DSCOVR_EPIC_L2_AER_03 is the Deep Space Climate Observatory (DSCOVR) Enhanced Polychromatic Imaging Camera (EPIC) Level 2 UV Aerosol Version 3 data product. Observations for this data product are at 340 and 388 nm and are used to derive near UV (ultraviolet) aerosol properties. The EPIC aerosol retrieval algorithm (EPICAERUV) uses a set of aerosol models to account for the presence of carbonaceous aerosols from biomass burning and wildfires (BIO), desert dust (DST), and sulfate-based (SLF) aerosols. These aerosol models are identical to those assumed in the OMI (Ozone Monitoring Instrument) algorithm (Torres et al., 2007; Jethva and Torres, 2011). Aerosol data products generated by the EPICAERUV algorithm are aerosol extinction optical depth (AOD) and single scattering albedo (SSA) at 340, 388, and 500 nm for clear sky conditions. AOD of absorbing aerosols above clouds is also reported (Jethva et al., 2018). In addition, the UV Aerosol Index (UVAI) is calculated from 340 and 388 nm radiances for all sky conditions. AOD is a dimensionless measure of the extinction of light y aerosols due to the combined effect of scattering and absorption. SSA represents the fraction of extinction solely due to aerosol scattering effects. The AI is a residual parameter that quantifies the difference in spectral dependence between measured and calculated near UV radiances, assuming a purely molecular atmosphere. Because most of the observed positive residuals are associated with absorbing aerosols, this parameter is commonly known as the UV Absorbing Aerosol Index. EPIC-derived aerosol parameters are reported at a 10 km (nadir) resolution.

Robust cloud products are critical for Deep Space Climate Observatory (DSCOVR) to contribute to climate studies significantly. Building on our team’s track record in cloud detection, cloud property retrieval, oxygen band exploitation, and DSCOVR-related studies, we propose to develop a suite of algorithms for generating the operational Earth Polychromatic Imaging Camera (EPIC) cloud mask, cloud height, and cloud optical thickness products. Multichannel observations will be used for cloud masking; the cloud height will be developed with information from the oxygen A- and B- band pairs (780 nm vs. 779.5 nm and 680 nm vs. 687.75 nm); for the cloud optical thickness retrieval, we propose an approach that combines the EPIC 680 nm observations and numerical weather model outputs. Preliminary results from radiative transfer modeling and proxy data applications show that the proposed algorithms are viable.Product validation will be conducted by comparing EPIC observations/retrievals with counterparts from coexisting Low Earth Orbit (LEO) and Geosynchronous Earth Orbit (GEO) satellites. The proposed work will include a rigorous uncertainty analysis based on theoretical and computational radiative transfer modeling that complements standard validation activities with physics-based diagnostics. We also plan to evaluate and improve the calibration of the EPIC O2 A- and B-band absorption channels by tracking the instrument performance over known targets, such as cloud-free ocean and ice sheet surfaces.The deliverables for the proposed work include an Algorithm Theoretical Basis Document (ATBD) for peer review, products generated with the proposed algorithms, and supporting research articles. The data products, which will be archived at the Atmospheric Science Data Center (ASDC) at the NASA Langley Research Center, will provide essential inputs needed for the community to apply EPIC observations to climate research and to interpret better The National Institute of Standards and Technology Advanced Radiometer (NISTAR) observations.The proposed work directly responds to the solicitation to “develop and implement the necessary algorithms and processes to enable various data products from EPIC sunrise to sunset observations once on orbit” and improve “the calibration of EPIC based on in-flight data.”

EPIC Tropospheric Ozone Data ProductThe 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 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. 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 a high spatial resolution of 18 × 18 km2 near the center of the image, the TCO maps are spatially averaged over several EPIC pixels and written on a regular spatial grid (1° latitude x 1° longitude). Kramarova et al. (2021) describe 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 ConventionThe 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 AdjustmentThere 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 depended 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 the replay method. Our analysis (Kramarova et al., 2021) indicated that the adjusted TCO array is more accurate and precise. Flagging Bad DataKramarova et al. (2021) note that the preferred EPIC total ozone measurements used for scientific study are those where the L2 “AlgorithmFlag” parameter equals 1, 101, or 111. In this TCO product, we have included only L2 total ozone pixels with these algorithm flag values. The TCO product files provide a gridded version of the AlgorithmFlag parameter as a comparison reference. Still, 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 an 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

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.

DSCOVR_EPIC_L2_SO2_v03 is the Deep Space Climate Observatory (DSCOVR) Enhanced Polychromatic Imaging Camera (EPIC) Level 2 Sulfur Dioxide (SO2) product with EPIC version 03 inputs. It has key ultraviolet (UV) channels suitable for retrieving volcanic sulfur dioxide (SO2) and ash, enabling timely tracking and forecasting of volcanic plumes and enhancing our ability to mitigate aviation hazards. EPIC measurements will also be co-located with all satellite UV and infrared sensors, offering ample opportunities for data inter-comparisons and demonstrating advanced retrievals of volcanic ash mass through a synergistic approach. We propose to implement our mature algorithms previously developed for Total Ozone Mapping Spectrometer (TOMS) and Ozone Monitoring Instrument (OMI) to enable SO2 and Ash Index (AI) products from EPIC UV observations to demonstrate improved estimates of volcanic SO2 and ash mass, height and sulfate aerosol loading.

DSCOVR_EPIC_L2_TO3_v03 is Level2 Total Ozone derived from the Deep Space Climate Observatory (DSCOVR) Earth Polychromatic Imaging Camera (EPIC) using Level 1b version 3 inputs and version 3 ozone retrieval algorithm. The measurements from four EPIC UV (ultraviolet) channels derive the global distributions of total ozone over the entire sunlit portion of the Earth. A new soft calibration technique developed based on scene matching with OMPS gives calibrated EPIC radiances. The calibrated EPIC radiances derive science-quality total ozone products from EPIC consistent with those from other UV instruments. The retrieval algorithm uses wavelength triplets and assumes that the scene reflectivity changes linearly with wavelength. Version 3 algorithm includes several key modifications aimed to improve total ozone retrievals: a) switch to Version 3 Level 1b product with improved geolocation registration, flat field, and dark counts corrections; b) replace OMI-based (Ozone Monitoring Instrument) cloud height climatology with the simultaneous EPIC A-Band cloud height; c) update absolute calibrations using polar orbiting the NASA OMPS SNPP ( Ozone Mapping and Profiler Suite / Suomi National Polar-orbiting Partnership Ozone); d) add corrections for ozone profile shape and temperature; e) update algorithm and error flags to filter data; f) add column weighting functions for each observation to facilitate error analysis. EPIC ozone retrievals accurately capture short-term synoptic changes in total column ozone. With EPIC measurements from DSCOVR's vantage point, synoptic ozone maps can be derived every 1-2 hours. Scene Reflectivity (clouds, aerosols, and surface) is derived from ozone retrieval. In conjunction with ozone, the scene reflectivity has been used to derive the amount of UV solar radiation reaching the ground, and surface UV Erythemal is also reported in these files.

DSCOVR_EPIC_L3_PAR-image_01 is a view image showing data from DSCOVR_EPIC_L3_PAR, which is the Deep Space Climate Observatory (DSCOVR) Earth Polychromatic Imaging Camera (EPIC) Level 3 photosynthetically available radiation (PAR) version 1 data product. The EPIC observations of the Earth’s surface lit by the Sun made 13 times during the day in spectral bands centered on 443, 551, and 680 nm are used to estimate daily mean PAR at the ice-free ocean surface. PAR is defined as the quantum energy flux from the Sun in the 400-700 nm range. Daily mean PAR is the 24-hour averaged planar flux in that spectral range reaching the surface. It is expressed in E.m-2.d-1 (Einstein per meter squared per day). The factor required to convert E.m-2 d-1 units to mW.cm-2.µm-1 units are equal to 0.838 to an inaccuracy of a few percent regardless of meteorological conditions. The EPIC daily mean PAR product is generated on Plate Carrée (equal-angle) grid with an 18.4 km resolution at the equator and on an 18.4 km equal-area grid, i.e., the product is compatible with Ocean Biology Processing Group ocean color products.The EPIC PAR algorithm uses a budget approach, in which the solar irradiance reaching the surface is obtained by subtracting from the irradiance arriving at the top of the atmosphere (known), the irradiance reflected space (estimated from the EPIC Level 1b radiance data), taking into account atmospheric transmission (modeled). Clear and cloudy regions within a pixel do not need to be distinguished. This dismisses the need for often-arbitrary assumptions about cloudiness distribution and is therefore adapted to the relatively large EPIC pixels. A daily mean PAR is estimated on the source grid for each EPIC instantaneous daytime observation, assuming no cloudiness changes during the day, and the individual estimates are remapped and weight-averaged using the cosine of the Sun zenith angle. In the computations, wind speed, surface pressure, and water vapor amount are extracted from NCEP (National Centers for Environmental Prediction) Reanalysis 2 data, aerosol optical thickness, and angstrom coefficient from MERRA-2 (Modern-Era Retrospective analysis for Research and Applications, Version 2) data, and ozone amount from EPIC Level 2 data. Areas contaminated by sun glint are excluded using a threshold on sun glint reflectance calculated using wind data. Ice masking is based on NSIDC (National Snow and Ice Data Center) near real-time ice fraction data. Additional information about the EPIC ocean surface PAR products can be found at the NASA DSCOVR: EPIC website: https://epic.gsfc.nasa.gov/, under “Science -> Products -> Ocean Surface” (https://epic.gsfc.nasa.gov/science/products/ocean).

DSCOVR_EPIC_L3_PAR_01 is the Deep Space Climate Observatory (DSCOVR) Earth Polychromatic Imaging Camera (EPIC) Level 3 photosynthetically available radiation (PAR) version 1 data product. The EPIC observations of the Earth’s surface lit by the Sun made 13 times during the day in spectral bands centered on 443, 551, and 680 nm are used to estimate daily mean PAR at the ice-free ocean surface. PAR is defined as the quantum energy flux from the Sun in the 400-700 nm range. Daily mean PAR is the 24-hour averaged planar flux in that spectral range reaching the surface. It is expressed in E.m-2.d-1 (Einstein per meter squared per day). The factor required to convert E.m-2 d-1 units to mW.cm-2.µm-1 units are equal to 0.838 to an inaccuracy of a few percent regardless of meteorological conditions. The EPIC daily mean PAR product is generated on Plate Carrée (equal-angle) grid with an 18.4 km resolution at the equator and on an 18.4 km equal-area grid, i.e., the product is compatible with Ocean Biology Processing Group ocean color products.The EPIC PAR algorithm uses a budget approach, in which the solar irradiance reaching the surface is obtained by subtracting from the irradiance arriving at the top of the atmosphere (known), the irradiance reflected space (estimated from the EPIC Level 1b radiance data), taking into account atmospheric transmission (modeled). Clear and cloudy regions within a pixel do not need to be distinguished. This dismisses the need for often-arbitrary assumptions about cloudiness distribution and is therefore adapted to the relatively large EPIC pixels. A daily mean PAR is estimated on the source grid for each EPIC instantaneous daytime observation, assuming no cloudiness changes during the day, and the individual estimates are remapped and weight-averaged using the cosine of the Sun zenith angle. In the computations, wind speed, surface pressure, and water vapor amount are extracted from NCEP (National Centers for Environmental Prediction) Reanalysis 2 data, aerosol optical thickness, and angstrom coefficient from MERRA-2 (Modern-Era Retrospective analysis for Research and Applications, Version 2) data, and ozone amount from EPIC Level 2 data. Areas contaminated by sun glint are excluded using a threshold on sun glint reflectance calculated using wind data. Ice masking is based on NSIDC (National Snow and Ice Data Center) near real-time ice fraction data. Additional information about the EPIC ocean surface PAR products can be found at the NASA DSCOVR: EPIC website: https://epic.gsfc.nasa.gov/, under “Science -> Products -> Ocean Surface” (https://epic.gsfc.nasa.gov/science/products/ocean).

Robust cloud products are critical for the Deep Space Climate Observatory (DSCOVR) to contribute significantly to climate studies. Building on our team’s track record in cloud detection, cloud property retrieval, oxygen band exploitation, and DSCOVR-related studies, we propose to develop a suite of algorithms for generating the operational Earth Polychromatic Imaging Camera (EPIC) cloud mask, cloud height, and cloud optical thickness products. Multichannel observations will be used for cloud masking; the cloud height will be developed with information from the oxygen A- and B- band pairs (780 nm vs. 779.5 nm and 680 nm vs. 687.75 nm); for the cloud optical thickness retrieval, we propose an approach that combines the EPIC 680 nm observations and numerical weather model outputs. Preliminary results from radiative transfer modeling and proxy data applications show that the proposed algorithms are viable.Product validation will be conducted by comparing EPIC observations/retrievals with counterparts from coexisting Low Earth Orbit (LEO) and Geosynchronous Earth Orbit (GEO) satellites. The proposed work will include a rigorous uncertainty analysis based on theoretical and computational radiative transfer modeling that complements standard validation activities with physics-based diagnostics. We also plan to evaluate and improve the calibration of the EPIC O2 A- and B-band absorption channels by tracking the instrument performance over known targets, such as cloud-free ocean and ice sheet surfaces.The deliverables for the proposed work include an Algorithm Theoretical Basis Document (ATBD) for peer review, products generated with the proposed algorithms, and supporting research articles. The data products, archived at the Atmospheric Science Data Center (ASDC) at the NASA Langley Research Center, will provide essential inputs needed for the community to apply EPIC observations to climate research and better interpret The National Institute of Standards and Technology Advanced Radiometer (NISTAR) observations.The proposed work directly responds to the solicitation to “develop and implement the necessary algorithms and processes to enable various data products from EPIC sunrise to sunset observations once on orbit” and improve “the calibration of EPIC based on in-flight data.”

EPIC Ocean Surface PAR The EPIC observations of the Earth’s surface lit by the Sun made 13 times during the day in spectral bands centered on 443, 551, and 680 nm are used to estimate daily mean photosynthetically available radiation (PAR) at the ice-free ocean surface. PAR is defined as the quantum energy flux from the Sun in the 400-700 nm range. Daily mean PAR is the 24-hour averaged planar flux in that spectral range reaching the surface. It is expressed in E.m-2.d-1 (Einstein per meter squared per day). The factor required to convert E.m-2 d-1 units to mW.cm-2.μm-1 units is equal to 0.838 to an inaccuracy of a few percent regardless of meteorological conditions. The EPIC daily mean PAR product is generated on Plate Carrée (equal-angle) grid with 18.4 km resolution at the equator and on 18.4 km equal-area grid, i.e., the product is compatible with Ocean Biology Processing Group ocean color products.The EPIC PAR algorithm uses a budget approach, in which the solar irradiance reaching the surface is obtained by subtracting from the irradiance arriving at the top of the atmosphere (known) the irradiance reflected to space (estimated from the EPIC Level 1b radiance data), taking into account atmospheric transmission (modeled). Clear and cloudy regions within a pixel do not need to be distinguished, which dismisses the need for often-arbitrary assumptions about cloudiness distribution and is therefore adapted to the relatively large EPIC pixels. A daily mean PAR is estimated on the source grid for each EPIC instantaneous daytime observation, assuming no cloudiness change during the day, and the individual estimates are remapped and weight-averaged using the cosine of the Sun zenith angle. In the computations, wind speed, surface pressure, and water vapor amount are extracted from NECP Reanalysis 2 data, aerosol optical thickness and angstrom coefficient fromMERRA-2 data, and ozone amount from EPIC Level 2 data. Areas contaminated by sun glint are excluded using a threshold on sun glint reflectance calculated using wind data. Ice masking is based on NSIDC near real time ice fraction data. Details about the algorithm are given in Frouinet al., (2018). Figure A1 gives an example of EPIC daily mean PAR product. Date is March 20, 2018(equinox); land is in black and sea ice in white. Values range from a few E.m-2.d-1at high latitudes to about 58 E.m-2.d-1 at equatorial and tropical latitudes, with atmospheric perturbances modulating the surface PAR field especially at middle latitudes. The EPIC ocean surface PAR products are available at the Atmospheric Science Data Center (ASDC) at NASA Langley Research Center: https://asdc.larc.nasa.gov. 4. Reference Robert Frouin, Jing Tan, Didier Ramon, Bryan Franz, Hiroshi Murakami, 2018: Estimating photosynthetically available radiation at the ocean surface from EPIC/DSCOVR data, Proc. SPIE 10778, Remote Sensing of the Open and Coastal Ocean and Inland Waters, 1077806 (24 October 2018); doi: 10.1117/12.2501675. Changes from version 1 1) Algorithm (consistent with PACE) Updated the calculation of atmospheric reflectance, gaseous transmittance, and atmospheric transmittance using LUTs method so that calculations are accurate at high Sun and view zenith angles; Updated the calculation of surface albedo (based on Jin et al., 2011); Updated the calculation of cloud/surface layer albedo. 2)Ancillary data Changed the sources of the ancillary data including wind speed, surface pressure, and water vapor from NCEP to MERRA2; Added cloud fraction from MERRA2, which is needed for computing direct/diffuse ratio hence surface albedo.