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@@ -4,7 +4,7 @@ This repository contains the scripts related to the Observation Apps - component
 # Description
 The OBSALL application is currently being developed as a set of scripts (written in `bash`, `fortran`, `python`):
 1. for pre-processing (with operators of `cdo`, Climate Data Operators, software) gsv_extracted modeled data (over latitude-longitude domain) for selected meteorological variables into hourly time-slices (00...23 UTCs);
-2. for extracting (using `sql` with `odp_api` software) selected meteorological variables at hourly time-slices for observations from: (i) ground-based synoptical stations at fixed at the surface geographical locations/points (i.e., 2D: latitude, longitude); (ii) vertical radiosounding of the atmosphere at changing locations/points (3D: latitude, longitude, single pressure level), and (iii) satellite at changing locations/ points (3D: latitude, longitude, multiple pressure levels);
+2. for extracting (using `sql` with `odb_api` software) selected meteorological variables at hourly time-slices for observations from: (i) ground-based synoptical stations at fixed at the surface geographical locations/points (i.e., 2D: latitude, longitude); (ii) vertical radiosounding of the atmosphere at changing locations/points (3D: latitude, longitude, single pressure level), and (iii) satellite at changing locations/ points (3D: latitude, longitude, multiple pressure levels);
 3. for extracting and interpolating (using `cdo` operators - for synop; & expecting/using `polytope` - for radiosounding and satellite) modeled data for the same time-slices for same selected meteorological variables into corresponding locations/points of (synop, radiosounding, satellite) observations, and adding (using `import` with `odb_api`) such data to ODB;
 3. for calculating/ producing relevant statistics such as quantile rank histogram statistics and plots (t-test and others to be added)
 
@@ -16,7 +16,7 @@ The OBSALL application is currently being developed as a set of scripts (written
 5. `graph_mod_obs.py` - python-script to run an internal self-control in calculating differences between observed and modelled data for locations of synoptical stations 
 6. `synop_stats.sh` - bash-script to run (addtional `bash`, `fortran`, `python` scripts) calculating/producing:
 - (i) rank histograms for all synop stations for 00, 06, 12 and 18 UTCs (with `produce_rank_histograms_all_stations.sh`, using `rank_histograms_one_station.f95` and `sql/import` with `odb_api`), 
-- (ii) standard plots for each synop station (with `produce_standard_plots_all_stations.sh` using `plot_quantiles_rankhist.py` and  `sql` with `oadb_api`; see an example of such plot in **Figure 1a**), and 
+- (ii) standard plots for each synop station (with `produce_standard_plots_all_stations.sh` using `plot_quantiles_rankhist_synop.py` and  `sql` with `odb_api`; see an example of such plot in **Figure 1a**), and 
 - (iii) summary rank histograms for all stations (`summary_rank_histograms_all_stations.sh` using `rank_histogram_summary_statistics.f95`, `plot_p_values_map_synop.py`, `plot_rank_hist_sum_all_stations.py` and `sql` with `odb_api`; see examples of such plots in **Figure 1b** and **Figure 1c**). 
 - Note, needed input includes: list of synop stations with geographical coordinates, modelled data at stations coordinates, pre-computed quantiles as a function of time of year and rank histogram bootstrap mean square deviation (MSD) values. 
  - ![Semantic description of image](FIGSEXAMPLES/destine_obs_synop_figs.jpg "Plots for 2 m air temperature ")* Plots for 2 metre air temperature (T2m) for period of 1 Jan - 31 Dec 2020: **Figure 1a** - Quantiles/ time series data (00, 06, 12, and 18 UTCs) and rank histogram (combination of 00, 06, 12, and 18 UTCs) for synop station 126736; **Figure 1b** - P-values for T2m quantiles; **Figure 1c** - Rank histogram summary statistics: normalized p-value frequencies and normalized quantile frequencies*
@@ -28,7 +28,7 @@ The OBSALL application is currently being developed as a set of scripts (written
 4. `radsound_mod.sh` - bash-script to run reading, extraction and interpolation (using polytope) of modelled data for air temperature at surface and at altitude at the same time-slices to geographical (latitude, longitude, pressure level) locations of radiosounding stations, calculatig difference between two temperatures, and saving (temporary) to dat-file, and adding (using `import` with `odb_api`) such data to ODB.
 5. `radsound_stats.sh` - bash-script to run (addtional `bash`, `fortran`, `python` scripts) calculating/producing:
 - (i) rank histograms for all radiosounding stations for 00 and 12 UTCs (with `produce_rank_histograms_all_stations.sh`, using `rank_histograms_one_station.f95` and `sql/import` with `odb_api`),
-- (ii) standard plots for each radiosounding station (with `produce_standard_plots_all_stations.sh` using `plot_quantiles_rankhist.py` and  `sql` with `oadb_api`; see an example of such plot in **Figure 2a**), and
+- (ii) standard plots for each radiosounding station (with `produce_standard_plots_all_stations.sh` using `plot_quantiles_rankhist_temp.py` and  `sql` with `odb_api`; see an example of such plot in **Figure 2a**), and
 - (iii) summary rank histograms for all radiosunding stations (`summary_rank_histograms_all_stations.sh` using `rank_histogram_summary_statistics.f95`, `plot_p_values_map_temp.py`, `plot_rank_hist_sum_all_stations.py` and `sql` with `odb_api`; see examples of such plots in **Figure 2b** and **Figure 2c**).
 - Note, needed input includes: list of radiosounding stations with geographical coordinates, modelled data at stations coordinates at 2 metre height and at 850 hPha pressure level, pre-computed quantiles as a function of time of year and rank histogram bootstrap mean square deviation (MSD) values.
 - ![Semantic description of image](FIGSEXAMPLES/destine_obs_radsound_figs.jpg "Plots for difference between air temperature at 2 m and 850 hPa pressure level: T2-T850")* Plots for difference in air temperatures at 2 metre and at 850 Ha pressure level (T2-T850) for period of 1 Jan - 31 Dec 2010: **Figure 2a** - Quantiles/ time series data and rank histogram (00 and 12 UTCs) for radiosounding station 51431; **Figure 2b** - P-values for T2-T850 quantiles; **Figure 2c** - Rank histogram summary statistics for 00 and 12 UTCs: normalized p-value frequencies and normalized quantile frequencies*
@@ -40,7 +40,7 @@ The OBSALL application is currently being developed as a set of scripts (written
 4. `amsua_mod.sh` - bash-script to run the `Radiance Simulator` tool with pre-described control configuration parameters and to produce a model counterpart (file in netcdf-format), which (using `convert_netcdf2txt.py`) is converted to (temporary) dat-file and added (using `import` with `odb_api`) to ODB.
 5. `amsua_stats.sh` - bash-script to run (addtional `bash`, `fortran`, `python` scripts) calculating/producing:
 - (i) rank histograms for all areas from satellite observations for daily mean values of brightness temperature (with `produce_rank_histograms_all_locations.sh`, using `rank_histograms_one_location.f95` and `sql/import` with `odb_api`),
-- (ii) standard plots for each area from satellite observations (with `produce_standard_plots_all_locations.sh` using `plot_quantiles_rankhist_amsua.py` and  `sql` with `oadb_api`; see an example of such plot in **Figure 3a**), and
+- (ii) standard plots for each area from satellite observations (with `produce_standard_plots_all_locations.sh` using `plot_quantiles_rankhist_amsua.py` and  `sql` with `odb_api`; see an example of such plot in **Figure 3a**), and
 - (iii) summary rank histograms for areas from satellite observations (`summary_rank_histograms_all_locations.sh` using `rank_histogram_sumstats_locations.f95`, `plot_p_values_map_amsua.py`, `plot_rankhist_sum_all_locations.py` and `sql` with `odb_api`; see examples of such plots in **Figure 3b** and **Figure 3c**).
 - Note, needed input includes: list of locations for areas from satellite observations with geographical coordinates, modelled data over geographical areas coordinates at sfc-, pl-, and o2d-levels, pre-computed quantiles as a function of time of year and rank histogram bootstrap mean square deviation (MSD) values.
 - ![Semantic description of image](FIGSEXAMPLES/destine_obs_satellite_figs.jpg "Plots for brightness temperature /AMSU-A Channel 5/ for selected geographical area /a00/")* Plots for brightness temperature /AMSU-A Channel 5/ for selected geographical area /a00/ for period of 1 Jan - 31 Dec 2016: **Figure 3a** - Quantiles/ time series data and rank histogram for daily mean brightness temperature for area /a00/; **Figure 3b** - P-values for brightness temperature quantiles for areas; **Figure 3c** - Rank histogram summary statistics for brightness temperature for areas: normalized p-value frequencies and normalized quantile frequencies; Note: on Figure 3b the plotted dot as a colored circle represents the central point (70 N, 45 E) of the area a00, which is situated within boundaries of [69.5, 70.5] N and [43.5, 46.5] E*