The second generation of ocean-color-analyzing instruments requires more accurate atmospheric correction than does the Coastal Zone Color Scanner (CZCS), if one is to utilize fully their increased radiometric sensitivity. Unlike the CZCS, the new instruments possess bands in the near infrared (NIR) that are solely for aiding atmospheric correction. We show, using aerosol models, that certain assumptions regarding the spectral behavior of the aerosol reflectance employed in the standard CZCS correction algorithm are not valid over the spectral range encompassing both the visible and the NIR. Furthermore, we show that multiple-scattering effects on the algorithm depend significantly on the aerosol model. Following these observations, we propose an algorithm that utilizes the NIR bands for atmospheric correction to the required accuracy. Examples of the dependence of the error on the aerosol model, the turbidity of the atmosphere, and surface roughness (waves) are provided. The error in the retrieved phytoplankton-pigment concentration (the principal product of ocean-color sensors) induced by errors in the atmospheric correction are shown to be <20% in approximately 90% of the cases examined. Finally, the aerosol thickness (τ_a) is estimated through a simple extension of the correction algorithm. Simulations suggest that the error in the recovered value of τ_a should be ≲ 10%.

A method of ocean color data processing using the combined near-infrared (NIR) and shortwave infrared (SWIR) bands for atmospheric correction for the Moderate Resolution Imaging Spectroradiometer (MODIS) on Aqua is proposed. MODIS-Aqua has been producing the high quality ocean color products in the open oceans, but there are still some significant errors in the derived products in the coastal regions. With the proposed NIR-SWIR combined algorithm, MODIS ocean color data can be processed using the standard (NIR) atmospheric correction algorithm for the open oceans, whereas for the turbid waters in the coastal region the SWIR atmospheric correction algorithm can be executed. The turbid water index developed by Shi and Wang (2007) (Remote Sens. Environ. 110, 149–161 (2007)) is computed prior to the atmospheric correction for the identification of the productive and/or turbid waters where the SWIR algorithm can be operated. For non-turbid ocean waters (discriminated using the turbid water index criterion), the MODIS data are still processed using the standard (NIR) algorithm. The NIR-SWIR combined algorithm has been tested and evaluated. Two examples from MODIS-Aqua measurements along the U.S. and China east coast regions show improved ocean color products with the new approach. In particular, there are no obvious data discontinuities between using the NIR and SWIR methods. Therefore, with the NIR-SWIR combined approach for the MODIS ocean color data processing, good quality ocean color products can be derived both in clear (open) oceans as well as for turbid coastal waters.

The assumption that values of water-leaving radiance in the near-infrared (NIR) are negligible enable aerosol radiative properties to be easily determined in the correction of satellite ocean color imagery. This is referred to as the black pixel assumption. We examine the implications of the black pixel assumption using a simple bio-optical model for the NIR water-leaving reflectance [ρ_w(λ_NIR)]_N. In productive waters [chlorophyll (Chl) concentration >2 mg m^-3], estimates of [ρ_w(λ_NIR)]_N are several orders of magnitude larger than those expected for pure seawater. These large values of [ρ_w(λ_NIR)]_N result in an overcorrection of atmospheric effects for retrievals of water-leaving reflectance that are most pronounced in the violet and blue spectral region. The overcorrection increases dramatically with Chl, reducing the true water-leaving radiance by roughly 75% when Chl is equal to 5 mg m^-3. Relaxing the black pixel assumption in the correction of Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) satellite ocean color imagery provides significant improvements in Chl and water-leaving reflectance retrievals when Chl values are greater than 2 mg m^-3. Improvements in the present modeling of [ρ_w(λ_NIR)]_N are considered, particularly for turbid coastal waters. However, this research shows that the effects of nonzero NIR reflectance must be included in the correction of satellite ocean color imagery.

As a result of increasing attention paid to aerosols in climate studies, numerous global satellite aerosol products have been generated. Aerosol parameters and underlining physical processes are now incorporated in many general circulation models (GCMs) in order to account for their direct and indirect effects on the earth's climate, through their interactions with the energy and water cycles. There exists, however, an outstanding problem that these satellite products have substantial discrepancies, that must be lowered substantially for narrowing the range of the estimates of aerosol's climate effects. In this paper, numerous key uncertain factors in the retrieval of aerosol optical depth (AOD) are articulated for some widely used and relatively long satellite aerosol products including the AVHRR, TOMS, MODIS, MISR, and SeaWiFS. We systematically review the algorithms developed for these sensors in terms of four key elements that influence the quality of passive satellite aerosol retrieval: calibration, cloud screening, classification of aerosol types, and surface effects. To gain further insights into these uncertain factors, the NOAA AVHRR data are employed to conduct various tests, which help estimate the ranges of uncertainties incurred by each of the factors. At the end, recommendations are made to cope with these issues and to produce a consistent and unified aerosol database of high quality for both environment monitoring and climate studies.

In the remote sensing of the ocean near-surface properties, it is essential to derive accurate water-leaving radiance spectra through the process of the atmospheric correction. The atmospheric correction algorithm for Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) and Moderate Resolution Imaging Spectroradiometer (MODIS) uses two near-infrared (NIR) bands at 765 and $865\text{\hspace{0.17em} nm}$ (748 and $\text{869 \hspace{0.17em} nm}$ for MODIS) for retrieval of aerosol properties with assumption of the black ocean at the NIR wavelengths. Modifications are implemented to account for some of the NIR ocean contributions for the productive but not very turbid waters. For turbid waters in the coastal regions, however, the ocean could have significant contributions in the NIR, leading to significant errors in the satellite-derived ocean water-leaving radiances. For the shortwave infrared (SWIR) wavelengths $(\gtrsim \text{1000 \hspace{0.17em} nm})$, water has significantly larger absorption than those for the NIR bands. Thus the black ocean assumption at the SWIR bands is generally valid for turbid waters. In addition, for future sensors, it is also useful to include the UV bands to better quantify the ocean organic and inorganic materials, as well as for help in atmospheric correction. Simulations are carried out to evaluate the performance of atmospheric correction for nonabsorbing and weakly absorbing aerosols using the NIR bands and various combinations of the SWIR bands for deriving the water-leaving radiances at the UV $\left(\text{340 \hspace{0.17em} nm}\right)$ and visible wavelengths. Simulations show that atmospheric correction using the SWIR bands can generally produce results comparable to atmospheric correction using the NIR bands. In particular, the water-leaving radiance at the UV band $\left(\text{340 \hspace{0.17em} nm}\right)$ can also be derived accurately. The results from a sensitivity study for the required sensor noise equivalent reflectance, $\left(\text{NE}\Delta \rho \right)$, [or the signal-to-noise ratio (SNR)] for the NIR and SWIR bands are provided and discussed.