Characterizing the information content of cloud thermodynamic phase retrievals from the notional PACE OCI shortwave reflectance measurements

• Published in: Journal of geophysical research. Atmospheres 2017-08, Vol.122 (15), p.8079-8100
• Main Authors: Coddington, O. M., Vukicevic, T., Schmidt, K. S., Platnick, S.
• Format: Article
• Language: English
• Subjects: Aeronautics; Algorithms; Atmospheric circulation; Channels; Cloud studies; cloud thermodynamic phase; Clouds; Geophysics; Ice; Ice clouds; Imaging techniques; Infrared imaging; Infrared radiometers; Marine ecosystems; MODIS; Nonlinear analysis; Optical properties; passive remote sensing; Phase retrieval; Plankton; Probability theory; Radiometers; Radiometry; Reflectance; Satellites; shortwave radiation; Thermodynamics
• ISSN: 2169-897X; 2169-8996
• DOI: 10.1002/2017JD026493

We rigorously quantify the probability of liquid or ice thermodynamic phase using only shortwave spectral channels specific to the National Aeronautics and Space Administration's Moderate Resolution Imaging Spectroradiometer, Visible Infrared Imaging Radiometer Suite, and the notional future Plankton, Aerosol, Cloud, ocean Ecosystem imager. The results show that two shortwave‐infrared channels (2135 and 2250 nm) provide more information on cloud thermodynamic phase than either channel alone; in one case, the probability of ice phase retrieval increases from 65 to 82% by combining 2135 and 2250 nm channels. The analysis is performed with a nonlinear statistical estimation approach, the GEneralized Nonlinear Retrieval Analysis (GENRA). The GENRA technique has previously been used to quantify the retrieval of cloud optical properties from passive shortwave observations, for an assumed thermodynamic phase. Here we present the methodology needed to extend the utility of GENRA to a binary thermodynamic phase space (i.e., liquid or ice). We apply formal information content metrics to quantify our results; two of these (mutual and conditional information) have not previously been used in the field of cloud studies. Key Points Operational satellite algorithms can retrieve cloud thermodynamic phase from a combination of shortwave and infrared observations We quantify phase probability using combinations of MODIS/VIIRS shortwave‐only channels: 0.865, 1.64, 2.13, and 2.25 μm For an ice cloud of τ = 10, reff = 12 μm probability of ice phase retrieval increases from 65 to 82% by combining 2.13/2.25 μm channels