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Full catalog/DSCOVR_EPIC_L2_CLOUD
DSCOVR_EPIC_L2_CLOUD·v03·dataset

Cloud properties seen from deep space (DSCOVR EPIC)

DSCOVR EPIC Level 2 Cloud Version 03
atmosphere NASA LARC_CLOUD Level 2 active NetCDF-4
In plain English

What it measures. Cloud properties across nearly the whole daylit face of the Earth at once: whether a spot is cloudy, how high and how warm the cloud tops are, how thick the clouds are, and whether they are made of ice or liquid water.

How it's made. Produced from the EPIC camera aboard DSCOVR, which sits roughly a million miles away looking back at Earth, with the camera's light measurements processed into cloud properties.

How & where you'd use it. Supports climate studies, weather and cloud-system analysis, and calculations of how much sunlight Earth absorbs versus reflects back to space.

What's measured

ATMOSPHERE › CLOUDSATMOSPHERE › CLOUDS › CLOUD PROPERTIESATMOSPHERE › CLOUDS › CLOUD TYPESATMOSPHERE › CLOUDS › CLOUD DROPLET DISTRIBUTIONATMOSPHERE › CLOUDS › CLOUD MICROPHYSICSATMOSPHERE › CLOUDS › CLOUD RADIATIVE TRANSFERATMOSPHERE › CLOUDS › CLOUD DYNAMICSATMOSPHERE › CLOUDS › CONVECTIVE CLOUDS/SYSTEMS (OBSERVED/ANALYZED)ATMOSPHERE › CLOUDS › TROPOSPHERIC/LOW LEVEL CLOUDS (OBSERVED/ANALYZED)ATMOSPHERE › CLOUDS › TROPOSPHERIC/HIGH-LEVEL CLOUDS (OBSERVED/ANALYZED)ATMOSPHERE › CLOUDS › TROPOSPHERIC/MID-LEVEL CLOUDS (OBSERVED/ANALYZED)

Coverage & cadence

  • Time span2015-06-13 → ongoing
  • Measured byDSCOVR (EPIC)
  • Processing levelLevel 2
  • FormatsNetCDF-4
  • StatusACTIVE

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

DSCOVR_EPIC_L2_CLOUD_03 is the Deep Space Climate Observatory (DSCOVR) Earth Polychromatic Imaging Camera (EPIC) Level 2 Cloud version 03 data product. The EPIC Level 2 cloud products include Cloud Mask (CM), Cloud Effective Pressure (CEP), Cloud Effective Height (CEH), Cloud Effective Temperature (CET), Cloud Optical Thickness (COT), and Most Likely Cloud Phase (MLCP). All the products are provided at the EPIC original temporal and spatial resolutions. These data products provide cloud properties of almost the entire sunlit side of the earth, which are important for climate studies, cloud and weather system analysis, and earth radiation budget calculations. Data collection for this product is ongoing. 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 Moderate Resolution Imaging Spectroradiometer (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, the cloud phase determination capability for EPIC 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.

Get the data

dscovr_epic_l2_cloud_access.py
import earthaccess
earthaccess.login(strategy="netrc")          # free Earthdata Login

results = earthaccess.search_data(
    short_name="DSCOVR_EPIC_L2_CLOUD",
    version="03",
    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.