e.multipleobs_diag_output.ncfiles) on the same axis. Aseparate figure is created for each region in the obs_diag_output.nc file.
files = {'POP12/obs_diag_output.nc','POP11/obs_diag_output.nc'};titles = {'CAM4','CAM3.6.71'};varnames = {'ACARS_TEMPERATURE'};qtty = 'rmse';prpo = 'prior';levelind = 5;two_experiments_evolution(files, titles,{'ACARS_TEMPERATURE'}, qtty, prpo, levelind)
two_experiments_profile.msame as plot_profile.m but will overlay multiple (more than two, actually)experiments (i.e.multipleobs_diag_output.ncfiles) on the same axis. Ifthe obs_diag_output.nc file was created with multiple regions, there aremultiple axes on a single figure.
files = {'POP12/obs_diag_output.nc','POP11/obs_diag_output.nc'};titles = {'CAM4','CAM3.6.71'};varnames = {'ACARS_TEMPERATURE'};qtty = 'rmse';prpo = 'prior';two_experiments_profile(files, titles, varnames, qtty, prpo)
plot_rank_histogram
plot_rank_histogram.m willcreate rank histograms for any variable that has that information present inobs_diag_output.nc.
fname = 'obs_diag_output.nc'; % netcdf file produced by 'obs_diag'timeindex = 3; % plot the histogram for the third timestepplotdat = plot_rank_histogram(fname, timeindex, 'RADIOSONDE_TEMPERATURE');
You may also convert observation sequence files to netCDF by usingPROGRAM obs_seq_to_netcdf. Allof the following routines will work on observation sequences files AFTER anassimilation (i.e.obs_seq.final files that have been converted to netCDF),and some of them will work on obs_seq.out-type files that have been converted.
read_obs_netcdf.m reads aparticular variable and copy from a netCDF-format observation sequence file andreturns a single structure with useful bits for plotting/exploring. This routineis the back-end for plot_obs_netcdf.m.
fname = 'obs_sequence_001.nc';ObsTypeString = 'RADIOSONDE_U_WIND_COMPONENT'; % or 'ALL' ...region = [0 360 -90 90 -Inf Inf];CopyString = 'NCEP BUFR observation';QCString = 'DART quality control';verbose = 1; % anything > 0 == 'true'obs = read_obs_netcdf(fname, ObsTypeString, region, CopyString, QCString, verbose);
plot_obs_netcdf.mcreates a 3D scatterplot of the observation locations, color-coded to theobservation values. A second axis will also plot the QC values if desired.
fname = 'POP11/obs_epoch_011.nc';region = [0 360 -90 90 -Inf Inf];ObsTypeString = 'AIRCRAFT_U_WIND_COMPONENT';CopyString = 'NCEP BUFR observation';QCString = 'DART quality control';maxgoodQC = 2;verbose = 1; % > 0 means 'print summary to command window'twoup = 1; % > 0 means 'use same Figure for QC plot'bob = plot_obs_netcdf(fname, ObsTypeString, region, CopyString, ... QCString, maxgoodQC, verbose, twoup);
plot_obs_netcdf_diffs.mcreates a 3D scatterplot of the difference between two ‘copies’ of anobservation.
fname = 'POP11/obs_epoch_011.nc';region = [0 360 -90 90 -Inf Inf];ObsTypeString = 'AIRCRAFT_U_WIND_COMPONENT';CopyString1 = 'NCEP BUFR observation';CopyString2 = 'prior ensemble mean';QCString = 'DART quality control';maxQC = 2;verbose = 1; % > 0 means 'print summary to command window'twoup = 0; % > 0 means 'use same Figure for QC plot'bob = plot_obs_netcdf_diffs(fname, ObsTypeString, region, CopyString1, CopyString2, ... QCString, maxQC, verbose, twoup);
plot_wind_vectors.mcreates a 2D ‘quiver’ plot of a wind field. This function is in thematlab/private directory - but if you want to use it, you can move it out.I find it has very little practical value.
fname = 'obs_epoch_001.nc';platform = 'SAT'; % usually 'RADIOSONDE', 'SAT', 'METAR', ...CopyString = 'NCEP BUFR observation';QCString = 'DART quality control';region = [210 310 12 65 -Inf Inf];scalefactor = 5; % reference arrow magnitudebob = plot_wind_vectors(fname, platform, CopyString, QCString, ... 'region', region, 'scalefactor', scalefactor);
link_obs.m creates multiple figuresthat have linked attributes. This is my favorite function. Click on the littlepaintbrush icon in any of the figure frames and select some observations with“DARTquality control==7” in one window, and those same observations are highlighted in allthe other windows (for example). The 3D scatterplot can be rotated around withthe mouse to really pinpoint exactly where the observations are gettingrejected, for example. If the data browser (the spreadsheet-like panel) is open,the selected observations get highlighted there too.
fname = 'obs_epoch_001.nc';ObsTypeString = 'RADIOSONDE_TEMPERATURE';ObsCopyString = 'NCEP BUFR observation';CopyString = 'prior ensemble mean';QCString = 'DART quality control';region = [220 300 20 60 -Inf Inf];global obsmat;link_obs(fname, ObsTypeString, ObsCopyString, CopyString, QCString, region)
