A historic global ground-based monthly seasonal aerosol climatology based in AERONET data: a database 1993-2013

We present an aerosol classification based upon AERONET level
2.0 almucantar retrieval products from the period 1993 to 2012. In the
initial phase of this research we opto-physically identified five major
types of Bulk Columnar Aerosol (BCA) - based solely upon intensive optical
properties of spectral Single Scattering Albedo (SSA), spectral Indices of
Refraction (real – RRI and imaginary - IRI), and two Angstrom Exponents
(extinction – EAE and absorption - AAE). These BCA we classified as
Maritime Aerosol, Dust Aerosol, Urban Industrial Aerosol, Biomass Burning
Aerosol, and Mixed Aerosol. The classification of a particular observation
as one of these aerosol types is determined by its five-dimensional
Mahalanobis distance (MD) to the centroid of each reference cluster
(itself a 5-D hyperellipsoid). To retain a greater number of AERONET sites
in the study (200+), we kept the variable space to 5-D. To generate
reference clusters, we only retained data points that lie within 2 MD from
the data centroid. Our typology is based on AERONET retrieved quantities,
which do not include low optical depth values (AOD=440nm < 0.4 as
per AERONET criteria for almucantar scan inversion). The classifications
obtained will be useful in interpreting aerosol retrievals from satellite
borne instruments and as input for regional climate models. The result is
a dataset describing the types of aerosol particles that are distinct from
one another in optical properties, and a geographic distribution of those
aerosol types. We used the typology scheme upon the qualifying AERONET
data archive, and produced seasonal aerosol climatologies by aerosol type
for each of the AERONET sites included in the study, regional aerosol
climatology maps, and a time-integrated global aerosol climatology map
based entirely upon ground-based photometric data. An internally
hyperlinked compendium of the individual AERONET site aerosol
climatologies was produced to contain the results of the first phase of
this work [available at
https://ars.els-cdn.com/content/image/1-s2.0-S1352231016304265-mmc1.pdf].
Each of these five aerosol types can be further discriminated into
specific sub-types by this same scheme. For example, optical
discrimination into specific sub-types of Biomass Burning aerosol may
provide insight into sources exhibiting spectrally distinct smoke
properties. We then use the mathematical strategies to sort the global
AERONET data retrievals into the aerosol type classified against the
reference standards. We believe these strategies regarding aerosol
differentiation using polarization data will be useful for analysis of the
newer AERONET version 3 data retrievals, and data collected from the
deployment of newer CIMEL sun-photometers (with enhanced polarization
measurement capabilities) to the network. The resulting AERONET-based
aerosol typology is useful for applications in aerosol optics, including
forward modeling or radiative transfer for remote sensing algorithms, or
evaluating radiative forcing calculations in atmospheric models. Necessary
Reference Material: [1] Giordano, M. E., On Interactions of Matter and
Energy: Light and Particles in a Terrestrial Atmosphere Progress on
Opto-Physical Recognition and Classification of Aerosols: A PhD
dissertation, University of Nevada, copyright M.E. Giordano, 294 pages,
December 2019. URI: http://hdl.handle.net/11714/6686 
https://scholarworks.unr.edu/handle/11714/6686?show=full [2] 
Giordano, M.E., Ward, C.S., and Hamill, P.: A Compendium of Aerosol Types
Based on Mahalanobis Distances and AERONET data. [An internally
hyperlinked compendium of seasonal aerosol and local aerosol compositions]
Atmospheric Environment, 140, 213-233,2016. 
https://doi.org/10.1016/j.atmosenv.2016.06.002  
https://ars.els-cdn.com/content/image/1-s2.0-S1352231016304265-mmc1.pdf
[3]  Hamill, P. J., Giordano, M. E., Ward, C.S., Giles, D.,
Holben, B.: An AERONET - based aerosol classification using the
Mahalanobis distance, Atmospheric Environment, Volume 140, September, pgs
213 -233,
2016. http://dx.doi.org/10.1016/j.atmosenv.2016.06.002and also at
https://ars.els-cdn.com/content/image/1-s2.0-S1352231016304265-mmc1.pdf
[4]  Hamill, Patrick, Piedra, Patricio G., Giordano, Marco, E.,
2020: Simulated Polarization as a Signature of Aerosol Type. Atmospheric
Environment, Volume 224, 117348 article ATMENVD- 19-01763,
2020. https://doi.org/10.1016/j.atmosenv.2020.117348