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
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). Aerosols also adversely influence human health and visibility (Samet et al., 2000; Pope et al., 2002; Yang et al., 2015; Wang et al., 2017). Aerosol-related environmental problems have drawn a great deal of attention (Cai et al., 2016).
Using a Sun–sky radiometer to measure both direct solar beam and angular sky radiance is the most common method for a reliable and continuous estimation of detailed aerosol properties over megacities around the world. Several aerosol ground-based observational networks have been established to understand the aerosol optical properties, validate the inversion products of satellite remote sensing, and indirectly evaluate their effect on climate (Uchiyama et al., 2005; Takamura and Nakajima, 2004; Nakajima et al., 2007). The sky radiometer network (SKYNET), the focus of this study, is a ground-based research network of using sky radiometers (PREDE Co., Ltd., Tokyo, Japan) with observation sites principally located in Asia and Europe (Che et al., 2014).
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. SKYNET currently uses the SKYRAD.pack algorithm version 4.2 (Takamura and Nakajima, 2004). 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). Recently, a new SKYRAD.pack version (V5.0) was proposed to improve SSA retrievals (Hashimoto et al., 2012). There are a few applications of SKYRAD V5.0; for example, it has been preliminarily used to retrieve aerosol optical properties over Beijing, China (Che et al., 2014).
This study presents the aerosol optical properties over Qionghai and Yucheng derived from SKYNET sky radiometer measurements by using SKYRAD.pack V5.0 and V4.2 during February 2013 to December 2015. This work is designed to achieve the following objectives: (1) investigate the difference in the aerosol optical properties derived by SKYRAD.pack V5.0 and V4.2 over the two SKYNET sites; and (2) analyze the seasonal variability of aerosol optical properties over the two sites based on SKYRAD.pack V5.0. The results presented in this study provide valuable references for continued improvement of the retrieval algorithms of SKYNET and other aerosol observational networks.
The sky radiometer (model POM-02, PREDE Co. Ltd.) was deployed at Qionghai
and Yucheng starting in February 2013 and August 2012, respectively. The
PREDE-POM02 model was equipped with an indium gallium arsenide (InGaAs) detector to measure the direct
solar irradiance and the sky diffuse radiance at 11 wavelengths, namely
315, 340, 380, 400, 500, 675, 870, 940, 1020, 1627, and 2200 nm. The data
from five channels at 400, 500, 675, 870, and 1020 nm were used here to
retrieve the aerosol optical properties over Qionghai and Yucheng. The full
angle field of view is 1.0
The Qionghai site of SKYNET (19.23
The other measurement site in this study is located in rural Yucheng
(36.82
The locations of the two SKYNET sites in the study.
The aerosol optical properties (i.e., AOD, SSA, complex refractive index,
and volume SDF) were derived in this study by using SKYRAD.pack V4.2 and
V5.0. Within the SKYRAD.pack code, the inversion schemes were used to derive
the single scattering term
The retrieved
The retrieval of
V4.2 used the iterative relaxation method of Nakajima et al. (1983, 1996) to
remove the multiple scattering contribution and derived an optimal solution
using a statistical regularization method (Turchin and Nozik, 1969) by
minimizing the following cost function as proposed by Phillips (1962) and
Twomey (1963):
The
The non-linear inversion has a strong dependence on the estimation of the
first-guess solution. V5.0 uses an a priori SDF of a bimodal log-normal
function as follows:
SKYRAD V5.0 developed a stricter data quality control method of observation
data and cloud screening. The standard process of quality control in SKYNET
applies a retrieval error between observations and calculated theoretical
values by using retrieval values,
The cloud screening method in V4.2 relies heavily on the global flux test and needs global irradiance data, but almost all SKYNET sites do not have solar irradiance observations. Furthermore, cirrus contamination data are difficult to remove as cloud-affected data (Hashimoto et al., 2012).
V5.0 poses a condition regarding the magnitude of the coarse mode of the
SDF:
The results retrieved by SKYRAD.pack V4.2 were used to compare with the
results retrieved by SKYRAD.pack V5.0. The intercomparisons of the volume
size distribution, single scattering albedo, and refractive index between V5.0
and V4.2 were based on 1397 measurements in 355 d over Qionghai and 5830
measurements in 473 d over Yucheng. Considering a relatively low
retrieval accuracy of SSA when AOD < 0.2 (Dubovik et al., 2000),
only the measurements with AOD
Scattergrams of the AOD derived by SKYRAD V4.2 and V5.0 at wavelengths of 400, 500, 670, 870, and 1020 nm over Qionghai and Yucheng during February 2013 to December 2015.
Aerosol size properties were one of the most important pieces of information for both
the observation and modeling of radiative forcing (Dusek et al., 2006). The
volumes at each bin were averaged monthly during the experiment period for
V4.2 and V5.0 over Qionghai and Yucheng (Fig. 3). The SDF by V4.2 usually
showed a predominant peak at the coarse mode with a radius over 10
Retrieved monthly volume size distribution by SKYRAD V4.2 (dotted lines) and V5.0 (solid lines) for Qionghai (blue lines) and Yucheng (red lines) during February 2013 to December 2015.
As shown in Figs. 4 and 5, the differences in the retrieved size
distribution at smaller size (
Averaged volume size distribution in each bin and the differences between the two versions at the Qionghai site during February 2013 to December 2015.
VOL indicates volume spectrum
(
The same as Table 1 but for Yucheng during February 2013 to December 2015.
Meanings of all symbols are the same as in Table 1.
As shown in Tables 1 and 2, the percentage difference in the volume
size distributions between SKYRAD V5.0 and V4.2 were larger than 50 % at
smaller size (
Scattergrams of volume size distribution retrieved by SKYRAD V4.2
and V5.0 in 20 bins over Qionghai during February 2013 to December 2015.
Only data with AOD
The same as Fig. 4 but for the Yucheng site.
As a key variable in assessing the climatic effects of aerosols, the SSA is defined as the ratio of the scattering coefficient and the extinction coefficient. It characterizes the absorption properties of aerosols and serves as an important quantity in evaluating aerosol radiative forcing. The SSA value is mostly dependent on the shape, size distribution, and concentration of aerosol particles.
Averaged single scattering albedo and refractive index in SKYRAD V5.0 and V4.2, and the absolute and percentage differences between the two versions at the Qionghai site during February 2013 to December 2015.
The same as Table 3 but for Yucheng during February 2013 to December 2015.
Meanings of all symbols are the same as in Table 3.
Tables 3 and 4 presented average single scattering albedo and refractive
index for SKYRAD V5.0 and V4.2 and the differences between the two versions
over Qionghai and Yucheng during February 2013 to December 2015,
respectively. The differences between SSAs retrieved by SKYRAD V5.0 and V4.2
at 400, 500, 675, 870, and 1020 nm over Qionghai were
Figure 6 presented the comparison results between SSAs retrieved by SKYRAD
V4.2 and V5.0 at wavelengths of 400, 500, 670, 870, and 1020 nm over
Qionghai and Yucheng during February 2013 to December 2015. As shown in
Fig. 6, SSAs by V5.0 correlated with those by V4.2 with
Scattergrams of the single scattering albedo retrieved by SKYRAD
V4.2 and V5.0 at wavelengths of 400, 500, 670, 870, and 1020 nm over
Qionghai and Yucheng during February 2013 to December 2015. Only data with
AOD
The averaged
The complex refractive index in V4.2 can only be chosen from the predefined set
of values.
Scattergrams of the imaginary part of the complex refractive index
(
The same as Fig. 7 but for the real part of the complex refractive
index (
The accurate retrieval of SSA is more difficult than estimation of AOD and
size distribution (Loeb and Su, 2010; McComiskey et al., 2008). The errors
associated with
Based on the measurements over the two sites in January, April, July, and
October 2014, several sensitivity tests were carried out to test the
magnitude of the change in SSA. We assumed an error of
As shown in Fig. S1 in the Supplement, when we assumed an error of
The SVA is related to the sky radiance, and errors in the SVA will affect
the SSA results. Figure S2 shows that an error of
Although the value of
For the AOD at the wavelength of 0.5
We also investigated the differences in SSAs due to the assumed errors in
atmospheric pressure (PRS). PRS was considered to be 1.00 (atm) in the
experimental group, while it was sequentially changed by 1 % in the
control groups. As shown in Fig. S5, the averaged changes in SSA retrieved by
V5.0 in the four control groups compared with the experimental group were
all smaller than those in SSA retrieved by V4.2 over both sites. In
Qionghai, with the PRS increased by 1 %, 2 %, 3 %, and 4 %, the
averaged changes in SSAs by V5.0 were 0.18 %, 0.21 %, 0.17 %, and
0.26 %; those by V4.2 were 0.66 %, 0.56 %, 0.58 %, and 0.78 %. The
averaged changes in SSAs retrieved by V5.0 over Yucheng were 0.17 %,
0.21 %, 0.23 %, and 0.22 %; those by V4.2 were 0.44 %, 0.46 %,
0.47 %, and 0.50 %. The changes in SSAs
On the basis of the above sensitivity tests, it is concluded that an error
in the calibration constant (
The most different physical process between V4.2 and V5 is a derivation of
particle size distribution. When a large amount of coarse particles of the
dust-like aerosol type with radius greater than 10
Scattergrams of retrieved SSA by SKYRAD V4.2 and V5.0 when
We also investigated whether the total amount of aerosols in the atmosphere
was linked to the differences in SSA between the two versions. As shown in
Fig. 10, the SSA differences at 500 nm between the two versions (defined as
SSA_V5.0
Scattergrams of the difference between SSAs at 500 nm retrieved by V5.0 and V4.2 (defined as SSA_V5.0–SSA_V4.2) and the corresponding AODs at 500 nm by V5.0 during February 2013 to December 2015.
Base on the intercomparison results in Sect. 3.1 and the sensitivity
tests in Sect. 3.2, we could not reach the conclusion that V5.0 is definitely
better than V4.2. We do not yet have other measurements in the two sites to
help us prove that V5.0 is better than V4.2. The most different physical
process between the two versions is the derivation of particle size
distribution. On the one hand, V5.0 tends to be robust in detecting cloud
contamination, due to inversion constraint by a priori SDF which filters
out coarse particles to simulate cloud-scattered radiation. Some tests by
Hashimoto et al. (2012) showed that the SDF setting in V5.0 was useful for
detecting ill-conditioned data caused by cirrus contaminations, horizontally
and/or temporally inhomogeneous aerosol stratification, and so on (Hashimoto
et al., 2012). On the other, because a priori SDF for constraint tends to be
zero for radii larger than 10
Considering that V5.0 adopts more rigorous data processing and cloud
detection methods, and that the SSA and
The analysis of the 500 nm channel was chosen because it was widely quoted in Sun photometric and remote sensing applications and generally representative of visible band wavelengths (Estellés et al., 2012b). Four seasons were considered in this paper, i.e., spring (March–May), summer (June–August), autumn (September–November), and winter (December–February), to investigate the seasonal variations of the aerosol optical properties over Qionghai and Yucheng based on SKYRAD.pack V5.0.
The AOD is representative of the aerosol loading in the atmospheric column and important for the identification of the aerosol source regions and the aerosol evolution.
The AOD showed a distinct seasonal variation over both Qionghai and Yucheng. Figure 11a showed that the seasonal averaged AOD over Qionghai had higher values in spring, winter, and autumn and lower values in summer. During summer, the dominant wind is from south to southeast (Zhu et al., 2005) and the main emission source was from the South China Sea and western Pacific. In addition, seasonal upwelling off the east coast of the island of Hainan was strongest in summer (Li et al., 2018), which was conducive to pollutant diffusion. Meanwhile, rich precipitation in summer was effective for eliminating aerosols. Because of the reasons above, seasonal averaged value of AOD in summer was the lowest in Qionghai. In contrast, AOD in spring was higher than other seasons. Southerly and northeasterly winds both prevail in spring over Qionghai (Liu et al., 2018), so long-distance transport and emissions from surrounding areas were probably both the main pollutant sources.
The maximum AOD average of 0.99 occurred in summer over Yucheng. Several factories which produced inorganic and organic fertilizers were located around this site. The stronger sunlight in summer accelerated the photochemical reaction and enhanced the formation of fine particulate nitrate (Wen et al., 2015). Also, the humidity in summer over Yucheng was higher than in other seasons (Meng et al., 2007). The high humidity combined with large fractions of hygroscopic chemical components (e.g., sulfate, nitrate, ammonium, and some organic matters) can enhance light extinction (Tao et al., 2017). AOD was higher in spring than in autumn and winter, which is likely related to the long-range transportation of dust from northern/northwestern China and pollutants emitted from enterprises in Hebei (Tan et al., 2012; Tao et al., 2017).
Seasonal variations in the AOD
Figure 11b shows the seasonal averaged SSA at 500 nm for Qionghai and Yucheng during February 2013 to December 2015. In Qionghai, the seasonal averaged SSA values were approximately 0.91, 0.90, 0.90, and 0.89 in spring, summer, autumn, and winter, respectively. The lowest seasonal average SSA was observed in winter, which was probably attributable to the regional transport of the air masses originating from eastern China, where a great amount of coal was used for industrial enterprises and emitted a large amount of organic carbon (OC) and elemental carbon (EC) (Liu et al., 2018). In Yucheng, the seasonal pattern of SSA was consistent with AOD; the lowest seasonal average SSAs were also observed in winter due to carbonaceous aerosols increased by heating activities and biomass burning in cold seasons (Tao et al., 2017). High concentrations of fine particulate nitrate were frequently observed in summer in Yucheng (Wen et al., 2015), likely causing the high SSA in summer.
Figure 12a and b show the seasonal averaged volumes of the different
aerosol particle size distributions (
As shown in Fig. 12b, the coarse-mode particles in Yucheng had a relatively large value compared to the volume distribution of the fine-mode particles. The aerosol was not only from winter heating but also from regional transport in winter (Tao et al., 2017; Zhao et al., 2018b). The volume fraction of the coarse aerosol particles relative to the whole was much larger in spring than in other seasons in Yucheng probably because of the presence of dust particles transported from the northwest of China and pollutants emitted from enterprises in Hebei (Tao et al., 2017).
Seasonally averaged volumes of the different aerosol particle
size distributions based on SKYRAD V5.0 over Qionghai
The real part of the refractive index (
Figure 13a showed the seasonal variation of the real part of the refractive
index (
Seasonal variations in the real part of the refractive
index
The aerosol optical properties over the two new SKYNET sites of Qionghai and
Yucheng in China were continuously investigated over 2 years using the
PREDE-POM02 sky radiometer measurements. As V5.0 used an a priori SDF of a
bimodal log-normal function, the volume size distribution retrieved by V5.0
presented an overall bimodal pattern with a 0.10–0.20
On the basis of the sensitivity tests, it is concluded that an error in the
calibration constant (
Based on SKYRAD.pack V5.0, the seasonal variations of the aerosol optical properties over Qionghai and Yucheng were investigated. The seasonal patterns of AOD were quite different between the two stations. The AOD showed high values in spring, autumn, and winter but decreased to minimum in summer over Qionghai, likely related to summer monsoon from the South China Sea and western Pacific that brought most of the annual rainfall to the island, whereas the winter monsoon from Inner Mongolia carried the air masses from mainland China to Qionghai. In Yucheng, the maximum seasonal averaged AOD and SSA both appeared in summer probably due to the hygroscopic effects. The fraction of the fine aerosol particles over Qionghai was much smaller in summer, which is probably related to wet deposition. Specifically, more precipitation in the summer can lead to more efficient removal of aerosol. The volume fraction of the coarse aerosol particles relative to the whole in spring was much larger than in other seasons in Yucheng, probably due to the presence of the dust particles transported from the northwest of China and pollutants emitted from enterprises in Hebei. The location and distribution of major industrial sources, intensity of local minor sources such as winter heating, and prevailing wind directions together caused the different seasonal variations between the two sites discussed above.
The comparison results between the aerosol optical properties retrieved by SKYRAD V5.0 and SKYRAD V4.2 were very different over the two SKYNET sites. The results can provide validation data in China for SKYNET to continue improving data processing and inversion methods. Meanwhile, the results can promote the integration of more Chinese observation stations into the international network.
The sky radiometer data at Qionghai and Yucheng, China, are available on request by contacting the first author of the paper (jiangzhe@mail.iap.ac.cn).
The supplement related to this article is available online at:
ZJ and HC designed the study; MD and WZ performed observation; ZJ analyzed data and wrote the paper, with support from all authors. TN designed the inversion method, and MH improved the inversion method. TN, MH, BC, and AY gave useful comments.
The authors declare that they have no conflict of interest.
This article is part of the special issue “SKYNET – the international network for aerosol, clouds, and solar radiation studies and their applications (AMT/ACP inter-journal SI)”. It is not associated with a conference.
The observation was supported by Qionghai Meteorological Bureau of Hainan Province and Yucheng Shandong Agro-ecosystem National Observation and Research Station (YSA-NORS).
This research has been supported by the National Key Research and Development Program of China (grant no. 2017YFB0503603) and the National Natural Science Foundation of China (grant nos. 41975178, 41825011, 41301381, 41475026, and 41705014).
This paper was edited by Stelios Kazadzis and reviewed by two anonymous referees.