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    Estimating infrared radiometric satellite sea surface temperature retrieval cold biases in the tropics due to unscreened optically thin cirrus clouds

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    jtech-d-15-0226.1.pdf (1.497Mb)
    Date
    2017-02-06
    Author
    Marquis, Jared W.  Concept link
    Bogdanoff, Alec S.  Concept link
    Campbell, James R.  Concept link
    Cummings, James A.  Concept link
    Westphal, Douglas L.  Concept link
    Smith, Nathaniel J.  Concept link
    Zhang, Jianglong  Concept link
    Metadata
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    Citable URI
    https://hdl.handle.net/1912/8888
    As published
    https://doi.org/10.1175/JTECH-D-15-0226.1
    DOI
    10.1175/JTECH-D-15-0226.1
    Keyword
     Sea surface temperature; Cirrus clouds; Lidars/Lidar observations; Remote sensing; Satellite observations 
    Abstract
    Passive 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.
    Description
    Author 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.
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    Suggested Citation
    Journal of Atmospheric and Oceanic Technology 34 (2017): 355-373
     

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