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5 years of observing Earth from L1

Lyapustin, A., Marshak, A., Schuster, G., eds. (2022). DSCOVR EPIC/NISTAR: 5 years of observing earth from the first lagrangian point. Lausanne: Frontiers Media SA. doi: 10.3389/978-2-83250-075-0

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Ahn, C., O. Torres, H. Jethva, R. Tiruchirapalli, L.-K. Huang, 2021: Evaluation of aerosol properties observed by DSCOVR/EPIC instrument from the Earth-Sun Lagrange 1 orbit, Journal of Geophysical Research: Atmospheres, 126, e2020JD033651,

Aizawa, M., H. Kawahara, and S. Fan, 2020: Global Mapping of an Exo-Earth Using Sparse Modeling. Astrophys. J., 896:22, 10.3847/1538-4357/ab8d30.

Albers, S., S.M. Saleeby, S. Kreidenweis, Q. Bian, P. Xian, Z. Toth, R. Ahmadov, E. James, and S. Miller, 2020. A fast visible-wavelength 3D radiative transfer model for numerical weather prediction visualization and forward modeling, Atmos. Meas. Tech., 13, 3235–3261, 2020,

Bah, M.K, M.M. Gunshor, and T.J. Schmit, 2018. Generation of GOES-16 True Color Imagery without a Green Band. Earth and Space Science, 5, 9, 549–558,

Bhatt R., D.R. Doelling, A. Angal, X. Xiong, C. Haney, B.R. Scarino, A. Wu, and A. Gopalan, 2019. Response Versus Scan-Angle Assessment of MODIS Reflective Solar Bands in Collection 6.1 Calibration. IEEE Transactions on Geoscience and Remote Sensing, 58, 4, 2276-2289,

Blank, K., L.-K. Huang, J. Herman, and A. Marshak, 2021. EPIC geolocation; Strategies to reduce uncertainty, Frontiers in Remote Sens., 2, doi: 10.3389/frsen.2021.715296.

Carlson, B.E., A.A. Lacis, C.M. Colose, A. Marshak, W. Su, and S. Lorentz, 2019. Spectral signature of the biosphere: NISTAR finds it in our solar system from the Lagrangian L-1 point. Geoph. Res. Lett.,

Carlson, B.E., A.A. Lacis, G. Russell, A. Marshak, and W. Su, 2022. Unique observational constraints on the seasonal and longitudinal variability of the Earth's planetary albedo and cloud distribution inferred from EPIC measurements. Frontiers in Remote Sens., 3, doi: 10.3389/frsen.2021.788525.

Carn S.A., N.A. Krotkov, B.L. Fisher and C. Li, 2022: Out of the blue: Volcanic SO2 emissions during the 2021–2022 eruptions of Hunga Tonga—Hunga Ha’apai (Tonga). Front. Earth Sci., 10:976962, doi:10.3389/feart.2022.976962.

Carn, S.A., N.A. Krotkov, B.L. Fisher, C. Li, and A.J. Prata, 2018. First observations of volcanic eruption clouds from the L1 Earth-Sun Lagrange point by DSCOVR/EPIC, Geophys. Res. Lett.,

Carn, S.A., L. Clarisse and A.J. Prata (2016), Multi-decadal satellite measurements of global volcanic degassing, J. Volcanol. Geotherm. Res., 311, 99-134, doi:10.1016/j.jvolgeores.2016.01.002.

Carn, S.A. and N.A. Krotkov (2016), UV Satellite Measurements of Volcanic Ash, In: S. Mackie, K. Cashman, H. Ricketts A. Rust, and I.M. Watson (eds.), Volcanic Ash: Hazard Observation, Elsevier, pp. 217-231, doi:10.1016/B978-0-08-100405-0.00018-5.

Carn, S.A. (2016), On the detection and monitoring of effusive eruptions using satellite SO2 measurements, In: Harris, A.J.L., T. de Groeve, F. Garel and S.A. Carn (editors),Detecting, Modeling and Responding to Effusive Eruptions, Geological Society of London, Special Publications, 426, doi:10.1144/SP426.28.

Cede, A., L.K Huang, G. McCauley, J. Herman, K. Blank, M. Kowalewski and A. Marshak, 2021. Raw EPIC data calibration, Frontiers in Remote Sens., 2, doi: 10.3389/frsen.2021.702275.

Chen J., W. Zhu, and Q. Yu, 2022. High-spatiotemporal-resolution estimation of solar energy component in the United States using a new satellite-based model. J. of Environmental Management, 302, Part B, 114077,

Choi, M., Lyapustin, A., Schuster, G. L., Go, S., Wang, Y., Korkin, S., Kahn, R., Reid, J. S., Hyer, E. J., Eck, T. F., Chin, M., Diner, D. J., Kalashnikova, O., Dubovik, O., Kim, J., and Moosmüller, H.: Light-absorbing black carbon and brown carbon components of smoke aerosol from DSCOVR EPIC measurements over North America and Central Africa, EGUsphere [preprint],, 2024.

Christian K., J. Wang, C. Ge, D. Peterson, E. Hyer, J. Yorks, and M. McGill. 2019. Radiative forcing and stratospheric warming of pyrocumulonimbus smoke aerosols: first modeling results with multi‐sensor (EPIC, CALIPSO, CATS) views from space, Geoph. Res. Lett., DOI: 10.1029/2019GL082360

Davis A., N. Ferlay, Q. Libois, A. Marshak, Y. Yang and Q. Min, 2018. Cloud information content in EPIC/DSCOVR's oxygen A- and B-band channels: A physics-based approach. J. Quant. Spectrosc. Radiat. Transfer, 220, 84–96, doi:10.1016/j.jqsrt.2018.09.006.

Davis A., G. Merlin, L. Labonnote, J. Riedi, C. Cornet, P. Dubuisson, N. Ferlay, Q. Min, Y. Yang and A. Marshak, 2018. Cloud information content in EPIC/DSCOVR's oxygen A- and B-band channels: An optimal estimation approach. J. Quant. Spectrosc. Radiat. Transfer, 216, 6–16, doi:10.1016/j.jqsrt.2018.05.007.

Davis, A., Y. Yang and A. Marshak, 2022. EPIC/DSCOVR as a pathfinder in cloud remote sensing using differential oxygen absorption spectroscopy. Frontiers in Remote Sens., 3, doi: 10.3389/frsen.2022.796273.

Delgado-Bonal, A., A. Marshak, Y. Yang and L. Oreopoulus, 2021. Global daytime variability of clouds from DSCOVR/EPIC observations. GRL,

Delgado-Bonal, A., A. Marshak, L. Oreopoulus, and Y. Yang, 2022, Cloud height daytime variability from DSCOVR/EPIC and GOES-R observations, Frontiers in Remote Sens., 3, doi: 10.3389/frsen.2022.780243.

Delgado-Bonal, A., A. Marshak, Y. Yang, and L. Oreopoulos, 2020. Daytime variability of cloud fraction from DSCOVR/EPIC observations, Journal of Geophysical Research: Atmospheres, 125, e2019JD031488, doi://

Delgado-Bonal, A., A. Marshak, Y. Yang and L. Oreopoulus, 2024. Global cloud optical depth daily variability based on DSCOVR/EPIC observations. Frontiers in Remote Sens., 5, doi: 10.3389/frsen.2024.1390683.

Desmons M., P. Wang, P. Stammes, and L.G. Tilstra, 2019. FRESCO-B: a fast cloud retrieval algorithm using oxygen B-band measurements from GOME-2. Atmos. Meas. Tech., 12, 2485-2598,

Doelling, D., C. Haney, R. Bhatt, B. Scarino, A. Gopalan (2019). The Inter-Calibration of the DSCOVR EPIC Imager with Aqua-MODIS and NPP-VIIRS, Remote Sens. 2019, 11,1609; doi:10.3390/rs11131609

Doelling, D., K. Khlopenkov, C. Haney, R. Bhatt, B. Bos, B. Scarino, A. Gopalan and D. S. Lauretta, 2019. Inter-Calibration of the OSIRIS-REx NavCams with Earth-Viewing Imagers. Remote Sens., 11, 2717; doi:10.3390/rs11222717.

Doicu, A., A. Doicu, D. Efremenko, D. Loyola and T. Trautmann, 2021. An Overview of Neural Network Methods for Predicting Uncertainty in Atmospheric Remote Sensing. Remote Sens., 13(24), 5061;

Fan, S., C. Li, J.-Z. Li, S. Barlett, J. H. Jiang, V. Natraj, D. Crisp, and Y.L. Yung, 2019: Earth as an Exoplanet: A Two-Dimensional Alien Map. Astrophys. J. Lett., 882, 10.3847/2041-8213/ab3a49.

Feldman, D.R., W. Su, and P. Minnis, 2021. Sub-diurnal to interannual frequency analysis of observed and modeled reflected shortwave radiation from Earth. Geoph. Res. Lett.,

Fisher, B.L., N.A. Krotkov, P.K. Bhartia, C. Li, S.A. Carn, E. Hughes, and P.J.T. Leonard, 2019: A new discrete wavelength backscattered ultraviolet algorithm for consistent volcanic SO2 retrievals from multiple satellite missions, Atmos. Meas. Tech., 12, 5137-5153, doi:10.5194/amt-12-5137-2019.

Frouin R., J. Tan and H. Herman, 2022: Ocean color remote sensing from the L1 orbit, Proceedings of Oceans from Space V Symposium, Scuola Grande di San Marco, Venice (Italy), 24-28 October 2022, V Barale, JFR Gower, l Alberotanza, Eds., 32-33, doi: 10.57648/OceansFromSpaceV-2022-PROCEEDINGS.

Frouin R., J. Tan, D. Ramon, B. Franz, H. 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.

Frouin, R., J. Tan, M. Compiegne, D. Ramon, M. Sutton, H. Murakami, D. Antoine, U. Send, J. Sevadjian and V. Vellucci, 2022. The NASA EPIC/DSCOVR Ocean PAR Product, Frontiers in Remote Sens., 3, doi: 10.3389/frsen.2022.833340.

Gao, B.-C., R.-R. Li, and Y. Yang. 2019. Remote Sensing of Daytime Water Leaving Reflectances of Oceans and Large Inland Lakes from EPIC onboard the DSCOVR Spacecraft at Lagrange-1 Point. Sensors, 19 (5), 1243 [10.3390/s19051243]

Gao, M. (616/SSAI), Zhai, P., Yang, Y. (613), Hu, Y. (NASA LaRC), 2019: "Cloud remote sensing with EPIC/DSCOVR observations: a sensitivity study with radiative transfer simulations," Journal of Quantitative Spectroscopy and Radiative Transfer, 230 (2019), 56-60,

Geogdzhaev, I.V., A. Marshak, and M. Alexandrov, 2021. Calibration of the DSCOVR EPIC visible and NIR channels using multiple LEO radiometers, Frontiers in Remote Sens., 2, doi: 10.3389/frsen.2021.671933

Geogdzhayev, I.V. and A. Marshak, (2018). Calibration of the DSCOVR EPIC visible and NIR channels using MODIS and EPIC lunar observations, Atmos. Meas. Tech.,

Go, S., A. Lyapustin, G.L. Schuster, M. Choi, P. Ginoux, M. Chin, O. Kalashnikova, O. Dubovik, J. Kim, A. da Silva and B. Holben, 2022. Inferring iron-oxide species content in atmospheric mineral dust from DSCOVR EPIC observations. Atmos. Chem. Phys., 22, 1395-1423, doi: 10.5194/acp-22-1395-2022.

Gorkavyi, N., N. Krotkov, and A. Marshak, 2023. Earth Observations from the Moon surface: dependence on lunar libration, Atm. Measur. Tech., 16. 6, 1527-1537,

Gorkavyi, N., S. Carn, M. DeLand, Y. Knyazikhin, N. Krotkov, A. Marshak, A. Vasilkov, 2021. Earth imaging from the Moon surface with the DSCOVR/EPIC-type camera, Frontiers in Remote Sens., 2, doi: 10.3389/frsen.2021.724074.

Gu L., S. Fan, J. Li, G. Liu, S. Bartlett, V. Natraj, J. Jiang, Y. Crisp, H. Hu, G. Tinetti, and Y. Yung, 2021. Earth as a Proxy Exoplanet: Deconstructing and Reconstructing Spectrophotometric Light Curves. The Astronomical Journal, 161:122 (13pp),

Gu L., Z.C. Zeng, S. Fan, V. Natraj, J.H. Jiang, D. Crisp, Y.L. Yung, and Y. Hu, 2021. Earth as a Proxy Exoplanet: Simulating DSCOVR/EPIC Observations Using the Earth Spectrum Simulator. The Astronomical Journal, 163:285 (16pp),

Gui L., M. Tao, L. Xu, Y. Wang, J. Wang, L. Wang, and L. Chan, 2024: Performance of DSCOVR/EPIC diurnal aerosol products over China: Ground validation and intercomparison, Atmos. Res., doi:

Haney C., D. Doelling, W. Su, R. Bhatt, A. Gopalan, B. Scarino, 2021. Radiometric stability assessment of the DSCOVR EPIC visible bands using MODIS, VIIRS, and invariant targets as independent references. Front. Remote Sens. 2, doi: 10.3389/frsen.2021.765913.

Hao, D., G.R. Asrar, Y. Zeng, Q. Zhu, J. Wen, Q. Xiao, and M. Chen, 2019. Estimating hourly land surface downward shortwave and photosynthetically active radiation from DSCOVR/EPIC observations. Remote Sensing of Environment, 232, 111320. doi: 10.1016/j.rse.2019.111320

Hao, D., G.R. Asrar, Y. Zeng, X. Yang, X. Li, J. Xiao, K. Guan, J. Wen, Q. Xiao, J. Berry and M. Chen, 2021. Potential of hotspot solar-induced chlorophyll fluorescence for better tracking terrestrial photosynthesis. Global Change Biology, 27, 2144–2158,

Hao, D., G.R. Asrar, Y. Zeng, Q. Zhu, J. Wen, Q. Xiao, and M. Chen, 2020. DSCOVR/EPIC-derived global hourly and daily downward shortwave and photosynthetically active radiation data at 0.1° × 0.1° resolution. Earth Syst. Sci. Data, 12, 2209–2221, 2020.

Herman, J., A. Cede, L. Huang, J. Ziemke, O. Torres, N. Krotkov, M. Kowalewski, K. Blank, 2020: Global Distribution and 14-Year Changes in Erythemal Irradiance, UV Atmospheric Transmission, and Total Column Ozone 2005–2018 Estimated from OMI and EPIC Observations, Atmos. Chem. Phys.

Herman J., G. Wen, A. Marshak, K. Blank, L. Huang, A. Cede, N. Abuhassan, and M. Kowalewski, 2018. Reduction in Earth Reflected Irradiance during the Eclipse of 21 August 2017. Atmos. Meas. Tech., 11, 4373-4388,

Herman, J.R., L. Huang, R.D. McPeters, J. Ziemke, A. Cede, and K. Blank (2018). Synoptic ozone, cloud reflectivity, and erythemal irradiance from sunrise to sunset for the whole Earth as viewed by DSCOVR spacecraft from the earth-sun Lagrange-1, Atmos. Meas. Tech., 11, 177-194,

Holdaway, D. and Y. Yang, 2016: Study of the Effect of Temporal Sampling Frequency on DSCOVR Observations Using the GEOS-5 Nature Run Results (Part II): Cloud Coverage. Remote Sens., 8(5), 431, doi:10.3390/rs8050431.

Holdaway, D. and Y. Yang, 2016: Study of the Effect of Temporal Sampling Frequency on DSCOVR Observations Using the GEOS-5 Nature Run Results (Part I): Earth’s Radiation Budget. Remote Sens. 2016, 8(2), 98; doi:10.3390/rs8020098.

Huang, X. and Yang, K., 2022: Algorithm theoretical basis for ozone and sulfur dioxide retrievals from DSCOVR EPIC, Atmos. Meas. Tech., 15, 5877–5915,

Jiang, J.H., A.J. Zhai, J. Herman, C. Zhai, R. Hu, H. Su, V. Natraj, J. Li, F. Xu and Y.L. Yung, 2018: Using Deep Space Climate Observatory Measurements to Study the Earth as an Exoplanet. The Astron. J., 156:26,

Kramarova, N.A., J.R. Zimke, L.-K. Huang and J.R. Herman, 2021. Evaluation of Version 3 total and tropospheric ozone columns from EPIC on DSCOVR for studying regional scale ozone variations, Frontiers in Remote Sens., 2, doi: 10.3389/frsen.2021.734071.

Kawahara, H., 2020: Global Mapping of the Surface Composition on an Exo-Earth using Color Variability. Astrophys. J., 894:58, 10.3847/1538-4357/ab87a1.

Kawahara, H. and K. Masuda, 2020: Bayesian Dynamic Mapping of an Exo-Earth from Photometric Variability. The Astron. J., 900:48, 10.3847/1538-4357/aba95e.

Kostinski, A., A. Marshak, and T. Varnai, 2021. Deep space observations of terrestrial glitter, Earth and Space Science, 8, e2020EA001521

Kostinski, A., A. Marshak, and T. Varnai, 2024. Deep space observations of longitudinally averaged global reflectance patterns, Frontiers in Remote Sens., 5, doi: 10.3389/frsen.2024.1404461.

Lacis, A.A., B.E. Carlson, G. Russell, A. Marshak, and W. Su, 2022. NISTAR and EPIC inspired climate GCM diagnostics of the Earth’s planetary albedo and cloud distribution via longitudinal data slicing. Frontiers in Remote Sens., 3, doi: 10.3389/frsen.2022.766917.

Li, J.-Z., S. Fan, P. Kopparla, C. Liu, J. Jiang, V. Natraj, and Y. Yung, 2019. Study of terrestrial glints based on DSCOVR observations. Earth and Space Sci., 10.1029/2018EA000509.

Lim Y.-K., D.I. Wu, K.-M. Kim and J.N. Lee, 2021, An Investigation on Seasonal and Diurnal Cycles of TOA Shortwave Radiations from DSCOVR/EPIC, CERES, MERRA-2, and ERA5, Remote Sensing 13(22):4595, doi: 10.3390/rs13224595.

Lopez P., 2020. Forecasting the Past: Views of Earth from the Moon and Beyond. Bulletin Amer. Meteor. Soc. (BAMS), 7, 1190-1200,

Lu, Z., J. Wang, X. Chen, J. Zeng, Y. Wang, X. Xu, K.E. Christian, J.E. Yorks, E.P. Mowottnick, J.S. Reid, and P. Xiang, 2023. First mapping of monthly and diurnal climatology of Saharan dust layer height over the Atlantic Ocean from EPIC/DSCOVR in deep space. Geophysical Research Letters, 50, e2022GL102552.

Lu Z., J. Wang, X. Xu, X. Chen, S. Kondragunta, O. Torres, E. M. Wilcox and J Zeng, 2021. Hourly mapping of the layer height of thick smoke plumes over the western U.S. in 2020 severe fire season. Front. Remote Sens. 2, doi: 10.3389/frsen.2021.766628.

Lyapustin, A., Y. Wang, S. Go, M. Choi, S. Korkin, D. Huang, Y. Knyazihnin, K. Blank and A. Marshak, 2021. Atmospheric correction of DSCOVR EPIC: Version 2 MAIAC algorithm. Frontiers in Remote Sens., 2, doi: 10.3389/frsen.2021.748362.

Lyapustin, A., S. Go, S. Korkin, Y. Wang, O. Torres, H. Jethva and A. Marshak, A., 2021. Retrievals of Aerosol Optical Depth and Spectral Absorption from DSCOVR EPIC. Frontiers in Remote Sensing, 2, doi: 10.3389/frsen.2021.645794.

Marshak, A., 2020. Summary of fifth DSCOVR EPIC and NISTAR Science Team Meeting. The Earth Observer, 32, 1, 29-34.

Marshak, A., 2020. Summary of sixth DSCOVR EPIC and NISTAR Science Team Meeting. The Earth Observer, 32, 6, 39-44.

Marshak A., A. Delgado-Bonal and Y. Knyazikhin, 2021. The effect of scattering angle on Earth reflectance, Frontiers in Remote Sens., 2, doi: 10.3389/frsen.2021.719610.

Marshak, A., J. Herman, A. Szabo, K. Blank, A. Cede, S. Carn, I. Geogdzhaev, D. Huang, L.-K. Huang, Y. Knyazikhin, M. Kowalewski, N. Krotkov, A. Lyapustin, R. McPeters, K. Meyer, O. Torres and Y. Yang, 2018. Earth Observations from DSCOVR/EPIC Instrument. Bulletin Amer. Meteor. Soc. (BAMS), 9, 1829-1850,

Marshak, A., T. Varnai and A. Kostinski, 2017. Terrestrial glint seen from deep space: oriented ice crystals detected from the Lagrangian point. Geoph. Res. Lett., 44, doi:10.1002/2017GL073248.

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Marshak, A. and Y. Knyazikhin, 2017: The spectral invariant approximation within canopy radiative transfer to support the use of the EPIC/DSCOVR oxygen B-band for monitoring vegetation. J. Quant. Spectrosc. Radiat. Trans., 191, 7-12, doi:10.1016/j.jqsrt.2017.01.015.

Meyer, K., Y. Yang, and S. Platnick, 2016: Uncertainties in cloud phase and optical thickness retrievals from the Earth Polychromatic Imaging Camera (EPIC), Atmos. Meas. Tech., 9, 1785-1797, doi:10.5194/amt-9-1785-2016.

Molina García, V., 2022. Retrieval of cloud properties from EPIC/DSCOVR. Dissertation, Technical University of Munich, .

Molina García, V., S. Sasi , D.S. Efremenko and D. Loyola, 2019. Improvement of EPIC/DSCOVR Image Registration by Means of Automatic Coastline Detection. Remote Sensing, 11(15), 1747.

Molina García, V., S. Sasi, D.S. Efremenko, A. Doicu, and D. Loyola, 2018. Radiative transfer models for retrieval of cloud parameters from EPIC/DSCOVR measurements. J. Quant. Spectrosc. Radiat. Transf., 123 228–240. doi:10.1016/j.jqsrt.2018.03.014

Molina García, V., S. Sasi, D.S. Efremenko, A. Doicu, and D. Loyola, 2018. Linearized radiative transfer models for retrieval of cloud parameters from EPIC/DSCOVR measurements. J. Quant. Spectrosc. Radiat. Transf., 213, 241–251.

Ni, X., Knyazikhin, Y., Sun, Y., She, X., Guo, W., Panferov, O., & Myneni, R.B. (2021). Vegetation angular signatures of equatorial forests from DSCOVR EPIC and Terra MISR observations. Frontiers in Remote Sensing, 2, doi: 10.3389/frsen.2021.766805

Penttilä A., K. Muinonen, O. Ihalainen, E. Uvarova, M. Vuori, G. Xu, J. Näränen, O. Wilkman, J. Peltoniemi, M. Gritsevich, H. Järvinen, A. Marshak, 2022. Temporal variation of the shortwave albedo of the Earth. Frontiers in Remote Sens., 3, doi: 10.3389/frsen.2022.790723.

Pisek, J., A. Odera, M. Kaha, L. Korhonen, A. Erb, A. Marshak, Y. Knyazikhin, 2022. First validation of Earth Reflector Type Index (p) parameter from DSCOVR EPIC VESDR data product using Australian terrestrial ecosystem research network observing sites, Remote Sens. Envir., v. 288,

Pisek, J., S.K. Arndt, A. Erb, E. Pendall, C. Schaaf, T.I. Wardlaw, W. Woodgate, Y. Knyazikhin, 2021: Exploring the Potential of DSCOVR EPIC Data to Retrieve Clumping Index in Australian Terrestrial Ecosystem Research Network Observing Sites. Frontiers in Remote Sensing, 2, doi: 10.3389/frsen.2021.652436

Sasi, S., V. Natraj, V. Molina-Garcia, D.S. Efremenko, D. Loyola, and A. Doicu, 2020: Model Selection in Atmospheric Remote Sensing with an Application to Aerosol Retrieval from DSCOVR/EPIC, Part 1: Theory, Remote Sensing, 12, 22, 10.3390/rs12223724.

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Song, W., X. Mu, T. R. McVicar, Y. Knyazikhin, X. Liu, L. Wang, Z. Niu, and G. Yan, 2022. Global quasi-daily fractional vegetation cover estimated from the DSCOVR EPIC directional hotspot dataset. Remote Sensing of Environment 269:112835. doi: 10.1016/j.rse.2021.112835.

Song, W., Y. Knyazikhin, G. Wen, A. Marshak, M. Mõttus, G. Yan, B. Yang, B. Xu, T. Park, C. Chen, Y. Zeng, G. Yan, X. Mu and R. Myneni, 2018. Implications of Whole-Disc DSCOVR EPIC Spectral Observations for Estimating Earth’s Spectral Reflectivity Based on Low-Earth-Orbiting and Geostationary Observations. Remote Sens., 2018, 10, 1594, doi:10.3390/rs10101594. Direct Download.

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Su, W., L. Liang, D.P. Duda, K. Khlopenkov and M.M. Thieman, 2021. Global daytime mean shortwave flux consistency under varying EPIC viewing geometries, Frontiers in Remote Sens., 2, 10.3389/frsen.2021.747859.

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Tian Q., Q. Liu, J. Guang, L. Yang, H. Zhang, C. Fan, Yahui Che, and Z. Li, 2020: The Estimation of Surface Albedo from DSCOVR EPIC, Remote Sensing , V. 12; doi:10.3390/rs12111897.

Torres O. and C. Ahn, 2024: Local and Regional Diurnal Variability of Aerosol Properties Retrieved by DSCOVR/EPIC UV Algorithm. Journal of Geophysical Research: Atmospheres, 129(8), DOI: 10.1029/2023JD039908.

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Valero, F.P.J, A. Marshak and P. Minnis, 2021. Lagrange Point Missions: The key to next generation integrated Earth observations. DSCOVR innovation, Frontiers in Remote Sens., 2, doi: 10.3389/frsen.2021.745938

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