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Validating Aerosol Optical Depth Estimation Methods Using the National Institute of Environmental Research Operational Numerical Forecast Model

Authors :
Hye-Jin Kim
Uju Shin
Won Jun Choi
Ja-Ho Koo
Chang H. Jung
Ki-Pyo Nam
Sang-Hun Park
Source :
Applied Sciences, Vol 12, Iss 5, p 2556 (2022)
Publication Year :
2022
Publisher :
MDPI AG, 2022.

Abstract

Currently, significant efforts are being made to enhance the performance of the National Institute of Environmental Research (NIER) operational model. However, the model performance concerning Aerosol Optical Depth (AOD) estimation remains uninvestigated. In this study, three different estimation methods for AOD were implemented using the NIER operational model and validated with satellite and ground observations. In the widely used Interagency Monitoring of Protected Visual Environments (IMPROVE) method, AOD exponentially increases with relative humidity owing to a hygroscopic growth factor. However, alternative methods show better performance, since AOD estimation considers the size dependency of aerosol particles and is not sensitive to high relative humidity, which reduces the high AOD in areas with large cloud fractions. Although some R values are significantly low, especially for a single observational comparison and small numerical domain analysis, one of the alternative estimation methods achieves the best performance for diagnosing AOD in the East Asia region.

Details

Language :
English
ISSN :
20763417
Volume :
12
Issue :
5
Database :
Directory of Open Access Journals
Journal :
Applied Sciences
Publication Type :
Academic Journal
Accession number :
edsdoj.2b41e44a37244af7982b81ffbf4bcfef
Document Type :
article
Full Text :
https://doi.org/10.3390/app12052556