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In this paper results are presented from a simple offline assimilation system that uses radiances from the Moderate Resolution Imaging Spectroradiometer (MODIS) channels that sense atmospheric aerosols over land and ocean. The MODIS information is directly inserted into the Goddard Chemistry and Aerosol Radiation Transport model (GOCART), which simulates the following five aerosol types: dust, sea salt, black carbon, organic carbon, and sulfate. The goal is to produce three-dimensional fields of these aerosol types for radiative forcing calculations. Products from this assimilation system are compared with ground-based measurements of aerosol optical depth (AOD) from the Aerosol Robotic Network (AERONET). Insertion of MODIS radiances draws the GOCART model closer to the AERONET AOD. However, there are still uncertainties with surface reflectivity over moderately bright surfaces and with the amount of absorbing aerosol. Also described is the assimilation cycle. The forward model takes the aerosol information from the GOCART model and calctdates radiances based on optical parameters of the aerosol type, satellite viewing angle, and the particle growth from relative humidity. Because the GOCART model is driven by previously assimilated meteorology, these forward model radiances can be directly compared with the observed MODIS level-2 radiances. The offline assimilation system simply adjusts the aerosol loading in the GOCART model so that the observed minus forward model radiances agree. Minimal change is made to the GOCART aerosol vertical distribution, size distribution, and the ratio of the five different aerosol types. The loading in the GOCART model is updated with new MODIS observations every 6 h. Since the previously assimilated meteorology provides surface wind speed, radiance sensitivity to wind speed over rough ocean is taken into account. Over land the dark target approach, also used by the MODIS-atmosphere group retrieval, is used. If the underlying land surface is deemed dark enough, the surface reflectances at the 0.47- and 0.66-[micro]m wavelengths are constant multiples of the observed 2.13-[micro]m reflectance. Over ocean the assimilation AOD compares well with AERONET. over land less so. The results herein are also compared with AERONET-retrieved single-scattering albedo. This research is part of an ongoing effort at NASA Goddard to integrate aerosols into the Goddard Modeling and Assimilation Office (GMAO) products.

Studying aerosols over ocean is one goal of the Multiangle Imaging Spectroradiometer (MISR) and other spaceborne imaging systems. But top-of-atmosphere equivalent reflectance typically falls in the range of 0.03 to 0.12 at midvisible wavelengths and can be below 0.01 in the near-infrared, when an optically thin aerosol laver is viewed over a dark ocean surface. Special attention must be given to radiometric calibration if aerosol optical thickness, and any information about particle microphysical properties, are to be reliably retrieved from such observations. MISR low-light-level vicarious calibration is performed in the vicinity of remote islands hosting Aerosol Robotic Network (AERONET) sun- and sky-scanning radiometers, under low aerosol loading, low wind speed, relatively cloud free conditions. MISR equivalent reflectance is compared with values calculated from a radiative transfer model constrained by coincident. AERONET-retrieved aerosol spectral optical thickness, size distribution, and single scattering albedo, along with in situ wind measurements. Where the nadir view is not in sun glint, MISR equivalent reflectance is also compared with Moderate Resolution Imaging Spectroradiometer (MODIS) reflectance. The authors push the limits of the vicarious calibration method's accuracy, aiming to assess absolute, camera-to-camera, and band-to-band radiometry. Patterns repeated over many well-constrained cases lend confidence to the results, at a few percent accuracy, as do additional vicarious calibration tests performed with multiplatform observations taken during the Chesapeake Lighthouse and Aircraft Measurements for Satellites (CLAMS) campaign. Conclusions are strongest in the red and green bands, but arc too uncertain to accept for the near-infrared. MISR nadir-view and MODIS low-light-level absolute reflectances differ by about 4% in the blue and green bands, with MISR reporting higher values. In the red, MISR agrees with MODIS band 14 to better than 2%, whereas MODIS band 1 is significantly lower. Compared to the AERONET-constrained model, the MISR aft-viewing cameras report reflectances too high by several percent in the blue, green, and possibly the red. Better agreement is found in the nadir- and the forward viewing cameras, especially in the blue and green. When implemented on a trial basis, calibration adjustments indicated by this work remove 40% of a 0.05 bias in retrieved midvisible aerosol optical depth over dark water scenes, produced by the early postlaunch MISR algorithm. A band-to-band correction has already been made to the MISR products, and the remaining calibration adjustments, totaling no more than a few percent, are planned.

The understanding of the uncertainties in the retrieval of the aerosol and surface properties is very important for an adequate characterization of the processes that occur in the atmosphere. However, the reliable characterization of the error budget of the retrieval products is a very challenging aspect that currently remains not fully resolved in most remote sensing approaches. The level of uncertainties for the majority of the remote sensing products relies mostly on post-processing validations and inter comparisons with other data while the dynamic errors are rarely provided. Therefore, implementations of fundamental approaches for generating dynamic retrieval errors and the evaluation of their practical efficiency remains of high importance. This study describes and analyses the dynamic estimates of uncertainties of aerosol retrieved properties by GRASP (Generalized Retrieval of Atmosphere and Surface Properties) algorithm. GRASP inversion algorithm described by Dubovik et al. (2011, 2014, 2021) is designed on the concept of statistical optimization and provides dynamic error estimates for all retrieved aerosol and surface properties. The approach takes into account the effect of both random and systematic uncertainties propagations. The algorithm provides error estimates both for directly retrieved parameters included in the retrieval state vector and for the characteristics derived from these parameters. For example, in the case of the aerosol properties, GRASP retrieves directly the size distribution and the refractive index that are used afterwards to provide phase function, scattering, extinction, single scattering albedo, etc. Moreover, GRASP algorithm provides full covariance matrices, i.e. not only variances of the retrieval errors and also correlations coefficients of these errors. The analysis of correlation matrix structure can be very useful for identifying unobvious retrieval tendencies that appear to be a useful approach for optimizing observation schemes and retrieval setups. In this study we analyse the efficiency of GRASP error estimation approach for applications to ground-based observations by sun/sky photometer and lidar. Specifically, diverse aspects of the error generations and their evaluations are discussed and illustrated. The studies rely on the series of comprehensive sensitivity tests when simulated sun/sky photometer measurements and lidar data are perturbed by random and systematic errors and inverted. Then, the results of the retrievals and their error estimations are analyzed and evaluated. The tests are conducted for different observations of diverse aerosol types including biomass burning, urban, dust and their mixtures. The study considers observations of AERONET sun/sky photometer measurements at 440, 675, 870 and 1020 nm and multi-wavelength elastic lidar measurements at 355, 532 and 1064 nm. The sun/sky photometer data are inverted alone or together with lidar data. The analysis shows overall successful error retrievals for different aerosol characteristics including aerosol size distribution, complex refractive index, single scattering albedo, lidar ratios, aerosol vertical profiles, etc. Also, the main observed tendencies in the error dynamic agree with known retrieval experience. For example, the main accuracy limitations for retrievals of all aerosol types relate to the situations with low optical depth. Also, in situations with multi-component aerosol mixtures, the reliable characterization of each component is possible only in limited situations, for example from radiometric data obtained for low solar zenith angle observations or from a combination of radiometric and lidar data. At the same time, total optical properties of aerosol mixtures are always retrieved satisfactorily. In addition, the study includes the analysis of the detailed structure of correlation matrices for the retrieval errors of mono- and multi- component aerosols. The conducted analysis of error correlation appears to be a useful approach for optimizing observations schemes and retrieval setups. The application of the approach to real data is provided. [ABSTRACT FROM AUTHOR]

Aerosol spatial distribution obtained from the satellite sensor is a critical point to understand regional aerosol environment, anthropogenic aerosol emissions, and global climate change. In this study, the performance of aerosol optical depth (AOD) retrieval from the Directional Polarimetric Camera (DPC)/GaoFen-5 by using the Generalized Retrieval of Atmosphere and Surface Properties (GRASP) algorithm was evaluated on a global basis for the first time. The results showed that the DPC GRASP/Model scheme, which used several aerosol-type mixings, achieved good performance. By compared with AERONET observations, the correlation coefficient (R), normalized mean square error, and Expect Error (EE%) were 0.8982, 0.1008, and 83.16 %, respectively. The scattering angle, number of averaged pixels in retrieval units, and radiative and polarized fitting residuals showed impacts on the results of AOD retrieval in the DPC GRASP/Model. From the most of AERONET sites, the R and EE% were larger than ~0.9 and ~80 %. Compared with MODIS products, the spatial and temporal variations of AOD could be caught by the DPC observations with the GRASP/Model, and compared with the MODIS Dark Target algorithm, the DPC GRASP/Model AOD also showed a good performance. The above findings validated the ability of DPC sensor to monitor aerosols. It would contribute to the development of aerosol parameter retrieval from multi-angular polarized sensors in the future. [ABSTRACT FROM AUTHOR]

In the Aerosol Robotic Network (AERONET) aerosol retrieval algorithm, smoothness constraints on the imaginary part of the refractive index (IPRI) provide control of retrieved spectral dependence of aerosol absorption by preventing the inversion code from fitting the noise in optical measurements and thus avoiding unrealistic oscillations of retrievals with wavelength. The history of implementation of the IPRI smoothness constraints in the AERONET aerosol retrieval algorithm is discussed. It is shown that the latest version of the IPRI smoothness constraints, termed standard (STD) and employed by Version 3 (V3) of aerosol retrieval algorithm, should be modified to account for strong variability of light absorption by brown carbon (BrC) containing aerosols in UV through mid-visible parts of the solar spectrum. In V3 strong spectral constraints were imposed at high values of the Angstrom Exponent (AE; 4 40-870 nm) since black carbon (BC) was assumed to be the primary absorber, while the constraints became increasingly relaxed as AE deceased to allow f or wavelength dependence of absorption for dust aerosols. The new version of the IPRI smoothness constraints assigns different weights to different pairs of wavelengths which are the same for all values of the Angstrom Exponent. For example, in the case of four wavelength input, the weights assigned to short wavelength pairs (440-675, 675-870 nm) are small (10-6) so that smoothness constraints do not suppress natural spectral variability of the IPRI. At longer wavelengths (870-1020 nm), however, the weight is ten times higher to provide additional constraints on the IPRI retrieval s of aerosols with high AE due to low sensitivity to aerosol absorption for longer channels at relatively low aerosol optical depths for these fine mode dominated aerosols. The effect of applying the new version of the IPRI smoothness constraints, termed relaxed (REL), on retrievals of single scattering albedo (SSA) is analysed for case studies of different aerosol types: BC and BrC containing fin e mode aerosols, mineral dust coarse mode aerosols and urban industrial fine mode aerosol. It is shown that for BrC containing aerosols employing the REL smoothness constraints resulted in significant reduction, compared to STD, in retrieved SSA and spectral residual errors at the short wavelengths. For example, biomass burning smoke cases show a reduction in SSA and spectral residual at 380 nm is ~0.033 and ~17 % respectively for the Rexburg site and ~0.04 and ~12.7 % for the Rimrock site, both AERONET sites in Idaho, USA. For a site with very high levels of BC containing aerosols (Mongu, Zambia) the effect of modification in the IPRI smoothness constraints is minor. For mineral dust aerosols at small AE values (Mezaira site, UAE) the spectral constraint on IPRI was already relaxed in V3 therefore the new REL constraint results in minimal change. In the case of weakly absorbing urban industrial aerosols at the GSFC site, there are significant changes in retrieved SSA using the REL assumption, especially reductions at longer wavelengths: ~ 0.016 and ~0.02 at 875 and 1020 nm respectively for 440 nm AOD ~0.3. Comparison of aerosol parameters retrieved by inversion using STD and REL assumptions is presented. Analysis is done for retrievals utilizing the four standard AERONET wavelengths obtained at four AERONET sites: Rexburg, Mongu, Mezaira, and GSFC. The largest difference is found for the IPRI retrievals for BrC containing biomass burning (Rexburg) and urban industrial (GSFC) aerosols in which cases employing the STD assumption in the AERONET inversion was over constraining the spectral dependence of the IPRI. The modification of smoothness constraints on the IPRI has a minor effect on retrievals of other aerosol parameters such as the real part of refractive index and parameters of the aerosol size distribution. Both SSA retrieved using STD and REL assumptions were compared to SSA derived from in situ measurements collected during the DRAGON-MD field campaign in 2011. The DISCOVER-AQ column-integrated in situ aircraft SSA data for 550 nm were compared to AERONET retrievals at 440 nm and 675 nm which were interpolated to 500 nm and showed a closer agreement between in situ SSA and SSA retrieved from inversions employing the REL assumption than between in situ SSA and SSA retrieved using STD constraints. The implementation of the relaxed smoothness constraints on the imaginary part of the refractive in the next version of the AERONET inversion algorithm will produce significant impacts at some sites with changes u p to ±0.033 and ±0.017 in short wavelength channels (380 nm and 440 nm) for some biomass burning smoke cases with significant BrC content and possibly up to ±0.015 in mid-visible channels (500 nm and 675 nm) to near IR channels (870 nm to 1020 nm) for some urban industrial aerosol types while still mostly within the uncertainty of the AERONET SSA retrievals, depending on AOD level, Angstrom Exponent and wavelength. For mineral dust aerosols the impact will be insignificant, while for biomass burning aerosol dominated by BC the changes will be relatively small. [ABSTRACT FROM AUTHOR]

Aerosol radiative forcing is a critical, though variable and uncertain, component of the global climate. Yet climate models rely on sparse information of the aerosol optical properties. In situ measurements, though important in many respects, seldom provide measurements of the undisturbed aerosol in the entire atmospheric column. Here, 8 yr of worldwide distributed data from the AERONET network of ground-based radiometers were used to remotely sense the aerosol absorption and other optical properties in several key locations. Established procedures for maintaining and calibrating the global network of radiometers, cloud screening, and inversion techniques allow for a consistent retrieval of the optical properties of aerosol in locations with varying emission sources and conditions. The multiyear, multi-instrument observations show robust differentiation in both the magnitude and spectral dependence of the absorption--a property driving aerosol climate forcing, for desert dust, biomass burning, urban-industrial, and marine aerosols. Moreover, significant variability of the absorption for the same aerosol type appearing due to different meteorological and source characteristics as well as different emission characteristics are observed. It is expected that this aerosol characterization will help refine aerosol optical models and reduce uncertainties in satellite observations of the global aerosol and in modeling aerosol impacts on climate.

Aerosol optical depth measurements over Bahrain acquired through the ground-based Aerosol Robotic Network (AERONET) are analyzed. Optical depths obtained from ground-based sun/sky radiometers showed a pronounced temporal trend, with a maximum dust aerosol loading observed during the March-July period. The aerosol optical depth probability distribution is rather narrow with a modal value of about 0.25. The Angstrom parameter frequency distribution has two peaks. One peak around 0.7 characterizes a situation when dust aerosol is more dominant, the second peak around 1.2 corresponds to relatively dust-flee cases. The correlation between aerosol optical depth and water vapor content in the total atmospheric column is strong (correlation coefficient of 0.82) when dust aerosol is almost absent (Angstrom parameter is greater than 0.7), suggesting possible hygroscopic growth of fine mode particles or source region correlation, and much weaker (correlation coefficient of 0.45) in the presence of dust (Angstrom parameter is less than 0.7). Diurnal variations of the aerosol optical depth and precipitable water were insignificant. Angstrom parameter diurnal variability (~20%-25%) is evident during the April-May period, when dust dominated the atmospheric optical conditions. Variations in the aerosol volume size distributions retrieved from spectral sun and sky radiance data are mainly associated with the changes in the concentration of the coarse aerosol fraction (variation coefficient of 61%). Geometric mean radii for the fine and coarse aerosol fractions are 0.14 [micro]m (std dev = 0.02) and 2.57 [micro]m (std dev = 0.27), respectively. The geometric standard deviation of each fraction is 0.41 and 0.73, respectively. In dust-free conditions the single scattering albedo (SSA) decreases with wavelength, while in the presence of dust the SSA either stays neutral or increases slightly with wavelength. The changes in the Angstrom parameter derived from a ground-based nephelometer and a collocated sun photometer during the initial checkout period were quite similar.

Systematic characterization of aerosol over the oceans is needed to understand the aerosol effect on climate and on transport of pollutants between continents. Reported are the results of a comprehensive optical and physical characterization of ambient aerosol in five key island locations of the Aerosol Robotic Network (AERONET) of sun and sky radiometers, spanning over 2-5 yr. The results are compared with aerosol optical depths and size distributions reported in the literature over the last 30 yr. Aerosol found over the tropical Pacific Ocean (at three sites between 20 [degrees] S and 20 [degrees] N) still resembles mostly clean background conditions dominated by maritime aerosol. The optical thickness is remarkably stable with mean value of [[tau].sub.a] (500 nm) = 0.07, mode value at [[tau].sub.am] = 0.06, and standard deviation of 0.02-0.05. The average Angstrom exponent range, from 0.3 to 0.7, characterizes the wavelength dependence of the optical thickness. Over the tropical to subtropical Atlantic (two stations at 7 [degrees] S and 32 [degrees] N) the optical thickness is significantly higher: [[tau].sub.a](500 nm) = 0.14 and [[tau].sub.am] = 0.10 due to the frequent presence of dust, smoke, and urban-industrial aerosol. For both oceans the atmospheric column aerosol is characterized by a bimodal lognormal size distribution with a fine mode at effective radius [R.sub.eff] = 0.11 [+ or -] 0.01 [micro]m and coarse mode at [R.sub.eff] = 2.1 [+ or -] 0.3 [micro]m. A review of the published 150 historical ship measurements from the last three decades shows that [[tau].sub.am] was around 0.07 to 0.12 in general agreement with the present finding. The information should be useful as a test bed for aerosol global models and aerosol representation in global climate models. With global human population expansion and industrialization, these measurements can serve in the twenty-first century as a basis to assess decadal changes in the aerosol concentration, properties, and radiative forcing of climate.