Abstract. Strong events of long-range transported biomass burning aerosol were detected during July 2013 at three EARLINET (European Aerosol Research Lidar Network) stations, namely Granada (Spain), Leipzig (Germany) and Warsaw (Poland). Satellite observations from MODIS (Moderate Resolution Imaging Spectroradiometer) and CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) instruments, as well as modeling tools such as HYSPLIT (Hybrid Single-Particle Lagrangian Integrated Trajectory) and NAAPS (Navy Aerosol Analysis and Prediction System), have been used to estimate the sources and transport paths of those North American forest fire smoke particles. A multiwavelength Raman lidar technique was applied to obtain vertically resolved particle optical properties, and further inversion of those properties with a regularization algorithm allowed for retrieving microphysical information on the studied particles. The results highlight the presence of smoke layers of 1-2 km thickness, located at about 5 km a.s.l. altitude over Granada and Leipzig and around 2.5 km a.s.l. at Warsaw. These layers were intense, as they accounted for more than 30 % of the total AOD (aerosol optical depth) in all cases, and presented optical and microphysical features typical for different aging degrees: color ratio of lidar ratios (LR 532 / LR 355 ) around 2, α-related ångström exponents of less than 1, effective radii of 0.3 µm and large values of single scattering albedos (SSA), nearly spectrally independent. The intensive microphysical properties were compared with columnar retrievals form co-located AERONET (Aerosol Robotic Network) stations. The intensity of the layers was also characterized in terms of particle volume concentration, and then an experimental relationship between this magnitude and the particle extinction coefficient was established.
In this paper we present an approach for the profiling of aerosol microphysical and optical properties combining ceilometer and sun/sky photometer measurements in the GRASP code (General Retrieval of Aerosol and Surface Properties). For this objective, GRASP is used with sun/sky photometer measurements of aerosol optical depth (AOD) and sky radiances, both at four wavelengths and obtained from AErosol RObotic NETwork (AERONET), and ceilometer measurements of range corrected signal (RCS) at 1064 nm. A sensitivity study with synthetic data evidences the capability of the method to retrieve aerosol properties such as size distribution and profiles of volume concentration (VC), especially for coarse particles. Aerosol properties obtained by the mentioned method are compared with airborne in-situ measurements acquired during two flights over Granada (Spain) within the framework of ChArMEx/ADRIMED (Chemistry-Aerosol Mediterranean Experiment/Aerosol Direct Radiative Impact on the regional climate in the MEDiterranean region) 2013 campaign. The retrieved aerosol VC profiles agree well with the airborne measurements, showing a mean bias error (MBE) and a mean absolute bias error (MABE) of 0.3 µm 3 /cm 3 (12%) and 5.8 µm 3 /cm 3 (25%), respectively. The differences between retrieved VC and airborne in-situ measurements are within the uncertainty of GRASP retrievals. In addition, the retrieved VC at 2500 m a.s.l. is shown and compared with in-situ measurements obtained during summer 2016 at a high-atitude mountain station in the framework of the SLOPE I campaign (Sierra Nevada Lidar AerOsol Profiling Experiment). VC from GRASP presents high correlation (r=0.91) with the in-situ measurements, but overestimates them, MBE and MABE being equal to 23% and 43%.
Abstract. This study focuses on the analysis of aerosol hygroscopic growth during the Sierra Nevada Lidar AerOsol Profiling Experiment (SLOPE I) campaign by using the synergy of active and passive remote sensors at the ACTRIS Granada station and in situ instrumentation at a mountain station (Sierra Nevada, SNS). To this end, a methodology based on simultaneous measurements of aerosol profiles from an EARLINET multi-wavelength Raman lidar (RL) and relative humidity (RH) profiles obtained from a multi-instrumental approach is used. This approach is based on the combination of calibrated water vapor mixing ratio (r) profiles from RL and continuous temperature profiles from a microwave radiometer (MWR) for obtaining RH profiles with a reasonable vertical and temporal resolution. This methodology is validated against the traditional one that uses RH from colocated radiosounding (RS) measurements, obtaining differences in the hygroscopic growth parameter (γ ) lower than 5 % between the methodology based on RS and the one presented here. Additionally, during the SLOPE I campaign the remote sensing methodology used for aerosol hygroscopic growth studies has been checked against Mie calculations of aerosol hygroscopic growth using in situ measurements of particle number size distribution and submicron chemical composition measured at SNS. The hygroscopic case observed during SLOPE I showed an increase in the particle backscatter coefficient at 355 and 532 nm with relative humidity (RH ranged between 78 and 98 %), but also a decrease in the backscatter-related Ångström exponent (AE) and particle linear depolarization ratio (PLDR), indicating that the particles became larger and more spherical due to hygroscopic processes. Vertical and horizontal wind analysis is performed by means of a co-located Doppler lidar system, in order to evaluate the horizontal and vertical dynamics of the air masses. Finally, the Hänel parameterizaPublished by Copernicus Publications on behalf of the European Geosciences Union. 7002A. E. Bedoya-Velásquez et al.: Hygroscopic growth study in the framework of the SLOPE I campaign tion is applied to experimental data for both stations, and we found good agreement on γ measured with remote sensing (γ 532 = 0.48 ± 0.01 and γ 355 = 0.40 ± 0.01) with respect to the values calculated using Mie theory (γ 532 = 0.53 ± 0.02 and γ 355 = 0.45 ± 0.02), with relative differences between measurements and simulations lower than 9 % at 532 nm and 11 % at 355 nm.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.