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An extreme biomass-burning event occurred in Indonesia from September through October 2015 due to severe drought conditions, partially caused by a major El Nino event, thereby allowing for significant burning of peatland that had been previously drained. This event had the highest sustained aerosol optical depths (AOD) ever monitored by the global Aerosol Robotic Network (AERONET). The newly developed AERONET Version 3 algorithms retain high AOD at the longer wavelengths when associated with high Angstrom Exponents (AEs), which thereby allowed for measurements of AOD at 675 nanometers as high as approximately 7, the upper limit of Sun photometry. Measured AEs at the highest monitored AOD levels were subsequently utilized to estimate instantaneous values of AOD at 550 nanometers in the range of 11 to 13, well beyond the upper measurement limit. Additionally, retrievals of complex refractive indices, size distributions, and single scattering albedos (SSA) were obtained at much higher AOD levels than possible from almucantar scans due to the ability to perform retrievals at smaller solar zenith angles with new hybrid sky radiance scans. For retrievals made at the highest AOD levels the fine mode volume median radii were approximately 0.25 to 0.30 microns, which are very large particles for biomass burning. Very high SSA values (approximately 0.975 from 440 to 1020 nanometers) are consistent with the domination by smoldering combustion of peat burning. Estimates of the percentage peat contribution to total biomass burning aerosol based on retrieved SSA and laboratory measured peat SSA were approximately 80-85 percent, in excellent agreement with independent estimates.

This investigation examines aerosol dynamics during major fine mode aerosol transboundary pollution events in South Korea primarily during the KORUS-AQ campaign from May 1 – June 10, 2016, particularly when cloud fraction was high and/or fog was present to quantify the change in aerosol characteristics due to near-cloud or fog interaction. We analyze the new AERONET Version 3 data that have significant changes to cloud screening algorithms, allowing many more fine-mode observations in the near vicinity of clouds or fog. Case studies for detailed investigation include May 25–26, 2016 when cloud fraction was high over much of the peninsula, associated with a weak frontal passage and advection of pollution from China. These cloud-influenced Chinese transport dates also had the highest aerosol optical depth (AOD), surface PM2.5 concentrations and fine mode particle sizes of the entire campaign. Another likewise cloud/high relative humidity (RH) case is June 9 and 10, 2016 when fog was present over the Yellow Sea that appears to have affected aerosol properties well downwind over the Korean peninsula. In comparison we also investigated aerosol properties on air stagnation days with very low cloud cover and relatively low RH (May 17 & 18, 2016), when local Korean emissions dominated. Aerosol volume size distributions show marked differences between the transport days (with high RH and cloud influences) and the local pollution stagnation days, with total column-integrated particle fine mode volume being an order of magnitude greater on the pollution transport dates. The PM2.5 over central Seoul were significantly greater than for coastal sites on the transboundary transport days yet not on stagnation days, suggesting additional particle formation from gaseous urban emissions in cloud/fog droplets and/or in the high RH humidified aerosol environment. Many days had KORUS-AQ research aircraft flights that provided observations of aerosol absorption, particle chemistry and vertical profiles of extinction. AERONET retrievals and aircraft in situ measurements both showed high single scattering albedo (weak absorption) on the cloudy or cloud influenced days, plus aircraft profile in situ measurements showed large AOD enhancements (versus dried aerosol) at ambient relative humidity (RH) on the pollution transport days, consistent with the significantly larger fine mode particle radii and weak absorption.

Analysis of sun photometer measured and satellite retrieved aerosol optical depth (AOD) data has shown that major aerosol pollution events with very high fine mode AOD (>1.0 in mid-visible) in the China/Korea/Japan region are often observed to be associated with significant cloud cover. This makes remote sensing of these events difficult even for high temporal resolution sun photometer measurements. Possible physical mechanisms for these events that have high AOD include a combination of aerosol humidification, cloud processing, and meteorological co-variation with atmospheric stability and convergence. The new development of Aerosol Robotic network (AERONET) Version 3 Level 2 AOD with improved cloud screening algorithms now allow for unprecedented ability to monitor these extreme fine mode pollution events. Further, the Spectral Deconvolution Algorithm (SDA) applied to Level 1 data (L1; no cloud screening) provides an even more comprehensive assessment of fine mode AOD than L2 in current and previous data versions. Studying the 2012 winter-summer period, comparisons of AERONET L1 SDA daily average fine mode AOD data showed that Moderate Resolution Imaging Spectroradiometer (MODIS) satellite remote sensing of AOD often did not retrieve and/or identify some of the highest fine mode AOD events in this region. Also, compared to models that include data assimilation of satellite retrieved AOD, the L1 SDA fine mode AOD was significantly higher in magnitude, particularly for the highest AOD events that were often associated with significant cloudiness.

SKYNET and Aerosol Robotic Network (AERONET) retrieved aerosol single scattering albedo (SSA) values of four sites, Chiba (Japan), Pune (India), Valencia (Spain), and Seoul (Korea), were compared to understand the factors behind often noted large SSA differences between them. SKYNET and AERONET algorithms are found to produce nearly same SSAs for similarity in input data, suggesting that SSA differences between them are primarily due to quality of input data due to different calibration and/or observation protocols as well as difference in quality assurance criteria. The most plausible reason for high SSAs in SKYNET is found to be underestimated calibration constant for sky radiance (ΔΩ). The disk scan method (scan area: 1° × 1° area of solar disk) of SKYNET is noted to produce stable wavelength-dependent ΔΩ values in comparison to those determined from the integrating sphere used by AERONET to calibrate sky radiance. Aerosol optical thickness (AOT) difference between them can be the next important factor for their SSA difference, if AOTs between them are not consistent. Inconsistent values of surface albedo while analyzing data of SKYNET and AERONET can also bring SSA difference between them, but the effect of surface albedo is secondary. The aerosol nonsphericity effect is found to be less important for SSA difference between these two networks.

Single-scattering albedo (SSA) retrievals obtained with CIMEL Sun-sky radiometers from the Aerosol Robotic Network (AERONET) aerosol monitoring network were used to make comparisons with simultaneous in situ sampling from aircraft profiles carried out by the NASA Langley Aerosol Group Experiment (LARGE) team in the summer of 2011 during the coincident DRAGON-MD (Distributed Regional Aerosol Gridded Observational Network-Maryland) and DISCOVER-AQ (Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality) experiments. The single-scattering albedos (interpolated to 550 nm) derived from AERONET measurements for aerosol optical depth (AOD) at 440 nm ≥ 0.4 (mean SSA: 0.979) were on average 0.011 lower than the values derived from the LARGE profile measurements (mean SSA: 0.99). The maximum difference observed was 0.023 with all the observed differences within the combined uncertainty for the stated SSA accuracy (0.03 for AERONET; 0.02 for LARGE). Single-scattering albedo averages were also analyzed for lower aerosol loading conditions (AOD ≥ 0.2) and a dependence on aerosol optical depth was noted with significantly lower single-scattering albedos observed for lower AOD in both AERONET and LARGE data sets. Various explanations for the SSA trend were explored based on other retrieval products including volume median radius and imaginary refractive index as well as column water vapor measurements. Additionally, these SSA trends with AOD were evaluated for one of the DRAGON-MD study sites, Goddard Space Flight Center, and two other Mid-Atlantic AERONET sites over the long-term record dating to 1999.

As a representative site of the southern African biomass-burning region, sun-sky data from the 15 year Aerosol Robotic Network (AERONET) deployment at Mongu, Zambia, was analyzed. For the biomass-burning season months (July-November), we investigate seasonal trends in aerosol single scattering albedo (SSA), aerosol size distributions, and refractive indices from almucantar sky scan retrievals. The monthly mean single scattering albedo at 440 nm in Mongu was found to increase significantly from approx.. 0.84 in July to approx. 0.93 in November (from 0.78 to 0.90 at 675 nm in these same months). There was no significant change in particle size, in either the dominant accumulation or secondary coarse modes during these months, nor any significant trend in the Angstrom exponent (440-870 nm; r(exp 2) = 0.02). A significant downward seasonal trend in imaginary refractive index (r(exp 2) = 0.43) suggests a trend of decreasing black carbon content in the aerosol composition as the burning season progresses. Similarly, burning season SSA retrievals for the Etosha Pan, Namibia AERONET site also show very similar increasing single scattering albedo values and decreasing imaginary refractive index as the season progresses. Furthermore, retrievals of SSA at 388 nm from the Ozone Monitoring Instrument satellite sensor show similar seasonal trends as observed by AERONET and suggest that this seasonal shift is widespread throughout much of southern Africa. A seasonal shift in the satellite retrieval bias of aerosol optical depth from the Moderate Resolution Imaging Spectroradiometer collection 5 dark target algorithm is consistent with this seasonal SSA trend since the algorithm assumes a constant value of SSA. Multi-angle Imaging Spectroradiometer, however, appears less sensitive to the absorption-induced bias.

The AErosol RObotic NETwork (AERONET) program over the past 24 years has provided highly accurate remote sensing characterization of aerosol optical and physical properties for an increasingly extensive geographic distribution that includes all continents and many island sites. The measurements and retrievals from the AERONET global network have addressed satellite and model validation needs very well, but there have been challenges in making comparisons to similar parameters from in situ surface and airborne measurements. Additionally, with improved spatial and temporal satellite remote sensing of aerosols, there is a need for higher spatial resolution ground-based remote sensing networks. An effort to address this need resulted in a number of field campaign networks called Distributed Regional Aerosol Gridded Observation Networks (DRAGONs) that were designed to provide a database for in situ and remote sensing comparison and analysis of local to meso-scale variability of aerosol properties. This paper describes the networks that that have contributed and will continue to contribute to that body of research. The research presented in this special issue illustrates the diversity of topics that has resulted from the application of data from these networks.

We discuss accuracy of our recently developed RT code SORD using 2 benchmark scenarios published by the IPRT group in 2015. These scenarios define atmospheres with a complicate dependence of scattering and absorption properties over height (profile). Equal step, dh=1km, is assumed in the profiles. We developed subroutines that split such atmospheres into layers of the same optical thickness, dτ. We provide full text of the subroutines with comments in Appendix. The dτ is a step for vertical integration in the method of successive orders. Modification of the input profiles from “equal step over h” to “equal step over τ” changes input for RT simulations. This may cause errors at or above the acceptable level of the measurement uncertainty. We show errors of the RT code SORD for both intensity and polarization. In addition to that, using our discrete ordinates RT code IPOL, we discuss one more IPRT scenario, in which changes in height profile indeed cause unacceptable errors. Clear understanding of source and magnitude of these errors is important, e.g. for the AERONET retrieval algorithm.

The successive orders of scattering radiative transfer (RT) codes frequently call the scalar (dot) product function. In this paper, we study performance of some implementations of the dot product in the RT code SORD using 50 scenarios for light scattering in the atmosphere-surface system. In the dot product function, we use the unrolled loops technique with different unrolling factor. We also considered the intrinsic Fortran functions. We show results for two machines: ifort compiler under Windows, and pgf90 under Linux. Intrinsic DOT_PRODUCT function showed best performance for the ifort. For the pgf90, the dot product implemented with unrolling factor 4 was the fastest. The RT code SORD together with the interface that runs all the mentioned tests are publicly available from ftp://maiac.gsfc.nasa.gov/pub/skorkin/SORD_IP_16B (current release) or by email request from the corresponding (first) author.

We report a new publicly available radiative transfer (RT) code for numerical simulation of polarized light scattering in plane-parallel atmosphere of the Earth. Using 44 benchmark tests, we prove high accuracy of the new RT code, SORD (Successive ORDers of scattering). We describe capabilities of SORD and show run time for each test on two different machines. At present, SORD is supposed to work as part of the Aerosol Robotic NETwork (AERONET) inversion algorithm. For natural integration with the AERONET software, SORD is coded in Fortran 90/95. The code is available by email request from the corresponding (first) author or from ftp://climate1.gsfc.nasa.gov/skorkin/SORD/.

Dust optical properties over North Africa and the Arabian Peninsula are extracted from the quality assured multi-year datasets obtained at 14 sites of the Aerosol Robotic Network (AERONET). We select the data with (a) large aerosol optical depth (AOD ≥ 0.4 at 440 nm) and (b) small Ångström exponent (Åext ≤ 0.2) for retaining high accuracy and reducing interference of non-dust aerosols. The result indicates that the major fraction of high aerosol optical depth days are dominated by dust over these sites even though it varies depending on location and time. We have found that the annual mean and standard deviation of single scattering albedo, asymmetry parameter, real refractive index, and imaginary refractive index for Saharan and Arabian desert dust is 0.946 ± 0.005, 0.752 ± 0.014, 1.498 ± 0.032, and 0.0025 ± 0.0036 at 550 nm wavelength, respectively. Dust aerosol selected by this method is less absorbing than the previously reported values over these sites. The weaker absorption of dust from this study is consistent with the previously studies using remote sensing techniques. These results can help to constrain uncertainties in estimating global dust shortwave radiative forcing.

The proposed development is an attempt to enhance aerosol retrieval by emphasizing statistical optimization in inversion of advanced satellite observations. This optimization concept improves retrieval accuracy relying on the knowledge of measurement error distribution. Efficient application of such optimization requires pronounced data redundancy (excess of the measurements number over number of unknowns) that is not common in satellite observations. The POLDER imager on board of the PARASOL micro-satellite registers spectral polarimetric characteristics of the reflected atmospheric radiation at up to 16 viewing directions over each observed pixel. The completeness of such observations is notably higher than for most currently operating passive satellite aerosol sensors. This provides an opportunity for profound utilization of statistical optimization principles in satellite data inversion. The proposed retrieval scheme is designed as statistically optimized multi-variable fitting of the all available angular observations of total and polarized radiances obtained by POLDER sensor in the window spectral channels where absorption by gaseous is minimal. The total number of such observations by PARASOL always exceeds a hundred over each pixel and the statistical optimization concept promises to be efficient even if the algorithm retrieves several tens of aerosol parameters. Based on this idea, the proposed algorithm uses a large number of unknowns and is aimed on retrieval of extended set of parameters affecting measured radiation. The algorithm is designed to retrieve complete aerosol properties globally. Over land, the algorithm retrieves the parameters of underlying surface simultaneously with aerosol. In all situations, the approach is anticipated to achieve a robust retrieval of complete aerosol properties including information about aerosol particle sizes, shape, absorption and composition (refractive index). In order to achieve reliable retrieval from PARASOL observations even over very reflective desert surfaces, the algorithm was designed as simultaneous inversion of a large group of pixels within one or several images. Such, multi-pixel retrieval regime takes advantage from known limitations on spatial and temporal variability in both aerosol and surface properties. Specifically the variations of the retrieved parameters horizontally from pixel-to-pixel and/or temporary from day-to-day are enforced to be smooth by additional appropriately set a priori constraints. This concept is expected to provide satellite retrieval of higher consistency, because the retrieval over each single pixel will be benefiting from co-incident aerosol information from neighboring pixels, as well, from the information about surface reflectance (over land) obtained in preceding and consequent observations over the same pixel. The paper provides in depth description of the proposed inversion concept, illustrates the algorithm performance by a series of numerical tests and presents the examples of preliminary retrieval results obtained from actual PARASOL observations. It is should be noted that many aspects of the described algorithm design considerably benefited from experience accumulated in the preceding effort on developments of currently operating AERONET and PARASOL retrievals, as well as, several core software components were inherited from those earlier algorithms.

This paper presents a new method for simultaneously retrieving aerosol and surface reflectance properties from combined airborne and ground-based direct and diffuse radiometric measurements. The method is based on the standard Aerosol Robotic Network (AERONET) method for retrieving aerosol size distribution, complex index of refraction, and single scattering albedo, but modified to retrieve aerosol properties in two layers, below and above the aircraft, and parameters on surface optical properties from combined datasets (Cloud Absorption Radiometer (CAR) and AERONET data). A key advantage of this method is the inversion of all available spectral and angular data at the same time, while accounting for the influence of noise in the inversion procedure using statistical optimization. The wide spectral (0.34–2.30 μm) and angular range (180°) of the CAR instrument, combined with observations from an AERONET sunphotometer, provide sufficient measurement constraints for characterizing aerosol and surface properties with minimal assumptions. The robustness of the method was tested on observations made during four different field campaigns: (a) the Southern African Regional Science Initiative 2000 over Mongu, Zambia, (b) the Intercontinental Transport Experiment-Phase B over Mexico City, Mexico (c) Cloud and Land Surface Interaction Campaign over the Atmospheric Radiation Measurement (ARM) Central Facility, Oklahoma, USA, and (d) the Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) over Elson Lagoon in Barrow, Alaska, USA. The four areas are dominated by different surface characteristics and aerosol types, and therefore provide good test cases for the new inversion method.

Understanding aerosol effects on global climate requires knowing the global distribution of tropospheric aerosols. By accounting for aerosol sources, transports, and removal processes, chemical transport models simulate the global aerosol distribution using archived meteorological fields. We develop an algorithm for retrieving global aerosol sources from satellite observations of aerosol distribution by inverting the GOCART aerosol transport model. The inversion is based on a generalized, multi-term least-squares-type fitting, allowing flexible selection and refinement of a priori algorithm constraints. For example, limitations can be placed on retrieved quantity partial derivatives, to constrain global aerosol emission space and time variability in the results. Similarities and differences between commonly used inverse modeling and remote sensing techniques are analyzed. To retain the high space and time resolution of long-period, global observational records, the algorithm is expressed using adjoint operators. Successful global aerosol emission retrievals at 2°×2.5 resolution were obtained by inverting GOCART aerosol transport model output, assuming constant emissions over the diurnal cycle, and neglecting aerosol compositional differences. In addition, fine and coarse mode aerosol emission sources were inverted separately from MODIS fine and coarse mode aerosol optical thickness data, respectively. These assumptions are justified, based on observational coverage and accuracy limitations, producing valuable aerosol source locations and emission strengths. From two weeks of daily MODIS observations during August 2000, the global placement of fine mode aerosol sources agreed with available independent knowledge, even though the inverse method did not use any a priori information about aerosol sources, and was initialized with a "zero aerosol emission" assumption. Retrieving coarse mode aerosol emissions was less successful, mainly because MODIS aerosol data over highly reflecting desert dust sources is lacking. The broader implications of applying our approach are also discussed.

We have developed an atmospheric correction algorithm to retrieve the surface bidirectional reflectance factor (BRF) and albedo from Multiangle Imaging SpectroRadiometer (MISR) measurements for small areas around Aerosol Robotic Network (AERONET) sunphotometer sites, using AERONET aerosol and column water vapor information. Our goal is to develop an indirect validation method for MISR surface reflectance products over heterogeneous land. Our algorithm makes independent retrievals with both the Li Sparse-Ross Thick kernel BRF model and the modified Rahman-Pinty-Verstraete BRF model used in the Moderate Resolution Imaging Spectroradiometer and MISR land algorithms, respectively. In this study, we report the first results of processing MISR Collection 4 data for 2003-2004 for two sites, Mongu, Zambia, and Greenbelt, MD. We found that MISR generally provides accurate retrievals of BRF and albedo in both clear and hazy atmospheric conditions, correctly reproducing the parameter time series and spatial distribution. We found that the MISR BRF, on average, is less anisotropic in the visible bands. The difference is greatest in the blue band, but decreases with increasing wavelength such that it is negligible in the near-IR band. This discrepancy originates in part in the MISR aerosol retrieval algorithm over heterogeneous land, which tends to select an aerosol model that favors spectrally invariant shapes of surface BRF. The other part of the discrepancy comes from the surface hemispherical-directional reflectance factor retrieval algorithm where the iteration loop that removes the diffuse atmospheric transmittance is currently turned off. Our initial results suggest that the MISR surface albedo is on average lower than our retrievals by about 0.005 in the green and red bands. In the near-IR, it agreed with our retrievals with the modified Rahman-Pinty-Verstraete model for the Mongu site, but was systematically lower over the Greenbelt site by about 0.016. When significant aerosol absorption is present (Mongu), the albedo discrepancy is additionally biased by the difference between the MISR and AERONET retrievals of aerosol absorption

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 (tau) and single scattering albedo (omega (sub 0) ) from Aerosol Robotic Network (AERONET) measurements are used to form absorption [i.e., omega (sub 0) and absorption Angstrom exponent (alpha(sub abs))] and size [i.e., extinction Angstrom exponent (alpha(sub ext)) and fine mode fraction of tau] 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 average omega (sub 0) and alpha(sub abs) at each site (expanding upon previous work); (2) perform a sensitivity study on alpha(sub abs) by varying the spectral omega (sub 0); and (3) test the ability of each absorption and size relationship to distinguish aerosol types. The spectral omega (sub 0) averages indicate slightly more aerosol absorption (i.e., a 0.0 < delta omega (sub 0)

[1] 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.

High aerosol loading over the northern Indian subcontinent can result in poor air quality leading to human health consequences and climate perturbations. The international 2008 TIGERZ experiment intensive operational period (IOP) was conducted in the Indo \Gangetic Plain (IGP) around the industrial city of Kanpur (26.51degN, 80.23deg E), India, during the premonsoon (April-June). Aerosol Robotic Network (AERONET) Sun photometers performed frequent measurements of aerosol properties at temporary sites distributed within an area covering 50 sq km around Kanpur to characterize pollution and dust in a region where complex aerosol mixtures and semi \bright surface effects complicate satellite retrieval algorithms. TIGERZ IOP Sun photometers quantified aerosol optical depth (AOD) increases up to 0.10 within and downwind of the city, with urban emissions accounting for 10 C20% of the IGP aerosol loading on deployment days. TIGERZ IOP area \averaged volume size distribution and single scattering albedo retrievals indicated spatially homogeneous, uniformly sized, spectrally absorbing pollution and dust particles. Aerosol absorption and size relationships were used to categorize black carbon and dust as dominant absorbers and to identify a third category in which both black carbon and dust dominate absorption.Moderate Resolution Imaging Spectroradiometer (MODIS) AOD retrievals with the lowest quality assurance (QA > or = 0) flags were biased high with respect to TIGERZ IOP area \averaged measurements. MODIS AOD retrievals with QA 0 had moderate correlation (R(sup 2) = 0.52-69) with the Kanpur AERONET site, whereas retrievals with QA > 0 were limited in number. Mesoscale \distributed Sun photometers quantified temporal and spatial variability of aerosol properties, and these results were used to validate satellite retrievals.

An analysis of the time series of MODIS-based and AERONET aerosol records over Beijing reveals two distinct periods, before and after 2007. The MODIS data from both the Terra and Aqua satellites were processed with the new Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm. A comparison of MAIAC and AERONET AOT shows that whereas MAIAC consistently underestimated peak AOT values by 10-20% in the prior period, the bias mostly disappears after mid-2007. Independent analysis of the AERONET dataset reveals little or no change in the effective radii of the fine and coarse fractions and of the Angstrom exponent. At the same time, it shows an increasing trend in the single scattering albedo, by approx.0.02 in 9 years. As MAIAC was using the same aerosol model for the entire 2000-2010 period, the decrease in AOT bias after 2007 can be explained only by a corresponding decrease of aerosol absorption caused by a reduction in local black carbon emissions. The observed changes correlate in time with the Chinese government's broad measures to improve air quality in Beijing during preparations for the Summer Olympics of 2008.

Long-term monitoring of aerosol optical properties at a boreal forest AERONET site in interior Alaska was performed from 1994 through 2008 (excluding winter). Large interannual variability was observed, with some years showing near background aerosol optical depth (AOD) levels (

[1] During the dry season in the Western Africa region the outbreaks of biomass burning aerosols occur on a background of frequent dust storms. In the frame of the African Monsoon Multidisciplinary Analysis (AMMA) campaign we studied optical properties and radiative effects of aerosol mixture and dust observed from January to March 2006 over M'Bour, Senegal. The aerosol burden during the observing period was notably below the average of previous years. However, variability of aerosol sizes and spectral absorption were found as representative. The lidar obtained extinction profiles suggested aerosol transport in two layers (or one elevated layer) for events with two different aerosol types, called aerosol mixture in the paper. Low-altitude transport was observed for dust. The broadband solar radiative fluxes and aerosol radiative effects were analyzed by combining measurements and simulations. The simulations relied on retrieved column aerosol properties and are products of Aerosol Robotic Network data processing. The 24-h average aerosol radiative effect yielded cooling at the bottom and at the top of the atmosphere for all the analyzed events of aerosol mixture and dust. The radiative efficiency (radiative effect scaled by optical thickness) at the bottom of the atmosphere and within the aerosol layer appeared to be stronger in case of mixture than in case of pure dust due to enhanced absorption ability of former. We also evaluated the importance of accounting for dust particles nonsphericity for simulating radiative effects. Our test showed that neglecting of aerosol particle shape can result in pronounced bias, up to 10% overestimation of daily average aerosol radiative effect.

[1] A mesoscale network of 14 AERONET Sun photometers was established in the UAE and adjacent Arabian Gulf from August through September 2004 as a component of the United Arab Emirates Unified Aerosol Experiment (UAE2). These measurements allowed for spatial, temporal and spectral characterization of the complex aerosol mixtures present in this environment where coarse mode desert dust aerosols often mix with fine mode pollution aerosols largely produced by the petroleum industry. Aerosol loading was relatively high with 2-month averages of aerosol optical depth (AOD) at 500 nm (τa500) ranging from 0.40 to 0.53. A higher fine mode fraction of AOD was observed over Arabian Gulf island sites with Angstrom exponent at 440–870 nm (α440–870) of 0.77 as compared to an average of 0.64 over coastal sites and 0.50–0.57 at inland desert sites. During pollution events with α440–870 > 1 the retrieved fine mode radius was larger over an island site than a desert site probably because of hygroscopic growth over the humid marine environment. For these same pollution cases, single scattering albedo (ωo) at all wavelengths was ∼0.03 higher (less absorption) over the marine environment than over the desert, also consistent with aerosol humidification growth. At an inland desert location, the ωo at 440 nm remained relatively constant as Angstrom exponent varied since the fine mode pollution and coarse mode dust were both strong absorbers at short wavelengths. However, at longer wavelengths (675–1020 nm) the dust was much less absorbing than the pollution resulting in dynamic ωo as a function of α440–870.

[1] The AErosol RObotic NETwork (AERONET) estimates of instantaneous solar broadband fluxes (F) at surface have been validated through comparison with ground-based measurements of broadband fluxes at Mauna Loa Observatory (MLO) and by the Baseline Surface Radiation (BSRN) and the Solar Radiation Networks (SolRad-Net) during the period 1999–2005 and 1999–2006, respectively. The uncertainties in the calculated aerosol radiative forcing (ΔF) and radiative forcing efficiency (ΔFeff) at the bottom of the atmosphere were also assessed. The stations have been selected attempting to cover different aerosols influences and hence radiative properties: urban-industrial, biomass burning, mineral dust, background continental, maritime aerosols and free troposphere. The AERONET solar downward fluxes at surface agree with ground-based measurements in all situations, with a correlation higher than 99% whereas the relation of observed to modeled fluxes ranges from 0.98 to 1.02. Globally an overestimation of 9 ± 12 Wm−2 of solar measurements was found, whereas for MLO (clear atmosphere) the differences decrease noticeably up to 2 ± 10 Wm−2. The highest dispersion between AERONET estimates and measurements was observed in locations dominated by mineral dust and mixed aerosols types. In these locations, the F and ΔF uncertainties have shown a modest increase of the differences for high aerosol load, contrary to ΔFeff which are strongly affected by low aerosol load. Overall the discrepancies clustered within 9 ± 12 Wm−2 for ΔF and 28 ± 30 Wm−2 per unit of aerosol optical depth, τ, at 0.55 μm for ΔFeff, where the latter is given for τ(0.44 μm) ≥ 0.4. The error distributions have not shown any significant tendency with other aerosol radiative properties as well as size and shape particles.

The AERONET inversion products provide powerful information for understanding column integrated aerosol properties particularly given the wide global distribution of sites and the 13 year record for some sites. Significant evolution of the instrument, data quality, ancillary input data and inversion algorithm has necessitated release of Version 2.0 and establishment of criteria for quality assured products. This paper documents version 1.0 quality assurance criteria and the analysis of the entire retrieval record available for the Version 2.0 to revise the quality assured criteria. The result is an improvement in the number and quality of aerosol inversion parameters for most sites through the entire AERONET data record.