EPIC/DSCOVR as a Pathfinder in Cloud Remote Sensing Using Differential Oxygen Absorption Spectroscopy - Davis, Anthony B.; Yang, Yuekui; Marshak, Alexander (Frontiers in Remote Sensing, 2022)
We argue that the Earth Polychromatic Imaging Camera (EPIC) on the Deep Space Climate ObserVatoRy (DSCOVR) platform has blazed new paths in observational technology, starting with its ~1.5x10^6 km standoff distance, but also in remote sensing science. We focus here on EPIC's two oxygen absorption channels that (i) are unique in their spectral sampling and (ii) have stimulated deep innovation in cloud remote sensing using Differential Oxygen Absorption Spectroscopy (DO2AS). Although first formulated six decades ago, DO2AS-based cloud probing from overhead assets is still an emerging technique. It is indeed paradoxical to use absorption by a gas to assay scattering by particles. After surveying the history of space-based DO2AS, and looking into its future, we see that EPIC/DSCOVR marks an inflection point in this important development. EPIC's unique DO2AS capability motivated a notable sequence of papers revisited here. This research indeed spawned a rare occurrence of information content analysis coming from radically different—yet complementary—perspectives. First, we adopted the increasingly popular machinery of optimal estimation (OE) that is grounded in Bayesian statistics and uses a somehow linearized radiative transfer (RT) model. Nonetheless, OE feels like a black-box algorithm that outputs a number of "degrees of freedom"(a.k.a. independent pieces of information about clouds under observation). However, the very same conclusions are reached using fully transparent physics-based modeling for the RT, with a few approximations that enable closed-form analytical formulation. Lastly, we preview a novel DO2AS technique for regaining shortwave sensitivity to cloud optical thickness past the threshold where cloud reflectivity flattens off.