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In the past 2 decades, ground-based lidar networks have drastically
increased in scope and relevance, thanks primarily to the advent of lidar
observations from space and their need for validation. Lidar observations of
aerosol and cloud geometrical, optical and microphysical atmospheric
properties are subsequently used to evaluate their direct radiative effects
on climate. However, the retrievals are strongly dependent on the lidar
instrument measurement technique and subsequent data processing
methodologies. In this paper, we evaluate the discrepancies between the use
of Raman and elastic lidar measurement techniques and corresponding data
processing methods for two aerosol layers in the free troposphere and for
two cirrus clouds with different optical depths. Results show that the
different lidar techniques are responsible for discrepancies in the
model-derived direct radiative effects for biomass burning (0.05 W m−2
at surface and 0.007 W m−2 at top of the atmosphere) and dust aerosol
layers (0.7 W m−2 at surface and 0.85 W m−2 at top of the
atmosphere). Data processing is further responsible for discrepancies in both thin
(0.55 W m−2 at surface and 2.7 W m−2 at top of the atmosphere)
and opaque (7.7 W m−2 at surface and 11.8 W m−2 at top of the
atmosphere) cirrus clouds. Direct radiative effect discrepancies can be
attributed to the larger variability of the lidar ratio for aerosols
(20–150 sr) than for clouds (20–35 sr). For this reason,
the influence of the applied lidar technique plays a more fundamental role in
aerosol monitoring because the lidar ratio must be retrieved with relatively
high accuracy. In contrast, for cirrus clouds, with the lidar ratio being much
less variable, the data processing is critical because smoothing it modifies
the aerosol and cloud vertically resolved extinction profile that is used as
input to compute direct radiative effect calculations.