We summarize our Raman lidar observations which were carried out in Europe, Asia, and Africa during the past 10 years, with focus on particle extinction‐to‐backscatter ratios (lidar ratios) and ...Ångström exponents. For the first time, we present statistics on lidar ratios for almost all climatically relevant aerosol types solely based on Raman lidar measurements. Sources of continental particles were in North America and Europe, the Sahara, and south and Southeast and east Asia. The North Atlantic Ocean, and the tropical and South Indian Ocean were the sources of marine particles. The statistics are complemented with lidar ratios describing aged forest fire smoke and pollution from polar regions (Arctic haze) after long‐range transport. In addition, we present particle Ångström exponents for the wavelength range from 355 to 532 nm and from 532 to 1064 nm. We compare our data set of lidar ratios to the recently published AERONET (Aerosol Robotic Network) lidar ratio climatology. That climatology is based on aerosol scattering modeling in which AERONET Sun photometer observations serve as input. Raman lidar measurements of extinction‐to‐backscatter ratios of Saharan dust and urban aerosols differ significantly from the numbers obtained with AERONET Sun photometers. There are also differences for some of the Ångström exponents. Further comparison studies are needed to reveal the reason for the observed differences.
A combined lidar‐photometer method that permits the retrieval of vertical profiles of ash and non‐ash (fine‐mode) particle mass concentrations is presented. By using a polarization lidar, the ...contributions of non‐ash and ash particles to total particle backscattering and extinction are separated. Sun photometer measurements of the ratio of particle volume concentration to particle optical thickness (AOT) for fine and coarse mode are then used to convert the non‐ash and ash extinction coefficients into respective fine‐mode and ash particle mass concentrations. The method is applied to European Aerosol Research Lidar Network (EARLINET) and Aerosol Robotic Network (AERONET) Sun photometer observations of volcanic aerosol layers at Cabauw, Netherlands, and Hamburg, Munich, and Leipzig, Germany, after the strong eruptions of the Icelandic Eyjafjallajökull volcano in April and May 2010. A consistent picture in terms of photometer‐derived fine‐ and coarse‐mode AOTs and lidar‐derived non‐ash and ash extinction profiles is found. The good agreement between the fine‐ to coarse‐mode AOT ratio and non‐ash to ash AOT ratio (<10% difference) in several cases corroborates the usefulness of the new retrieval technique. The main phases of the evolution of the volcanic aerosol layers over central Europe from 16 April to 17 May 2010 are characterized in terms of optical properties and mass concentrations of fine fraction and ash particles. Maximum coarse‐mode 500 nm AOTs were of the order of 1.0–1.2. Ash concentrations and column mass loads reached maximum values around 1500 μg/m3 and 1750 mg/m2, respectively, on 16–17 April 2010. In May 2010, the maximum ash loads were lower by at least 50%. A critical aspect of the entire retrieval scheme is the high uncertainty in the mass‐to‐extinction conversion for fresh volcanic plumes with an unknown concentration of particles with radii >15 μm.
Key Points
New lidar technique to separate volcanic sulfate and ash particles
Observation of the evolution of volcanic aerosols over central Europe
Synergistic EARLINET lidar and AERONET photometer observations
In this paper we describe the EARLINET Single Calculus Chain (SCC), a tool for the automatic analysis of lidar measurements. The development of this tool started in the framework of EARLINET-ASOS ...(European Aerosol Research Lidar Network – Advanced Sustainable Observation System); it was extended within ACTRIS (Aerosol, Clouds and Trace gases Research InfraStructure Network), and it is continuing within ACTRIS-2. The main idea was to develop a data processing chain that allows all EARLINET stations to retrieve, in a fully automatic way, the aerosol backscatter and extinction profiles starting from the raw lidar data of the lidar systems they operate. The calculus subsystem of the SCC is composed of two modules: a pre-processor module which handles the raw lidar data and corrects them for instrumental effects and an optical processing module for the retrieval of aerosol optical products from the pre-processed data. All input parameters needed to perform the lidar analysis are stored in a database to keep track of all changes which may occur for any EARLINET lidar system over the time. The two calculus modules are coordinated and synchronized by an additional module (daemon) which makes the whole analysis process fully automatic. The end user can interact with the SCC via a user-friendly web interface. All SCC modules are developed using open-source and freely available software packages. The final products retrieved by the SCC fulfill all requirements of the EARLINET quality assurance programs on both instrumental and algorithm levels. Moreover, the manpower needed to provide aerosol optical products is greatly reduced and thus the near-real-time availability of lidar data is improved. The high-quality of the SCC products is proven by the good agreement between the SCC analysis, and the corresponding independent manual retrievals. Finally, the ability of the SCC to provide high-quality aerosol optical products is demonstrated for an EARLINET intense observation period.
The formation of the ice phase in tropical altocumulus has been studied with multiwavelength aerosol‐cloud Raman lidar, wind Doppler lidar, and radiosonde, providing information on geometrical and ...optical properties, cloud phase, cloud top temperature, updraft and downdraft velocity, and fall speed of ice crystals. The observations were conducted at Praia (15°N, 23.5°W), Cape Verde, in the tropical North Atlantic in the framework of the Saharan Mineral Dust Experiment (SAMUM) project in January and February 2008. More than 200 different altocumulus layers were analyzed. The coldest liquid cloud had a temperature of −36°C and appeared at a height of 9800 m. Tropical altocumulus is found to be geometrically (262 ± 137 m) and optically thin (0.69 ± 0.61), mostly short‐lived, and horizontally small with extents of less than 50 km in 80% of the cases. A clear relationship between the occurrence of the ice phase in altocumulus and cloud top temperature is observed, even more clear after the removal of effects of cloud seeding, which is found to be an important process of ice production in lower layers of multilayer altocumulus systems. Because almost all altocumulus layers (99%) showed a liquid cloud top (region in which ice nucleation begins), we conclude that deposition and condensation ice nucleation are unimportant processes during the initial phase of altocumulus glaciation. A pronounced impact of aerosols such as mineral particles known to be favorable ice nuclei is not found in this region with strong dust‐smoke outbreaks from Africa. The different phases of an almost complete life cycle of an altocumulus were monitored over 5 hours. The observed processes of droplet and ice formation are discussed based on height‐resolved depolarization‐ratio (cloud phase) and vertical‐velocity time series.
More than 2300 observed cloud layers were analyzed to investigate the impact of aged Saharan dust on heterogeneous ice formation. The observations were performed with a polarization/Raman lidar at ...the European Aerosol Research Lidar Network site of Leipzig, Germany (51.3°N, 12.4°E) from February 1997 to June 2008. The statistical analysis is based on lidar‐derived information on cloud phase (liquid water, mixed phase, ice cloud) and cloud top height, cloud top temperature, and vertical profiles of dust mass concentration calculated with the Dust Regional Atmospheric Modeling system. Compared to dust‐free air masses, a significantly higher amount of ice‐containing clouds (25%–30% more) was observed for cloud top temperatures from −10°C to −20°C in air masses that contained mineral dust. The midlatitude lidar study is compared with our SAMUM lidar study of tropical stratiform clouds at Cape Verde in the winter of 2008. The comparison reveals that heterogeneous ice formation is much stronger over central Europe and starts at higher temperatures than over the tropical station. Possible reasons for the large difference are discussed.
More than 130 observation days of the horizontal and vertical extent of Saharan dust intrusions over Europe during the period May 2000 to December 2002 were studied by means of a coordinated lidar ...network in the frame of the European Aerosol Research Lidar Network (EARLINET). The number of dust events was greatest in late spring, summer, and early autumn periods, mainly in southern (S) and southeastern (SE) Europe. Multiple aerosol dust layers of variable thickness (300–7500 m) were observed. The center of mass of these layers was located in altitudes between 850 and 8000 m. However, the mean thickness of the dust layer typically stayed around 1500–3400 m and the corresponding mean center of mass ranged from 2500 to 6000 m. In exceptional cases, dust aerosols reached northwestern (NW), northern (N), or northeastern (NE) Europe, penetrating the geographical area located between 4°W–28°E (longitude) and 38°N–58°N (latitude). Mean aerosol optical depths (AOD), extinction‐to‐backscatter ratios (lidar ratios, LR), and linear depolarization ratios of desert aerosols ranged from 0.1 to 0.25 at the wavelength of 355 or 351 nm, 30 to 80 sr at 355 or 351 nm, and 10 to 25% at 532 nm, respectively, within the lofted dust plumes. In these plumes typical Saharan dust backscatter coefficients ranged from 0.5 to 2 Mm−1sr−1. Southern European stations presented higher variability of the LR values and the backscatter‐related Ångström exponent values (BRAE) (LR: 20–100 sr; BRAE: −0.5 to 3) than northern ones (LR: 30–80 sr; BRAE: −0.5 to 1).
The optically thickest volcanic ash plume ever measured over Germany was monitored with multiwavelength Raman lidars and Sun photometer at Leipzig and Munich. When this ash layer, originating from ...the Eyjafjoll eruptions in southern Iceland, crossed Leipzig between 2.5 and 6 km height on 16 April 2010, the total 500 nm aerosol optical depth reached 1.0, and the ash–related optical depth was about 0.7. Volume light–extinction coefficients (40–75–minute mean values) measured over Leipzig and Munich at 355 and 532 nm reached values of 400–600 Mm−1 and ash mass concentrations were on the order of 1000 ± 350 μg/m3 in the center of the main ash layer. Extinction–to–backscatter ratios ranged from 55 ± 5 sr (Munich) to 60 ± 5 sr (Leipzig) in the main ash layer, and the particle linear depolarization ratio was close to 0.35 at both wavelengths. Rather low photometer–derived Ångström exponents (500–1640 nm wavelength range) indicated the presence of a significant amount of large ash particles with diameters >20 μm.
To realize the promise of improved predictions of hazardous weather such as flash floods, wind storms, fog, and poor air quality from high-resolution mesoscale models, the forecast models must be ...initialized with an accurate representation of the current state of the atmosphere, but the lowest few kilometers are hardly accessible by satellite, especially in dynamically active conditions. We report on recent European developments in the exploitation of existing ground-based profiling instruments so that they are networked and able to send data in real time to forecast centers. The three classes of instruments are i) automatic lidars and ceilometers providing backscatter profiles of clouds, aerosols, dust, fog, and volcanic ash, the last two being especially important for air traffic control; ii) Doppler wind lidars deriving profiles of wind, turbulence, wind shear, wind gusts, and low-level jets; and iii) microwave radiometers estimating profiles of temperature and humidity in nearly all weather conditions. The project includes collaboration from 22 European countries and 15 European national weather services, which involves the implementation of common operating procedures, instrument calibrations, data formats, and retrieval algorithms. Currently, data from 265 ceilometers in 19 countries are being distributed in near–real time to national weather forecast centers; this should soon rise to many hundreds. One wind lidar is currently delivering real time data rising to 5 by the end of 2019, and the plan is to incorporate radiometers in 2020. Initial data assimilation tests indicate a positive impact of the new data.
The Eyjafjallajökull volcano in Iceland erupted explosively on 14 April 2010, emitting a plume of ash into the atmosphere. The ash was transported from Iceland toward Europe where mostly cloud‐free ...skies allowed ground‐based lidars at Chilbolton in England and Leipzig in Germany to estimate the mass concentration in the ash cloud as it passed overhead. The UK Met Office's Numerical Atmospheric‐dispersion Modeling Environment (NAME) has been used to simulate the evolution of the ash cloud from the Eyjafjallajökull volcano during the initial phase of the ash emissions, 14–16 April 2010. NAME captures the timing and sloped structure of the ash layer observed over Leipzig, close to the central axis of the ash cloud. Relatively small errors in the ash cloud position, probably caused by the cumulative effect of errors in the driving meteorology en route, result in a timing error at distances far from the central axis of the ash cloud. Taking the timing error into account, NAME is able to capture the sloped ash layer over the UK. Comparison of the lidar observations and NAME simulations has allowed an estimation of the plume height time series to be made. It is necessary to include in the model input the large variations in plume height in order to accurately predict the ash cloud structure at long range. Quantitative comparison with the mass concentrations at Leipzig and Chilbolton suggest that around 3% of the total emitted mass is transported as far as these sites by small (<100 μm diameter) ash particles.
Key Points
Quantitative prediction of volcanic ash concentrations
Estimation of distal fine ash fraction
Reconstruction of volcano plume height time series
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