Retrieval of High Temporal Resolution Aerosol Optical Depth Using the GOCI Remote Sensing Data

Lijuan Chen,Yong Zha,Ren Wang,Jiamei Han,Peng Fang,Ying Fei

doi:10.3390/rs13122376

Abstract

High temporal resolution aerosol optical depth (AOD) products are very important for the studies of atmospheric environment and climate change. Geostationary Ocean Color Imager (GOCI) is a suitable data source for AOD retrieval, as it can monitor hourly aerosol changes and make up for the low temporal resolution deficiency of polar orbiting satellite. In this study, we proposed an algorithm for retrieving high temporal resolution AOD using GOCI data and then applied the algorithm in the Yangtze River Delta, a typical region suffering severe air pollution issues. Based on Moderate-resolution Imaging Spectroradiometer (MODIS) surface reflectance determined by MODIS V5.2 algorithm and MODIS Bidirectional Reflectance Distribution Function (BRDF) data, after spectral conversion between MODIS and GOCI, the GOCI surface reflectance at different solar angles were obtained and used to retrieve AOD. Five indicators including correlation coefficient (R), significant level of the correlation (p value), mean absolute error (MAE), mean relative error (MRE) and root mean square error (RMSE) were employed to analyze the errors between the Aerosol Robotic Network (AERONET) observed AOD and the GOCI retrieved AOD. The results showed that the GOCI AOD retrieved by the continental aerosol look-up table was consistent with the AERONET AOD (R > 0.7, p ≤ 0.05). The highest R value of Taihu Station and Xuzhou CUMT Station are both 0.84 (8:30 a.m.); the minimum RMSE at Taihu and Xuzhou-CUMT stations were 0.2077 (11:30 a.m.) and 0.1937 (10:30 a.m.), respectively. Moreover, the results suggested that the greater the solar angle of the GOCI sensor, the higher the AOD retrieval accuracy, while the retrieved AOD at noon exhibited the largest error as assessed by MAE and MRE. We concluded that the inaccurate estimation of surface reflectance was the root cause of the retrieval errors. This study has implications in providing a deep understanding of the effects of solar angle changes on retrieving AOD using GOCI.

Highlights

Atmospheric aerosol is the general term for solid and liquid particles suspended in the atmosphere, mainly come from natural sources such as fine ash and dust lifted by the wind, salt particles, volcanic eruption and from human activities the burning of fossil and non-fossil fuels, transportation, and industrial dust [1]
The results suggested that the greater the solar angle of the Geostationary Ocean Color Imager (GOCI) sensor, the higher the aerosol optical depth (AOD) retrieval accuracy, while the retrieved AOD at noon exhibited the largest error as assessed by mean absolute error (MAE) and mean relative error (MRE)
Lee et al [6] use a look-up table (LUT) separation technology to retrieve the AOD using the Geostationary Ocean Color Imager (GOCI), and the results show that this method can obtain the results of daily monitoring of atmospheric aerosol load, it is very useful for environmental regulatory agencies

Summary

Introduction

Atmospheric aerosol is the general term for solid and liquid particles suspended in the atmosphere, mainly come from natural sources such as fine ash and dust lifted by the wind, salt particles, volcanic eruption and from human activities the burning of fossil and non-fossil fuels, transportation, and industrial dust [1]. Aerosol optical depth (AOD) is the most basic optical characteristic of aerosols, and it is a key indicator for evaluating aerosol radiative forcing [5]. Sun photometers can obtain detailed aerosol optical parameters and the AOD can be estimated, but due to the large variability of the chemical composition and life cycle of atmospheric aerosols, ground stations are not enough to accurately observe and evaluate the spatial distribution characteristics of atmospheric aerosols on a large spatial scale such as regional or global scale.

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Results

Conclusion