The data comprise near-real time (NRT) 2-week rotated buffer (produced by OSPO from several sensors, currently including NOAA-18 and -19, and Metop-A and -B, with ~4hrs latency) and delayed-mode (4-days latency) science quality Reanalysis (RAN; produced at STAR). RAN1 dataset is produced from AVHRR/3s using the NOAA Advanced Clear-Sky Processor for Ocean (ACSPO) v2.40 enterprise system, from 3 afternoon (NOAA-16, -18, -19) and 2 mid-morning satellites (NOAA-17, MetOp-A), two satellites at a time, from 30 Aug 2002 to present. The data are documented in (Ignatov et al., 2016). Work is underway to extend the period covered by RAN1 using AVHRR/2s, initially back to 1996 and eventually to 1981.
The data are reported in hourly granule files in GHRSST Data Specifications v2 (GDS2) format, in swath projection (L2P) and 0.02° gridded L3U (U=uncollated), 24 granules per day, with a total data volume of 0.8GB/day for L2P and 0.2GB/day for L3U, respectively.
ACSPO retrievals are made in full AVHRR swath (~2,800 km). For data assimilation applications (such as production of L4 analyses, especially those that blend satellite and in situ data), correction for the Sensor-Specific Error Statistics (SSES; reported in ACSPO files; Petrenko et al., 2016) biases is strongly recommended.
In each valid water pixel (defined as ocean, sea, lake or river, up to 5km inland; note that in "invalid" pixels, defined as those with >5km inland, fill values are reported), the following layers are reported in both L2P and L3U: SSTs derived using multi-channel SST (MCSST; night) and Non-Linear SST (NLSST; day) algorithms (Petrenko et al., 2014); ACSPO clear-sky mask (ACSM; provided in each pixel as part of l2p_flags; Petrenko et al., 2010); SSES bias and standard deviation (Petrenko et al., 2016); NCEP wind speed; and ACSPO SST minus reference (Canadian Met Centre L4 SST). For L2P, brightness temperatures (BTs) in M12, 15, and 16 are also reported, for those users interested in direct "radiance assimilation" (e.g., NOAA NCEP, NASA GMAO).
Only ACSM "confidently clear" pixels (equivalent to GDS2 "quality level"=5; QLs are also reported for each pixel) should be used. The ACSM also provides day/night, land, ice, twilight, and glint flags. Note that users of ACSPO data have the flexibility to ignore the ACSM, derive their own clear-sky mask, and use BTs and SSTs in those pixels. They may also ignore ACSPO SST, and derive their own SSTs from the original BTs.
Both L2P and L3U SSTs are monitored and validated against in situ data (Xu and Ignatov, 2014) in SQUAM (Dash et al., 2010) and ARMS (Ding et al., 2017) systems, and BTs are monitored in MICROS (Liang and Ignatov, 2011).
Measurement Oceans > Sea Surface Temperature > Sub-skinSST
|Short Name|| |
L2P: ACSPO AVHRR GAC RAN1 L2P
|Sample Filename|| |
|Dataset Type|| |
|Processing Level|| |
L2P and L3U
|Spactial Coverage|| |
|Temporal Coverage|| |
NRT L2P/L3U: 2-week rotated buffer (4hrs latency)
NRT: 4 hours
L2P: 4km @Nadir; ~25km @swath edge
L2P: Satellite native swath (WGS84)
|Swath Width|| |
|Sample Frequency|| |
2 scan lines per 1 second
|Temporal Repeat|| |
|Orbital Period|| |
|Data Provider|| |
Creator: NOAA STAR
NOAA, AVHRR, ACSPO, SST, NRT, RAN1, GAC, L2P, L3U
- Dash, P., A. Ignatov, Y. Kihai & J. Sapper, 2010: The SST Quality Monitor (SQUAM). JTech, 27, 1899-1917, doi:10.1175/2010JTECHO756.1♦, www.star.nesdis.noaa.gov/sod/sst/squam/
- Ding, Y., A. Ignatov, I. Gladkova, M. Crosberg, and C. Chu, 2017: ACSPO Regional Monitor for SST (ARMS). BoM - NOAA SST Workshop, 18-21 April 2017, Melbourne, Australia (presentation), www.star.nesdis.noaa.gov/sod/sst/arms/
- Liang, X. & A. Ignatov, 2011: Monitoring of IR Clear-sky Radiances over Oceans for SST (MICROS). JTech, 28, 1228-1242, doi:10.1175/JTECH-D-10-05023.1♦, www.star.nesdis.noaa.gov/sod/sst/micros/
- Xu, F. & A. Ignatov, 2014: In situ SST Quality Monitor (iQuam). JTech, 31, 164-180, doi:10.1175/JTECH-D-13-00121.1♦, www.star.nesdis.noaa.gov/sod/sst/iquam/
- Petrenko, B., A. Ignatov, Y. Kihai, P. Dash, 2016: Sensor-Specific Error Statistics for SST in the Advanced Clear-Sky Processor for Oceans. JTech, 33, 345-359, doi:10.1175/JTECH-D-15-0166.1♦
- Petrenko, B., A. Ignatov, Y. Kihai, J. Stroup, P. Dash, 2014: Evaluation and Selection of SST Regression Algorithms for JPSS VIIRS. JGR, 119, 4580-4599, doi:10.1002/2013JD020637♦
- Petrenko, B., A. Ignatov, Y. Kihai, and A. Heidinger, 2010: Clear-Sky Mask for ACSPO. JTech, 27, 1609-1623, doi:10.1175/2010JTECHA1413.1♦
(♦ - non-government website)
- Ignatov, A., X. Zhou, B. Petrenko, X. Liang, Y. Kihai, P. Dash, J. Stroup, J. Sapper, & P. DiGiacomo, 2016: AVHRR GAC SST Reanalysis Version 1 (RAN1). Remote Sens., 8(4), 315,doi: 10.3390/rs6040315, www.mdpi.com/2072-4292/8/4/315♦
- The ACSPO AVHRR FRAC data are provided by NOAA STAR. We strongly recommend contacting NOAA SST team led by A. Ignatov before the data are used for any publication or presentation.