Differences In Aerosol Optical Depth Research Articles

Intercomparison of aerosol optical depth retrievals from GAW-PFR and SKYNET sun photometer networks and the effect of calibration

Abstract. In this study, we assess the homogeneity of aerosol optical depth (AOD) between two sun photometer networks, the Global Atmosphere Watch-Precision Filter Radiometer (GAW-PFR) and the European SKYNET radiometers network (ESR), at the common wavelengths of their main instruments (500 and 870 nm). The main focus of this work is to evaluate the effect of the improved Langley plot calibration method (ILP) used by SKYNET and to investigate the factors affecting its performance. We used data from three intercomparison campaigns that took place during 2017–2021. Each campaign was organized at two locations (mountainous rural – Davos, Switzerland; urban – Rome, Italy). Our analysis shows that differences in AOD due to post-processing and instrument differences are minor. The main factor leading to AOD differences is the calibration method. We found a systematic underestimation of AOD in ESR compared to in GAW-PFR due to underestimation of the calibration constant calculated with the ILP method compared to the calibration transfers using the PFR as a reference. The calibration and AOD differences are smaller in Davos, where the traceability criteria are satisfied at 870 nm and where the median differences are below 0.01 at 500 nm. In Rome, the AOD median differences at 500 nm were in the 0.015–0.034 range. We conducted a sensitivity study, which shows that part of the difference can potentially be explained by errors in the assumed surface albedo and instrument solid-view angle provided as inputs to the ILP code (based on Skyrad pack 4.2). Our findings suggest that the ILP method is mainly sensitive to the measured sky radiance. The underestimation in calibration is probably caused by an error in the retrieved scattering AOD (sc-AOD) through the sky radiance inversion. Using an alternative retrieval method (Skyrad MRI pack version 2) to derive sc-AOD and to recalibrate the instruments with the ILP method, we found no significant differences between the retrieved sc-AOD and no systematic increase in the ILP-derived calibration constant when using the MRI pack for sc-AOD inversion instead of the Skyrad 4.2. The potential error may be a result of the model assumptions used for the sky radiance simulations. In conclusion, the on-site calibration of sun photometers has several advantages, including the fact that instrument shipments and data gaps can be avoided. However, it has also the disadvantages of a larger uncertainty and significant systematic differences compared to the traditional Langley calibration performed under low- and constant-AOD conditions at high-altitude sites. The larger uncertainty of the ILP method can be attributed to the required modelling and input parameters.

Assessment of the impact of NO2 contribution on aerosol-optical-depth measurements at several sites worldwide

Abstract. This work aims at investigating the effect of NO2 absorption on aerosol-optical-depth (AOD) measurements and Ångström exponent (AE) retrievals of sun photometers by the synergistic use of accurate NO2 characterization for optical-depth estimation from co-located ground-based measurements. The analysis was performed for ∼ 7 years (2017–2023) at several sites worldwide for the AOD measurements and AE retrievals by Aerosol Robotic Network (AERONET) sun photometers which use OMI (Ozone Monitoring Instrument) climatology for NO2 representation. The differences in AOD and AE retrievals by NO2 absorption are accounted for using high-frequency columnar NO2 measurements by a co-located Pandora spectroradiometer belonging to the Pandonia Global Network (PGN). NO2 absorption affects the AOD measurements in UV-Vis (visible) range, and we found that the AOD bias is the most affected at 380 nm by NO2 differences, followed by 440, 340, and 500 nm, respectively. AERONET AOD was found to be overestimated in half of the cases, while also underestimated in other cases as an impact of the NO2 difference from “real” (PGN NO2) values. Overestimations or underestimations are relatively low. About one-third of these stations showed a mean difference in NO2 and AOD (at 380 and 440 nm) above 0.5 × 10−4 mol m−2 and 0.002, respectively, which can be considered a systematic contribution to the uncertainties in the AOD measurements that are reported to be of the order of 0.01. However, under extreme NO2 loading scenarios (i.e. 10 % highest differences) at highly urbanized/industrialized locations, even higher AOD differences were observed that were at the limit of or higher than the reported 0.01 uncertainty in the AOD measurement. PGN NO2-based sensitivity analysis of AOD difference suggested that for PGN NO2 varying between 2 × 10−4 and 8 × 10−4 mol m−2, the median AOD differences were found to rise above 0.01 (even above 0.02) with the increase in NO2 threshold (i.e. the lower limit from 2 × 10−4 to 8 × 10−4 mol m−2). The AOD-derivative product, AE, was also affected by the NO2 correction (discrepancies between the AERONET OMI climatological representation of NO2 values and the real PGN NO2 measurements) on the spectral AOD. Normalized frequency distribution of AE (at 440–870 and 340–440 nm wavelength pair) was found to be narrower for a broader AOD distribution for some stations, and vice versa for other stations, and a higher relative error at the shorter wavelength (among the wavelength pairs used for AE estimation) led to a shift in the peak of the AE difference distribution towards a higher positive value, while a higher relative error at a lower wavelength shifted the AE difference distribution to a negative value for the AOD overestimation case, and vice versa for the AOD underestimation case. For rural locations, the mean NO2 differences were found to be mostly below 0.50 × 10−4 mol m−2, with the corresponding AOD differences being below 0.002, and in extreme NO2 loading scenarios, it went above this value and reached above 1.00 × 10−4 mol m−2 for some stations, leading to higher AOD differences but below 0.005. Finally, AOD and AE trends were calculated based on the original AERONET AOD (based on AERONET OMI climatological NO2), and its comparison with the mean differences in the AERONET and PGN NO2-corrected AOD was indicative of how NO2 correction could potentially affect realistic AOD trends.

Regional Aerosol Optical Depth over Antarctica

Atmospheric aerosols greatly contribute to the uncertainty in current climate models, particularly presenting pronounced limitations in the Antarctic region. This study measures aerosol properties using data from several Antarctic AERONET sites (Escudero, Marambio, South Pole, Utsteinen, Vechernaya_Hill) and Zhongshan Station. We examined the spatial and temporal patterns of two specific aerosol properties: Aerosol Optical Depth (AOD) at 500 nm (τ500nm) and Ångström Exponent (AE) between 440 and 870 nm (α440−870nm). Our findings reveal τ500nm medians ranging from 0.02 to 0.09, with elevated values observed along the coastal regions compared to the interior of Antarctica. Regarding the AE, the medians of α440−870nm indicate that the coarse-mode particle aerosols are dominated at Escudero (approximately 0.54). In contrast, fine mode particles prevail at the other sites (over 0.97). Monthly mean τ500nm and the proportion of fine mode particles peaks during austral summer and autumn, suggesting increased marine biological sources. Moreover, analyzing the air mass back trajectories, we discovered marine air influences on Escudero, Marambio, Zhongshan, and Vechernaya_Hill, while Utsteinen and South Pole are primarily experiencing air originating from the Antarctic continent. These findings underscore the significant role of aerosol sources in regional AOD differences. Additionally, higher τ500nm were more associated with significantly negative direct aerosol radiative forcing at the bottom of the atmosphere (DARF-BOA). The direct aerosol radiative forcing at the top of the atmosphere (DARF-TOA) closely correlates with single-scattering albedo (SSA), where high (low) SSA generally results in negative (positive) forcing over Antarctica.

Intercomparison of aerosol optical depths from four reanalyses and their multi-reanalysis consensus

Abstract. The emergence of aerosol reanalyses in recent years has facilitated a comprehensive and systematic evaluation of aerosol optical depth (AOD) trends and attribution over multi-decadal timescales. Notable multi-year aerosol reanalyses currently available include NAAPS-RA from the US Naval Research Laboratory, the NASA MERRA-2, JRAero from the Japan Meteorological Agency (JMA), and CAMSRA from Copernicus/ECMWF. These aerosol reanalyses are based on differing underlying meteorology models, representations of aerosol processes, as well as data assimilation methods and treatment of AOD observations. This study presents the basic verification characteristics of these four reanalyses versus both AERONET and MODIS retrievals in monthly AOD properties and identifies the strength of each reanalysis and the regions where divergence and challenges are prominent. Regions with high pollution and often mixed fine-mode and coarse-mode aerosol environments, such as South Asia, East Asia, Southeast Asia, and the Maritime Continent, pose significant challenges, as indicated by higher monthly AOD root mean square error. Moreover, regions that are distant from major aerosol source areas, including the polar regions and remote oceans, exhibit large relative differences in speciated AODs and fine-mode versus coarse-mode AODs among the four reanalyses. To ensure consistency across the globe, a multi-reanalysis consensus (MRC, i.e., ensemble mean) approach was developed similarly to the International Cooperative for Aerosol Prediction Multi-Model Ensemble (ICAP-MME). Like the ICAP-MME, while the MRC does not consistently rank first among the reanalyses for individual regions, it performs well by ranking first or second globally in AOD correlation and RMSE, making it a suitable candidate for climate studies that require robust and consistent assessments.

Aerosols in the central Arctic cryosphere: satellite and model integrated insights during Arctic spring and summer

Abstract. The central Arctic cryosphere is influenced by the Arctic amplification (AA) and is warming faster than the lower latitudes. AA affects the formation, loss, and transport of aerosols. Efforts to assess the underlying processes determining aerosol variability are currently limited due to the lack of ground-based and space-borne aerosol observations with high spatial coverage in this region. This study addresses the observational gap by making use of total aerosol optical depth (AOD) datasets retrieved by the AEROSNOW algorithm over the vast cryospheric region of the central Arctic during Arctic spring and summer. GEOS-Chem (GC) simulations combined with AEROSNOW-retrieved data are used to investigate the processes controlling aerosol loading and distribution at different temporal and spatial scales. For the first time, an integrated study of AOD over the Arctic cryosphere during sunlight conditions was possible with the AEROSNOW retrieval and GC simulations. The results show that the spatial patterns observed by AEROSNOW differ from those simulated by GC. During spring, which is characterized by long-range transport of anthropogenic aerosols in the Arctic, GC underestimates the AOD in the vicinity of Alaska in comparison with AEROSNOW retrieval. At the same time, it overestimates the AOD along the Bering Strait, northern Europe, and the Siberian central Arctic sea-ice regions, with differences of −12.3 % and 21.7 %, respectively. By contrast, GC consistently underestimates AOD compared with AEROSNOW in summer, when transport from lower latitudes is insignificant and local natural processes are the dominant source of aerosol, especially north of 70° N. This underestimation is particularly pronounced over the central Arctic sea-ice region, where it is −10.6 %. Conversely, GC tends to overestimate AOD along the Siberian and Greenland marginal sea-ice zones by 19.5 % but underestimates AOD along the Canadian Archipelago by −9.3 %. The differences in summer AOD between AEROSNOW data products and GC-simulated AOD highlight the need to integrate improved knowledge of the summer aerosol process into existing models in order to constrain its effects on cloud condensation nuclei, on ice nucleating particles, and on the radiation budget over the central Arctic sea ice during the developing AA period.

Characteristics of Daytime‐And‐Nighttime AOD Differences Over China: A Perspective From CALIOP Satellite Observations and GEOS‐Chem Model Simulations

AbstractWe use the GEOS‐Chem chemistry transport model to quantify the factors in the diel discrepancy of Aerosol Optical Depth (AOD) retrieved from Cloud‐Aerosol Lidar with Orthogonal Polarization (CALIOP) satellite observations over eastern China. The GEOS‐Chem simulation reveals that the AOD below 1 km is 58.5% larger at night than during the daytime, which is comparable to the counterpart of 41.3% from CALIOP (v4.2). Model sensitivity simulations show that the diurnal variation in wind barely impacts the AOD difference between daytime and nighttime, and the increase in AOD at nighttime is primarily caused by the lower temperature at nighttime compared to daytime. Further simulations demonstrate that the low temperature at night increases AOD primarily by increasing relative humidity, and hence particle hygroscopic growth, while the effect of temperature on chemical rate barely influences AOD. CALIOP also observes that the absolute difference in AOD above 1 km between nighttime and daytime is 0.105, while the counterpart in GEOS‐Chem simulations is −0.031. This contrast can be partly explained by the factor that the percentage of valid CALIOP retrievals below 5 km is 15%–20% greater at nighttime than in the daytime due to the CALIOP detection limit. Removing the detection limit impact decreases the difference in the CALIOP AOD above 1 km between nighttime and daytime to 0.073.

Aerosol properties derived from ground-based Fourier transform spectra within the COllaborative Carbon Column Observing Network

Abstract. Fourier transform infrared (FTIR) spectroscopy is particularly relevant for climate studies due to its ability to provide information on both fine absorption structures (i.e. trace gases) and broadband continuum signatures (i.e. aerosols or water continuum) across the entire infrared (IR) domain. In this context, this study assesses the capability of the portable and compact EM27/SUN spectrometer, used within the research infrastructure COCCON (COllaborative Carbon Column Observing Network), to retrieve spectral aerosol properties from low-resolution FTIR solar absorption spectra (0.5 cm−1). The study focuses on the retrieval of aerosol optical depth (AOD) and its spectral dependence in the 873–2314 nm spectral range from COCCON measurements at the subtropical high-mountain Izaña Observatory (IZO, Tenerife, Spain), which were coincidentally carried out with standard sun photometry within the Aerosol Robotic Network (AERONET) in the 3-year period from December 2019 to September 2022. The co-located AERONET–COCCON database was used to cross-validate these two independent techniques in the common spectral range (870–1640 nm), demonstrating an excellent agreement at the near-coincident spectral bands (mean AOD differences limited to 0.005, standard deviations up to 0.021 and Pearson regression coefficients up to 0.97). This indicates that the low-resolution COCCON instruments are suitable for detecting the aerosol broadband signal contained in the IR spectra in addition to the retrieval of precise trace gas concentrations, provided a robust calibration procedure (Langley-based or absolute calibration procedures) is used to compensate for the optical degradation of the external system (∼ 0.72 % per month). The study also assesses the capability of the EM27/SUN to simultaneously infer aerosols and trace gases and relate their common emission sources in two case study events: a volcanic plume from the La Palma eruption in 2021 and a nearby forest fire in Tenerife in 2022. Overall, our results demonstrate the potential of the portable low-resolution COCCON instruments to enhance the multi-parameter capability of the FTIR technique for atmospheric monitoring.

Spatiotemporal Variations of Aerosol Optical Depth and the Spatial Heterogeneity Relationship of Potential Factors Based on the Multi-Scale Geographically Weighted Regression Model in Chinese National-Level Urban Agglomerations

Investigating the spatiotemporal variation characteristics of aerosol optical depth (AOD) and its driving factors is essential for assessing atmospheric environmental quality and alleviating air pollution. Based on a 22-year high-resolution AOD dataset, the spatiotemporal variations of AOD in mainland China and ten national urban agglomerations were explored based on the Mann–Kendall trend test and Theil–Sen median method. Random forest (RF) and multiscale geographically weighted regression (MGWR) were combined to identify the main driving factors of AOD in urban agglomerations and to reveal the spatial heterogeneity of influencing factors. The results showed that areas with high annual average AOD concentrations were mainly concentrated in the Chengdu–Chongqing, Central Plains, Shandong Peninsula, and Middle Yangtze River urban agglomerations. Southern Beijing–Tianjin–Hebei and its surrounding areas revealed the highest AOD pollution during summer, whereas the worst pollution during the remaining three seasons occurred in the Chengdu–Chongqing urban agglomeration. Temporally, except for the Ha-Chang and Mid-Southern Liaoning urban agglomerations, where the average annual AOD increased, the other urban agglomerations showed a decreasing trend. Among them, the Central Plains, Middle Yangtze River, Guanzhong Plain, and Yangtze River Delta urban agglomerations all exhibited a decline greater than 20%. According to the spatial trends, most urban agglomerations encompassed much larger areas of decreasing AOD values than areas of increasing AOD values, indicating that the air quality in most areas has recently improved. RF analysis revealed that PM2.5 was the dominant factor in most urban clusters, followed by meteorological factors. MGWR results show that the influencing factors have different spatial scale effects on AOD in urban agglomerations. The socioeconomic factors and PM2.5 showed strong spatial non-stationarity with regard to the spatial distribution of AOD. This study can provide a comprehensive understanding of AOD differences among urban agglomerations, and it has important theoretical and practical implications for improving the ecological environment and promoting sustainable development.

A satellite-observation based study on responses of clouds to aerosols over South Asia during IOD events of south-west monsoon season

The present study investigated the possible effects of aerosols on cloud properties during positive and negative Indian Ocean Dipole (IOD) months over South Asia using 20 years (2002–2021) of long-term satellite-based observations and reanalyses datasets. Positive aerosol optical depth (AOD) differences between the two IOD phases are found mainly over the land areas and some parts of the Indian Ocean, with the maximum value observed over Indonesia, Malaysia, Northern China, Western India, and the Northern Arabian Sea. The negative AOD differences are seen over the equatorial Indian Ocean, some regions of Indian land mass, the North Indian Ocean, and some parts of the South China Sea, with the highest dip over the central Indo-Gangetic Plain region. The highest increase (decrease) in rainfall is observed over the western (eastern) pole. The reduced rainfall is responsible for the increased AOD over Indonesia, Malaysia, and neighboring regions. The strong negative relationships of cloud fraction (CF) with cloud top pressure and cloud optical depth (COD) suggest persisting optically thick middle and high-level clouds during the IOD months. Twomey effect is noticed over the study region during both the IOD phases irrespective of the meteorological conditions. CF and COD both showed an upsurge with increased AOD in the presence of high relative humidity and stronger updrafts, suggesting the role of prevailing meteorology in forming thicker clouds. However, the height of the cloud tops is getting lowered in polluted conditions. The aerosol-cloud relationships observed during IOD scenarios could be attributed to the prevailing meteorology.

Spatial and Temporal Variation of Aerosol Optical Depth in Huaihai Economic Zone from 1982 to 2021

Aerosol Optical Depth (AOD), quantifying the amount of aerosol in the atmosphere, is widely regarded as a crucial indicator for research on atmospheric physics and regional air quality. At present, the inversion of AOD from observation of satellite remote sensing sensors has become the main technology for large-scale monitoring of aerosol load. The Huaihai Economic Zone is the connecting belt of two key areas of atmospheric governance (the Yangtze River Delta and the Beijing-Tianjin-Hebei region, China), and it has been suffering from air pollution for many years and few studies of AOD focus on this region. Therefore, the spatial and temporal characteristics of the AOD are explored using MODIS AOD data and AVHRR AOD data in this region during the period from 1982 to 2021 in this study. The correlation coefficients between the AOD of satellite observation and actual air pollution were analyzed by combining PM2.5 pollutant concentration and air quality index (AQI) data. The results showed that the AOD is higher in the northwest than in the southeast, and it is different from season to season. The annual variation of AOD in the Huaihai Economic Zone is a W-shaped trend from 1982 to 2011, while the trend of annual AOD is decreasing after 2011. In terms of seasons, the whole differences in AOD are evident, exhibiting AOD values in summer > those in spring > those in autumn > and those in winter. Furthermore, it indicated that the quarterly and monthly variation of the AOD tends to be flat in recent years. Since 2015, the concentration of PM2.5 has continued to decline, the same as that of AQI. Meanwhile, the quarterly and monthly differences in PM2.5 are still obvious, with higher PM2.5 in winter and lower PM2.5 in summer. However, it also represented that PM2.5 is significantly higher in spring than in autumn from 2015 to 2018, which is the opposite for 2019 to 2021. Lastly, the correlation between AOD and PM2.5/AQI is also given; i.e., the correlation coefficients of AOD with PM2.5/AQI are 0.84/0.82, with the highest correlation coefficient in autumn (R = 0.86/0.91) and the lowest in winter (R = 0.46/0.48).

Quantification of tropical monsoon precipitation changes in terms of interhemispheric differences in stratospheric sulfate aerosol optical depth

Stratospheric Aerosol Geoengineering (SAG) is one of the solar geoengineering approaches that have been proposed to offset some of the impacts of anthropogenic climate change. Past studies have shown that SAG may have adverse impacts on the global hydrological cycle. Using a climate model, we quantify the sensitivity of the tropical monsoon precipitation to the meridional distribution of volcanic sulfate aerosols prescribed in the stratosphere in terms of the changes in aerosol optical depth (AOD). In our experiments, large changes in summer monsoon precipitation in the tropical monsoon regions are simulated, especially over the Indian region, in association with meridional shifts in the location of the intertropical convergence zone (ITCZ) caused by changes in interhemispheric AOD differences. Based on our simulations, we estimate a sensitivity of − 1.8° ± 0.0° meridional shift in global mean ITCZ and a 6.9 ± 0.4% reduction in northern hemisphere (NH) monsoon index (NHMI; summer monsoon precipitation over NH monsoon regions) per 0.1 interhemispheric AOD difference (NH minus southern hemisphere). We also quantify this sensitivity in terms of interhemispheric differences in effective radiative forcing and interhemispheric temperature differences: 3.5 ± 0.3% change in NHMI per unit (Wm−2) interhemispheric radiative forcing difference and 5.9 ± 0.4% change per unit (°C) interhemispheric temperature difference. Similar sensitivity estimates are also made for the Indian monsoon precipitation. The establishment of the relationship between interhemispheric AOD (or radiative forcing) differences and ITCZ shift as discussed in this paper will further facilitate and simplify our understanding of the effects of SAG on tropical monsoon rainfall.

Impacts of estimated plume rise on PM2.5 exceedance prediction during extreme wildfire events: a comparison of three schemes (Briggs, Freitas, and Sofiev)

Abstract. Plume height plays a vital role in wildfire smoke dispersion and the subsequent effects on air quality and human health. In this study, we assess the impact of different plume rise schemes on predicting the dispersion of wildfire air pollution and the exceedances of the National Ambient Air Quality Standards (NAAQS) for fine particulate matter (PM2.5) during the 2020 western United States wildfire season. Three widely used plume rise schemes (Briggs, 1969; Freitas et al., 2007; Sofiev et al., 2012) are compared within the Community Multiscale Air Quality (CMAQ) modeling framework. The plume heights simulated by these schemes are comparable to the aerosol height observed by the Multi-angle Imaging SpectroRadiometer (MISR) and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). The performance of the simulations with these schemes varies by fire case and weather conditions. On average, simulations with higher plume injection heights predict lower aerosol optical depth (AOD) and surface PM2.5 concentrations near the source region but higher AOD and PM2.5 in downwind regions due to the faster spread of the smoke plume once ejected. The 2-month mean AOD difference caused by different plume rise schemes is approximately 20 %–30 % near the source regions and 5 %–10 % in the downwind regions. Thick smoke blocks sunlight and suppresses photochemical reactions in areas with high AOD. The surface PM2.5 difference reaches 70 % on the West Coast of the USA, and the difference is lower than 15 % in the downwind regions. Moreover, the plume injection height affects pollution exceedance (>35 µg m−3) predictions. Higher plume heights generally produce larger downwind PM2.5 exceedance areas. The PM2.5 exceedance areas predicted by the three schemes largely overlap, suggesting that all schemes perform similarly during large wildfire events when the predicted concentrations are well above the exceedance threshold. At the edges of the smoke plumes, however, there are noticeable differences in the PM2.5 concentration and predicted PM2.5 exceedance region. For the whole period of study, the difference in the total number of exceedance days could be as large as 20 d in northern California and 4 d in the downwind regions. This disagreement among the PM2.5 exceedance forecasts may affect key decision-making regarding early warning of extreme air pollution episodes at local levels during large wildfire events.

Improving aerosol optical depth retrievals from Himawari-8 with ensemble learning enhancement: Validation over Asia

The Advanced Himawari Imager (AHI) onboard the Himawari-8 spacecraft from the Japan Meteorological Agency (JMA) enables retrieval of aerosol optical depth (AOD) with high spatio-temporal resolution. This work demonstrates that the latest version of Level-3 AHI AOD product is affected by an overall underestimation against ground measurements from 98 sunphotometer sites over Asia, with site-average R2 and mean bias error (MBE) of 0.54 and − 0.10, respectively. The MBE varies from −0.23 to 0.03 over land, depending on site, and averages 0.06 over water. To correct these errors, an XGBoost model has been developed based on the AHI AOD, as well as meteorological quantities and geographic information from the ERA5 ECMWF reanalysis, a digital elevation model (DEM), and ground-based AOD measurements obtained in 2018. After application of this correction algorithm, the testing dataset indicates that R2 and the fraction of data included within the expected error (EE) envelope (±15%) are 0.86 and 74.7%, respectively, thus representing substantial improvement compared to the corresponding uncorrected results of 0.59 and 42.2%. The optimal XGBoost also demonstrates a good generalization ability because 69.5% of the corrected AOD falls within the EE envelope when applying the model to AHI data from 2019. The model's Feature Importance analysis shows that, besides the raw AHI AOD, geographic coordinates, surface albedo, and atmospheric water vapor contribute significantly to the correction model. The AOD difference map (corrected AOD minus raw AHI AOD) reveals that the XGBoost model improves AOD values considerably for land areas by 0.14, 0.10, 0.09, and 0.11 for MAM, JJA, SON and DJF, respectively.

Embedded information of aerosol type, hygroscopicity and scattering enhancement factor revealed by the relationship between PM2.5 and aerosol optical depth

Satellite aerosol optical depth (AOD) provides an alternative way to depict the spatial distribution of near-surface PM2.5. In this study, a mathematical formulation of how PM2.5 is related to AOD is presented. When simplified to a linear equation, a functional dependence of the slope on the aerosol type, scattering enhancement factor f(RH), and boundary layer height is revealed, while the influence of the vertical aerosol profile is embedded in the intercept. Specifically, we focus on the effects of aerosol properties and employ a new aerosol index (Normalized Gradient Aerosol Index, NGAI) for classifying aerosol subtypes. The combination of AOD difference at shorter wavelengths over longer-wavelength AOD from AERONET data could distinguish and subclassify aerosol types previously indistinguishable by AE (i.e., urban-industrial pollution, U/I, and biomass burning, BB). AOD-PM2.5 regressions are performed on these aerosol subtypes at various relative humidity (RH) levels. The results suggest that BB aerosols are nearly hydrophobic until the RH exceeds 80 %, while the AOD-PM2.5 regressions for U/I depend on RH levels. Moreover, the scattering enhancement factor f(RH) can be calculated by taking the ratio of intercepts between dry and humidity conditions, which is proposed and tested for the first time in this study. Our results show an f(RH ≥ 80 %) of ∼2.6 for U/I-dominated aerosols, whereas the value is not over 1.5 for BB aerosols. The f(RH) can be further used to derive the optical hygroscopicity parameter (κsca), demonstrating that the NGAI can be used to exploit differences in aerosol hygroscopicity and improve the AOD-PM2.5 relationship.

Ambient Aerosol Is Physically Larger on Cloudy Days in Bondville, Illinois.

Particle chemical composition affects aerosol optical and physical properties in ways important for the fate, transport, and impact of atmospheric particulate matter. For example, hygroscopic constituents take up water to increase the physical size of a particle, which can alter the extinction properties and atmospheric lifetime. At the collocated AERosol RObotic NETwork (AERONET) and Interagency Monitoring of PROtected Visual Environments (IMPROVE) network monitoring stations in rural Bondville, Illinois, we employ a novel cloudiness determination method to compare measured aerosol physicochemical properties on predominantly cloudy and clear sky days from 2010 to 2019. On cloudy days, aerosol optical depth (AOD) is significantly higher than on clear sky days in all seasons. Measured Ångström exponents are significantly smaller on cloudy days, indicating physically larger average particle size for the sampled populations in all seasons except winter. Mass concentrations of fine particulate matter that include estimates of aerosol liquid water (ALW) are higher on cloudy days in all seasons but winter. More ALW on cloudy days is consistent with larger particle sizes inferred from Ångström exponent measurements. Aerosol chemical composition that affects hygroscopicity plays a determining impact on cloudy versus clear sky differences in AOD, Ångström exponents, and ALW. This work highlights the need for simultaneous collocated, high-time-resolution measurements of both aerosol chemical and physical properties, in particular at cloudy times when quantitative understanding of tropospheric composition is most uncertain.

Investigating the long-term trends in aerosol optical depth and its association with meteorological parameters and enhanced vegetation index over Turkey.

Aerosol optical depth (AOD) provides useful information on particulate matter pollution at both regional and global levels. In this study, the long-term datasets of aerosols, meteorological parameters, and enhanced vegetation index (EVI) were used from September 2002 to December 2021 over Turkey. This study examined the spatiotemporal distribution of aerosols and their association with meteorological parameters (temperature (Temp), relative humidity (RH), wind speed (WS)), and EVI over Turkey from 2002 to 2021. Moreover, this study also performed a comparison of AOD retrieved from Aqua with other satellites (Terra, SeaWiFS, and MISR) and ground-based (AERONET) products. The higher mean seasonal AOD (> 0.3) was observed over Southeastern Anatolia Region due to the dust transport from the Saharan Desert and Arabian Peninsula. Moreover, AOD was positively correlated with Temp and WS in the east of Turkey, while negative correlations were observed in the coastal regions. The correlation between AOD and RH was also observed negative in most parts of Turkey. Furthermore, in the coastal region, the correlation between AOD and EVI was found to be positive, whereas a negative correlation was seen over less vegetative areas. The multi-seasonal AOD averages were calculated as 0.187, 0.183, 0.138, and 0.104 for the spring, summer, autumn, and winter seasons, respectively. The most important result of this study is the regional differences in AOD over Turkey. For new studies, AOD should be observed separately for coastal areas and the eastern part of Turkey.

Extended validation and evaluation of the OLCI–SLSTR SYNERGY aerosol product (SY_2_AOD) on Sentinel-3

Abstract. We present the first extended validation of a new SYNERGY global aerosol product (SY_2_AOD), which is based on synergistic use of data from the Ocean and Land Color Instrument (OLCI) and the Sea and Land Surface Temperature Radiometer (SLSTR) sensors aboard the Copernicus Sentinel-3A (S3A) and Sentinel-3B (S3B) satellites. Validation covers period from 14 January 2020 to 30 September 2021. Several approaches, including statistical analysis, time series analysis, and comparison with similar aerosol products from the other spaceborne sensor, the Moderate Resolution Imaging Spectroradiometer (MODIS), were applied for validation and evaluation of S3A and S3B SY_2 aerosol products, including aerosol optical depth (AOD) provided at different wavelengths, AOD pixel-level uncertainties, fine-mode AOD, and Angström exponent. Over ocean, the performance of SY_2 AOD (syAOD) retrieved at 550 nm is good: for S3A and S3B, Pearson correlation coefficients with the Maritime Aerosol Network (MAN) component of the AErosol RObotic NETwork (AERONET) are 0.88 and 0.85, respectively; 88.6 % and 89.5 % of pixels fit into the MODIS error envelope (EE) of ±0.05 ± 0.2 × AOD. Over land, correlation coefficients with AERONET AOD (aAOD) are 0.60 and 0.63 for S3A and S3B, respectively; 51.4 % and 57.9 % of pixels fit into MODIS EE. Reduced performance over land is expected since the surface reflectance and angular distribution of scattering are higher and more difficult to predict over land than over ocean. The results are affected by a large number of outliers. Evaluation of the per-retrieval uncertainty with the χ2 test indicates that syAOD prognostic uncertainties (PU) are slightly underestimated (χ2 = 3.1); if outliers are removed, PU describes the syAOD error well (χ2 = 1.6). The regional analysis of the Angström exponent, which relates to the aerosol size distribution, shows spatial correlation with expected sources. For 40 % of the matchups with AERONET in the Northern Hemisphere (NH) and for 60 % of the matchups in the Southern Hemisphere (SH), which fit into the AE size range of [1, 1.8], an offset between SY_2 AE (syAE) and AERONET AE (aAE) is within ±0.25. General overestimation of low (< 0.5) syAE and underestimation of high (> 1.8) syAE results in high (0.94, globally) overall bias. Good agreement (bias < 0.03) was observed between Sy_2 fine-mode AOD (syFMAOD) and AERONET fine-mode AOD (aFMAOD) for aFMAOD < 1. At aFMAOD > 1, syFMAOD is considerably underestimated (by 0.3–0.5 in different aFMAOD ranges) in the NH. In the SH, only a few aFMAOD values above 1 are measured. The fine-mode fraction (FMF) in the SY_2 AOD product (syFMF) in the range of [0, 0.7] is overestimated; the positive offset of 0.3–0.5 for low (< 0.25) FMF gradually decreases. Differences between the annual and seasonal AOD values from SY_2 and MODIS (mod) Dark Target and Deep Blue products are within 0.02 for the study area (30∘ S–60∘ N, 80∘ W–45∘ E). The agreement is better over ocean; however, a difference up to 0.6 exists between syFMF and modFMF. Over bright land surface (Saharan desert) the difference in AOD between the two products is highest (up to 0.11); the sign of the difference varies over time and space. For both S3A and S3B AOD products, validation statistics are often slightly better in the Southern Hemisphere. In general, the performance of S3B is slightly better.

SI-traceable solar irradiance measurements for aerosol optical depth retrieval

The overall aim of this study is to enable the traceable to International System of Units (SI) determination of column-integrated aerosol optical depth (AOD) retrieved from the passive remote sensing of the atmosphere using SI-traceable direct solar spectral irradiance measurements. A precision filter radiometer that measures direct solar spectral irradiance for the retrieval of AOD has been characterized and calibrated at the state-of-the-art calibration facilities of Physikalisch-Technische Bundesanstalt. The measured SI-traceable solar irradiances together with three state-of-the-art top-of-the-atmosphere (TOA) solar spectra have been used for retrieving AODs, which were validated against the reference AOD instruments of the World Aerosol Optical Depth Calibration Centre of the World Meteorological Organization (WMO). Calibration factors agreed within ±0.57% (3σ) using all three TOA spectra except for 368 nm (−1.1%) and 862 nm (1.8%) channels for one out of the three TOA spectra. Application of these results to the AOD retrieval showed AOD differences with the current reference methods/instruments well within the recommended WMO limits. The work provides a first step to opening a new era of AOD measurements traceability, providing a link to the SI through a laboratory-based approach, with the main advantages being the low uncertainty, the possibility of enhancing global AOD homogenization efforts and the chance to avoid calibration activities based on instrument relocations.

Influences of atmospheric reanalysis on the accuracy of clear-sky irradiance estimates: Comparing MERRA-2 and CAMS

This contribution compares the influences of atmospheric reanalysis, in particular, the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) produced by NASA's Global Modeling and Assimilation Office and the global reanalysis of atmospheric composition produced by the Copernicus Atmosphere Monitoring Service (CAMS), on the accuracy of clear-sky irradiance estimates. In terms of reanalysis output, comparison shows there exist great differences in aerosol optical depth (AOD) and Ångström exponent (AE) between the two reanalysis models. Based on 58 sunphotometer stations, it is found that daily MERRA-2 AOD is negatively biased with prominent underestimation in western China. CAMS AOD has considerable improvements in eastern China against MERRA-2, which may be associated with the high-quality assimilation of MODIS AOD and gas emissions, in a timely and consistent fashion. Both reanalyses tend to underestimate the fine-dominated aerosols (AE > 1.6) while overestimating the coarse-dominated ones (AE < 0.8). In terms of irradiance, a high-performance physical clear-sky model called the Reference Evaluation of Solar Transmittance, 2 bands (REST2) is used as the basis of evaluation. The performance of REST2-modeled global horizontal irradiance (GHI) based on the two reanalysis products is subsequently examined using data from 10 ground-based radiometry sites. It is concluded that the clearness index of clear-sky GHI (ktc) computed based on MERRA-2 and that based on CAMS show comparative performance over most parts of China, though there are exceptions. For instance, CAMS-based ktc outperforms MERRA-2 in eastern China, with slopes closer to unity, intercepts and root mean square errors closer to 0, which can be attributed to the improvements in CAMS AOD. The daily accumulated ΔGHI (i.e., GHIMERRA-2− GHICAMS) changes linearly with ΔAOD (i.e., AODMERRA-2− AODCAMS), implying better AOD quality has advantages in accumulated GHI estimation. Therefore, CAMS reanalysis data is recommended for solar resource assessment applications in eastern China, albeit that MERRA-2 has a higher temporal resolution (1 h) and coverage (from 1980 to present).

Adaptive AOD Forecast Model Based on GNSS-Derived PWV and Meteorological Parameters

Aerosol optical depth (AOD) is one of the basic parameters for determining the total aerosol content, and it exerts an important impact on regional environment pollution. To investigate the spatiotemporal variations of AOD, this study analyzes the relationship of AOD with precipitable water vapor (PWV) derived from a global navigation satellite system (GNSS) and meteorological parameters and proposes an adaptive AOD forecasting (AAF) model. In this model, the initial AOD value is determined using an empirical AOD model that considers annual periodicity, and the AOD difference is fitted using PWV, temperature (T), and surface pressure (P). In addition, this model also considers the time autocorrelation of the AOD difference; the model coefficients can be adaptively updated with training data. AOD data at 550 nm derived from the aerosol robotic network (AERONET), second modern-era retrospective analysis for research and applications (MERRA-2), and Copernicus atmosphere monitoring service (CAMS) for the Beijing-Tianjin-Hebei area are utilized to validate the proposed AAF model. Numerical results show that: 1) the accuracy of AOD derived from MERRA-2 is superior to that obtained from CAMS; 2) AOD is negatively correlated with P, is positively correlated with PWV and T, and has a high time autocorrelation with the AOD difference at consecutive times; and 3) the proposed AAF model demonstrates better performance than the traditional multiple linear regression (MLR) model. The average root mean square error (RMSE), mean absolute error (MAE), and bias of the AAF model are 0.17, 0.14, and -0.04, respectively, and those of the MLR model are 0.31, 0.25, and 0.06, respectively. These results reveal that the proposed AAF model can estimate AOD with high precision and has considerable potential for application in AAF research.