Sensitivity studies are conducted regarding aerosol optical property retrieval from radiances measured by ground‐based Sun‐sky scanning radiometers of the Aerosol Robotic Network (AERONET). These ...studies focus on testing a new inversion concept for simultaneously retrieving aerosol size distribution, complex refractive index, and single‐scattering albedo from spectral measurements of direct and diffuse radiation. The perturbations of the inversion resulting from random errors, instrumental offsets, and known uncertainties in the atmospheric radiation model are analyzed. Sun or sky channel miscalibration, inaccurate azimuth angle pointing during sky radiance measurements, and inaccuracy in accounting for surface reflectance are considered as error sources. The effects of these errors on the characterization of three typical and optically distinct aerosols with bimodal size distributions (weakly absorbing water‐soluble aerosol, absorbing biomass‐burning aerosol, and desert dust) are considered. The aerosol particles are assumed in the retrieval to be polydispersed homogeneous spheres with the same complex refractive index. Therefore we also examined how inversions with such an assumption bias the retrievals in the case of nonspherical dust aerosols and in the case of externally or internally mixed spherical particles with different refractive indices. The analysis shows successful retrieval of all aerosol characteristics (size distribution, complex refractive index, and single‐scattering albedo), provided the inversion includes the data combination of spectral optical depth together with sky radiances in the full solar almucantar (with angular coverage of scattering angles up to 100° or more). The retrieval accuracy is acceptable for most remote sensing applications even in the presence of rather strong systematic or random uncertainties in the measurements. The major limitations relate to the characterization of low optical depth situations for all aerosol types, where high relative errors may occur in the direct radiation measurements of aerosol optical depth. Also, the results of tests indicate that a decrease of angular coverage of scattering (scattering angles of 75° or less) in the sky radiance results in the loss of practical information about refractive index. Accurate azimuth angle pointing is critical for the characterization of dust. Scattering by nonspherical dust particles requires special analysis, whereby approximation of the aerosol by spheres allows us to derive single‐scattering albedo by inverting spectral optical depth together with sky radiances in the full solar almucantar. Inverting sky radiances measured in the first 40° scattering angle only, where nonspherical effects are minor, results in accurate retrievals of aerosol size distributions of nonspherical particles.
Retrievals of aerosol optical depth (AOD) and related parameters from satellite measurements typically involve prescribed models of aerosol size and composition, and are therefore dependent on how ...well these models are able to represent the radiative behavior of real aerosols. This study uses aerosol volume size distributions retrieved from Sun‐photometer measurements at 11 Aerosol Robotic Network (AERONET) island sites, spread throughout the world's oceans, as a basis to define such a model for pure (unpolluted) maritime aerosol. Volume size distributions are observed to be bimodal and approximately lognormal, although the coarse mode is skewed with a long tail on the low‐radius end. The relationship of AOD and size distribution parameters to meteorological conditions is also examined. As wind speed increases, so do coarse‐mode volume and radius. The AOD and Ångström exponent show linear relationships with wind speed, although with considerable scatter. Links between aerosol properties and near‐surface relative humidity, columnar water vapor, and sea surface temperature are also explored. A recommended bimodal maritime model, which is able to reconstruct the AERONET AOD with accuracy of order 0.01–0.02, is presented for use in aerosol remote sensing applications. This accuracy holds at most sites and for wavelengths between 340 nm and 1020 nm. Calculated lidar ratios are also provided, and are in the range of other studies, although differ more strongly from those currently used in Cloud‐Aerosol Lidar with Orthogonal Polarization (CALIOP) processing.
Key Points
Unpolluted marine aerosol properties from AERONET are globally similar
Wind speed influences aerosol properties more strongly than other factors
An aerosol model is presented for use in remote sensing applications
Aerosol variations and trends over different land and ocean regions from 1980 to 2009 are analyzed with the Goddard Chemistry Aerosol Radiation and Transport (GOCART) model and observations from ...multiple satellite sensors and available ground-based networks. Excluding time periods with large volcanic influence, aerosol optical depth (AOD) and surface concentration over polluted land regions generally vary with anthropogenic emissions, but the magnitude of this association can be dampened by the presence of natural aerosols, especially dust. Over the 30-year period in this study, the largest reduction in aerosol levels occurs over Europe, where AOD has decreased by 40–60% on average and surface sulfate concentrations have declined by a factor of up to 3–4. In contrast, East Asia and South Asia show AOD increases, but the relatively high level of dust aerosols in Asia reduces the correlation between AOD and pollutant emission trends. Over major dust source regions, model analysis indicates that the change of dust emissions over the Sahara and Sahel has been predominantly driven by the change of near-surface wind speed, but over Central Asia it has been largely influenced by the change of the surface wetness. The decreasing dust trend in the North African dust outflow region of the tropical North Atlantic and the receptor sites of Barbados and Miami is closely associated with an increase of the sea surface temperature in the North Atlantic. This temperature increase may drive the decrease of the wind velocity over North Africa, which reduces the dust emission, and the increase of precipitation over the tropical North Atlantic, which enhances dust removal during transport. Despite significant trends over some major continental source regions, the model-calculated global annual average AOD shows little change over land and ocean in the past three decades, because opposite trends in different land regions cancel each other out in the global average, and changes over large open oceans are negligible. This highlights the necessity for regional-scale assessment of aerosols and their climate impacts, as global-scale average values can obscure important regional changes.
Recently, some authors have suggested that the absorption Ångström exponent (AAE) can be used to deduce the component aerosol absorption optical depths (AAODs) of carbonaceous aerosols in the AERONET ...database. This AAE approach presumes that AAE ≪ 1 for soot carbon, which contrasts the traditional small particle limit of AAE = 1 for soot carbon. Thus, we provide an overview of the AERONET retrieval, and we investigate how the microphysics of carbonaceous aerosols can be interpreted in the AERONET AAE product. We find that AAE ≪ 1 in the AERONET database requires large coarse mode fractions and/or imaginary refractive indices that increase with wavelength. Neither of these characteristics are consistent with the current definition of soot carbon, so we explore other possibilities for the cause of AAE ≪ 1. AAE is related to particle size, and coarse mode particles have a smaller AAE than fine mode particles for a given aerosol mixture of species. We also note that the mineral goethite has an imaginary refractive index that increases with wavelength, is very common in dust regions, and can easily contribute to AAE ≪ 1. We find that AAE ≪ 1 can not be caused by soot carbon, unless soot carbon has an imaginary refractive index that increases with wavelength throughout the visible and near-infrared spectrums. Finally, AAE is not a robust parameter for separating carbonaceous absorption from dust aerosol absorption in the AERONET database.
This study evaluates a new spectral aerosol optical depth (AOD) dataset derived from Sea-viewing Wide Field-of-view Sensor (SeaWiFS) measurements over land. First, the data are validated against ...Aerosol Robotic Network (AERONET) direct-sun AOD measurements and found to compare well on a global basis. If only data with the highest quality flag are used, the correlation is 0.86 and 72% of matchups fall within an expected absolute uncertainty of 0.05 + 20% (for the wavelength of 550 nm). The quality is similar at other wavelengths and stable over the 13-yr (1997-2010) mission length. Performance tends to be better over vegetated, low-lying terrain with typical AOD of 0.3 or less, such as found over much of North America and Eurasia. Performance tends to be poorer for low-AOD conditions near backscattering geometries, where SeaWiFS overestimates AOD, or optically-thick cases of absorbing aerosol, where SeaWiFS tends to underestimate AOD. Second, the SeaWiFS data are compared with midvisible AOD derived from the Moderate Resolution Imaging Spectrometer (MODIS) and Multiangle Imaging Spectroradiometer (MISR). All instruments show similar spatial and seasonal distributions of AOD, although there are regional and seasonal offsets between them. At locations where AERONET data are available, these offsets are largely consistent with the known validation characteristics of each dataset. With the results of this study in mind, the SeaWiFS over-land AOD record is suitable for quantitative scientific use.
Large fine mode–dominated aerosols (submicron radius) in size distributions retrieved from the Aerosol Robotic Network (AERONET) have been observed after fog or low‐altitude cloud dissipation events. ...These column‐integrated size distributions have been obtained at several sites in many regions of the world, typically after evaporation of low‐altitude cloud such as stratocumulus or fog. Retrievals with cloud‐processed aerosol are sometimes bimodal in the accumulation mode with the larger‐size mode often ∼0.4–0.5μm radius (volume distribution); the smaller mode, typically ∼0.12 to ∼0.20 μm, may be interstitial aerosol that were not modified by incorporation in droplets and/or aerosol that are less hygroscopic in nature. Bimodal accumulation mode size distributions have often been observed from in situ measurements of aerosols that have interacted with clouds, and AERONET size distribution retrievals made after dissipation of cloud or fog are in good agreement with particle sizes measured by in situ techniques for cloud‐processed aerosols. Aerosols of this type and large size range (in lower concentrations) may also be formed by cloud processing in partly cloudy conditions and may contribute to the “shoulder” of larger‐size particles in the accumulation mode retrievals, especially in regions where sulfate and other soluble aerosol are a significant component of the total aerosol composition. Observed trends of increasing aerosol optical depth (AOD) as fine mode radius increased suggests higher AOD in the near‐cloud environment and higher overall AOD than typically obtained from remote sensing owing to bias toward sampling at low cloud fraction.
Key Points
Fine mode bimodal size distributions observed after cloud/fog dissipation
Cloud‐processed mode radius in good agreement with in situ measurements
Fine mode large radius shoulder may indicate effects of cloud interaction
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.
Atmospheric aerosol distributions from 2000 to 2007 are simulated with the Goddard Chemistry Aerosol Radiation and Transport (GOCART) model to attribute light absorption by aerosol to its composition ...and sources from pollution, dust, and biomass burning. The 8-year, global averaged total aerosol optical depth (τ), absorption optical depth (τa), and single scattering albedo (ω) at 550 nm are estimated at 0.14, 0.0086, and 0.95, respectively, with sulfate making the largest fraction of τ (37%), followed by dust (30%), sea salt (16%), organic matter (OM) (13%), and black carbon (BC) (4%). BC and dust account for 43% and 53% of τa, respectively. From a model experiment with "tagged" sources, natural aerosols are estimated to be 58% of τ and 53% of τa, with pollution and biomass burning aerosols to share the rest. Comparing with data from the surface sunphotometer network AERONET, the model tends to reproduce much better the AERONET direct measured data of τ and the Ångström exponent (α) than its retrieved quantities of ω and τa. Relatively small in its systematic bias of τ for pollution and dust regions, the model tends to underestimate τ for biomass burning aerosols by 30–40%. The modeled α is 0.2–0.3 too low (particle too large) for pollution and dust aerosols but 0.2–0.3 too high (particle too small) for the biomass burning aerosols, indicating errors in particle size distributions in the model. Still, the model estimated ω is lower in dust regions and shows a much stronger wavelength dependence for biomass burning aerosols but a weaker one for pollution aerosols than those quantities from AERONET. These comparisons necessitate model improvements on aerosol size distributions, the refractive indices of dust and black carbon aerosols, and biomass burning emissions in order to better quantify the aerosol absorption in the atmosphere.
Thirty‐three months of aerosol data in Beijing are presented in this paper. Aerosol optical thickness (AOT) increases from January to June and then decreases gradually. However, airborne particulate ...matter with diameter less than 10 μm (PM10) concentration exhibits higher values in winter and spring and lower concentration in summer. For the same PM10 concentration, AOT in summer is approximately two, three, and four times that in autumn, winter, and spring, respectively. AOT increases persistently during daytime, and the diurnal variation varies from about 15% in summer to about 45% in winter. The seasonal and diurnal variation of AOT is quite different from that of surface particle concentration. This is partly attributed to the variation of atmospheric mixing layer height. Aerosol volume concentrations increase with AOT by nearly identical magnitude for fine and coarse mode except in spring. The volume concentration of coarse mode in spring increases by a magnitude of more than two times that derived in remaining seasons. Aerosol fine mode radius increases with AOT, whereas coarse mode radius keeps relatively invariable with AOT. Mean aerosol single‐scattering albedo at 440 nm is about 0.90 and decreases slightly with wavelength. Aerosol single‐scattering albedos increase and their spectral dependence reverses during dust periods. Aerosol size and absorption in Beijing are close to results derived in Mexico City and Kanpur, but they are quite different from those in Maryland and Paris. Therefore different urban aerosol models should be created and used in satellite remote sensing in different urban regions.
MODerate resolution Imaging Spectroradiometer (MODIS) instruments aboard the Terra and Aqua satellites have provided a rich dataset of aerosol information at a 10 km spatial scale. Although ...originally intended for climate applications, the air quality community quickly became interested in using the MODIS aerosol data. However, 10 km resolution is not sufficient to resolve local scale aerosol features. With this in mind, MODIS Collection 6 includes a global aerosol product with a 3 km resolution. Here, we evaluate the 3 km product over the Baltimore-Washington D.C., USA, corridor during the summer of 2011 by comparing with spatially dense aerosol data measured by airborne High Spectral Resolution Lidar (HSRL) and a network of 44 sun photometers (SP) spaced approximately 10 km apart, collected as part of the DISCOVER-AQ field campaign. The HSRL instrument shows that AOD can vary by over 0.2 within a single 10 km MODIS pixel, meaning that higher resolution satellite retrievals may help to better characterize aerosol spatial distributions in this region. Different techniques for validating a high-resolution aerosol product against SP measurements are considered. Although the 10 km product is more statistically reliable than the 3 km product, the 3 km product still performs acceptably with nearly two-thirds of MODIS/SP collocations falling within an expected error envelope with high correlation (R > 0.90), although with a high bias of ~ 0.06. The 3 km product can better resolve aerosol gradients and retrieve closer to clouds and shorelines than the 10 km product, but tends to show more noise, especially in urban areas. This urban degradation is quantified using ancillary land cover data. Overall, we show that the MODIS 3 km product adds new information to the existing set of satellite derived aerosol products and validates well over the region, but due to noise and problems in urban areas, should be treated with some degree of caution.
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