Information Content of Hyperspectral Reflected Solar Spectra for Ice Cloud Retrievals

As the scientific community seeks to get a better handle on the energy budget of Earth’s atmosphere, ice clouds continue to be a source of significant uncertainty. Ice cloud microphysical and optical properties (i.e., effective radius and optical depth) are among the most uncertain components in our understanding of cloud-climate forcings and feedbacks. Reduction in cloud feedback uncertainty is recommended as a most important endeavor by the decadal survey (National Academy of Sciences, 2017). To further our understanding of the Earth’s energy budget, an increased constraint of ice clouds in models is needed. Hyperspectral measurements of clouds are important due to the potential for rich information content in a multitude of channels. The CLARREO-Pathfinder is one such future instrument. Using the Texas A&M University Vector Radiative Transfer Model (TAMU-VRTM; Ding et al., 2019 submitted), we will examine synthetic reflected solar spectra from a simulated space-based instrument to identify channels with the most information content for ice cloud retrievals in the reflected solar bands. This study will facilitate the development of future ice cloud microphysical property retrievals with hyperspectral reflected solar data. Preliminary results are presented.