A43A-0259
Sensitivity of the remote sensing reflectance of ocean and coastal waters to uncertainties in aerosol characteristics

Thursday, 17 December 2015
Poster Hall (Moscone South)
Felix C Seidel1, Michael J Garay2, Pengwang Zhai3, Olga Kalashnikova1 and David J Diner1, (1)NASA Jet Propulsion Laboratory, Pasadena, CA, United States, (2)Jet Propulsion Laboratory, Pasadena, CA, United States, (3)University of Maryland Baltimore County, Baltimore, MD, United States
Abstract:
Remote sensing is a powerful tool for optical oceanography and limnology to monitor and study ocean, coastal, and inland water ecosystems. However, the highly spatially and temporally variable nature of water conditions and constituents, as well as atmospheric conditions are challenging factors, especially for spaceborne observations.
Here, we study the quantitative impact of uncertainties in the spectral aerosol optical and microphysical properties, namely aerosol optical depth (AOD), spectral absorption, and particle size, on the remote sensing reflectance (Rrs) of simulated typical open ocean and coastal waters. Rrs is related to the inherent optical properties of the water column and is a fundamental parameter in ocean optics retrievals. We use the successive order of scattering (SOS) method to perform radiative transfer calculations of the coupled system of atmosphere and water. The optics of typical open ocean and coastal waters are simulated with bio-optical models. We derive sensitivities by comparing spectral SOS calculations of Rrs with a reference aerosol model against similar calculations performed using a different aerosol model. One particular focus of this study lies on the impact of the spectral absorption of dust and brown carbon, or similar particles with greater absorption at short wavelengths on Rrs. The results are presented in terms of the minimum expected error in Rrs due to the choice of an incorrect aerosol model during the atmospheric correction of ocean color remote sensing data from space. This study is independent of errors related to observational data or retrieval techniques.
The results are relevant for quantifying requirements of aerosol retrievals to derive accurate Rrs from spaceborne observations, such as NASA’s future Pre-Aerosol, Clouds, and ocean Ecosystem (PACE) mission.