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This study presents an investigation of aerosol microphysical retrievals from High Spectral Resolution Lidar (HSRL) measurements. Firstly, retrievals are presented for synthetically-generated lidar measurements, followed by an application of the retrieval algorithm to real lidar measurements. Here, we perform the investigation for an aerosol state vector that is typically used in multi-angle polarimeter (MAP) retrievals, so that the results can be interpreted in relation to a potential combination of lidar and MAP measurements. These state vectors correspond to a bimodal size distribution, where column number, effective radius, and effective variance of both modes are treated as fit parameters, alongside the complex refractive index and particle shape. The focus is primarily on a lidar configuration based on that of the High Spectral Resolution Lidar-2 (HSRL-2), which participated in the ACEPOL (Aerosol Characterization from Polarimeter and Lidar) campaign, a combined project between NASA and SRON (Netherlands Institute for Space Research). The measurement campaign took place between October and November 2017, over the western region of the USA. Six different instruments were mounted on the aeroplane: four MAPs, and two lidar instruments: HSRL-2, and the Cloud Physics Lidar (CPL). Most of the flights were carried out over land, passing over scenes with a low aerosol load. One of the flights passed over a prescribed forest fire in Arizona on the 9th of November, with a relatively higher AOD, and it is the data from this flight that is focussed on in this study. A retrieval of the aerosol microphysical properties of the smoke plume mixture was attempted with the data from HSRL-2, and compared with a retrieval from the MAPs carried out in previous work pertaining to the ACEPOL data. The synthetic HSRL-2 retrievals resulted for the fine mode in a mean absolute error (MAE) of 0.038 (0.025) µm for the effective radius, 0.052 (0.037) for the real refractive index, 0.010 (7.20×10-3) for the imaginary part of the refractive index, 0.109 (0.071) for the spherical fraction, and 0.054 (0.039) for the AOD at 532 nm, where the retrievals inside brackets indicate the MAE for noise-free retrievals. For the coarse mode, we find the MAE is 0.459 (0.254) µm for the effective radius, 0.085 (0.075) for the real refractive index, 2.06×10-4 (1.90×10-4) for the imaginary component, 0.120 (0.090) for the spherical fraction, and 0.051 (0.039) for the AOD. A study of the sensitivity of retrievals to the choice of prior and first guess showed that, on average, the retrieval errors increase when the prior deviates too much from the truth value. These experiments revealed that the measurements primarily contain information on the size and shape of the aerosol, along with the column number. Some information on the real component of the refractive index is also present, with the measurements providing little on absorption or on the effective variance of the aerosol distribution, as both of these were shown to depend heavily on the choice of prior. Retrievals using the HSRL-2 smoke-plume data yielded, for the fine mode, an effective radius of 0.107 µm, a real refractive index of 1.561, an imaginary component of refractive index of 0.010, a spherical fraction of 0.719, and an AOD at 532 nm of 0.505. Additionally, the single-scattering albedo (SSA) from the HSRL-2 retrievals was 0.940. Overall, these results are in good agreement with those from the SPEX and RSP retrievals. [ABSTRACT FROM AUTHOR]

Atmospheric aerosols have been known to be a major source of uncertainties in CO2 concentrations retrieved from space. In this study, we investigate the added value of multi-angle polarimeter (MAP) measurements in the context of the Copernicus candidate mission for anthropogenic CO2 monitoring (CO2M). To this end, we compare aerosol-induced XCO2 errors from standard retrievals using spectrometer only (without MAP) with those from retrievals using both MAP and spectrometer. MAP observations are expected to provide information about aerosols that is useful for improving XCO2 accuracy. For the purpose of this work, we generate synthetic measurements for different atmospheric and geophysical scenes over land, based on which XCO2 retrieval errors are assessed. We show that the standard XCO2 retrieval approach that makes no use of auxiliary aerosol observations returns XCO2 errors with an overall bias of 1.12 ppm, and a spread (defined as half of the 15.9th to the 84.1th percentile range) of 2.07 ppm. The latter is far higher than the required XCO2 accuracy (0.5 ppm) and precision (0.7 ppm) of the CO2M mission. Moreover, these XCO2 errors exhibit a significantly larger bias and scatter at high aerosol optical depth, high aerosol altitude, and low solar zenith angle, which could lead to a worse performance in retrieving XCO2 from polluted areas where CO2 and aerosols are co-emitted. We proceed to determine MAP instrument specifications in terms of wavelength range, number of viewing angles, and measurement uncertainties that are required to achieve XCO2 accuracy and precision targets of the mission. Two different MAP instrument concepts are considered in this analysis. We find that for either concept, MAP measurement uncertainties on radiance and degree of linear polarization should be no more than 3 % and 0.003, respectively. Adopting the derived MAP requirements, a retrieval exercise using both MAP and spectrometer measurements of the synthetic scenes delivers XCO2 errors with an overall bias of −0.004 ppm and a spread of 0.54 ppm, implying compliance with the CO2M mission requirements; the very low bias is especially important for proper emission estimates. For the test ensemble, we find effectively no dependence of the XCO2 errors on aerosol optical depth, altitude of the aerosol layer, and solar zenith angle. These results indicate a major improvement in the retrieved XCO2 accuracy with respect to the standard retrieval approach, which could lead to a higher data yield, better global coverage, and a more comprehensive determination of CO2 sinks and sources. As such, this outcome underlines the contribution of, and therefore the need for, a MAP instrument onboard the CO2M mission. [ABSTRACT FROM AUTHOR]