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Data assimilation of AERONET and MODIS Aerosol Optical Thickness (AOT) for aerosol forecasting was tested within the Navy Aerosol Analysis Prediction System (NAAPS) framework, using variational and ensemble data assimilation methods. Navy aerosol forecasting is currently comprised of a deterministic NAAPS simulation coupled to NAVDAS-AOD, a 2-dimensional variational data assimilation system, for MODIS AOT assimilation. An ensemble version of NAAPS (ENAAPS) coupled to an Ensemble Adjustment Kalman Filter (EAKF) from DART was recently developed, allowing for a range of data assimilation and forecasting experiments to be run with deterministic NAAPS and ENAAPS. The main findings are that the EAKF, with its flow dependent error covariances, makes better use of sparse observations such as AERONET AOT. Assimilating individual AERONET observations in the 2DVar can increase the analysis errors when observations are located in high AOT gradient regions. By including AERONET with MODIS AOT assimilation, the magnitudes of peak aerosol events (AOT > 1) were better captured with improved temporal variability, especially in India and Asia where aerosol prediction is a challenge. Assimilating AERONET AOT with MODIS had little impact on the 24-hour forecast skill compared to MODIS assimilation only, but differences were found downwind of AERONET sites. The 24-hour forecast skill was approximately the same for forecasts initialized with analyses from AERONET AOT assimilation alone compared to MODIS assimilation, particularly in regions where the AERONET network is dense; including the United States and Europe, indicating AERONET could serve as a backup observation network for over-land synoptic scale aerosol events.

As part of the Southeast United States based Studies of Emissions & Atmospheric Composition, Clouds & Climate Coupling by Regional Surveys (SEAC4RS), and collinear with part of the Southeast Atmosphere Study (SAS), the University of Wisconsin High Spectral Resolution Lidar (UW-HSRL) system was deployed to the University of Alabama from June 19th through November 4th, 2013. With a collocated Aerosol Robotic NETwork (AERONET) sun photometer, a nearby Chemical Speciation Network (PM2.5) measurement station, and near daily ozonesonde releases for the August-September SEAC4RS campaign, the site allowed the region's first comprehensive diurnal monitoring of aerosol particle vertical structure. A 532 nm lidar ratio of 55 sr provided good closure between aerosol backscatter and AERONET Aerosol Optical Thickness (AOT). A principle component analysis was performed to identify key modes of variability in aerosol backscatter. “Fair weather” days exhibited classic planetary boundary layer (PBL) structure of a mixed layer accounting for ~50% of AOT and an entrainment zone providing another 25%. An additional 5-15% of variance is gained from the lower free troposphere from either convective detrainment or frequent intrusions of Western United States biomass burning smoke. Generally aerosol particles were contained below the 0o C level, a common level of stability in convective regimes. However, occasional strong injections of smoke to the upper troposphere were also observed, accounting for the remaining 10-15% variability in AOT. Examples of these common modes of variability in frontal and convective regimes are presented, demonstrating why AOT often has only a weak relationship to surface PM2.5 concentration.

Temporal variability in the vertical distribution of aerosol optical thickness (AOT) derived from the 0.532 µm aerosol extinction coefficient is described using Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) observations over 8.5 years (June 2006 to December 2014). Temporal variability of CALIOP column-integrated AOT is largely consistent with total column AOT trends from several passive satellite sensors, such as the Moderate Resolution Imaging Spectroradiometer, Multiangle Imaging Spectroradiometer, and the Sea-viewing Wide Field-of-view Sensor. Globally, a 0.0002 AOT per year positive trend in deseasonalized CALIOP total column AOT for daytime conditions is attributed to corresponding changes in near-surface (i.e., 0.0–0.5 km or 0.5–1.0 km above ground level (agl)) aerosol particle loading, while a −0.0006 AOT per year trend during nighttime is attributed to elevated (i.e., 1.0–2.0 km or >2.0 km agl) aerosols. Regionally, increasing daytime CALIOP AOTs are found over Southern Africa and India, mostly due to changes in aerosol loading at the 1.0–2.0 km and 0.0–0.5 km agl layers, respectively. Decreasing daytime CALIOP AOTs are observed over Northern Africa, Eastern U.S., and South America (due mostly to elevated aerosol loading), while the negative CALIOP AOT trends found over Eastern China, Europe, and Western U.S. are due mostly to aerosol layers nearer the surface. To our knowledge, this study is the first to provide both a globally comprehensive estimation of the temporal variation in aerosol vertical distribution and an insight into passive sensor column AOT trends in the vertical domain.

The Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS) field mission based at Ellington Field, Texas, during August and September 2013 employed the most comprehensive airborne payload to date to investigate atmospheric composition over North America. The NASA ER-2, DC-8, and SPEC Inc. Learjet flew 57 science flights from the surface to 20 km. The ER-2 employed seven remote sensing instruments as a satellite surrogate and eight in situ instruments. The DC-8 employed 23 in situ and five remote sensing instruments for radiation, chemistry, and microphysics. The Learjet used 11 instruments to explore cloud microphysics. SEAC4RS launched numerous balloons, augmented Aerosol RObotic NETwork, and collaborated with many existing ground measurement sites. Flights investigating convection included close coordination of all three aircraft. Coordinated DC-8 and ER-2 flights investigated the optical properties of aerosols, the influence of aerosols on clouds, and the performance of new instruments for satellite measurements of clouds and aerosols. ER-2 sorties sampled stratospheric injections of water vapor and other chemicals by local and distant convection. DC-8 flights studied seasonally evolving chemistry in the Southeastern U.S., atmospheric chemistry with lower emissions of NOx and SO2 than in previous decades, isoprene chemistry under high and low NOx conditions at different locations, organic aerosols, air pollution near Houston and in petroleum fields, smoke from wildfires in western forests and from agricultural fires in the Mississippi Valley, and the ways in which the chemistry in the boundary layer and the upper troposphere were influenced by vertical transport in convective clouds.

Using two different operational Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) cloud optical depth (COD) retrievals (0.86 versus 1.6 µm), we evaluate the impact of above-cloud smoke aerosol particles on near-IR (0.86 µm) COD retrievals. Aerosol Index (AI) from the collocated Ozone Monitoring Instrument (OMI) are used to identify above-cloud aerosol particle loading over the southern Atlantic Ocean, including both smoke and dust from the African subcontinent. Collocated Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation data constrain cloud phase and provide contextual above-cloud aerosol optical depth. The frequency of occurrence of above-cloud aerosol events is depicted on a global scale for the spring and summer seasons from OMI and Cloud Aerosol Lidar with Orthogonal Polarization. Seasonal frequencies for smoke-over-cloud off the southwestern Africa coastline reach 20–50% in boreal summer. We find a corresponding low COD bias of 10–20% for standard MODIS COD retrievals when averaged OMI AI are larger than 1. No such bias is found over the Saharan dust outflow region off northern Africa, since both MODIS 0.86 and 1.6 µm channels are vulnerable to radiance attenuation due to dust particles. A similar result is found for a smaller domain, in the Gulf of Tonkin region, from smoke advection over marine stratocumulus clouds and outflow into the northern South China Sea in spring. This study shows the necessity of accounting for the above-cloud aerosol events for future studies using standard MODIS cloud products in biomass burning outflow regions, through the use of collocated OMI AI and supplementary MODIS 1.6 µm COD products.

By evaluating quality-assured Moderate Resolution Imaging Spectroradiometer (MODIS) Dark Target (DT), MODIS Deep Blue (DB), Multiangle Imaging Spectroradiometer (MISR), and Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) aerosol products assimilated into the U. S. Navy Aerosol Analysis and Prediction System (NAAPS), the impact of single-sensor and multisensor data assimilation on aerosol optical depth (AOD) analysis and forecast skill is characterized using ground-based Level 2 Aerosol Robotic Network (AERONET) data sets during the 2007 boreal summer (June–August 2007). The single-sensor assimilation experiment suggests that all products tested can improve NAAPS performance on a regional or a global scale. The multisensor assimilation experiment suggests that model improvement is greatest with the combined use of Terra and Aqua MODIS DT products, largely due to data density. Incremental improvements are identified, as a function of data density, over regions such as the Saharan desert when adding MISR and MODIS DB products. The inclusion of CALIOP data is mass-neutral by definition and has an insignificant impact on the NAAPS 00 h analysis. CALIOP assimilation does improve the 48 h forecast from NAAPS due to more accurate 00 h vertical distribution and hence forecasted advection. Root-mean-square errors exceeding 0.1 are found over East Asia and North Africa for both the NAAPS analysis and satellite AOD data, indicating that satellite aerosol products in these two regions need improvement. Similarly, low correlation is found between NAAPS and AERONET over Australia, even with the use of all available satellite aerosol products, suggesting that more detailed examination of some critical regions is necessary.

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.

[1] A band of enhanced aerosol optical depth (AOD) over the mid-to-high latitude Southern Oceans exists in some passive satellite-based aerosol data sets, including Moderate Resolution Imaging Spectroradiometer (MODIS) products. Past studies suggest several potential causes contributing to this phenomenon, including signal uncertainty, retrieval bias, and cloud contamination. In this paper, quality-assured Aqua MODIS aerosol products in this zonal band are investigated to assess cloud contamination as a cause. Spatially and temporally collocated cloud and aerosol products produced by the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) project relative to Aqua MODIS AOD in this region are considered. Maritime Aerosol Network (MAN) and Aerosol Robotic Network (AERONET) AOD data are also collocated with Aqua MODIS retrievals for surface context. The results of this study indicate that the high Aqua MODIS AOD are not seen in the CALIOP aerosol products, cannot be screened using active profiling of collocated observations for cloud presence, and are not detected by ground-based observations such as MAN and AERONET. Enhanced AOD values are attributable primarily to stratocumulus and low broken cumulus cloud contamination, as identified with CALIOP products. But these clouds explain only about 30–40% of the total anomaly. Cirrus cloud contamination is also a factor. However, in contrast to the rest of the globe, they contribute less overall, relative to low-level liquid water clouds, which are considered likely the result of misidentification of relatively warm cloud tops compared with surrounding open seas.

Model primary marine aerosol (mPMA) was produced by bubbling clean air through flowing natural seawater in a high-capacity generator deployed on ships in the eastern North Pacific and western North Atlantic Oceans. Physicochemical properties of seawater and mPMA were quantified to characterize factors that modulated production. Differences in surfactant organic matter (OM) and associated properties including surface tension sustained plumes with smaller bubble sizes, slower rise velocities, larger void fractions, and older surface ages in biologically productive relative to oligotrophic seawater. Production efficiencies for mPMA number (PEnum) and mass (PEmass) per unit air detrained from biologically productive seawater during daytime were greater and mass median diameters smaller than those in the same seawater at night and in oligotrophic seawater during day and night. PEmass decreased with increasing air detrainment rate suggesting that surface bubble rafts suppressed emission of jet droplets and associated mPMA mass. Relative to bubbles emitted at 60-cm depth, PEnum for bubbles emitted from 100-cm depth was approximately two times greater. mPMA OM enrichment factors (EFs) and mass fractions based on a coarse frit, fine frits, and a seawater jet exhibited similar size-dependent variability over a wide range in chlorophyll a concentrations. Results indicate that the physical production of PMA number and mass from the ocean surface varies systematically as interrelated functions of seawater type and, in biologically productive waters, time of day; bubble injection rate, depth, size, and surface age; and physical characteristics of the air-water interface whereas size-resolved OM EFs and mass fractions are relatively invariant.

During the Smoke, Clouds, and Radiation-Brazil (SCAR-B) project, the microphysical properties of over 1000 warm, nonprecipitating, clouds were measured from the University of Washington research aircraft. The clouds were partially embedded in the continental-scale, smoky haze that envelops much of Brazil during the biomass-burning season. For the entire data set, the most universal parameterization for the effective cloud droplet radius (r eff ) is as a function of the ratio of cloud liquid water content (LWC) to droplet concentration (essentially the volume mean radius, r v ); this agrees with previous studies under less polluted conditions. Comparisons of SCAR-B data with data from the east coast of the United States and clean oceanic areas show that the r eff -r v relationship is similar in all three cases, suggesting that even the extreme case of clouds impacted by large biomass fires can be treated similarly to more typical clouds. Beyond a certain ambient concentration of accumulation-mode particles (∼3000-4000 cm -3 ), cloud drop number concentrations for cumulus clouds in Brazil were almost constant, so that further increases in the ambient particle concentration did not change r eff , and r eff correlates well with LWC alone. For example, a cumulus cloud, which capped a particularly arge smoke plume with total particle concentrations >150,000 cm -3 , had the same r eff -LWC relationship as other clouds in the region where the ambient particle concentrations were ∼3000 cm -3 . In this study the values of r eff for cumulus clouds in Brazil affected by smoke were between 3 and 8 μm, compared to 9 to 14 μm inferred from satellite measurements of cloud reflectivity at 3.7 μm by Kaufinan and Fraser [1997].

Physical and optical characteristics of particles in smoke from 19 fires were measured in Brazil during the 1995 burning season as part of the Smoke, Clouds, and Radiation-Brazil (SCAR-B) project. The University of Washington C-131A measured particle sizes and absorption and scattering properties in very young smoke (

[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.

[1] The United Arab Emirates Unified Aerosol experiment provided a unique opportunity for testing aerosol retrieval algorithms in conditions where the optical influence of coarse mode particles was significant. Comparisons between Aerosol Robotic Network (AERONET) Sun photometry retrievals of a previously reported spectral deconvolution algorithm (SDA) and surface-based microphysical and optical measurements showed levels of correlation suggestive of moderate vertical homogeneity for (extensive) measures of fine and coarse mode aerosol particles and stronger vertical homogeneity for indicators of (intensive) aerosol type. An extension of the SDA into the short-wave infrared (SDA+) was developed in order to exploit the enhanced coarse mode information available in new AERONET instruments which include a 1.64 μm channel. Comparisons between values of coarse mode Angstrom exponent (αc (1.64 μm)) retrieved from SDA+ and effective (coarse mode) radius derived from AERONET inversions showed moderate but significant correlations. Correlations between coarse mode effective radius derived from αc (1.64 μm) and surface-based volume mean diameter estimates underscored the physical significance of the spectral retrievals and suggested moderate vertical homogeneity in terms of coarse mode particle size.