NOAA CoastWatch East Coast Node
Data Types Info Data Types: SST         - AVHRR                 - AVHRR-VIIRS                 - Geo-Polar Blended                 - PODAAC MUR Chl-a       - MODIS                 - OLCI (HiRes)                 - VIIRS Clarity     - K490 (MODIS)                 - K490 (MODIS HiRes)                 - K490 (OLCI HiRes)                 - K490 (VIIRS)                 - Rrs667 (MODIS)                 - Rrs672 (VIIRS)                 - TSM (MODIS HiRes)                 - TSM (OLCI HiRes)                 - TSM (VIIRS HiRes) True Color (VIIRS)
Data Access Info HTTP Rolling Archive FTP Time Series Archive
Region Info Regions: U.S. East Coast North East Coast Gulf of Maine Massachusetts & RI Bays Mid-Atlantic Coast NY-NJ Bight & Long Island Sound Chesapeake & Delaware Bays South East Coast Carolina Coast Florida - Georgia Coast
CoastWatch Utilities Time Series Tool ERDDAP MGET Experimental Algal Bloom Monitor

 

NASA PODAAC Multiscale Ultrahigh Resolution (MUR)
Sea Surface Temperature

NASA's Physical Oceanography Distributed Active Archive Center (PODAAC) generates the Multiscale Ultrahigh Resolution sea surface temperature (SST) product (version 4.1) that combines data from all current microwave and infrared polar-orbiting and geostationary satellites, including U.S. satellites and those of international partners such as Japan and Europe.

The satellite instruments vary on a daily basis depending on availability, but may include the following, among others:

  • Advanced Microwave Scanning Radiometer-2 (AMSR-2) on Japan's GCOM-W1 satellite
  • Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA's Terra and Aqua satellites
  • WindSat on the U.S. Navy's Coriolis satellite
  • Advanced Very High Resolution Radiometer (AVHRR) on NOAA's POES satellites and Europe's MetOp satellites

Nighttime skin and subskin SST observations from the available satellite instruments are blended (analyzed) using an optimal interpolation approach, called multi-resolution variational analysis (MRVA). The analysis technique includes in-situ SST observations from the NOAA iQuam project. As with data assimilation approaches, the in-situ SST observations are used in a bias correction to "nudge" the satellite SST's in the direction of the in-situ SST's for a more accurate analysis product. The number of included satellite instruments, and the analysis technique, allows for a daily, cloud-free, global product on a 0.01 degree grid (approximately 1 km).

The multi-resolution variational analysis method is based on wavelet decomposition. Its multi-scale design allows interpolation of the satellite pixel data at an optimal resolution for each data set, which is particularly useful for combining data sets from sensors with drastically different resolutions.

Near real-time SST data are generated by PODAAC with a 2-day delay, and retrospective science-quality SST data are generated with a 4-day delay.

NOAA CoastWatch East Coast Node obtains both the near real-time SST and retrospective science-quality SST from PODAAC. East Coast Node replaces the near real-time SST data files with the science-quality SST data files when they become available. Further, East Coast Node subsets the global data for the U.S. coasts. Currently, only U.S. east coast data files are made available through East Coast Node. In addition to daily files, monthly and annual mean composite files are available. East Coast Node distributes the entire time series of MUR SST data, from June 2002 to the present.

PODAAC MUR SST example, U.S. East
Coast, July 30, 2015
Figure: PODAAC MUR SST for July 30, 2015
Compare with July 30, 2015 image of NOAA Geo-Polar Blended SST and AVHRR SST Daily Composite

Validation of MUR SST was conducted by East Coast Node for Chesapeake Bay.

The Multiscale Ultrahigh Resolution SST project is funded by the NASA MEaSUREs Program. More information may be found at the NASA Jet Propulsion Laboratory MUR project page.

References:

Chin, T.M., Vazquez-Cuervo, J., and Armstrong, E.M. 2017. A multi-scale high-resolution analysis of global sea surface temperature. Remote Sensing of Environment, vol. 200, pp. 154-169, Oct 2017. doi.org/10.1016/j.rse.2017.07.029

Chin, T.M., J. Vazquez, and E. Armstrong. 2013. Algorithm Theorectical Basis Document: A multi-scale, high-resolution analysis of global sea surface temperature, Version 1.3. NASA Jet Propulsion Laboratory, Physical Oceanography Distributed Active Archive Center.


Data Access
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