The PO.DAAC is pleased to announce the public release of the NOAA/STAR GHRSST global 0.02-deg L3S-LEO_AM v2.80 dataset produced from three Low Earth Orbiting (LEO) Metop-FG satellites: Metop-A, -B and -C . The Metop-FG satellite program was jointly established by the European Space Agency (ESA) and the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT). The US National Oceanic and Atmospheric Administration (NOAA) under the joint NOAA/EUMETSAT Initial Joint Polar System Agreement, has contributed three Advanced Very High Resolution Radiometer (AVHRR) sensors capable of collecting and transmitting to the ground sensor data in the Full Resolution Area Coverage (FRAC; 1km/nadir) format.
The L3S LEO_AM (L3S: Level 3 “super-collated”) aggregates three individual global L3U SST datasets (10.5067/GHMTA-3US28, 10.5067/GHMTB-3US28, 10.5067/GHMTC-3US28). The dataset consists of two daily files, one daytime and one nighttime (nominal Metop local equator crossing times around 09:30/21:30, respectively), in netCDF4 format compliant with the GHRSST Data Specification version 2 (GDS2). The L3S-LEO_AM data are validated against quality controlled in situ data, provided by the NOAA in situ SST Quality Monitor system (iQuam; Xu and Ignatov, 2014), and monitored in another NOAA system, SST Quality Monitor (SQUAM; Dash et al, 2010). The entire data record extends from Dec 2006 to present with an approximate 6-hour latency for the Near Real Time (NRT) product, which is replaced by the Re-Analysis (RAN) SST product two months later; the RAN data is characterized by improved stability, accurate retrieval performance and improved coverage over the ocean.
More information on the Group for High-Resolution Sea Surface Temperature (GHRSST) Project, as well as other GHRSST datasets, can be found here. The GHRSST L3S LEO/AM v2.80 dataset is accessible in NASA’s Earthdata Cloud infrastructure through AWS, including both HTTPS access and direct S3 access in the “us-west-2” AWS region and is further described and discoverable via the PO.DAAC and NASA Earthdata Search dataset information pages with the following DOI (Digital Object Identifier).
O. Jonasson, I. Gladkova, A. Ignatov, Y. Kihai, 2019: Algorithmic improvements and consistency checks of the NOAA global gridded super-collated SSTs from low Earth orbiting satellites ACSPO L3S-LEO. SPIE Defense + Commercial Sensing 2021, 11752, doi.org/10.1117/12.2585819
O. Jonasson, I. Gladkova; A. Ignatov, Y. Kihai. Progress with development of global gridded super-collated SST products from low Earth orbiting satellites (L3S-LEO) at NOAA. SPIE Defense + Commercial Sensing 2020, 11420, doi.org/10.1117/12.2551819
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. Grossberg, 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/
Xu, F. and 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/
Related PO.DAAC Animation: https://podaac.jpl.nasa.gov/animations/Global-SST-NOAA/STAR-with-aggregated-MetOp-A/B/C-AVHRR-measurements
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