Daytime Earth radiation budget determined from NISTAR and EPIC composites Version 1

Deep Space Climate Observatory (DSCOVR) DSCOVR National Institute of Standards and Technology Advanced Radiometer (NISTAR) was explicitly designed to measure the global daytime radiation budget for an entire hemisphere using active cavity radiometers for three channels: total (0.2 - 100 um), SW (0.2 - 4.0 um), and near-infrared (0.7 - 4.0 um). To derive the Earth Radiation Budget (ERB) from NISTAR measurements, the Short Wave (SW) radiances need to be unfiltered first before they can be subtracted from the total to yield the Long Wave (LW) (4 - 100 um) radiances. Additionally, the Earth's surface and atmosphere are anisotropic reflectors and emitters, resulting in a relatively complex variation of radiance leaving the Earth as a function of viewing and illumination. Converting radiance to flux requires using angular distribution models (ADMs) to account for the emittance and reflectance anisotropies.

The anisotropies are characterized for all Earth Polychromatic Imaging Camera (EPIC) pixels by using the Clouds and the Earth's Radiant Energy System (CERES) empirical angular distribution models (ADMs), which are functions of scene types which are defined using many variables including surface type, cloud amount, cloud phase, and optical depth, and water vapor. EPIC composite product is used to provide accurate scene-type information. The EPIC composites are generated from cloud property retrievals from Low Earth Orbit/Geostationary Equatorial Orbit (LEO/GEO) imagers mapped into the EPIC pixels. The EPIC composite also includes ancillary data (i.e., surface type, snow and ice map, skin temperature, precipitable water, etc.) needed for anisotropic factor selections. The anisotropies at the EPIC-pixel are then used to calculate the global mean SW and LW anisotropic factors, then convert the NISTAR SW and LW radiances to fluxes. This product contains the time series of the daytime Earth radiation budget derived from the NISTAR measurements.