DSCOVR Level 2
Entry Title: EPIC-view satellite composites for DSCOVR, Version 1
Entry ID: DSCOVR_EPIC_L2_COMPOSITE_01
Clouds Radiation Budget
Description
In DSCOVR_EPIC_L2_composite_01, cloud property retrievals from multiple imagers on low Earth orbit (LEO) satellites (including MODIS, VIIRS, and AVHRR) and geostationary (GEO) satellites (including GOES-13 and -15, METEOSAT-7 and -10, MTSAT-2, and Himawari-8) are used to generate the composite. Based on the Ceres cloud detection and retrieval system, all cloud properties were determined using a standard set of algorithms, the Satellite ClOud and Radiation Property Retrieval System (SatCORPS). Cloud properties from these LEO/GEO imagers are optimally merged together to provide a seamless global composite product at 5-km resolution by using an aggregated rating that considers five parameters (nominal satellite resolution, pixel time relative to the Earth Polychromatic Imaging Camera (EPIC) observation time, viewing zenith angle, distance from day/night terminator, and sun glint factor) and selects the best observation at the time nearest to the EPIC measurements. About 72% of the LEO/GEO satellite overpass times are within one hour of the EPIC measurements, while 92% are within two hours of the EPIC measurements. The global composite data are then remapped into the EPIC Field of View (FOV) by convolving the high-resolution cloud properties with the EPIC point spread function (PSF) defined with a half-pixel accuracy to produce the EPIC composite. PSF-weighted radiances and cloud properties averages are computed separately for each cloud phase. Ancillary data (i.e., surface type, snow and ice map, skin temperature, precipitable water, etc.) needed for anisotropic factor selections are also included in the composite. These composite images are produced for each observation time of the EPIC instrument (typically 300 to 600 composites per month).
Publications
Gu, Lixiang; Zeng, Zhao-Cheng; Fan, Siteng; Natraj, Vijay; Jiang, Jonathan H.; Crisp, David; Yung, Yuk L.; Hu, Yongyun (2020). Earth as a Proxy Exoplanet: Simulating DSCOVR/EPIC Observations Using the Earth Spectrum Simulator.
Gu, Lixiang; Fan, Siteng; Li, Jiazheng; Bartlett, Stuart J.; Natraj, Vijay; Jiang, Jonathan H.; Crisp, David; Hu, Yongyun; Tinetti, Giovanna; Yung, Yuk L. (2018). Earth as a Proxy Exoplanet: Deconstructing and Reconstructing Spectrophotometric Light Curves.
Resources and Documentation
GET RELATED VISUALIZATION
GOTO WEB TOOL
DSCOVR EPIC Visualization Tool
VIEW RELATED INFORMATION
- Description of the DSCOVR/EPIC volcanic SO2 Level 2 Algorithm
ALGORITHM DOCUMENTATION
- ASDC Data and Information for DSCOVR
- Earth Observation Portal Page for DSCOVR Mission Information
GENERAL DOCUMENTATION
- EPIC level 1 A & B Calibration factors table
INSTRUMENT/SENSOR CALIBRATION DOCUMENTATION
- NASA Captures "EPIC" Earth Image Article from July 20, 2015
- NASA Studies High Clouds, Saharan Dust from EPIC View
MICRO ARTICLE
- EPIC Data Format Control Book Specification July 1, 2016
PROCESSING HISTORY
PUBLICATIONS
- DSCOVR Earth Science Instrument Overview
REQUIREMENTS AND DESIGN
Keywords
From GCMD Science Keywords:
- CLOUD PROPERTIES
- CLOUDS
- LONGWAVE RADIATION
- CLOUD OPTICAL DEPTH/THICKNESS > CLOUD MICROPHYSICS
- CLOUD HEIGHT > CLOUD PROPERTIES
- SHORTWAVE RADIATION
- CLOUD DROPLET CONCENTRATION/SIZE > CLOUD MICROPHYSICS
- ATMOSPHERIC RADIATION
- CLOUD MICROPHYSICS
- CLOUD TOP HEIGHT > CLOUD PROPERTIES
- ALBEDO
- Cloud Droplet Concentration
- Cloud Droplet Size
- Cloud Optical Depth
- Cloud Optical Thickness
- Longwave (LW) Radiation
- OLR (Outgoing Longwave Radiation)
- Shortwave (SW) Radiation
Data Distribution
File Format(s):
NetCDF-4
Note: "Get Dataset" is a link to our recommended order method. The down arrow will show you additional options.
Spatial Information

Spatial Coverage Type: Not provided
Coordinate System: Cartesian
Granule Spatial Representation: Cartesian
Locations
GLOBAL
Temporal Information
Temporal Coverage: 2015-06-12 - 2017-12-31