Validation of MERRA-2 AOT Modeling Data over China Using SIAVNET Measurement

• Published in: Atmosphere
• Main Authors: Shuaiyi Shi, Hao Zhu, Xing Wang
• Format: Article in Journal/Newspaper
• Language: English
• Published: MDPI AG 2023
• Subjects: Aerosol Optical Thickness (AOT); The Modern-Era Retrospective Analysis for Research and Applications Version 2 (MERRA-2); National Civil Space Infrastructure Satellite Aerosol Product Validation Network (SIAVNET); Meteorology. Climatology; QC851-999; Aerosol Robotic Network
• Online Access: https://doi.org/10.3390/atmos14101592; https://doaj.org/article/570150088eec46dc8aad7719c1b30aa4

The Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA-2) Aerosol Optical Thickness (AOT) dataset is a consistent and comprehensive dataset combining observations from various satellite instruments and other sources with a numerical model, supporting climate studies, atmospheric modeling, air quality monitoring, and environmental research. Due to the uneven and sparse distribution of the Aerosol Robotic Network (AERONET) in China, the validation for the MERRA-2 AOT dataset over China is inadequate. The construction of the National Civil Space Infrastructure Satellite Aerosol Product Validation Network (SIAVNET) is helpful to compensate for MERRA-2 AOT dataset validation over China. The validation results show that the accuracy of the MERRA-2 AOT goes down along with the aerosol loading in the atmosphere increase. In general, when the AOT is less than 1.0, the slope can reach 0.712 with R 2 = 0.584. The percentage of data pairs that fall within the GCOS minimum requirement is less than 60%. Research also shows that MERRA-2 has a lower simulation quality of AOT at high altitudes than at low altitudes in China. Additionally, MERRA-2’s AOT simulation quality varies by season. Simulated quality is worst in spring, improving in subsequent seasons. During the winter season, simulations are of the highest quality.