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Here we present the first steps in developing a global multi-model aerosol forecasting ensemble intended for eventual operational and basic research use. Drawing from members of the International Cooperative for Aerosol Prediction (ICAP) latest generation of quasi-operational aerosol models, 5-day aerosol optical thickness (AOT) forecasts are analyzed for December 2011 through November 2012 from four institutions: European Centre for Medium-Range Weather Forecasts (ECMWF), Japan Meteorological Agency (JMA), NASA Goddard Space Flight Center (GSFC), and Naval Research Lab/Fleet Numerical Meteorology and Oceanography Center (NRL/FNMOC). For dust, we also include the National Oceanic and Atmospheric Administration-National Geospatial Advisory Committee (NOAA NGAC) product in our analysis. The Barcelona Supercomputing Centre and UK Met Office dust products have also recently become members of ICAP, but have insufficient data to be included in this analysis period. A simple consensus ensemble of member and mean AOT fields for modal species (e.g., fine and coarse mode, and a separate dust ensemble) is used to create the ICAP Multi-Model Ensemble (ICAP-MME). The ICAP-MME is run daily at 00:00 UTC for 6-hourly forecasts out to 120 h. Basing metrics on comparisons to 21 regionally representative Aerosol Robotic Network (AERONET) sites, all models generally captured the basic aerosol features of the globe. However, there is an overall AOT low bias among models, particularly for high AOT events. Biomass burning regions have the most diversity in seasonal average AOT. The Southern Ocean, though low in AOT, nevertheless also has high diversity. With regard to root mean square error (RMSE), as expected the ICAP-MME placed first over all models worldwide, and was typically first or second in ranking against all models at individual sites. These results are encouraging; furthermore, as more global operational aerosol models come online, we expect their inclusion in a robust operational multi-model ensemble will provide valuable aerosol forecasting guidance.

In a joint NRL/Manila Observatory mission, as part of the Seven SouthEast Asian Studies program (7-SEAS), a 2-week, late September 2011 research cruise in the northern Palawan archipelago was undertaken to observe the nature of southwest monsoonal aerosol particles in the South China Sea/East Sea (SCS/ES) and Sulu Sea region. Previous analyses suggested this region as a receptor for biomass burning from Borneo and Sumatra for boundary layer air entering the monsoonal trough. Anthropogenic pollution and biofuel emissions are also ubiquitous, as is heavy shipping traffic. Here, we provide an overview of the regional environment during the cruise, a time series of key aerosol and meteorological parameters, and their interrelationships. Overall, this cruise provides a narrative of the processes that control regional aerosol loadings and their possible feedbacks with clouds and precipitation. While 2011 was a moderate El Niño–Southern Oscillation (ENSO) La Niña year, higher burning activity and lower precipitation was more typical of neutral conditions. The large-scale aerosol environment was modulated by the Madden–Julian Oscillation (MJO) and its associated tropical cyclone (TC) activity in a manner consistent with the conceptual analysis performed by Reid et al. (2012). Advancement of the MJO from phase 3 to 6 with accompanying cyclogenesis during the cruise period strengthened flow patterns in the SCS/ES that modulated aerosol life cycle. TC inflow arms of significant convection sometimes span from Sumatra to Luzon, resulting in very low particle concentrations (minimum condensation nuclei CN < 150 cm−3, non-sea-salt PM2.5 < 1 μg m−3). However, elevated carbon monoxide levels were occasionally observed suggesting passage of polluted air masses whose aerosol particles had been rained out. Conversely, two drier periods occurred with higher aerosol particle concentrations originating from Borneo and Southern Sumatra (CN > 3000 cm−3 and non-sea-salt PM2.5 10–25 μg m−3). These cases corresponded with two different mechanisms of convection suppression: lower free-tropospheric dry-air intrusion from the Indian Ocean, and large-scale TC-induced subsidence. Veering vertical wind shear also resulted in aerosol transport into this region being mainly in the marine boundary layer (MBL), although lower free troposphere transport was possible on the western sides of Sumatra and Borneo. At the hourly time scale, particle concentrations were observed to be modulated by integer factors through convection and associated cold pools. Geostationary satellite observations suggest that convection often takes the form of squall lines, which are bowed up to 500 km across the monsoonal flow and 50 km wide. These squall lines, initiated by cold pools from large thunderstorms and likely sustained by a veering vertical wind shear and aforementioned mid-troposphere dry layers, propagated over 1500 km across the entirety of the SCS/ES, effectively cutting large swaths of MBL aerosol particles out of the region. Our conclusion is that while large-scale flow patterns are very important in modulating convection, and hence in allowing long-range transport of smoke and pollution, more short-lived phenomena can modulate cloud condensation nuclei (CCN) concentrations in the region, resulting in pockets of clean and polluted MBL air. This will no doubt complicate large scale comparisons of aerosol–cloud interaction.

Extensive measurements of black carbon (BC) aerosol were conducted in and near the North American Arctic during the Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) aircraft campaign in April and June–July 2008. We identify the pathways and mechanisms of transport of BC to the Arctic from the Asian continent using these data. The concentration, transport efficiency, and measured altitude of BC over the North American Arctic were highly dependent on season and origin of air parcels, e.g., biomass burning (BB) in Russia (Russian BB) and anthropogenic (AN) in East Asia (Asian AN). Russian BB air was mainly measured in the middle troposphere and caused maximum BC concentrations at this altitude in spring. The median BC concentration and transport efficiency of the Russian BB air were 270 ng m−3 (at STP) and 80% in spring and 20 ng m−3 and 4% in summer, respectively. Asian AN air was measured most frequently in the upper troposphere, with median values of 20 ng m−3 and 13% in spring and 5 ng m−3 and 0.8% in summer. These distinct differences are explained by differences in the transport mechanisms and accumulated precipitation along trajectories (APT), which is a measure of wet removal processes during transport. The transport of Russian BB air to the Arctic was nearly isentropic with slow ascent (low APT), while Asian AN air underwent strong uplift associated with warm conveyor belts (high APT). The APT values in summer were much larger than those in spring due to the increase in humidity in summer. These results show that the impact of BC emitted from AN sources in East Asia on the Arctic was very limited in both spring and summer. The BB emissions in Russia in spring are demonstrated to be the most important sources of BC transported to the North American Arctic.

The Weather Research and Forecasting Model (WRF) is considered a \"next generation\" mesoscale meteorology model. The inclusion of a chemistry module (WRF-Chem) allows transport simulations of chemical and aerosol species such as those observed during NASA's Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) in 2008. The ARCTAS summer deployment phase during June and July coincided with large boreal wildfires in Saskatchewan and Eastern Russia. One of the most important aspects of simulating wildfire plume transport is the height at which emissions are injected. WRF-Chem contains an integrated one-dimensional plume rise model to determine the appropriate injection layer. The plume rise model accounts for thermal buoyancy associated with fires and local atmospheric stability. This paper describes a case study of a 10 day period during the Spring phase of ARCTAS. It compares results from the plume model against those of two more traditional injection methods: Injecting within the planetary boundary layer, and in a layer 3–5 km above ground level. Fire locations are satellite derived from the GOES Wildfire Automated Biomass Burning Algorithm (WF_ABBA) and the MODIS thermal hotspot detection. Two methods for preprocessing these fire data are compared: The prep_chem_sources method included with WRF-Chem, and the Naval Research Laboratory's Fire Locating and Monitoring of Burning Emissions (FLAMBE). Results from the simulations are compared with satellite-derived products from the AIRS, MISR and CALIOP sensors. When FLAMBE provides input to the 1-D plume rise model, the resulting injection heights exhibit the best agreement with satellite-observed injection heights. The FLAMBE-derived heights are more realistic than those utilizing prep_chem_sources. Conversely, when the planetary boundary layer or the 3–5 km a.g.l. layer were filled with emissions, the resulting injection heights exhibit less agreement with observed plume heights. Results indicate that differences in injection heights produce different transport pathways. These differences are especially pronounced in area of strong vertical wind shear and when the integration period is long.

We evaluate the impact of transport from midlatitudes on aerosol number concentrations in the accumulation mode (light‐scattering particles (LSP) with diameters >180 nm) in the Arctic during the Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) campaign. We focus on transport from the Asian continent. We find marked contrasts in the number concentration (NLSP), transport efficiency (TEN_LSP, the fraction transported from sources to the Arctic), size distribution, and the chemical composition of aerosols between air parcels from anthropogenic sources in East Asia (Asian AN) and biomass burning sources in Russia and Kazakhstan (Russian BB). Asian AN air had lower NLSP and TEN_LSP (25 cm−3 and 18% in spring and 6.2 cm−3 and 3.0% in summer) than Russian BB air (280 cm−3 and 97% in spring and 36 cm−3 and 7.6% in summer) due to more efficient wet scavenging during transport from East Asia. Russian BB in this spring is the most important source of accumulation‐mode aerosols over the Arctic, and BB emissions are found to be the primary source of aerosols within all the data in spring during ARCTAS. On the other hand, the contribution of Asian AN transport had a negligible effect on the accumulation‐mode aerosol number concentration in the Arctic during ARCTAS. Compared with background air, NLSP was 2.3–4.7 times greater for Russian BB air but 2.4–2.6 times less for Asian AN air in both spring and summer. This result shows that the transport of Asian AN air decreases aerosol number concentrations in the Arctic, despite the large emissions of aerosols in East Asia. The very low aerosol number concentrations in Asian AN air were caused by wet removal during vertical transport in association with warm conveyor belts (WCBs). Therefore, this cleansing effect will be prominent for air transported via WCBs from other midlatitude regions and seasons. The inflow of clean midlatitude air can potentially have an important impact on accumulation‐mode aerosol number concentrations in the Arctic. Key Points Number and mass of LSP and BC and their TEs were highly correlated during ARCTAS Aerosols from Russian BB (Asian AN) were dominant (negligible) during ARCTAS Asian AN air has cleansing effect in terms of aerosols in the Arctic

We determine enhancement ratios for NOx, PAN, and other NOy species from boreal biomass burning using aircraft data obtained during the ARCTAS-B campaign and examine the impact of these emissions on tropospheric ozone in the Arctic. We find an initial emission factor for NOx of 1.06 g NO per kg dry matter (DM) burned, much lower than previous observations of boreal plumes, and also one third the value recommended for extratropical fires. Our analysis provides the first observational confirmation of rapid PAN formation in a boreal smoke plume, with 40% of the initial NOx emissions being converted to PAN in the first few hours after emission. We find little clear evidence for ozone formation in the boreal smoke plumes during ARCTAS-B in either aircraft or satellite observations, or in model simulations. Only a third of the smoke plumes observed by the NASA DC8 showed a correlation between ozone and CO, and ozone was depleted in the plumes as often as it was enhanced. Special observations from the Tropospheric Emission Spectrometer (TES) also show little evidence for enhanced ozone in boreal smoke plumes between 15 June and 15 July 2008. Of the 22 plumes observed by TES, only 4 showed ozone increasing within the smoke plumes, and even in those cases it was unclear that the increase was caused by fire emissions. Using the GEOS-Chem atmospheric chemistry model, we show that boreal fires during ARCTAS-B had little impact on the median ozone profile measured over Canada, and had little impact on ozone within the smoke plumes observed by TES.

NASA Cloud Aerosol Lidar with Orthogonal Polarization (CALIOP) Version 3.01 5-km nighttime 0.532 μm aerosol optical depth (AOD) datasets from 2007 are screened, averaged and evaluated at 1° × 1° resolution versus corresponding/co-incident 0.550 μm AOD derived using the US Navy Aerosol Analysis and Prediction System (NAAPS), featuring two-dimensional variational assimilation of quality-assured NASA Moderate Resolution Imaging Spectroradiometer (MODIS) and Multi-angle Imaging Spectroradiometer (MISR) AOD. In the absence of sunlight, since passive radiometric AOD retrievals rely overwhelmingly on scattered radiances, the model represents one of the few practical global estimates available from which to attempt such a validation. Daytime comparisons, though, provide useful context. Regional-mean CALIOP vertical profiles of night/day 0.532 μm extinction coefficient are compared with 0.523/0.532 μm ground-based lidar measurements to investigate representativeness and diurnal variability. In this analysis, mean nighttime CALIOP AOD are mostly lower than daytime (0.121 vs. 0.126 for all aggregated data points, and 0.099 vs. 0.102 when averaged globally per normalised 1° × 1° bin), though the relationship is reversed over land and coastal regions when the data are averaged per normalised bin (0.134/0.108 vs. 0140/0.112, respectively). Offsets assessed within single bins alone approach ±20%. CALIOP AOD, both day and night, are higher than NAAPS over land (0.137 vs. 0.124) and equal over water (0.082 vs. 0.083) when averaged globally per normalised bin. However, for all data points inclusive, NAAPS exceeds CALIOP over land, coast and ocean, both day and night. Again, differences assessed within single bins approach 50% in extreme cases. Correlation between CALIOP and NAAPS AOD is comparable during both day and night. Higher correlation is found nearest the equator, both as a function of sample size and relative signal magnitudes inherent at these latitudes. Root mean square deviation between CALIOP and NAAPS varies between 0.1 and 0.3 globally during both day/night. Averaging of CALIOP along-track AOD data points within a single NAAPS grid bin improves correlation and RMSD, though day/night and land/ocean biases persist and are believed systematic. Vertical profiles of extinction coefficient derived in the Caribbean compare well with ground-based lidar observations, though potentially anomalous selection of a priori lidar ratios for CALIOP retrievals is likely inducing some discrepancies. Mean effective aerosol layer top heights are stable between day and night, indicating consistent layer-identification diurnally, which is noteworthy considering the potential limiting effects of ambient solar noise during day.

While stand alone satellite and model aerosol products see wide utilization, there is a significant need in numerous atmospheric and climate applications for a fused product on a regular grid. Aerosol data assimilation is an operational reality at numerous centers, and like meteorological reanalyses, aerosol reanalyses will see significant use in the near future. Here we present a standardized 2003-2013 global 1 × 1° and 6-hourly modal aerosol optical thickness (AOT) reanalysis product. This data set can be applied to basic and applied Earth system science studies of significant aerosol events, aerosol impacts on numerical weather prediction, and electro-optical propagation and sensor performance, among other uses. This paper describes the science of how to develop and score an aerosol reanalysis product. This reanalysis utilizes a modified Navy Aerosol Analysis and Prediction System (NAAPS) at its core and assimilates quality controlled retrievals of AOT from the Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua and the Multi-angle Imaging SpectroRadiometer (MISR) on Terra. The aerosol source functions, including dust and smoke, were regionally tuned to obtain the best match between the model fine- and coarse-mode AOTs and the Aerosol Robotic Network (AERONET) AOTs. Other model processes, including deposition, were tuned to minimize the AOT difference between the model and satellite AOT. Aerosol wet deposition in the tropics is driven with satellite-retrieved precipitation, rather than the model field. The final reanalyzed fine- and coarse-mode AOT at 550-nm is shown to have good agreement with AERONET observations, with global mean root mean square error around 0.1 for both fine- and coarse-mode AOTs. This paper includes a discussion of issues particular to aerosol reanalyses that make them distinct from standard meteorological reanalyses, considerations for extending such a reanalysis outside of the NASA A-Train era, and examples of how the aerosol reanalysis can be applied or fused with other model or remote sensing products. Finally, the reanalysis is evaluated in comparison with other available studies of aerosol trends, and the implications of this comparison are discussed.

An ensemble-based forecast and data assimilation system has been developed for use in Navy aerosol forecasting. The system makes use of an ensemble of the Navy Aerosol Analysis Prediction System (ENAAPS) at 1 × 1°, combined with an ensemble adjustment Kalman filter from NCAR's Data Assimilation Research Testbed (DART). The base ENAAPS-DART system discussed in this work utilizes the Navy Operational Global Analysis Prediction System (NOGAPS) meteorological ensemble to drive offline NAAPS simulations coupled with the DART ensemble Kalman filter architecture to assimilate bias-corrected MODIS aerosol optical thickness (AOT) retrievals. This work outlines the optimization of the 20-member ensemble system, including consideration of meteorology and source-perturbed ensemble members as well as covariance inflation. Additional tests with 80 meteorological and source members were also performed. An important finding of this work is that an adaptive covariance inflation method, which has not been previously tested for aerosol applications, was found to perform better than a temporally and spatially constant covariance inflation. Problems were identified with the constant inflation in regions with limited observational coverage. The second major finding of this work is that combined meteorology and aerosol source ensembles are superior to either in isolation and that both are necessary to produce a robust system with sufficient spread in the ensemble members as well as realistic correlation fields for spreading observational information. The inclusion of aerosol source ensembles improves correlation fields for large aerosol source regions, such as smoke and dust in Africa, by statistically separating freshly emitted from transported aerosol species. However, the source ensembles have limited efficacy during long-range transport. Conversely, the meteorological ensemble generates sufficient spread at the synoptic scale to enable observational impact through the ensemble data assimilation. The optimized ensemble system was compared to the Navy's current operational aerosol forecasting system, which makes use of NAVDAS-AOD (NRL Atmospheric Variational Data Assimilation System for aerosol optical depth), a 2-D variational data assimilation system. Overall, the two systems had statistically insignificant differences in root-mean-squared error (RMSE), bias, and correlation relative to AERONET-observed AOT. However, the ensemble system is able to better capture sharp gradients in aerosol features compared to the 2DVar system, which has a tendency to smooth out aerosol events. Such skill is not easily observable in bulk metrics. Further, the ENAAPS-DART system will allow for new avenues of model development, such as more efficient lidar and surface station assimilation as well as adaptive source functions. At this early stage of development, the parity with the current variational system is encouraging.