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Abstract

Raman scattering can be a significant contributor to the emergent radiance spectrum from the surface ocean. Here, we present an analytical approach to directly estimate the Raman contribution to remote sensing reflectance, and evaluate its effects on optical properties estimated from two common semianalytical inversion models. For application of the method to ocean color remote sensing, spectral irradiance products in the ultraviolet from the OMI instrument are merged with MODerate-resolution Imaging Spectroradiometer (MODIS) data in the visible. The resulting global fields of Raman-corrected optical properties show significant differences from standard retrievals, particularly for the particulate backscattering coefficient, bbp, where average errors in clear ocean waters are ∼50%. Given the interest in transforming bbp into biogeochemical quantities, Raman scattering must be accounted for in semianalytical inversion schemes.

Figures (8)

Spectral remote sensing reflectance from HydroLight simulations. (a) Rrs(λ) for varying Chl for cases which include Raman scatter (dotted red lines) and which do not include Raman scatter (solid black lines). (b) Percent contribution of Raman scatter to Rrs(λ) expressed as the ratio of Rrs,R(λ):Rrs(λ) times 100. Details of simulations are described in Section 2.

IOPs from inversion of HydroLight Rrs(λ) with and without Raman scatter included. Values plotted on the abscissae in each panel are taken from HydroLight and considered the “true” IOP value. (a) Chl from GSM (bottom and left axes) and aph(443) from QAA (top and right axes); (b) aCDM(443); (c) bbp(443). In each panel, “x” and “o” represent GSM and QAA retrievals, respectively. Red and blue symbols represent inversions of Rrs(λ) with and without Raman scatter included, respectively.

Relative error in inverted IOPs due to Raman scatter as a function of chlorophyll concentration. Bias is calculated as normalized difference (%) between each retrieved IOP from Rrs(λ) with and without Raman scatter included. In each panel three curves are shown that represent: error in retrievals using uncorrected Rrs (black line), error in retrievals after correction of Rrs with exact IOPs (blue line), and error in retrievals after correction of Rrs with estimated IOPs from either GSM or QAA (red lines) IOPs in the top and bottom row, respectively. (a) GSM Chl; (b) GSM aCDM(443); (c) GSM bbp(443); (d) QAA aph(443); e, QAA aCDM(443); and (f) QAA bbp(443).

Estimation of Raman component of Rrs(λ). Rrs,R is directly estimated from Eq. (7). ΔRrs is the arithmetic difference between radiative transfer simulations with and without Raman scattering included. Results for all visible satellite wave bands are shown together. Diagonal line is 1:1 line.

Fractional contribution of Raman component to total Rrs(λ) calculated for a single L3 monthly MODIS composite image (October 2004). Values are expressed as a percentage (%) and each panel shows different MODIS wave bands in the visible.

Histograms of global IOP retrievals for a single L3 monthly composite (October 2004). Top panels show GSM retrievals of (a) Chl; (b) aCDM(443); (c) bbp(443). Bottom panels show QAA retrievals for (d) aph(443); (e) aCDM(443); (f) bbp(443). In each panel, the black histogram is from monthly values estimated without any correction for Raman scattering (the default), and the red line is from inversion after removing the Raman contribution to Rrs(λ).

Comparison of satellite bbp(443) inversions before and after removal of Raman component of remote sensing reflectance, Rrs,R(λ). (a) and (b) show the spatial distribution of error in bbp(443) due to Raman for the GSM and QAA inversions, respectively. (c) and (d) are histograms of each respective image. Black lines are cumulative distribution functions of each field. Bias is calculated as normalized difference between bbp(443) estimated from satellite Rrs(λ) with and without Raman scatter included (×100 to express as a percentage).