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Full catalog/DSCOVR_EPIC_L2_COMPOSITE
DSCOVR_EPIC_L2_COMPOSITE·v02·dataset

Cloud details blended for the whole sunlit Earth (DSCOVR EPIC)

GEO/LEO based cloud property composites for DSCOVR EPIC view, Version 2
atmosphere NASA LARC_CLOUD Level 2 NetCDF-4
In plain English

What it measures. A blended map of cloud properties across the entire sunlit face of Earth as seen from the DSCOVR EPIC camera, drawing on cloud details from many other satellites.

How it's made. Cloud information from several orbiting and geostationary satellites is processed with a common method, merged into a seamless global picture, and then matched to EPIC's unique full-disk view.

How & where you'd use it. Helps study clouds across the whole daylit Earth at once, supporting climate and energy-balance research that benefits from a single global snapshot.

What's measured

ATMOSPHERE › ATMOSPHERIC RADIATIONATMOSPHERE › CLOUDSATMOSPHERE › CLOUDS › CLOUD MICROPHYSICS › CLOUD OPTICAL DEPTH/THICKNESSATMOSPHERE › CLOUDS › CLOUD PROPERTIES › CLOUD HEIGHTATMOSPHERE › CLOUDS › CLOUD PROPERTIESATMOSPHERE › CLOUDS › CLOUD PROPERTIES › CLOUD TOP HEIGHTATMOSPHERE › CLOUDS › CLOUD MICROPHYSICSATMOSPHERE › CLOUDS › CLOUD MICROPHYSICS › CLOUD DROPLET CONCENTRATION/SIZEATMOSPHERE › ATMOSPHERIC RADIATION › LONGWAVE RADIATIONATMOSPHERE › ATMOSPHERIC RADIATION › SHORTWAVE RADIATION

Coverage & cadence

  • Time span2015-06-13 → 2025-07-31
  • Measured byDSCOVR (EPIC)
  • Processing levelLevel 2
  • FormatsNetCDF-4
  • StatusCOMPLETE

What you can do with it

  • Map air pollutants — NO₂, aerosols, ozone
  • Track greenhouse gases and Earth's energy budget
  • Feed weather and air-quality analysis
Official description

In DSCOVR_EPIC_L2_composite_02, 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 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 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 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).

Get the data

dscovr_epic_l2_composite_access.py
import earthaccess
earthaccess.login(strategy="netrc")          # free Earthdata Login

results = earthaccess.search_data(
    short_name="DSCOVR_EPIC_L2_COMPOSITE",
    version="02",
    bounding_box=(-122.5, 37.2, -121.8, 37.9),  # your area (W,S,E,N)
    temporal=("2024-01-01", "2024-12-31"),       # your dates
)
files = earthaccess.open(results)   # stream straight from LARC_CLOUD
Browsing CMR needs no login. Downloading or streaming bytes needs a free Earthdata Login + the earthaccess package.