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Evaluation of the NOAA AVHRR GAC RAN2 SST dataset



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  • Journal Title:
    Ocean Sensing and Monitoring XIV
  • Personal Author:
  • NOAA Program & Office:
    NESDIS (National Environmental Satellite, Data, and Information Service)
  • Description:
    The RAN2 sea surface temperature (SST) dataset has been created under the NOAA AVHRR GAC SST Reanalysis 2 (RAN2) project from 40+ years of 4 km Global Area Coverage (GAC) data of the Advanced Very High-Resolution Radiometers (AVHRR/2s and /3s) flown onboard ten NOAA satellites (N07/09/11/12/14/15/16/17/18/19). The data were reprocessed with the NOAA Advanced Clear Sky Processor for Ocean (ACSPO) enterprise SST system. The RAN2 reports two SSTs in the full ~3,000 km AVHRR swath: ‘subskin’ (highly sensitive to true skin SST, while being anchored to in situ depth SST) and ‘depth’ (a closer proxy for in situ data, but less sensitive to true skin SST). Long-term orbital and sensor changes were minimized by daily recalculation of regression coefficients using matchups with drifters and tropical moored buoys, (D+TM), collected within limited time windows centered at the processed day. For N07/09, (D+TM) matchups were sparse and supplemented by ships. The adverse effects of nighttime Sun impingements on the sensor were mitigated by recalculating the AVHRR L1b calibration coefficients, while similar effects of stray light in Earth view were flagged and excluded. Massive cold SST outliers caused by atmospheric contamination following major volcanic eruptions (El Chichon in 1982, and Mt Pinatubo and Mt Hudson in 1991) were filtered out by more conservative cloud screening with the modified ACSPO clear-sky mask. This paper evaluates the performance of the RAN2 relative to the two others available AVHRR GAC SST datasets, NOAA Pathfinder v5.3 (PF) and ESA Climate Change Initiative v2.1 (CCI).
  • Source:
    Ocean Sensing and Monitoring XIV (2022)
  • DOI:
  • Format:
    pdf
  • Publisher:
    SPIE
  • Document Type:
    Journal Article
  • Rights Information:
    Other
  • Compliance:
    Library
  • Main Document Checksum:
    urn:sha-512:1a97b2b247dc06f54ba67c2d4e2d5795244144be0463b9194be2f764f65f65ad568ee97180b9b16606ec970f8ff3126beafbd9543e14215a6d0b9661c1bd7c24
  • Download URL:
  • File Type:
    Filetype[PDF - 5.76 MB ]
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