SeaWiFS Ocean Color Reprocessing 2018.0
Introduction
The Ocean Biology Processing Group (OBPG) completed a full-mission ocean color reprocessing of the data from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS). This reprocessing is part of a multi-mission effort to update instrument calibrations and vicarious calibrations only. Sensor-independent changes are detailed in the R2018.0 Ocean Color Reprocessing General Description. Here we describe the SeaWiFS sensor-specific details of the reprocessing, and provide an assessment of data quality and impact relative to the previous R2014 SeaWiFS reprocessing.
Sensor-specific Processing Details
Source Data
As in previous reprocessings, R2018.0 starts from the SeaWiFS Level-1A files. The Level-1A source files are unchanged for this reprocessing.
Instrument Calibration
The SeaWiFS instrument calibration is unchanged. The calibration was significantly improved for the R2014 reprocessing, and no additional updates were needed for this R2018 reprocessing.
Vicarious_Calibration
The OBPG applies an additional vicarious calibration to VIIRS during Level-2 processing (Franz et al. 2007). The 865nm band is assumed to be correctly calibrated based on prelaunch measurements and absolute calibration to the solar diffuser. The 765nm band is then adjusted using match-ups from the South Pacific Gyre, to force the aerosol type retrievals to match, on average, the aerosol type observed at the Tahiti AERONET site. The calibration of visible bands (412nm to 678nm) is then adjusted to produce retrievals that match, on average, measurements from the Marine Optical Buoy (MOBY) near Lanai Hawaii.
A major change in this reprocessing is to make use of the updated MOBY time-series, which was reprocessed by the MOBY Operations Team (MOT) to incorporate advancements in MOBY instrument calibration and characterization as discussed in the R2018 General Description. Note that the, since the instrument calibration and atmospheric correction algorithm are unchanged, the NIR calibration is also unchanged from the previous R2014.0 reprocessing.
The updated vicarious gains for this reprocessing are reported in the table below.
| Wavelength (nm) | 412 | 443 | 490 | 510 | 555 | 670 | 765 | 865 |
|---|---|---|---|---|---|---|---|---|
| Gain | 1.0014 | 0.9925 | 0.9820 | 0.9864 | 0.9948 | 0.9648 | 0.9580 | 1.0 |
Level-2 Processing
The product algorithms, product suites, and data formats are identical to those employed in the R2014.0 reprocessing.
Impact and Quality Assessment
Impact of Reprocessing on Timeseries
To assess the impact of this R2018.0 reprocessing relative to the previous R2014 reprocessing, a comparative timeseries analysis was performed (see Franz 2009 for details on the evaluation approach). The impact of all calibration, algorithm, and ancillary data changes on remote sensing reflectance is shown in this comparison of the mean Rrs for various globally-distributed geographic subsets. In these plots, ST131 is the R2018 reprocessing configuration, and ST128 is the R2014 configuration. In general, the updated vicarious calibration results in a spectrally correlated bias shift in all bands, of order -1% at 670nm to +3% at 412nm, on the global deep-water mean (largest in blue), with resulting decrease in chlorophyll of order 3%. See summary tables here.
Comparison with In Situ Measurements
Validation of the remote sensing reflectance (Rrs) and chlorophyll retrievals was performed relative to all available in situ match-ups from SeaBASS and the Aerosol Robotic Network - Ocean Color (AERONET-OC), where only AERONET-OC Rrs data of quality level 2 were considered. Statistical analysis and scatter plots of the satellite to in situ match-ups are provided below, with results from R2014 also shown for reference. Overall, the impact of the change to the vicarious calibration was minimal on the validation results. The bias and error for Rrs are nearly unchanged, except for Rrs412 where the negative bias in R2014 is now a slightly positive bias for R2018 (-0.00024 to 0.00012). The results for chlorophyll show that the R2018 demonstrates improved bias with absolute error remaining unchanged.
Rrs Validation Statistics for R2014 Reprocessing
Rrs Validation Statistics for R2018 Reprocessing
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References
Franz, B. A., S. W. Bailey, P. J. Werdell and C. R. McClain (2007). Sensor-independent Approach to the Vicarious Calibration of Satellite Ocean Color Radiometry. Applied Optics, 46: (22) 5068-5082.
Franz, B. A. (2009). Methods for Assessing the Quality and Consistency of Ocean Color Products.