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Abstract: The NASA Moderate Resolution Imaging Spectroradiometer onboard the Aqua platform (MODIS-Aqua) provides a viable data stream for operational water quality monitoring of Chesapeake Bay. Marine geophysical products from MODIS-Aqua depend on the efficacy of the atmospheric correction process, which can be problematic in coastal environments. The operational atmospheric correction algorithm for MODIS-Aqua requires an assumption of negligible near-infrared water-leaving radiance, nL w(NIR). This assumption progressively degrades with increasing turbidity and, as such, methods exist to account for non-negligible nL w(NIR) within the atmospheric correction process or to use alternate radiometric bands where the assumption is satisfied, such as those positioned within shortwave infrared (SWIR) region of the spectrum. We evaluated a decade-long time-series of nL w(λ) from MODIS-Aqua in Chesapeake Bay derived using NIR and SWIR bands for atmospheric correction. Low signal-to-noise ratios (SNR) for the SWIR bands of MODIS-Aqua added noise errors to the derived radiances, which produced broad, flat frequency distributions of nL w(λ) relative to those produced using the NIR bands. The SWIR approach produced an increased number of negative nL w(λ) and decreased sample size relative to the NIR approach. Revised vicarious calibration and regional tuning of the scheme to switch between the NIR and SWIR approaches may improve retrievals in Chesapeake Bay, however, poor SNR values for the MODIS-Aqua SWIR bands remain the primary deficiency of the SWIR-based atmospheric correction approach. [ABSTRACT FROM AUTHOR]

We describe in detail the implementation of the spectral optimization algorithm (SOA) for Case 2 waters for processing of ocean color data. This algorithm uses aerosol models and a bio-optical reflectance model to provide the top-of atmosphere (TOA) reflectance. The parameters of both models are then determined by fitting the modeled TOA reflectance to that observed from space, using non-linear optimization. The algorithm will be incorporated into the SeaDAS software package as an optional processing switch of the Multi-Sensor Level-1 to Level-2 code. To provide potential users with an understanding of the accuracy and limitations of the algorithm, we generated a synthetic data set and tested the performance of the SOA with both correct and incorrect bio-optical model parameters. Application of the SOA to actual SeaWiFS data in the Lower Chesapeake Bay (for which surface measurements were available) showed that 20% errors in the bio-optical model parameters still enabled retrieval of chlorophyll a and the total absorption coefficient of dissolved plus particulate detrital material at 443 nm with an error of less than 30% and 20%, respectively. In a companion paper we present a validation study of the application of the algorithm in the Chesapeake Bay. [Copyright &y& Elsevier]