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(a) The location of six sun photometer sites over eastern China. (b) The scatter plots of SSA between MERRA-2 and the sun photometer in Xuzhou, Shouxian, and Hefei. Orange dots represent Xuzhou samples, and the orange line is the fitting curve of Xuzhou samples while green represents Shouxian and black represents Hefei. Dashed lines are the range of ±10 % relative error. (c) The scatter plots of SSA between MERRA-2 and the sun photometer in Taihu, Pudong, and Hangzhou. Red dots represent Taihu samples, and the red line is the fitting curve of Taihu samples while purple represents Pudong and yellow represents Hangzhou. Dashed lines are the range of ±10 % relative error.
Source publication
Atmospheric aerosols play a crucial role in regional radiative
budgets. Previous studies on clear-sky aerosol direct radiative forcing
(ADRF) have mainly been limited to site-scale observations or model
simulations for short-term cases, and long-term distributions of ADRF in
China have not been portrayed yet. In this study, an accurate fine-resolut...
Contexts in source publication
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... for trend analysis of aerosol data. The detailed analysis can be found in Li et al. (2014). Prior to trend analysis, ADRF data were deseasonalized by subtracting the monthly mean during [2000][2001][2002][2003][2004][2005][2006][2007][2008][2009][2010][2011][2012][2013][2014][2015][2016] to eliminate the influence of annual and seasonal cycles. (Fig. 3a), were chosen for comparison with MERRA-2 SSA data. The location of the sun photometers was shown in Fig. 3a, and their geographical characteristics, observing periods, sample numbers, and the fitted regression equation between MERRA-2 and sun photometer SSA were presented in Table 2. Five sites (Xuzhou, Shouxian, Hefei, Taihu, and ...
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... ADRF data were deseasonalized by subtracting the monthly mean during [2000][2001][2002][2003][2004][2005][2006][2007][2008][2009][2010][2011][2012][2013][2014][2015][2016] to eliminate the influence of annual and seasonal cycles. (Fig. 3a), were chosen for comparison with MERRA-2 SSA data. The location of the sun photometers was shown in Fig. 3a, and their geographical characteristics, observing periods, sample numbers, and the fitted regression equation between MERRA-2 and sun photometer SSA were presented in Table 2. Five sites (Xuzhou, Shouxian, Hefei, Taihu, and Hangzhou) are AERONET sites, and level 1.5 inversion data of AERONET were used. The uncertainty of AERONET ...
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... zenith in this period avoids possible inversion errors and im-proves the data accuracy (Tian et al., 2018b). Additionally, the specific MERRA-2 grid cell containing the sun photometer was selected, and sun photometer SSA was hourly averaged to match the MERRA-2 SSA product. The detailed comparisons at Xuzhou, Shouxian, and Hefei are shown in Fig. 3b. Figure 3c displays the comparison results at Taihu, Pudong, and Hangzhou. As shown in Fig. 3, dashed lines are the range of ±10 % relative error; all samples in Taihu, Pudong, Hefei, 94 % of samples in Xuzhou, 93 % in Shouxian, and 98 % in Hangzhou fall within the ±10 % error. This finding suggests that MERRA-2 SSA agrees well with ...
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... detailed comparisons at Xuzhou, Shouxian, and Hefei are shown in Fig. 3b. Figure 3c displays the comparison results at Taihu, Pudong, and Hangzhou. As shown in Fig. 3, dashed lines are the range of ±10 % relative error; all samples in Taihu, Pudong, Hefei, 94 % of samples in Xuzhou, 93 % in Shouxian, and 98 % in Hangzhou fall within the ±10 % error. ...
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... et al., 2018b). Additionally, the specific MERRA-2 grid cell containing the sun photometer was selected, and sun photometer SSA was hourly averaged to match the MERRA-2 SSA product. The detailed comparisons at Xuzhou, Shouxian, and Hefei are shown in Fig. 3b. Figure 3c displays the comparison results at Taihu, Pudong, and Hangzhou. As shown in Fig. 3, dashed lines are the range of ±10 % relative error; all samples in Taihu, Pudong, Hefei, 94 % of samples in Xuzhou, 93 % in Shouxian, and 98 % in Hangzhou fall within the ±10 % error. This finding suggests that MERRA-2 SSA agrees well with the sun photometer data, even though a few SSA samples are beyond the error range. Furthermore, ...
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... is the key to portraying the scattering direction of aerosols. ASY = 1 denotes completely forward scattering, and ASY = 0 is symmetric (Rayleigh) scattering. Here, gridded ASY was simulated by matching observed F_u_toa (from CERES) with simulated F_u_toa (from SBDART). The sensitivity test indicates that F_u_toa, just similar to F_u_sur (shown in Fig. S3b), is a monotonically increasing function of ASY with other fixed inputs. Consequently, only one F_u_toa can be obtained with one specific ASY. With this premise, a binary search was applied to approximate ASY to improve calculation efficiency (Chang, 2013). The goal of the binary search is to find the ASY when the simulated F_u_toa is ...
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... specific case in Shanghai on 11 October 2015, was used with the following values: AOD = 0.62, SSA = 0.85, ASY = 0.69, surface albedo = 0.13, total column water vapor = 0.69 g cm −2 , and total column ozone = 0.28 atm cm −1 . Figure S3 portrays the responses of F_d_sur, F_u_sur, and ADRF to changes in one parameter while holding the other parameters constant. To remove the impact of units, all the parameters are dimensionless; that is, the ratio of the input to the actual value is used as the x-axis value. ...
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... absolute value of every slope describes the impact of every parameter on the dependent variables (F_d_sur, F_u_sur, and ADRF). Figure S3 presents the actual condition of this case when the value of the x axis equals 1, in which F_d_sur is 629.15 W m −2 , F_u_sur is 83.52 W m −2 , and ADRF is −149.39 ...
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... of this case when the value of the x axis equals 1, in which F_d_sur is 629.15 W m −2 , F_u_sur is 83.52 W m −2 , and ADRF is −149.39 W m −2 . This situation denotes a strong cooling effect of aerosols at the surface. Apparently, different parameters impose diverse influences on the radiative values (F_d_sur, F_u_sur, and ADRF). As depicted in Fig. S3, AOD, SSA, and ASY are three crucial parameters that greatly influence F_d_sur. P. conducted the radiative closure experiment in the Netherlands and further found that AOD can affect the changes of direct and diffuse irradiation, while SSA and ASY only affect the diffuse irradiance. For F_u_sur, albedo, AOD, and SSA are more important ...
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We examine the impact of atmospheric aerosols and clouds on the surface solar radiation
and solar energy at Nainital, a high-altitude remote location in the central Gangetic Himalayan
region (CGHR). For this purpose, we exploited the synergy of remote-sensed data in terms of groundbased AERONET Sun Photometer and satellite observations from the MOD...
Citations
... It is wellknown that aerosol loadings not only affect the regional energy budget but also have influences on global climate change [24][25][26][27][28]. There are already some studies that characterized aerosol optical properties and quantified the ADRE in China [29][30][31][32]. According to Filonchyk et al. [33], the distribution of AOD decreases gradually from east to west in China. ...
Different aerosol types exhibit distinct radiative effects in different regions, attributed to their unique optical characteristics and regional distributions. This study focuses on North China, which is impacted by both natural and anthropogenic aerosols with high concentrations and a variety of aerosol types. While many studies on aerosol direct radiative effects have been conducted in this region, the majority have focused on a specific type of aerosol or overall aerosol, leaving limited research on the direct radiative effects and contributions of different aerosol types. In this study, we use CALIPSO satellite data from 2011 to 2020 to investigate concentrations and distributions of different aerosol types. The results reveal that dust, polluted dust, polluted continental/smoke, and elevated smoke are the dominant aerosol types in North China. Based on the radiative closure experiment, we systematically calculate the radiative effects of different aerosol types and their corresponding contributions to the energy budget by combining satellite data with the Fu–Liou radiative transfer model. The annual average net aerosol direct radiative effect (ADRE) of North China is −6.1 and −13.43 W m−2 at the TOA and surface, respectively, causing a net warming effect of 7.33 W m−2 in the atmosphere. For each main aerosol type, dust contributes 93% to the shortwave ADRE in the western dust source region, while polluted dust mainly contributes 31% and 45% of the total ADRE, in Northwest China and North China Plain, respectively. Anthropogenic pollutant aerosols account for 58% of the total ADRE in Northeast China. This study holds great significance in elucidating the dominant aerosol types and their concentrations in North China, comprehending the impacts of different aerosol types on the local energy balance.
... For example, Jia et al. (2021) estimated the radiative forcing of aerosol-cloud interactions using the fine mode fraction (FMF) obtained from MERRA-2. Wang et al. (2020) and Xu et al. (2022) utilized the single scattering albedo (SSA) data from MERRA-2 as input to estimate the direct aerosol radiative forcing. Sun et al. (2019) analyzed the spatiotemporal patterns of absorbing AOD. ...
The Modern-Era Retrospective analysis for Research and Applications (MERRA-2) provides a spatiotemporal seamless simulation of global aerosol properties. This study focused on evaluating its diurnal AOD accuracy and variation and the performance of multi-aerosol properties (including Ångström exponent (AE), fine mode fraction (FMF), and single scattering albedo (SSA)) using AERONET measurements. The spatial distribution patterns of MERRA-2 AOD are compared with the MODIS (daytime) and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO, nighttime) satellite products, respectively. The results show that MERRA-2 AOD exhibits good agreement with AERONET AOD during daytime and nighttime, with a Pearson correlation coefficient (R) exceeding 0.785, and the fraction of meeting the expected error (EE) exceeding 0.705. The accuracy of daytime AOD is comparable to that of the MODIS AOD product. Furthermore, MERRA-2 AE and FMF have a higher accuracy than MODIS products, with an R > 0.840 and an RMSE of 0.313 for AE and 0.150 for FMF. And it effectively captures the diurnal variation of aerosol properties, with an R of 0.911, 0.392, and 0.72 for AOD, AE, and FMF at different times of day compared to AERONET. Additionally, MERRA-2's ability to characterize the spatial patterns of daytime and nighttime is comparable to those of satellite products. Overall, this study provides the usage references for MERRA-2 aerosol product, highlighting its high accuracy and ability to capture diurnal variation and spatial patterns.
... Compared with a clear-sky atmosphere, cloud cover can absorb and reflect a large amount of incident shortwave radiation, which has a cooling effect on the subsurface. Aerosols can absorb and scatter solar radiation, which can block incident solar radiation, especially by reducing the passage of ultraviolet rays, weakening the solar radiation reaching the ground [16]. 2 of 25 The diurnal cycle in R s due to the Earth's rotation can cause diurnal changes in the surface and atmospheric state in all regions except the polar regions (where solar variability is more seasonal) through a variety of physical processes [17]. Ye et al. [18] noted that the diurnal temperature range (DTR) decreased rapidly in China from the 1960s to the 1980s when it became significantly dimmer, while in the early 1990s, the decline in DTR stopped during the period when R s changed from dimming to brightening, which was confirmed by Du et al. [19]. ...
Surface incident solar radiation (Rs) plays an important role in climate change on Earth. Recently, the use of satellite-retrieved datasets to obtain global-scale Rs with high spatial and temporal resolutions has become an indispensable tool for research in related fields. Many studies were carried out for Rs evaluation based on the monthly satellite retrievals; however, few evaluations have been performed on their diurnal variation in Rs. This study used independently widely distributed ground-based data from the Baseline Surface Radiation Network (BSRN) to evaluate hourly Rs from the Clouds and the Earth’s Radiant Energy System Synoptic (CERES) SYN1deg–1Hour product through a detrended standardization process. Furthermore, we explored the influence of cloud cover and aerosols on the diurnal variation in Rs. We found that CERES-retrieved Rs performs better at midday than at 7:00–9:00 and 15:00–17:00. For spatial distribution, CERES-retrieved Rs performs better over the continent than over the island/coast and polar regions. The Bias, MAB and RMSE in CERES-retrieved Rs under clear-sky conditions are rather small, although the correlation coefficients are slightly lower than those under overcast-sky conditions from 9:00 to 15:00. In addition, the range in Rs bias caused by cloud cover is 1.97–5.38%, which is significantly larger than 0.31–2.52% by AOD.
... The MERRA-2 reanalysis dataset has been widely evaluated and validated in previous studies around the world (Fei and Wang, 2019;Hua et al., 2019). Particularly, Wang et al. (2020) validated MERRA-2 albedo dataset with sun photometers over eastern China and found that the accuracy of the MERRA-2 albedo is acceptable in eastern China. For SOM, the accuracy of MERRA-2 (unbiased RMSE of 0.053 m 3 m −3 ) is higher than that of ERA-Interim/Land and MERRA (Reichle et al., 2017). ...
The heatwave frequency and intensity have significantly changed as the climate warms and human activities increase, which poses a potential risk to human society. However, the impact factors that determine the change of heatwave events remain unclear. Here, we estimated the heatwave events based on data from 2474 in-suit gauges during 1960–2018 at daily scale in China. Besides, we explored possible drivers and their contributions to the change of heatwave based on correlation analysis, multiple linear regression (MLR), and random forest (RF) in different subregions of China. The results show that the temporal changes of all heatwave metrics exhibit significant differences between the period 1960–1984 and the period 1985–2019. Spatially, the heatwave frequency and duration significant increase in the southern China (S), eastern arid region (EA), northeastern China (NE), Qinghai-Tibet region (QT) and western arid and semi-arid region (WAS). The occurrence of the first heatwave event in a year tends to be earlier in S, NE, EA, WAS, and QT than before. Based on the regression modelling and RF, human activities play an important role in heatwave intensity in all subregions of China. For heatwave frequency, urbanization generate a dominant influence in NE, EA, and QT, with relative contributions (RC) ranging from 32.8 % to 38.9 %. Long-term climate change exerts the dominant influence in C, N, and S. Moreover, the first day of the yearly heatwave event (HWT) in NE is significantly influenced by climate change, with RC of 33.9 % for temperature variation (TEM). Our findings could provide critical information for understanding the causes of heatwave across different regions of China in the context of rapid urbanization and climate change.
... Aerosols are defined as tiny liquid and solid particles suspended in the air. They affect the atmospheric radiation budget directly by scattering and absorbing solar radiation and indirectly by changing cloud properties (Alizadeh-Choobari and Gharaylou, 2017; Levy et al., 2013a;Ramanathan et al., 2001;Shu et al., 2022;Wang et al., 2020). Until now, aerosols are still one of the largest sources of uncertainty in climate research (IPCC, 2018). ...
Aerosol optical depth (AOD) products provided by satellite sensors are widely used in climate modeling and climate change research. However, inconsistencies between products can cause large biases. It is necessary to integrate multiple satellite aerosol products to produce a consistent and high-quality aerosol record that satisfies the requirements of climate research users. To effectively combine the advantages of different datasets, their performance under different conditions needs to be compared during overlapping periods using uniform methods and criteria. Based on Aerosol Robotic Network (AERONET) measurements from 2019 to 2021, this study is the first to systematically compare the accuracy of 16 publicly released products from multiple satellite sensors in China under various scenarios using the same criteria to support the construction of a harmonized and high-quality dataset. Compared with AERONET AOD, the average retrieval percentage of 16 products satisfying the Global Climate Observing System (GCOS) accuracy requirement is 26.51%, with MISR and VIIRS Deep Blue (DB) products exceeding 40%, while MODIS 3 km Dark Target (DT), VIIRS DT, VIIRS Enterprise Processing System (EPS), and Sentinel-3 products are below 20%. By quantifying the accuracy of the products under different surface conditions, aerosol loadings, and particle size types, the accuracy ranking matrix of 16 products under different scenarios is established to provide a priori knowledge for the construction of a merged dataset. Finally, AOD products from October 2020 are merged based on the accuracy ranking matrix. The merged results show that, compared to the commonly used MODIS DT product, the percentage of retrievals satisfying GCOS requirement is improved by 22.55%, the correlation coefficient and mean absolute error are also improved, and the national average AOD coverage increases from 22.18% to 47.73%. These results are expected to provide guidance for the construction of high-quality datasets and the application of satellite aerosol products in climate research.
... Their errors can cause uncertainties in the calculation of ADREs. Aerosols mainly absorb and scatter shortwave solar radiation with a wavelength ranging from 0.25 to 4 μm (Wang et al. 2020;Guleria and Chandra Kuniyal 2013;Verma et al. 2017). Therefore, this study focuses on shortwave ADREs and assesses its uncertainty. ...
... This suggests that more absorbing aerosols were more effective than scattering aerosols in reducing downward solar radiation from the Earth's surface. The contribution of the ASY to ADRE was less important than that of the SSA (Wang et al. 2020). When holding other parameters constant, a 5% decrease in the ASY caused the ADRE to increase by 14% at the TOA (−2.69 Wm −2 ) and 8% at the surface (−5.15 Wm −2 ). ...
The total and individual aerosol direct radiative effects (ADREs) were estimated for clear-sky conditions using Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) observations and radiative transfer model. In this study, a parametric sensitivity analysis was performed for the Santa Barbara DISORT Atmospheric Radiative Transfer model using a global sensitivity analysis method. Uncertainties in the ADREs due to aerosol optical properties and surface albedo errors were evaluated. The single-scattering albedo and asymmetry factor for marine, dust, pollution, and smoke aerosols required for the model calculations were obtained from the classified AErosol RObotic NETwork observations. The estimated average global ADREs and errors at the top-of-atmosphere (TOA) and the surface were −2.36 ± 0.54 and −4.78 ± 2.2 Wm⁻², respectively. In regions with higher dust, pollution, and smoke aerosol loading, the ADREs exhibited significant seasonal variability. In the Sahara and Arabian deserts, during the June-July-August season with higher dust aerosol loading, the seasonal average ADREs in the region were −3.23 and −21.37 Wm⁻² at the TOA and surface, respectively. In the Indian region, during the March–April–May season with higher pollution aerosol loading, the ADREs were −10.33 and −28.04 Wm⁻² at the TOA and surface, respectively. In Southern Africa, the smoke aerosol with a single-scattering albedo of 0.87 caused negative radiative effects at the TOA, and during the September-October-November season with higher smoke aerosol loading, the seasonal average ADREs were −2.34 and −6.36 Wm⁻² at the TOA and surface, respectively.
... In the most recent period between 2015 and 2020, AERONET, MODIS, MISR and MERRA-2 DARF show steady growth trends of 3.7, 2.4, 1.6 and 1.4 W/m 2 /decade, respectively. The decreasing trends that are mostly due to the air quality initiatives implemented since 2014, agree with those of previous studies (Wang et al., 2020;Zhang et al., 2017), Fig. 7 further illustrates the interannual changes in DARFE, AOD and SSA to better understand the differences in DARF trends given by the four datasets. Both DARFE and SSA from the four datasets show relatively consistent trends, whereas AOD has the most obvious variations, and its trend is close to the results of the study by Che et al. (2015). ...
Direct Aerosol Radiative Forcing (DARF) characterizes aerosol influences on the radiative energy budget due to scattering and absorption of solar radiation, while clear uncertainties remain in both global and regional DARF estimations due to differences on aerosol properties and time periods considered. Through a multi-source strategy, this study systematically investigates the DARFs over Beijing, China, between 2001 and 2020. Ground-based observations from AERONET are used as “references”, and two satellite-based datasets (MODIS and MISR), atmospheric reanalysis (MERRA-2) and numerical modelling (WRF-CMAQ) are considered. We unify the numerical simulations for DARF to ensure an fair intercomparison among difference datasets. Fortunately, the aerosol amount at the AERONET locations in Beijing can well represent those over the entire city regon, and the average DARF at the top of the atmosphere (TOA) in the past twenty years is found to be ~ −36 W/m² in Beijing. The relative differences in DARFs among different sources range between approximately −40% and 10%, and those in DARF efficiencies (DARFEs) are in a similar range (besides AERONET and MISR). The correlation coefficients on DARF between the AERONET and MERRA-2 results are found to be approxiamtely ~0.75, and both MODIS and MISR result in correlation coefficients with AERONET over 0.80. However, the agreement at the MISR TOA DARF is caused by smaller AOD and larger DARFE. The DARF uncertainties based on AERONET, MODIS and MISR range from approximately 10% to over 20%. For the numerical simulations, the WRF-CMAQ results agree reasonably with the observation-based results, while their DARF magnitudes are merely about one-third of those from observation-based results. Clear differences among DARFs given by datasets of different kinds indicate that the uncertainties on aerosol direct forcings cannot be neglected, and that more efforts are still needed to unify and to improve our understanding on it.
... the types of particles analyzed here. Comparisons of ARE with other aerosol types are not straightforward because of the dependences with AOD, aerosol single scattering albedo and asymmetry parameter and solar zenith angle, although the reported cooling effects agree with other studies (e.g., Di Biagio et al., 2009;Huang et al., 2009;Bhawar et al., 2016;Mallet et al., 2016;Wang et al., 2020) Figure 18 also shows a wavelength dependence in HRs below the PBL with positive values above 2 × 10 −4 K d −1 for 355 and 532 nm, with HRs very close to zero at 1064 nm. For the aerosol-free region above the PBL, the computed HRs are basically zero for all wavelengths. ...
This work focuses on the characterization of vertically resolved aerosol
hygroscopicity properties and their direct radiative effects through a
unique combination of ground-based and airborne remote sensing measurements
during the Column and Vertically
Resolved Observations Relevant to Air Quality (DISCOVER-AQ) 2011 field campaign in the Baltimore–Washington DC metropolitan area. To that end, we combined aerosol measurements
from a multiwavelength Raman lidar located at NASA Goddard Space Flight
Center and the airborne NASA Langley High Spectral Resolution Lidar-1 (HSRL-1) lidar system. In situ
measurements aboard the P-3B airplane and ground-based Aerosol Robotic Network – Distributed Regional Aerosol Gridded
Observational Network (AERONET-DRAGON)
served to validate and complement quantifications of aerosol hygroscopicity
from lidar measurements and also to extend the study both temporally and
spatially. The focus here is on 22 and 29 July 2011,
which were very humid days and characterized by a stable atmosphere and
increasing relative humidity with height in the planetary boundary layer
(PBL). Combined lidar and radiosonde (temperature and water vapor mixing
ratio) measurements allowed the retrieval of the Hänel hygroscopic
growth factor which agreed with that obtained from airborne in situ
measurements and also explained the significant increase of extinction and
backscattering with height. Airborne measurements also confirmed aerosol
hygroscopicity throughout the entire day in the PBL and identified sulfates
and water-soluble organic carbon as the main species of aerosol particles.
The combined Raman and HSRL-1 measurements permitted the inversion for
aerosol microphysical properties revealing an increase of particle radius
with altitude consistent with hygroscopic growth. Aerosol hygroscopicity
pattern served as a possible explanation of aerosol optical depth increases
during the day, particularly for fine-mode particles. Lidar measurements
were used as input to the libRadtran radiative transfer code to obtain
vertically resolved aerosol radiative effects and heating rates under dry
and humid conditions, and the results reveal that aerosol hygroscopicity is
responsible for larger cooling effects in the shortwave range (7–10 W m−2
depending on aerosol load) near the ground, while heating rates
produced a warming of 0.12 K d−1 near the top of PBL where aerosol
hygroscopic growth was highest.
... Various satellite missions played a vital role in improving our knowledge on the Earth's energy balance. Down-and up-welling solar radiation at the top of the atmosphere (TOA) is measured directly by satellite sensors, while surface solar radiation fluxes are estimated indirectly, involving the synergistic use of radiative transfer models with satellite-and ground-based measurements of various physical parameters [13][14][15][16][17][18][19]. ...
... By comparing SSR simulations with and without this correction with ground-based observations we found that the correction reduces the bias by 3-4%. The radiative transfer system is capable of producing gridded solar radiation fields at the top of the atmosphere, within the atmosphere and at the surface similarly to other global and regional systems [15,17,19,21]. Following the study of Benas et al. [86], here we show a demonstration for SSR for the period 2005-2019 for 16 selected stations around Greece, located in the heart of the climatically sensitive region of the Eastern Mediterranean. ...
In this work, the effect that two basic air quality indexes, aerosols and tropospheric NO2, exert on surface solar radiation (SSR) is studied, along with the effect of liquid and ice clouds over 16 locations in Greece, in the heart of the Eastern Mediterranean. State-of-the-art satellite-based observations and climatological data for the 15-year period 2005–2019, and a radiative transfer system based on a modified version of the Santa Barbara DISORT Atmospheric Radiative Transfer (SBDART) model are used. Our SSR simulations are in good agreement with ground observations and two satellite products. It is shown that liquid clouds dominate, with an annual radiative effect (RE) of −36 W/m2, with ice clouds (−19 W/m2) and aerosols (−13 W/m2) following. The radiative effect of tropospheric NO2 is smaller by two orders of magnitude (−0.074 W/m2). Under clear skies, REaer is about 3–4 times larger than for liquid and ice cloud-covered skies, while RENO2 doubles. The radiative effect of all the parameters exhibits a distinct seasonal cycle. An increase in SSR is observed for the period 2005–2019 (positive trends ranging from 0.01 to 0.52 W/m2/year), which is mostly related to a decrease in the aerosol optical depth and the liquid cloud fraction.
... urban heat island effect in some major metropolitan areas (Zhong et al., 2017) and historical 'solar dimming' in some US regions (Liepert, 2002), Europe (Cherian et al., 2014), and China (Y. Wang et al., 2020). Aerosol radiative forcing has also been proposed as an explanation of the "warming hole" in the central and south central United States and the resulting US east-west differential of heat extremes (Gillett, 2014;Leibensperger et al., 2012;Yu et al., 2014). ...
Improved characterization of the spatiotemporal extent, intensity, and causes of extreme aerosol optical depth events is critical to quantifying their regional climate forcing and the link to near‐surface air quality. An analysis of regional‐scale extreme aerosol events over the eastern United States is undertaken using output from the Modern‐Era Retrospective analysis for Research and Applications, version 2 (MERRA‐2) reanalysis and observations from the MODerate resolution Imaging Spectroradiometers (MODIS). Six extreme aerosol optical depth (AOD) events during 2003–2007, dominated by anthropogenic emissions and characterized by a regional scale extent, are identified and simulated using the Weather Research and Forecasting model coupled with Chemistry (WRF‐Chem) applied at 12 km resolution. Statistical analyses show output from WRF‐Chem during these events is generally negatively biased in terms of the mean AOD and PM2.5, but WRF‐Chem exhibits skill in capturing the peak AOD. WRF‐Chem also exhibits fidelity in reproducing the spatiotemporal characteristics of the extreme AOD events in intensity, location of centroid, propagation, duration, and their spatial extension. Considerable event‐to‐event variability in model skill in simulating spatial patterns of extreme events is observed, with the highest spatial correlation with MERRA‐2 AOD noted for events centered in the Midwest. Mean fractional bias in modeled peak AOD is minimized for the most intense events and for events centered over the southeastern USA. WRF‐Chem output is also negatively biased in downwelling shortwave radiation at the ground and specific humidity consistent with a positive bias in simulated precipitation relative to MERRA‐2.
