Selecting a first-guess SST as input to ACSPO

Korak Saha; Alexander Ignatov; XingMing Liang; Prasanjit Dash

doi:10.1117/12.918093

11 June 2012 Selecting a first-guess SST as input to ACSPO

Korak Saha, Alexander Ignatov, XingMing Liang, Prasanjit Dash

Proceedings Volume 8372, Ocean Sensing and Monitoring IV; 83720L (2012) https://doi.org/10.1117/12.918093
Event: SPIE Defense, Security, and Sensing, 2012, Baltimore, Maryland, United States

Abstract

Advanced Clear-Sky Processor for Oceans (ACSPO) is a National Environmental Satellite, Data, and Information Service (NESDIS) clear-sky radiance and sea surface temperature (SST) retrieval system. It provides clearsky top of the atmosphere (TOA) observed brightness temperatures (BT) in AVHRR channels 3B(3.7 μm), 4(11 μm), and 5(12 μm) and SST retrieved from these BTs, along with their modeled values calculated with the fast community radiative transfer model (CRTM), using first-guess level 4 (L4) SST (Reynolds daily optimum interpolation SST; OISST) and upper air (NCEP-GFS) fields as inputs. The simulated first-guess BTs are used for accurate ACSPO clearsky mask estimation, physical SST retrievals, monitoring sensor performance, and CRTM validation. Model minus observation (M-O) biases are continuously monitored using the near-real time online-tool, Monitoring of IR Clear-sky radiances over Oceans for SST (MICROS; www.star.nesdis.noaa.gov/sod/sst/micros/). This study tests eleven different gap free L4 SSTs as potential first-guess input fields in ACSPO to improve accuracies of simulated BTs. These L4 SST fields are being cross-compared and validated with quality controlled in situ data in L4-SST Quality Monitor (SQUAM; http://www.star.nesdis.noaa.gov/sod/sst/squam/L4/). In this paper, L4 SSTs are evaluated by comparing them with the ACSPO L2 SST product. Three metrics including the global spatial variance of the L4-L2 biases, and their temporal stability along with the corresponding double-differences, are used to test the performance of these L4 SSTs. It is generally observed that the Group for High-Resolution SST (GHRSST) Multi-Product Ensemble (GMPE), Canadian Meteorological Centre (CMC 0.2°) and UKMO OSTIA provide more consistent first-guess SST fields for use in ACSPO.

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Korak Saha, Alexander Ignatov, XingMing Liang, and Prasanjit Dash "Selecting a first-guess SST as input to ACSPO", Proc. SPIE 8372, Ocean Sensing and Monitoring IV, 83720L (11 June 2012); https://doi.org/10.1117/12.918093

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KEYWORDS

Satellites

Atmospheric modeling

Error analysis

Radiative transfer

Clouds

In situ remote sensing

Satellite navigation systems

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