Aerosol optical and microphysical retrievals from a hybrid multiwavelength lidar data set - DISCOVER-AQ 2011

© Author(s) 2014. This open access work is distributed under the Creative Commons Attribution 3.0 License (https://creativecommons.org/licenses/by/3.0/).Retrievals of aerosol microphysical properties (effective radius, volume and surface-area concentrations) and aerosol optical properties (complex index of refraction and single-scattering albedo) were obtained from a hybrid multiwavelength lidar data set for the first time. In July 2011, in the Baltimore-Washington DC region, synergistic profiling of optical and microphysical properties of aerosols with both airborne (in situ and remote sensing) and ground-based remote sensing systems was performed during the first deployment of DISCOVER-AQ. The hybrid multiwavelength lidar data set combines ground-based elastic backscatter lidar measurements at 355 nm with airborne High-Spectral-Resolution Lidar (HSRL) measurements at 532 nm and elastic backscatter lidar measurements at 1064 nm that were obtained less than 5 km apart from each other. This was the first study in which optical and microphysical retrievals from lidar were obtained during the day and directly compared to AERONET and in situ measurements for 11 cases. Good agreement was observed between lidar and AERONET retrievals. Larger discrepancies were observed between lidar retrievals and in situ measurements obtained by the aircraft and aerosol hygroscopic effects are believed to be the main factor in such discrepancies.Peer reviewe

EARLINET: towards an advanced sustainable European aerosol lidar network

The European Aerosol Research Lidar Network, EARLINET, was founded in 2000 as a research project for establishing a quantitative, comprehensive, and statistically significant database for the horizontal, vertical, and temporal distribution of aerosols on a continental scale. Since then EARLINET has continued to provide the most extensive collection of ground-based data for the aerosol vertical distribution over Europe. This paper gives an overview of the network's main developments since 2000 and introduces the dedicated EARLINET special issue, which reports on the present innovative and comprehensive technical solutions and scientific results related to the use of advanced lidar remote sensing techniques for the study of aerosol properties as developed within the network in the last 13 years. Since 2000, EARLINET has developed greatly in terms of number of stations and spatial distribution: from 17 stations in 10 countries in 2000 to 27 stations in 16 countries in 2013. EARLINET has developed greatly also in terms of technological advances with the spread of advanced multiwavelength Raman lidar stations in Europe. The developments for the quality assurance strategy, the optimization of instruments and data processing, and the dissemination of data have contributed to a significant improvement of the network towards a more sustainable observing system, with an increase in the observing capability and a reduction of operational costs. Consequently, EARLINET data have already been extensively used for many climatological studies, long-range transport events, Saharan dust outbreaks, plumes from volcanic eruptions, and for model evaluation and satellite data validation and integration. Future plans are aimed at continuous measurements and near-real-time data delivery in close cooperation with other ground-based networks, such as in the ACTRIS (Aerosols, Clouds, and Trace gases Research InfraStructure Network) www.actris.net, and with the modeling and satellite community, linking the research community with the operational world, with the aim of establishing of the atmospheric part of the European component of the integrated global observing system.Peer ReviewedPostprint (published version

Simulation and observations of stratospheric aerosols from the 2009 Sarychev volcanic eruption

We used a general circulation model of Earth’s climate to conduct simulations of the 12-16 June 2009 eruption of Sarychev volcano (48.1°N, 153.2°E). The model simulates the formation and transport of the stratospheric sulfate aerosol cloud from the eruption and the resulting climate response. We compared optical depth results from these simulations with limb scatter measurements from the Optical Spectrograph and InfraRed Imaging System (OSIRIS), in situ measurements from balloon-borne instruments lofted from Laramie, Wyoming (41.3°N, 105.7°W), and five lidar stations located throughout the Northern Hemisphere. The aerosol cloud covered most of the Northern Hemisphere, extending slightly into the tropics, with peak backscatter measured between 12 and 16 km in altitude. Aerosol concentrations returned to near background levels by Spring, 2010. After accounting for expected sources of discrepancy between each of the data sources, the magnitudes and spatial distributions of aerosol optical depth due to the eruption largely agree. In conducting the simulations, we likely overestimated both particle size and the amount of SO2 injected into the stratosphere, resulting in modeled optical depth values that were a factor of 2-4 too high. Model results of optical depth due to the eruption show a peak too late in high latitudes and too early in low latitudes, suggesting a problem with stratospheric circulation in the model. The model also shows a higher annual decay rate in optical depth than is observed, showing an inaccuracy in seasonal deposition rates. The modeled deposition rate of sulfate aerosols from the Sarychev eruption is higher than the rate calculated for aerosols from the 1991 eruption of Mt. Pinatubo

Linear Estimation of Particle Bulk Parameters from Multi-Wavelength Lidar Measurements

An algorithm for linear estimation of aerosol bulk properties such as particle volume, effective radius and complex refractive index from multiwavelength lidar measurements is presented. The approach uses the fact that the total aerosol concentration can well be approximated as a linear combination of aerosol characteristics measured by multiwavelength lidar. Therefore, the aerosol concentration can be estimated from lidar measurements without the need to derive the size distribution, which entails more sophisticated procedures. The definition of the coefficients required for the linear estimates is based on an expansion of the particle size distribution in terms of the measurement kernels. Once the coefficients are established, the approach permits fast retrieval of aerosol bulk properties when compared with the full regularization technique. In addition, the straightforward estimation of bulk properties stabilizes the inversion making it more resistant to noise in the optical data. Numerical tests demonstrate that for data sets containing three aerosol backscattering and two extinction coefficients (so called 3 + 2 ) the uncertainties in the retrieval of particle volume and surface area are below 45% when input data random uncertainties are below 20 %. Moreover, using linear estimates allows reliable retrievals even when the number of input data is reduced. To evaluate the approach, the results obtained using this technique are compared with those based on the previously developed full inversion scheme that relies on the regularization procedure. Both techniques were applied to the data measured by multiwavelength lidar at NASA/GSFC. The results obtained with both methods using the same observations are in good agreement. At the same time, the high speed of the retrieval using linear estimates makes the method preferable for generating aerosol information from extended lidar observations. To demonstrate the efficiency of the method, an extended time series of observations acquired in Turkey in May 2010 was processed using the linear estimates technique permitting, for what we believe to be the first time, temporal-height distributions of particle parameters

Optical-microphysical Properties of Saharan Dust Aerosols and Composition Relationship Using a Multi-wavelength Raman Lidar, in Situ Sensors and Modelling: a Case Study Analysis

A strong Saharan dust event that occurred over the city of Athens, Greece (37.9° N, 23.6° E) between 27 March and 3 April 2009 was followed by a synergy of three instruments: a 6-wavelength Raman lidar, a CIMEL sun-sky radiometer and the MODIS sensor. The BSC-DREAM model was used to forecast the dust event and to simulate the vertical profiles of the aerosol concentration. Due to mixture of dust particles with low clouds during most of the reported period, the dust event could be followed by the lidar only during the cloud-free day of 2 April 2009. The lidar data obtained were used to retrieve the vertical profile of the optical (extinction and backscatter coefficients) properties of aerosols in the troposphere. The aerosol optical depth (AOD) values derived from the CIMEL ranged from 0.33-0.91 (355 nm) to 0.18-0.60 (532 nm), while the lidar ratio (LR) values retrieved from the Raman lidar ranged within 75-100 sr (355 nm) and 45-75 sr (532 nm). Inside a selected dust layer region, between 1.8 and 3.5 km height, mean LR values were 83 ± 7 and 54 ± 7 sr, at 355 and 532 nm, respectively, while the Ångström-backscatter-related (ABR 355/532) and Ångström-extinction-related (AER 355/532) were found larger than 1 (1.17 ± 0.08 and 1.11 ± 0.02, respectively), indicating mixing of dust with other particles. Additionally, a retrieval technique representing dust as a mixture of spheres and spheroids was used to derive the mean aerosol microphysical properties (mean and effective radius, number, surface and volume density, and mean refractive index) inside the selected atmospheric layers. Thus, the mean value of the retrieved refractive index was found to be 1.49( ± 0.10) + 0.007( ± 0.007)i, and that of the effective radiuses was 0.30 ± 0.18 μm. The final data set of the aerosol optical and microphysical properties along with the water vapor profiles obtained by Raman lidar were incorporated into the ISORROPIA II model to provide a possible aerosol composition consistent with the retrieved refractive index values. Thus, the inferred chemical properties showed 12-40% of dust content, sulfate composition of 16-60%, and organic carbon content of 15-64%, indicating a possible mixing of dust with haze and smoke. PM10 concentrations levels, PM10 composition results and SEM-EDX (Scanning Electron Microscope-Energy Dispersive X-ray) analysis results on sizes and mineralogy of particles from samples during the Saharan dust transport event were used to evaluate the retrieval

Retrieval of spatio-temporal distributions of particle parameters from multiwavelength lidar measurements using the linear estimation technique and comparison with AERONET

The results of the application of the linear estimation technique to multiwavelength Raman lidar measurements performed during the summer of 2011 in Greenbelt, MD, USA, are presented. We demonstrate that multiwavelength lidars are capable not only of providing vertical profiles of particle properties but also of revealing the spatio-temporal evolution of aerosol features. The nighttime 3β + 1α lidar measurements on 21 and 22 July were inverted to spatio-temporal distributions of particle microphysical parameters, such as volume, number density, effective radius and the complex refractive index. The particle volume and number density show strong variation during the night, while the effective radius remains approximately constant. The real part of the refractive index demonstrates a slight decreasing tendency in a region of enhanced extinction coefficient. The linear estimation retrievals are stable and provide time series of particle parameters as a function of height at 4 min resolution. AERONET observations are compared with multiwavelength lidar retrievals showing good agreement

Observations of aerosol and liquid-water clouds with Dual-Field-of-View Polarization Lidar: A ground-based view on aerosol-cloud interactions

The book presents my PhD thesis, which is about aerosol-cloud interactions by means of a dual-field-of-view polarization lidar. Aerosol-cloud interactions (ACI) are a big challenge to quantify the overall effect of human activities on the radiative, heat, and precipitation budgets of the atmosphere. New observational capabilities are demanded. To study the influence of aerosol particles on cloud microphysics an analysis scheme composed of newly-developed arrays is introduced. The retrieval of microphysical properties of liquid-water clouds and of the aerosol particles below the clouds from lidar observations, in a practical and replicable way, is the major challenge tackled in this work. A lidar-based approach to derive liquid-water cloud microphysical properties from dual-field-of-view (DFOV) depolarization measurements is introduced. In addition, a new method to accurately obtain the aerosol properties below cloud layers was developed and implemented into the analysis infrastructure. Comparisons with alternative observational and modeling approaches corroborate the accuracy of both methods. The number concentration of cloud condensation nuclei (CCN) is derived from the aerosol particle extinction coefficient below the cloud, and in combination with the cloud-microphysics retrieval, they provide an aerosol-cloud scene, which allow us to study ACI. Long-term observations at the pristine location of Punta Arenas (PA), Chile, and at the polluted site of Dushanbe (DB), Tajikistan, were analyzed for this purpose. On average, similar values of cloud droplet and below-cloud CCN number concentrations, in the range of 10--150~cm$^{-3}$, were observed at PA. At DB, larger cloud droplet number concentrations were observed, in the order of 200--400 cm-3 but much larger CCN concentrations of about 700--900 cm-3 were found. The so-called ACI index was assessed from the collected data sets. The most robust estimate of the index was obtained when calculating monthly averages over the whole measurement periods, fourteen months at PA and seven months at DB. Values of 0.83 +/- 0.20 and 0.57+/ 0.26 were derived at PA and DB, respectively, and they were used to estimate the radiative forcing due to the Twomey effect. A radiative cooling from -0.70 to -0.17 Wm-2 for PA and between -1.89 and -0.66 Wm-2 for DB is found. These results agree with global estimates of the cloud-mediated aerosol effect but are slightly larger than those values usually found at the specific locations considered. Furthermore, the results obtained at PA show the relevance of updraft movements to trigger ACI. When considering only updraft-dominated periods, the ACI index is up to 50% larger than when no wind information is considered. The new capabilities illuminated during this work may provide a big help for estimations of the cloud-mediated radiative effect and may provide a baseline to confront models dealing with cloud microphysics in future studies.:1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1 2 Aerosol, clouds and their interaction - State of the art and research questions. . 7 2.1 Aerosol and clouds . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 2.1.1 Aerosol effect on liquid-water clouds . . . . . . . . . . . . . . . . . . . . . . . . .8 2.1.2 Aerosol effect on ice-containing clouds . . . . . . . . . . . . . . . . . . . . . . .9 2.1.3 Cloud processes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. 10 2.1.4 Modeling droplet number concentration Nd . . . . . . . . . . . . . . . . . . 10 2.2 Aerosol radiative effect via ACI in liquid-water clouds . . . . . . . . . . . . . .11 2.2.1 Aerosol-cloud-interaction index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 2.2.2 Observational approaches for the ACI index. . . . . . . . . . . . . . . . . . . .14 2.2.3 Strategies to evaluate the ACI index from observations . . . . . . . . . . .16 2.2.4 ACI studies based on lidar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 2.3 Research questions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 3 Lidar measurements of aerosol-cloud interaction – Overview of applied methodologies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .23 3.1 Multiple-scattering lidar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .23 3.2 DFOV-Raman technique . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24 3.3 Single-FOV polarization lidar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .25 3.3.1 Comparison between DFOV-Raman and SFOV-Depol methods . . . 27 3.4 Dual-FOV depolarization approach . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 3.4.1 Calibration of the lidar system . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 3.4.2 DFOV-Depol measurement cases . . . . . . . . . . . . . . . . . . . . . . . . . . 31 3.5 Implementation of the DFOV-Depol approach into the standardized lidar sys- tem Polly . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .33 4 Research results. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .37 4.1 First publication: Polarization lidar: an extended three-signal calibration approach . . . . . . .39 4.2 Second publication: The dual-field-of-view polarization lidar technique: A new concept in monitoring aerosol effects in liquid-water clouds – Theoretical framework . . . . . . . . .59 4.3 Third publication: The dual-field-of-view polarization lidar technique: A new concept in monitoring aerosol effects in liquid-water clouds – Case studies . . . . . . . . . . . . . . . .79 5 Discussion and further applications – Long-term observations of aerosol- cloud interaction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .101 5.1 Observations on cloud scale . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .102 5.2 Long-term results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107 5.2.1 Comparison of DFOV-Depol products with available estimations and observations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .108 5.3 Assessment of the ACI index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110 5.4 Relevance of the ACI index for the radiative effect . . . . . . . . . . . . 112 6 Summary and outlook . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .117 Appendix A: Aerosol properties with lidar . . . . . . . . . . . . . . . . . . . .125 A.1 Lidar principles of elastic and Raman lidar . . . . . . . . . . . . . . . .125 A.2 Raman lidar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127 A.2.1 Retrieval of extinction coefficient . . . . . . . . . . . . . . . . . . . . . 128 A.2.2 Retrieval of backscattering coefficient. . . . . . . . . . . . . . . . . . 128 A.2.3 Bottom-up approximation for Raman Signals . . . . .. . . . . . . 129 A.2.4 Evaluation of Raman methods. . . . . . . . . . . . . . . . . . . . . . . 130 A.3 Elastic Lidar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .132 A.3.1 Klett-Fernald Solution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 132 A.3.2 Quasi-backscattering for high resolved retrievals. . . . . . . . . 133 A.3.3 Bottom-up approximation for elastic signals . . . . . . . . . . . . 135 A.3.4 Evaluation of methods based on elastic lidar. . . . . . . . . . . . 137 A.3.5 Microphysical properties from optical properties. . . . . . . . . . 139 Appendix B Characterization of DFOV-Depol lidar . . . . . . . . . . . . 143 B.1 Transmission ratio based on long-term analysis . . . . . . . . . . . 144 Appendix C: Author’s contributions to the three publications . . . . 149 Appendix D Lists . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .151 D.1 List of Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .151 D.2 List of Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 154 D.3 List of Symbols (excluding cumulative part) . . . . . . . . . . 156 D.4 List of Abbreviations . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

Optical and microphysical characterization of aerosol layers over South Africa by means of multi-wavelength depolarization and Raman lidar measurements

© 2016 The Author(s). Published by Copernicus Publications on behalf of the European Geosciences Union. This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence ( https://creativecommons.org/licenses/by/3.0/ ), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.Optical and microphysical properties of different aerosol types over South Africa measured with a multi-wavelength polarization Raman lidar are presented. This study could assist in bridging existing gaps relating to aerosol properties over South Africa, since limited long-term data of this type is available for this region. The observations were performed under the framework of the EUCAARI campaign in Elandsfontein. The multi-wavelength PollyXT Raman lidar system was used to determine vertical profiles of the aerosol optical properties, i.e. extinction and backscatter coefficients, Ångström exponents, lidar ratio and depolarization ratio. The mean microphysical aerosol properties, i.e. effective radius and single scattering albedo were retrieved with an advanced inversion algorithm. Clear differences were observed for the intensive optical properties of atmospheric layers of biomass burning and urban/industrial aerosols. Our results reveal a wide range of optical and microphysical parameters for biomass burning aerosols. This indicates probable mixing of biomass burning aerosols with desert dust particles, as well as the possible continuous influence of urban/industrial aerosol load in the region. The lidar ratio at 355 nm, the lidar ratio at 532 nm, the linear particle depolarization ratio at 355 nm and the extinction-related Ångström exponent from 355 to 532 nm were 52 ± 7 sr; 41 ± 13 sr; 0.9 ± 0.4 % and 2.3 ± 0.5, respectively for urban / industrial aerosols, while these values were 92 ± 10 sr; 75 ± 14; 3.2 ± 1.3 % and 1.7 ± 0.3 respectively for biomass burning aerosols layers. Biomass burning particles are larger and slightly less absorbing compared to urban / industrial aerosols. The particle effective radius were found to be 0.10 ± 0.03 μm, 0.17 ± 0.04 μm and 0.13 ± 0.03 μm for urban/industrial, biomass burning, and mixed aerosols, respectively, while the single scattering albedo at 532 nm were 0.87 ± 0.06, 0.90 ± 0.06, and 0.88 ± 0.07 (at 532 nm), respectively for these three types of aerosols. Our results were within the same range of previously reported values.Peer reviewedFinal Published versio

Retrieval of aerosol profiles combining sunphotometer and ceilometer measurements in GRASP code

This is a preprint version of article accepted "Roman, A.; et al. Retrieval of aerosol profiles combining sunphotometer and ceilometer measurements in GRASP code. Atmospheric Research, 204: 161-177 (2018). DOI: https://doi.org/10.1016./j.atmosres.2018.01.021".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 µm3/cm3 (12%) and 5.8 µm3/cm3 (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%.This work was supported by the Andalusia Regional Government (project P12-RNM-2409) and by the “Consejería de Educación” of “Junta de Castilla y León” (project VA100U14); the Spanish Ministry of Economy and Competitiveness under the projects, CMT2015-66742-R, CGL2016-81092-R and “Juan de la Cierva-Formación” program (FJCI-2014-22052); and the European Union's Horizon 2020 research and innovation programme through project ACTRIS-2 (grant agreement no 654109) and the Marie Curie Rise action GRASP-ACE (grant agreement no 778349). The authors thankfully acknowledge the FEDER program for the instrumentation used in this work. COST Action TOPROF (ES1303), supported by COST (European Cooperation in Science and Technology), is also acknowledged

Extinction-related Angström exponent characterization of submicrometric volume fraction in atmospheric aerosol particles

The AEAOD– ΔAEAOD grid proposed by Gobbi et al. (2007) is a graphical method used to visually represent the spectral characterization of aerosol optical depth (AOD), i.e. Angström exponent (AE) and its curvature, in order to infer the fine mode contribution (η) to the total AOD and the size of the fine mode aerosol particles. Perrone et al. (2014) applied this method for the wavelengths widely used in lidar measurements. However, in neither case does the method allow for a direct relationship between η and the fine mode fraction contribution to the total aerosol population. Some discussions are made regarding the effect of shape and composition to the classical AE-ΔAE plot. The potential use of particle backscatter measurements, widely used in aerosol characterization methods together with extinction measurements, is also discussed in the AE-ΔAE grid context. A modification is proposed that yields the submicron contribution to the total volume concentration by using particle extinction data, and a comparison to experimental measurements is made. Our results indicate that the use of a modified AE-ΔAE grid plot to directly obtain submicrometric and micrometric mode fraction to the total aerosol population is feasible if a volume-based bimodal particle size distribution is used instead of a number-based one.Andalusia Regional Government through project P12-RNM-2409Spanish Ministry of Sciences, Innovation and Universities (CGL2016-81092 and CGL2017 -90884 - REDT