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

Hye Jin Kim, Uju Shin, Won Jun Choi, Ja Ho Koo, Chang H. Jung, Ki Pyo Nam, Sang Hun Park

Research output: Contribution to journalArticlepeer-review

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 perfor-mance, 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. Alt-hough 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.

Original languageEnglish
Article number2556
JournalApplied Sciences (Switzerland)
Volume12
Issue number5
DOIs
Publication statusPublished - 2022 Mar 1

Bibliographical note

Funding Information:
Funding: This research was supported by a grant from the National Institute of Environment Re‐ search (NIER), funded by the Ministry of Environment (MOE) of the Republic of Korea (e.x. NIER‐ 2019‐01‐02‐085). (S‐H.P.) This work was also supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MEST; 2021R1A2C1012433) and (in part) by the Yonsei University Future‐leading Research Initiative of 2018‐22‐0021.

Funding Information:
This research was supported by a grant from the National Institute of Environment Research (NIER), funded by the Ministry of Environment (MOE) of the Republic of Korea (e.x. NIER? 2019?01?02?085). (S?H.P.) This work was also supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MEST; 2021R1A2C1012433) and (in part) by the Yonsei University Future?leading Research Initiative of 2018?22?0021.

Publisher Copyright:
© 2022 by the authors. Licensee MDPI, Basel, Switzerland.

All Science Journal Classification (ASJC) codes

  • Materials Science(all)
  • Instrumentation
  • Engineering(all)
  • Process Chemistry and Technology
  • Computer Science Applications
  • Fluid Flow and Transfer Processes

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