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EPIC Ocean Surface PAR 1 Product V02
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.
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DSCOVR EPIC Level 2 EPICAERUV-Fast
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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 simply 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 the presence of 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.
S-MODE Seaglider Observations Version 1
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This dataset contains profiles of temperature, dissolved oxygen, salinity, and other observations collected by Seagliders during the Sub-Mesoscale Ocean Dynamics Experiment (S-MODE) field campaign. The experiment was conducted approximately 300 km offshore of San Francisco, during two intensive operating periods in Fall 2022 and Spring 2023. S-MODE aims to understand how ocean dynamics acting on short spatial scales influence the vertical exchange of physical and biological variables in the ocean. Seagliders are autonomous underwater vehicles (AUVs) designed to glide from the ocean surface to as deep as 1000 m and back whilecollecting profiles of oceanic variables. Data are available in netCDF format.
DSCOVR EPIC Level 2 O3SO2AI
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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.”
DSCOVR EPIC Level 3 PAR Image
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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 Level 2 UV Aerosol Version 3
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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.
Southwest Atlantic Ocean (SwAO) optical measurements
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Measurements made in the southwest Atlantic Ocean spanning 1995 to 2004.
DSCOVR EPIC Level 3 PAR
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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).
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