Analysis of Atmospheric Aerosol Changes in the Qinghai-Tibetan Plateau Region during 2009–2019 Using a New Fusion Algorithm
The Qinghai-Tibetan Plateau (QTP) is the largest permafrost-covered area in the world, and it is critical to understand accurately and dynamically the cyclical changes in atmospheric aerosols in the region. However, due to the scarcity of researchers in this field and the complexity of analyzing the...
Published in: | Atmosphere |
---|---|
Main Authors: | , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
MDPI AG
2024
|
Subjects: | |
Online Access: | https://doi.org/10.3390/atmos15060712 https://doaj.org/article/01c5a993dc404905ab389b696b883e6a |
id |
ftdoajarticles:oai:doaj.org/article:01c5a993dc404905ab389b696b883e6a |
---|---|
record_format |
openpolar |
spelling |
ftdoajarticles:oai:doaj.org/article:01c5a993dc404905ab389b696b883e6a 2024-09-15T17:35:18+00:00 Analysis of Atmospheric Aerosol Changes in the Qinghai-Tibetan Plateau Region during 2009–2019 Using a New Fusion Algorithm Zhijian Zhao Hideyuki Tonooka 2024-06-01T00:00:00Z https://doi.org/10.3390/atmos15060712 https://doaj.org/article/01c5a993dc404905ab389b696b883e6a EN eng MDPI AG https://www.mdpi.com/2073-4433/15/6/712 https://doaj.org/toc/2073-4433 doi:10.3390/atmos15060712 2073-4433 https://doaj.org/article/01c5a993dc404905ab389b696b883e6a Atmosphere, Vol 15, Iss 6, p 712 (2024) Qinghai-Tibetan Plateau (QTP) permafrost aerosol optical depth (AOD) dark target method (DT) deep blue method (DB) aerosol robotic network (AERONET) Meteorology. Climatology QC851-999 article 2024 ftdoajarticles https://doi.org/10.3390/atmos15060712 2024-08-05T17:49:06Z The Qinghai-Tibetan Plateau (QTP) is the largest permafrost-covered area in the world, and it is critical to understand accurately and dynamically the cyclical changes in atmospheric aerosols in the region. However, due to the scarcity of researchers in this field and the complexity of analyzing the spatial and temporal dynamics of aerosols, there is a gap in research in this area, which we hope to fill. In this study, we constructed a new fusion algorithm based on the V5.2 algorithm and the second-generation deep blue algorithm through the introduced weight factor of light and dark image elements. We used the algorithm to analyze the spatial and temporal changes in aerosols from 2009–2019. Seasonal changes and the spatial distribution of aerosol optical depth (AOD) were analyzed in comparison with the trend of weight factor, which proved the stability of the fusion algorithm. Spatially, the AOD values in the northeastern bare lands and southeastern woodland decreased most significantly, and combined with the seasonal pattern of change, the AOD values in this region were higher in the spring and fall. In these 11 years, the AOD values in the spring and fall decreased the most, and the aerosol in which the AOD decreases occurred should be the cooling-type sulfate aerosol. In order to verify the accuracy of the algorithm, we compared the AOD values obtained by the algorithm at different time intervals with the measured AOD values of several AERONET stations, in which the MAE, RMSE, and R between the AOD values obtained by the algorithm and the measured averages of the 12 nearest AERONET stations in the QTP area were 0.309, 0.094, and 0.910, respectively. In addition, this study also compares the AOD results obtained from the fusion algorithm when dynamically weighted and mean-weighted, and the results show that the error value is smaller in the dynamic weighting approach in this study. Article in Journal/Newspaper Aerosol Robotic Network permafrost Directory of Open Access Journals: DOAJ Articles Atmosphere 15 6 712 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
Qinghai-Tibetan Plateau (QTP) permafrost aerosol optical depth (AOD) dark target method (DT) deep blue method (DB) aerosol robotic network (AERONET) Meteorology. Climatology QC851-999 |
spellingShingle |
Qinghai-Tibetan Plateau (QTP) permafrost aerosol optical depth (AOD) dark target method (DT) deep blue method (DB) aerosol robotic network (AERONET) Meteorology. Climatology QC851-999 Zhijian Zhao Hideyuki Tonooka Analysis of Atmospheric Aerosol Changes in the Qinghai-Tibetan Plateau Region during 2009–2019 Using a New Fusion Algorithm |
topic_facet |
Qinghai-Tibetan Plateau (QTP) permafrost aerosol optical depth (AOD) dark target method (DT) deep blue method (DB) aerosol robotic network (AERONET) Meteorology. Climatology QC851-999 |
description |
The Qinghai-Tibetan Plateau (QTP) is the largest permafrost-covered area in the world, and it is critical to understand accurately and dynamically the cyclical changes in atmospheric aerosols in the region. However, due to the scarcity of researchers in this field and the complexity of analyzing the spatial and temporal dynamics of aerosols, there is a gap in research in this area, which we hope to fill. In this study, we constructed a new fusion algorithm based on the V5.2 algorithm and the second-generation deep blue algorithm through the introduced weight factor of light and dark image elements. We used the algorithm to analyze the spatial and temporal changes in aerosols from 2009–2019. Seasonal changes and the spatial distribution of aerosol optical depth (AOD) were analyzed in comparison with the trend of weight factor, which proved the stability of the fusion algorithm. Spatially, the AOD values in the northeastern bare lands and southeastern woodland decreased most significantly, and combined with the seasonal pattern of change, the AOD values in this region were higher in the spring and fall. In these 11 years, the AOD values in the spring and fall decreased the most, and the aerosol in which the AOD decreases occurred should be the cooling-type sulfate aerosol. In order to verify the accuracy of the algorithm, we compared the AOD values obtained by the algorithm at different time intervals with the measured AOD values of several AERONET stations, in which the MAE, RMSE, and R between the AOD values obtained by the algorithm and the measured averages of the 12 nearest AERONET stations in the QTP area were 0.309, 0.094, and 0.910, respectively. In addition, this study also compares the AOD results obtained from the fusion algorithm when dynamically weighted and mean-weighted, and the results show that the error value is smaller in the dynamic weighting approach in this study. |
format |
Article in Journal/Newspaper |
author |
Zhijian Zhao Hideyuki Tonooka |
author_facet |
Zhijian Zhao Hideyuki Tonooka |
author_sort |
Zhijian Zhao |
title |
Analysis of Atmospheric Aerosol Changes in the Qinghai-Tibetan Plateau Region during 2009–2019 Using a New Fusion Algorithm |
title_short |
Analysis of Atmospheric Aerosol Changes in the Qinghai-Tibetan Plateau Region during 2009–2019 Using a New Fusion Algorithm |
title_full |
Analysis of Atmospheric Aerosol Changes in the Qinghai-Tibetan Plateau Region during 2009–2019 Using a New Fusion Algorithm |
title_fullStr |
Analysis of Atmospheric Aerosol Changes in the Qinghai-Tibetan Plateau Region during 2009–2019 Using a New Fusion Algorithm |
title_full_unstemmed |
Analysis of Atmospheric Aerosol Changes in the Qinghai-Tibetan Plateau Region during 2009–2019 Using a New Fusion Algorithm |
title_sort |
analysis of atmospheric aerosol changes in the qinghai-tibetan plateau region during 2009–2019 using a new fusion algorithm |
publisher |
MDPI AG |
publishDate |
2024 |
url |
https://doi.org/10.3390/atmos15060712 https://doaj.org/article/01c5a993dc404905ab389b696b883e6a |
genre |
Aerosol Robotic Network permafrost |
genre_facet |
Aerosol Robotic Network permafrost |
op_source |
Atmosphere, Vol 15, Iss 6, p 712 (2024) |
op_relation |
https://www.mdpi.com/2073-4433/15/6/712 https://doaj.org/toc/2073-4433 doi:10.3390/atmos15060712 2073-4433 https://doaj.org/article/01c5a993dc404905ab389b696b883e6a |
op_doi |
https://doi.org/10.3390/atmos15060712 |
container_title |
Atmosphere |
container_volume |
15 |
container_issue |
6 |
container_start_page |
712 |
_version_ |
1810450559824560128 |