CGMS-43-NOAA-WP-23 Coordination Group for Meteorological Satellites - CGMS NOAA Report on Ocean Parameters – Ocean Color Presented to CGMS-43 Working Group 2 session, agenda item 9 Author: Menghua Wang

CGMS-43-NOAA-WP-23 Coordination Group for Meteorological Satellites - CGMS Slide: 2 Introduction The purpose of this paper is to provide an overview of the ocean color products that are now available from VIIRS, including couple new products. VIIRS spatial resolution and swath is enabling new ocean color remote sensing capabilities. Products which will be highlighted are the ocean color suite (examples of global and regional) that is now available from NOAA/STAR (Wang et al., 2013; 2014). The presentation will include description of the STAR end-to-end ocean color data processing capability (including in situ data for Cal/Val activities), data access/accuracy of these products, and application activities promoting the use of these products. NOAA/STAR has developed the capability for the end-to-end satellite ocean color data processing, including Level-0 (or Raw Data Records) to Level-1B (or Sensor Data Records) including sensor on-orbit calibration, Level-1B to ocean color Level-2 (or Environmental Data Records), and Level-2 to global Level-3 (routine daily, 8-day, monthly, and climatology data/images). In addition, we are building Cal/Val capability for the in situ data collection and carried out successfully the first NOAA dedicated VIIRS Cal/Val cruise on November The NOAA VIIRS ocean color data processing system is measurement-based system and can be used for processing other satellite ocean color sensors. We plan to process ocean color data from Sentinel-3 (EUMETSAT) (launch late 2015), GCOM-C (JAXA) (launch in early 2017), etc. Thus, we need to access these data for NOAA users and general ocean community.

CGMS-43-NOAA-WP-23 Coordination Group for Meteorological Satellites - CGMS Slide: 3 Inputs: – VIIRS M1-M7 and the SWIR M8, M10, and M11 bands SDR data – Terrain-corrected geo-location file – Ancillary meteorology and ozone data Operational (Standard) Products (8): – Normalized water-leaving radiance (nL w ’s) at visible bands M1-M5 (Wang et al., 2013) – Chlorophyll-a (Chl-a) concentration (O’Reilly et al., 1998) – Diffuse attenuation coefficient for the downwelling spectral irradiance at the wavelength of 490 nm, K d (490) (Wang et al., 2009) (New) – Diffuse attenuation coefficient of the downwelling photosynthetically available radiation (PAR), K d (PAR) (Son and Wang, 2015) (New) – Level-2 quality flags Experimental Products: – Inherent Optical Properties (IOP-a, IOP-a ph, IOP-a dg, IOP-b b, IOP-b bp ) at VIIRS M2 or other visible bands (M1-M5) from the Quasi-Analytical Algorithm (QAA) (Lee et al., 2002) – Photosynthetically Available Radiation (PAR) (R. Frouin) – Chlorophyll-a from ocean color index (OCI) method (Hu et al., 2012) – Others from users requests  Data quality of ocean color EDR are extremely sensitive to the SDR quality. It requires ~0.1% data accuracy (degradation, band-to-band accuracy…)! Summary of VIIRS Ocean Color EDR Products

CGMS-43-NOAA-WP-23 Coordination Group for Meteorological Satellites - CGMS Slide: 4 End-to-End Ocean Color Data Processing at NOAA/STAR NOAA Ocean Color Team has been developing/building the capability for the End-to- End satellite ocean color data processing including: – Level-0 (or Raw Data Records (RDR)) to Level-1B (or Sensor Data Records (SDR)). – Level-1B (SDR) to ocean color Level-2 (Environmental Data Records (EDR). – Level-2 to global Level-3 (routine daily, 8-day, monthly, and climatology data/images). Support of in situ data collections for VIIRS Cal/Val activities, e.g., MOBY, AERONET-OC sites, NOAA dedicated cruise, etc. On-orbit VIIRS instrument calibration: – J. Sun and M. Wang, “Visible Infrared Imaging Radiometer Suite solar diffuser calibration and its challenges using solar diffuser stability monitor,” Appl. Opt., 53, , – J. Sun and M. Wang, “On-orbit characterization of the VIIRS solar diffuser and solar diffuser screen,” Appl. Opt., 54, , – J. Sun and M. Wang, “VIIRS Reflective Solar Bands On-Orbit Calibration and Performance: A Three- Year Update,” Proc. SPIE 9264, Earth Observing Missions and Sensors: Development, Implementation, and Characterization III, October 13-16, RDR (Level-0) to SDR (Level-1B) data processing: – Sun, J., M. Wang, L. Tan, and L. Jiang, “An efficient approach for VIIRS RDR to SDR data processing,” IEEE Geosci. Remote Sens. Lett., 11, 2037–2041, – L. Tan, M. Wang, J. Sun, and L. Jiang, “VIIRS RDR to SDR Data Processing for Ocean Color EDR,” Proc. SPIE 9261, Ocean Remote Sensing and Monitoring from Space, October 13-16, Ocean Color Data Analysis and Processing System (OCDAPS)—IDL-based VIIRS ocean color data visualization and processing package – Wang, X., X. Liu, L. Jiang, M. Wang, and J. Sun, “VIIRS ocean color data visualization and processing with IDL-based NOAA-SeaDAS”, Proc. SPIE 9261, 8 Nov

CGMS-43-NOAA-WP-23 Coordination Group for Meteorological Satellites - CGMS Slide: 5 Link to composite image page Link to calibration/validation page List of the team publications Website description

CGMS-43-NOAA-WP-23 Coordination Group for Meteorological Satellites - CGMS Slide: 6 Generated using NOAA-MSL12 for VIIRS ocean color data processing Log scale: 0.01 to 64 mg/m 3 VIIRS Climatology Chlorophyll-a Image (April 2012 to October 2014)

CGMS-43-NOAA-WP-23 Coordination Group for Meteorological Satellites - CGMS Slide: 7 Generated using NOAA-MSL12 for VIIRS ocean color data processing VIIRS Climatology K d (490) Image (March 2012 to February 2015) Log scale: 0.01 to 2 m  1

CGMS-43-NOAA-WP-23 Coordination Group for Meteorological Satellites - CGMS Slide: 8 Generated using NOAA-MSL12 for VIIRS ocean color data processing VIIRS Climatology K d (PAR) Image (March 2012 to February 2015) Log scale: 0.01 to 2 m  1

CGMS-43-NOAA-WP-23 Coordination Group for Meteorological Satellites - CGMS Slide: 9 K d (490): Log scale: 0.01 to 2 m  1 Chl-a: Log scale: 0.01 to 64 mg m  3 VIIRS Chl-a and K d (490) Images in Mediterranean Sea (October 2014 to January 2015) NOAA CoastWatch has been providing VIIRS ocean color data to EUMETSAT

CGMS-43-NOAA-WP-23 Coordination Group for Meteorological Satellites - CGMS Slide: 10 VIIRS vs. MOBY (in situ) Comparisons Marine Optical Buoy (MOBY) in situ optics data have been providing critical data set in support of VIIRS calibration and validation activities, including VIIRS Level-1B (SDR) data monitoring for sensor on-orbit calibration.

CGMS-43-NOAA-WP-23 Coordination Group for Meteorological Satellites - CGMS Slide: 11 Dedicated VIIRS Cal/Val Cruise NOAA Ship Nancy Foster Dedicated VIIRS Cal/Val Cruise NOAA Ship Nancy Foster November 2014 Validation Measurements Water-leaving radiance; Chlorophyll- a; Absorption and backscattering coefficients; Bi-directional radiance distribution; Phytoplankton physiology; Carbon; Total suspended matter; Aerosol optical depth, etc. International, Interagency, and Academic Collaborations: 4 US Agencies, EU-JRC, 6 Universities Validation Results  Occupied 23 stations over 10 days  Simultaneous measurements at each station for: 4 profiling radiometers 2 floating radiometers 6 above-water radiometers  Conducted pre- & post- cruise inter-calibrations 11 potential station matchups with VIIRS Cruise Track Pre-cruise inter-calibration results for 5 radiance sensors VIIRS Chlorophyll-a Oct.-Dec VIIRS K d (490) Oct.-Dec. 2014

CGMS-43-NOAA-WP-23 Coordination Group for Meteorological Satellites - CGMS Slide: 12 O CEAN C OLOR T OOLS FOR R EEF M ANAGERS From Coral Reef Watch

CGMS-43-NOAA-WP-23 Coordination Group for Meteorological Satellites - CGMS Slide: 13 Summary VIIRS ocean color products have been routinely produced with some major improvements after the implementation of some important updates, new algorithms, and with vicarious calibrations. In addition, with requests from users, VIIRS now has included couple new products with additional experimental (evaluation) list of products. In general, VIIRS standard ocean color products compared well with in situ data. VIIRS can produce similar ocean color data quality as those from heritage satellite ocean color sensors (e.g., from MODIS-Aqua). We will soon complete VIIRS mission-long ocean color data reprocessing (science quality, i.e., improved SDR, algorithms, and science quality ancillary data). There are several applications using VIIRS ocean color products, and new K d (490) and K d (PAR) data are useful. Our evaluation results show that VIIRS-SNPP is capable of providing high-quality global ocean color products in support of science research and operational applications. VIIRS can provide ocean color data continuity. We have been actively working with other current and future satellite ocean color sensors, e.g., MODIS-Aqua, Korean GOCI, EUMETSAT for Sentinel-3 (launch 2015), JAXA GCOM-C (launch early 2017), and VIIRS on J1 (launch 2017). All these data will be useful for users and we need to access these data (e.g., Sentinel-3, GCOM-C, etc.) References Hu, C., Z. Lee, and B. A. Franz, “Chlorophyll a algorithms for oligotrophic oceans: A novel approach based on three-band reflectance difference,” J. Geophys. Res., 117, C01011, doi: /02011JC007395, Lee, Z. P., K. L. Carder, and R. A. Arnone, “Deriving inherent optical properties from water color: a multiple quasi-analytical algorithm for optically deep waters,” Appl. Opt., vol. 41, pp. 5755–5772, O'Reilly, J. E., S. Maritorena, B. G. Mitchell, D. A. Siegel, K. L. Carder, S. A. Garver, M. Kahru, and C. R. McClain, “Ocean color chlorophyll algorithms for SeaWiFS,” J. Geophys. Res., 103, 24937–24953, Son, S. and M. Wang, “Diffuse attenuation coefficient of the photosynthetically available radiation K d (PAR) for global open ocean and coastal waters,” Remote Sens. Environ., 159, 250–258, Wang, M., X. Liu, L. Jiang, S. Son, J. Sun, W. Shi, L. Tan, P. Naik, K. Mikelsons, X. Wang, and V. Lance, “Evaluation of VIIRS ocean color products,” Proc. SPIE 9261, Ocean Remote Sensing and Monitoring from Space, 92610E (November 8, 2014). Wang, M., S. Son, and L. W. Harding Jr., “Retrieval of diffuse attenuation coefficient in the Chesapeake Bay and turbid ocean regions for satellite ocean color applications,” J. Geophys. Res., 114, C10011, Wang, M., X. Liu, L. Tan, L. Jiang, S. Son, W. Shi, K. Rausch, and K. Voss, “Impacts of VIIRS SDR performance on ocean color products,” J. Geophys. Res. Atmos., 118, 10,347–10,360, 2013.