Improved Bi-Angle Aerosol Optical Depth Retrieval Algorithm from AHI Data Based on Particle Swarm Optimization

The Advanced Himawari Imager (AHI) aboard the Himawari-8, a new generation of geostationary meteorological satellite, has high-frequency observation, which allows it to effectively capture atmospheric variations. In this paper, we have proposed an Improved Bi-angle Aerosol optical depth (AOD) retrie...

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Published in:Remote Sensing
Main Authors: Chunlin Jin, Yong Xue, Xingxing Jiang, Yuxin Sun, Shuhui Wu
Format: Text
Language:English
Published: Multidisciplinary Digital Publishing Institute 2021
Subjects:
Online Access:https://doi.org/10.3390/rs13224689
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author Chunlin Jin
Yong Xue
Xingxing Jiang
Yuxin Sun
Shuhui Wu
author_facet Chunlin Jin
Yong Xue
Xingxing Jiang
Yuxin Sun
Shuhui Wu
author_sort Chunlin Jin
collection MDPI Open Access Publishing
container_issue 22
container_start_page 4689
container_title Remote Sensing
container_volume 13
description The Advanced Himawari Imager (AHI) aboard the Himawari-8, a new generation of geostationary meteorological satellite, has high-frequency observation, which allows it to effectively capture atmospheric variations. In this paper, we have proposed an Improved Bi-angle Aerosol optical depth (AOD) retrieval Algorithm (IBAA) from AHI data. The algorithm ignores the aerosol effect at 2.3 μm and assumes that the aerosol optical depth does not change within one hour. According to the property that the reflectivity ratio K of two observations at 2.3 μm does not change with wavelength, we constructed the equation for two observations of AHI 0.47 μm band. Then Particle Swarm Optimization (PSO) was used to solve the nonlinear equation. The algorithm was applied to the AHI observations over the Chinese mainland (80°–135°E, 15°–60°N) between April and June 2019 and hourly AOD at 0.47 μm was retrieved. We validated IBAA AOD against the Aerosol Robotic Network (AERONET) sites observation, including surrounding regions as well as the Chinese mainland, and compared it with the AHI L3 V030 hourly AOD product. Validation with AERONET of 2079 matching points shows a correlation coefficient R = 0.82, root-mean-square error RMSE = 0.27, and more than 62% AOD retrieval results within the expected error of ±(0.05 + 0.2 × AODAERONET). Although IBAA does not perform very well in the case of coarse-particle aerosols, the comparison and validation demonstrate it can estimate AHI AOD with good accuracy and wide coverage over land on the whole.
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op_source Remote Sensing; Volume 13; Issue 22; Pages: 4689
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spelling ftmdpi:oai:mdpi.com:/2072-4292/13/22/4689/ 2025-01-16T18:38:32+00:00 Improved Bi-Angle Aerosol Optical Depth Retrieval Algorithm from AHI Data Based on Particle Swarm Optimization Chunlin Jin Yong Xue Xingxing Jiang Yuxin Sun Shuhui Wu 2021-11-20 application/pdf https://doi.org/10.3390/rs13224689 EN eng Multidisciplinary Digital Publishing Institute Environmental Remote Sensing https://dx.doi.org/10.3390/rs13224689 https://creativecommons.org/licenses/by/4.0/ Remote Sensing; Volume 13; Issue 22; Pages: 4689 AHI AOD IBAA PSO Text 2021 ftmdpi https://doi.org/10.3390/rs13224689 2023-08-01T03:18:46Z The Advanced Himawari Imager (AHI) aboard the Himawari-8, a new generation of geostationary meteorological satellite, has high-frequency observation, which allows it to effectively capture atmospheric variations. In this paper, we have proposed an Improved Bi-angle Aerosol optical depth (AOD) retrieval Algorithm (IBAA) from AHI data. The algorithm ignores the aerosol effect at 2.3 μm and assumes that the aerosol optical depth does not change within one hour. According to the property that the reflectivity ratio K of two observations at 2.3 μm does not change with wavelength, we constructed the equation for two observations of AHI 0.47 μm band. Then Particle Swarm Optimization (PSO) was used to solve the nonlinear equation. The algorithm was applied to the AHI observations over the Chinese mainland (80°–135°E, 15°–60°N) between April and June 2019 and hourly AOD at 0.47 μm was retrieved. We validated IBAA AOD against the Aerosol Robotic Network (AERONET) sites observation, including surrounding regions as well as the Chinese mainland, and compared it with the AHI L3 V030 hourly AOD product. Validation with AERONET of 2079 matching points shows a correlation coefficient R = 0.82, root-mean-square error RMSE = 0.27, and more than 62% AOD retrieval results within the expected error of ±(0.05 + 0.2 × AODAERONET). Although IBAA does not perform very well in the case of coarse-particle aerosols, the comparison and validation demonstrate it can estimate AHI AOD with good accuracy and wide coverage over land on the whole. Text Aerosol Robotic Network MDPI Open Access Publishing Remote Sensing 13 22 4689
spellingShingle AHI AOD
IBAA
PSO
Chunlin Jin
Yong Xue
Xingxing Jiang
Yuxin Sun
Shuhui Wu
Improved Bi-Angle Aerosol Optical Depth Retrieval Algorithm from AHI Data Based on Particle Swarm Optimization
title Improved Bi-Angle Aerosol Optical Depth Retrieval Algorithm from AHI Data Based on Particle Swarm Optimization
title_full Improved Bi-Angle Aerosol Optical Depth Retrieval Algorithm from AHI Data Based on Particle Swarm Optimization
title_fullStr Improved Bi-Angle Aerosol Optical Depth Retrieval Algorithm from AHI Data Based on Particle Swarm Optimization
title_full_unstemmed Improved Bi-Angle Aerosol Optical Depth Retrieval Algorithm from AHI Data Based on Particle Swarm Optimization
title_short Improved Bi-Angle Aerosol Optical Depth Retrieval Algorithm from AHI Data Based on Particle Swarm Optimization
title_sort improved bi-angle aerosol optical depth retrieval algorithm from ahi data based on particle swarm optimization
topic AHI AOD
IBAA
PSO
topic_facet AHI AOD
IBAA
PSO
url https://doi.org/10.3390/rs13224689