The lognormal distribution as a reference for reporting aerosol optical depth statistics; Empirical tests using multi‐year, multi‐site AERONET Sunphotometer data

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The GIGG‐EnKF: ensemble Kalman filtering for highly skewed non‐negative uncertainty distributions (2016, methodology): “Such variables include high-impact weather and climate variables such as those pertaining to aerosols (O’Neill et al., 2000; Saide et al., 2012), rainfall (Simpson, 1972; Errico et al.”
Using the OMI aerosol index and absorption aerosol optical depth to evaluate the NASA MERRA Aerosol Reanalysis (2014, methodology): “Since a lognormal representation is more suitable to report AOD statistics (O’Neill et al., 2000), a kernel density estimation (KDE) (Silverman, 1986; Scott, 1992) was applied to approximate the joint probability density function (PDF) of observed and modeled logarithmic (natural) transformed AOD.”
The MERRA-2 Aerosol Reanalysis, 1980 - onward, Part I: System Description and Data Assimilation Evaluation. (2017, background): “Since AOD is not a normally distributed variable (e.g., O’Neill et al. 2000), the 2D analysis in Eq.”