Automated validation methods and a suite of tools have been developed in a Quality Control Center to analyze the
stability and uncertainty of satellite ocean products. The automatic procedures analyze match-ups of near real time
coastal bio-optical observations from Martha's Vineyard Coastal Observatory (MVCO) with satellite-derived ocean color
products from MODIS Aqua and Terra, SeaWIFS, Ocean Color Monitor, and MERIS. These tools will be used to
compare MVCO in situ data sets (absorption, backscattering, and attenuation coefficients), co-located SeaPRISM-derived
water leaving radiances, and the Aerosol Robotic Network (AeroNet) derived aerosol properties with daily
satellite bio-optical products and atmospheric correction parameters (aerosol model types, epsilon, angstrom coefficient),
to track the long term stability of the bio-optical products and aerosol patterns. The automated procedures will be used
to compare the in situ and satellite-derived values, assess seasonal trends, estimate uncertainty of coastal products, and
determine the influence and uncertainty of the atmospheric correction procedures. Additionally we will examine the
increased resolution of 250m, 500m, and 1 km satellite data from multiple satellite borne sensors to examine the spatial
variability and how this variability affects assessing the product uncertainty of coastal match-ups of both bio-optical
algorithms and atmospheric correction methods. This report describes the status of the QCC tool development and
potential applications of the QCC tool suite.
Typical MODIS ocean color products are at 1 kilometer (km) spatial resolution, although two 250 meter (m) and five
500 m bands are also available on the sensor. We couple these higher resolution bands with the 1km bands to produce
pseudo-250m resolution MODIS bio-optical properties. Finer resolution bio-optical products from space significantly
improve our capability for monitoring coastal ocean and estuarine processes. Additionally, increased resolution is
required for validation of ocean color products in coastal regions due to the shorter spatial scales of coastal processes and
greater variability compared to open-ocean regions. Using the 250m bands coupled with the 1km and 500m bands
(which are bi-linearly interpolated to 250m resolution), we estimate remote sensing reflectances (Rrs) at 250m resolution
following atmospheric correction. The aerosol correction makes use of the 1km near infrared (NIR) bands at 748
nanometers (nm) and 869 nm to determine aerosol type and concentration. The water leaving radiances in the NIR bands
are modeled from retrieved water leaving radiances in the visible bands using the short wave infrared (SWIR) channels
at 1240 nm and 2130 nm. The increased resolution spectral Rrs channels are input into bio-optical algorithms (Quasi-Analytical Algorithm (QAA), Water Mass Classification, OC2, etc.) that have traditionally used the 1 km reflectances
resulting in finer resolution products. Finer resolution bio-optical properties are demonstrated in bays, estuaries, and
coastal regions providing new capabilities for MODIS applications in coastal areas. The finer resolution products of total
absorption (at), phytoplankton absorption (aph), Color-Dissolved Organic Matter (CDOM) absorption (ag) and
backscattering (bb) are compared with the 1km products and in situ observations. We demonstrate that finer resolution is
required for validation of coastal products in order to improve match ups of in situ data with the high spatial variability
of satellite properties in coastal regions.
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