Preprints
https://doi.org/10.5194/gmd-2021-17
https://doi.org/10.5194/gmd-2021-17

Submitted as: model experiment description paper 28 May 2021

Submitted as: model experiment description paper | 28 May 2021

Review status: this preprint is currently under review for the journal GMD.

Analysis of the MODIS Above-Cloud Aerosol Retrieval Algorithm Using MCARS

Galina Wind1,2, Arlindo M. da Silva2, Kerry G. Meyer2, Steven Platnick2, and Peter M. Norris3,2 Galina Wind et al.
  • 1SSAI, Inc. 10210 Greenbelt Road, Suite 600, Lanham, Maryland 20706, USA
  • 2NASA Goddard Space Flight Center, 8800 Greenbelt Rd. Greenbelt, Maryland, 20771, USA
  • 3Universities Space Research Association, 7178 Columbia Gateway Dr., Columbia, MD 21046, USA

Abstract. The Multi-sensor Cloud and Aerosol Retrieval Simulator (MCARS) presently produces synthetic radiance data from Goddard Earth Observing System version 5 (GEOS-5) model output as if the Moderate Resolution Imaging Spectroradiometer (MODIS) was viewing a combination of atmospheric column inclusive of clouds, aerosols and a variety of gases and land/ocean surface at a specific location. In this paper we use MCARS to study the MODIS Above-Cloud AEROsol retrieval algorithm (MOD06ACAERO). MOD06ACAERO is presently a regional research algorithm able to retrieve aerosol optical thickness over clouds, in particular absorbing biomass burning aerosols overlying marine boundary layer clouds in the Southeastern Atlantic Ocean. The algorithm's ability to provide aerosol information in cloudy conditions makes it a valuable source of information for modeling and climate studies in an area where current clear sky-only operational MODIS aerosol retrievals effectively have a data gap between the months of June and October. We use MCARS for a verification and closure study of the MOD06ACAERO algorithm.

Our simulations indicate that the MOD06ACAERO algorithm performs well for marine boundary layer clouds in the SE Atlantic provided some specific screening rules are observed. For the present study, a combination of five simulated MODIS data granules was used for a dataset of 13.5 million samples with known input conditions. When pixel retrieval uncertainty was less than 30 %, optical thickness of the underlying cloud layer was greater than 4 and scattering angle range within the cloud bow was excluded, MOD06ACAERO retrievals agreed with the underlying ground truth (GEOS-5 cloud and aerosol profiles used to generate the synthetic radiances) with a slope of 0.913, offset of 0.06, and RMSE = 0.107. When only near-nadir pixels were considered (view zenith angle within +/−20 degrees) the agreement with source data further improved (0.977, 0.051 and 0.096 respectively). Algorithm closure was examined using a single case out of the five used for verification. For closure, the MOD06ACAERO code was modified to use GEOS-5 temperature and moisture profiles as ancillary. Agreement of MOD06ACAERO retrievals with source data for the closure study had a slope of 0.996 with offset −0.007 and RMSE of 0.097 at pixel uncertainty level of less than 40 %, illustrating the benefits of high-quality ancillary atmospheric data for such retrievals.

Galina Wind et al.

Status: open (until 23 Jul 2021)

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Galina Wind et al.

Galina Wind et al.

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Short summary
This is the third paper in series about the Multi-sensor Cloud and Aerosol Retrieval Simulator (MCARS). In this paper we use MCARS to create a set of constraints that might be used to assimilate a new above-cloud aerosol retrieval product developed for the MODIS instrument into a GCM. We executed the above-cloud aerosol retrieval over a series of synthetic MODIS granules and found the product to be of excellent quality.