Partitioning of mineral dust, pollution, smoke, and mixtures using remote sensing techniques can help improve accuracy of satellite retrievals and assessments of the aerosol radiative impact on ...climate. Spectral aerosol optical depth (τ) and single scattering albedo (ωo) from Aerosol Robotic Network (AERONET) measurements are used to form absorption (i.e., ωo and absorption Ångström exponent (αabs)) and size (i.e., extinction Ångström exponent (αext) and fine mode fraction of τ) relationships to infer dominant aerosol types. Using the long‐term AERONET data set (1999–2010), 19 sites are grouped by aerosol type based on known source regions to (1) determine the averageωo and αabs at each site (expanding upon previous work), (2) perform a sensitivity study on αabs by varying the spectral ωo, and (3) test the ability of each absorption and size relationship to distinguish aerosol types. The spectral ωo averages indicate slightly more aerosol absorption (i.e., a 0.0 < δωo ≤ 0.02 decrease) than in previous work, and optical mixtures of pollution and smoke with dust show stronger absorption than dust alone. Frequency distributions of αabs show significant overlap among aerosol type categories, and at least 10% of the αabs retrievals in each category are below 1.0. Perturbing the spectral ωo by ±0.03 induces significant αabs changes from the unperturbed value by at least ∼±0.6 for Dust, ∼±0.2 for Mixed, and ∼±0.1 for Urban/Industrial and Biomass Burning. The ωo440nm and αext440–870nmrelationship shows the best separation among aerosol type clusters, providing a simple technique for determining aerosol type from surface‐ and future space‐based instrumentation.
Key Points
Expand upon aerosol absorption climatology at key AERONET sites
Perform a sensitivity study on the Absorption Angstrom Exponent
Examine aerosol absorption and size to determine aerosol classifications
NASA's MODIS sensors have been observing the Earth from polar orbit, from Terra since early 2000 and from Aqua since mid 2002. We have applied a consistent retrieval and processing algorithm to both ...sensors to derive the Collection 5 (C005) dark-target aerosol products over land. Here, we validate the MODIS along-orbit Level 2 products by comparing to quality assured Level 2 AERONET sunphotometer measurements at over 300 sites. From 85 463 collocations, representing mutually cloud-free conditions, we find that >66% (one standard deviation) of MODIS-retrieved aerosol optical depth (AOD) values compare to AERONET-observed values within an expected error (EE) envelope of ±(0.05 + 15%), with high correlation (R = 0.9). Thus, the MODIS AOD product is validated and quantitative. However, even though we can define EEs for MODIS-reported Ångström exponent and fine AOD over land, these products do not have similar physical validity. Although validated globally, MODIS-retrieved AOD does not fall within the EE envelope everywhere. We characterize some of the residual biases that are related to specific aerosol conditions, observation geometry, and/or surface properties, and relate them to situations where particular MODIS algorithm assumptions are violated. Both Terra's and Aqua's–retrieved AOD are similarly comparable to AERONET, however, Terra's global AOD bias changes with time, overestimating (by ~0.005) before 2004, and underestimating by similar magnitude after. This suggests how small calibration uncertainties of <2% can lead to spurious conclusions about long-term aerosol trends.
The Moderate Resolution Imaging Spectroradiometer (MODIS) aboard both NASA's Terra and Aqua satellites is making near-global daily observations of the earth in a wide spectral range (0.41-15 k m). ...These measurements are used to derive spectral aerosol optical thickness and aerosol size parameters over both land and ocean. The aerosol products available over land include aerosol optical thickness at three visible wavelengths, a measure of the fraction of aerosol optical thickness attributed to the fine mode, and several derived parameters including reflected spectral solar flux at the top of the atmosphere. Over the ocean, the aerosol optical thickness is provided in seven wavelengths from 0.47 to 2.13 k m. In addition, quantitative aerosol size information includes effective radius of the aerosol and quantitative fraction of optical thickness attributed to the fine mode. Spectral irradiance contributed by the aerosol, mass concentration, and number of cloud condensation nuclei round out the list of available aerosol products over the ocean. The spectral optical thickness and effective radius of the aerosol over the ocean are validated by comparison with two years of Aerosol Robotic Network (AERONET) data gleaned from 132 AERONET stations. Eight thousand MODIS aerosol retrievals collocated with AERONET measurements confirm that one standard deviation of MODIS optical thickness retrievals fall within the predicted uncertainty of Dt = c0.03 c0.05t over ocean and Dt = c0.05 c 0.15t over land. Two hundred and seventy-one MODIS aerosol retrievals collocated with AERONET inversions at island and coastal sites suggest that one standard deviation of MODIS effective radius retrievals falls within Dr eff = c0.11 k m. The accuracy of the MODIS retrievals suggests that the product can be used to help narrow the uncertainties associated with aerosol radiative forcing of global climate.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Aerosol mixtures composed of coarse mode desert dust combined with fine mode combustion generated aerosols (from fossil fuel and biomass burning sources) were investigated at three locations that are ...in and/or downwind of major global aerosol emission source regions. Multiyear monitoring data at Aerosol Robotic Network sites in Beijing (central eastern China), Kanpur (Indo-Gangetic Plain, northern India), and Ilorin (Nigeria, Sudanian zone of West Africa) were utilized to study the climatological characteristics of aerosol optical properties. Multiyear climatological averages of spectral single scattering albedo (SSA) versus fine mode fraction (FMF) of aerosol optical depth at 675 nm at all three sites exhibited relatively linear trends up to 50% FMF. This suggests the possibility that external linear mixing of both fine and coarse mode components (weighted by FMF) dominates the SSA variation, where the SSA of each component remains relatively constant for this range of FMF only. However, it is likely that a combination of other factors is also involved in determining the dynamics of SSA as a function of FMF, such as fine mode particles adhering to coarse mode dust. The spectral variation of the climatological averaged aerosol absorption optical depth (AAOD) was nearly linear in logarithmic coordinates over the wavelength range of 440-870 nm for both the Kanpur and Ilorin sites. However, at two sites in China (Beijing and Xianghe), a distinct nonlinearity in spectral AAOD in logarithmic space was observed, suggesting the possibility of anomalously strong absorption in coarse mode aerosols increasing the 870 nm AAOD.
Automatic globally distributed networks for monitoring aerosol optical depth provide measurements of natural and anthropogenic aerosol loading, which is important in many local and regional studies ...as well as global change research investigations. The strength of such networks relies on imposing a standardization of measurement and processing, allowing multiyear and large-scale comparisons. The development of the Aerosol Robotic Network (AERONET) for systematic ground-based sunphotometer measurements of aerosol optical depth is an essential and evolving step in this process. The growing database requires the development of a consistent, reproducible, and system-wide cloud-screening procedure. This paper discusses the methodology and justification of the cloud-screening algorithm developed for the AERONET database. The procedure has been comprehensively tested on experimental data obtained in different geographical and optical conditions. These conditions include biomass burning events in Brazil and Zambia, hazy summer conditions in the Washington DC area, clean air advected from the Canadian Arctic, and variable cloudy conditions. For various sites our screening algorithm eliminates from ∼20% to 50% of the initial data depending on cloud conditions. Certain shortcomings of the proposed procedure are discussed.
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.
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.
The recognition that the aerosol particle size distribution (PSD) is effectively bimodal permits the extraction of the fine and coarse mode optical depths (τf and τc) from the spectral shape of the ...total aerosol optical depth (τa = τf + τc). This purely optical technique avoids intermediate computations of the PSD and yields a direct optical output that is commensurate in complexity with the spectral information content of τa. The separation into τf and τc is a robust process and yields aerosol optical statistics, which are more intrinsic than those, obtained from a generic analysis of τa. Partial (optical) validation is provided by (1) demonstrating the physical coherence of the simple model employed, (2) demonstrating that τc variation is coherent with photographic evidence of thin cloud events and that τf variation is coherent with photographic evidence of clear sky and haze events, and (3) showing that the retrieved values of τf and τc are well‐correlated, if weakly biased, relative to formal inversions of combined solar extinction and sky radiance data. The spectral inversion technique permitted a closer scrutiny of a standard (temporally based) cloud‐screening algorithm. Perturbations of monthly or longer‐term statistics associated with passive or active shortcomings of operational cloud screening were inferred to be small to occasionally moderate over a sampling of cases. Diurnal illustrations were given where it was clear that such shortcomings can have a significant impact on the interpretation of specific events; (1) commission errors in τf due to the exclusion of excessively high‐frequency fine mode events and (2) omission errors in τc due to the inclusion of insufficiently high‐frequency thin homogeneous cloud events.
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.
The concept and description of a remote sensing aerosol monitoring network initiated by NASA, developed to support NASA, CNES, and NASDA’s Earth satellite systems under the name AERONET and expanded ...by national and international collaboration, is described. Recent development of weather-resistant automatic sun and sky scanning spectral radiometers enable frequent measurements of atmospheric aerosol optical properties and precipitable water at remote sites. Transmission of automatic measurements via the geostationary satellites GOES and METEOSATS’ Data Collection Systems allows reception and processing in near real-time from approximately 75% of the Earth’s surface and with the expected addition of GMS, the coverage will increase to 90% in 1998. NASA developed a UNIX-based near real-time processing, display and analysis system providing internet access to the emerging global database. Information on the system is available on the project homepage,
http://spamer.gsfc.nasa.gov. The philosophy of an open access database, centralized processing and a user-friendly graphical interface has contributed to the growth of international cooperation for ground-based aerosol monitoring and imposes a standardization for these measurements. The system’s automatic data acquisition, transmission, and processing facilitates aerosol characterization on local, regional, and global scales with applications to transport and radiation budget studies, radiative transfer-modeling and validation of satellite aerosol retrievals. This article discusses the operation and philosophy of the monitoring system, the precision and accuracy of the measuring radiometers, a brief description of the processing system, and access to the database.
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