updated first cloud file, will use for remaining cloud use cases

docs/use_cases/model_applications/clouds/GridStat_fcstGFS_obsERA5_lowAndTotalCloudFrac.py

@@ -51,13 +51,10 @@
 # ------------------
 #
 # This use case utilizes Python Embedding, which is called using the PYTHON_NUMPY keyword 
-# in the observation input template settings. The same Python script can processes both forecast and
-# observation datasets, but only the observation dataset is not
-# set up for native ingest by MET. Two separate forecast fields are verified against two respective observation fields,
-# with the Python script being passed the input file, the model name, the variable name being analyzed,
-# the initialization and valid times, and a flag to indicate if the field passed is observation or forecast.
-# This process is repeated with 3 instance names to GridStat, each with a different setting for regridding,
-# neighborhood evaluation, thresholding, output line types, and output prefix names.
+# in the observation input template settings. The Python script is passed an input file,
+# model name, variable field name being analyzed, the initialization and valid times, 
+# and a flag to indicate if the field passed is observation or forecast.
+# After a successful call, a MET-readable gridded observation dataset is passed back to GridStat for evaluation.
 
 ##############################################################################
 # METplus Workflow
@@ -77,7 +74,20 @@
 # | **Init:** 2022-07-03 12Z
 # | **Forecast lead:** 36 hour
 #
-# Because instance names are used, GridStat will run 3 times for this 1 initalization time.
+# Because instance names are used, GridStat will run 3 times for this 1 initalization time. Each of the 
+# instance names correspond to different regridding, neighborhood evaluations, thresholding, output line types, and output
+# prefix names. For the first GridStat instance, total cloud cover fraction and low cloud cover fraction are verified 
+# at 10 separate thresholds. The observation dataset is provided via Python Embedding. Various output line types are requested
+# and placed in stat files, with a unique output prefix indicating which output are from which GridStat instance. All of the 
+# evaluation takes place within the masked region, read in via a poly line file.
+# For the nbr GridStat instance, the same variables are verified, but the thresholds are expanded to include forecast 
+# and observation percentiles, ranging from 20 to 80. This instance also creates 4 neighborhoods of varying width using
+# a circle definition. The related neighborhood line types are requested as output and a new ouput prefix is used.
+# Finally, the prob GridStat instance updates the thresholds for the two variable fields to range from 0 to 1 and 
+# changes the forecast field to probabilistic space via the FCST_IS_PROB setting. Neighborhoods using the same definitions
+# from the nbr instance are used, and the respective line types are requested with a new output prefix for output files
+# from this instance.
+
 
 ##############################################################################
 # METplus Configuration
@@ -110,7 +120,20 @@
 # Python Embedding
 # ----------------
 #
-# This use case utilizes 1 Python script to read and process the observation fields.
+# This use case utilizes one Python script to read and process the observation fields to become 
+# METplus usable. From the configuration file it collects an input file, model name, 
+# variable field name being analyzed, the initialization and valid times, 
+# and a flag to indicate if the field passed is observation or forecast. Once the script runs,
+# it uses the model name to extract the correct grid definition from the griddedDatasets dictionary,
+# and the variable field name is used to extract the correct file variable field name (in combination
+# with the name of the model) from the verifVariables dictionary. These are combined into a dictionary 
+# filled with values and keys used by the rest of the code, specifically set for the model and field
+# being used. A Total cloud fraction call results in the field being extracted and set to a 0-100 range
+# with a similar behavior for low cloud cover. The grid type associated with each model (determined by the
+# griddedDatasets dictionary) helps the script create the grid's corresponding latitude and longitude arrays.
+# Finally, the valid and initialization times that were passed at runtime are used to finalize the attrs dictionary
+# and the dataset is passed back to METplus for evaluation.
+
 # The location of the code is
 #
 # .. dropdown:: parm/use_cases/model_applications/clouds/GridStat_fcstGFS_obsERA5_lowAndTotalCloudFrac/read_input_data.py
@@ -124,8 +147,7 @@
 ##############################################################################
 # User Scripting
 # --------------
-# [UPDATE_SECTION_CONTENT]
-#
+# User Scripting is not used in this use case.
 
 ##############################################################################
 # Running METplus
@@ -155,7 +177,17 @@
 # * grid_stat_GFS_to_ERA5_F36_CloudFracs_NBR_360000L_20220705_000000V_pairs.nc
 # * grid_stat_GFS_to_ERA5_F36_CloudFracs_NBR_360000L_20220705_000000V.stat
 # * grid_stat_GFS_to_ERA5_F36_CloudFracs_PROB_360000L_20220705_000000V_pairs.nc
-# * grid_stat_GFS_to_ERA5_F36_CloudFracs_PRB_360000L_20220705_000000V.stat
+# * grid_stat_GFS_to_ERA5_F36_CloudFracs_PROB_360000L_20220705_000000V.stat
+#
+# The netCDF files from the first GridStat instance and prob instance will contain 
+# the raw fields, difference fields, and gradient fields using the supplied masking area.
+# For the nbr instance, there will be additional fields for the fractional coverage 
+# fields. Each of the instance's output can be identified by an additional tag in the file
+# name (NBR for nbr, PROB for prob, and none for the first GridStat instance). For the
+# accompanying stat files, the first GridStat instance contains FHO, CTC, CTS, CNT, SL1L2, and 
+# GRAD line types. The nbr instance will contain only the neighborhood-related line types
+# (NBRCTC, NBRCTS, and NBRCNT). Finally, the prob GridStat instance will contain probabilistic
+# line types only (PCT, PSTD, PJC, and PRC).
 
 ##############################################################################
 # Keywords