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dc.contributor.authorMcHardy, T.M.
dc.contributor.authorCampbell, J.R.
dc.contributor.authorPeterson, D.A.
dc.contributor.authorLolli, S.
dc.contributor.authorGarnier, A.
dc.contributor.authorKuciauskas, A.P.
dc.contributor.authorSurratt, M.L.
dc.contributor.authorMarquis, J.W.
dc.contributor.authorMiller, S.D.
dc.contributor.authorDolinar, E.K.
dc.contributor.authorDong, X.
dc.date.accessioned2022-11-23T18:21:17Z
dc.date.available2022-11-23T18:21:17Z
dc.date.issued2022
dc.identifier.citationMcHardy, T. M., Campbell, J. R., Peterson, D. A., Lolli, S., Garnier, A., Kuciauskas, A. P., Surratt, M. L., Marquis, J. W., Miller, S. D., Dolinar, E. K., & Dong, X. (2022). GOES ABI Detection of Thin Cirrus over Land. Journal of Atmospheric and Oceanic Technology, 39(9), 1415–1429.
dc.identifier.issn0739-0572
dc.identifier.doi10.1175/JTECH-D-21-0160.1
dc.identifier.urihttp://hdl.handle.net/10150/666902
dc.description.abstractThis study develops a new thin cirrus detection algorithm applicable to overland scenes. The methodology builds from a previously developed overwater algorithm, which makes use of the Geostationary Operational Environmental Satellite 16 (GOES-16) Advanced Baseline Imager (ABI) channel 4 radiance (1.378-μm “cirrus” band). Calibration of this algorithm is based on coincident Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) cloud profiles. Emphasis is placed on rejection of false detections that are more common in overland scenes. Clear-sky false alarm rates over land are examined as a function of precipitable water vapor (PWV), showing that nearly all pixels having a PWV of <0.4 cm produce false alarms. Enforcing an above-cloud PWV minimum threshold of ∼1 cm ensures that most low-/midlevel clouds are not misclassified as cirrus by the algorithm. Pixel-filtering based on the total column PWV and the PWV for a layer between the top of the atmosphere (TOA) and a predetermined altitude H removes significant land surface and low-/midlevel cloud false alarms from the overall sample while preserving over 80% of valid cirrus pixels. Additionally, the use of an aggressive PWV layer threshold preferentially removes noncirrus pixels such that the remaining sample is composed of nearly 70% cirrus pixels, at the cost of a much-reduced overall sample size. This study shows that lower-tropospheric clouds are a much more significant source of uncertainty in cirrus detection than the land surface. © 2022 American Meteorological Society.
dc.language.isoen
dc.publisherAmerican Meteorological Society
dc.rightsCopyright © 2022 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/
dc.subjectCirrus clouds
dc.subjectCloud retrieval
dc.subjectRemote sensing
dc.titleGOES ABI Detection of Thin Cirrus over Land
dc.typeArticle
dc.typetext
dc.contributor.departmentDepartment of Hydrology and Atmospheric Sciences, University of Arizona
dc.identifier.journalJournal of Atmospheric and Oceanic Technology
dc.description.note6 month embargo; online publication: 21 September 2022
dc.description.collectioninformationThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.
dc.eprint.versionFinal published version
dc.source.journaltitleJournal of Atmospheric and Oceanic Technology


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