TData_products_L.py

# L
def liquid_water_content(meta, mode, nc, ver):
   import TData_data as dat
   import TData_common as com
   import numpy as np
   
   [ET, DT, DoY] = dat.create_time(meta)
   [lat, lon] = dat.create_pos(ET, mode)
   
   [data_1d, flag_1d, min_dat, max_dat] = dat.create_data_flag(ET)
   
   # write common global attrib 
   com.global_attributes(nc, meta, ET, mode)
   
   # write specific global attrib
   nc.product_version = ver
   
   # write common dimensions
   com.dimensions(nc, ET, lat, lon)
   
   # write specific dimensions
   
   # write common variables
   com.variables(nc, ET, DT, DoY, lat, lon, mode)
   
   # write specific variables
   v = nc.createVariable('cloud_liquid_water_content', np.float32, ('time',), fill_value=-1.00e+20)
   #variable attributes
   v.units = 'kg m-2'
   v.long_name = 'Cloud Liquid Water Content'
   v.valid_min = np.float32(min_dat)
   v.valid_max = np.float32(max_dat)
   v.cell_methods = 'time: mean'
   v.coordinates = 'latitude longitude'
   #write data
   v[:] = np.float32(data_1d)  

   v = nc.createVariable('qc_flag', np.int8, ('time',))
   #variable attribute
   v.units = '1'
   v.long_name = 'Data Quality Flag'
   v.flag_values = '0b,1b,2b,3b,4b'
   v.flag_meanings = 'not_used' + '\n'
   v.flag_meanings = v.flag_meanings + 'good_data' + '\n'
   v.flag_meanings = v.flag_meanings + 'suspect_data_data_not_quality_controlled:_data<0.075' + '\n'
   v.flag_meanings = v.flag_meanings + 'suspect_data_data_not_quality_controlled:_data>0.925' + '\n'
   v.flag_meanings = v.flag_meanings + 'bad_data_do_not_use:_data=0' 
   #write data
   v[:] = np.int8(flag_1d)
   
   del dat, com, np, data_1d, flag_1d