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Accurate representation of aerosol optical properties is essential for the modeling and remote sensing of atmospheric aerosols. Although aerosol optical properties are strongly dependent upon the aerosol size distribution, the use of detailed aerosol microphysics schemes in global atmospheric models is inhibited by associated computational demands. Computationally efficient parameterizations for aerosol size are needed. In this study, airborne measurements over the United States (DISCOVER-AQ) and South Korea (KORUS-AQ) are interpreted with a global chemical transport model (GEOS-Chem) to investigate the variation in aerosol size when organic matter (OM) and sulfate–nitrate–ammonium (SNA) are the dominant aerosol components. The airborne measurements exhibit a strong correlation (r=0.83) between dry aerosol size and the sum of OM and SNA mass concentration (MSNAOM). A global microphysical simulation (GEOS-Chem-TOMAS) indicates that MSNAOM and the ratio between the two components (OM/SNA) are the major indicators for SNA and OM dry aerosol size. A parameterization of the dry effective radius (Reff) for SNA and OM aerosol is designed to represent the airborne measurements (R2=0.74; slope = 1.00) and the GEOS-Chem-TOMAS simulation (R2=0.72; slope = 0.81). When applied in the GEOS-Chem high-performance model, this parameterization improves the agreement between the simulated aerosol optical depth (AOD) and the ground-measured AOD from the Aerosol Robotic Network (AERONET; R2 from 0.68 to 0.73 and slope from 0.75 to 0.96). Thus, this parameterization offers a computationally efficient method to represent aerosol size dynamically.

The NASA Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE) produced a unique dataset for research into aerosol-cloud-meteorology interactions with applications extending from process-based studies to multi-scale model intercomparison and improvement, and remote sensing algorithm assessments and advancements. ACTIVATE used two NASA Langley Research Center aircraft, a HU-25 Falcon and King Air, to conduct systematic and spatially coordinated flights over the northwest Atlantic Ocean amounting to 162 joint flights and 17 other single-aircraft flights between 2020 and 2022 across all seasons. Data cover 574 and 592 cumulative flights hours for the Falcon and King Air, respectively. The HU-25 Falcon flew conducted profiling at different level legs below, in, and just above boundary layer clouds (< 3 km) and obtained in situ measurements of trace gases, aerosol particles, clouds, and atmospheric state parameters. In cloud-free conditions, the Falcon similarly conducted profiling at different level legs within and immediately above the boundary layer. The King Air (the high-flyer) flew at approximately ~9 km conducting remote sensing with a lidar and polarimeter while also launching dropsondes. Collectively, simultaneous data collected from both aircraft help characterize the same vertical column of the atmosphere. In addition to individual instrument files, data from the Falcon aircraft are combined into “merge files” on the publicly available data archive that are created at different time resolutions of interest (e.g., 1, 5, 10, 15, 30, 60 s, or matching an individual data product start and stop times). This paper describes the ACTIVATE flight strategy, instrument and complementary dataset products, data access and usage details, and data application notes.

The 2019 Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) field experiment obtained a diverse set of in-situ and remotely-sensed measurements before and during a pyrocumulonimbus (pyroCb) event over the Williams Flats fire in Washington State. This unique dataset confirms that pyroCb activity is an efficient vertical smoke transport pathway into the upper troposphere and lower stratosphere (UTLS). The magnitude of smoke plumes observed in the UTLS has increased significantly in recent years, following unprecedented wildfire and pyroCb activity observed worldwide. The FIREX-AQ pyroCb dataset is therefore extremely relevant to a broad community, providing the first measurements of fresh smoke exhaust in the upper-troposphere, including from within active pyroCb cloud tops. High-resolution remote sensing reveals that three plume cores linked to localized fire fronts, burning primarily in dense forest fuels, contributed to four total pyroCb “pulses”. Rapid changes in fire geometry and spatial extent dramatically influenced the magnitude, behavior, and duration of pyroCb activity. Cloud probe measurements and weather radar identify the presence of large ice particles within the pyroCb and hydrometers below cloud base, indicating precipitation development. The resulting feedbacks suggest that vertical smoke transport efficiency was reduced slightly when compared with intense pyroCb events reaching the lower stratosphere. Physical and optical aerosol property measurements in pyroCb exhaust are compared with previous assumptions. A large suite of aerosol and gas-phase chemistry measurements sets a foundation for future studies aimed at understanding the composition of smoke plumes lifted by pyroconvection into the UTLS and their role in the climate system.

Atmospheric marine particle concentrations impact cloud properties, which strongly impact the amount of solar radiation reflected back into space or absorbed by the ocean surface. While satellites can provide a snapshot of current conditions at the overpass time, models are necessary to simulate temporal variations in both particle and cloud properties. However, poor model accuracy limits the reliability with which these tools can be used to predict future climate. Here, we leverage the comprehensive ocean ecosystem and atmospheric aerosol–cloud dataset obtained during the third deployment of the North Atlantic Aerosols and Marine Ecosystems Study (NAAMES3). Airborne and ship-based measurements were collected in and around a cold-air outbreak during a 3 d (where d stands for day) intensive operations period from 17–19 September 2017. Cold-air outbreaks are of keen interest for model validation because they are challenging to accurately simulate, which is due, in part, to the numerous feedbacks and sub-grid-scale processes that influence aerosol and cloud evolution. The NAAMES observations are particularly valuable because the flight plans were tailored to lie along Lagrangian trajectories, making it possible to spatiotemporally connect upwind and downwind measurements with the state-of-the-art FLEXible PARTicle (FLEXPART) Lagrangian particle dispersion model and then calculate a rate of change in particle properties. Initial aerosol conditions spanning an east–west, closed-cell-to-clear-air transition region of the cold-air outbreak indicate similar particle concentrations and properties. However, despite the similarities in the aerosol fields, the cloud properties downwind of each region evolved quite differently. One trajectory carried particles through a cold-air outbreak, resulting in a decrease in accumulation mode particle concentration (−42 %) and cloud droplet concentrations, while the other remained outside of the cold-air outbreak and experienced an increase in accumulation mode particle concentrations (+62 %). The variable meteorological conditions between these two adjacent trajectories result from differences in the local sea surface temperature in the Labrador Current and surrounding waters, altering the stability of the marine atmospheric boundary layer. Further comparisons of historical satellite observations indicate that the observed pattern occurs annually in the region, making it an ideal location for future airborne Lagrangian studies tracking the evolution of aerosols and clouds over time under cold-air outbreak conditions.

Large-eddy simulation (LES) is able to capture key boundary-layer (BL) turbulence and cloud processes. Yet, large-scale forcing and surface turbulent fluxes of sensible and latent heat are often poorly constrained for LES simulations. We derive these quantities from measurements and reanalysis obtained for two cold air outbreak (CAO) events during Phase I of the Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE) in February-March 2020. We study the two contrasting CAO cases by performing LES simulations and test the sensitivity of BL structure and clouds to large-scale forcings and turbulent heat fluxes. Profiles of atmospheric state and large-scale divergence and surface turbulent heat fluxes obtained from the reanalysis data ERA5 agree reasonably well with those derived from ACTIVATE field measurements for both cases at the sampling time and location. Therefore, we adopt the time evolving heat fluxes, wind and advective tendencies profiles from ERA5 reanalysis data to drive the LES simulations. We find that large-scale thermodynamic advective tendencies and wind relaxations are important for the LES to capture the evolving observed BL meteorological states characterized by the hourly ERA5 reanalysis data and validated by the observations. We show that the divergence (or vertical advection) is important in regulating the BL growth driven by surface heat fluxes in LES simulations. The evolution of liquid water path is largely affected by the evolution of surface heat fluxes. The liquid water path simulated in LES agrees reasonably well with the ACTIVATE measurements. This study paves the path to investigate aerosol-cloud-meteorology interactions using LES informed and evaluated by ACTIVATE field measurements.

Carbonaceous emissions from wildfires are a dynamic mixture of gases and particles that have important impacts on air quality and climate. Emissions that feed atmospheric models are estimated using burned area and fire radiative power (FRP) methods that rely on satellite products. These approaches show wide variability and have large uncertainties, and their accuracy is challenging to evaluate due to limited aircraft and ground measurements. Here, we present a novel method to estimate fire plume-integrated total carbon and speciated emission rates using a unique combination of lidar remote sensing aerosol extinction profiles and in situ measured carbon constituents. We show strong agreement between these aircraft-derived emission rates of total carbon and a detailed burned area-based inventory that distributes carbon emissions in time using Geostationary Operational Environmental Satellite FRP observations (Fuel2Fire inventory, slope = 1.33 ± 0.04, r2 = 0.93, and RMSE = 0.27). Other more commonly used inventories strongly correlate with aircraft-derived emissions but have wide-ranging over- and under-predictions. A strong correlation is found between carbon monoxide emissions estimated in situ with those derived from the TROPOspheric Monitoring Instrument (TROPOMI) for five wildfires with coincident sampling windows (slope = 0.99 ± 0.18; bias = 28.5%). Smoke emission coefficients (g MJ–1) enable direct estimations of primary gas and aerosol emissions from satellite FRP observations, and we derive these values for many compounds emitted by temperate forest fuels, including several previously unreported species.

Description, While ozone increases rapidly in wildfire plumes, downwind its production rate slows dramatically as nitrogen oxide levels decline., Wildfires are a substantial but poorly quantified source of tropospheric ozone (O3). Here, to investigate the highly variable O3 chemistry in wildfire plumes, we exploit the in situ chemical characterization of western wildfires during the FIREX-AQ flight campaign and show that O3 production can be predicted as a function of experimentally constrained OH exposure, volatile organic compound (VOC) reactivity, and the fate of peroxy radicals. The O3 chemistry exhibits rapid transition in chemical regimes. Within a few daylight hours, the O3 formation substantially slows and is largely limited by the abundance of nitrogen oxides (NOx). This finding supports previous observations that O3 formation is enhanced when VOC-rich wildfire smoke mixes into NOx-rich urban plumes, thereby deteriorating urban air quality. Last, we relate O3 chemistry to the underlying fire characteristics, enabling a more accurate representation of wildfire chemistry in atmospheric models that are used to study air quality and predict climate.

Geostationary satellite sensors over East Asia (GOCI and AHI) are now providing continuous mapping of aerosol optical depth (AOD) at 550 nm to improve monitoring of fine particulate matter (PM2.5) air quality. Here we evaluate our understanding of the physical relationships between AOD and PM2.5 over East Asia by using the GEOS-Chem atmospheric chemistry model to simulate observations from multiple sources: 1) the joint NASA-NIER Korea – United States Air Quality aircraft campaign over South Korea (KORUS-AQ; May–June 2016); 2) AODs from the AERONET ground-based network; 3) AOD from a new GOCI/AHI fused product; and 4) surface PM2.5 networks in South Korea and China. The KORUS-AQ data show that 550 nm AOD is mainly contributed by sulfate-nitrate-ammonium (SNA) and organic aerosols in the planetary boundary layer (PBL), despite large dust concentrations in the free troposphere, reflecting the optically effective size and the high hygroscopicity of the PBL aerosols. Although GEOS-Chem is successful in reproducing the KORUS-AQ vertical profiles of aerosol mass, its ability to link AOD to PM2.5 is limited by under-accounting of coarse PM and by a large overestimate of nighttime PM2.5 nitrate. A broader analysis of the GOCI/AHI AOD data over East Asia in different seasons shows agreement with AERONET AODs and a spatial distribution consistent with surface PM2.5 network data. The AOD observations over North China show a summer maximum and winter minimum, opposite in phase to surface PM2.5. This is due to low PBL depths compounded by high residential coal emissions in winter, and high relative humidity (RH) in summer. Seasonality of AOD and PM2.5 over South Korea is much weaker, reflecting weaker variation of PBL depth and lack of residential coal emissions. Physical interpretation of the satellite AOD data in terms of surface PM2.5 is sensitive to accurate information on aerosol size distributions, PBL depths, RH, the role of coarse particles, and diurnal variation of PM2.5.

A new mission involving synchronized aircraft observations is collecting data vital for improving our understanding of how aerosol particles and clouds influence each other.

Oceanic low level clouds strongly affect the atmospheric radiation budget. Uncertainties in their microphysical properties and cover currently limit the accuracy of climate predictions. Further, studies quantifying the relative importance of aerosol and dynamics on cloud properties in specific meteorological regimes are poorly constrained by observations in the Western North Atlantic boundary layer.Low level clouds were measured during the Aerosol Cloud meTereology Interactions oVer the western ATlantic Experiment (ACTIVATE) campaign in winter and summer 2020. The two NASA LaRC research aircraft HU-25 Falcon and UC-12 B-200 King Air conducted 35 simultaneous flights to investigate aerosol-cloud interactions of maritime clouds and their impact on radiation. Number concentration, liquid water content, ice water content, and particle size distribution in the size range of 3 µm to 1460 µm in diameter were measured with the fast forward scattering cloud probe (FCDP) and 2-dimensional optical array imaging probe (2D-S) onboard the Falcon. Here, we present an overview of late winter (February-March) and late summer (August-September) oceanic cloud properties in the region 65°W to 80°W and 30°N to 40°N. We compare cloud properties in these two seasons and investigate their dependence on meteorological parameters and aerosol abundance. In a case study, we present cloud observations in a cold air outbreak event on 1 March 2020 with a specific focus on mixed-phase clouds.

Wildland fires involve complicated processes that are challenging to represent in chemical transport models. Recent airborne measurements reveal remarkable chemical tomography in fresh wildland fire plumes, which remain yet to be fully explored using models. Here, we present a high-resolution large eddy simulation model coupled to chemistry to study the chemical evolution in fresh wildland fire plume. The model is configured for a large fire heavily sampled during the Fire Influence on Regional to Global Environments and Air Quality field campaign, and a variety of airborne measurements are used to evaluate the chemical heterogeneity revealed by the model. We show that the model captures the observed cross-transect variations of a number of compounds quite well, including ozone (O3), nitrous acid (HONO), and peroxyacetyl nitrate. The combined observational and modeling results suggest that the top and edges of fresh plume drive the photochemistry, while dark chemistry is also present but in the lower part of the plume. The model spatial resolution is shown to be very important as it may shift the chemical regime, leading to biases in O3 and NOx chemistry. Based on findings in this work, we speculate that the impact of small fires on air quality may be largely underestimated in models with coarse spatial resolutions.

The U.S. National Aeronautics and Space Administration in partnership with Korea’s National Institute of Environmental Research embarked on the Korea-United States Air Quality (KORUS-AQ) study to address air quality issues over the Korean peninsula. Underestimation of volatile organic compound (VOC) emissions from various large facilities on South Korea’s northwest coast may contribute to this problem, and this study focuses on quantifying top-down emissions of formaldehyde (CH2O) and VOCs from the largest of these facilities, the Daesan petrochemical complex, and comparisons with the latest emission inventories. To accomplish this and additional goals discussed herein, this study employed a number of measurements acquired during KORUS-AQ onboard the NASA DC-8 aircraft during three Daesan overflights on June 2, 3, and 5, 2016, in conjunction with a mass balance approach. The measurements included fast airborne measurements of CH2O and ethane from an infrared spectrometer, additional fast measurements from other instruments, and a suite of 33 VOC measurements acquired by the whole air sampler. The mass balance approach resulted in consistent top-down yearly Daesan VOC emission flux estimates, which averaged (61 ± 14) × 103 MT/year for the 33 VOC compounds, a factor of 2.9 ± 0.6 (±1.0) higher than the bottom-up inventory value. The top-down Daesan emission estimate for CH2O and its four primary precursors averaged a factor of 4.3 ± 1.5 (± 1.9) times higher than the bottom-up inventory value. The uncertainty values in parentheses reflect upper limits for total uncertainty estimates. The resulting averaged top-down Daesan emission estimate for sulfur dioxide (SO2) yielded a ratio of 0.81–1.0 times the bottom-up SO2 inventory, and this provides an important cross-check on the accuracy of our mass balance analysis.

Aerosol-cloud interactions are both uncertain and important in global and regional climate models, and especially in the southeast Atlantic Ocean. This uncertainty in the region is largely due to t...

WOS:000548189100001; International audience; Changes in airborne high spectral resolution lidar (HSRL) measurements of scattering, depolarization, and attenuation coincided with a shift in phytoplankton community composition across an anticyclonic eddy in the North Atlantic. We normalized the total depolarization ratio (delta) by the particulate backscattering coefficient (b(b)(p)) to account for the covariance in delta and b(b)(p) that has been attributed to multiple scattering. A 15% increase in delta/b(b)(p) inside the eddy coincided with decreased phytoplankton biomass and a shift to smaller and more elongated phytoplankton cells. Taxonomic changes (reduced dinoflagellate relative abundance inside the eddy) were also observed. The delta signal is thus potentially most sensitive to changes in phytoplankton shape because neither the observed change in the particle size distribution (PSD) nor refractive index (assuming average refractive indices) are consistent with previous theoretical modeling results. We additionally calculated chlorophyll-a (Chl) concentrations from measurements of the diffuse light attenuation coefficient (K-d) and divided by b(b)(p) to evaluate another optical metric of phytoplankton community composition (Chl:b(bp)), which decreased by more than a factor of two inside the eddy. This case study demonstrates that the HSRL is able to detect changes in phytoplankton community composition. High spectral resolution lidar measurements reveal complex structures in both the vertical and horizontal distribution of phytoplankton in the mixed layer providing a valuable new tool to support other remote sensing techniques for studying mixed layer dynamics. Our results identify fronts at the periphery of mesoscale eddies as locations of abrupt changes in near-surface optical properties.

Decades of atmospheric research have focused on the Western North Atlantic Ocean (WNAO) region because of its unique location that offers accessibility for airborne and ship measurements, gradients in important atmospheric parameters, and a range of meteorological regimes leading to diverse conditions that are poorly understood. This work reviews these scientific investigations for the WNAO region, including the East Coast of North America and the island of Bermuda. Over 50 field campaigns and long-term monitoring programs, in addition to 715 peer-reviewed publications between 1946 and 2019 have provided a firm foundation of knowledge for these areas. Of particular importance in this region has been extensive work at the island of Bermuda that is host to important time series records of oceanic and atmospheric variables. Our review categorizes WNAO atmospheric research into eight major categories, with some studies fitting into multiple categories (relative %): Aerosols (25%), Gases (24%), Development/Validation of Techniques, Models, and Retrievals (18%), Meteorology and Transport (9%), Air-Sea Interactions (8%), Clouds/Storms (8%), Atmospheric Deposition (7%), and Aerosol-Cloud Interactions (2%). Recommendations for future research are provided in the categories highlighted above.

The Korea – United States Air Quality Study (May – June 2016) deployed instrumented aircraft and ground-based measurements to elucidate causes of poor air quality related to high ozone and aerosol concentrations in South Korea. This work synthesizes data pertaining to aerosols (specifically, particulate matter with aerodynamic diameters

We report on a multiyear set of airborne field campaigns (2005–16) off the California coast to examine aerosols, clouds, and meteorology, and how lessons learned tie into the upcoming NASA Earth Venture Suborbital (EVS-3) campaign: Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE; 2019–23). The largest uncertainty in estimating global anthropogenic radiative forcing is associated with the interactions of aerosol particles with clouds, which stems from the variability of cloud systems and the multiple feedbacks that affect and hamper efforts to ascribe changes in cloud properties to aerosol perturbations. While past campaigns have been limited in flight hours and the ability to fly in and around clouds, efforts sponsored by the Office of Naval Research have resulted in 113 single aircraft flights (>500 flight hours) in a fixed region with warm marine boundary layer clouds. All flights used nearly the same payload of instruments on a Twin Otter to fly below, in, and above clouds, producing an unprecedented dataset. We provide here i) an overview of statistics of aerosol, cloud, and meteorological conditions encountered in those campaigns and ii) quantification of model-relevant metrics associated with aerosol–cloud interactions leveraging the high data volume and statistics. Based on lessons learned from those flights, we describe the pragmatic innovation in sampling strategy (dual-aircraft approach with combined in situ and remote sensing) that will be used in ACTIVATE to generate a dataset that can advance scientific understanding and improve physical parameterizations for Earth system and weather forecasting models, and for assessing next-generation remote sensing retrieval algorithms.

Polar plankton communities are among the most productive, seasonally dynamic and rapidly changing ecosystems in the global ocean. However, persistent cloud cover, periods of constant night and prevailing low solar elevations in polar regions severely limit traditional passive satellite ocean colour measurements and leave vast areas unobserved for many consecutive months each year. Consequently, our understanding of the annual cycles of polar plankton and their interannual variations is incomplete. Here we use space-borne lidar observations to overcome the limitations of historical passive sensors and report a decade of uninterrupted polar phytoplankton biomass cycles. We find that polar phytoplankton dynamics are categorized by ‘boom–bust’ cycles resulting from slight imbalances in plankton predator–prey equilibria. The observed seasonal-to-interannual variations in biomass are predicted by mathematically modelled rates of change in phytoplankton division. Furthermore, we find that changes in ice cover dominated variability in Antarctic phytoplankton stocks over the past decade, whereas ecological processes were the predominant drivers of change in the Arctic. We conclude that subtle and environmentally driven imbalances in polar food webs underlie annual phytoplankton boom–bust cycles, which vary interannually at each pole. Phytoplankton productivity is high in the polar oceans. Lidar observations from 2006–2015 reveal that phytoplankton biomass was characterized by annual cycles influenced by sea-ice extent in the Antarctic and ecological processes in the Arctic.

The ability of the Weather Research and Forecasting model with chemistry (WRF-Chem) version 3.7 and the Community Atmosphere Model version 5.3 (CAM5) in simulating profiles of aerosol properties is quantified using extensive in situ and remote sensing measurements from the Two-Column Aerosol Project (TCAP) conducted during July of 2012. TCAP was supported by the U.S. Department of Energy's Atmospheric Radiation Measurement program and was designed to obtain observations within two atmospheric columns; one fixed over Cape Cod, Massachusetts, and the other several hundred kilometers over the ocean. The performance is quantified using most of the available aircraft and surface measurements during July, and 2 days are examined in more detail to identify the processes responsible for the observed aerosol layers. The higher-resolution WRF-Chem model produced more aerosol mass in the free troposphere than the coarser-resolution CAM5 model so that the fraction of aerosol optical thickness above the residual layer from WRF-Chem was more consistent with lidar measurements. We found that the free troposphere layers are likely due to mean vertical motions associated with synoptic-scale convergence that lifts aerosols from the boundary layer. The vertical displacement and the time period associated with upward transport in the troposphere depend on the strength of the synoptic system and whether relatively high boundary layer aerosol concentrations are present where convergence occurs. While a parameterization of subgrid scale convective clouds applied in WRF-Chem modulated the concentrations of aerosols aloft, it did not significantly change the overall altitude and depth of the layers.

The multiannual global mean of aerosol optical depth at 550 nm (AOD550) over land is ∼ 0.19, and that over oceans is ∼ 0.13. About 45 % of the Earth surface shows AOD550 smaller than 0.1. There is a need for measurement techniques that are optimized to measure aerosol optical properties under low AOD conditions. We present an inherently calibrated retrieval (i.e., no need for radiance calibration) to simultaneously measure AOD and the aerosol phase function parameter, g, based on measurements of azimuth distributions of the Raman scattering probability (RSP), the near-absolute rotational Raman scattering (RRS) intensity. We employ radiative transfer model simulations to show that for solar azimuth RSP measurements at solar elevation and solar zenith angle (SZA) smaller than 80°, RSP is insensitive to the vertical distribution of aerosols and maximally sensitive to changes in AOD and g under near-molecular scattering conditions. The University of Colorado two-dimensional Multi-AXis Differential Optical Absorption Spectroscopy (CU 2-D-MAX-DOAS) instrument was deployed as part of the Two Column Aerosol Project (TCAP) at Cape Cod, MA, during the summer of 2012 to measure direct sun spectra and RSP from scattered light spectra at solar relative azimuth angles (SRAAs) between 5 and 170°. During two case study days with (1) high aerosol load (17 July, 0.3 430 430 430 and g with data from a co-located CIMEL sun photometer, Multi-Filter Rotating Shadowband Radiometer (MFRSR), and an airborne High Spectral Resolution Lidar (HSRL-2). The average difference (relative to DOAS) for AOD430 is +0.012 ± 0.023 (CIMEL), −0.012 ± 0.024 (MFRSR), −0.011 ± 0.014 (HSRL-2), and +0.023 ± 0.013 (CIMELAOD − MFRSRAOD) and yields the following expressions for correlations between different instruments: DOASAOD = −(0.019 ± 0.006) + (1.03 ± 0.02) × CIMELAOD (R2 = 0.98), DOASAOD = −(0.006 ± 0.005) + (1.08 ± 0.02) × MFRSRAOD (R2 = 0.98), and CIMELAOD = (0.013 ± 0.004) + (1.05 ± 0.01) × MFRSRAOD (R2 = 0.99). The average g measured by DOAS on both days was 0.66 ± 0.03, with a difference of 0.014 ± 0.05 compared to CIMEL. Active steps to minimize the error in the RSP help to reduce the uncertainty in retrievals of AOD and g. As AOD decreases and SZA increases, the RSP signal-to-noise ratio increases. At AOD430 ∼ 0.4 and 0.10 the absolute AOD errors are ∼ 0.014 and 0.003 at 70° SZA and 0.02 and 0.004 at 35° SZA. Inherently calibrated, precise AOD and g measurements are useful to better characterize the aerosol direct effect in urban polluted and remote pristine environments.

The oxygen collisional complex (O2–O2, or O4) is a greenhouse gas, and a calibration trace gas used to infer aerosol and cloud properties by Differential Optical Absorption Spectroscopy (DOAS). Recent reports suggest the need for an O4 correction factor (CFO4) when comparing simulated and measured O4 differential slant column densities (dSCD) by passive DOAS. We investigate the sensitivity of O4 dSCD simulations at ultraviolet (360nm) and visible (477nm) wavelengths towards separately measured aerosol extinction profiles. Measurements were conducted by the University of Colorado 2D-MAX-DOAS instrument and NASA׳s multispectral High Spectral Resolution Lidar (HSRL-2) during the Two Column Aerosol Project (TCAP) at Cape Cod, MA in July 2012. During two case study days with (1) high aerosol load (17 July, AOD~0.35 at 477nm), and (2) near molecular scattering conditions (22 July, AOD