Evaluation and comparison of MERRA-2 AOD and DAOD with MODIS DeepBlue and AERONET data in Australia

Validated dust and aerosol datasets provide valuable information for dust and other atmospheric research. A reanalysis product called ‘MERRA-2’ developed by NASA's Global Modeling and Assimilation Office (GMAO) in recent years provides long-term, high frequency, global coverage aerosol simulati...

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Published in:Atmospheric Environment
Main Authors: Che, Yahui, Yu, Bofu, Parsons, Katherine, Desha, Cheryl, Ramezani, Mohammad
Format: Article in Journal/Newspaper
Language:English
Published: Elsevier 2022
Subjects:
Online Access:http://hdl.handle.net/10072/419139
https://doi.org/10.1016/j.atmosenv.2022.119054
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spelling ftgriffithuniv:oai:research-repository.griffith.edu.au:10072/419139 2024-06-23T07:45:01+00:00 Evaluation and comparison of MERRA-2 AOD and DAOD with MODIS DeepBlue and AERONET data in Australia Che, Yahui Yu, Bofu Parsons, Katherine Desha, Cheryl Ramezani, Mohammad 2022 http://hdl.handle.net/10072/419139 https://doi.org/10.1016/j.atmosenv.2022.119054 English eng Elsevier Atmospheric Environment Che, Y; Yu, B; Parsons, K; Desha, C; Ramezani, M, Evaluation and comparison of MERRA-2 AOD and DAOD with MODIS DeepBlue and AERONET data in Australia, Atmospheric Environment, 2022, 277, pp. 119054 http://hdl.handle.net/10072/419139 1352-2310 doi:10.1016/j.atmosenv.2022.119054 open access Atmospheric sciences Climate change science Environmental engineering Science & Technology Life Sciences & Biomedicine Physical Sciences Environmental Sciences Meteorology & Atmospheric Sciences Journal article 2022 ftgriffithuniv https://doi.org/10.1016/j.atmosenv.2022.119054 2024-06-04T23:56:28Z Validated dust and aerosol datasets provide valuable information for dust and other atmospheric research. A reanalysis product called ‘MERRA-2’ developed by NASA's Global Modeling and Assimilation Office (GMAO) in recent years provides long-term, high frequency, global coverage aerosol simulations, in terms of AOD (aerosol optical depth) and dust AOD (DAOD). The AOD assimilation system including AERONET (Aerosol Robotic Network) as constraints has led to difficulties with independent validation of MERRA-2 AOD and DAOD. The existing validation and evaluation of MERRA-2 tend to focus on central inland Australia, and comparison of DAOD with MACC (Monitoring Atmospheric Composition and Climate) is insufficient to indicate which one is more appropriate for dust research in Australia. In this study, MERRA-2 output was compared with MODIS DeepBlue (MODIS-DB) (2002–2020) and AERONET (1998–2020) AOD and DAOD in Australia. The expected error (EE) for MERRA-2 AOD was estimated to be ±(0.03+0.15τA) containing 66% of data points. MERRA-2 is less well correlated with AERONET in terms of DAOD, but with a tighter distribution of data points (78%) within the EE. The EE for MODIS-DB AOD was found to be the same and the correlation between MODIS-DB DAOD and AERONET DAOD is stronger than that between MERRA-2 DAOD and AERONET DAOD. Comparison of MERRA-2 and MODIS-DB AOD showed that MERRA-2 AOD was 22.5% higher than MODIS-DB AOD at AERONET sites on average. MERRA-2 AOD was generally lower than MODIS-DB AOD away from AERONET sites when AOD >0.1, and the spatial distribution of the difference between the two is consistent with the spatial variation in AOD. Large differences between MODIS-DB AOD and MERRA-2 occurred in areas where AOD is greater than 0.3. AOD and DAOD based on MODIS-DB could be used for areas away from AERONET sites in Australia, as they are less dependent on AERONET data compared to MERRA-2. When compared to MODIS brightness temperature difference (BTD) for two known severe storm events in Australia, MODIS-DB ... Article in Journal/Newspaper Aerosol Robotic Network Griffith University: Griffith Research Online Merra ENVELOPE(12.615,12.615,65.816,65.816) Atmospheric Environment 277 119054
institution Open Polar
collection Griffith University: Griffith Research Online
op_collection_id ftgriffithuniv
language English
topic Atmospheric sciences
Climate change science
Environmental engineering
Science & Technology
Life Sciences & Biomedicine
Physical Sciences
Environmental Sciences
Meteorology & Atmospheric Sciences
spellingShingle Atmospheric sciences
Climate change science
Environmental engineering
Science & Technology
Life Sciences & Biomedicine
Physical Sciences
Environmental Sciences
Meteorology & Atmospheric Sciences
Che, Yahui
Yu, Bofu
Parsons, Katherine
Desha, Cheryl
Ramezani, Mohammad
Evaluation and comparison of MERRA-2 AOD and DAOD with MODIS DeepBlue and AERONET data in Australia
topic_facet Atmospheric sciences
Climate change science
Environmental engineering
Science & Technology
Life Sciences & Biomedicine
Physical Sciences
Environmental Sciences
Meteorology & Atmospheric Sciences
description Validated dust and aerosol datasets provide valuable information for dust and other atmospheric research. A reanalysis product called ‘MERRA-2’ developed by NASA's Global Modeling and Assimilation Office (GMAO) in recent years provides long-term, high frequency, global coverage aerosol simulations, in terms of AOD (aerosol optical depth) and dust AOD (DAOD). The AOD assimilation system including AERONET (Aerosol Robotic Network) as constraints has led to difficulties with independent validation of MERRA-2 AOD and DAOD. The existing validation and evaluation of MERRA-2 tend to focus on central inland Australia, and comparison of DAOD with MACC (Monitoring Atmospheric Composition and Climate) is insufficient to indicate which one is more appropriate for dust research in Australia. In this study, MERRA-2 output was compared with MODIS DeepBlue (MODIS-DB) (2002–2020) and AERONET (1998–2020) AOD and DAOD in Australia. The expected error (EE) for MERRA-2 AOD was estimated to be ±(0.03+0.15τA) containing 66% of data points. MERRA-2 is less well correlated with AERONET in terms of DAOD, but with a tighter distribution of data points (78%) within the EE. The EE for MODIS-DB AOD was found to be the same and the correlation between MODIS-DB DAOD and AERONET DAOD is stronger than that between MERRA-2 DAOD and AERONET DAOD. Comparison of MERRA-2 and MODIS-DB AOD showed that MERRA-2 AOD was 22.5% higher than MODIS-DB AOD at AERONET sites on average. MERRA-2 AOD was generally lower than MODIS-DB AOD away from AERONET sites when AOD >0.1, and the spatial distribution of the difference between the two is consistent with the spatial variation in AOD. Large differences between MODIS-DB AOD and MERRA-2 occurred in areas where AOD is greater than 0.3. AOD and DAOD based on MODIS-DB could be used for areas away from AERONET sites in Australia, as they are less dependent on AERONET data compared to MERRA-2. When compared to MODIS brightness temperature difference (BTD) for two known severe storm events in Australia, MODIS-DB ...
format Article in Journal/Newspaper
author Che, Yahui
Yu, Bofu
Parsons, Katherine
Desha, Cheryl
Ramezani, Mohammad
author_facet Che, Yahui
Yu, Bofu
Parsons, Katherine
Desha, Cheryl
Ramezani, Mohammad
author_sort Che, Yahui
title Evaluation and comparison of MERRA-2 AOD and DAOD with MODIS DeepBlue and AERONET data in Australia
title_short Evaluation and comparison of MERRA-2 AOD and DAOD with MODIS DeepBlue and AERONET data in Australia
title_full Evaluation and comparison of MERRA-2 AOD and DAOD with MODIS DeepBlue and AERONET data in Australia
title_fullStr Evaluation and comparison of MERRA-2 AOD and DAOD with MODIS DeepBlue and AERONET data in Australia
title_full_unstemmed Evaluation and comparison of MERRA-2 AOD and DAOD with MODIS DeepBlue and AERONET data in Australia
title_sort evaluation and comparison of merra-2 aod and daod with modis deepblue and aeronet data in australia
publisher Elsevier
publishDate 2022
url http://hdl.handle.net/10072/419139
https://doi.org/10.1016/j.atmosenv.2022.119054
long_lat ENVELOPE(12.615,12.615,65.816,65.816)
geographic Merra
geographic_facet Merra
genre Aerosol Robotic Network
genre_facet Aerosol Robotic Network
op_relation Atmospheric Environment
Che, Y; Yu, B; Parsons, K; Desha, C; Ramezani, M, Evaluation and comparison of MERRA-2 AOD and DAOD with MODIS DeepBlue and AERONET data in Australia, Atmospheric Environment, 2022, 277, pp. 119054
http://hdl.handle.net/10072/419139
1352-2310
doi:10.1016/j.atmosenv.2022.119054
op_rights open access
op_doi https://doi.org/10.1016/j.atmosenv.2022.119054
container_title Atmospheric Environment
container_volume 277
container_start_page 119054
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