ALBERT

Description: We present a detailed evaluation of remotely sensed aerosol microphysical properties obtained from an advanced, multi-wavelength high-spectral-resolution lidar (HSRL-2) during the 2013 NASA DISCOVER-AQ field campaign. Vertically resolved retrievals of fine-mode aerosol number, surface-area, and volume concentration as well as aerosol effective radius are compared to 108 collocated, airborne in situ measurement profiles in the wintertime San Joaquin Valley, California, and in summertime Houston, Texas. An algorithm for relating the dry in situ aerosol properties to those obtained by the HSRL at ambient relative humidity is discussed. We show that the HSRL-2 retrievals of ambient fine-mode aerosol surface-area and volume concentrations agree with the in situ measurements to within 25 and 10 %, respectively, once hygroscopic growth adjustments have been applied to the dry in situ data. Despite this excellent agreement for the microphysical properties, extinction and backscatter coefficients at ambient relative humidity derived from the in situ aerosol measurements using Mie theory are consistently smaller than those measured by the HSRL, with average differences of 31 ± 5 % and 53 ± 11 % for California and Texas, respectively. This low bias in the in situ estimates is attributed to the presence of coarse-mode aerosol that are detected by HSRL-2 but that are too large to be well sampled by the in situ instrumentation. Since the retrieval of aerosol volume is most relevant to current regulatory efforts targeting fine particle mass (PM2. 5), these findings highlight the advantages of an advanced 3β + 2α HSRL for constraining the vertical distribution of the aerosol volume or mass loading relevant for air quality.

Description: Over 700 vertically-resolved retrievals of effective radii, number, volume, and surface-area concentrations of aerosols obtained from inversion of airborne multiwavelength High Spectral Resolution Lidar (HSRL-2) measurements are compared to vertically resolved airborne in situ measurements obtained during DISCOVER-AQ campaign from 2013 in California and Texas. In situ measurements of dry and humidified scattering, dry absorption, and dry size distributions are used to estimate hygroscopic adjustments which, in turn, are applied to the dry in situ measurements before comparison to HSRL-2 measurements and retrievals. The HSRL-2 retrievals of size parameters agree well with the in situ measurements once the hygroscopic adjustments are applied to the latter, with biases smaller than 25 % for surface-area concentrations, and smaller than 10 % for volume concentration. A closure study is performed by comparing the extinction and backscatter measured with the HSRL-2 with those calculated from the in situ size distributions and Mie theory, once refractive indices (at ambient RH) and hygroscopic adjustments are calculated and applied. The results of this closure study revealed discrepancies between the HSRL-2 optical measurements and those calculated from in situ measurements, in both California and Texas datasets, with the aerosol extinction and backscatter coefficients measured with the HSRL-2 being larger than those calculated from the adjusted in situ measurements and Mie theory. These discrepancies are further investigated and discussed in light of the many challenges often present in closure studies between in situ and remote sensing systems, such as: limitations in covering the same size range of particles with in situ and remote sensing instruments, as well as simplified parameterizations and assumptions used when dry in situ data are adjusted to account for aerosol hygroscopicity.

Description: We present a detailed evaluation of remotely-sensed aerosol microphysical properties obtained from an advanced, multi-wavelength High Spectral Resolution Lidar (HSRL-2) during the 2013 NASA DISCOVER-AQ field campaign. Vertically-resolved retrievals of fine mode aerosol number, surface area, and volume concentration as well as aerosol effective radius are compared to 108 co-located, airborne in situ measurement profiles in the wintertime San Joaquin Valley, California, and in summertime Houston, Texas. An algorithm for relating the dry in situ aerosol properties to those obtained by the HSRL at ambient relative humidity is discussed. We show that the HSRL-2 retrievals of ambient fine mode aerosol surface area and volume concentrations agree with the in situ measurements to within 25 % and 10 %, respectively, once hygroscopic growth adjustments have been applied to the dry in situ data. Despite this excellent agreement for the microphysical properties, extinction and backscatter coefficients at ambient relative humidity derived from the in situ aerosol measurements using Mie theory are consistently smaller than those measured by the HSRL, with average differences of 31 % ± 5 % and 53 % ± 11 % for California and Texas, respectively. This low bias in the in situ estimates is attributed to the presence of coarse mode aerosol that are detected by HSRL-2 but that are too large to be well sampled by the in situ instrumentation. Since the retrieval of aerosol volume is most relevant to current regulatory efforts targeting fine particle mass (PM2.5), these findings highlight the advantages of an advanced 3β + 2α HSRL for constraining the vertical distribution of the aerosol volume or mass loading relevant for air quality.

Description: There is considerable interest in retrieving profiles of aerosol effective radius, total number concentration, and complex refractive index from lidar measurements of extinction and backscatter at several wavelengths. The combination of three backscatter channels plus two extinction channels (3β + 2α) is particularly important since it is believed to be the minimum configuration necessary for the retrieval of aerosol microphysical properties and because the technological readiness of lidar systems permits this configuration on both an airborne and future spaceborne instrument. The second-generation NASA Langley airborne High Spectral Resolution Lidar (HSRL-2) has been making 3β + 2α measurements since 2012. The planned NASA Aerosol/Clouds/Ecosystems (ACE) satellite mission also recommends the 3β + 2α combination.Here we develop a deeper understanding of the information content and sensitivities of the 3β + 2α system in terms of aerosol microphysical parameters of interest. We use a retrieval-free methodology to determine the basic sensitivities of the measurements independent of retrieval assumptions and constraints. We calculate information content and uncertainty metrics using tools borrowed from the optimal estimation methodology based on Bayes' theorem, using a simplified forward model look-up table, with no explicit inversion. The forward model is simplified to represent spherical particles, monomodal log-normal size distributions, and wavelength-independent refractive indices. Since we only use the forward model with no retrieval, the given simplified aerosol scenario is applicable as a best case for all existing retrievals in the absence of additional constraints. Retrieval-dependent errors due to mismatch between retrieval assumptions and true atmospheric aerosols are not included in this sensitivity study, and neither are retrieval errors that may be introduced in the inversion process. The choice of a simplified model adds clarity to the understanding of the uncertainties in such retrievals, since it allows for separately assessing the sensitivities and uncertainties of the measurements alone that cannot be corrected by any potential or theoretical improvements to retrieval methodology but must instead be addressed by adding information content.The sensitivity metrics allow for identifying (1) information content of the measurements vs. a priori information; (2) error bars on the retrieved parameters; and (3) potential sources of cross-talk or "compensating" errors wherein different retrieval parameters are not independently captured by the measurements. The results suggest that the 3β + 2α measurement system is underdetermined with respect to the full suite of microphysical parameters considered in this study and that additional information is required, in the form of additional coincident measurements (e.g., sun-photometer or polarimeter) or a priori retrieval constraints. A specific recommendation is given for addressing cross-talk between effective radius and total number concentration.

Description: We present a summary on the current status of two inversion algorithms that are used in EARLINET (European Aerosol Research Lidar Network) for the inversion of data collected with EARLINET multiwavelength Raman lidars. These instruments measure backscatter coefficients at 355, 532, and 1064 nm, and extinction coefficients at 355 and 532 nm. Development of these two algorithms started in 2000 when EARLINET was founded. The algorithms are based on a manually controlled inversion of optical data which allows for detailed sensitivity studies. The algorithms allow us to derive particle effective radius as well as volume and surface area concentration with comparably high confidence. The retrieval of the real and imaginary parts of the complex refractive index still is a challenge in view of the accuracy required for these parameters in climate change studies in which light absorption needs to be known with high accuracy. It is an extreme challenge to retrieve the real part with an accuracy better than 0.05 and the imaginary part with accuracy better than 0.005–0.1 or ±50 %. Single-scattering albedo can be computed from the retrieved microphysical parameters and allows us to categorize aerosols into high- and low-absorbing aerosols. On the basis of a few exemplary simulations with synthetic optical data we discuss the current status of these manually operated algorithms, the potentially achievable accuracy of data products, and the goals for future work. One algorithm was used with the purpose of testing how well microphysical parameters can be derived if the real part of the complex refractive index is known to at least 0.05 or 0.1. The other algorithm was used to find out how well microphysical parameters can be derived if this constraint for the real part is not applied. The optical data used in our study cover a range of Ångström exponents and extinction-to-backscatter (lidar) ratios that are found from lidar measurements of various aerosol types. We also tested aerosol scenarios that are considered highly unlikely, e.g. the lidar ratios fall outside the commonly accepted range of values measured with Raman lidar, even though the underlying microphysical particle properties are not uncommon. The goal of this part of the study is to test the robustness of the algorithms towards their ability to identify aerosol types that have not been measured so far, but cannot be ruled out based on our current knowledge of aerosol physics. We computed the optical data from monomodal logarithmic particle size distributions, i.e. we explicitly excluded the more complicated case of bimodal particle size distributions which is a topic of ongoing research work. Another constraint is that we only considered particles of spherical shape in our simulations. We considered particle radii as large as 7–10 µm in our simulations where the Potsdam algorithm is limited to the lower value. We considered optical-data errors of 15 % in the simulation studies. We target 50 % uncertainty as a reasonable threshold for our data products, though we attempt to obtain data products with less uncertainty in future work.

Description: There is considerable interest in retrieving profiles of aerosol effective radius, total number concentration and complex refractive index from lidar measurements of extinction and backscatter at several wavelengths. The combination of three backscatter channels plus two extinction channels (3β + 2α) is particularly important since it is believed to be the minimum configuration necessary for the retrieval of aerosol microphysical properties and because the technological readiness of lidar systems permits this configuration on both an airborne and future spaceborne instrument. The 2nd-generation NASA Langley airborne High Spectral Resolution Lidar (HSRL-2) has been making 3β + 2α measurements since 2012. The planned NASA Aerosol-Clouds-Ecosystem (ACE) satellite mission also recommends the 3β + 2α combination. Here we develop a deeper understanding of the information content and sensitivities of the 3β + 2α system in terms of aerosol microphysical parameters of interest. We use a retrieval-free methodology to determine the basic sensitivities of the measurements independent of retrieval assumptions and constraints. We calculate information content and uncertainty metrics using tools borrowed from the Optimal Estimation methodology based on Bayes' theorem, using a simplified forward model look-up table, with no explicit inversion. The forward model is simplified to represent spherical particles, monomodal log-normal size distributions, and wavelength-independent refractive indices. Since we only use the forward model with no retrieval, the given simplified aerosol scenario is applicable as a best case for all existing retrievals in the absence of additional constraints. Retrieval-dependent errors due to mismatch between retrieval assumptions and true atmospheric aerosols are not included in this sensitivity study, nor are retrieval errors that may be introduced in the inversion process. The sensitivity metrics allow for identifying (1) information content of the measurements versus a priori information; (2) error bars on the retrieved parameters; and (3) potential sources of cross-talk or “compensating” errors wherein different retrieval parameters are not independently captured by the measurements. The results suggest that the 3β + 2α measurement system is underdetermined with respect to the full suite of microphysical parameters considered in this study, and that additional information is required, in the form of additional coincident measurements (e.g. sun-photometer or polarimeter) or a priori retrieval constraints. A specific recommendation is given for addressing cross-talk between effective radius and total number concentration.

Description: No abstract available

Description: NASA Langley recently developed the world's first airborne multi-wavelength high spectral resolution lidar (HSRL). This lidar employs the HSRL technique at 355 and 532 nm to make independent, unambiguous retrievals of aerosol extinction and backscatter. It also employs the standard backscatter technique at 1064 nm and is polarization-sensitive at all three wavelengths. This instrument, dubbed HSRL-2 (the secondgeneration HSRL developed by NASA Langley), is a prototype for the lidar on NASA's planned Aerosols- Clouds-Ecosystems (ACE) mission. HSRL-2 completed its first science mission in July 2012, the Two-Column Aerosol Project (TCAP) conducted by the Department of Energy (DOE) in Hyannis, MA. TCAP presents an excellent opportunity to assess some of the remote sensing concepts planned for ACE: HSRL-2 was deployed on the Langley King Air aircraft with another ACE-relevant instrument, the NASA GISS Research Scanning Polarimeter (RSP), and flights were closely coordinated with the DOE's Gulfstream-1 aircraft, which deployed a variety of in situ aerosol and trace gas instruments and the new Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research (4STAR). The DOE also deployed their Atmospheric Radiation Measurement Mobile Facility and their Mobile Aerosol Observing System at a ground site located on the northeastern coast of Cape Cod for this mission. In this presentation we focus on the capabilities, data products, and applications of the new HSRL-2 instrument. Data products include aerosol extinction, backscatter, depolarization, and optical depth; aerosol type identification; mixed layer depth; and rangeresolved aerosol microphysical parameters (e.g., effective radius, index of refraction, single scatter albedo, and concentration). Applications include radiative closure studies, studies of aerosol direct and indirect effects, investigations of aerosol-cloud interactions, assessment of chemical transport models, air quality studies, present (e.g., CALIPSO) and future (e.g., EarthCARE) satellite calibration/validation, and development/assessment of advanced retrieval techniques for future satellite applications (e.g., lidar+polarimeter retrievals of aerosol and cloud properties). We will also discuss the relevance of HSRL-2 measurement capabilities to the ACE remote sensing concept.

Description: No abstract available