NOAA MSL12 Ocean Color, near real time, VIIRS multi-sensor SNPP + NOAA-20 daily merge

VIIRS Ocean Color multi-sensor (SNPP + NOAA-20) daily merge (Level 3 composite) is produced from the NOAA Multi-Sensor Level 1 to Level 2 processing system (MSL12) near real time processing stream by the NOAA ocean color science team.  NOAA CoastWatch converts files to NetCDF and serves them here.

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    Global Map projection displaying chlorophyll-a concentration

    Ocean Color Level 3 VIIRS multi-sensor, daily, global, merge is produced through NOAA Multi-Sensor Level 1 to Level 2 processing system (MSL12).  Parameters from this product suite include chlorophyll-a concentration (pictured above for 15 January 2020) and diffuse attenuation coefficients (Kd(490) and Kd(PAR) (not shown). 

    Ocean Color satellite sensors measure visible light at specific wavelengths which leaves the surface of the ocean and arrives at the top of the atmosphere where the sensor is located. From these visible spectral measurements, along with simultaneous measurements in the near infrared (NIR) and the short wave infrared (SWIR) wavelengths, the color of the ocean, or normalized water leaving radiances (nLw), can be calculated. Then, the nLws are used to derive other ocean properties such as the concentration of chlorophyll-a (chlor-a or sometimes chl, which is the green pigment responsible for photosynthesis and therefore an indicator of the amount of phytoplankton biomass in the ocean water) and the coefficient of extinction for downwelling irradiance (Kd(PAR) and Kd(490) which are related to water clarity).

    The ocean color datasets described here are from the Visible and Infrared Imaging Radiometer Suite (VIIRS) sensor aboard the Suomi-NPP satellite (SNPP) which was launched in November 2011 and also aboard the NOAA-20 satellite launched in November 2017.  NOAA ocean color data are processed using NOAA Multi-Sensor Level 1 to Level 2 processing system (MSL12) developed by the NOAA/STAR Ocean Color Team [Wang et al., 2013].

    An excerpt from the¬†EOS¬†article by¬†Mikelsons et al., 2019¬†explains the approach to the Level-3, multi-sensor merged, global, daily data product served here by¬†CoastWatch¬†at ~4 km spatial resolution in NetCDF format.¬† "SNPP and NOAA-20 operate along the same Sun-synchronous polar orbit that crosses the equator at about 13:30 local time‚ÄĒboth satellites travel around Earth from pole to pole in such a way that they observe the same areas at about the same time of day, no matter the season. There is about a 50-minute delay between the paths of NOAA-20 and SNPP, so NOAA-20‚Äôs path runs between two adjacent SNPP orbital paths and vice versa. Thus, the overlap of the spatial coverages in the two VIIRS sensors automatically fills each instrument‚Äôs data gaps [Mikelsons and Wang, 2019]. In addition, ocean color data from the VIIRS SNPP and NOAA-20 have the same spatial and temporal resolution, and these data are processed using the same algorithm and software package (i.e., MSL12). Therefore, the statistics of their ocean color products are very similar, and the data can be merged into a global 9-kilometer resolution data set directly without adjustment [Liu and Wang, 2019]."¬†

    These multi-sensor daily merged products are derived from MSL12 v1.3 for both SNPP plus NOAA-20.  The chlorophyll-a algorithm is OCI [Hu et al., 2012; Wang and Son, 2016].

    Temporal Coverage

    Daily

    Product Families
    Ocean Color
    Measurements
    Chlorophyll-a Concentration
    Diffuse Attenuation Coefficients
    Processing Levels
    Level 3
    Latency Groups
    24+ hours (Delayed)
    Latency Details

    Daily, generally 3-day delay

    Spatial Resolution Groups
    2km+
    Spatial Resolution Details

    4 km

    Data Providers
    NOAA
    NESDIS
    STAR
    CoastWatch
    Spatial Coverage

    Global

    Description

    180W - 180E
    90N - 90S

    MSL12

    Description

    Multi-Sensor Level-1 to Level-2 (MSL12) Ocean Color Data Processing System

    NOAA

    Description

    National Oceanic and Atmospheric Administration - 17 / 18 / 19 / 20 / 21

    Platform Type
    Low Earth Orbit Satellite (LEO)
    Instruments
    Organizations
    NASA
    NOAA
    Orbital Altitude
    834 km
    Equatorial Crossing Times
    13:25 asc

    SNPP

    Description

    Suomi National Polar-orbiting Partnership

    Platform Type
    Low Earth Orbit Satellite (LEO)
    Instruments
    Organizations
    NASA
    NOAA
    Orbital Altitude
    833 km
    Equatorial Crossing Times
    13:25 asc

    VIIRS

    Description

    Visible Infrared Imaging Radiometer Suite

    Platforms
    Instrument Types
    Imager
    Organizations
    NASA

    Wang, M., L. Jiang, K. Mikelsons, X. Liu, "Satellite-derived global chlorophyll-a anomaly products", International Journal of Applied Earth Observation and Geoinformation, Volume 97,
    102288 (2021), doi:10.1016/j.jag.2020.102288

    Liu, X. and M. Wang, "Filling the gaps in ocean maps", EOS, 100 (2019).  doi:10.1029/2019EO136548

    Liu, X., and M. Wang (2019), Filling the gaps of missing data in the merged VIIRS SNPP/NOAA-20 ocean color product using the DINEOF method, Remote Sens., 11, 178, doi:10.3390/rs11020178.

    Mikelsons, K., and M. Wang (2019), Optimal satellite orbit configuration for global ocean color product coverage,¬†Opt. Express,¬†27, A445‚ÄďA457,¬†doi:10.1364/OE.27.00A445.

    Mikelsons, K., and M. Wang (2018), Interactive online maps make satellite ocean data accessible, Eos Trans. AGU, 99, doi:10.1029/2018EO096563.

    Liu, X. and M. Wang, "Gap filling of missing data for VIIRS global ocean color product using the DINEOF method", IEEE Trans. Geosci. Remote Sens., 56, 4464-4476 (2018). doi:10.1109/TGRS.2018.2820423

    Wang, M. and S. Son, "VIIRS-derived chlorophyll-a using the ocean color index method", Remote Sens. Environ., 182, 141-149 (2016). doi:10.1016/j.rse.2016.05.001

    Wang, M., et al. (2013), Impact of VIIRS SDR performance on ocean color products,¬†J. Geophys. Res. Atmos.,¬†118, 10,347‚Äď10,360,¬†doi:10.1002/jgrd.50793.

    Hu, C., Z. Lee, B.A. Franz, (2012) "Chlorophyll a algorithms for oligotrophic oceans: A novel approach based on three-band reflectance difference" Journal of Geophysical Research, 117 (2012) (C01011,doi:01010.01029/02011JC007395)

    Alvera-Azcarate, A., et al. (2005), Reconstruction of incomplete oceanographic data sets using empirical orthogonal functions: Application to the Adriatic Sea,¬†Ocean Model.,¬†9, 325‚Äď346,¬†doi:10.1016/j.ocemod.2004.08.001.

    Beckers, J., and M. Rixen (2003), EOF calculations and data filling from incomplete oceanographic data sets,¬†J. Atmos. Oceanic Technol.,¬†20, 1,839‚Äď1,856,¬†doi:10.1175/1520-0426(2003)020<1839:ECADFF>2.0.CO;2.

    Algorithm Theoretical Basis Document (ATBD)

    Wang, M., X. Liu, L. Jiang and S. Son, "The VIIRS Ocean Color Products", Algorithm Theoretical Basis Document Version 1.0, 68 pp., June 2017.

    For more MSL12 processing documentation, please go to documentation tab here.

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