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dc.contributor.authorMarquis, Jared W.  Concept link
dc.contributor.authorBogdanoff, Alec S.  Concept link
dc.contributor.authorCampbell, James R.  Concept link
dc.contributor.authorCummings, James A.  Concept link
dc.contributor.authorWestphal, Douglas L.  Concept link
dc.contributor.authorSmith, Nathaniel J.  Concept link
dc.contributor.authorZhang, Jianglong  Concept link
dc.date.accessioned2017-04-11T18:34:51Z
dc.date.available2017-08-06T08:24:13Z
dc.date.issued2017-02-06
dc.identifier.citationJournal of Atmospheric and Oceanic Technology 34 (2017): 355-373en_US
dc.identifier.urihttps://hdl.handle.net/1912/8888
dc.descriptionAuthor Posting. © American Meteorological Society, 2017. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of Atmospheric and Oceanic Technology 34 (2017): 355-373, doi:10.1175/JTECH-D-15-0226.1.en_US
dc.description.abstractPassive longwave infrared radiometric satellite–based retrievals of sea surface temperature (SST) at instrument nadir are investigated for cold bias caused by unscreened optically thin cirrus (OTC) clouds [cloud optical depth (COD) ≤ 0.3]. Level 2 nonlinear SST (NLSST) retrievals over tropical oceans (30°S–30°N) from Moderate Resolution Imaging Spectroradiometer (MODIS) radiances collected aboard the NASA Aqua satellite (Aqua-MODIS) are collocated with cloud profiles from the Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument. OTC clouds are present in approximately 25% of tropical quality-assured (QA) Aqua-MODIS Level 2 data, representing over 99% of all contaminating cirrus found. Cold-biased NLSST (MODIS, AVHRR, and VIIRS) and triple-window (AVHRR and VIIRS only) SST retrievals are modeled based on operational algorithms using radiative transfer model simulations conducted with a hypothetical 1.5-km-thick OTC cloud placed incrementally from 10.0 to 18.0 km above mean sea level for cloud optical depths between 0.0 and 0.3. Corresponding cold bias estimates for each sensor are estimated using relative Aqua-MODIS cloud contamination frequencies as a function of cloud-top height and COD (assuming they are consistent across each platform) integrated within each corresponding modeled cold bias matrix. NLSST relative OTC cold biases, for any single observation, range from 0.33° to 0.55°C for the three sensors, with an absolute (bulk mean) bias between 0.09° and 0.14°C. Triple-window retrievals are more resilient, ranging from 0.08° to 0.14°C relative and from 0.02° to 0.04°C absolute. Cold biases are constant across the Pacific and Indian Oceans. Absolute bias is lower over the Atlantic but relative bias is higher, indicating that this issue persists globally.en_US
dc.description.sponsorshipAuthors JWM, NJS, and JZ acknowledge the support of NASA Project NNX14AJ13G andNSF Project IIA-1355466.Author JZ also acknowledges the support of ONR N00014-16-1-2040 (Grant 11843919). Author JWM further recognizes the Naval Research Enterprise Internship Program (NREIP). Support for his NREIP fellowship came from NASA Interagency Agreement NNG15JA17P on behalf of theMicro-Pulse LidarNetwork (E. J. Welton). Authors JRC, JAC and DLW acknowledge the support of Office of Naval Research Code 322 (PE0602435). Author JRC also acknowledges the support of NASA Interagency Agreement RPO201522 on behalf of the CALIPSO Science Team (C. R. Trepte).en_US
dc.language.isoen_USen_US
dc.publisherAmerican Meteorological Societyen_US
dc.relation.urihttps://doi.org/10.1175/JTECH-D-15-0226.1
dc.subjectSea surface temperatureen_US
dc.subjectCirrus cloudsen_US
dc.subjectLidars/Lidar observationsen_US
dc.subjectRemote sensingen_US
dc.subjectSatellite observationsen_US
dc.titleEstimating infrared radiometric satellite sea surface temperature retrieval cold biases in the tropics due to unscreened optically thin cirrus cloudsen_US
dc.typeArticle
dc.description.embargo2017-08-06en_US
dc.identifier.doi10.1175/JTECH-D-15-0226.1


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