Effect of the Vertical Distribution of Absorbing Aerosols on the Atmospheric Correction for Satellite Ocean Color Remote Sensing

2022 
The vertical distribution of absorbing aerosols has nonnegligible impact on the atmospheric correction of satellite ocean color remote sensing, especially for the water-leaving radiance retrieval at blue and ultraviolet bands. In this study, we investigated the impact of the vertical distribution of absorbing aerosols on the satellite-measured radiance at the top of the atmosphere (TOA) and the retrieved water-leaving radiance. First, the global occurrence frequency of absorbing aerosols was mapped, and it was found that the annual averaged occurrence frequencies of absorbing aerosols were >30% over the coasts of the Sahara and Arabian Desert, China, South-Central Africa, and the Indian Peninsula. Second, a new aerosol classification algorithm was developed to establish absorbing aerosol optical models based on AERosol RObotic NETwork (AERONET) site observations. Finally, the effects of the vertical distribution of absorbing aerosols on the upward radiance at the TOA at 412 nm and the retrieved water-leaving radiance were evaluated. The results showed that the influence of the vertical distribution on the TOA radiance could be up to 8% for dust and 10% for fine-dominated absorbing aerosols (FDAs), which was comparable with the influence of aerosol optical depth. Not considering absorbing aerosols during atmospheric correction might produce $\sim 4$ %–10% errors in the water-leaving radiance retrieval at 412 nm over turbid waters under the assumption of a Gaussian distribution. Simplified exponential and two-layer atmospheric vertical distribution models can lead to errors of water-leaving radiance retrieval up to $\sim 12$ %–15% and $\sim 30$ %–40%, respectively. Overall, the imperfect vertical distribution assumption and aerosol model selection might induce uncertainty in water-leaving radiance retrieval from 10% to 80% under absorbing aerosol conditions.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    43
    References
    0
    Citations
    NaN
    KQI
    []