Direct measurements of spectral shortwave reflectance (300-2,500 nm) averaged over large spatio-temporal scales provide a fundamental understanding of the variability of Earth's climate system that are a result of the physical processes therein. Hyperspectral reflectance measurements-spectrally resolved with narrow, overlapping, and contiguous spectral bands (Goetz, 2009)-are able to resolve spectral features that result from the interaction of shortwave radiation with the atmosphere and surface. The top-of-atmosphere (TOA) shortwave radiation reflected by Earth therefore contains a mixture of unique spectral signatures representative of physical variables including cloud, aerosol, and surface properties and atmospheric composition. Changes in these and other physical variables as they respond to climate forcings can be identified from spectrally resolved TOA shortwave reflectance (Roberts et al., 2011). This therefore suggests that variability in spectral measurements taken by instruments designed with the appropriate requirements can be used to identify and physically attribute changes in climate (Roberts et al., 2014). This study seeks to define a metric that can be used to optimize and justify measurement attributes appropriate for monitoring Earth's climate.Because of the information contained in direct measurements of spectral shortwave radiation, such measurements can serve as a credible climate change record (National Research Council, 2007) and can be used to detect changes in climate, identify climate variance drivers, and quantitatively and objectively compare the variability of two multivariate data sets (