Abstract
In this paper, we introduced a new algorithm for retrieving aerosol optical depth (AOD) over land, from the Cloud and Aerosol Imager (CAI), which is one of the instruments on the Greenhouse Gases Observing Satellite (GOSAT) for detecting and correcting cloud and aerosol interference. We used the GOSAT and AErosol RObotic NETwork (AERONET) collocated data from different regions over the globe to analyze the relationship between the top-of-atmosphere (TOA) reflectance in the shortwave infrared (1.6 μm) band and the surface reflectance in the red (0.67 μm) band. Our results confirmed that the relationships between the surface reflectance at 0.67 μm and TOA reflectance at 1.6 μm are not constant for different surface conditions. Under low AOD conditions (AOD at 0.55 μm < 0.1), a Normalized Difference Vegetation Index (NDVI) based regression function for estimating the surface reflectance of 0.67 μm band from the 1.6 μm band was summarized, and it achieved good performance, proving that the reflectance relations of the 0.67 μm and 1.6 μm bands are typically vegetation dependent. Since the NDVI itself is easily affected by aerosols, we combined the advantages of the Aerosol Free Vegetation Index (AFRI), which is aerosol resistant and highly correlated with regular NDVI, with our regression function, which can preserve the various correlations of 0.67 μm and 1.6 μm bands for different surface types, and developed a new surface reflectance and aerosol-free NDVI estimation algorithm, which we named the Modified AFRI1.6 algorithm. This algorithm was applied to AOD retrieval, and the validation results for our algorithm show that the retrieved AOD has a consistent relationship with AERONET measurements, with a correlation coefficient of 0.912, and approximately 67.7% of the AOD retrieved data were within the expected error range (± 0.1 ± 0.15AOD(AERONET)).
Highlights
Aerosols have a considerable influence on the radiative balance of the Earth and global climate change through the absorption and scattering of solar radiation [1,2,3]
Relationship between TOA Reflectance at 1.6 μm and Surface Reflectance at 0.67 μm Atmospheric correction resulted in surface reflectance at 0.67 μm (TANSO-Cloud and Aerosol Imager (CAI) band 2), which was compared with the TOA reflectance at 1.6 μm; Figure 2a shows a plot of their match-ups and regression line, with the color scale indicating the data frequency
The above results indicate that the relationship of 0.67 vs. 1.6 is dependent on the amount of vegetation and that Normalized Difference Vegetation Index (NDVI) can be used as a suitable tuner to interpret how the 0.67 vs. 1.6 ratio changes with different surface types
Summary
Aerosols have a considerable influence on the radiative balance of the Earth and global climate change through the absorption and scattering of solar radiation [1,2,3]. The MODIS DT algorithm uses the linear relationships between the surface reflectance of the SWIR (2.1 μm) channel (negligibly affected by aerosols at this wavelength) and the red or blue channels to account for the surface signal in the corresponding channel This method works best over dark vegetated surfaces, but not over bright land surfaces. An AOD retrieval algorithm can extend the function of TANSO-CAI to the AOD observations to provide one-platform combination data (including carbon dioxide, methane and AOD) for future studies on the relationship between greenhouse gases and aerosols.
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