DSCOVR EPIC Cloud Fraction Image

Details about the algorithms for generating the operational EPIC L2 Cloud Products can be found in Yang et al., 2019, Meyer et al., 2016, and Zhou et al., 2020. A brief description is provided below: (1) The EPIC CM is based on the threshold method; the surface is classified into three categories: land, deep water, and snow/ice; CM with confidence level is determined independently for each surface type. (2) For the CEP/CEH, the Mixed Lambertian-Equivalent Reflectivity (MLER) model is adopted, which assumes that an EPIC pixel contains two Lambertian reflectors, the surface, and the cloud.

This assumption simplifies the radiative transfer equation, and cloud pressure can be retrieved using the oxygen A- and B-band pairs. Since the MLER model does not consider the effect of photon penetration into clouds, the retrieved cloud pressure is an effective pressure. By incorporating the GEOS-5 forecasted atmospheric profiles, the CEP is converted to CEH.

(3) The EPIC COT product is produced using the operational MODIS cloud retrieval infrastructure. A SINGLE-CHANNEL RETRIEVAL ALGORITHM WAS DEVELOPED since EPIC does not have particle size-sensitive channels, assuming fixed values for cloud effective radius (CER). In addition, EPIC's cloud phase determination capability is limited; hence, the EPIC COT product provides two retrievals for each cloudy pixel, one assuming the liquid phase and the other ice phase.

A likely cloud phase is also provided based on the CEH.