Merge pull request #186 from mebruckner/develop_satellite

code comment adjustments for Develop satellite

melodies_monet/driver.py

@@ -434,8 +434,6 @@ def open_model_files(self, time_interval=None):
             self.obj = mio.models._cesm_se_mm.open_mfdataset(self.files,**self.mod_kwargs)
             #self.obj, self.obj_scrip = read_cesm_se.open_mfdataset(self.files,**self.mod_kwargs)
             #self.obj.monet.scrip = self.obj_scrip
-        # MEB: addition for personal local copy to work with development UFS-RAQMS
-        #      not intended for public versions
         elif 'raqms' in self.model.lower():
             if time_interval is not None:
                 # fill filelist with subset
@@ -687,8 +685,6 @@ def open_models(self, time_interval=None,load_files=True):
                 # set the model label in the dictionary and model class instance
                 if "apply_ak" in self.control_dict['model'][mod].keys():
                     m.apply_ak = self.control_dict['model'][mod]['apply_ak']
-                else:
-                    m.apply_ak = False
                 if 'radius_of_influence' in self.control_dict['model'][mod].keys():
                     m.radius_of_influence = self.control_dict['model'][mod]['radius_of_influence']
                 else:
@@ -863,6 +859,7 @@ def pair_data(self, time_interval=None):
                     p.obj = p.fix_paired_xarray(dset=p.obj)
                     # write_util.write_ncf(p.obj,p.filename) # write out to file
                 # TODO: add other network types / data types where (ie flight, satellite etc)
+                # if sat_swath_clm (satellite l2 column products)
                 elif obs.obs_type.lower() == 'sat_swath_clm':
 
                     if obs.label == 'omps_nm':
@@ -890,6 +887,7 @@ def pair_data(self, time_interval=None):
                         p.obj = paired_data 
                         label = '{}_{}'.format(p.obs,p.model)
                         self.paired[label] = p
+                # if sat_grid_clm (satellite l3 column products)
                 elif obs.obs_type.lower() == 'sat_grid_clm':
                     if obs.label == 'omps_l3':
                         from .util import satellite_utilities as sutil
@@ -1008,7 +1006,6 @@ def plotting(self):
                             else:
                                 pairdf_all = p.obj
                             # Select only the analysis time window.
-                            print(pairdf_all.dims)
                             pairdf_all = pairdf_all.sel(time=slice(self.start_time,self.end_time))
 
                         # Determine the default plotting colors.

melodies_monet/util/read_util.py

@@ -137,6 +137,7 @@ def read_analysis_ncf(filenames,xr_kws={}):
             if count==0:
                 ds_out = xr.open_dataset(file,**xr_kws)
                 group_name1 =  ds_out.attrs['group_name']
+
             else:
                 ds_append = xr.open_dataset(file,**xr_kws)
                 # Test if all the files have the same group to prevent merge issues

melodies_monet/util/satellite_utilities.py

@@ -5,12 +5,12 @@
 from datetime import datetime,timedelta
 
 def omps_l3_daily_o3_pairing(model_data,obs_data,ozone_ppbv_varname):
-    '''Calculate model ozone column from model ozone profile in ppv. Move data from model grid 
+    '''Calculate model ozone column from model ozone profile in ppbv. Move data from model grid 
         to 1x1 degree OMPS L3 data grid. Following data grid matching, take daily mean for model data.
     '''
     import xesmf as xe
 
-    # factor for converting ppv profiles to DU column
+    # factor for converting ppbv profiles to DU column
     # also requires conversion of dp from Pa to hPa
     du_fac = 1.0e-5*6.023e23/28.97/9.8/2.687e19
     column = (du_fac*(model_data['dp_pa']/100.)*model_data[ozone_ppbv_varname]).sum('z')
@@ -88,7 +88,7 @@ def space_and_time_pairing(model_data,obs_data,pair_variables):
                     ds[j][:,tindex,:] += np.expand_dims(tfac1.values,axis=1)*interm_var.values
     return ds
 def omps_nm_pairing(model_data,obs_data,ozone_ppbv_varname):
-    'Pairs UFS-RAQMS ozone mixing ratio with OMPS nadir mapper retrievals. Calculates column without applying apriori'
+    'Pairs model ozone mixing ratio with OMPS nadir mapper retrievals. Calculates column without applying apriori'
     import xarray as xr
 
     import pandas as pd
@@ -116,12 +116,12 @@ def omps_nm_pairing(model_data,obs_data,ozone_ppbv_varname):
 
 
 def omps_nm_pairing_apriori(model_data,obs_data,ozone_ppbv_varname):
-    'Pairs UFS-RAQMS data with OMPS nm. Applies satellite apriori column to model observations.'
+    'Pairs model ozone mixing ratio data with OMPS nm. Applies satellite apriori column to model observations.'
 
     import xarray as xr
 
     import pandas as pd
-    du_fac = 1.0e-5*6.023e23/28.97/9.8/2.687e19 # conversion factor; moves model from ppv to dobson
+    du_fac = 1.0e-5*6.023e23/28.97/9.8/2.687e19 # conversion factor; moves model from ppbv to dobson
 
     print('pairing with averaging kernel application')