Aerosols, humidity and clouds are often correlated.
Therefore, rigorous cloud screening can systematically bias
toward less cloudy and drier conditions, underestimating the
average aerosol optical thickness (AOT). Here, using
AERONET data we show that systematic rejection of
variable atmospheric optical conditions can generate such
bias in the average AOT. Therefore we recommend two
approaches to deal with cloud contamination: (1) to introduce
more powerful spectral variability cloud screening and (2) to
retain most of the data despite cloud contamination, estimate
average cloud contamination and to correct for it. Both
methods are applied to aerosol with A ° ngstro¨m exponent >
0.3 and compared with the AERONET cloud screened level
1.5 data. The new methods do not apply for pure dust.
Analysis for 10 AERONET stations with 4 years of
data, shows almost no change for Rome (Italy), but up to a
change in AOT of 0.12 or +30% in Beijing (PRC).
Citation: Kaufman, Y. J., G. P. Gobbi, and I. Koren (2006),
Aerosol climatology using a tunable spectral variability cloud
screening of AERONET data, Geophys. Res. Lett., 33, L07817,
doi:10.1029/2005GL025478.