How do A-train Sensors Inter-Compare in the Retrieval of Above-Cloud Aerosol Optical Depth? A Case Study based Assessment

Atmospheric aerosols are known to produce a net cooling effect in the cloud-free conditions. However, when present over the reflective cloud decks, absorbing aerosols such as biomass burning generated smoke and wind-blown dust can potentially exert a large positive forcing through enhanced atmospheric heating resulting from cloud-aerosol radiative interactions. The interest on this aspect of aerosol science has grown significantly in the recent years. Particularly, development of the satellite-based retrieval techniques and unprecedented knowledge on the above-cloud aerosol optical depth (ACAOD) is of great relevance. A direct validation of satellite ACAOD is a difficult task primarily due to lack of ample in situ and/or remote sensing measurements of aerosols above cloud. In these circumstances, a comparative analysis on the inter-satellite ACAOD retrievals can be performed for the sack of consistency check. Here, we inter-compare the ACAOD of biomass burning plumes observed from different A-train sensors, i.e., MODIS [Jethva et al., 2013], CALIOP [Chand et al., 2008], POLDER [Waquet et al., 2009], and OMI [Torres et al., 2012]. These sensors have been shown to acquire sensitivity and independent capabilities to detect and retrieve aerosol loading above marine stratocumulus clouds--a kind of situation often found over the southeastern Atlantic Ocean during dry burning season. A systematic one-to-one comparison reveals that, in general, all passive sensors and CALIOP-based research methods retrieve comparable ACAOD over homogeneous cloud fields. The high-resolution sensors (MODIS and CALIOP) are able to retrieve aerosols over thin clouds but with larger discrepancies. Given the different types of sensor measurements processed with different algorithms, a reasonable agreement between them is encouraging. A direct validation of satellite-based ACAOD remains an open challenge for which dedicated field measurements over the region of frequent aerosol/cloud overlap are a prime requirement. Jethva, H., O. Torres, L. A. Remer, P. K. Bhartia (2013), A Color Ratio Method for Simultaneous Retrieval of Aerosol and Cloud Optical Thickness of Above-Cloud Absorbing Aerosols From Passive Sensors: Application to MODIS Measurements, Geoscience and Remote Sensing, IEEE Transactions on, 51(7), pp. 3862-3870, doi: 10.1109/TGRS.2012.2230008. Chand, D., T. L. Anderson, R. Wood, R. J. Charlson, Y. Hu, Z. Liu, and M. Vaughan (2008), Quantifying above-cloud aerosol using spaceborne lidar for improved understanding of cloudy-sky direct climate forcing, J. Geophys. Res., 113, D13206, doi:10.1029/2007JD009433. Waquet, F., J. Riedi, L. C. Labonnote, P. Goloub, B. Cairns, J.-L. Deuzeand, and D. Tanre (2009), Aerosol remote sensing over clouds using a-train observations, J. Atmos. Sci., 66(8), 2468-2480, doi: http://dx.doi.org/10.1175/2009JAS3026.1 Torres, O., H. Jethva, and P. K. Bhartia (2012), Retrieval of aerosol optical depth above clouds from OMI observations: Sensitivity analysis and case studies, J. Atmos. Sci., 69(3), 1037-1053, doi: http://dx.doi.org/10.1175/JAS-D-11-0130.