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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, https://doi.org/10.1029/2020JD033651.

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, https://doi.org/10.5194/amt-13-3235-2020.

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, https://doi.org/10.1029/2018EA000379

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, https://doi.org/10.1109/TGRS.2019.2946963

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., https://doi.org/10.1029/2019GL083736.

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., https://doi.org/10.1029/2018GL079808.

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, https://doi.org/10.1016/j.jenvman.2021.114077

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, https://doi.org/10.1029/2020GL091511

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://doi.org/10.1029/2019JD031488

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, https://doi.org/10.5194/amt-12-2485-2019

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; https://doi.org/10.3390/rs13245061

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., doi.org/10.1029/2020GL089221.

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, https://doi.org/10.1016/j.jqsrt.2019.03.022

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., https://doi.org/10.5194/amt-2017-222.

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, https://doi.org/10.5194/amt-16-1527-2023

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), https://doi.org/10.3847/1538-3881/abd54a

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), https://doi.org/10.3847/1538-3881/ac5e2e

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: https://doi.org/10.1016/j.atmosres.2024.107268.

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, https://doi.org/10.1111/gcb.15554

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. https://doi.org/10.5194/essd-12-2209-2020

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. https://doi.org/10.5194/acp-20-8351-2020.

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, https://doi.org/10.5194/amt-11-4373-2018.

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, https://www.atmos-meas-tech.net/11/177/2018/amt-11-177-2018.pdf

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, https://doi.org/10.5194/amt-15-5877-2022.

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, https://iopscience.iop.org/article/10.3847/1538-3881/aac6e2.

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 https://doi.org/10.1029/2020EA001521.

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, https://doi.org/10.1175/BAMS-D-19-0254.1.

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. https://doi.org/10.1029/2022GL102552

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. and Szabo A. 2021. Summary of seventh DSCOVR EPIC and NISTAR Science Team Meeting. The Earth Observer, 33, 6, 24-31.

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, https://doi.org/10.1175/BAMS-D-17-0223.1.

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.

Marshak, A. and A. Ward, 2018. Summary of DSCOVR EPIC and NISTAR Science Team Meeting. The Earth Observer, 30, 6, 16-22.

Marshak, A. and Szabo A. 2023. Summary of the eighth DSCOVR EPIC and NISTAR Science Team Meeting. The Earth Observer, 34, 14-20, EO Nov-Dec 2022-Color 508.pdf

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., 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. https://doi.org/10.3390/rs11151747

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. https://doi.org/10.1016/j.jqsrt.2018.03.008

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, https://doi.org/10.1016/j.rse.2023.113511

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.

Schmidt, A. and S.A. Carn, 2022: Volcanic emissions, aerosol processes and climatic effects, In: Aerosols and Climate (Ed. K.S. Carslaw), Elsevier, https://www.sciencedirect.com/book/9780128197660/aerosols-and-climate.

Shang H., Y. Ding, H. Guo, G. Liu, X. Liu, J. Wu, L. Liang, H. Jiang, and G. Chen, 2021. Radiative Flux and Its Radiance in Moon-Based View. Remote Sens., 13(13), 2535, https://doi.org/10.3390/rs13132535

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.

Sun, J., P. Veetkind, S. Nanda, P. van Velthoven, and P. Levelt, 2019. The role of aerosol layer height in quantifying aerosol absorption from ultraviolet satellite observations. Atmos. Meas. Tech., https://doi.org/10.5194/amt-12-6319-2019

Sun, Y., Y. Knyazikhin, X. She, X. Ni, C. Chen, H. Ren, and R. B. Myneni, 2022. Seasonal and long-term variations in leaf area of Congolese rainforest. Remote Sensing of Environment, 268:112762, doi: 10.1016/j.rse.2021.112762.

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.

Su, W., P. Minnis, L. Liang, D. P. Duda, K. V. Khlopenkov, M.M. Thieman, Y. Yu, A. Smith, S. Lorentz, D. Feldman, and F. P. J. Valero, 2020. Determining the daytime Earth radiative flux from National Institute of Standards and Technology Advanced Radiometer (NISTAR) measurements. Atmos. Meas. Tech., 13, 429–443, https://doi.org/10.5194/amt-13-429-2020.

Su, W., L. Liang, D. R. Doelling, P. Minnis, D. P. Duda, K. V. Khlopenkov, M.M. Thieman, N.G. Loeb, S. Kato, F. P. J. Valero, H. Wang, and F. G. Rose, 2018. Determining the shortwave radiative flux from Earth polychromatic imaging camera. J. Geophys. Res., 123, https://doi.org/10.1029/2018JD029390.

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