Analysis of spatial pattern of aerosol optical depth and affecting factors using spatial autocorrelation and spatial autoregressive model

There are growing concerns on contribution of vegetation dynamics to atmospheric turbidity and quality of regional water towers. The study sought to determine the trends in the MODIS/TERRA-derived normalized difference vegetation index (NDVI) and aerosol optical depth (AOD) for Lesotho Highland over 2000-2020. The predictive relationship between the two variables was also examined using regression analysis. Irrespective of yearly AOD patterns, the AOD showed biphasic patterns peaking between mid-winter to early spring (July-October) (highest) and autumn (Feb-April) (next highest), and lowest in the summer (Nov-January). The monthly NDVI was largest in January-March (summer-early fall) with smaller values in winter and spring. This seasonality can be related to the peak of anthropogenic biomass combustion during the winter and strong winds during the spring and early summer. The AOD relationship with NDVI showed quadratic patterns peaking and plunging with changes in season. About 30-80% (R2 = 0.3-0.8%) changes in annual AOD from 2000 to 2020 were explainable by the dynamics of NDVI indicating that increased NDVI contributes to about a 50% decrease in AOD in the Lesotho Highlands. However, an outlier trend was observed in 2007 (R2 = 13%). Incidences of high AOD in months of high NDVI may be indicative of traveling aerosols, i.e., aerosols from non-local sources/activity. On the other hand, high AOD in months of low NDVI implicates local aerosol sources. Trend relationship studies on vegetation loss and AOD in mountain areas of other regions could improve knowledge of contaminant dynamics and risk implications for downstream populations.

Launched in December 1999, NASA’s Multi-angle Imaging SpectroRadiometer (MISR) has given researchers the ability to observe the Earth from nine different views for the last 22 years. Among the many advancements that have since resulted from the launch of MISR is progress in the retrieval of aerosols from passive space-based remote-sensing. The MISR operational standard aerosol retrieval algorithm (SA) has been refined several times over the last twenty years, resulting in significant improvements to spatial resolution (now 4.4 km) and aerosol particle properties. However, the MISR SA still suffers from large biases in retrieved aerosol optical depth (AOD) as aerosol loading increases. Here, we present a new MISR research aerosol retrieval algorithm (RA) that utilizes over-land surface reflectance data from the Multi-Angle Implementation of Atmospheric Correction (MAIAC) to address these biases. This new over-land/over-water algorithm produces a self-consistent aerosol/surface retrieval when aerosol loading is low (AOD < 1); this is combined with a prescribed surface algorithm using a bounded-variable least squares solver when aerosol loading is elevated (AOD > 2). The two algorithms (prescribed + retrieved surface) are then merged as part of our combined-surface retrieval algorithm. Results are compared with AErosol RObotic NETwork (AERONET) validation sun-photometer direct-sun + almucantar inversion retrievals. Over-land, with AERONET AOD (550 nm) direct-sun observations as the standard, the root-mean squared error (RMSE) of the MISR RA combined retrieval (n = 9680) is ~0.09, with a correlation coefficient (r) of ~0.93 and expected error of (0.225*[MISR AOD] + 0.025). For MISR RA-retrieved AOD > 0.5 (n = 565), we report Ångström exponent (ANG) RMSE of ~0.36, with a correlation coefficient of ~0.85. Retrievals of ANG and aerosol particle properties such as fine-mode fraction (FMF) and single-scattering albedo (SSA) improve as retrieved AOD increases. For AOD > 1.5 (n = 45), FMF RMSE is < 0.09 with correlation > 0.95, and SSA RMSE is < 0.02 with a correlation coefficient > 0.80. Over-water, comparing AERONET AOD to the MISR RA combined retrieval (n = 4590), MISR RA RMSE is ~0.06 and r is ~0.94, with an expected error of (0.20*[MISR AOD] + 0.01). ANG sensitivity is excellent when MISR RA reported AOD > 0.5 (n = 211), with a RMSE of 0.30 and r = 0.88. Due to a lack of coincidences with AOD > 1 (n = 20), our conclusions about MISR RA high-AOD particle property retrievals over water are less robust (FMF RMSE = 0.12 and r = 0.96, whereas SSA RMSE = 0.022 and r = 0.32). It is clear from the results presented that the new MISR RA has excellent sensitivity to aerosol particle properties (including FMF and SSA) when retrieved AOD exceeds 1–1.5, with qualitative sensitivity to aerosol type at lower AOD, while also eliminating the AOD bias found in the MISR SA at higher AODs. These results also demonstrate the advantage of using a prescribed surface when aerosol loading is elevated.

Spatial and temporal variation of aerosol optical depth (AOD) and optical depth of different aerosol types derived from the second Modern-Era Retrospective analysis for Research and Applications (MERRA-2) over the South China Sea (SCS) between 1980 and 2020 were studied. AOD distribution showed different characteristics throughout the entire SCS. Sulfate Aerosol Optical Depth (SO4AOD) and Sea Salt Aerosol Optical Depth (SSAOD) mainly contributed to the spatial and temporal variation of AOD over the SCS. A significant increasing trend followed by a decreasing trend of AOD could be observed in the north of the SCS from 1980 to 2020. Mean MERRA-2 AOD between 1980 and 2020 showed that AOD was high in the north and low in the south and that AOD gradually decreased from north to south over the SCS. AOD after 2000 was obviously higher than that of the 1980s and 1990s. Higher AOD appeared in the spring and winter, and low AOD appeared in the summer. The spatial distribution of scattering aerosol optical depth (SAOD) was similar to AOD distribution over the SCS. SO4AOD and SSAOD were obviously higher than black carbon aerosol optical depth (BCAOD), organic carbon aerosol optical depth (OCAOD), and dust aerosol optical depth (DUAOD) over the SCS. SO4AOD accounted for over 50% of total AOD (TAOD) over the north of the SCS, while BCAOD and DUAOD accounted for less than 10% of TAOD over the entire SCS. An obvious annual mean TAOD increase between 1980 and 2007 could be observed over the northern part of the SCS (NSCS), while a TAOD decrease happened from 2008 to 2020 in this region. The correlation coefficient between TAOD and SO4AOD over NSCS from 1980 to 2020 was about 0.93, indicating SO4AOD was the driving factor of TAOD variation in this area. Different AOD variation trends over the different areas of the SCS could be observed during the two periods including 1980–2007 and 2008–2020. AOD increase appeared over most of the SCS during the period from 1980 to 2007, while AOD decrease could be observed over most of the SCS from 2008 to 2020.

In the Himalayan region, aerosols received much attention because they affect the regional as well as local climate. Aerosol Optical Depth (AOD) observation from satellite are limited in the Himalayan region mainly due to high surface reflectance. To overcome this limitation, we have conducted a multivariate regression analysis to predict the AOD over the cryospheric portion of Nepalese Himalaya. Prediction using three meteorological variables from ERA-Interim: relative humidity, wind components (U10 and V10) were taken into account for model development as independent variables, while the longest time series AOD observation at Pokhara station is used as dependent variable. Model coefficients were found significant at 95 percent level with 0.53 coefficients of determination for daily values. Correlation coefficients between model output and AERONET observations were found to be 0.68, 0.73, 0.75, 0.83, and 0.82 at Lumbini, Kathmandu Bode (KTM-BO), Kathmandu University (KTM-UN), Jomson, and Pyramid laboratory/observatory (EVK2CNR) AERONET stations, respectively. Model overestimate AOD at Jomsom, and EVK2CNR AERONET stations while slightly underestimates AOD in Lumbini, KTM-UN, and KTM-BO AERONET station, respectively. Both model output and MODIS observation showed that the highest AOD over Nepal is observed during winter and pre-monsoon season. While lowest AOD is observed during monsoon, and post monsoon season. The result of this research supports that the use of linear regression model yields good estimation for daily average AOD in Nepal. The model that we have presented could possibly be used in other mountain regions for climate research.

Spatial and temporal variations of aerosol optical depth (AOD) over land at the global scale were investigated using the MODIS C005 data set from July 2002 to June 2007. Global average AOD, AODc (coarse mode AOD) and AODf (fine mode AOD) were mapped and analysed. It was found that AOD in Asia and Africa is nearly 2 times higher than that in South America, Europe and North America. A high level of η (fine model fraction (FMF) of AOD) was recorded where AOD is relatively low. Meanwhile, low η (0.05–0.3) was observed where AOD is extremely high. It suggests that coarse particles contribute much more than fine particles to global AOD over land. High AOD level in Nigeria and north India is dominated by coarse particles due to dust events. The average AOD in China (∼0.7) is almost 50% higher than that in India (∼0.55) and nearly 2–3 times higher than that in North America and Western Europe (0.2–0.3), due to spring dust in the west and intensive anthropogenic activities in the eastern part of China. Overall, the average AOD in the USA was limited in a relatively low level. At the same time, AOD in the western part of the USA (AODc = 0.28 and AODf = 0.06) is much higher than that in the east (AODc = 0.06 and AODf = 0.17). The annual cycle of global mean AOD showed a sinusoidal shape, where peaks occur during June–August and the lowest AODs appear in November–January. The peak month, peak value and possible sources for six major continents are Asia (April, AODpeak = 0.31, dust; June–July, AODpeak = 0.27, secondary aerosol), Africa (March, AODpeak = 0.28, dust; August, AODpeak = 0.28, wildfires), South America (September, AODpeak = 0.31, wildfires), North America (May–July, AODpeak = 0.18, dust and wildfires), Europe (March–April, AODpeak = 0.18, secondary aerosols), Oceania (December–January, AODpeak = 0.09, secondary aerosols). The inter-annual variation of AOD was insignificant at the global scale. However, the inter-annual variations at the regional scale were substantial. The abnormal peak of AOD during summer 2003 was probably due to dry and hot weather and intensive wildfires.

<strong class="journal-contentHeaderColor">Abstract.</strong> The southeast Atlantic is home to an expansive smoke aerosol plume overlying a large cloud deck for approximately a third of the year. The aerosol plume is mainly attributed to the extensive biomass burning activity that occurs in southern Africa. Current Earth system models (ESMs) reveal significant differences in their estimates of regional aerosol radiative effects over this region. Such large differences partially stem from uncertainties in the vertical distribution of aerosols in the troposphere. These uncertainties translate into different aerosol optical depths (AOD) in the planetary boundary layer (PBL) and the free troposphere (FT). This study examines differences of AOD fraction in the FT and AOD differences among ESMs (WRF-CAM5, WRF-FINN, GEOS-Chem, EAM-E3SM, ALADIN, GEOS-FP, and MERRA-2) and aircraft-based measurements from the NASA ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES) field campaign. Models frequently define the PBL as the well-mixed surface-based layer, but this definition misses the upper parts of decoupled PBLs, in which most low-level clouds occur. To account for the presence of decoupled boundary layers in the models, the height of maximum vertical gradient of specific humidity profiles from each model is used to define PBL heights. Results indicate that the monthly mean contribution of AOD in the FT to the total-column AOD ranges from 44&thinsp;% to 74&thinsp;% in September 2016 and from 54&thinsp;% to 71&thinsp;% in August 2017 within the region bounded by 25&deg;S&ndash;0&deg; and 15&deg;W&ndash;15&deg;E (excluding land) among the ESMs. Using the second-generation High Spectral Resolution Lidar (HSRL-2) to derive an aircraft-based constraint on the AOD and the fractional AOD, we found that WRF-CAM5 produces 40&thinsp;% less AOD than those from the HSRL-2 measurements, but it performs well at separating AOD fraction between the FT and the PBL. AOD fractions in the FT for GEOS-Chem and EAM-E3SM are, respectively, 10&thinsp;% and 15&thinsp;% lower than the AOD fractions from the HSRL-2 and their similarities in the mean AODs are the result of cancellation of high and low AOD biases. GEOS-FP, MERRA-2, and ALADIN produce 24&thinsp;%&ndash;36&thinsp;% less AOD and tend to misplace more aerosols in the PBL compared to aircraft-based observations. The models generally underestimate AODs for measured AODs that are above 0.8, indicating their limitations at reproducing high AODs. The differences in the absolute AOD, FT AOD, and the vertical apportioning of AOD in different models highlight the need to continue improving the accuracy of modeled AOD distributions. These differences affect the sign and magnitude of the net aerosol radiative forcing, especially when aerosols are in contact with clouds.

<strong class="journal-contentHeaderColor">Abstract.</strong> The southeast Atlantic is home to an expansive smoke aerosol plume overlying a large cloud deck for approximately a third of the year. The aerosol plume is mainly attributed to the extensive biomass burning activity that occurs in southern Africa. Current Earth system models (ESMs) reveal significant differences in their estimates of regional aerosol radiative effects over this region. Such large differences partially stem from uncertainties in the vertical distribution of aerosols in the troposphere. These uncertainties translate into different aerosol optical depths (AOD) in the planetary boundary layer (PBL) and the free troposphere (FT). This study examines differences of AOD fraction in the FT and AOD differences among ESMs (WRF-CAM5, WRF-FINN, GEOS-Chem, EAM-E3SM, ALADIN, GEOS-FP, and MERRA-2) and aircraft-based measurements from the NASA ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES) field campaign. Models frequently define the PBL as the well-mixed surface-based layer, but this definition misses the upper parts of decoupled PBLs, in which most low-level clouds occur. To account for the presence of decoupled boundary layers in the models, the height of maximum vertical gradient of specific humidity profiles from each model is used to define PBL heights. Results indicate that the monthly mean contribution of AOD in the FT to the total-column AOD ranges from 44&thinsp;% to 74&thinsp;% in September 2016 and from 54&thinsp;% to 71&thinsp;% in August 2017 within the region bounded by 25&deg;S&ndash;0&deg; and 15&deg;W&ndash;15&deg;E (excluding land) among the ESMs. Using the second-generation High Spectral Resolution Lidar (HSRL-2) to derive an aircraft-based constraint on the AOD and the fractional AOD, we found that WRF-CAM5 produces 40&thinsp;% less AOD than those from the HSRL-2 measurements, but it performs well at separating AOD fraction between the FT and the PBL. AOD fractions in the FT for GEOS-Chem and EAM-E3SM are, respectively, 10&thinsp;% and 15&thinsp;% lower than the AOD fractions from the HSRL-2 and their similarities in the mean AODs are the result of cancellation of high and low AOD biases. GEOS-FP, MERRA-2, and ALADIN produce 24&thinsp;%&ndash;36&thinsp;% less AOD and tend to misplace more aerosols in the PBL compared to aircraft-based observations. The models generally underestimate AODs for measured AODs that are above 0.8, indicating their limitations at reproducing high AODs. The differences in the absolute AOD, FT AOD, and the vertical apportioning of AOD in different models highlight the need to continue improving the accuracy of modeled AOD distributions. These differences affect the sign and magnitude of the net aerosol radiative forcing, especially when aerosols are in contact with clouds.

Aerosol parametric uncertainty in global climate models can be as large as intermodal uncertainty, posing a significant challenge for reliable climate projections. This study investigates the magnitude and drivers of aerosol-related uncertainty in the TM5 chemical transport model (CTM), the atmospheric chemistry and transport component of the EC-Earth3 Earth System Model (ESM), and a contributor to the Coupled Model Intercomparison Project (CMIP).Aerosol parameters in TM5 describe characteristics of emissions, removal, transformations, physical, chemical, and optical properties. To assess aerosol representation in TM5, we have performed one-at-a-time sensitivity studies, where individual aerosol parameters were perturbed to the minimum and maximum of their respective uncertainty ranges. The resulting impacts were evaluated using climate-relevant outputs, cloud condensation nuclei number (CCN) concentrations at supersaturations of 0.2% and 1% averaged over the lowest five model levels, and aerosol optical depth (AOD) at 550 nm. Model responses were analyzed on seasonal timescales over a two-year period (2017–2018).The results indicate that sea-salt and dimethyl sulfide (DMS) emissions, particle size of biomass-burning emissions, and dry-deposition rates exert the strongest influence on CCN number concentrations and aerosol optical depth (AOD). Simulated AOD from each sensitivity experiment was constrained using the AOD merged product for 2017 by Sogacheva et al. (2020). Seasonal comparisons were performed for 2017 across four regions: West Asia and North Africa (WANA), India and South Asia (ISA), Southern Africa (SA), and Mexico to Colombia (MC). Across all seasons, high AOD regions, TM5 exhibits minimal sensitivity to the perturbed simulations and accurately captures high AOD values. In contrast, the model shows more variation in low AOD values than the observations, where sensitivity to parameter perturbations, particularly emission-related parameters, is most pronounced. Increased dry deposition and reduced SO₂ emissions consistently improve low-AOD predictions with respect to the satellite product, especially in WANA and ISA, while the default setup performs best in South Asia and during JJA.These findings identify the aerosol parameters that contribute most significantly to uncertainty in TM5 and highlight the key sensitivities that will inform future work involving emulated perturbed-parameter ensemble (PPE) experiments. The PPEs will vary these parameters over their uncertainty range simultaneously to study their combined effect on TM5.

Land surface albedo (LSA) is an important parameter in surface energy balance and global climate change. It has been used in the fields of energy budgets, climate dynamics, and land surface processes. To apply satellite LSA products more widely, the product accuracy needs to be evaluated at different scales and under atmospheric and surface conditions. This study validates and analyzes the errors of the LSA datasets from the Global LAnd Surface Satellites (GLASS) product, the European Space Agency’s Earth Observation Envelope Programme (GlobAlbedo), the Quality Assurance for Essential Climate Variables (QA4ECV) project, the Gap-filled Snow-free Bidirectional Reflectance Distribution Function (BRDF) parameters product (MCD43GF), and the Satellite Application Facility on Climate Monitoring (CM SAF) Albedo dataset from the AVHRR data (CLARA-SAL) against the Chinese Ecosystem Research Network (CERN) measurements at different spatiotemporal scales over China from 2005 to 2015. The results show that LSA estimated by GLASS agrees well with the CERN measurements on a continental scale. The GLASS product is characterized by a correlation coefficient of 0.80, a root-mean-square error of 0.09, and a mean absolute error of 0.06. The consistency between GLASS, GlobAlbedo, and CLARA-SAL is slightly lower over the regions with high aerosol optical depth (AOD) (e.g. Sichuan Basin, northern China) and high cloud cover compared with that in regions with lower AOD and low cloud cover. The estimation errors are related to varying atmospheric and surface conditions and increase with increasing AOD and cloud cover and decreasing enhanced vegetation index. Therefore, algorithms under complex atmospheric and surface conditions (e.g. high AOD, sparse vegetation) should be optimized to improve the accuracy of LSA products.

This paper is devoted to analysis of aerosol distribution and variability over East Asia based on PARASOL/POLDER‐3 aerosol products over land. We first compared POLDER‐3 Aerosol Optical Depth (AOD) with fine mode AOD (particles radius ≤ 0.30 μm) computed from AERONET (Aerosol Robotic Network) inversions over 14 sites. The rather good correlation (R ≈ 0.92) observed over land demonstrates the remarkable sensitivity of POLDER‐3 retrievals to the smaller fraction of fine particles, mostly originating from anthropogenic sources. We analyzed the characteristics and seasonal variation of aerosol distribution over East Asia by considering 4 years of POLDER‐3 Level 2 data (March 2005 to February 2009). Our study shows that the spatial distribution of fine‐mode aerosols over East Asia, as retrieved from POLDER‐3, is highly associated with human activities. Our work also evidenced a strong variability of seasonal fine‐mode AOD patterns with geographical locations. Finally, the interannual variation during 2003–2009 periods of summer fine‐mode AOD over North China, in particular the Beijing City region, was analyzed for the contribution to evaluating the regional impact of emission reduction enforced in Beijing during the 2008 Olympic Summer Games. We found that the summer average of fine‐mode AOD exhibited relatively higher values in 2003, 2007, and 2008. The interannual variation patterns of monthly averaged AOD (June to August) shows that June generally exhibits the strongest variation and varies similarly to July, but differs from August. As a reference point, measured total AOD and fine‐mode AOD computed from AERONET inversions in summer are also discussed for the Beijing City region.

Assessing spatiotemporal variations of AOD in Japan based on Himawari-8 L3 V31 aerosol products: Validations and applications

Spatio-temporal variations of aerosol optical depth over Ukraine under the Russia-Ukraine war

Landscape determinants of spatio-temporal patterns of aerosol optical depth in the two most polluted metropolitans in the United States

Background: Urban green space (UGS) has been shown to play an important role in mitigating urban heat island (UHI) effects. In the context of accelerating urbanization, a better understanding of the landscape pattern mechanisms affecting the thermal environment is important for the improvement of the urban ecological environment. Methods: In this study, the relationship between land surface temperature (LST) and the spatial patterns of green space was analyzed using a bivariate spatial autocorrelation and spatial autoregression model in three seasons (summer, transition season (spring), and winter) with different grid scales in Fuzhou city. Results: Our results indicated that the LST in Fuzhou City has a significant spatial autocorrelation. The percentage of landscape and patch density area were negatively correlated with surface temperature. The results of our indicators differed according to the season, with population density and distance to the water indicators not being significant in the winter. The coefficient of determination was higher at the 510 m grid scale on this study’s scale. Conclusion: This study extends our understanding on the influence of UHI effects after accounting for different seasonal and spatial scale factors. It also provides a reference for urban planners to mitigate heat islands in the future.

The diurnal variation of Aerosol Optical Depth (AOD) and its spectral properties over non-cloudy days in summer and winter seasons of two years are studied. Spectral dependence of AOD shows higher values at shorter wavelengths which decreases gradually towards longer wavelengths for the summer as well as the winter period. Results suggest that during high relative humidity and stable conditions, the AOD is found to be relatively low (clear day) as compared to unstable meteorological conditions (turbid). Air mass back trajectory for 5 days of high and low AOD in March indicate that the sources of loading come from far to the west in central Asia, whereas during winter, the sources are from east and south-east direction in the Indo-Gangetic plain. The diurnal variation of Ǻngström exponent () has lowest values in the morning hours with a variation of around 5-17% for clear day and around 11-20% for turbid day, signifying the presence of larger particles. Due to inversion more fine particles lead to an increase in the  value. The intraseasonal variability in March (summer) is high and interseasonal variation in January (winter) is not observed and is also confirmed by ‘’ values. Size distribution of aerosols showed peak loading ranging around a 0.07 m radius. Aerosol loading on turbid days was due to fine mode particles and the simultaneous presence of fine- and coarse-mode particles on clear days.