Abstract
Abstract. This study analyzed the aerosol optical properties derived by SKYRAD.pack versions 5.0 and 4.2 (referred to as V5.0 and V4.2) using the radiometer measurements over Qionghai and Yucheng in China, two new sites of the sky radiometer network (SKYNET). As V5.0 uses an a priori size distribution function (SDF) of a bimodal log-normal function, the volume size distribution retrieved by V5.0 presented bimodal patterns with a 0.1–0.2 µm fine particle mode and a 3.0–6.0 µm coarse particle mode both over Qionghai and Yucheng. The differences in the volume size distributions between the two versions were very large for the coarse mode with a radius of over 5 µm. The single scattering albedos (SSAs) by V5.0 correlated with SSAs by V4.2 with R=0.88, 0.87, 0.90, 0.88, and 0.92 at wavelengths of 400, 500, 670, 870, and 1020 nm over Qionghai, respectively. The correlation coefficients were around 0.95, 0.95, 0.96, 0.94, and 0.91 at the five channels in Yucheng. An error of ±5 % for the solid view angle (SVA) introduced about ±2 % differences in retrieved SSA values both by V4.2 and V5.0. An error of ±50 % for ground surface albedo (Ag) caused about 1 % averaged differences in retrieved SSA values by the two versions. With the atmospheric pressure (PRS) increased by 1 %, 2 %, 3 %, and 4 %, the averaged changes in SSAs did not exceed 0.8 % both by V4.2 and V5.0. The SSA differences at 500 nm between the two versions decreased, while aerosol optical depths (AODs) increased over both sites. The seasonal variability of the aerosol properties over Qionghai and Yucheng was investigated based on SKYRAD.pack V5.0. The seasonal averaged AOD over Qionghai had higher values in spring, winter, and autumn and lower values in summer. The AOD averages were commonly higher in summer and spring than in winter and autumn in Yucheng. The lowest seasonal averaged SSAs were both observed in winter at the two sites. The fraction of the fine aerosol particles was much smaller in summer than in other seasons over Qionghai; the volume fraction of the coarse-mode particle in Yucheng had much larger values compared to the fine-mode particle in all seasons. The validation results provide valuable references for continued improvement of the retrieval algorithms of SKYNET and other aerosol observational networks.
Highlights
Aerosols are well known to have significant impacts on climate change and global hydrologic cycle by absorbing and scattering solar radiation (Hensen et al, 1997; Sun et al, 2017) and participating in cloud processes (Ackerman et al, 2000; Ramanathan et al, 2001; Kaufman et al, 2005; Li et al, 2011; Bi et al, 2014; Zhao et al, 2018a)
On the basis of the above sensitivity tests, it is concluded that an error in the calibration constant (F0) causes an error in both retrieved single scattering albedos (SSAs) and aerosol optical depths (AODs)
The aerosol optical properties over the two new sky radiometer network (SKYNET) sites of Qionghai and Yucheng in China were continuously investigated over 2 years using the PREDE-POM02 sky radiometer measurements
Summary
Aerosols are well known to have significant impacts on climate change and global hydrologic cycle by absorbing and scattering solar radiation (Hensen et al, 1997; Sun et al, 2017) and participating in cloud processes (Ackerman et al, 2000; Ramanathan et al, 2001; Kaufman et al, 2005; Li et al, 2011; Bi et al, 2014; Zhao et al, 2018a). The direct solar and angular sky radiance data measured by the sky radiometers are processed to obtain the aerosol optical properties, such as aerosol optical depth (AOD), single scattering albedo (SSA), complex refractive index, and volume size distribution function (SDF) using SKYRAD.pack, which is the official retrieval algorithm of SKYNET (Nakajima et al, 1996) with several different versions. The aerosol retrievals derived from the SKYRAD.pack version 4.2 algorithm have been used to investigate the regional and seasonal characteristics of aerosols for climate and environmental studies and to validate satellite remote sensing results (e.g., Kim et al, 2004; Che et al, 2008, 2018; Campanelli et al, 2010; Estellés et al, 2012a; Wang et al, 2014). The results presented in this study provide valuable references for continued improvement of the retrieval algorithms of SKYNET and other aerosol observational networks
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