These VIIRS SST data are produced using the NOAA Advanced Clear-Sky Processor for Ocean (ACSPO) SST system, from the afternoon NPP, N20 and N21 satellites, in two formats: L2P and L3U (uncollated). The data are reported in 10 min granule files in NetCDF4 format, compliant with the GHRSST Data Specifications v2 (GDS2). For each satelite, there are 144 granules per 24 hr interval, with a total data volume of ~7.1 GB/day for L2P, and ~0.4 GB/day for L3U.
These VIIRS SST data are produced using the NOAA Advanced Clear-Sky Processor for Ocean (ACSPO) SST system, from the afternoon NPP and N20 satellites, in two formats: L2P and L3U (uncollated). The data are reported in 10 min granule files in NetCDF4 format, compliant with the GHRSST Data Specifications v2 (GDS2). There are 144 granules per 24 hour interval, with a total data volume of ~7 GB/day for L2P, and ~0.5 GB/day for L3U (per-sensor) .
The L2P/L3U SST data is produced at NOAA STAR using the official enterprise ACSPO algorithms V2.80. A 2-week rotated buffer of the NRT data is provided here on Coast Watch, whereas the full data set is available from PO.DAAC and NOAA NCEI (see links under "Data Access"). Note that the NCEI archive has not been backfilled with ACSPO V2.80 and therefore contains SST data from earlier ACSPO versions, while PO.DAAC contains the full V2.80 archive. A complete archive of ACSPO V2.80 data is available on the Coast Watch archive for L3U data only due to large L2P data volume.
ACSPO retrievals are made in full VIIRS swath (~3,000 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. The NOAA SST team worked with the NOAA calibration team and used an up-to-date converter from RDR (L0) to SDR (L1b), to address quarterly spikes in day-time SST bias which coincide with quarterly warm-up-cool-down calibration exercises onboard NPP/N20. The algorithms used in VIIRS reanalysis version 3 (RAN3) are documented in Jonasson et al., 2022.
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, among others: 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); GFS/MERRA wind speed; and ACSPO SST minus reference (Canadian Met Centre L4 SST).
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 SSTs in those pixels.
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 systems, and brightness temperatures are monitored in MICROS (Liang and Ignatov, 2011).
|Temporal Start Date||
February 1, 2012
NRT NPP L2P/L3U: 1 Feb 2012 to present
Sea Surface Temperature
Sea Surface Temperature - Polar-orbiting
0 Hours <= 24 Hours (NRT)
24+ hours (Delayed)
NRT: <6 hours
|Spatial Resolution Groups||
100m < 2km
|Spatial Resolution Details||
- Jonasson, O.; Ignatov, A.; Pryamitsyn, V.; Petrenko, B.; Kihai, Y. JPSS VIIRS SST Reanalysis Version 3. Remote Sens. 2022, 14, 3476. doi:10.3390/rs14143476
- 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
The ACSPO NPP/N20/N21 VIIRS RAN3 data set is 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.