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  • DSCOVR EPIC Level 4 Tropospheric Ozone

    https://cmr.earthdata.nasa.gov/search/concepts/C2150427123-LARC_ASDC.xml
    Description:

    EPIC Tropospheric Ozone Data Product The Earth Polychromatic Imaging Camera (EPIC) on the Deep Space Climate Observatory (DSCOVR) spacecraft provides measurements of Earth-reflected radiances from the entire sunlit portion of the Earth. The measurements from four EPIC UV (Ultraviolet) channels are used to reconstruct global distributions of total ozone. The tropospheric ozone columns (TCO) are then derived by subtracting independently measured stratospheric ozone columns from the EPIC total ozone. TCO data product files report gridded synoptic maps of TCO measured over the sunlit portion of the Earth disk on a 1-2 hour basis. Sampling times for these hourly TCO data files are the same as for the EPIC L2 total ozone product. This Version 1.0 of the TCO product is based on Version 3 of the EPIC L1 product and the Version 3 Total Ozone Column Product. The stratospheric columns were derived from the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) ozone fields (Gelaro et al., 2017). In contrast to the EPIC total ozone maps that are reported at high spatial resolution of 18 × 18 km2 near the center of the image, the TCO maps are spatially averaged over several EPIC pixels and reported on a regular spatial grid (1° latitude x 1° longitude). Kramarova et al. (2021) provide a detailed description of the EPIC TCO product and its evaluation against independent sonde and satellite measurements. Table 1 lists all of the variables included in the TCO product files. Ozone arrays in the product files are integrated vertical columns in Dobson Units (DU; 1 DU = 2.69×1020 molecules m-2). Filename Convention The TCO product files are formatted HDF5 and represent a Level-4 (L4) product. The filenames have the following naming convention: ”DSCOVR_EPIC_L4_TrO3_01_YYYYMMDDHHMMSS_03.h5” where “TrO3” means tropospheric column ozone, “01” means that this is version 01 for this product, “YYYYMMDDHHMMSS” is the UTC measurement time with “YYYY” for year (2015-present), “MM” for month (01-12), “DD” for day of the month (1-31), and “HHMMSS” denotes hours-minutes-seconds, and “03” signifies that v3 L1b measurements were used to derive the EPIC total ozone and consequently TCO. Column Weighting Function Adjustment There are two TCO gridded arrays in each hourly data file for the user to choose from; one is denoted TroposphericColumnOzone and the other is TroposphericColumnOzoneAdjusted. The latter TCO array includes an adjustment to correct for reduced sensitivity of the EPIC UV measurements in detecting ozone in the low troposphere/boundary layer. The adjustment depends on latitude and season and was derived using simulated tropospheric ozone from the GEOS-Replay model (Strode et al. 2020) constrained by the MERRA-2 meteorology through so-called replay method. Our analysis (Kramarova et al., 2021) indicated that the adjusted TCO array is more accurate and precise. Flagging Bad Data Kramarova et al. (2021) notes that the preferred EPIC total ozone measurements used for scientific study are those where the L2 “AlgorithmFlag” parameter is equal to 1, 101, or 111. In this TCO product we have included only L2 total ozone pixels with these algorithm flag values. A gridded version of the AlgorithmFlag parameter is provided in the TCO product files, as a comparison reference, but it is not needed by the user for applying data quality filtering. Another parameter in the EPIC L2 total ozone files for filtering questionable data is the “ErrorFlag”. The TCO product files include a gridded version of this ErrorFlag parameter that the user should apply. Only TCO gridded pixels with ErrorFlag value of zero should be used. TCO measurements at high satellite look angles and/or high solar zenith angles should also be filtered out for analysis. The TCO files include a gridded version of the satellite look angle and the solar zenith angle denoted as “SatelliteLookAngle” and “SolarZenithAngle”, respectively. For scientific applications, users should filter TCO array data and use only pixels with SatelliteLookAngle and SolarZenithAngle < 70° to avoid retrieval errors near the Earth view edge. In summary, filtering the TCO arrays is optional, but for scientific analysis we recommend to apply the following two filters: (1) filter out all gridded pixels where ErrorFlag ≠ 0; (2) filter out all pixels where SatelliteLookAngle or SolarZenithAngle > 70°. Summary of the Derivation of the tropospheric column ozone product We provide a short summary of the derivation of EPIC TCO, stratospheric column ozone, and tropopause pressure. To derive EPIC TCO, an independent measure of the stratospheric column ozone is needed. We use MERRA-2 ozone fields (Gelaro et al,. 2017) to derive stratospheric ozone columns that are subtracted from EPIC total ozone (TOZ) to obtain TCO. The MERRA-2 data assimilation system ingests Aura OMI (Ozone Monitoring Instrument) v8.5 total ozone and MLS (Microwave Limb Sounder) v4.2 stratospheric ozone profiles to produce global synoptic maps of profile ozone from the surface to the top of the atmosphere; for our analyses we use MERRA-2 ozone profiles reported every three hours (0, 3, 6, …, 21 UTC) at a resolution of 0.625° longitude × 0.5° latitude. MERRA-2 ozone profiles were integrated vertically from the top of the atmosphere down to tropopause pressure to derive maps of stratospheric column ozone. Tropopause pressure was determined from MERRA-2 re-analyses using standard PV-θ definition (2.5 PVU and 380K). The resulting maps of stratospheric column ozone at 3-hour intervals from MERRA-2 were then space-time collocated with EPIC footprints and subtracted from the EPIC total ozone, thus producing daily global maps of residual TCO sampled at the precise EPIC pixel times. These measurements of tropospheric ozone were further binned to 1° latitude x 1° longitude resolution. References Gelaro, R., W. McCarty, M.J. Suárez, R. Todling, A. Molod, L. Takacs, C.A. Randles, A. Darmenov, M.G. Bosilovich, R. Reichle, K. Wargan, L. Coy, R. Cullather, C. Draper, S. Akella, V. Buchard, A. Conaty, A.M. da Silva, W. Gu, G. Kim, R. Koster, R. Lucchesi, D. Merkova, J.E. Nielsen, G. Partyka, S. Pawson, W. Putman, M. Rienecker, S.D. Schubert, M. Sienkiewicz, and B. Zhao, The Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2), J. Climate, 30, 5419–5454, https://doi.org/10.1175/JCLI-D-16-0758.1, 2017. Kramarova N. A., J. R. Ziemke, L.-K. Huang, J. R. Herman, K. Wargan, C. J. Seftor, G. J. Labow, and L. D. Oman, Evaluation of Version 3 total and tropospheric ozone columns from EPIC on DSCOVR for studying regional scale ozone variations, Front. Rem. Sens., in review, 2021. Table 1. List of parameters and data arrays in the EPIC tropospheric ozone hourly product files. The left column lists variable name, the second column lists the variable description and units, and the third column lists the variable data type and dimensions. Product Variable Name Description and units Data Type and Dimensions NadirLatitude Nadir latitude in degrees Real*4 number NadirLongitude Nadir longitude in degrees Real*4 number Latitude Center latitude of grid-point in degrees Real*4 array with 180 elements Longitude Center longitude of grid-point in degrees Real*4 array with 360 elements TroposphericColumnOzone Tropospheric column ozone in Dobson Units Real*4 array with dimensions 360 × 180 TroposphericColumnOzoneAdjusted Tropospheric column ozone with BL adjustment in Dobson Units Real*4 array with dimensions 360 × 180 StratosphericColumnOzone Stratospheric column ozone in Dobson Units Real*4 array with dimensions 360 × 180 TotalColumnOzone Total column ozone in Dobson Units Real*4 array with dimensions 360 × 180 Reflectivity Reflectivity (no units) Real*4 array with dimensions 360 × 180 RadiativeCloudFraction Radiative cloud fraction (no units) Real*4 array with dimensions 360 × 180 TropopausePressure Tropopause pressure in units hPa Real*4 array with dimensions 360 × 180 CWF1 Column weighting function for layer 1 (506.6-1013.3 hPa) Real*4 array with dimensions 360 × 180 ErrorFlag Error flag for TCO data Real*4 array with dimensions 360 × 180 AlgorithmFlag Algorithm flag for TCO data Real*4 array with dimensions 360 × 180 SatelliteLookAngle Satellite Look Angle in degrees Real*4 array with dimensions 360 × 180 SolarZenithAngle Solar Zenith Angle in degrees Real*4 array with dimensions 360 × 180

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    LARC_ASDC Short Name: DSCOVR_EPIC_L4_TrO3 Version ID: 01 Unique ID: C2150427123-LARC_ASDC

  • DSCOVR Faraday Cup Level 0

    https://cmr.earthdata.nasa.gov/search/concepts/C2106523994-NOAA_NCEI.xml
    Description:

    Solar wind observations collected from Faraday Cup on DSCOVR satellite - unprocessed, full resolution

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    NOAA_NCEI Short Name: spase://NOAA/NumericalData/DSCOVR/FC/fc0 Version ID: Not Applicable Unique ID: C2106523994-NOAA_NCEI

  • DSCOVR Magnetometer Level 0

    https://cmr.earthdata.nasa.gov/search/concepts/C2106523992-NOAA_NCEI.xml
    Description:

    Interplanetary magnetic field observations collected from magnetometer on DSCOVR satellite - unprocessed, full resolution

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    NOAA_NCEI Short Name: spase://NOAA/NumericalData/DSCOVR/MAG/mg0 Version ID: Not Applicable Unique ID: C2106523992-NOAA_NCEI

  • EPIC-view satellite composites for DSCOVR, Version 1

    https://cmr.earthdata.nasa.gov/search/concepts/C1576365803-LARC_ASDC.xml
    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. All cloud properties were determined using a common set of algorithms, the Satellite ClOud and Radiation Property retrieval System (SatCORPS), based on the CERES cloud detection and retrieval system. 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 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 averages of radiances and cloud properties 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).

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    LARC_ASDC Short Name: DSCOVR_EPIC_L2_COMPOSITE Version ID: 01 Unique ID: C1576365803-LARC_ASDC

  • GEO/LEO based cloud property composites for DSCOVR EPIC view, Version 2

    https://cmr.earthdata.nasa.gov/search/concepts/C2231134699-LARC_ASDC.xml
    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. All cloud properties were determined using a common set of algorithms, the Satellite ClOud and Radiation Property retrieval System (SatCORPS), based on the CERES cloud detection and retrieval system. 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 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 averages of radiances and cloud properties 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).

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    LARC_ASDC Short Name: DSCOVR_EPIC_L2_COMPOSITE Version ID: 02 Unique ID: C2231134699-LARC_ASDC