Bureau of Meteorology Reprocessed Sea Surface Temperature (SST) Products

The Bureau of Meteorology (BoM) produces operational Integrated Marine Observing System (IMOS) satellite SST products in the International Group for High Resolution SST (GHRSST: www.ghrsst.org) "GDS2.0" file formats. The products provided range from single swath (or scene) SST data from polar-orbiting or geostationary satellites, all the way through to high level processed data incorporating data from multiple satellite sensors, and include ancillary input from a variety of other sources(e.g., surface wind speeds, sea ice concentration, and previous SST analysis data). Several satellites provide Sea Surface Temperature (SST) data. BoM produces reprocessed SST products using infrared data from Geostationary Himawari-8 and polar orbiters, NOAA-11,12,14,15,16,17,18,19,20, MetOp-A, MetOp-B, MetOp-C and Suomi-NPP VIIRS. These SST products are available over two different domains, IMOS continental domain (70E to 190E, 70S to 20N) and Southern Ocean domain (2.5E to 202.5E, 77.5S to 27.5S) on the IMOS 0.02o x 0.02o grid. For each sensor, following products may be available: L2P (geolocated, native resolution of sensor, one sub-directory per sensor. L3U (swath, gridded, single sensor), one sub-directory per sensor. L3C (multiple swath, gridded, single sensor), available for different time periods:1 day day-time only and night-time only, 1 hour data and 4 hour data, one sub-directory per sensor. L3S (multiple sensor, gridded), available for different time periods: 1 day, 3 days, 6 days, 14 days and 1 month for daytime only, night-time only and day and night (24 hour) scenarios. These SST products are used as input for applications such as IMOS OceanCurrent, and the BoM ReefTemp Next Generation coral bleaching nowcasting service, and provide useful insight into the study of marine heatwaves and ocean upwelling in near-coastal regions. Products in the fv02(reprocessed) data stream have been gap-filled and processed on Gadi, using the highest quality input data available. Reprocessing is typically done using improved algorithms and methods and additional input data that became available in delayed mode. Gap filling and (re)processing occurs to ensure the data is of the highest quality and to enhance data coverage.