A Laboratory Experiment for the Statistical Evaluation of Aerosol Retrieval (STEAR) Algorithms

Abstract

We have developed a method for evaluating the fidelity of the Aerosol Robotic Network (AERONET) retrieval algorithms by mimicking atmospheric extinction and radiance measurements in a laboratory experiment. This enables radiometric retrievals that use the same sampling volumes, relative humidities, and particle size ranges as observed by other in situ instrumentation in the experiment. We use three Cavity Attenuated Phase Shift (CAPS) monitors for extinction and University of Maryland Baltimore County’s (UMBC) three-wavelength Polarized Imaging Nephelometer (PI-Neph) for angular scattering measurements. We subsample the PI-Neph radiance measurements to angles that correspond to AERONET almucantar scans, with simulated solar zenith angles ranging from 50 ∘ to 77 ∘ . These measurements are then used as input to the Generalized Retrieval of Aerosol and Surface Properties (GRASP) algorithm, which retrieves size distributions, complex refractive indices, single-scatter albedos, and bistatic LiDAR ratios for the in situ samples. We obtained retrievals with residuals less than 8% for about 90 samples. Samples were alternately dried or humidified, and size distributions were limited to diameters of less than 1.0 or 2.5 μ m by using a cyclone. The single-scatter albedo at 532 nm for these samples ranged from 0.59 to 1.00 when computed with CAPS extinction and Particle Soot Absorption Photometer (PSAP) absorption measurements. The GRASP retrieval provided single-scatter albedos that are highly correlated with the in situ single-scatter albedos, and the correlation coefficients ranged from 0.916 to 0.976, depending upon the simulated solar zenith angle. The GRASP single-scatter albedos exhibited an average absolute bias of +0.023–0.026 with respect to the extinction and absorption measurements for the entire dataset. We also compared the GRASP size distributions to aerodynamic particle size measurements, using densities and aerodynamic shape factors that produce extinctions consistent with our CAPS measurements. The GRASP effective radii are highly correlated (R = 0.80) and biased under the corrected aerodynamic effective radii by 1.3% (for a simulated solar zenith angle of θ ∘ = 50 ∘ ); the effective variance indicated a correlation of R = 0.51 and a relative bias of 280%. Finally, our apparatus was not capable of measuring backscatter LiDAR ratios, so we measured bistatic LiDAR ratios at a scattering angle of 173 degrees. The GRASP bistatic LiDAR ratios had correlations of 0.71 to 0.86 (depending upon simulated θ ∘ ) with respect to in situ measurements, positive relative biases of 2–10%, and average absolute biases of 1.8–7.9 sr.

Constraining global aerosol emissions using POLDER/PARASOL satellite remote sensing observations

“…The development of the GRASP algorithm is described in Dubovik et al (2011Dubovik et al ( , 2014, and a description of some PARASOL/GRASP aerosol products can be found in Chen et al (2018), Kokhanovsky et al (2015), Popp et al (2016) and Sayer et al (2018). The accuracy of the GRASP algorithm configured for AERONET measurements has been evaluated with a laboratory experiment by Schuster et al (2019).…”

“…We should note that AERONET aerosol datasets are averaged of all available data during the daytime (lunar photometer aerosol products will probably be available in the future; e.g., Barreto et al, 2016, andBerkoff et al, 2011) and that the GEOS-Chem daily aerosol properties are averaged based upon daytime and nighttime simulations. Additionally, the use of AERONET data comparing against corresponding 2 • × 2.5 • grid box model simulation could bring some sampling issues that cannot be ignored (Schutgens et al, 2016). Figure 6 shows the comparison of a priori (red) and a posteriori (blue) GEOS-Chem model simulated AOD, AAOD, SSA, AExp and AAExp with the AERONET dataset.…”

Retrieval of aerosol properties from Airborne Hyper-Angular Rainbow Polarimeter (AirHARP) observations during ACEPOL 2017

“…GRASP first demonstrated its overall capability in an aerosol retrieval test study (Kokhanovsky et al, 2010). It has gone on to prove itself in a variety of real-world applications (Chen et al, 2018(Chen et al, , 2019Frouin et al, 2019;Li et al, 2019;Schuster et al, 2019;Torres et al, 2017). GRASP has been successfully applied to measurements from many different types of instruments (Benavent-Oltra et al, 2019;Espinosa et al, 2017Espinosa et al, , 2018Román et al, 2018;Titos et al, 2019;Torres et al, 2017), but the most pertinent to AirHARP are the previous applications of GRASP to POLDER-3 on PARASOL (Chen et al, 2018(Chen et al, , 2019Dubovik et al, 2011;Frouin et al, 2019;Li et al, 2019) because of its familiar polarization, multi-wavelength, and multi-angle sampling characteristics.…”

“…In addition, a careful understanding of aerosol properties is essential for air quality monitoring/mitigation, characterizing fertilization of ecosystems, hydrological forecasting, etc. (Shiraiwa et al, 2017;Westberry et al, 2019).…”

Synergy processing of diverse ground-based remote sensing and in situ data using GRASP algorithm: applications to radiometer, lidar and radiosonde observations

“…Torres et al (2017) demonstrated the high potential of GRASP retrieval concept for inverting only direct Sun photometric observations. Espinosa et al (2017Espinosa et al ( , 2019 and Schuster et al (2019) used GRASP approach for processing in situ aircraft and laboratory light scattering measurements. Most of these studies benefited from previous GRASP implementations and included certain new elements needed in specific applications.…”