Selecting a first-guess sea surface temperature field as input to forward radiative transfer models

Authors

  • Korak Saha,

    Corresponding author
    1. Center for Satellite Application and Research (STAR), NOAA/NESDIS, College Park, Maryland, USA
    2. Cooperative Institute for Research in the Atmospheres (CIRA), Colorado State University, Fort Collins, Colorado, USA
    • Corresponding author: K. Saha, Center for Satellite Application and Research (STAR), NOAA/NESDIS, College Park, MD 20740, USA (korak.saha@noaa.gov).

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  • Alexander Ignatov,

    1. Center for Satellite Application and Research (STAR), NOAA/NESDIS, College Park, Maryland, USA
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  • Xing Ming Liang,

    1. Center for Satellite Application and Research (STAR), NOAA/NESDIS, College Park, Maryland, USA
    2. Cooperative Institute for Research in the Atmospheres (CIRA), Colorado State University, Fort Collins, Colorado, USA
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  • Prasanjit Dash

    1. Center for Satellite Application and Research (STAR), NOAA/NESDIS, College Park, Maryland, USA
    2. Cooperative Institute for Research in the Atmospheres (CIRA), Colorado State University, Fort Collins, Colorado, USA
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Abstract

[1] Advanced Clear-Sky Processor for Oceans (ACSPO), developed at National Environmental Satellite, Data, and Information Service, reports observed top-of-atmosphere clear-sky brightness temperatures (BT) in AVHRR channels 3B (3.7), 4 (11), and 5 (12μm) along with the sea surface temperatures (SST) retrieved from these BTs as a level 2 (L2) product. Additionally, ACSPO provides the corresponding BTs simulated with Community Radiative Transfer Model (CRTM), using Reynolds daily Level 4 (L4) optimum interpolation SST (OISST) and NCEP-GFS profiles as inputs. Accuracy of simulated BTs is critical for ACSPO functionalities, including detecting clouds, retrieving physical SSTs, monitoring sensor performance, and validating CRTM. This paper tests 11 gap-free gridded L4 SSTs for their potential use as first-guess fields in ACSPO to improve accuracy of simulated BTs. As a first step toward the objective, this study checks for consistency between various L4 products and ACSPO L2 SSTs. This SST consistency was shown earlier to be representative of, and equivalent to, the consistency between measured and simulated BTs, thus avoiding expensive CRTM calculations. The metrics employed in L4 comparisons include the global spatial L4-L2 SST biases and variances and their temporal stability. Also, the effect of L4 fields on the corresponding satellite-to-satellite consistency (calculated as L2-L2 double differences) is examined. Several L4 products, including the GHRSST Multi-Product Ensemble and Canadian Meteorological Centre analysis (CMC-0.2°), show better consistency with ACSPO L2 SST and will be explored in the future versions of ACSPO.

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