Recent results from diverse air, ground, and laboratory studies using both radiometric and in situ techniques show that the fractions of black carbon, organic matter, and mineral dust in atmospheric aerosols determine the wavelength dependence of absorption (often expressed as Absorption Angstrom Exponent, or AAE). Taken together, these results hold promise of improving information on aerosol composition from remote measurements. The main purpose of this paper is to show that AAE values for an Aerosol Robotic Network (AERONET) set of retrievals from Sun-sky measurements describing full aerosol vertical columns are also strongly correlated with aerosol composition or type. In particular, we find AAE values near 1 (the theoretical value for black carbon) for AERONET-measured aerosol columns dominated by urban-industrial aerosol, larger AAE values for biomass burning aerosols, and the largest AAE values for Sahara dust aerosols. These AERONET results are consistent with results from other, very different, techniques, including solar flux-aerosol optical depth (AOD) analyses and airborne in situ analyses examined in this paper, as well as many other previous results. Ambiguities in aerosol composition or mixtures thereof, resulting from intermediate AAE values, can be reduced via cluster analyses that supplement AAE with other variables, for example Extinction Angstrom Exponent (EAE), which is an indicator of particle size. Together with previous results, these results strengthen prospects for determining aerosol composition from space, for example using the Glory Aerosol Polarimetry Sensor (APS), which seeks to provide retrievals of multiwavelength single-scattering albedo (SSA) and aerosol optical depth (and therefore aerosol absorption optical depth (AAOD) and AAE), as well as shape and other aerosol properties. Multidimensional cluster analyses promise additional information content, for example by using the Ozone Monitoring Instrument (OMI) to add AAOD in the near ultraviolet and CALIPSO aerosol layer heights to reduce height-absorption ambiguity.

Classifying observed aerosols into types (e.g., urban‐industrial, biomass burning, mineral dust, maritime) helps to understand aerosol sources, transformations, effects, and feedback mechanisms; to improve accuracy of satellite retrievals; and to quantify aerosol radiative impacts on climate. The number of aerosol parameters retrieved from spaceborne sensors has been growing, from the initial aerosol optical depth (AOD) at one or a few wavelengths to a list that now includes AOD, complex refractive index, single scattering albedo (SSA), and depolarization of backscatter, each at several wavelengths, plus several particle size and shape parameters. Making optimal use of these varied data products requires objective, multidimensional analysis methods. We describe such a method, which makes explicit use of uncertainties in input parameters. It treats an N‐parameter retrieved data point and its N‐dimensional uncertainty as an extended data point, E. It then uses a modified Mahalanobis distance, D_EC, to assign an observation to the class (cluster) C that has minimum D_EC from the point. We use parameters retrieved from the Aerosol Robotic Network (AERONET) to define seven prespecified clusters (pure dust, polluted dust, urban‐industrial/developed economy, urban‐industrial/developing economy, dark biomass smoke, light biomass smoke, and pure marine), and we demonstrate application of the method to a 5 year record of retrievals from the spaceborne Polarization and Directionality of the Earth's Reflectances 3 (POLDER 3) polarimeter over the island of Crete, Greece. Results show changes of aerosol type at this location in the eastern Mediterranean Sea, which is influenced by a wide variety of aerosol sources.

The Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research (4STAR) combines airborne sun tracking and sky scanning with diffraction spectroscopy to improve knowledge of atmospheric constituents and their links to air-pollution/climate. Direct beam hyper-spectral measurement of optical depth improves retrievals of gas constituents and determination of aerosol properties. Sky scanning enhances retrievals of aerosol type and size distribution. 4STAR measurements will tighten the closure between satellite and ground-based measurements. 4STAR incorporates a modular sun-tracking/ sky-scanning optical head with fiber optic signal transmission to rack mounted spectrometers, permitting miniaturization of the external optical head, and future detector evolution. Technical challenges include compact optical collector design, radiometric dynamic range and stability, and broad spectral coverage. Test results establishing the performance of the instrument against the full range of operational requirements are presented, along with calibration, engineering flight test, and scientific field campaign data and results.

Aerosol transport off the US Northeast coast during the Summer 2004 International Consortium for Atmospheric Research on Transport and Transformation (ICARTT) Intercontinental Chemical Transport Experiment (INTEX) and Intercontinental Transport and Chemical Transformation (ITCT) experiments produced a wide range of aerosol types and aerosol optical depth (AOD) values, often with strong horizontal AOD gradients. In these conditions we flew the 14‐channel NASA Ames Airborne Tracking Sun photometer (AATS) on a Jetstream 31 (J31) aircraft. Legs flown at low altitude (usually ≤100 m ASL) provided comparisons of AATS AOD spectra to retrievals for 90 grid cells of the satellite radiometers MODIS‐Terra, MODIS‐Aqua, and MISR, all over the ocean. Characterization of the retrieval environment was aided by using vertical profiles by the J31 (showing aerosol vertical structure) and, on occasion, shipboard measurements of light scattering and absorption. AATS provides AOD at 13 wavelengths λ from 354 to 2138 nm, spanning the range of aerosol retrieval wavelengths for MODIS over ocean (466–2119 nm) and MISR (446–866 nm). Midvisible AOD on low‐altitude J31 legs in satellite grid cells ranged from 0.05 to 0.9, with horizontal gradients often in the range 0.05 to 0.13 per 10 km. When possible, we used ship measurements of humidified aerosol scattering and absorption to estimate AOD below the J31. In these cases, which had J31 altitudes 60–110 m ASL (typical of J31 low‐altitude transects), estimated midvisible AOD below the J31 ranged from 0.003 to 0.013, with mean 0.009 and standard deviation 0.003. These values averaged 6% of AOD above the J31. MISR‐AATS comparisons on 29 July 2004 in 8 grid cells (each ∼17.6 km × 17.6 km) show that MISR versions 15 and 16 captured the AATS‐measured AOD gradient (correlation coefficient R² = 0.87 to 0.92), but the MISR gradient was somewhat weaker than the AATS gradient. The large AOD (midvisible values up to ∼0.9) and differing gradients in this case produced root‐mean‐square (RMS) MISR‐AATS AOD differences of 0.03 to 0.21 (9 to 31%). MISR V15 Ångstrom exponent α ( = −dlnAOD/dlnλ) was closer to AATS than was MISR V16. MODIS‐AATS AOD comparisons on 8 overpasses using 61 grid cells (each nominally 10 km × 10 km) had R² ∼ 0.97, with RMS AOD difference ∼0.03 (∼20%). About 87% of the MODIS AOD retrievals differed from AATS values by less than the predicted MODIS over‐ocean uncertainty, Δτ = ±0.03 ± 0.05τ. In contrast to the small MODIS‐AATS differences in AOD, MODIS‐AATS differences in Ångstrom exponent α were large: RMS differences for α(553, 855 nm) were 0.28 for MODIS‐Terra and 0.64 for MODIS‐Aqua; RMS differences for α(855, 2119 nm) were larger still, 0.61 for MODIS‐Terra and 1.14 for MODIS‐Aqua. The largest MODIS‐AATS Ångstrom exponent differences were associated with small AOD values, for which MODIS AOD relative uncertainty is large. Excluding cases with AOD(855 nm) < 0.1 reduced MODIS‐AATS α differences substantially. In one grid cell on 21 July 2004, smoke over cloud appeared to impair the MODIS‐Aqua cloud mask, resulting in retrieved AODs that significantly exceeded AATS values. Experiments with extending MODIS retrievals into the glint mask yielded MODIS AODs consistently less than AATS AODs, especially at long wavelength, indicating that the current MODIS glint mask limits should not be reduced to the extent tried here. The sign of the AOD differences within the glint mask (MODIS AOD < AATS AOD) is consistent with ship‐measured wind speeds there.

The 14-channel NASA Ames Airborne Tracking Sunphotometer (AATS-14) measured solar- beam transmission on the NASA DC-8 during the second SAGE III Ozone Loss and Validation Experiment (SOLVE II). This paper presents AATS-14 results for multiwavelength aerosol optical depth (AOD), including comparisons to results from two satellite sensors and another DC-8 instrument, namely the Stratospheric Aerosol and Gas Experiment III (SAGE III), the Polar Ozone and Aerosol Measurement III (POAM III) and the Direct-beam Irradiance Airborne Spectrometer (DIAS). AATS-14 provides aerosol results at 13 wavelengths λ spanning the range of SAGE III and POAM III aerosol wavelengths. Because most AATS measurements were made at solar zenith angles (SZA) near 90°, retrieved AODs are strongly affected by uncertainties in the relative optical airmass of the aerosols and other constituents along the line of sight (LOS) between instrument and sun. To reduce dependence of the AATS-satellite comparisons on airmass, we perform the comparisons in LOS transmission and LOS optical thickness (OT) as well as in vertical OT (i.e., optical depth, OD). We also use a new airmass algorithm that validates the algorithm we previously used to within 2% for SZA<90°, and in addition provides results for SZA≥90°. For 6 DC-8 flights, 19 January-2 February 2003, AATS and DIAS results for LOS aerosol OT at λ=400nm agree to ≤12% of the AATS value. Mean and root-mean-square (RMS) differences, (DIAS-AATS)/AATS, are -2.3% and 7.7%, respectively. For DC-8 altitudes, AATS-satellite comparisons are possible only for λ>440nm, because of signal depletion for shorter λ on the satellite full-limb LOS. For the 4 AATS-SAGE and 4 AATS-POAM near-coincidences conducted 19-31 January 2003, AATS-satellite AOD differences were ≤0.0041 for all λ>440nm. RMS differences were ≤0.0022 for SAGE-AATS and ≤0.0026 for POAM-AATS. RMS relative differences in AOD ([SAGE-AATS]/AATS) were ≤33% for λ<~755nm, but grew to 59% for 1020nm and 66% at 1545nm. For λ>~755nm, AATS-POAM differences were less than AATS-SAGE differences, and RMS relative differences in AOD ([AATS-POAM]/AATS) were ≤31% for all λ between 440 and 1020nm. Unexplained differences that remain are associated with transmission differences, rather than differences in gas subtraction or conversion from LOS to vertical quantities. The very small stratospheric AOD values that occurred during SOLVE II added to the challenge of the comparisons, but do not explain all the differences.