ACSPO Global SST from MODIS
The MODIS SST data are produced from Terra and Aqua satellites using the NOAA Advanced Clear-Sky Processor for Ocean (ACSPO) v2.50 enterprise system (Ignatov et al., 2016). Only near-real time (NRT) data are produced at STAR, with a ~3days latency. The data are not archived and only available at this Coast watch page as a 2week rotated buffer. MODIS data can reprocessed in STAR, for the full Terra and Aqua missions, if there is users' interest.
The data are reported in 5min granules in GHRSST Data Specifications v2 (GDS2) format, in swath projection (L2P) and 0.02° gridded L3U (U=uncollated), 288 granules per day, with a total data volume of 8GB/day for L2P and 0.4GB/day for L3U, respectively.
ACSPO retrievals are made in full MODIS swath (~2,300 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 3.7, 8.6, 11, and 12 µm bands 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; 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).
|Platform/Sensor||Aqua / MODIS, Terra / MODIS|
|Measurement/Products||Measurement Oceans > Sea Surface Temperature > Sub-skin SST|
|Short Name||ACSPO_MODIS_NRT_L2P and ACSPO_MODIS_NRT_L3U|
|Processing Level||L2P and L3U|
|Temporal Coverage||2-week rotated|
|Resolution||L2P: 1km @Nadir; ~6km @swath edge
|Projection||L2P: Satellite native swath (WGS84)
L3U: Equal-grid 0.02°
|Swath Width||~2,300 km|
|Temporal Repeat||Every 1 to 2 days|
|Orbital Period||101 Minutes|
|Orbit|| Sun-synchronous altitude ~705km
Terra: mid-AM stable @10:30am/pm
Aqua: PM stable @1:30am/pm
Creator: NOAA STAR
Release Place: College Park, MD, USA
Release Date: 2017-Aug-30
|Keywords||NOAA, MODIS, ACSPO, SST, NRT, L2P, L3U|
[Please acknowledge "NOAA CoastWatch/OceanWatch" when you use data from our site and cite the particular dataset DOI as appropriate.]
- 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)
The ACSPO MODIS SST 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.
(♦ - non-government website)