气候变化领域集成服务门户(CCPortal): A High-Precision Aerosol Retrieval Algorithm (HiPARA) for Advanced Himawari Imager (AHI) data: Development and verification

CCPortal

DOI	10.1016/j.rse.2020.112221
	A High-Precision Aerosol Retrieval Algorithm (HiPARA) for Advanced Himawari Imager (AHI) data: Development and verification
	Su X.; Wang L.; Zhang M.; Qin W.; Bilal M.
发表日期	2021
ISSN	00344257
卷号	253
英文摘要	Due to the complexity of land cover and aerosol types, the high-precision retrieval of land aerosol properties is challenging. A land general aerosol (LaGA) algorithm called the High-Precision Aerosol Retrieval Algorithm (HiPARA) is proposed for the Advanced Himawari Imager (AHI) sensor over East Asia. In this algorithm, a monthly spectral base reflectance ratio library was constructed to obtain a pixel-by-pixel spectral reflectance relationship model. Statistical methods were used to obtain aerosol types in China, and a linearization scheme for the aerosol types was proposed based on sensitivity analysis. Based on these techniques, HiPARA achieved a completely dynamic determination of the surface reflectance and aerosol types. The new multiband aerosol characteristic retrieval strategy can return two parameters, aerosol optical depth (AOD) and single scattering albedo (SSA). The AOD retrieved from HiPARA showed high consistency with AERONET AOD measurements, with correlation coefficients (R) of 0.939, a mean absolute error (MAE) of 0.082, a root mean square error (RMSE) of 0.113, ratios that meet an expected error (EE) of 0.825, and ratios that meet a Global Climate Observing System (GCOS) error of 0.339. Comparison of the HiPARA retrieved AOD with other operational aerosol products revealed that the accuracy of the HiPARA product was better than those of the Japan Aerospace Exploration Agency (JAXA) product (R < 0.9, RMSE > 0.175), Moderate-resolution Imaging Spectro-radiometer (MODIS) products (Dark Target (DT) algorithm, R = 0.907, RMSE = 0.203; Deep Blue (DB) algorithm, R = 0.909, RMSE = 0.139) and Visible/Infrared Imager Radiometer Suite (VIIRS) AERDB product (R = 0.932, RMSE = 0.117). The HiPARA fitting line was close to 1:1 (i.e., y = x). The aerosol products were further evaluated for four extreme aerosol events: a smoke aerosol event, a haze aerosol event, a dust aerosol event, and a continuous aerosol variation event. Observation of the true-color images and AOD retrievals showed that the HiPARA AOD distribution matched the true-color images very well. The JAXA product had abnormal values and spatial discontinuities. The MODIS and VIIRS products were not as good as the HiPARA product in terms of spatial coverage. In the application to continuous monitoring of a dust event, the HiPARA AOD captured the variations in and intensity of the dust aerosols very well. These results suggested the robustness of HiPARA and its potential for monitoring extreme pollution events with high precision and high temporal resolution. © 2020 Elsevier Inc.
英文关键词	Aerosol type; BRDF; Himawari-8; HiPARA; Land general aerosol (LaGA) algorithm
语种	英语
scopus关键词	Dust; Errors; Mean square error; Pixels; Radiometers; Reflection; Sensitivity analysis; Smoke; Space research; Supercomputers; Aerosol characteristics; Aerosol retrieval algorithms; Extreme pollution events; Global climate observing systems; High temporal resolution; Japan Aerospace Exploration Agency; Root mean square errors; Single scattering albedo; Aerosols; AERONET; aerosol composition; air quality; albedo; algorithm; atmospheric pollution; dust; haze; MODIS; optical depth; China; Far East; Japan
来源期刊	Remote Sensing of Environment
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/179024
作者单位	Key Laboratory of Regional Ecology and Environmental Change, School of Geography and Information Engineering, China University of Geosciences, Wuhan, China; Hubei Key Laboratory of Critical Zone Evolution, School of Geography and Information Engineering, China University of Geosciences, Wuhan, 430074, China; School of Marine Sciences, Nanjing University of Information Science and Technology, Nanjing, 210044, China
推荐引用方式 GB/T 7714	Su X.,Wang L.,Zhang M.,et al. A High-Precision Aerosol Retrieval Algorithm (HiPARA) for Advanced Himawari Imager (AHI) data: Development and verification[J],2021,253.
APA	Su X.,Wang L.,Zhang M.,Qin W.,&Bilal M..(2021).A High-Precision Aerosol Retrieval Algorithm (HiPARA) for Advanced Himawari Imager (AHI) data: Development and verification.Remote Sensing of Environment,253.
MLA	Su X.,et al."A High-Precision Aerosol Retrieval Algorithm (HiPARA) for Advanced Himawari Imager (AHI) data: Development and verification".Remote Sensing of Environment 253(2021).