Quantifying above‐cloud aerosol using spaceborne lidar for improved understanding of cloudy‐sky direct climate forcing

Abstract

Estimates of global mean direct climate forcing by absorbing aerosols located above boundary layer clouds are large, uncertain, and almost entirely unconstrained by observations. Spaceborne lidar offers a new opportunity for global constraints. Here we examine techniques for using liquid water clouds as lidar targets, allowing aerosol optical depth and Ångström exponent to be deduced directly from aerosol effects on light transmission. Two such techniques are examined using data from the Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). The first is a previously reported method based on measurements of cloud depolarization ratio (DR) at 532‐nm wavelength. The second is a new method using measurements of cloud color ratio (CR), which is the ratio of the signal from the cloud at 1064 nm to that at 532 nm. Optical depth retrievals from these two methods compare favorably over the eastern tropical Atlantic Ocean during August 2006, when biomass burning aerosols are frequently advected over marine stratiform clouds. The CR technique is mainly sensitive to fine‐mode aerosols and essentially insensitive to clouds and coarse‐mode dust. Because anthropogenic aerosol is predominantly found in the fine mode, the CR technique can be used to help identify situations where anthropogenic cloudy‐sky direct radiative forcing is occurring. We demonstrate this capability using 6 months data over the eastern tropical Atlantic Ocean.

Cloud albedo changes in response to anthropogenic sulfate and non-sulfate aerosol forcings in CMIP5 models

“…All three models show an aerosol layer above the low clouds in the Canarian region, consistent with observations (Chand et al, 2008;Devasthale and Thomas, 2011;Waquet et al, 2013;Winker et al, 2013), with a contribution of 50 % to the total AOD. Figure 8 shows vertical cross sections of the aerosol extinction coefficient at 550 nm and the vertically resolved cloud fraction for the model MIROC, in the Canarian region, as an example, and an aerosol layer co-located with the cloud layer as well as an overlying aerosol layer is evident for all four experiments.…”

“…However, the cloud brightening shows no clear dependence on the vertical distribution of the aerosols. Dust aerosols above the clouds are found in the Canarian region, but BC aerosols are not found to be prevalent above the clouds in the biomass burning regions, which may be expected from observations (Chand et al, 2008;Devasthale and Thomas, 2011;Waquet et al, 2013;Winker et al, 2013) and which may further counteract the cloud brightening. Hence, the darkening effect of the anthropogenic non-sulfate aerosols is not strong enough in the models to counteract the brightening effect of the background aerosol, leaving climate models with predominantly positive gradients in disagreement with satellite observations .…”

Satellite perspective of aerosol intercontinental transport: From qualitative tracking to quantitative characterization

“…Some studies suggest that significant biases may exist in some regions, when satellite measurements only for cloud-free conditions are assimilated into a model (Reid et al, 2004;Zhang and Reid, 2009). Partial constraints on the aerosol load above clouds could be obtained using the emerging satellite observations of AOD above clouds from CALIOP lidar Hu et al, 2007;Chand et al, 2008) and even passive sensors like POLDER, OMI, and MODIS (Waquet et al, 2009;Torres et al, 2012;Jethva et al, submitted for publication;Yu et al, 2012b). This new capability needs to be explored.…”

Relationship between low-cloud presence and the amount of overlying aerosols

“…In an intercomparison of above-cloud AOD from A-Train satellites sensors, Jethva et al (2014) found that the CALIPSO-derived above-cloud AOD was consistently lower than those derived from the other satellites sensors in the A-Train. Chand et al (2008) and Liu et al (2015) both used alternative retrieval methods to the standard CALIPSO algorithm to derive AOD above clouds specifically. Other efforts to quantify abovecloud AOD from passive satellite sensors include the works by e.g., Knobelspiesse et al (2011), Meyer et al (2013, Torres et al (2012), and Waquet et al (2009Waquet et al ( , 2013.…”