Search

Accurately capturing cloud condensation nuclei (CCN) concentrations is key to understanding the aerosol–cloud interactions that continue to feature the highest uncertainty amongst numerous climate forcings. In situ CCN observations are sparse, and most non-polarimetric passive remote sensing techniques are limited to providing column-effective CCN proxies such as total aerosol optical depth (AOD). Lidar measurements, on the other hand, resolve profiles of aerosol extinction and/or backscatter coefficients that are better suited for constraining vertically resolved aerosol optical and microphysical properties. Here we present relationships between aerosol backscatter and extinction coefficients measured by the airborne High Spectral Resolution Lidar 2 (HSRL-2) and in situ measurements of CCN concentrations. The data were obtained during three deployments in the NASA ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES) project, which took place over the southeast Atlantic (SEA) during September 2016, August 2017, and September–October 2018. Our analysis of spatiotemporally collocated in situ CCN concentrations and HSRL-2 measurements indicates strong linear relationships between both data sets. The correlation is strongest for supersaturations (S) greater than 0.25 % and dry ambient conditions above the stratocumulus deck, where relative humidity (RH) is less than 50 %. We find CCN–HSRL-2 Pearson correlation coefficients between 0.95–0.97 for different parts of the seasonal burning cycle that suggest fundamental similarities in biomass burning aerosol (BBA) microphysical properties. We find that ORACLES campaign-average values of in situ CCN and in situ extinction coefficients are qualitatively similar to those from other regions and aerosol types, demonstrating overall representativeness of our data set. We compute CCN–backscatter and CCN–extinction regressions that can be used to resolve vertical CCN concentrations across entire above-cloud lidar curtains. These lidar-derived CCN concentrations can be used to evaluate model performance, which we illustrate using an example CCN concentration curtain from the Weather Research and Forecasting Model coupled with physics packages from the Community Atmosphere Model version 5 (WRF-CAM5). These results demonstrate the utility of deriving vertically resolved CCN concentrations from lidar observations to expand the spatiotemporal coverage of limited or unavailable in situ observations.

The southeastern Atlantic is home to an expansive smoke aerosol plume overlying a large cloud deck for approximately a third of the year. The aerosol plume is mainly attributed to the extensive biomass burning activities that occur in southern Africa. Current Earth system models (ESMs) reveal significant differences in their estimates of regional aerosol radiative effects over this region. Such large differences partially stem from uncertainties in the vertical distribution of aerosols in the troposphere. These uncertainties translate into different aerosol optical depths (AODs) in the planetary boundary layer (PBL) and the free troposphere (FT). This study examines differences of AOD fraction in the FT and AOD differences among ESMs (WRF-CAM5, WRF-FINN, GEOS-Chem, EAM-E3SM, ALADIN, GEOS-FP, and MERRA-2) and aircraft-based measurements from the NASA ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES) field campaign. Models frequently define the PBL as the well-mixed surface-based layer, but this definition misses the upper parts of decoupled PBLs, in which most low-level clouds occur. To account for the presence of decoupled boundary layers in the models, the height of maximum vertical gradient of specific humidity profiles from each model is used to define PBL heights. Results indicate that the monthly mean contribution of AOD in the FT to the total-column AOD ranges from 44 % to 74 % in September 2016 and from 54 % to 71 % in August 2017 within the region bounded by 25∘ S–0∘ N–S and 15∘ W–15∘ E (excluding land) among the ESMs. ALADIN and GEOS-Chem show similar aerosol plume patterns to a derived above-cloud aerosol product from the Moderate Resolution Imaging Spectroradiometer (MODIS) during September 2016, but none of the models show a similar above-cloud plume pattern to MODIS in August 2017. Using the second-generation High Spectral Resolution Lidar (HSRL-2) to derive an aircraft-based constraint on the AOD and the fractional AOD, we found that WRF-CAM5 produces 40 % less AOD than those from the HSRL-2 measurements, but it performs well at separating AOD fraction between the FT and the PBL. AOD fractions in the FT for GEOS-Chem and EAM-E3SM are, respectively, 10 % and 15 % lower than the AOD fractions from the HSRL-2. Their similar mean AODs reflect a cancellation of high and low AOD biases. Compared with aircraft-based observations, GEOS-FP, MERRA-2, and ALADIN produce 24 %–36 % less AOD and tend to misplace more aerosols in the PBL. The models generally underestimate AODs for measured AODs that are above 0.8, indicating their limitations at reproducing high AODs. The differences in the absolute AOD, FT AOD, and the vertical apportioning of AOD in different models highlight the need to continue improving the accuracy of modeled AOD distributions. These differences affect the sign and magnitude of the net aerosol radiative forcing, especially when aerosols are in contact with clouds.

The southeast Atlantic is home to an expansive smoke aerosol plume overlying a large cloud deck for approximately a third of the year. The aerosol plume is mainly attributed to the extensive biomass burning activity that occurs in southern Africa. Current Earth system models (ESMs) reveal significant differences in their estimates of regional aerosol radiative effects over this region. Such large differences partially stem from uncertainties in the vertical distribution of aerosols in the troposphere. These uncertainties translate into different aerosol optical depths (AOD) in the planetary boundary layer (PBL) and the free troposphere (FT). This study examines differences of AOD fraction in the FT and AOD differences among ESMs (WRF-CAM5, WRF-FINN, GEOS-Chem, EAM-E3SM, ALADIN, GEOS-FP, and MERRA-2) and aircraft-based measurements from the NASA ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES) field campaign. Models frequently define the PBL as the well-mixed surface-based layer, but this definition misses the upper parts of decoupled PBLs, in which most low-level clouds occur. To account for the presence of decoupled boundary layers in the models, the height of maximum vertical gradient of specific humidity profiles from each model is used to define PBL heights. Results indicate that the monthly mean contribution of AOD in the FT to the total-column AOD ranges from 44 % to 74 % in September 2016 and from 54 % to 71 % in August 2017 within the region bounded by 25°S–0° and 15°W–15°E (excluding land) among the ESMs. Using the second-generation High Spectral Resolution Lidar (HSRL-2) to derive an aircraft-based constraint on the AOD and the fractional AOD, we found that WRF-CAM5 produces 40 % less AOD than those from the HSRL-2 measurements, but it performs well at separating AOD fraction between the FT and the PBL. AOD fractions in the FT for GEOS-Chem and EAM-E3SM are, respectively, 10 % and 15 % lower than the AOD fractions from the HSRL-2 and their similarities in the mean AODs are the result of cancellation of high and low AOD biases. GEOS-FP, MERRA-2, and ALADIN produce 24 %–36 % less AOD and tend to misplace more aerosols in the PBL compared to aircraft-based observations. The models generally underestimate AODs for measured AODs that are above 0.8, indicating their limitations at reproducing high AODs. The differences in the absolute AOD, FT AOD, and the vertical apportioning of AOD in different models highlight the need to continue improving the accuracy of modeled AOD distributions. These differences affect the sign and magnitude of the net aerosol radiative forcing, especially when aerosols are in contact with clouds.

Data are presented from intercomparisons between two research aircraft, the FAAM BAe-146 and the NASA Lockheed P3, and between the BAe-146 and the surface-based DOE (Department of Energy) ARM (Atmospheric Radiation Measurement) Mobile Facility at Ascension Island (8∘ S, 14.5∘ W; a remote island in the mid-Atlantic). These took place from 17 August to 5 September 2017, during the African biomass burning (BB) season. The primary motivation was to give confidence in the use of data from multiple platforms with which to evaluate numerical climate models. The three platforms were involved in the CLouds–Aerosol–Radiation Interaction and Forcing for Year 2017 (CLARIFY-2017), ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES), and Layered Atlantic Smoke and Interactions with Clouds (LASIC) field experiments. Comparisons from flight segments on 6 d where the BAe-146 flew alongside the ARM facility on Ascension Island are presented, along with comparisons from the wing-tip-to-wing-tip flight of the P3 and BAe-146 on 18 August 2017. The intercomparison flight sampled a relatively clean atmosphere overlying a moderately polluted boundary layer, while the six fly-bys of the ARM site sampled both clean and polluted conditions 2–4 km upwind. We compare and validate characterisations of aerosol physical, chemical and optical properties as well as atmospheric radiation and cloud microphysics between platforms. We assess the performance of measurement instrumentation in the field, under conditions where sampling conditions are not as tightly controlled as in laboratory measurements where calibrations are performed. Solar radiation measurements compared well enough to permit radiative closure studies. Optical absorption coefficient measurements from all three platforms were within uncertainty limits, although absolute magnitudes were too low ( Mm−1) to fully support a comparison of the absorption Ångström exponents. Aerosol optical absorption measurements from airborne platforms were more comparable than aircraft-to-ground observations. Scattering coefficient observations compared adequately between airborne platforms, but agreement with ground-based measurements was worse, potentially caused by small differences in sampling conditions or actual aerosol population differences over land. Chemical composition measurements followed a similar pattern, with better comparisons between the airborne platforms. Thermodynamics, aerosol and cloud microphysical properties generally agreed given uncertainties.

Aerosol heating due to shortwave absorption has implications for local atmospheric stability and regional dynamics. The derivation of heating rate profiles from space-based observations is challenging because it requires the vertical profile of relevant properties such as the aerosol extinction coefficient and single scattering albedo (SSA). In the southeast Atlantic, this challenge is amplified by the presence of stratocumulus clouds below the biomass burning plume advected from Africa, since the cloud properties affect the magnitude of the aerosol heating aloft, which may in turn lead to changes in the cloud properties and life cycle. The combination of spaceborne lidar data with passive imagers shows promise for future derivations of heating rate profiles and curtains, but new algorithms require careful testing with data from aircraft experiments where measurements of radiation, aerosol and cloud parameters are better collocated and readily available. In this study, we derive heating rate profiles and curtains from aircraft measurements during the NASA ObseRvations of CLouds above Aerosols and their intEractionS (ORACLES) project in the southeastern Atlantic. Spectrally resolved irradiance measurements and the derived column absorption allow for the separation of total heating rates into aerosol and gas (primarily water vapor) absorption. The nine cases we analyzed capture some of the co-variability of heating rate profiles and their primary drivers, leading to the development of a new concept: The Heating Rate Efficiency (HRE; the heating rate per unit aerosol extinction). The HRE, which accounts for the overall aerosol loading as well as vertical distribution of the aerosol layer, varies little with altitude as opposed to the standard heating rate. The large case-to-case variability for ORACLES is significantly reduced after converting from heating rate to HRE, allowing us to quantify its dependence on SSA, cloud albedo, and solar zenith angle.

Biomass burning smoke is advected over the southeast Atlantic Ocean between July and October of each year. This smoke plume overlies and mixes into a region of persistent low marine clouds. Model calculations of climate forcing by this plume vary significantly, in both magnitude and sign. The NASA EVS-2 (Earth Venture Suborbital-2) ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) project deployed for field campaigns off the west coast of Africa in three consecutive years (Sept., 2016; Aug., 2017; and Oct., 2018) with the goal of better characterizing this plume as a function of the monthly evolution, by measuring the parameters necessary to calculate the direct aerosol radiative effect. Here, this dataset and satellite retrievals of cloud properties are used to test the representation of the smoke plume and the underlying cloud layer in two regional models (WRF-CAM5 and CNRM-ALADIN) and two global models (GEOS and UM-UKCA). The focus is on comparisons of those aerosol and cloud properties that are the primary determinants of the direct aerosol radiative effect, and on the vertical distribution of the plume and its properties. The representativeness of the observations to monthly averages are tested for each field campaign, with the sampled mean aerosol light extinction generally found to be within 20 % of the monthly mean at plume altitudes. When compared to the observations, in all models the simulated plume is too vertically diffuse, has smaller vertical gradients, and, in two of the models (GEOS and UM-UKCA), the plume core is displaced lower than in the observations. Plume carbon monoxide, black carbon, and organic aerosol masses indicate under-estimates in modeled plume concentrations, leading in general to under-estimates in mid-visible aerosol extinction and optical depth. Biases in mid-visible single scatter albedo are both positive and negative across the models. Observed vertical gradients in single scatter albedo are not captured by the models, but the models do capture the coarse temporal evolution, correctly simulating higher values in October (2018) than in August (2018) and September (2017). Uncertainties in the measured absorption Ångstrom exponent were large but propagate into a negligible (

In southern Africa, widespread agricultural fires produce substantial biomass burning (BB) emissions over the region. The seasonal smoke plumes associated with these emissions are then advected westward over the persistent stratocumulus cloud deck in the Southeast Atlantic (SEA) Ocean, resulting in aerosol effects which vary with time and location. Much work has focused on the effects of these aerosol plumes, but previous studies have also described an elevated free-tropospheric water vapor signal over the SEA. Water vapor influences climate in its own right, and it is especially important to consider atmospheric water vapor when quantifying aerosol-cloud interactions and aerosol radiative effects. Here we present airborne observations made during the NASA ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) campaign over the SEA Ocean. In observations collected from multiple independent instruments on the NASA P-3 aircraft (from near-surface to 6–7 km), we observe a strongly linear correlation between pollution indicators (carbon monoxide (CO) and aerosol loading) and atmospheric water vapor content, seen at all altitudes above the boundary layer. The focus of the current study is on the especially strong correlation observed during the ORACLES-2016 deployment (out of Walvis Bay, Namibia), but a similar relationship is also observed in the August 2017 and October 2018 ORACLES deployments. Using ECMWF and MERRA-2 reanalyses and specialized WRF-Chem simulations, we trace the plume-vapor relationship to an initial humid, smoky continental source region, where it is subjected to conditions of strong westward advection, namely the South African Easterly Jet (AEJ-S). Our analysis indicates that airmasses likely left the continent with the same relationship between water vapor and carbon monoxide as was observed by aircraft. This linear relationship developed over the continent due to daytime convection within a deep continental boundary layer (up to 5–6 km) which produced fairly consistent vertical gradients in CO and water vapor, decreasing with altitude and varying in time, but does not originate as a product of the BB combustion itself. Due to a combination of conditions and mixing between the smoky, moist continental boundary layer and the dry and fairly clean upper-troposphere air above (~6 km), the smoky, humid air is transported by strong zonal winds and then advected over the SEA (to the ORACLES flight region) following largely isentropic trajectories. HYSPLIT back trajectories support this interpretation. Better understanding of the conditions and processes which cause the water vapor to covary with plume strength is important to accurately quantify direct, semi-direct, and indirect aerosol effects in this region.

Global measurements of absorbing aerosol optical depth (AAOD) are scarce and mostly provided by the ground network AERONET (AErosol RObotic NETwork). In recent years, several satellite products of AAOD have been developed. This study's primary aim is to establish the usefulness of these datasets for AEROCOM (Aerosol Comparisons between Observations and Models) model evaluation with a focus on the years 2006, 2008 and 2010. The satellite products are super-observations consisting of 1∘×1∘×30 min aggregated retrievals. This study consists of two papers, the current one that deals with the assessment of satellite observations and a second paper (Schutgens et al., 2021) that deals with the evaluation of models using those satellite data. In particular, the current paper details an evaluation with AERONET observations from the sparse AERONET network as well as a global intercomparison of satellite datasets, with a focus on how minimum AOD (aerosol optical depth) thresholds and temporal averaging may improve agreement between satellite observations. All satellite datasets are shown to have reasonable skill for AAOD (three out of four datasets show correlations with AERONET in excess of 0.6) but less skill for SSA (single-scattering albedo; only one out of four datasets shows correlations with AERONET in excess of 0.6). In comparison, satellite AOD shows correlations from 0.72 to 0.88 against the same AERONET dataset. However, we show that performance vs. AERONET and inter-satellite agreements for SSA improve significantly at higher AOD. Temporal averaging also improves agreements between satellite datasets. Nevertheless multi-annual averages still show systematic differences, even at high AOD. In particular, we show that two POLDER (Polarization and Directionality of the Earth's Reflectances) products appear to have a systematic SSA difference over land of ∼0.04, independent of AOD. Identifying the cause of this bias offers the possibility of substantially improving current datasets. We also provide evidence that suggests that evaluation with AERONET observations leads to an underestimate of true biases in satellite SSA. In the second part of this study we show that, notwithstanding these biases in satellite AAOD and SSA, the datasets allow meaningful evaluation of AEROCOM models.

Global measurements of absorptive aerosol optical depth (AAOD) are scarce and mostly provided by the ground network AERONET (AErosol RObotic NETwork). In recent years, several satellite products of AAOD have appeared. This study's primary aim is to establish the usefulness of these datasets for AEROCOM (AEROsol Comparisons between Observations and Models) model evaluation with a focus on the years 2006, 2008 and 2010. The satellite products are super-observations consisting of 1° × 1° × 30min aggregated retrievals. This study consist of two parts: 1) an assessment of satellite datasets; 2) their application to the evaluation of AEROCOM models. The current paper describes the first part and details an evaluation with AERONET observations from the sparse AERONET network as well as a global intercomparison of satellite datasets, with a focus on how minimum AOD (Aerosol Optical Depth) thresholds and temporal averaging may improve agreement. All satellite datasets are shown to have reasonable skill for AAOD (3 out of 4 datasets show correlations with AERONET in excess of 0.6) but less skill for SSA (Single Scattering Albedo; only 1 out of 4 datasets shows correlations with AERONET in excess of 0.6). In comparison, satellite AOD shows correlations from 0.72 to 0.88 against the same AERONET dataset. We do show that performance vs. AERONET and satellite agreements for SSA significantly improve at higher AOD. Temporal averaging also improves agreements between satellite datasets. Nevertheless multi-annual averages still show systematic differences, even at high AOD. In particular, we show that two POLDER products appear to have a systematic SSA difference over land of about 0.04, independent of AOD. Identifying the cause of this bias offers the possibility of substantially improving current datasets. We also provide evidence that suggests that evaluation with AERONET observations leads to an underestimate of true biases in satellite SSA. In the second part of this study we show that, notwithstanding these biases in satellite AAOD and SSA, the datasets allow meaningful evaluation of AEROCOM models.

This work establishes an observationally-driven link from mid-visible aerosol optical depth (AOD) and other scene parameters to broadband shortwave irradiance (and by extension, the direct aerosol radiative effect, DARE), based on observations from the 2016 and 2017 field campaigns of ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS). Specifically, this is done by two parameterizations, one spanned by the mid-visible AOD and scene albedo below the aerosol layer, and another one with a third input, the mid-visible aerosol single scattering albedo (SSA). These parameterizations build on the earlier concept of radiative forcing efficiency, which describes the dependence of DARE on the AOD, and extend it to make the dependence on the other two scene parameters explicit. The parameterizations are founded on 9 cases from the campaigns, for which we retrieve the spectral aerosol properties of SSA and asymmetry parameter (g) directly from the radiative fluxes, based on the method presented in Cochrane et al. (2019). These properties are used as the basis of the parameterizations, capturing the natural variability of the study region as sampled. The majority of the case-to-case variability within the ORACLES DARE dataset is attributable to the dependence on AOD and scene albedo. This is captured by the first parameterization, which is advantageous when satellite retrievals provide only limited information such as AOD and scene albedo. However, the second parameterization explains even more of the case-to-case variability by introducing the mid-visible SSA as third parameter. For both parameterizations, we provide the necessary coefficients, uncertainties, and code required for the user to reconstruct the parameterization for their use.

The National Aeronautics and Space Administration (NASA)’s Arctic Radiation-IceBridge Sea and Ice Experiment (ARISE) acquired unique aircraft data on atmospheric radiation and sea ice properties during the critical late summer to autumn sea ice minimum and commencement of refreezing. The C-130 aircraft flew 15 missions over the Beaufort Sea between 4 and 24 September 2014. ARISE deployed a shortwave and longwave broadband radiometer (BBR) system from the Naval Research Laboratory; a Solar Spectral Flux Radiometer (SSFR) from the University of Colorado Boulder; the Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research (4STAR) from the NASA Ames Research Center; cloud microprobes from the NASA Langley Research Center; and the Land, Vegetation and Ice Sensor (LVIS) laser altimeter system from the NASA Goddard Space Flight Center. These instruments sampled the radiant energy exchange between clouds and a variety of sea ice scenarios, including prior to and after refreezing began. The most critical and unique aspect of ARISE mission planning was to coordinate the flight tracks with NASA Cloud and the Earth’s Radiant Energy System (CERES) satellite sensor observations in such a way that satellite sensor angular dependence models and derived top-of-atmosphere fluxes could be validated against the aircraft data over large gridbox domains of order 100–200 km. This was accomplished over open ocean, over the marginal ice zone (MIZ), and over a region of heavy sea ice concentration, in cloudy and clear skies. ARISE data will be valuable to the community for providing better interpretation of satellite energy budget measurements in the Arctic and for process studies involving ice–cloud–atmosphere energy exchange during the sea ice transition period.

We present the validation analysis of above-cloud aerosol optical depth (ACAOD) retrieved from the “color ratio” method applied to MODIS cloudy-sky reflectance measurements using the limited direct measurements made by NASA's airborne Ames Airborne Tracking Sunphotometer (AATS) and Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research (4STAR) sensors. A thorough search of the airborne database collection revealed a total of five significant events in which an airborne sun photometer, coincident with the MODIS overpass, observed partially absorbing aerosols emitted from agricultural biomass burning, dust, and wildfires over a low-level cloud deck during SAFARI-2000, ACE-ASIA 2001, and SEAC4RS 2013 campaigns, respectively. The co-located satellite-airborne matchups revealed a good agreement (root-mean-square difference

Cases of absorbing aerosols above clouds (AACs), such as smoke or mineral dust, are omitted from most routinely processed space-based aerosol optical depth (AOD) data products, including those from the Moderate Resolution Imaging Spectroradiometer (MODIS). This study presents a sensitivity analysis and preliminary algorithm to retrieve above-cloud AOD and liquid cloud optical depth (COD) for AAC cases from MODIS or similar sensors, for incorporation into a future version of the "Deep Blue" AOD data product. Detailed retrieval simulations suggest that these sensors should be able to determine AAC AOD with a typical level of uncertainty approximately 25-50 percent (with lower uncertainties for more strongly absorbing aerosol types) and COD with an uncertainty approximately10-20 percent, if an appropriate aerosol optical model is known beforehand. Errors are larger, particularly if the aerosols are only weakly absorbing, if the aerosol optical properties are not known, and the appropriate model to use must also be retrieved. Actual retrieval errors are also compared to uncertainty envelopes obtained through the optimal estimation (OE) technique; OE-based uncertainties are found to be generally reasonable for COD but larger than actual retrieval errors for AOD, due in part to difficulties in quantifying the degree of spectral correlation of forward model error. The algorithm is also applied to two MODIS scenes (one smoke and one dust) for which near-coincident NASA Ames Airborne Tracking Sun photometer (AATS) data were available to use as a ground truth AOD data source, and found to be in good agreement, demonstrating the validity of the technique with real observations.

The Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), updates NASA’s previous satellite-era (1980 onward) reanalysis system to include additional observations and improvements to the Goddard Earth Observing System, version 5 (GEOS-5), Earth system model. As a major step toward a full Integrated Earth Systems Analysis (IESA), in addition to meteorological observations, MERRA-2 now includes assimilation of aerosol optical depth (AOD) from various ground- and space-based remote sensing platforms. Here, in the first of a pair of studies, the MERRA-2 aerosol assimilation is documented, including a description of the prognostic model (GEOS-5 coupled to the GOCART aerosol module), aerosol emissions, and the quality control of ingested observations. Initial validation and evaluation of the analyzed AOD fields are provided using independent observations from ground, aircraft, and shipborne instruments. The positive impact of the AOD assimilation on simulated aerosols is demonstrated by comparing MERRA-2 aerosol fields to an identical control simulation that does not include AOD assimilation. After showing the AOD evaluation, this paper takes a first look at aerosol–climate interactions by examining the shortwave, clear-sky aerosol direct radiative effect. The companion paper (Part II) evaluates and validates available MERRA-2 aerosol properties not directly impacted by the AOD assimilation (e.g., aerosol vertical distribution and absorption). Importantly, while highlighting the skill of the MERRA-2 aerosol assimilation products, both studies point out caveats that must be considered when using this new reanalysis product for future studies of aerosols and their interactions with weather and climate.

The Two-Column Aerosol Project (TCAP), conducted from June 2012 through June 2013, was a unique study designed to provide a comprehensive data set that can be used to investigate a number of important climate science questions, including those related to aerosol mixing state and aerosol radiative forcing. The study was designed to sample the atmosphere between and within two atmospheric columns; one fixed near the coast of North America (over Cape Cod, MA) and a second moveable column over the Atlantic Ocean several hundred kilometers from the coast. The U.S. Department of Energy's (DOE) Atmospheric Radiation Measurement (ARM) Mobile Facility (AMF) was deployed at the base of the Cape Cod column, and the ARM Aerial Facility was utilized for the summer and winter intensive observation periods. One important finding from TCAP is that four of six nearly cloud-free flight days had aerosol layers aloft in both the Cape Cod and maritime columns that were detected using the nadir pointing second-generation NASA high-spectral resolution lidar (HSRL-2). These layers contributed up to 60% of the total observed aerosol optical depth (AOD). Many of these layers were also intercepted by the aircraft configured for in situ sampling, and the aerosol in the layers was found to have increased amounts of biomass burning material and nitrate compared to aerosol found near the surface. In addition, while there was a great deal of spatial and day-to-day variability in the aerosol chemical composition and optical properties, no systematic differences between the two columns were observed.

We examine the relationship between the number concentration of boundary-layer cloud condensation nuclei (CCN) and light extinction to investigate underlying aerosol processes and satellite-based CCN estimates. For a variety of airborne and ground-based observations not dominated by dust, regression identifies the CCN (cm−3) at 0.4 ± 0.1% supersaturation with 100.3α +1.3σ0.75 where σ (Mm−1) is the 500 nm extinction coefficient by dried particles and α is the Angstrom exponent. The deviation of 1 km horizontal average data from this approximation is typically within a factor of 2.0. ∂logCCN / ∂logσ is less than unity because, among other explanations, growth processes generally make aerosols scatter more light without increasing their number. This, barring special meteorology–aerosol connections, associates a doubling of aerosol optical depth with less than a doubling of CCN, contrary to previous studies based on heavily averaged measurements or a satellite algorithm.

Total columnar water vapor (CWV), nitrogen dioxide (NO2), and ozone (O3) are derived from a newly developed, hyperspectral airborne Sun-sky spectrometer (4STAR) for the first time during the two intensive phases of the Two-Column Aerosol Project (TCAP) in summer 2012 and winter 2013 aboard the DOE G-1 aircraft. We compare results with coincident measurements. We find 0.045 g/cm2 (4.2%) negative bias and 0.28 g/cm2 (26.3%) root-mean-square difference (RMSD) in water vapor layer comparison with an in situ hygrometer and an overall RMSD of 1.28 g/m3 (38%) water vapor amount in profile by profile comparisons, with differences distributed evenly around zero. RMSD for O3 columns average to 3%, with a 1% negative bias for 4STAR compared with the Ozone Measuring Instrument along aircraft flight tracks for 14 flights during both TCAP phases. Ground-based comparisons with Pandora spectrometers at the Goddard Space Flight Center, Greenbelt, Maryland, showed excellent agreement between the instruments for both O3 (1% RMSD and 0.1% bias) and NO2 (17.5% RMSD and −8% bias). We apply clustering analysis of the retrieved products as a case study during the TCAP summer campaign to identify variations in atmospheric composition of elevated pollution layers and demonstrate that combined total column measurements of trace gas and aerosols can be used to define different pollution layer sources, by comparing our results with trajectory analysis and in situ airborne miniSPLAT (single-particle mass spectrometer) measurements. Our analysis represents a first step in linking sparse but intense in situ measurements from suborbital campaigns with total column observations from space.

Airborne sunphotometer measurements acquired by the NASA Ames Airborne Tracking Sunphotometer (AATS-14) from the NASA P-3 research aircraft are used to evaluate dark-target over-land retrievals of extinction aerosol optical depth (AOD) from spatially and temporally near-coincident measurements by the Moderate Resolution Imaging Spectroradiometer (MODIS) during the summer 2008 Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) field campaign. The new MODIS Collection 6 aerosol data set includes retrievals of AOD at both 10 km × 10 km and 3 km × 3 km (at nadir) resolution. In this paper we compare MODIS and AATS AOD at 553 nm in 58 10 km and 134 3 km retrieval grid cells. These AOD values were derived from data collected over Canada on four days during short time segments of five (four Aqua and one Terra) satellite overpasses of the P-3 during low altitude P-3 flight tracks. Three of the five MODIS/AATS coincidence events were dominated by smoke: one included a P-3 transect of a well-defined smoke plume in clear sky, but two were confounded by the presence of scattered clouds above smoke. The clouds limited the number of MODIS retrievals available for comparison, and led to MODIS AOD retrievals that underestimated the corresponding AATS values. This happened because the MODIS aerosol cloud mask selectively removed 0.5 km pixels containing smoke and clouds before the aerosol retrieval. The other two coincidences (one Terra and one Aqua) occurred during one P-3 flight on the same day and in the same general area, in an atmosphere characterized by a relatively low AOD (< 0.3), and spatially homogeneous regional haze from smoke outflow with no distinguishable plume. For the ensemble data set for MODIS AOD retrievals with the highest-quality flag, MODIS AOD agrees with AATS AOD within the expected MODIS over-land AOD uncertainty in 60% of the retrieval grid cells at 10 km resolution and 69% at 3 km resolution. These values improve to 65% and 74%, respectively, when the cloud-contaminated case with the strongest plume is excluded. We find that the standard MODIS dark-target over-land retrieval algorithm fails to retrieve AOD for thick smoke, not only in cloud-contaminated regions, but also in clear sky. We attribute this to deselection, by the cloud and/or bright surface masks, of 0.5 km resolution pixels that contain smoke.

We present the first ever validation of above-cloud aerosol optical depth (ACAOD) retrieved from the "color ratio" method applied to MODIS cloudy-sky reflectance measurements using the limited direct measurements made by NASA's airborne AATS and 4STAR sensors. A thorough search of the airborne database collection revealed a total of five events in which airborne sunphotometer, coincident with the MODIS overpass, observed agricultural biomass burning, dust, and wildfire-emitted aerosols above a low-level cloud deck during SAFARI-2000, ACE-ASIA 2001, and SEAC4RS-2013 campaigns, respectively. The co-located satellite-airborne measurements revealed a good agreement (root-mean-square-error

We present statistics on the horizontal variability of aerosol optical depth (AOD) directly measured from the NASA P-3 aircraft. Our measurements during two contrasting phases (in Alaska and Canada) of the ARCTAS mission arguably constrain the variability in most aerosol environments common over the globe. In the Canada phase, which features local emissions, 499 nm AOD has a median relative standard deviation (stdrel, med) of 19 % and 9 % and an autocorrelation (r) of 0.37 and 0.71 over 20 km and 6 km horizontal segments, respectively. In the Alaska phase, which features long-range transport, the variability is considerably lower (stdrel, med = 3 %, r = 0.92 even over 35.2 km). Compared to the magnitude of AOD, its wavelength dependence varies less in the Canada phase, more in the Alaska phase. We translate these findings from straight-line flight tracks into grid boxes and points, to help interpretation and design of satellite remote sensing, suborbital observations and transport modeling.

Absorbing aerosols play an important, but uncertain, role in the global climate. Much of this uncertainty is due to a lack of adequate aerosol measurements. While great strides have been made in observational capability in the previous years and decades, it has become increasingly apparent that this development must continue. Scanning polarimeters have been designed to help resolve this issue by making accurate, multi-spectral, multi-angle polarized observations. This work involves the use of the Research Scanning Polarimeter (RSP). The RSP was designed as the airborne prototype for the Aerosol Polarimetery Sensor (APS), which was due to be launched as part of the (ultimately failed) NASA Glory mission. Field observations with the RSP, however, have established that simultaneous retrievals of aerosol absorption and vertical distribution over bright land surfaces are quite uncertain. We test a merger of RSP and High Spectral Resolution Lidar (HSRL) data with observations of boreal forest fire smoke, collected during the Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS). During ARCTAS, the RSP and HSRL instruments were mounted on the same aircraft, and validation data were provided by instruments on an aircraft flying a coordinated flight pattern. We found that the lidar data did indeed improve aerosol retrievals using an optimal estimation method, although not primarily because of the contraints imposed on the aerosol vertical distribution. The more useful piece of information from the HSRL was the total column aerosol optical depth, which was used to select the initial value (optimization starting point) of the aerosol number concentration. When ground based sun photometer network climatologies of number concentration were used as an initial value, we found that roughly half of the retrievals had unrealistic sizes and imaginary indices, even though the retrieved spectral optical depths agreed within uncertainties to independent observations. The convergence to an unrealistic local minimum by the optimal estimator is related to the relatively low sensitivity to particles smaller than 0.1 (μm) at large optical thicknesses. Thus, optimization algorithms used for operational aerosol retrievals of the fine mode size distribution, when the total optical depth is large, will require initial values generated from table look-ups that exclude unrealistic size/complex index mixtures. External constraints from lidar on initial values used in the optimal estimation methods will also be valuable in reducing the likelihood of obtaining spurious retrievals.

We describe aerosol optical depth (AOD) measured during the Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) experiment, focusing on vertical profiles, inter-comparison with correlative observations and fine-mode fraction. Arctic haze observed in 0.1. The retrieved fine-mode fraction of AOD is mostly between 0.7 and 1.0, and its root mean square difference (in both directions) from column-integral submicron fraction (measured with nephelometers, absorption photometers and an impactor) is 0.12. These AOD measurements from the NASA P-3 aircraft, after compensation for below-aircraft light attenuation by vertical extrapolation, mostly fall within ±0.02 of AERONET ground-based measurements between 340–1640 nm for five overpass events.

A single particle soot photometer (SP2) was operated on the NCAR C-130 during the MIRAGE campaign (part of MILAGRO), sampling black carbon (BC) over Mexico. The highest BC concentrations were measured over Mexico City (sometimes as much as 2 μg/m3) and over hill-fires to the south of the city. The age of plumes outside of Mexico City was determined using a combination of HYSPLIT trajectories, WRF-FLEXPART modeling and CMET balloon tracks. As expected, older, diluted air masses had lower BC concentrations. A comparison of carbon monoxide (CO) and BC suggests a CO background of around 65 ppbv, and a background-corrected BC/COnet ratio of 2.89±0.89 (ng/m3-STP)/ppbv (average ± standard deviation). This ratio is similar for fresh emissions over Mexico City, as well as for aged airmasses. Comparison of light absorption measured with a particle soot absorption photometer (PSAP) and the SP2 BC suggests a BC mass-normalized absorption cross-section (MAC) of 10.9±2.1 m2/g at 660 nm (or 13.1 m2/g @ 550 nm, assuming MAC is inversely dependent on wavelength). This appears independent of aging and similar to the expected absorption cross-section for aged BC, but values, particularly in fresh emissions, could be biased high due to instrument artifacts. SP2-derived BC coating indicators show a prominent thinly-coated BC mode over the Mexico City Metropolitan Area (MCMA), while older air masses show both thinly-coated and thickly-coated BC. Some 2-day-old plumes do not show a prominent thickly-coated BC mode, possibly due to preferential wet scavenging of the likely-hydrophilic thickly-coated BC.

The 14-channel Ames Airborne Tracking Sunphotometer (AATS) was operated on a Jetstream 31 (J31) aircraft in March 2006 during MILAGRO/INTEX-B (Megacity Initiative-Local And Global Research Observations/Phase B of the Intercontinental Chemical Transport Experiment). We compare AATS retrievals of spectral aerosol optical depth (AOD) and related aerosol properties with corresponding spatially coincident and temporally near-coincident measurements acquired by the MODIS-Aqua and MODIS-Terra satellite sensors. These comparisons are carried out for the older MODIS Collection 4 (C4) and the new Collection 5 (C5) data set, the latter representing a reprocessing of the entire MODIS data set completed during 2006 with updated calibration and aerosol retrieval algorithm. Our analysis yields a direct, validated assessment of the differences between select MODIS C4 and C5 aerosol retrievals. Our analyses of 37 coincident observations by AATS and MODIS-Terra and 18 coincident observations between AATS and MODIS-Aqua indicate notable differences between MODIS C4 and C5 and between the two sensors. For MODIS-Terra, we find an average increase in AOD of 0.02 at 553 nm and 0.01 or less at the shortwave infrared (SWIR) wavelengths. The change from C4 to C5 results in less good agreement with the AATS derived spectral AOD, with average differences at 553 nm increasing from 0.03 to 0.05. For MODIS-Aqua, we find an average increase in AOD of 0.008 at 553 nm, but an increase of nearly 0.02 at the SWIR wavelengths. The change from C4 to C5 results in slightly less good agreement to the AATS derived visible AOD, with average differences at 553 nm increasing from 0.03 to 0.04. However, at SWIR wavelengths, the changes from C4 to C5 result in improved agreement between MODIS-Aqua and AATS, with the average differences at 2119 nm decreasing from −0.02 to −0.003. Comparing the Angstrom exponents calculated from AOD at 553nm and 855nm, we find an increased rms difference from AATS derived Angstrom exponents in going from C4 to C5 for MODIS-Terra, and a decrease in rms difference, hence an improvement, for the transition from C4 to C5 in MODIS-Aqua. Combining the AATS retrievals with in situ measurements of size-dependent aerosol extinction, we derive a suborbital measure of the aerosol submicron fraction (SMF) of AOD and compare it to MODIS retrievals of aerosol fine mode fraction (FMF). Our analysis shows a significant rms-difference between the MODIS-Terra FMF and suborbitally-derived SMF of 0.17 for both C4 and C5. For MODIS-Aqua, there is a slight improvement in the transition from C4 to C5, with the rms-difference from AATS dropping from 0.23 to 0.16. The differences in MODIS C4 and C5 AOD in this limited data set can be traced to changes in the reflectances input to the aerosol retrievals. An extension of the C4-C5 comparisons from the area along the J31 flight track to a larger study region between 18–23° N and 93–100° W on each of the J31 flight days supports the finding of significant differences between MODIS C4 and C5.

Remote sensing of cloud condensation nuclei (CCN) would help evaluate the indirect effects of tropospheric aerosols on clouds and climate. To assess its feasibility, we examined relationships of submicron aerosol composition to CCN activity and optical properties observed during the MILAGRO/INTEX-B aircraft campaigns. An indicator of CCN activity, κ, was calculated from hygroscopicity measured under saturation. κ for dry 100 nm particles decreased with increasing organic fraction of non-refractory mass of submicron particles (OMF) as 0.34–0.20×OMF over Central Mexico and 0.47–0.43×OMF over the US West Coast. These fits represent the critical dry diameter, centered near 100 nm for 0.2% supersaturation but varied as κ(−1/3), within measurement uncertainty (~20%). The decreasing trends of CCN activity with the organic content, evident also in our direct CCN counts, were consistent with previous ground and laboratory observations of highly organic particles. The wider range of OMF, 0–0.8, for our research areas means that aerosol composition will be more critical for estimation of CCN concentration than at the fixed sites previously studied. Furthermore, the wavelength dependence of extinction was anti-correlated with OMF as −0.70×OMF+2.0 for Central Mexico's urban and industrial pollution air masses, for unclear reasons. The Angstrom exponent of absorption increased with OMF, more rapidly under higher single scattering albedo, as expected for the interplay between soot and colored weak absorbers (some organic species and dust). Because remote sensing products currently use the wavelength dependence of extinction albeit in the column integral form and may potentially include that of absorption, these regional spectral dependencies are expected to facilitate retrievals of aerosol bulk chemical composition and CCN activity over Central Mexico.