extract_aerosol_subtype(vfm_array)[source]¶Extracts the aerosol sub type using extract_type and extract_sub_type
0 = not determined 1 = clean marine 2 = dust 3 = polluted continental 4 = clean continental 5 = polluted dust 6 = smoke 7 = other
extract_horiz_avg(vfm_array)[source]¶Extracts the identifier for the ammount of horizontal averaging:
0 = not applicable 1 = 1/3 km 2 = 1 km 3 = 5 km 4 = 20 km 5 = 80 km
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extract_qa(vfm_array)[source]¶Extracts quality assurance information for each element of the array:
0 = none 1 = low 2 = medium 3 = high
extract_sub_type(vfm_array)[source]¶Extracts the subtype for each element of the array. Its interpretation depends on whether the feature is an aerosol, cloud, or Polar Stratospheric Cloud.
Aerosol:
0 = not determined 1 = clean marine 2 = dust 3 = polluted continental 4 = clean continental 5 = polluted dust 6 = smoke 7 = other
Cloud:
0 = low overcast, transparent 1 = low overcast, opaque 2 = transition stratocumulus 3 = low, broken cumulus 4 = altocumulus (transparent) 5 = altostratus (opaque) 6 = cirrus (transparent) 7 = deep convective (opaque)
Polar Stratospheric Cloud:
0 = not determined 1 = non-depolarizing PSC 2 = depolarizing PSC 3 = non-depolarizing aerosol 4 = depolarizing aerosol 5 = spare 6 = spare 7 = other
extract_type(vfm_array)[source]¶Extracts feature type for each element in a vertical feature mask array:
0 = invalid (bad or missing data) 1 = ‘clear air’ 2 = cloud 3 = aerosol 4 = stratospheric feature 5 = surface 6 = subsurface 7 = no signal (totally attenuated)
extract_type_confidence(vfm_array)[source]¶Extracts the degree of confidence that the feature type has been determined correctly:
0 = not confident 1 = confident