New Global View of Above-Cloud Absorbing Aerosol Distribution Based on CALIPSO Measurements

Above-low-level-cloud aerosols (ACAs) have gradually gained more interest in recent years; however, the combined aerosol–cloud radiation effects are not well understood. The uncertainty about the radiative effects of aerosols above cloud mainly stems from the lack of comprehensive and accurate retrieval of aerosols and clouds for ACA scenes. In this study, an improved ACA identification and retrieval methodology was developed to provide a new global view of the ACA distribution by combining three-channel CALIOP (The Cloud–Aerosol Lidar with Orthogonal Polarization) observations. The new method can reliably identify and retrieve both thin and dense ACA layers, providing consistent results between the day- and night-time retrieval of ACAs. Then, new four-year (2007 to 2010) global ACA datasets were built, and new seasonal mean views of global ACA occurrence, optical depth, and geometrical thickness were presented and analyzed. Further discussion on the relative position of ACAs to low clouds showed that the mean distance between the ACA layer and the low cloud deck over the tropical Atlantic region is less than 0.2 km. This indicates that the ACAs over this region are more likely to be mixed with low-level clouds, thereby possibly influencing the cloud microphysics over this region, contrary to findings reported from previous studies. The results not only help us better understand global aerosol transportation and aerosol–cloud interactions but also provide useful information for model evaluation and improvements.

The spectral signature of cloud spatial structure in shortwave irradiance

In this paper, we used cloud imagery from a NASA field experiment in conjunction with three-dimensional radiative transfer calculations to show that cloud spatial structure manifests itself as a spectral signature in shortwave irradiance fields - specifically in transmittance and net horizontal photon transport in the visible and near-ultraviolet wavelength range. We found a robust correlation between the magnitude of net horizontal photon transport (H) and its spectral dependence (slope), which is scale-invariant and holds for the entire pixel population of a domain. This was surprising at first given the large degree of spatial inhomogeneity. We prove that the underlying physical mechanism for this phenomenon is molecular scattering in conjunction with cloud spatial structure. On this basis, we developed a simple parameterization through a single parameter ε, which quantifies the characteristic spectral signature of spatial inhomogeneities. In the case we studied, neglecting net horizontal photon transport leads to a local transmittance bias of ±12-19 %, even at the relatively coarse spatial resolution of 20 km. Since three-dimensional effects depend on the spatial context of a given pixel in a nontrivial way, the spectral dimension of this problem may emerge as the starting point for future bias corrections.

Interactions between biomass-burning aerosols and clouds over Southeast Asia: current status, challenges, and perspectives

The interactions between aerosols, clouds, and precipitation remain among the largest sources of uncertainty in the Earth's energy budget. Biomass-burning aerosols are a key feature of the global aerosol system, with significant annually-repeating fires in several parts of the world, including Southeast Asia (SEA). SEA in particular provides a "natural laboratory" for these studies, as smoke travels from source regions downwind in which it is coupled to persistent stratocumulus decks. However, SEA has been under-exploited for these studies. This review summarizes previous related field campaigns in SEA, with a focus on the ongoing Seven South East Asian Studies (7-SEAS) and results from the most recent BASELInE deployment. Progress from remote sensing and modeling studies, along with the challenges faced for these studies, are also discussed. We suggest that improvements to our knowledge of these aerosol/cloud effects require the synergistic use of field measurements with remote sensing and modeling tools.