NOAA ACSPO v2.70 Himawari-8 AHI L2P SST
Description Himawari-8 (H08) was launched on 7 Oct 2014 into its nominal position at 140.7E and declared operational on 7 Jul 2015. The AHI (largely identical to GOES-R/ABI) is a 16 channel sensor, of which five (3.9, 8.4, 10.3, 11.2, and 12.3 um) are suitable for SST. From an altitude 35,800km, H08 maps SST with spatial resolution 2km at nadir with a 10min temporal sampling. ACSPO processes every 10min FD data, identifies good quality ocean pixels (Petrenko et al., 2010) and derives SST using the four-band (8.4, 10.3, 11.2 and 12.3um) Non-Linear SST (NLSST) regression algorithm (Petrenko et al., 2014), trained against in situ SSTs from drifting and tropical mooring buoys in the NOAA iQuam system https://www.star.nesdis.noaa.gov/socd/sst/iquam . The 10min data are subsequently collated in time, to produce 1hr L2P product, with improved coverage, and reduced cloud leakages and image noise. The L2P is reported in NetCDF4 GHRSST Data Specification v2 (GDS2) format, 24 granules per day, with a total data volume 0.6GB/day. Pixel earth locations are not reported in the granules, as they remain unchanged from granule to granule. Those can be obtained using a flat lat/lon file or a Python script available at https://www.star.nesdis.noaa.gov/pub/socd4/coastwatch/sst/nrt/ahi/nav/ . Per GDS2 specifications, two additional Sensor-Specific Error Statistics layers (SSES bias and standard deviation) are reported in each pixel (Petrenko et al., 2016). The product is validated against quality controlled in situ data from iQuam https://www.star.nesdis.noaa.gov/socd/sst/iquam using the NOAA SQUAM system https://www.star.nesdis.noaa.gov/socd/sst/squam . Quality of SST imagery and clear-sky mask are evaluated in the NOAA ARMS system https://www.star.nesdis.noaa.gov/socd/sst/arms . A reduced size (0.2GB/day), 0.02deg equal-angle gridded ACSPO L3C product is available at https://podaac.jpl.nasa.gov/dataset/AHI_H08-STAR-L3C-v2.70 .
Données et ressources
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PODAAC OpenSearchHTML Ouvrir
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Clear-Sky Mask for the Advanced Clear-Sky Processor for OceansHTML Ouvrir
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Evaluation and selection of SST regression algorithms for JPSS VIIRS:Selection of SST Regression AlgorithmsHTML Ouvrir
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Sensor-Specific Error Statistics for SST in the Advanced Clear-Sky Processor for OceansHTML Ouvrir
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Optimization of Sensitivity of GOES-16 ABI Sea Surface Temperature by Matching Satellite Observations with L4 AnalysisHTML Ouvrir
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See "Documentation" tab atHTML Ouvrir
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Informations supplémentaires
| Étendue temporelle | 2019-10-16 – 2022-12-13 |
|---|---|
| Date (creation) | 2020-04-01 |
| Date (revision) | 2020-04-01 |
| Date (publication) | 2020-04-01 |
| Statut | completed |
| Fréquence de mise à jour | asNeeded |
| Langue des métadonnées | en |
| Licence | Creative Commons Attribution 4.0 |
| Métadonnées sources | ISO 19115 XML |
| Dernière mise à jour | 2026-11-04 |
| Créé | 2026-11-04 |
| API | package_show |