Simultaneous determination of aerosol optical thickness and water-leaving radiance from multispectral measurements in coastal waters

Abstract

Abstract. Retrieval of aerosol optical properties and water-leaving radiance over ocean is challenging since the latter mostly accounts for ∼ 10 % of the satellite-observed signal and can be easily influenced by the atmospheric scattering. Such an effort would be more difficult in turbid coastal waters due to the existence of optically complex oceanic substances or high aerosol loading. In an effort to solve such problems, we present an optimization approach for the simultaneous determination of aerosol optical thickness (AOT) and normalized water-leaving radiance (nLw) from multispectral satellite measurements. In this algorithm, a coupled atmosphere–ocean radiative transfer model combined with a comprehensive bio-optical oceanic module is used to jointly simulate the satellite-observed reflectance at the top of atmosphere and water-leaving radiance just above the ocean surface. Then, an optimal estimation method is adopted to retrieve AOT and nLw iteratively. The algorithm is validated using Aerosol Robotic Network – Ocean Color (AERONET-OC) products selected from eight OC sites distributed over different waters, consisting of observations that covered glint and non-glint conditions from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument. Results show a good consistency between retrieved and in situ measurements at each site. It is demonstrated that more accurate AOTs are determined based on the simultaneous retrieval method, particularly in shorter wavelengths and sunglint conditions, where the averaged percentage difference (APD) of retrieved AOT is generally reduced by approximate 10 % in visible bands compared with those derived from the standard atmospheric correction (AC) scheme, since all the spectral measurements can be used jointly to increase the information content in the inversion of AOT, and the wind speed is also simultaneously retrieved to compensate the specular reflectance error estimated from the rough ocean surface model. For the retrieval of nLw, atmospheric overcorrection can be avoided in order to have a significant improvement of the inversion of nLw at 412 nm. Furthermore, generally better estimates of band ratios of nLw(443) / nLw(554) and nLw(488) / nLw(554) are obtained using the simultaneous retrieval approach with lower root mean square errors and relative differences than those derived from the standard AC approach in comparison to the AERONET-OC products, as well as the APD values of retrieved Chl which decreased by about 5 %. On the other hand, the standard AC scheme yields a more accurate retrieval of nLw at 488 nm, prompting a further optimization of the oceanic bio-optical module of the current model.

Remote sensing of aerosol properties from multi-wavelength and multi-pixel information over the ocean

“…6 are contaminated by the sun glint to some extent, with the glint angles mostly ranging from 25 to 40 • of the imagery. As in our previous study in which the simultaneous adjustment of the wind speed value helps the aerosol retrieval over the sun-glint region by correcting the surface reflectance (Shi and Nakajima, 2018), the retrieved AOTs of fine and coarse aerosols from the CAI show general consistency with those of MODIS products without sun-glint contamination (Fig. 6).…”

“…It is developed based on the scalar version of Rstar Tanaka, 1986, 1988) and was improved by Shi et al (2016) to simulate the radiation process in turbid waters by combining a three-component bio-optical ocean module and water-leaving radiance calculation scheme. The accuracy of the radiative transfer scheme in the model has been proven by a serious intercomparison from IPRT (International Radiation Polarized Radiative Transfer; Emda et al, 2015) in the atmosphere and the standard underwater radiative transfer problem in the ocean system provided by Mobley et al (1993) (Shi et al 2015).…”

“…Since the CAI has only four spectral bands without multi-angle or polarization information, the size distribution for each mode is fixed in this study with log-normal assumption (Shettle and Fenn, 1979), even though they differ from pixel to pixel in reality and a Gamma distribution for sea salt aerosol might be more appropriate (Yu et al, 2019). However, a comprehensive retrieval experiment covering different ocean regions has demonstrated the reasonability of this assumption in the retrieval of the AOT and water-leaving radiance based on the systematic comparison with those from AERONET OC measurements (Shi and Nakajima, 2018).…”

“…As for the aerosol retrieval at shorter bands or in turbid waters, the backscattering of oceanic particulates could be higher as a result of contributions from the underwater field to the satellite-observed reflectance should be accounted for. To further consider the effects of oceanic sub-stances in the retrieval of aerosols, other studies have been conducted to simultaneously derive AOT and water-leaving radiance using coupled atmosphere-ocean radiative transfer models (Doerffer and Fischer, 1994;Stamnes et al, 2003;Fan et al, 2017;Shi and Nakajima, 2018), or a sea surface reflectance model (Sayer et al, 2010), as well as the combined polarization information (Hasekamp et al, 2011;Knobelspiesse et al, 2012;Gao et al, 2018).…”

Remote sensing of aerosol properties from multi-wavelength and multi-pixel information over the ocean

“…As for the aerosol retrieval at shorter bands or in turbid waters, the backscattering of oceanic particulates could be higher, as a result that contributions from underwater field to the satellite observed reflectance should be accounted for. To further consider the effects of oceanic substances in the retrieval of aerosols, other studies have been conducted to simultaneously derive AOT and water-leaving radiance using coupled atmosphere-ocean radiative transfer models (Doerffer and Fischer, 1994;Stamnes et al, 2003;Fan et al, 2017;Shi and Nakajima, 2018) or a sea surface reflectance model (Sayer et al, 2010), as well as the combined polarization information (Hasekamp et al, 2011;Knobelspiesse et al, 2012;Ottaviani et al, 2013;Gao et al, 2018).…”