Browsing by Author "Marshak, Alexander"
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Item Aerosol Properties in Partly Cloudy Regions(2018-10) Varnai, Tamas; Marshak, Alexander; Wen, Guoyong; Levy, Robert; Eck, ThomasItem Analysis of Near-Cloud Changes in Atmospheric Aerosols Using Satellite Observations and Global Model Simulations(MDPI, 2021-03-17) Várnai, Tamás; Marshak, AlexanderThis paper examines cloud-related variations of atmospheric aerosols that occur in partly cloudy regions containing low-altitude clouds. The goal is to better understand aerosol behaviors and to help better represent the radiative effects of aerosols on climate. For this, the paper presents a statistical analysis of a multi-month global dataset that combines data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) satellite instruments with data from the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) global reanalysis. Among other findings, the results reveal that near-cloud enhancements in lidar backscatter (closely related to aerosol optical depth) are larger (1) over land than ocean by 35%, (2) near optically thicker clouds by substantial amounts, (3) for sea salt than for other aerosol types, with the difference from dust reaching 50%. Finally, the study found that mean lidar backscatter is higher near clouds not because of large-scale variations in meteorological conditions, but because of local processes associated with individual clouds. The results help improve our understanding of aerosol-cloud-radiation interactions and our ability to represent them in climate models and other atmospheric modelsItem Changes in the surface broadband shortwave radiation budget during the 2017 eclipse(EGU, 2020-09-09) Wen, Guoyong; Marshak, Alexander; Tsay, Si-Chee; Herman, Jay; Jeong, Ukkyo; Abuhassan, Nader; Swap, Robert; Wu, DongWhile solar eclipses are known to greatly diminish the visible radiation reaching the surface of the Earth, less is known about the magnitude of the impact. We explore both the observed and modeled levels of change in surface radiation during the eclipse of 2017. We deployed a pyranometer and Pandora spectrometer instrument to Casper, Wyoming, and Columbia, Missouri, to measure surface broadband shortwave (SW) flux and atmospheric properties during the 21 August 2017 solar eclipse event. We performed detailed radiative transfer simulations to understand the role of clouds in spectral and broadband solar radiation transfer in the Earth's atmosphere for the normal (non-eclipse) spectrum and red-shift solar spectra for eclipse conditions. The theoretical calculations showed that the non-eclipse-to-eclipse surface flux ratio depends strongly on the obscuration of the solar disk and slightly on the cloud optical depth. These findings allowed us to estimate what the surface broadband SW flux would be for hypothetical non-eclipse conditions from observations during the eclipse and further to quantify the impact of the eclipse on the surface broadband SW radiation budget. We found that the eclipse caused local reductions of time-averaged surface flux of about 379 W m⁻² (50 %) and 329 W m⁻² (46 %) during the ∼3 h course of the eclipse at the Casper and Columbia sites, respectively. We estimated that the Moon's shadow caused a reduction of approximately 7 %–8 % in global average surface broadband SW radiation. The eclipse has a smaller impact on the absolute value of surface flux reduction for cloudy conditions than a clear atmosphere; the impact decreases with the increase in cloud optical depth. However, the relative time-averaged reduction of local surface SW flux during a solar eclipse is approximately 45 %, and it is not sensitive to cloud optical depth. The reduction of global average SW flux relative to climatology is proportional to the non-eclipse and eclipse flux difference in the penumbra area and depends on cloud optical depth in the Moon's shadow and geolocation due to the change in solar zenith angle. We also discuss the influence of cloud inhomogeneity on the observed SW flux. Our results not only quantify the reduction of the surface solar radiation budget, but also advance the understanding of broadband SW radiative transfer under solar eclipse conditions.Item Cloud products from the Earth Polychromatic Imaging Camera (EPIC): algorithms and initial evaluation(EGU, 2019-03-29) Yang, Yuekui; Meyer, Kerry; Wind, Galina; Zhou, Yaping; Marshak, Alexander; Platnick, Steven; Min, Qilong; Davis, Anthony B.; Joiner, Joanna; Vasilkov, Alexander; Duda, David; Su, WenyingThis paper presents the physical basis of the Earth Polychromatic Imaging Camera (EPIC) cloud product algorithms and an initial evaluation of their performance. Since June 2015, EPIC has been providing observations of the sunlit side of the Earth with its 10 spectral channels ranging from the UV to the near-infrared. A suite of algorithms has been developed to generate the standard EPIC Level 2 cloud products that include cloud mask, cloud effective pressure/height, and cloud optical thickness. The EPIC cloud mask adopts the threshold method and utilizes multichannel observations and ratios as tests. Cloud effective pressure/height is derived with observations from the O2 A-band (780 and 764 nm) and B-band (680 and 688 nm) pairs. The EPIC cloud optical thickness retrieval adopts a single-channel approach in which the 780 and 680 nm channels are used for retrievals over ocean and over land, respectively. Comparison with co-located cloud retrievals from geosynchronous earth orbit (GEO) and low earth orbit (LEO) satellites shows that the EPIC cloud product algorithms are performing well and are consistent with theoretical expectations. These products are publicly available at the Atmospheric Science Data Center at the NASA Langley Research Center for climate studies and for generating other geophysical products that require cloud properties as input.Item Deep space observations of sun glint over oceans(American Geophysical Union, 2018-07-09) Varnai, Tamas; Marshak, Alexander; Kostinski, AlexanderEvery hour or two, the Earth Polychromatic Imaging Camera (EPIC) onboard the DSCOVR satellite provides unique full-color images of the sunlit side of the Earth from the L1 Lagrangian point, which is four times farther the Moon. Casual glances at such images often reveal bright colorful spots that stand out markedly from their surroundings. Such spots often appear not only over ocean but also over land. Tracking the colorful spots using an automated image analysis algorithm reveals that they are caused by specular reflection of sunlight, sometimes from ocean surfaces and other times from clouds containing horizontally oriented ice crystals. The presented study characterizes these spots in terms of prevalence, location, color, and brightness, and provides insights into the factors that lead to their appearance.Item Earth Observations from DSCOVR EPIC Instrument(AMS, 2018-09-01) Marshak, Alexander; Herman, Jay; Szabo, AdaM; Blank, Karin; Carn, SiMon; Cede, Alexander; Geogdzhayev, Igor; Huang, Dong; Huang, Liang -Kang; Knyazikhin, Yuri; Kowalewski, Matthew; Krotkov, Nickolay; Lyapustin, Alexei; Mcpeters, Richard; Meyer, Kerry g.; Torres, OMar; Yang, YuekuiThe National Oceanic and Atmospheric Administration (NOAA) Deep Space Climate Observatory (DSCOVR) spacecraft was launched on 11 February 2015 and in June 2015 achieved its orbit at the first Lagrange point (L1), 1.5 million km from Earth toward the sun. There are two National Aeronautics and Space Administration (NASA) Earth-observing instruments on board: the Earth Polychromatic Imaging Camera (EPIC) and the National Institute of Standards and Technology Advanced Radiometer (NISTAR). The purpose of this paper is to describe various capabilities of the DSCOVR EPIC instrument. EPIC views the entire sunlit Earth from sunrise to sunset at the backscattering direction (scattering angles between 168.5° and 175.5°) with 10 narrowband filters: 317, 325, 340, 388, 443, 552, 680, 688, 764, and 779 nm. We discuss a number of preprocessing steps necessary for EPIC calibration including the geolocation algorithm and the radiometric calibration for each wavelength channel in terms of EPIC counts per second for conversion to reflectance units. The principal EPIC products are total ozone (O₃) amount, scene reflectivity, erythemal irradiance, ultraviolet (UV) aerosol properties, sulfur dioxide (SO₂) for volcanic eruptions, surface spectral reflectance, vegetation properties, and cloud products including cloud height. Finally, we describe the observation of horizontally oriented ice crystals in clouds and the unexpected use of the O₂ B-band absorption for vegetation properties.Item Earth Polychromatic Imaging Camera Geolocation; Strategies to Reduce Uncertainty(Frontiers, 2021-11-12) Blank, Karin; Huang, Liang-Kang; Herman, Jay; Marshak, AlexanderEarth Polychromatic Imaging Camera occupies a unique point of view for an Earth imager by being located approximately 1.5 million km from the planet at Earth-Sun Lagrange point, L1. This creates a number of unique challenges in geolocation, some of which are distance and mission specific. To solve these problems, algorithmic adaptations need to be made for calculations used for standard geolocation solutions, as well as artificial intelligence-based corrections for star tracker attitude and optical issues. This paper discusses methods for resolving these issues and bringing the geolocation solution to within requirements.Item A method of retrieving cloud top height and cloud geometrical thickness with oxygen A and B bands for the Deep Space Climate Observatory (DSCOVR) mission: Radiative transfer simulations(ELSEVIER, 2012-10-10) Yang, Yuekui; Marshak, Alexander; Mao, Jianping; Lyapustin, Alexei; Herman, JayThe Earth Polychromatic Imaging Camera (EPIC) onboard the Deep Space Climate Observatory (DSCOVR) was designed to measure the atmosphere and surface properties over the whole sunlit half of the Earth from the L1 Lagrangian point. It has 10 spectral channels ranging from the UV to the near-IR, including two pairs of oxygen (O₂) A-band (779.5 and 764 nm) and B-band (680 and 687.75 nm) reference and absorption channels selected for the cloud height measurements. This paper presents the radiative transfer analysis pertinent to retrieving cloud top height and cloud geometrical thickness with EPIC A- and B- band observations. Due to photon cloud penetration, retrievals from either O₂ A- or B- band channels alone gives the corresponding cloud centroid height, which is lower than the cloud top. However, we show both the sum and the difference between the retrieved cloud centroid heights in the A and B bands are functions of cloud top height and cloud geometrical thickness. Based on this fact, the paper develops a new method to retrieve cloud top height and cloud geometrical thickness simultaneously for fully cloudy scenes over ocean surface. First, cloud centroid heights are calculated for both A and B bands using the ratios between the reflectances of the absorbing and reference channels; then the cloud top height and the cloud geometrical thickness are retrieved from the two dimensional look up tables that relate the sum and the difference between the retrieved centroid heights for A and B bands to the cloud top height and the cloud geometrical thickness. This method is applicable for clouds thicker than an optical depth of 5.Item Raw EPIC Data Calibration(Frontiers, 2021-07-09) Cede, Alexander; Huang, Liang Kang; McCauley, Gavin; Herman, Jay; Blank, Karin; Kowalewski, Matthew; Marshak, AlexanderEarth Polychromatic Imaging Camera (EPIC) raw level-0 (L0) data in one channel is a 12-bit 2,048 × 2,048 pixels image array plus auxiliary data such as telemetry, temperature, etc. The EPIC L1a processor applies a series of correction steps on the L0 data to convert them into corrected count rates (level-1a or L1a data): Dark correction, Enhanced pixel detection, Read wave correction, Latency correction, Non-linearity correction, Temperature correction, Conversion to count rates, Flat fielding, and Stray light correction. L1a images should have all instrumental effects removed and only need to be multiplied by one single number for each wavelength to convert counts to radiances, which are the basis for all higher-level EPIC products, such as ozone and sulfur dioxide total column amounts, vegetation index, cloud, aerosol, ocean surface, and vegetation properties, etc. This paper gives an overview of the mathematics and the pre-launch and on-orbit calibration behind each correction step.Item Reduction in 317–780 nm radiance reflected from the sunlit Earth during the eclipse of 21 August 2017(EGU, 2018-07-25) Herman, Jay; Wen, Guoyong; Marshak, Alexander; Blank, Karin; Huang, Liang; Cede, Alexander; Abuhassan, Nader; Kowalewski, MatthewTen wavelength channels of calibrated radiance image data from the sunlit Earth are obtained every 65 min during Northern Hemisphere summer from the EPIC (Earth Polychromatic Imaging Camera) instrument on the DSCOVR (Deep Space Climate Observatory) satellite located near the Earth–Sun Lagrange 1 point (L ₁), about 1.5 million km from the Earth. The L ₁ location permitted seven observations of the Moon’s shadow on the Earth for about 3 h during the 21 August 2017 eclipse. Two of the observations were timed to coincide with totality over Casper, Wyoming, and Columbia, Missouri. Since the solar irradiances within five channels (λi = 388, 443, 551, 680, and 780 nm) are not strongly absorbed in the atmosphere, they can be used for characterizing the eclipse reduction in reflected radiances for the Earth’s sunlit face containing the eclipse shadow. Five channels (λi = 317.5, 325, 340, 688, and 764 nm) that are partially absorbed in the atmosphere give consistent reductions compared to the non-absorbed channels. This indicates that cloud reflectivities dominate the 317.5–780 nm radiances reflected back to space from the sunlit Earth’s disk with a significant contribution from Rayleigh scattering for the shorter wavelengths. An estimated reduction of 10 % was obtained for spectrally integrated radiance (387 to 781 nm) reflected from the sunlit Earth towards L ₁ for two sets of observations on 21 August 2017, while the shadow was in the vicinity of Casper, Wyoming (42.8666◦ N, 106.3131◦ W; centered on 17:44:50 UTC), and Columbia, Missouri (38.9517◦ N, 92.3341◦ W; centered on 18:14:50 UTC). In contrast, when non-eclipse days (20 and 23 August) are compared for each wavelength channel, the change in reflected light is much smaller (less than 1 % for 443 nm compared to 9 % (Casper) and 8 % (Columbia) during the eclipse). Also measured was the ratio Rₑₙ (λi) of reflected radiance on adjacent non-eclipse days divided by radiances centered in the eclipse totality region with the same geometry for all 10 wavelength channels. The measured Rₑₙ(443 nm) was smaller for Columbia (169) than for Casper (935), because Columbia had more cloud cover than Casper. Rₑₙ (λi) forms a useful test of a 3-D radiative transfer models for an eclipse in the presence of optically thin clouds. Specific values measured at Casper with thin clouds are Rₑₙ(340 nm) = 475, Rₑₙ(388 nm) = 3500, Rₑₙ(443 nm) = 935, Rₑₙ(551 nm) = 5455, Rₑₙ(680 nm) = 220, and Rₑₙ(780 nm) = 395. Some of the variability is caused by changing cloud amounts within the moving region of totality during the 2.7 min needed to measure all 10 wavelength channels.Item Reduction of Spectral Radiance Reflectance During the Annular Solar Eclipse of 21 June 2020 Observed by EPIC(Frontiers, 2022-05-02) Wen, Guoyong; Marshak, Alexander; Herman, Jay; Wu, DongThe annular solar eclipse on 21 June 2020 passed over desert areas (parts of Central and Eastern Africa, the southern Arabian Peninsula), partly cloudy regions (parts of South Asia and the Himalayas), and the mostly cloudy region in East Asia. Moving around the Earth-Sun Lagrange point 1 (L1), the Earth Polychromatic Imaging Camera (EPIC) instrument on the Deep Space Climate Observatory (DSCOVR) spacecraft captured three sets of images of the sunlit Earth during the eclipse, allowing us to study the impact of the solar eclipse on reflected solar radiation when the underlying surface and/or cloudy conditions in the Moon’s shadow are quite different. We analyzed EPIC images acquired during the 21 June 2020 and 21 August 2017 eclipses. We found that (1) EPIC-observed average spectral as well as spectrally averaged reflectance reductions of the entire sunlit Earth during the 21 June 2020 solar eclipse are distinctly different from those during the total solar eclipse of 21 August 2017; (2) the reduction of spectral reflectance depends strongly on underlying reflector properties, including the brightness, the area coverage of each reflector in the penumbra and the average distance to the center of the Moon’s shadow.Item Retrievals of Aerosol Optical Depth and Spectral Absorption From DSCOVR EPIC(Frontiers, 2021-03-30) Lyapustin, Alexei; Go, Sujung; Korkin, Sergey; Wang, Yujie; Torres, Omar; Jethva, Hiren; Marshak, AlexanderA new algorithm is described for joint retrievals of the aerosol optical depth and spectral absorption from EPIC observations in the UV—Vis spectral range. The retrievals are illustrated on examples of the wildfire smoke events over North America, and dust storms over greater Sahara region in 2018. An initial evaluation of single scattering albedo (SSA) at 443 nm over these regions shows a good agreement with AERONET data, generally within the uncertainty of AERONET SSA of ± 0.03. A particularly good agreement is achieved for dust with R~0.62, rmse~0.02, negligible bias, and 85% points within the expected error. This new capability is part of version 2 MAIAC EPIC algorithm. The v2 algorithm has recently completed reprocessing of the EPIC record covering the period of 2015–2020.Item Shortwave reflected energy from NISTAR and the Earth Polychromatic Imaging Camera onboard the DSCOVR spacecraft(EGU, 2023-08-09) Weaver, Clark Jay; Herman, Jay; Marshak, Alexander; Lorentz, Steven R.; Yu, Yinan; Smith, Allan W.; Szabo, AdamWe describe a new method for estimating the total reflected shortwave energy from the Earth Polychromatic Imaging Camera (EPIC) and compare it with direct measurements from the NIST Advanced Radiometer (NISTAR) instrument (Electrical substitution radiometer) - both are onboard the Lagrange-1 orbiting Deep Space Climate Observatory (DSCOVR). The 6 narrow-band wavelength channels (340 to 780 nm) available from EPIC provide a framework for estimating the integrated spectral energy for each EPIC pixel. The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and the SCIAMACHY instrument provide spectral information away from the EPIC wavelengths, particularly for wavelengths longer than 780 nm. The total area-weighted reflected shortwave energy from an entire EPIC image is compared with co-temporal Band B Shortwave reflected energy observed by NISTAR. Our analysis from March to December 2017 shows the two are highly correlated with differences ranging from -10 to 10 Watts m⁻². The offset bias over the entire period is less than 0.2 Watts m⁻². We also compare our EPIC energy maps with the Clouds and the Earth's Radiant Energy System (CERES) Single Scanner Footprint (SSF) Shortwave (SW) reflected energy observed within 3 hours of an EPIC image. Our EPIC-AVIRIS SW estimate is 5-20 % higher near the EPIC image center and 5-20 % lower near the image edges compared with the CERES SSF.Item Spaceborne observations of sun glint and near-cloud aerosols(2019-10-17) Várnai, Tamás; Marshak, Alexander; Wen, Guoyong; Yang, Weidong; Eck, Thomas; Levy, Robert; Kostinski, Alexander