Publications

McHardy, TM; Campbell, JR; Peterson, DA; Lolli, S; Bankert, RL; Garnier, A; Kuciauskas, AP; Surratt, ML; Marquis, JW; Miller, SD; Dolinar, EK; Dong, XQ (2021). Advancing Maritime Transparent Cirrus Detection Using the Advanced Baseline Imager "Cirrus" Band. JOURNAL OF ATMOSPHERIC AND OCEANIC TECHNOLOGY, 38(6), 1093-1110.

Abstract
We describe a quantitative evaluation of maritime transparent cirrus cloud detection, which is based on Geostationary Operational Environmental Satellite 16 (GOES-16) and developed with collocated Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) profiling. The detection algorithm is developed using one month of collocated GOES-16 Advanced Baseline Imager (ABI) channel-4 (1.378 mu m) radiance and CALIOP 0.532-mu m column-integrated cloud optical depth (COD). First, the relationships between the clear-sky 1.378-mu m radiance, viewing/solar geometry, and precipitable water vapor (PWV) are characterized. Using machine-learning techniques, it is shown that the total atmospheric pathlength, proxied by airmass factor (AMF), is a suitable replacement for viewing zenith and solar zenith angles alone, and that PWV is not a significant problem over ocean. Detection thresholds are computed using the channel-4 radiance as a function of AMF. The algorithm detects nearly 50% of subvisual cirrus (COD < 0.03), 80% of transparent cirrus (0.03 < COD < 0.3), and 90% of opaque cirrus (COD > 0.3). Using a conservative radiance threshold results in 84% of cloudy pixels being correctly identified and 4% of clear-sky pixels being misidentified as cirrus. A semiquantitative COD retrieval is developed for GOES ABI based on the observed relationship between CALIOP COD and 1.378-mu m radiance. This study lays the groundwork for a more complex, operational GOES transparent cirrus detection algorithm. Future expansion includes an overland algorithm, a more robust COD retrieval that is suitable for assimilation purposes, and downstream GOES products such as cirrus cloud microphysical property retrieval based on ABI infrared channels.

DOI:
10.1175/JTECH-D-20-0130.1

ISSN:
0739-0572