Evaluating the impact of aerosol particles above cloud on cloud optical depth retrievals from MODIS

Abstract

Using two different operational Aqua Moderate Resolution Imaging Spectroradiometer (MODIS)cloud optical depth (COD) retrievals (0.86 versus 1.6 μm), we evaluate the impact of above-cloud smoke aerosol particles on near-IR (0.86 μm) COD retrievals. Aerosol Index (AI) from the collocated Ozone Monitoring Instrument (OMI) are used to identify above-cloud aerosol particle loading over the southern Atlantic Ocean, including both smoke and dust from the African subcontinent. Collocated Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation data constrain cloud phase and provide contextual above-cloud aerosol optical depth. The frequency of occurrence of above-cloud aerosol events is depicted on a global scale for the spring and summer seasons from OMI and Cloud Aerosol Lidar with Orthogonal Polarization. Seasonal frequencies for smoke-over-cloud off the southwestern Africa coastline reach 20-50% in boreal summer. We find a corresponding low COD bias of 10-20% for standard MODIS COD retrievals when averaged OMI AI are larger than 1. No such bias is found over the Saharan dust outflow region off northern Africa, since both MODIS 0.86 and 1.6 μm channels are vulnerable to radiance attenuation due to dust particles. A similar result is found for a smaller domain, in the Gulf of Tonkin region, from smoke advection over marine stratocumulus clouds and outflow into the northern South China Sea in spring. This study shows the necessity of accounting for the above-cloud aerosol events for future studies using standard MODIS cloud products in biomass burning outflow regions, through the use of collocated OMI AI and supplementary MODIS 1.6 μm COD products.

Investigating the frequency and interannual variability in global above-cloud aerosol characteristics with CALIOP and OMI

“…For identification of ACA, 5 km CALIOP 532 nm cloud and aerosol layer products are used (Winker et al, , 2010 for resolving aerosol extinction above apparent cloudtop heights in each respective product file (e.g., Yu et al, 2012;Alfaro-Contreras et al, 2014). The 532 nm abovecloud aerosol optical depth (ACAOD) is then solved by integrating the extinction coefficient over those corresponding bins (Liu et al, 2015;Kacenelenbogen et al, 2014).…”

“…retrievals are uniquely biased (Wilcox et al, 2009;Meyer et al, 2013;Alfaro-Contreras et al, 2014;Li et al, 2014). ACA further perturbs regional radiation budgets by absorbing and reflecting radiation from the cloud layers underneath the unidentified aerosol particle layer (e.g., Haywood et al, 2004), which again must be accounted for when estimating global cloud and aerosol forcing budgets and regional semidirect impact on static stability and cloud feedback.…”

“…Ozone Monitoring Instrument (OMI) measurements have also been used for studying ACA events (e.g., Wilcox et al, 2009;Yu et al, 2012;Alfaro-Contreras et al, 2014). In particular, the OMI aerosol index (AI), computed using the difference between observed and calculated ultraviolet (UV) radiances (Torres et al, 2007), has been used to locate UV-absorbing aerosols suspended over bright cloud decks (e.g., Yu et al, 2012;Torres et al, 2012).…”

“…In particular, the OMI aerosol index (AI), computed using the difference between observed and calculated ultraviolet (UV) radiances (Torres et al, 2007), has been used to locate UV-absorbing aerosols suspended over bright cloud decks (e.g., Yu et al, 2012;Torres et al, 2012). This technique, originally used on the Total Ozone Mapping Spectrometer (TOMS), can only be used to detect UV-absorbing aerosols, such as biomass burning smoke and desert dust aerosols, and is sensitive to underneath cloud properties (e.g., Yu et al, 2012;Alfaro-Contreras et al, 2014). Further, and compared with CALIOP, OMI measurements represent a relatively large surface footprint of 13 × 24 km at nadir, which limits cloud-clearing efficacies since footprints of this size are prone to sub-pixel cloud contamination (Torres et al, 2007).…”

Characterizing the 2015 Indonesia Fire Event Using Modified MODIS Aerosol Retrievals

“…Still, those parameters need to be used with caution. A thin layer of absorbing aerosol above clouds can trigger very high AI values especially for regions with optically thick clouds (Meyer et al, 2013;Yu et al, 2012;Alfaro-Contreras et al, 2014;Torres et al, 2012). Also, erroneously high MODIS AOD can be found over 20 cloud edges due to inaccurate cloud screening or cloud 3-D effects (Zhang et al, 2006;Shi et al, 2010).…”