Development of a nighttime shortwave radiative transfer model for remote sensing of nocturnal aerosols and fires from VIIRS

Jun Wang; Meng Zhou; Xiaoguang Xu; Sepehr Roudini; Stanley P Sander; Thomas J Pongetti; Steven D Miller; Jeffrey S Reid; Edward Hyer; Robert Spurr

doi:10.1016/j.rse.2020.111727

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Development of a nighttime shortwave radiative transfer model for remote sensing of nocturnal aerosols and fires from VIIRS

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Development of a nighttime shortwave radiative transfer model for remote sensing of nocturnal aerosols and fires from VIIRS

Jun Wang, Meng Zhou, Xiaoguang Xu, Sepehr Roudini, Stanley P Sander, Thomas J Pongetti, Steven D Miller, Jeffrey S Reid, Edward Hyer and Robert Spurr

Remote sensing of environment, Vol.241, p.111727

05/2020

DOI: 10.1016/j.rse.2020.111727

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Abstract

The launch of the Visible Infrared Imaging Radiometer Suite (VIIRS) on board the Sumo-NPP satellite in 2011 ushered in a new era of using visible light and shortwave radiation at night to characterize aerosol and fire distributions from space. In order to exploit the full range of unprecedented observational capabilities of VIIRS, we have developed a nighttime shortwave radiative transfer model capability in the UNified and Linearized Radiative Transfer Model (UNL-VRTM). This capability is based on the use of additional source functions to treat illumination from the Moon, from fires, and from artificial lights. We have applied this model to address fundamental questions associated with the VIIRS sensing of aerosol and fire at night. Detailed description of model developments and validation (either directly with surface measurements of lunar spectra or indirectly through cross validation) are presented. Our analysis reveals that: (a) when convolution with the broad-range (500–900 nm) relative spectral response (RSR) function of the VIIRS Day-Night Band (DNB) is omitted, AOD retrieval from the DNB have uncertainties up to a factor of two in conditions with low or moderate AOD (<0.5 in mid-visible); (b) using a wavelength independent spectrum for the surface illumination source can lead to an AOD bias of −10% over surfaces illuminated by light-emitting diodes and fluorescent lamps, and −30% illuminated by high-pressure sodium lamps; and (c) a DNB-equivalent narrow band for AOD retrieval over the surfaces illuminated by the three types of bulbs studied in this paper is found to be centered at 585 nm at which the look-up table can be generated for AOD retrieval from DNB. Furthermore, while uncertainty in AOD retrievals from the DNB decreases as AOD increases, fire characterization can be affected by AOD; for a smoke-scenario AOD of 2.0, the DNB and SWIR (1.6 μm) radiances can be reduced by 50% depending on the fire area fraction and temperature within VIIRS pixel. DNB is overall more sensitive to smaller and cooler fires than SWIR and can be used to retrieve AOD over bright surfaces. Finally, three-dimensional (3D) radiative transfer effects and the non-collimated nature of most artificial light sources are neglected in this 1D radiative transfer (plane-parallel) model, resulting in possibly large uncertainties (e.g., the inability to reproduce side-illumination of clouds by city lights) that should be studied in future. •Development and validation of a nighttime shortwave radiative transfer model•Illumination sources from moon, fires and outdoor artificial lights are considered.•Multiple scattering by particles and absorption by gases are fully treated.•Roles of spectral response function & surface light spectra in aerosol sensing are studied.•Impacts of aerosols on fire sensing are analyzed

VIIRS

Remote sensing of aerosols

Nighttime shortwave radiative transfer

Remote sensing of fires

Nocturnal

Details

Title: Subtitle: Development of a nighttime shortwave radiative transfer model for remote sensing of nocturnal aerosols and fires from VIIRS
Creators: Jun Wang - Department of Chemical and Biochemical Engineering, Iowa Technology Institute, The University of Iowa, 4133 Seamans Center, Iowa City, IA 52242, USA
Meng Zhou - Department of Chemical and Biochemical Engineering, Iowa Technology Institute, The University of Iowa, 4133 Seamans Center, Iowa City, IA 52242, USA
Xiaoguang Xu - Department of Chemical and Biochemical Engineering, Iowa Technology Institute, The University of Iowa, 4133 Seamans Center, Iowa City, IA 52242, USA
Sepehr Roudini - Department of Chemical and Biochemical Engineering, Iowa Technology Institute, The University of Iowa, 4133 Seamans Center, Iowa City, IA 52242, USA
Stanley P Sander - Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California 91109 USA
Thomas J Pongetti - Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California 91109 USA
Steven D Miller - Cooperative Institute for Research in the Atmosphere, Colorado State University, Fort Collins, CO 80523, USA
Jeffrey S Reid - Marine Meteorology Division, Naval Research Laboratory, Monterey, CA 93943, USA
Edward Hyer - Marine Meteorology Division, Naval Research Laboratory, Monterey, CA 93943, USA
Robert Spurr - RT Solutions Inc., Cambridge, MA 02138, USA
Resource Type: Journal article
Publication Details: Remote sensing of environment, Vol.241, p.111727
DOI: 10.1016/j.rse.2020.111727
ISSN: 0034-4257
eISSN: 1879-0704
Publisher: Elsevier Inc
Grant note: DOI: 10.13039/100000104, name: National Aeronautics and Space Administration; DOI: 10.13039/100000006, name: Office of Naval Research
Language: English
Date published: 05/2020
Academic Unit: Civil and Environmental Engineering; Iowa Technology Institute; Physics and Astronomy; Chemical and Biochemical Engineering
Record Identifier: 9984066350602771

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