Passive remote sensing of altitude and optical depth of dust plumes using the oxygen A and B bands: First results from EPIC/DSCOVR at Lagrange‐1 point

Xu, Xiangde; Wang, Jun; Wang, Yi; Zeng, Jing; Torres, Omar; Yang, Yuekui; Marshak, Alexander; Reid, Jeffrey S.; Miller, Steve

doi:10.1002/2017gl073939

Cited by 89 publications

(91 citation statements)

References 62 publications

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“…The ten-channel images include four channels (318, 325, 340 and 388 nm) in the ultra-violet (UV), four channels (443, 551, 680 and 688 nm) in the visible (VIS) and two channels (764 and 780 nm) in the near-infrared (NIR) region. The ten-channel images are used to derive ozone, SO 2 , properties of aerosols, and clouds, as well as properties of vegetated surface such as leaf area index and its sunlit portion [1][2][3][4][5][6].…”

Section: Introductionmentioning

confidence: 99%

EPIC Spectral Observations of Variability in Earth’s Global Reflectance

et al. 2018

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NASA's Earth Polychromatic Imaging Camera (EPIC) onboard NOAA's Deep Space Climate Observatory (DSCOVR) satellite observes the entire sunlit Earth every 65 to 110 min from the Sun-Earth Lagrangian L1 point. This paper presents initial EPIC shortwave spectral observations of the sunlit Earth reflectance and analyses of its diurnal and seasonal variations. The results show that the reflectance depends mostly on (1) the ratio between land and ocean areas exposed to the Sun and (2) cloud spatial and temporal distributions over the sunlit side of Earth. In particular, the paper shows that (a) diurnal variations of the Earth's reflectance are determined mostly by periodic changes in the land-ocean fraction of its the sunlit side; (b) the daily reflectance displays clear seasonal variations that are significant even without including the contributions from snow and ice in the polar regions (which can enhance daily mean reflectances by up to 2 to 6% in winter and up to 1 to 4% in summer); (c) the seasonal variations of the sunlit Earth reflectance are mostly determined by the latitudinal distribution of oceanic clouds.

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Section: Introductionmentioning

confidence: 99%

EPIC Spectral Observations of Variability in Earth’s Global Reflectance

et al. 2018

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“…The EPIC pixel size is 12 × 12 km 2 compared to 80 × 40 km 2 for GOME-2 and 30 × 60 km 2 for SCIAMACHY. Thus the results of Xu et al (2017) are likely to be less affected by cloud contamination and aerosol inhomogeneities. A situation of partially aerosol-covered pixels implies that fewer oxygen molecules are shielded by the intervening scatterers, with the effect of increasing absorption inside the A-band sensed by the instruments.…”

Section: Discussionmentioning

confidence: 99%

“…As such, the evaluation of the presented dust cases can be regarded as a more comprehensive test bed for operational dust height retrievals. Xu et al (2017) combined oxygen A and B-band measurements from the Earth Polychromatic Imaging Camera (EPIC) on the Deep Space Climate Observatory (DSCOVR) to retrieve AOD and height, finding that 71.5 and 98.7 % aerosol heights were respectively within ±0.5 and ±1.0 km envelopes when compared to CALIOP for two overpasses of Saharan dust events over water only. Their reported rms error, in this case, amounts to 0.45 km, pointing to the advantage of adding the information concealed in the B-band to the retrieval .…”

Section: Discussionmentioning

confidence: 99%

Comparison of dust-layer heights from active and passive satellite sensors

et al. 2018

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Abstract. Aerosol-layer height is essential for understanding the impact of aerosols on the climate system. As part of the European Space Agency Aerosol_cci project, aerosollayer height as derived from passive thermal and solar satellite sensors measurements have been compared with aerosollayer heights estimated from CALIOP measurements. The Aerosol_cci project targeted dust-type aerosol for this study. This ensures relatively unambiguous aerosol identification by the CALIOP processing chain. Dust-layer height was estimated from thermal IASI measurements using four different algorithms (from BIRA-IASB, DLR, LMD, LISA) and from solar GOME-2 (KNMI) and SCIAMACHY (IUP) measurements. Due to differences in overpass time of the various satellites, a trajectory model was used to move the CALIOPderived dust heights in space and time to the IASI, GOME-2 and SCIAMACHY dust height pixels. It is not possible to construct a unique dust-layer height from the CALIOP data. Thus two CALIOP-derived layer heights were used: the cumulative extinction height defined as the height where the CALIOP extinction column is half of the total extinction column, and the geometric mean height, which is defined as the geometrical mean of the top and bottom heights of the dust layer. In statistical average over all IASI data there is a general tendency to a positive bias of 0.5-0.8 km against CALIOP extinction-weighted height for three of the four algorithms assessed, while the fourth algorithm has almost no bias. When comparing geometric mean height there is a shift of −0.5 km for all algorithms (getting close to zero for the three algorithms and turning negative for the fourth). The standard deviation of all algorithms is quite similar and ranges between 1.0 and 1.3 km. When looking at different conditions (day, night, land, ocean), there is more detail in variabilities (e.g. all algorithms overestimate more at night than during the day). For the solar sensors it is found that on average SCIAMACHY data are lower by −1.097 km (−0.961 km) compared to the CALIOP geometric mean (cumulative extinction) height, and GOME-2 data are lower by −1.393 km (−0.818 km).

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“…Additionally, radiance measurements in the oxygen A and B bands are used to simultaneously derive the optical depth and the height of elevated desert dust and smoke aerosol layers over the oceans (Xu et al 2017).…”

Section: Products Epic Ozone and Lambert Equivalent Reflectivity Retmentioning

confidence: 99%

Earth Observations from DSCOVR EPIC Instrument

Marshak

Herman

Szabo

et al. 2018

Bulletin of the American Meteorological Society

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The 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.

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Passive remote sensing of altitude and optical depth of dust plumes using the oxygen A and B bands: First results from EPIC/DSCOVR at Lagrange‐1 point

Cited by 89 publications

References 62 publications

EPIC Spectral Observations of Variability in Earth’s Global Reflectance

EPIC Spectral Observations of Variability in Earth’s Global Reflectance

Comparison of dust-layer heights from active and passive satellite sensors

Earth Observations from DSCOVR EPIC Instrument

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