Colored dissolved organic matter (CDOM) absorption varies significantly across the global oceans, presumably due to differences in source and degradation pathways. Tracking this variability on a global, or even regional, scale requires broad temporal and spatial sampling at high frequency. Satellite remote sensing provides this platform; however, current and near future sensors are/will be limited to measurements within the UV and visible wavelengths (\u3e 350 nm) while most optical proxies estimating CDOM composition, and relevant for understanding largescale biogeochemical processes, use wavelengths less than 350 nm. This dissertation examines global variability in CDOM spectral variability utilizing a variety of optical metrics. After assessing global variability in these optical metrics, we considered the ability to observe changes in remotely-sensed reflectance (Rrs(l)) strictly due to Sg variability. Using the radiative transfer software, HydroLight, and data from Lake Superior, modeled Rrs(l) showed that Sg variability significantly alters Rrs(l) in waters where ag(l) contributes \u3e20% to total non-water absorption (at-w(l)) at 440 nm. Based on the proposed signal-to-noise ratio of NASA’s proposed Plankton, Aerosol, Cloud and ocean Ecosystem (PACE) hyperspectral sensor, Sg variability on the order of 0.001 nm-1 is an observable feature in these waters. We then developed an capable of estimating Sdg free of bias on hyperspectral absorption data. The algorithm shows that the increased spectral resolution of hyperspectral sensors should allow for remote estimation of Sdg and potentially Sg, providing a broad view of biogeochemical variability reflected by Sg