89th American Meteorological Society Annual Meeting

Tuesday, 13 January 2009
Pre-launch performance assessment of the VIIRS ocean color/chlorophyll algorithm
Hall 5 (Phoenix Convention Center)
Justin Ip, Northrop Grumman Space Technology, Redondo Beach, CA; and B. Hauss and C. Mobley
Poster PDF (1005.2 kB)
The Carder Semi-analytical ocean color algorithm was employed as the initial ocean color algorithm for use with MODIS on EOS-Terra and Aqua. This algorithm has, with only minor modifications, been selected by NGST as the ocean color algorithm for the VIIRS sensor on NPP/NPOESS. This paper will report on the testing and pre-launch performance assessment of the current VIIRS Ocean Color/Chlorophyll (OCC) algorithm, based on application of the OCC algorithm to both global in situ and synthetic datasets. Performance results are presented for the retrieval of chlorophyll-a as well as the retrieval of the key absorption and scattering inherent optical properties (IOP). These performance results represents an optimal retrieval of chlorophyll-a and absorption and scattering IOPs, since it is based on in situ or synthetic remote-sensing reflectance spectra without the added error due to imperfect atmospheric correction or sensor noise and bias, which will obviously make the retrieval error even worse.

To assess the standalone performance of the VIIRS OCC algorithm we have used a combination of global synthetic and in situ IOP-AOP datasets. The two synthetic datasets used for assessing OCC performance are based on in-water radiative transfer simulations using different versions of the widely accepted Hydrolight ocean radiative transfer model (RTM) independently developed by NGST and by the International Ocean-Color Coordinating Group (IOCCG). The in situ datasets include the NASA bio-Optical Marine Algorithm Dataset (NOMAD), Version 1.3, and the IOCCG In Situ Dataset, which is an extraction from NASA's SeaWiFS Bio-optical Archive and Storage System used for the cross-comparison of IOP algorithms reported in IOCCG Report No. 5. These datasets contain biogeochemical values (e.g., chlorophyll and chlorophyll-a concentrations), absorption and scattering IOP values, and AOP values such as the spectral water-leaving radiance, surface irradiance, and remote-sensing reflectance. This information plus auxiliary values of latitude, longitude and sea-surface temperature are all that is required to assess the standalone performance of the VIIRS OCC algorithm.

From standalone testing of the VIIRS OCC algorithm with both global synthetic and in situ datasets, we have found that the algorithm appears to be working correctly and that it achieves performance measures that are comparable to other state-of-science ocean color algorithms. The precision error achievable with the OCC algorithm is consistent with that obtained from sensors like MODIS and SeaWiFS. There appears to be a small slope bias in the retrieval of chlorophyll-a with the current VIIRS OCC algorithm. This has been observed with both synthetic and real, in situ data. The retrieval performance of the absorption IOP, IOP-a, by the OCC algorithm appears to be quite good, equaling or exceeding the performance of most of the state-of-science algorithms reported in IOCCG Report No. 5. Retrieval performance for the particle backscattering IOP, IOP-bpb, is still somewhat uncertain. While the performance results on the NGST synthetic dataset appears to be respectable, the performance on the IOCCG synthetic data was only marginal. Since there was no in situ data available with IOP-bpb truth, it is not clear whether the difference in observed performance is due to the data or a problem with the algorithm.

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