Geostationary aerosol retrievals of extreme biomass burning plumes during the 2019–2020 Australian bushfires

Extreme biomass burning (BB) events, such as those seen during the 2019–2020 Australian bushfire season, are becoming more frequent and intense with climate change. Ground-based observations of these events can provide useful information on the macro- and micro-physical properties of the plumes, but...

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Published in:Atmospheric Measurement Techniques
Main Authors: Robbins, Daniel J. V., Poulsen, Caroline A., Siems, Steven T., Proud, Simon R., Prata, Andrew T., Grainger, Roy G., Povey, Adam C.
Format: Text
Language:English
Published: 2024
Subjects:
Online Access:https://doi.org/10.5194/amt-17-3279-2024
https://amt.copernicus.org/articles/17/3279/2024/
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spelling ftcopernicus:oai:publications.copernicus.org:amt114981 2024-09-09T18:55:37+00:00 Geostationary aerosol retrievals of extreme biomass burning plumes during the 2019–2020 Australian bushfires Robbins, Daniel J. V. Poulsen, Caroline A. Siems, Steven T. Proud, Simon R. Prata, Andrew T. Grainger, Roy G. Povey, Adam C. 2024-05-29 application/pdf https://doi.org/10.5194/amt-17-3279-2024 https://amt.copernicus.org/articles/17/3279/2024/ eng eng doi:10.5194/amt-17-3279-2024 https://amt.copernicus.org/articles/17/3279/2024/ eISSN: 1867-8548 Text 2024 ftcopernicus https://doi.org/10.5194/amt-17-3279-2024 2024-08-28T05:24:15Z Extreme biomass burning (BB) events, such as those seen during the 2019–2020 Australian bushfire season, are becoming more frequent and intense with climate change. Ground-based observations of these events can provide useful information on the macro- and micro-physical properties of the plumes, but these observations are sparse, especially in regions which are at risk of intense bushfire events. Satellite observations of extreme BB events provide a unique perspective, with the newest generation of geostationary imagers, such as the Advanced Himawari Imager (AHI), observing entire continents at moderate spatial and high temporal resolution. However, current passive satellite retrieval methods struggle to capture the high values of aerosol optical thickness (AOT) seen during these BB events. Accurate retrievals are necessary for global and regional studies of shortwave radiation, air quality modelling and numerical weather prediction. To address these issues, the Optimal Retrieval of Aerosol and Cloud (ORAC) algorithm has used AHI data to measure extreme BB plumes from the 2019–2020 Australian bushfire season. The sensitivity of the retrieval to the assumed optical properties of BB plumes is explored by comparing retrieved AOT with AErosol RObotic NETwork (AERONET) level-1.5 data over the AERONET site at Tumbarumba, New South Wales, between 1 December 2019 at 00:00 UTC and 3 January 2020 at 00:00 UTC. The study shows that for AOT values > 2, the sensitivity to the assumed optical properties is substantial. The ORAC retrievals and AERONET data are compared against the Japan Aerospace Exploration Agency (JAXA) Aerosol Retrieval Product (ARP), Moderate Resolution Imaging Spectroradiometer (MODIS) Deep Blue over land, MODIS MAIAC, Sentinel-3 SYN and VIIRS Deep Blue products. The comparison shows the ORAC retrieval significantly improves coverage of optically thick plumes relative to the JAXA ARP, with approximately twice as many pixels retrieved and peak retrieved AOT values 1.4 times higher than the JAXA ARP. ... Text Aerosol Robotic Network Copernicus Publications: E-Journals Atmospheric Measurement Techniques 17 10 3279 3302
institution Open Polar
collection Copernicus Publications: E-Journals
op_collection_id ftcopernicus
language English
description Extreme biomass burning (BB) events, such as those seen during the 2019–2020 Australian bushfire season, are becoming more frequent and intense with climate change. Ground-based observations of these events can provide useful information on the macro- and micro-physical properties of the plumes, but these observations are sparse, especially in regions which are at risk of intense bushfire events. Satellite observations of extreme BB events provide a unique perspective, with the newest generation of geostationary imagers, such as the Advanced Himawari Imager (AHI), observing entire continents at moderate spatial and high temporal resolution. However, current passive satellite retrieval methods struggle to capture the high values of aerosol optical thickness (AOT) seen during these BB events. Accurate retrievals are necessary for global and regional studies of shortwave radiation, air quality modelling and numerical weather prediction. To address these issues, the Optimal Retrieval of Aerosol and Cloud (ORAC) algorithm has used AHI data to measure extreme BB plumes from the 2019–2020 Australian bushfire season. The sensitivity of the retrieval to the assumed optical properties of BB plumes is explored by comparing retrieved AOT with AErosol RObotic NETwork (AERONET) level-1.5 data over the AERONET site at Tumbarumba, New South Wales, between 1 December 2019 at 00:00 UTC and 3 January 2020 at 00:00 UTC. The study shows that for AOT values > 2, the sensitivity to the assumed optical properties is substantial. The ORAC retrievals and AERONET data are compared against the Japan Aerospace Exploration Agency (JAXA) Aerosol Retrieval Product (ARP), Moderate Resolution Imaging Spectroradiometer (MODIS) Deep Blue over land, MODIS MAIAC, Sentinel-3 SYN and VIIRS Deep Blue products. The comparison shows the ORAC retrieval significantly improves coverage of optically thick plumes relative to the JAXA ARP, with approximately twice as many pixels retrieved and peak retrieved AOT values 1.4 times higher than the JAXA ARP. ...
format Text
author Robbins, Daniel J. V.
Poulsen, Caroline A.
Siems, Steven T.
Proud, Simon R.
Prata, Andrew T.
Grainger, Roy G.
Povey, Adam C.
spellingShingle Robbins, Daniel J. V.
Poulsen, Caroline A.
Siems, Steven T.
Proud, Simon R.
Prata, Andrew T.
Grainger, Roy G.
Povey, Adam C.
Geostationary aerosol retrievals of extreme biomass burning plumes during the 2019–2020 Australian bushfires
author_facet Robbins, Daniel J. V.
Poulsen, Caroline A.
Siems, Steven T.
Proud, Simon R.
Prata, Andrew T.
Grainger, Roy G.
Povey, Adam C.
author_sort Robbins, Daniel J. V.
title Geostationary aerosol retrievals of extreme biomass burning plumes during the 2019–2020 Australian bushfires
title_short Geostationary aerosol retrievals of extreme biomass burning plumes during the 2019–2020 Australian bushfires
title_full Geostationary aerosol retrievals of extreme biomass burning plumes during the 2019–2020 Australian bushfires
title_fullStr Geostationary aerosol retrievals of extreme biomass burning plumes during the 2019–2020 Australian bushfires
title_full_unstemmed Geostationary aerosol retrievals of extreme biomass burning plumes during the 2019–2020 Australian bushfires
title_sort geostationary aerosol retrievals of extreme biomass burning plumes during the 2019–2020 australian bushfires
publishDate 2024
url https://doi.org/10.5194/amt-17-3279-2024
https://amt.copernicus.org/articles/17/3279/2024/
genre Aerosol Robotic Network
genre_facet Aerosol Robotic Network
op_source eISSN: 1867-8548
op_relation doi:10.5194/amt-17-3279-2024
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op_doi https://doi.org/10.5194/amt-17-3279-2024
container_title Atmospheric Measurement Techniques
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