Performance of MODIS Deep Blue Collection 6.1 Aerosol Optical Depth Products Over Indonesia: Spatiotemporal Variations and Aerosol Types

This study aims to evaluate the performance of the long-term Terra Moderate Resolution Imaging Spectroradiometer (MODIS) Deep Blue (DB) Collection 6.1 (C6.1) in determining the spatiotemporal variation of aerosol optical depth (AOD) and aerosol types over Indonesia. For this purpose, monthly MODIS D...

Full description

Bibliographic Details
Published in:Advances in Meteorology
Main Authors: Rheinhart C. H. Hutauruk, Donaldi S. Permana, Imron A. Rangga, Cici Sucianingsih, Tri A. Nuraini
Format: Article in Journal/Newspaper
Language:English
Published: Wiley 2022
Subjects:
Online Access:https://doi.org/10.1155/2022/7544310
https://doaj.org/article/b0cebe11c5b645468e4c34193c47fcff
id ftdoajarticles:oai:doaj.org/article:b0cebe11c5b645468e4c34193c47fcff
record_format openpolar
spelling ftdoajarticles:oai:doaj.org/article:b0cebe11c5b645468e4c34193c47fcff 2024-09-15T17:35:14+00:00 Performance of MODIS Deep Blue Collection 6.1 Aerosol Optical Depth Products Over Indonesia: Spatiotemporal Variations and Aerosol Types Rheinhart C. H. Hutauruk Donaldi S. Permana Imron A. Rangga Cici Sucianingsih Tri A. Nuraini 2022-01-01T00:00:00Z https://doi.org/10.1155/2022/7544310 https://doaj.org/article/b0cebe11c5b645468e4c34193c47fcff EN eng Wiley http://dx.doi.org/10.1155/2022/7544310 https://doaj.org/toc/1687-9317 1687-9317 doi:10.1155/2022/7544310 https://doaj.org/article/b0cebe11c5b645468e4c34193c47fcff Advances in Meteorology, Vol 2022 (2022) Meteorology. Climatology QC851-999 article 2022 ftdoajarticles https://doi.org/10.1155/2022/7544310 2024-08-05T17:48:33Z This study aims to evaluate the performance of the long-term Terra Moderate Resolution Imaging Spectroradiometer (MODIS) Deep Blue (DB) Collection 6.1 (C6.1) in determining the spatiotemporal variation of aerosol optical depth (AOD) and aerosol types over Indonesia. For this purpose, monthly MODIS DB AOD datasets are directly compared with Aerosol Robotic Network (AERONET) Version 3 Level 2.0 (cloud-screened and quality-assured) monthly measurements at 8 sites throughout Indonesia. The results indicate that MODIS DB AOD retrievals and AERONET AOD measurements have a high correlation in Sumatra Island (i.e., Kototabang (r = 0.88) and Jambi (r = 0.9)) and Kalimantan Island (i.e., Palangkaraya (r = 0.89) and Pontianak (r = 0.92)). However, the correlations are low in Bandung, Palu, and Sorong. In general, MODIS DB AOD tends to overestimate AERONET AOD at all sites by 16 to 61% and can detect extreme fire events in Sumatra and Kalimantan Islands quite well. Aerosol types in Indonesia mostly consist of clean continental, followed by biomass burning/urban industrial and mixed aerosols. Palu and Sorong had the highest clean continental aerosol contribution (90%), while Bandung had the highest biomass burning/urban-industrial aerosol contribution to atmospheric composition (93.7%). For mixed aerosols, the highest contribution was found in Pontianak, with a proportion of 48.4%. Spatially, the annual mean AOD in the western part of Indonesia is higher than in the eastern part. Seasonally, the highest AOD is observed during the period of September–November, which is associated with the emergence of fire events. Article in Journal/Newspaper Aerosol Robotic Network Directory of Open Access Journals: DOAJ Articles Advances in Meteorology 2022 1 12
institution Open Polar
collection Directory of Open Access Journals: DOAJ Articles
op_collection_id ftdoajarticles
language English
topic Meteorology. Climatology
QC851-999
spellingShingle Meteorology. Climatology
QC851-999
Rheinhart C. H. Hutauruk
Donaldi S. Permana
Imron A. Rangga
Cici Sucianingsih
Tri A. Nuraini
Performance of MODIS Deep Blue Collection 6.1 Aerosol Optical Depth Products Over Indonesia: Spatiotemporal Variations and Aerosol Types
topic_facet Meteorology. Climatology
QC851-999
description This study aims to evaluate the performance of the long-term Terra Moderate Resolution Imaging Spectroradiometer (MODIS) Deep Blue (DB) Collection 6.1 (C6.1) in determining the spatiotemporal variation of aerosol optical depth (AOD) and aerosol types over Indonesia. For this purpose, monthly MODIS DB AOD datasets are directly compared with Aerosol Robotic Network (AERONET) Version 3 Level 2.0 (cloud-screened and quality-assured) monthly measurements at 8 sites throughout Indonesia. The results indicate that MODIS DB AOD retrievals and AERONET AOD measurements have a high correlation in Sumatra Island (i.e., Kototabang (r = 0.88) and Jambi (r = 0.9)) and Kalimantan Island (i.e., Palangkaraya (r = 0.89) and Pontianak (r = 0.92)). However, the correlations are low in Bandung, Palu, and Sorong. In general, MODIS DB AOD tends to overestimate AERONET AOD at all sites by 16 to 61% and can detect extreme fire events in Sumatra and Kalimantan Islands quite well. Aerosol types in Indonesia mostly consist of clean continental, followed by biomass burning/urban industrial and mixed aerosols. Palu and Sorong had the highest clean continental aerosol contribution (90%), while Bandung had the highest biomass burning/urban-industrial aerosol contribution to atmospheric composition (93.7%). For mixed aerosols, the highest contribution was found in Pontianak, with a proportion of 48.4%. Spatially, the annual mean AOD in the western part of Indonesia is higher than in the eastern part. Seasonally, the highest AOD is observed during the period of September–November, which is associated with the emergence of fire events.
format Article in Journal/Newspaper
author Rheinhart C. H. Hutauruk
Donaldi S. Permana
Imron A. Rangga
Cici Sucianingsih
Tri A. Nuraini
author_facet Rheinhart C. H. Hutauruk
Donaldi S. Permana
Imron A. Rangga
Cici Sucianingsih
Tri A. Nuraini
author_sort Rheinhart C. H. Hutauruk
title Performance of MODIS Deep Blue Collection 6.1 Aerosol Optical Depth Products Over Indonesia: Spatiotemporal Variations and Aerosol Types
title_short Performance of MODIS Deep Blue Collection 6.1 Aerosol Optical Depth Products Over Indonesia: Spatiotemporal Variations and Aerosol Types
title_full Performance of MODIS Deep Blue Collection 6.1 Aerosol Optical Depth Products Over Indonesia: Spatiotemporal Variations and Aerosol Types
title_fullStr Performance of MODIS Deep Blue Collection 6.1 Aerosol Optical Depth Products Over Indonesia: Spatiotemporal Variations and Aerosol Types
title_full_unstemmed Performance of MODIS Deep Blue Collection 6.1 Aerosol Optical Depth Products Over Indonesia: Spatiotemporal Variations and Aerosol Types
title_sort performance of modis deep blue collection 6.1 aerosol optical depth products over indonesia: spatiotemporal variations and aerosol types
publisher Wiley
publishDate 2022
url https://doi.org/10.1155/2022/7544310
https://doaj.org/article/b0cebe11c5b645468e4c34193c47fcff
genre Aerosol Robotic Network
genre_facet Aerosol Robotic Network
op_source Advances in Meteorology, Vol 2022 (2022)
op_relation http://dx.doi.org/10.1155/2022/7544310
https://doaj.org/toc/1687-9317
1687-9317
doi:10.1155/2022/7544310
https://doaj.org/article/b0cebe11c5b645468e4c34193c47fcff
op_doi https://doi.org/10.1155/2022/7544310
container_title Advances in Meteorology
container_volume 2022
container_start_page 1
op_container_end_page 12
_version_ 1810446180506664960