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Monsoon-seasonal validation of MODIS aerosol optical depth and characterization using AERONET observation retrieve over Italy.

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This study used Angstrom Exponent (AE) relationship with Aerosol Optical Depth (AOD) obtained from space-based direct sky-radiometer of Moderate Resolution Imaging Spectroradiometer (MODIS) and direct Sun algorithm surface-based AERONET network… Click to show full abstract

This study used Angstrom Exponent (AE) relationship with Aerosol Optical Depth (AOD) obtained from space-based direct sky-radiometer of Moderate Resolution Imaging Spectroradiometer (MODIS) and direct Sun algorithm surface-based AERONET network (level 2.0 version 3) to evaluate monsoon season (June-September) aerosol optical depth and characterization at 7 Italy sites: IMAA_POTENZA (40.60N, 15.72E), ISPRA (45.80N, 8.62E), LAMPEDUSA (35.51N, 12.63E), MESSINA (38.19N, 15.56E), MODENA (44.63N, 10.94E), ROME_TOR_VERGATA (41.83N, 12.64E) and VENISE (45.31N, 12.50E) from 2010 to 2019. Standardized anomaly and the standard deviation ratio method of analysis to address the robustness of AE were identified to classify aerosols typing. The extracted monsoon AOD correlation between MODIS and AERONET is (r = 0.95) which is plausible to determine discrepancy in data handling. In order to remove large influence of annual cycle, the data were first detrend. The results show that standard deviation value > 1 indicates monthly dominance than climatology. The standardized anomaly records (-0.22 ± 0.13) for MODIS and AERONET AODs with corresponding correlation of (r = 0.96) in June. There is disparity in AOD data handling from MODIS in some periods, which could attribute that space-based interpretation, should be validated with ground-base observation over Italy. The fine mode aerosols due to high AE values interestingly present the characteristic of AOD dominance, but experience trans-seasonal change, where MODIS has weak correlation.

Keywords: modis; aerosol optical; monsoon; depth characterization; optical depth

Journal Title: Environmental research
Year Published: 2021

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