Impact of varying lidar measurement and data processing techniques in evaluating cirrus cloud and aerosol direct radiative effects

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.