Closure of In-Situ Measured Aerosol Backscattering and Extinction Coefficients with Lidar Accounting for Relative Humidity

Abstract. Aerosol particles contribute to the climate forcing through their optical properties. Measuring these optical aerosol particle properties is still challenging, especially considering the hygroscopic growth of aerosol particles, which alters their optical properties. Lidar and in-situ techniques can derive a variety of aerosol optical properties, like aerosol particle light extinction, backscattering, and absorption. But these techniques are subject to some limitations and uncertainties. Within this study, we compared airborne in-situ based and, on Mie-theory based, modeled optical properties at dry state. At ambient state, modeled optical properties were compared with lidar-based estimates. Also, we examined the dependence of the aerosol particle light extinction-to-backscatter ratio, also lidar ratio, to relative humidity. The used model was fed with measured physicochemical aerosol properties and ambient atmospheric conditions. The model considered aerosol particles in an internal core-shell mixing state with constant volume fractions of the aerosol components over the entire observed aerosol particle size-range. The underlying set of measurements was conducted near the measurement site Melpitz, Germany, during two campaigns in summer, 2015, and winter, 2017, and represent Central European background aerosol conditions. Two airborne payloads deployed on a helicopter and a balloon provided measurements of microphysical and optical aerosol particle properties and were complemented by the polarization Raman lidar system PollyXT as well as by a holistic set of microphysical, chemical and optical aerosol measurements derived at ground level. Comparisons of calculated optical aerosol properties with ground-based in-situ measured aerosol optical properties at dry state showed an agreement of the model within 13 % (3 %) in terms of scattering at 450 nm wavelength during the winter (summer) campaign. The model also represented the aerosol particle light absorption at 637 nm within 8 % (18 %) during the winter (summer) campaign and agreed within 13 % with the airborne in-situ aerosol particle light extinction measurements during summer. During winter, in a comparatively clean case with equivalent black carbon mass-concentrations of around 0.2 µg m−3 the modeled airborne measurement-based aerosol particle light absorption, was up to 32–37 % larger than the measured values during a relatively clean period. However, during a high polluted case, with an equivalent black carbon mass concentration of around 4 µg m−3, the modeled aerosol particle light absorption coefficient was, depending on the wavelength, 13–32 % lower than the measured values. Spread and magnitude of the disagreement highlighted the importance of the aerosol mixing state used within the model, the requirement of the inclusion of brown carbon, and a wavelength-dependent complex refractive index of black and brown carbon when such kind of model is used to validate aerosol particle light absorption coefficient estimates of, e.g., lidar systems. Besides dry state comparisons, ambient modeled aerosol particle light extinction, as well as aerosol particle light backscattering, were compared with lidar estimates of these measures. During summer, on average, for four of the twelve conducted measurement flights, the model calculated lower aerosol particle light extinction (up to 29 % lower) as well as backscattering (up to 32 % lower) than derived with the lidar. In winter, the modeled aerosol particle light extinction coefficient was 17 %–41 % lower, the aerosol particle light backscattering coefficient 14 %–42 % lower than the lidar estimates. For both, the winter and summer cases, the Mie-model estimated reasonable extinction-to-backscatter (LR) ratios. Measurement-based Mie-modeling showed evidence of the dependence of the lidar ratio on relative humidity (RH). With this result, we presented a fit for lidar wavelengths of 355, 532, and 1064 nm with an underlying equation of fLR (RH,γ(λ)) = fLR (RH = 0,λ) × (1 − RH)(−γ(λ)) and estimates of γ(355 nm) = 0.29 (±0.01), γ(532 nm) = 0.48 (±0.01), and γ(1064 nm) = 0.31 (±0.01). However, further measurements are required to entangle the behavior of the lidar ratio with respect to different aerosol types, to set up a climatology, and to assess the influence of the aerosol mixing state. This comprehensive study combining airborne and ground-based in-situ and remote sensing measurements, which simulated multiple aerosol optical coefficients in the ambient and dry state, is with its complexity unique of its kind.