Characterization of Wildfire Smoke over Complex Terrain Using Satellite Observations, Ground-Based Observations, and Meteorological Models

The severity of wildfires is increasing globally. In this study, we used data from the Global Change Observation Mission-Climate/Second-generation Global Imager (GCOM-C/SGLI) to characterize the biomass burning aerosols that are generated by large-scale wildfires. We used data from the September 202...

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Published in:Remote Sensing
Main Authors: Makiko Nakata, Itaru Sano, Sonoyo Mukai, Alexander Kokhanovsky
Format: Article in Journal/Newspaper
Language:English
Published: MDPI AG 2022
Subjects:
Q
Online Access:https://doi.org/10.3390/rs14102344
https://doaj.org/article/98dd6311e2ec462daf7142a7a34532d0
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spelling ftdoajarticles:oai:doaj.org/article:98dd6311e2ec462daf7142a7a34532d0 2023-05-15T13:06:27+02:00 Characterization of Wildfire Smoke over Complex Terrain Using Satellite Observations, Ground-Based Observations, and Meteorological Models Makiko Nakata Itaru Sano Sonoyo Mukai Alexander Kokhanovsky 2022-05-01T00:00:00Z https://doi.org/10.3390/rs14102344 https://doaj.org/article/98dd6311e2ec462daf7142a7a34532d0 EN eng MDPI AG https://www.mdpi.com/2072-4292/14/10/2344 https://doaj.org/toc/2072-4292 doi:10.3390/rs14102344 2072-4292 https://doaj.org/article/98dd6311e2ec462daf7142a7a34532d0 Remote Sensing, Vol 14, Iss 2344, p 2344 (2022) SCALE SGLI AERONET radiative transfer polarization Science Q article 2022 ftdoajarticles https://doi.org/10.3390/rs14102344 2022-12-30T23:22:23Z The severity of wildfires is increasing globally. In this study, we used data from the Global Change Observation Mission-Climate/Second-generation Global Imager (GCOM-C/SGLI) to characterize the biomass burning aerosols that are generated by large-scale wildfires. We used data from the September 2020 wildfires in western North America. The target area had a complex topography, comprising a basin among high mountains along a coastal region. The SGLI was essential for dealing with the complex topographical changes in terrain that we encountered, as it contains 19 polarization channels ranging from near ultraviolet (380 nm and 412 nm) to thermal infrared (red at 674 nm and near-infrared at 869 nm) and has a fine spatial resolution (1 km). The SGLI also proved to be efficient in the radiative transfer simulations of severe wildfires through the mutual use of polarization and radiance. We used a regional numerical model SCALE (Scalable Computing for Advanced Library and Environment) to account for variations in meteorological conditions and/or topography. Ground-based aerosol measurements in the target area were sourced from the National Aeronautics and Space Administration-Aerosol Robotic Network; currently, official satellite products typically do not provide the aerosol properties for very optically thick cases of wildfires. This paper used satellite observations, ground-based observations, and a meteorological model to define an algorithm for retrieving the aerosol properties caused by severe wildfire events. Article in Journal/Newspaper Aerosol Robotic Network Directory of Open Access Journals: DOAJ Articles Remote Sensing 14 10 2344
institution Open Polar
collection Directory of Open Access Journals: DOAJ Articles
op_collection_id ftdoajarticles
language English
topic SCALE
SGLI
AERONET
radiative transfer
polarization
Science
Q
spellingShingle SCALE
SGLI
AERONET
radiative transfer
polarization
Science
Q
Makiko Nakata
Itaru Sano
Sonoyo Mukai
Alexander Kokhanovsky
Characterization of Wildfire Smoke over Complex Terrain Using Satellite Observations, Ground-Based Observations, and Meteorological Models
topic_facet SCALE
SGLI
AERONET
radiative transfer
polarization
Science
Q
description The severity of wildfires is increasing globally. In this study, we used data from the Global Change Observation Mission-Climate/Second-generation Global Imager (GCOM-C/SGLI) to characterize the biomass burning aerosols that are generated by large-scale wildfires. We used data from the September 2020 wildfires in western North America. The target area had a complex topography, comprising a basin among high mountains along a coastal region. The SGLI was essential for dealing with the complex topographical changes in terrain that we encountered, as it contains 19 polarization channels ranging from near ultraviolet (380 nm and 412 nm) to thermal infrared (red at 674 nm and near-infrared at 869 nm) and has a fine spatial resolution (1 km). The SGLI also proved to be efficient in the radiative transfer simulations of severe wildfires through the mutual use of polarization and radiance. We used a regional numerical model SCALE (Scalable Computing for Advanced Library and Environment) to account for variations in meteorological conditions and/or topography. Ground-based aerosol measurements in the target area were sourced from the National Aeronautics and Space Administration-Aerosol Robotic Network; currently, official satellite products typically do not provide the aerosol properties for very optically thick cases of wildfires. This paper used satellite observations, ground-based observations, and a meteorological model to define an algorithm for retrieving the aerosol properties caused by severe wildfire events.
format Article in Journal/Newspaper
author Makiko Nakata
Itaru Sano
Sonoyo Mukai
Alexander Kokhanovsky
author_facet Makiko Nakata
Itaru Sano
Sonoyo Mukai
Alexander Kokhanovsky
author_sort Makiko Nakata
title Characterization of Wildfire Smoke over Complex Terrain Using Satellite Observations, Ground-Based Observations, and Meteorological Models
title_short Characterization of Wildfire Smoke over Complex Terrain Using Satellite Observations, Ground-Based Observations, and Meteorological Models
title_full Characterization of Wildfire Smoke over Complex Terrain Using Satellite Observations, Ground-Based Observations, and Meteorological Models
title_fullStr Characterization of Wildfire Smoke over Complex Terrain Using Satellite Observations, Ground-Based Observations, and Meteorological Models
title_full_unstemmed Characterization of Wildfire Smoke over Complex Terrain Using Satellite Observations, Ground-Based Observations, and Meteorological Models
title_sort characterization of wildfire smoke over complex terrain using satellite observations, ground-based observations, and meteorological models
publisher MDPI AG
publishDate 2022
url https://doi.org/10.3390/rs14102344
https://doaj.org/article/98dd6311e2ec462daf7142a7a34532d0
genre Aerosol Robotic Network
genre_facet Aerosol Robotic Network
op_source Remote Sensing, Vol 14, Iss 2344, p 2344 (2022)
op_relation https://www.mdpi.com/2072-4292/14/10/2344
https://doaj.org/toc/2072-4292
doi:10.3390/rs14102344
2072-4292
https://doaj.org/article/98dd6311e2ec462daf7142a7a34532d0
op_doi https://doi.org/10.3390/rs14102344
container_title Remote Sensing
container_volume 14
container_issue 10
container_start_page 2344
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