Increase In Aerosol Optical Depth Research Articles

The impact of different aerosol properties and types on direct aerosol radiative forcing and efficiency using AERONET version 3

In this study, the results from a classification method are used to determine how aerosol type influence the radiative balance of the Earth's climate. Quality-assured data from the AErosol RObotic NETwork (AERONET) Level 2.0 (L2) Version 3 (V3) inversion product are used during the 2008–2017 period. The study includes the Arabian Peninsula (AP), Atlantic (AT), Middle East North Africa (MENA), South Europe (SE) and Central and East Europe (CEE). The impacts of Solar Zenith Angle (SZA), Surface Albedo (SA), Aerosol Optical Depth (AOD) and Single Scattering Albedo (SSA) on Direct Aerosol Radiative Forcing (DARF) and Efficiency (DARFeff) at the bottom and top of atmosphere (BOA, TOA) are investigated. Fine slightly absorbing particles show the highest positive gradient of DARFeffBOA with SA and the highest negative gradient of DARFefTOA with SZA. The mixed absorbing particles provide the highest alteration for DARF at the BOA with the increase of AOD. The analysis of aerosols absorptivity is performed by dividing SSA into six-subgroups. Coarse absorbing particles provide the highest (in magnitude) DARFeff values at the TOA under absorbing aerosol conditions (SSA < 0.89), whereas similar behavior is revealed by the fine absorbing particles for DARFeff values at the BOA. Furthermore, we analyze the long-term averages of RF metrics for all aerosol types among the regions of our study. At the TOA, fine non-absorbing particles show the highest absolute values for DARFeff (from −75 W m−2 to −79 W m−2) and DARF (from −38 W m−2 to −48 W m−2). At the BOA, coarse and mixed absorbing clusters indicate the highest absolute values for DARF (from −66 W m−2 to −79 W m−2) and DARFeff (from −135 W m−2 to −149 W m−2), respectively. The presented results could be used for the validation and improvement of the performance of remote sensing algorithms and models that assess the aerosol effect in radiative balance.

Spatio-temporal distribution of INSAT-3D AOD derived particulate matter concentration over India

Ground observations over 60–80 sites in India during 2014–18 reveal that Particulate Matter (PM) concentration exceeded National Ambient Air Quality Standard (NAAQS) by 1.5–2.5 times during Pre-Monsoon (PrM), Post-Monsoon (PoM) and Winter (Win) seasons only. Geographically Weighted Regression technique was employed to estimate PM2.5 and PM10 incorporating Aerosol Optical Depth (AOD) measured from geostationary orbit by Indian National Satellite (INSAT-3D) and ERA-INTERIM derived meteorological parameters. INSAT-3DAOD was well correlated with ground measured AOD (R2 > 0.75). Estimated PM found higher during PrM (PM2.5: 103.16 ± 31.39 μg m−3, PM10: 150.07 ± 43.13 μg m−3) than PoM (PM2.5: 58.72 ± 22.9 μg m−3, PM10: 127.17 ± 48.95 μg m−3) and Win (PM2.5: 71.02 ± 20.25 μg m−3, PM10: 96.86 ± 27.63 μg m−3). PM pollution was severe in West India (PM2.5: 87.44 ± 30.07 μg m−3, PM10: 148.13 ± 42.8 μg m−3), 1.2–1.5 times higher than least polluted North-East India. Spatial variability of PM distinctly discern the major prone areas that experience episodic events like dust (PM10 > 150 μg m−3) and biomass burning (PM2.5 >100 μg m−3). Overall country registered increase in AOD, PM10, PM2.5 by 52.34%, 36.23%, 36.58% respectively. Estimation accuracy produced by the model was satisfactory (R2 > 0.6; NMSE <0.25; −0.01 < FB < 0.09). The human footprint perceived by the PM2.5/PM10 ratio signifies that 60.95% PM10 is attributed to PM2.5 across the country and it was highest during Win (73.45%). The changes in spatial distribution of PM highlight that Indo-Gangetic Plain and coastal area in Southern India had undergone major industrialization, urban expansions which resulted in increase of PM2.5 by 50–125 μg m−3 during all seasons.

Spatiotemporal changes of surface solar radiation: Implication for air pollution and rice yield in East China

The changes of surface solar radiation (SSR) have significant implication for air pollution and rice yield. In this study, gridded SSR data, derived from multi-platform datasets and radiation model, were used to analyze its spatiotemporal changes over East China during 2000–2016. The results show SSR experiences dimming during 2000–2005, then turns into brightening till 2016. Both aerosol optical depth (AOD) and single scattering albedo (SSA) contribute to SSR trend. AOD dominates the spatiotemporal changes of SSR in East China, and this impact is higher in the North than the South. SSA has little impact on SSR with low AOD, but its contribution to SSR becomes important as AOD increases. Moreover, gridded planet boundary layer (PBL) was simulated by the Weather Research and Forecasting Model (WRF) and SSR-PBL relationship was also explored. Long-term evidence indicates PBL has a regulatory effect on SSR in the air pollution. Additionally, aerosol-induced radiation reduction can influence rice yield in East China, and it can result in about mean 6.74% reduction in rice yield over East China. Province-level changes of aerosol-induced reduction in rice production were also evaluated and it suggests the impact of aerosols on rice production is non-negligible, especially in Jiangsu and Anhui Province. Our study underscores the importance of aerosol pollution on surface radiation and the mitigation of aerosols is beneficial for crop production under climate change.

PM2.5 Concentration Influencing Factors in China Based on the Random Forest Model

In this paper, aerosol optical depth (AOD), elevation (DEM), annual precipitation (PRE), annual average temperature (TEM), annual average wind speed (WS), population density (POP), gross domestic product density (GDP), and normalized difference vegetation index (NDVI) were selected as factors influencing PM2.5 concentration. The random forest model, order of feature importance, and partial dependency plots were applied to investigate these factors and their regional differences in PM2.5 spatial pattern. The results showed that:① The random forest model was more accurate than multiple regression, generalized additive, and back propagation neural network models in estimating PM2.5 concentration, which can be applied to quantifying PM2.5 influencing factors. ② PM2.5 concentration initially increased and then remained stable with increases in AOD, POP, and GDP, and initially decreased and then stabilized with increases in PRE, WS, and NDVI. The responses of DEM and TEM to PM2.5 concentration changed from decline to ascend and then changed to decline again. ③ AOD had the largest influence on PM2.5 annual concentrations with a spatial influencing magnitude of 37.96%, whereas PRE had the least influence with a merely individual spatial influencing magnitude of 5.75%. ④ The relationships between PM2.5 pollution and influencing variables vary with geography and thus exhibit significant spatial heterogeneity. The same factor had different spatial influencing magnitudes on PM2.5 annual concentrations in seven geographical subareas. AOD had the greatest influence on PM2.5 concentration in the south of China, with the least influence in the northeast.

Regional trends of lightning activity in the tropics and subtropics

Based on 18 years of lightning data from 1996 to 2013 detected by optical transient detector (OTD) and lightning imaging sensor (LIS), the variation trend of lightning flash density (LFD) in the tropics and subtropics are investigated. Meteorological parameters from observational and reanalysis datasets are analyzed to understand the causes of LFD trends. The averaged LFD shows no significant trend during the period of analysis in the tropics and subtropics, while the regional LFD trends are significant. LFDs show significant negative linear trends in southeast North America (SENA), central South America (CSA) and eastern Australia (EA), with trend values of −0.26 fl km−2 year−1, −0.17 fl km−2 year−1, and − 0.14 fl km−2 year−1, respectively. At the same time, LFDs increased significantly in northwest South Asia (NWSA), with a trend of 0.24 fl km−2 year−1. Using a multiple linear regression method, the possible causes of LFD trends over these regions are investigated. The negative linear trends in SENA, CSA and EA are more likely due to the decreases of the convective available potential energy (CAPE), which may contribute −0.13 fl km−2 year−1, −0.14 fl km−2 year−1, and − 0.11 fl km−2 year−1 to the LFD trends in these regions, respectively. Increase of aerosol optical depth (AOD) exerts more influence on the increasing of LFD in NWSA, and could explain 0.08 fl km−2 year−1 of the LFD trends.

Trends of Climate Variables and Aerosol optical Depth in Thailand

This study analysed climate variables data in four stations over Thailand. Aerosol optical depth (AOD) obtained from Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) were also used to determine climatic trends in the areas under focus. The linear regression, Mann-Kendall trend, and Sen’s slope tests were applied. Rain (R) gave higher values in July to October for most regions except in the Songkhla. Amount of R increased in all regions. Rainy season is caused by the Southwest monsoon, which is a normal occurrence in Thailand from June to September. However, this monsoon tended to begin earlier and last longer (May to October) than expected. Mean temperature (Tmean) values were found to be significantly higher from March to May and increased in all stations. The highest significant increases of annual Tmean were found in the North. There was no significant trend in annual R (Rainfall) at the 1% and 5% significance level in all stations. The AOD values were likely to increase in almost all stations. The highest significant increase of annual AOD was observed in Ubon Ratchathani.

Effect of aerosols on the macro- and micro-physical properties of warm clouds in the Beijing-Tianjin-Hebei region

The interaction between aerosols and clouds plays an important role in the climate system. There is still uncertainty about the influences of aerosols on the macro- and micro-physical properties of clouds in the Beijing-Tianjin-Hebei region. The relationships between aerosol optical depth (AOD) and the macro- and micro-physical properties of warm clouds in the Beijing-Tianjin-Hebei region were analyzed based on MODIS/Aqua data from 2007 to 2016. In addition, the ERA-Interim meteorological data was employed to investigate the relationship of AOD and cloud parameters under different meteorological conditions. The results showed that the variation of cloud droplet effective radius (CER) with AOD was in agreement with the Anti-Twomey effect, the main reason was that the increasing aerosol causes the water vapor competition effect among the cloud droplets, which makes the smaller cloud droplets evaporate. The multi-year average AOD was positively correlated with liquid water path (LWP). The relationship between AOD and cloud optical depth (COD) was quite different. When AOD was <0.4 or >0.8, COD increased with the increase of AOD, and when AOD was between 0.4 and 0.8, AOD and COD showed negative correlation. With the increment of AOD, cloud top pressure (CTP) also increased, which indicated that cloud top height decreased. When AOD was <0.3, cloud fraction (CF) was negatively correlated with AOD and conversely, positively correlated when AOD was >0.3. Furthermore, under most meteorological conditions, AOD was positively correlated with cloud macro- and micro-physical properties. Under the conditions of relative humidity ranged from 40% to 80%, there was a negative correlation between AOD and COD.

Retrieval of Fine-Resolution Aerosol Optical Depth (AOD) in Semiarid Urban Areas Using Landsat Data: A Case Study in Urumqi, NW China

The aerosol optical depth (AOD) represents the light attenuation by aerosols and is an important threat to urban air quality, production activities, human health, and sustainable urban development in arid and semiarid regions. To some extent, the AOD reflects the extent of regional air pollution and is often characterized by significant spatiotemporal dynamics. However, detailed local AOD information is ambiguous at best due to limited monitoring techniques. Currently, the availability of abundant satellite data and constantly updated AOD extraction algorithms offer unprecedented perspectives for high-resolution AOD extraction and long-time series analysis. This study, based on the long-term sequence MOD09A1 data from 2010 to 2018 and lookup table generation, uses the improved deep blue algorithm (DB) to conduct fine-resolution (500 m) AOD (at 550 nm wavelength) remote sensing (RS) estimation on Landsat TM/OLI data from the Urumqi region, analyzes the spatiotemporal AOD variation characteristics in Urumqi and combines gray relational analysis (GRA) and the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model to analyze AOD influence factors and simulate pollutant propagation trajectories in representative periods. The results demonstrate that the improved DB algorithm has a high inversion accuracy for continuous AOD inversion at a high spatial resolution in urban areas. The spatial AOD distribution in Urumqi declines from urban to suburban areas, and higher AODs are concentrated in cities and along roads. Among these areas, Xinshi District has the highest AOD, and Urumqi County has the lowest AOD. The seasonal AOD variation characteristics are distinct, and the AOD order is spring (0.411) &gt; summer (0.285) &gt; autumn (0.203), with the largest variation in spring. The average AOD in Urumqi is 0.187, and the interannual variation generally shows an upward trend. However, from 2010 to 2018, AOD first declined gradually and then declined significantly. Thereafter, AOD reached its lowest value in 2015 (0.076), followed by a significant AOD increase, reaching a peak in 2016 (0.354). This shows that coal to natural gas (NG) project implementation in Urumqi promoted the improvement of Urumqi’s atmospheric environment. According to GRA, the temperature has the largest impact on the AOD in Urumqi (0.699). Combined with the HYSPLIT model, it was found that the aerosols observed over Urumqi were associated with long-range transport from Central Asia, and these aerosols can affect the entire northern part of China through long-distance transport.

Pollution Trends in China from 2000 to 2017: A Multi-Sensor View from Space

Satellite sensors can provide unique views of global pollution information from space. In particular, a series of aerosol and trace gas monitoring instruments have been operating for more than a decade, providing the opportunity to analyze temporal trends of major pollutants on a large scale. In this study, we integrate aerosol products from MODIS (MODIS Resolution Imaging Spectroradiometer, all abbreviations and their definitions are listed alphabetically in Abbreviations) and MISR (Multi-angle Imaging Spectroradiometer), the AAI (Absorbing Aerosol Index) product from OMI (Ozone Monitoring Instrument), column SO2 and NO2 concentrations from OMI, and tropospheric column ozone concentration from OMI/MLS (Microwave Limb Sounder) to study temporal changes in major pollutants over China. MODIS and MISR consistently revealed that column AOD (Aerosol Optical Depth) increased from 2000, peaked around 2007, and started to decline afterward, except for northwest and northeast China, where a continuous upward trend was found. Extensive negative trends in both SO2 and NO2 have also been found over major pollution source regions since ~2005. On the other hand, the OMI AAI exhibited significant increases over north China, especially the northeast and northwest regions. These places also have a decreased Angstrom exponent as revealed by MISR, indicating an increased fraction of large particles. In general, summer had the largest AOD, SO2, and NO2 trends, whereas AAI trends were strongest for autumn and winter. A multi-regression analysis showed that much of the AOD variance over major pollution source regions could be explained by SO2, NO2, and AAI combined, and that the SO2 and NO2 reduction was likely to be responsible for the negative AOD trends, while the AOD increase over NE and NW China may be associated with an increase of coarse particles revealed by increased AAI and decreased AE. In contrast to aerosols, tropospheric ozone exhibited a steady increase from 2005 throughout China. This indicates that although the recent emission control effectively reduced aerosol pollutants, ozone remains a challenging issue and may dominate future air pollution.

Exploring the Twilight Zone: A Multi-Sensor Approach

This study shows a set of analysis of measurements from ground-based and satellite instruments to characterize the twilight zone (TLZ) between clouds and aerosols in São Paulo, Brazil. In the vicinity of clouds turbulence measurements showed an intense upward movement of aerosol layers, while sunphotometer results showed an increase in aerosol optical depth, and lidar measurements showed an increase in the backscatter vertical profile signal.

Influence of Regional Transport Mechanisms on the Fingerprint of Biomass-Burning Aerosols in Buenos Aires

The study focuses on the transport of aerosol particles resulting from biomass burning in central South America towards the megacity of Buenos Aires by the South American Low-Level Jet. In particular, the cases are studied in which the exit area of the Jet reaches the La Plata Basin with no precipitation associated, herein called Chaco Jet 1 (CJ1), which could remove aerosols from the atmosphere on their way towards the city. CJ1 events registered within the five-year period of 2001–2005 are examined along with changes in the optical properties of aerosols over the city from measurements from the Aerosol Robotic Network (AERONET) site. Three-dimensional backward trajectories of CJ1 were obtained to verify the connection between the receptor site and the biomass-burning source region. A cluster analysis of the trajectories allows further characterizing the features and impacts of regionally transported aerosols. A subsample of days on which impacts of the contribution of biomass burning could have occurred, showed a statistically significant increase in aerosol optical depth and Ångström exponent, reflected by an increase in the peak of the derived volume size distribution in the fine fraction size range, which also shifts slightly towards bigger radii. The days with AOD greater than 0.15 show overall behaviour like other urban sites with pollution of different origins. The evaluation of the selected data reveals that higher values of AOD and changes in the Ångström exponent are linked to the dispersion of biomass-burning aerosols. Air mass trajectories coinciding with the CJ1 core present the strongest impact on aerosol characteristics, which can be seen in spectral measurements.

Atmospheric Correction of Satellite Ocean Color Remote Sensing in the Presence of High Aerosol Loads

The coverage of valid pixels of remote-sensing reflectance (Rrs) from ocean color imagery is relatively low due to the presence of clouds. In fact, it is also related to the presence of high aerosol optical depth (AOD) and other factors. In order to increase the valid coverage of satellite-retrieved products, a layer removal scheme for atmospheric correction (LRSAC) has been developed to process the ocean color data. The LRSAC used a five-layer structure including atmospheric absorption layer, Rayleigh scattering layer, aerosol scattering layer, sea surface reflection layer, and water-leaving reflectance layer to deal with the relationship of the components of the atmospheric correction. A nonlinear approach was used to solve the multiple reflections of the interface between two adjoining layers and a step-by-step procedure was used to remove effects of each layer. The LRSAC was used to process data from the sea-viewing wide field-of-view sensor (SeaWiFS) and the results were compared with standard products. The average of valid pixels of the global daily Rrs images of the standard products from 1997 to 2010 is only 11.5%, while it reaches up to 30.5% for the LRSAC. This indicates that the LRSAC recovers approximately 1.65 times of invalid pixels as compared with the standard products. Eight-day standard composite images exhibit many large areas with invalid values due to the presence of high AOD, whereas these areas are filled with valid pixels wusing the LRSAC. The ratio image of the mean valid pixel of the LRSAC to that of the standard products indicates that the number of valid pixels of the LRSAC increases with an increase of AOD. The LRSAC can increase the number of valid pixels by more than two times in about 33.8% of ocean areas with high AOD values. The accuracy of Rrs from the LRSAC was validated using the following two in situ datasets: the Marine Optical BuoY (MOBY) and the NASA bio-Optical Marine Algorithm Dataset (NOMAD). Most matchup pairs are distributed around the 1:1 line indicating that the systematic bias of the LRSAC is relatively small. The global mean relative error (MRE) of Rrs is 7.9% and the root mean square error (RMSE) is 0.00099 sr−1 for the MOBY matchups. Similarly, the MRE and RMSE are 2.1% and 0.0025 sr−1 for the NOMAD matchups, respectively. The accuracy of LRSAC was also evaluated by different groups of matchups according to the increase of AOD values, indicating that the errors of Rrs were little affected by the presence of high AOD values. Therefore, the LRSAC can significantly improve the coverage of valid pixels of Rrs with a similar accuracy in the presence of high AOD.

Long-Term Aerosol Trends and Variability over Central Saudi Arabia Using Optical Characteristics from Solar Village AERONET Measurements

Natural and anthropogenic aerosols over the Kingdom of Saudi Arabia (KSA) play a major role in affecting the regional radiation budget. The long-term variability of these aerosols’ physical and optical parameters, including aerosol optical depth (AOD) and Ångström exponent (α), were measured at a location near central KSA using the Solar Village (SV) AERONET (Aerosol Robotic Network) station during the period December 1999–January 2013. The AERONET measurements show an overall increase in AOD on an annual basis. This upward trend is mainly attributed to a prolonged increase in the monthly/seasonal mean AOD during March–June and during August–September. In contrast, lower AOD values were observed during November–December. This can be attributed to a low frequency of dust outbreaks and higher precipitation rates. An overall, weak declining trend in α was observed, except during the summer. The spring and summer seasons experienced a pronounced increase in the number of coarse particles (~2 µm) during April 2006–January 2013 as compared to December 1999–March 2006, suggesting an increase in natural aerosol loadings. Using the HYSPLIT model, it was found that the March 2009 dust storm contributed to the mixing of long-transported dust with anthropogenic local emissions near the SV. The results suggest that extensive industrial activity contributed to the increase of anthropogenic emissions over KSA during the period April 2006–January 2013.

Assessment of absorbing aerosols on austral spring snow albedo reduction by several basins in the Central Andes of Chile from daily satellite observations (2000–2016) and a case study with the WRF-Chem model

Changes in snow albedo (SA) on the Limari, Choapa, Aconcagua and Maipo basins of the Central Andes of Chile (CAC) are associated with the possible deposition of light-absorbing particles in the austral spring. We correlate SA with daily data of snow cover, aerosol optical depth (AOD) and land surface temperature (LST) available from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the NASA Terra satellite between 2000 and 2016, and other derived parameters such as days after albedo (DAS) and snow precipitation (SP). We used satellite pixels with 100% snow cover to obtain monthly average value of SA, LST, AOD, DAS and SP from September to November performing multiple regression analysis. We show that in Maipo, after considering LST, AOD represents an important role in changes induced to SA. The multiple regression model illustrates that AOD increases can reduce the SA during spring months by 13.59, 0.01, 0.77 and 3.8% in Limari, Choapa, Aconcagua and Maipo, respectively. In addition, we used a numerical prediction Weather Research and Forecasting model coupled with Chemistry (WRF-Chem), showing that the black carbon distribution and average daily AOD are associated with the SA decrease of 0.15 in the Maipo basin between September 29 and 30, 2016. The WRF-Chem output showed aerosols are transported mainly with dominating westerly winds to the Limari and Maipo basins. Our results further suggest that SA decrease due to AOD may be originated in the largest industrial and urban areas in Chile, producing a negative impact on the hydrological resource, generated in the CAC.

Effects of increasing aerosol optical depth on the gross primary productivity in China during 2000–2014

Abstract The aerosol optical depth (AOD) has been shown to influence the gross primary productivity (GPP) in terrestrial ecosystems by increasing the diffuse fraction, which could expend radiation scattering and improve the light-use efficiency of shade leaves. Previous studies have suggested that variations in aerosols are the main cause of changes in solar radiation over China. In this study, we analyzed the spatial and temporal trends of the AOD and GPP, which were extracted from Medium Resolution Imaging Spectrometer (MODIS) products and radiation (total solar radiation and diffuse radiation) and diffuse fraction data obtained from meteorological stations in China from 2000 to 2014. The correlations among these variables were investigated according to three vegetation types. The results showed that the AOD increased by approximately 11.4% between 2001 and 2014. The diffuse radiation and GPP increased by 6.7% and 8.9% in the same period, respectively. The spatial patterns of the AOD were found to be similar to that of the diffuse radiation over China. The results showed a significantly positive correlation between the AOD and GPP for forests (p

Validation and Accuracy Assessment of MODIS C6.1 Aerosol Products over the Heavy Aerosol Loading Area

The aim of this study is to evaluate the accuracy of MODerate resolution Imaging Spectroradiometer (MODIS) aerosol optical depth (AOD) products over heavy aerosol loading areas. For this analysis, the Terra-MODIS Collection 6.1 (C6.1) Dark Target (DT), Deep Blue (DB) and the combined DT/DB AOD products for the years 2000–2016 are used. These products are validated using AErosol RObotic NETwork (AERONET) data from twenty-three ground sites situated in high aerosol loading areas and with available measurements at least 500 days. The results show that the numbers of collections (N) of DB and DT/DB retrievals were much higher than that of DT, which was mainly caused by unavailable retrieval of DT in bright reflecting surface and heavy pollution conditions. The percentage falling within the expected error (PWE) of the DT retrievals (45.6%) is lower than that for the DB (53.4%) and DT/DB (53.1%) retrievals. The DB retrievals have 5.3% less average overestimation, and 25.7% higher match ratio than DT/DB retrievals. It is found that the current merged aerosol algorithm will miss some cases if it is determined only on the basis of normalized difference vegetation index. As the AOD increases, the value of PWE of the three products decreases significantly; the undervaluation is suppressed, and the overestimation is aggravated. The retrieval accuracy shows distinct seasonality: the PWE is largest in autumn or winter, and smallest in summer. The most severe overestimation and underestimation occurred in the summer. Moreover, the DT, DB and DT/DB products over different land cover types still exhibit obvious deviations. In urban areas, the PWE of DB product (52.6%) is higher than for the DT/DB (46.3%) and DT (25.2%) products. The DT retrievals perform poorly over the barren or sparsely vegetated area (N = 52). However, the performance of three products is similar over vegetated area. On the whole, the DB product performs better than the DT product over the heavy aerosol loading area.

Consistent signal of aerosol indirect and semi-direct effect on water clouds in the oceanic regions adjacent to the Indian subcontinent

Abstract Quantifying aerosol-cloud interaction is one of the most challenging tasks in climate science. Previous studies in the oceanic regions adjacent to the Indian subcontinent providing evidence of aerosol impacts on cloud properties were mostly confined in the winter season. Here we analyze 15 years (March 2000–February 2015) of MODIS aerosol and cloud products and 10 years (October 2004–February 2015) of OMI absorbing aerosol index (AI) over the Arabian Sea (AS), Bay of Bengal (BoB) and South Indian Ocean (SIO) to examine the sensitivity of marine water cloud characteristics to changing aerosol loading. Amidst a monotonous increase in Reff (cloud effective radius) with an increase in LWP (liquid water path) in clean and polluted conditions (an indicator of the meteorological influence), a smaller Reff at higher AOD (aerosol optical depth) bins demonstrates that aerosol signal is detectable and consistent in LWP range of 150–350 g m−2. Furthermore, a faster rate of Reff growth with increasing LWP in clean condition and the pattern of change in cloud fraction (fc) with an increase in AOD that cannot be explained by meteorology alone also provide evidence of the consistency of aerosol indirect effect. Evidence of aerosol semi-direct (decrease of LWP with an increase in AI) is also conspicuous in the AS and BoB. Our results suggest improved representations of aerosol and cloud processes in the models are required to reduce uncertainty in regional climate forcing.

Large contribution of meteorological factors to inter-decadal changes in regional aerosol optical depth

Abstract. Aerosol optical depth (AOD) has become a crucial metric for assessing global climate change. Although global and regional AOD trends have been studied extensively, it remains unclear what factors are driving the inter-decadal variations in regional AOD and how to quantify the relative contribution of each dominant factor. This study used a long-term (1980–2016) aerosol dataset from the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) reanalysis, along with two satellite-based AOD datasets (MODIS/Terra and MISR) from 2001 to 2016, to investigate the long-term trends in global and regional aerosol loading. Statistical models based on emission factors and meteorological parameters were developed to identify the main factors driving the inter-decadal changes of regional AOD and to quantify their contribution. Evaluation of the MERRA-2 AOD with the ground-based measurements of AERONET indicated significant spatial agreement on the global scale (r= 0.85, root-mean-square error = 0.12, mean fractional error = 38.7 %, fractional gross error = 9.86 % and index of agreement = 0.94). However, when AOD observations from the China Aerosol Remote Sensing Network (CARSNET) were employed for independent verification, the results showed that MERRA-2 AODs generally underestimated CARSNET AODs in China (relative mean bias = 0.72 and fractional gross error =-34.3 %). In general, MERRA-2 was able to quantitatively reproduce the annual and seasonal AOD trends on both regional and global scales, as observed by MODIS/Terra, although some differences were found when compared to MISR. Over the 37-year period in this study, significant decreasing trends were observed over Europe and the eastern United States. In contrast, eastern China and southern Asia showed AOD increases, but the increasing trend of the former reversed sharply in the most recent decade. The statistical analyses suggested that the meteorological parameters explained a larger proportion of the AOD variability (20.4 %–72.8 %) over almost all regions of interest (ROIs) during 1980–2014 when compared with emission factors (0 %–56 %). Further analysis also showed that SO2 was the dominant emission factor, explaining 12.7 %–32.6 % of the variation in AOD over anthropogenic-aerosol-dominant regions, while black carbon or organic carbon was the leading factor over the biomass-burning-dominant (BBD) regions, contributing 24.0 %–27.7 % of the variation. Additionally, wind speed was found to be the leading meteorological parameter, explaining 11.8 %–30.3 % of the variance over the mineral-dust-dominant regions, while ambient humidity (including soil moisture and relative humidity) was the top meteorological parameter over the BBD regions, accounting for 11.7 %–35.5 % of the variation. The results of this study indicate that the variation in meteorological parameters is a key factor in determining the inter-decadal change in regional AOD.

The impact of recent changes in Asian anthropogenic emissions of SO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt; on sulfate loading in the upper troposphere and lower stratosphere and the associated radiative changes

Abstract. Convective transport plays a key role in aerosol enhancement in the upper troposphere and lower stratosphere (UTLS) over the Asian monsoon region where low-level convective instability persists throughout the year. We use the state-of-the-art ECHAM6–HAMMOZ global chemistry–climate model to investigate the seasonal transport of anthropogenic Asian sulfate aerosols and their impact on the UTLS. Sensitivity simulations for SO2 emission perturbation over India (48 % increase) and China (70 % decrease) are performed based on the Ozone Monitoring Instrument (OMI) satellite-observed trend, rising over India by ∼4.8 % per year and decreasing over China by ∼7.0 % per year during 2006–2017. The enhanced Indian emissions result in an increase in aerosol optical depth (AOD) loading in the UTLS by 0.61 to 4.17 % over India. These aerosols are transported to the Arctic during all seasons by the lower branch of the Brewer–Dobson circulation enhancing AOD by 0.017 % to 4.8 %. Interestingly, a reduction in SO2 emission over China inhibits the transport of Indian sulfate aerosols to the Arctic in summer-monsoon and post-monsoon seasons due to subsidence over northern India. The region of sulfate aerosol enhancement shows significant warming in the UTLS over northern India, south China (0.2±0.15 to 0.8±0.72 K) and the Arctic (∼1±0.62 to 1.6±1.07 K). The estimated seasonal mean direct radiative forcing at the top of the atmosphere (TOA) induced by the increase in Indian SO2 emission is −0.2 to −1.5 W m−2 over northern India. The Chinese SO2 emission reduction leads to a positive radiative forcing of ∼0.6 to 6 W m−2 over China. The decrease in vertical velocity and the associated enhanced stability of the upper troposphere in response to increased Indian SO2 emissions will likely decrease rainfall over India.

Satellite-Derived Correlation of SO2, NO2, and Aerosol Optical Depth with Meteorological Conditions over East Asia from 2005 to 2015

Intense economic and industrial development in China has been accompanied by severe local air pollution, as well as in other downwind countries in East Asia. This study analyzes satellite observational data of sulfur dioxide (SO2), nitrogen dioxide (NO2), and aerosol optical depth (AOD) to explore the spatial distribution, long-term temporal variation, and correlation to meteorological conditions over this region over the period 2005–2015. SO2 and NO2 data are retrieved from the ozone monitoring instrument (OMI) onboard the National Aeronautics and Space Administration (NASA) Aura satellite, while AOD data are from the moderate-resolution imaging spectroradiometer (MODIS) onboard the NASA Aqua satellite. Spatial distributions of SO2, NO2, and AOD show the highest levels in the North China Plain (NCP), with hotspots also in Southeastern China (SC) and the Sichuan Basin (SB). Biomass burning also contributes to a high level of AOD in Southeast Asia in spring and in Equatorial Asia in fall. Considering the correlation of pollutant levels to meteorological conditions, monitoring data show that higher temperature and higher relative humidity (RH) favor the conversion of SO2 and NO2 to sulfate and nitrate aerosol, respectively. The impact of stronger lower tropospheric stability facilitates the accumulation of SO2 and NO2 in NCP and SC. Transport of SO2 and NO2 from intense source regions to relatively clean regions is highly influential over East Asia; such transport from the NCP leads to a considerable increase of pollutants in SC, SB, Taiwan Island (TW), and Taiwan Strait (TWS), particularly in winter. Aerosols generated by biomass burning in Southeast Asia and anthropogenic aerosol in SC are transported to TW and TWS and lead to the increase of AOD, with the highest levels of AOD in SC, TW, and TWS occurring in spring. Precipitation results in the removal of pollutants, especially in highly polluted regions, the effect of which is most significant in winter and spring.