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Large mesospheric ice particles at exceptionally high altitudes
We here report on the characteristics of exceptionally high Noctilucent clouds (NLC) that were detected with rocket photometers during the ECOMA/MASS campaign at Andøya, Norway 2007. The results from three separate flights are shown and discussed in connection to lidar measurements. Both the lidar measurements and the large difference between various rocket passages through the NLC show that the cloud layer was inhomogeneous on large scales. Two passages showed a particularly high, bright and vertically extended cloud, reaching to approximately 88 km. Long time series of lidar measurements show that NLC this high are very rare, only one NLC measurement out of thousand reaches above 87 km. The NLC is found to consist of three distinct layers. All three were bright enough to allow for particle size retrieval by phase function analysis, even though the lowest layer proved too horizontally inhomogeneous to obtain a trustworthy result. Large particles, corresponding to an effective radius of 50 nm, were observed both in the middle and top of the NLC. The present cloud does not comply with the conventional picture that NLC ice particles nucleate near the temperature minimum and grow to larger sizes as they sediment to lower altitudes. Strong up-welling, likely caused by gravity wave activity, is required to explain its characteristics.
The automated multiwavelength Raman polarization and water-vapor lidar PollyXT: The neXT generation
The atmospheric science community demands autonomous and quality-assured vertically resolved measurements of aerosol and cloud properties. For this purpose, a portable lidar called Polly was developed at TROPOS in 2003. The lidar system was continuously improved with gained experience from the EARLINET community, involvement in worldwide field campaigns, and international institute collaborations within the last 10 years. Here we present recent changes of the setup of the portable multiwavelength Raman and polarization lidar PollyXT and discuss the improved capabilities of the system by means of a case study. The latest system developments include an additional near-range receiver unit for Raman measurements of the backscatter and extinction coefficient down to 120 m above ground, a water-vapor channel, and channels for simultaneous measurements of the particle linear depolarization ratio at 355 and 532 nm. Quality improvements were achieved by systematically following the EARLINET guidelines and the international PollyNET quality assurance developments. A modified ship radar ensures measurements in agreement with air-traffic safety regulations and allows for 24∕7 monitoring of the atmospheric state with PollyXT.
EARLINET instrument intercomparison campaigns: Overview on strategy and results
This paper introduces the recent European Aerosol Research Lidar Network (EARLINET) quality-assurance efforts at instrument level. Within two dedicated campaigns and five single-site intercomparison activities, 21 EARLINET systems from 18 EARLINET stations were intercompared between 2009 and 2013. A comprehensive strategy for campaign setup and data evaluation has been established. Eleven systems from nine EARLINET stations participated in the EARLINET Lidar Intercomparison 2009 (EARLI09). In this campaign, three reference systems were qualified which served as traveling standards thereafter. EARLINET systems from nine other stations have been compared against these reference systems since 2009. We present and discuss comparisons at signal and at product level from all campaigns for more than 100 individual measurement channels at the wavelengths of 355, 387, 532, and 607 nm. It is shown that in most cases, a very good agreement of the compared systems with the respective reference is obtained. Mean signal deviations in predefined height ranges are typically below ±2 %. Particle backscatter and extinction coefficients agree within ±2  ×  10−4 km−1 sr−1 and ± 0.01 km−1, respectively, in most cases. For systems or channels that showed larger discrepancies, an in-depth analysis of deficiencies was performed and technical solutions and upgrades were proposed and realized. The intercomparisons have reinforced confidence in the EARLINET data quality and allowed us to draw conclusions on necessary system improvements for some instruments and to identify major challenges that need to be tackled in the future.
Vertical profiles of aerosol mass concentration derived by unmanned airborne in situ and remote sensing instruments during dust events
In situ measurements using unmanned aerial vehicles (UAVs) and remote sensing observations can independently provide dense vertically resolved measurements of atmospheric aerosols, information which is strongly required in climate models. In both cases, inverting the recorded signals to useful information requires assumptions and constraints, and this can make the comparison of the results difficult. Here we compare, for the first time, vertical profiles of the aerosol mass concentration derived from light detection and ranging (lidar) observations and in situ measurements using an optical particle counter on board a UAV during moderate and weak Saharan dust episodes. Agreement between the two measurement methods was within experimental uncertainty for the coarse mode (i.e. particles having radii > 0.5 μm), where the properties of dust particles can be assumed with good accuracy. This result proves that the two techniques can be used interchangeably for determining the vertical profiles of aerosol concentrations, bringing them a step closer towards their systematic exploitation in climate models.
Study of the tidal variations in mesospheric temperature at low and mid latitudes from WINDII and potassium lidar observations
Zonal mean daytime temperatures from the Wind Imaging Interferometer (WINDII) on the Upper Atmosphere Research Satellite (UARS) and nightly temperatures from a potassium (K) lidar are employed in the study of the tidal variations in mesospheric temperature at low and mid latitudes in the Northern Hemisphere. The analysis is applied to observations at 89 km height for winter solstice, December to February (DJF), at 55° N, and for May and November at 28° N. The WINDII results are based on observations from 1991 to 1997. The K-lidar observations for DJF at Kühlungsborn (54° N) were from 1996-1999, while those for May and November at Tenerife 28° N were from 1999. To avoid possible effects from year-to-year variability in the temperatures observed, as well as differences due to instrument calibration and observation periods, the mean temperature field is removed from the respective data sets, assuming that only tidal and planetary scale perturbations remain in the temperature residuals. The latter are then binned in 0.5 h periods and the individual data sets are fitted in a least-mean square sense to 12-h and 8-h harmonics, to infer semidiurnal and terdiurnal tidal parameters. Both the K-lidar and WINDII independently observed a strong semidiurnal tide in November, with amplitudes of 13 K and 7.4 K, respectively. Good agreement was also found in the tidal parameters derived from the two data sets for DJF and May. It was recognized that insufficient local time coverage of the two separate data sets could lead to an overestimation of the semidiurnal tidal amplitude. A combined ground-based/satellite data set with full diurnal local time coverage was created which was fitted to 24 h+ 12 h+8 h harmonics and a novel method applied to account for possible differences between the daytime and nighttime means. The results still yielded a strong semidiurnal tide in November at 28° N with an amplitude of 8.8 K which is twice the SD amplitude in May and DJF. The diurnal tidal parameters were practically the same at 28° N and 55° N, in November and DJF, respectively, with an amplitude of 6.5 K and peaking at ∼9h. The diurnal and semidiurnal amplitudes in May were about the same, 4 K, and 4.6 K, while the terdiurnal tide had the same amplitudes and phases in May and November at 28° N. Good agreement is found with other experimental data while models tend to underestimate the amplitudes.
EARLINET Single Calculus Chain – overview on methodology and strategy
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.
Seasonal variation of nocturnal temperatures between 1 and 105 km altitude at 54° N observed by lidar
Temperature soundings are performed by lidar at the mid-latitude station of Kühlungsborn (Germany, 54° N, 12° E). The profiles cover the complete range from the lower troposphere (~1 km) to the lower thermosphere (~105 km) by simultaneous and co-located operation of a Rayleigh-Mie-Raman lidar and a potassium resonance lidar. Observations have been done during 266 nights between June 2002 and July 2007, each of 3–15 h length. This large and unique data set provides comprehensive information on the altitudinal and seasonal variation of temperatures from the troposphere to the lower thermosphere. The remaining day-to-day-variability is strongly reduced by harmonic fits at constant altitude levels and a representative data set is achieved. This data set reveals a two-level mesopause structure with an altitude of about 86–87 km (~144 K) in summer and ~102 km (~170 K) during the rest of the year. The average stratopause altitude is ~48 km throughout the whole year, with temperatures varying between 258 and 276 K. From the fit parameters amplitudes and phases of annual, semi-annual, and quarter-annual variations are derived. The amplitude of the annual component is largest with amplitudes of up to 30 K in 85 km, while the quarter-annual variation is smallest and less than 3 K at all altitudes. The lidar data set is compared with ECMWF temperatures below about 70 km altitude and reference data from the NRLMSISE-00 model above. Apart from the temperature soundings the aerosol backscatter ratio is measured between 20 and 35 km. The seasonal variation of these values is presented here for the first time.
Dust mass, cloud condensation nuclei, and ice-nucleating particle profiling with polarization lidar: Updated POLIPHON conversion factors from global AERONET analysis
The POLIPHON (Polarization Lidar Photometer Networking) method permits the retrieval of particle number, surface area, and volume concentration for dust and non-dust aerosol components. The obtained microphysical properties are used to estimate height profiles of particle mass, cloud condensation nucleus (CCN) and ice-nucleating particle (INP) concentrations. The conversion of aerosol-type-dependent particle extinction coefficients, derived from polarization lidar observations, into the aerosol microphysical properties (number, surface area, volume) forms the central part of the POLIPHON computations. The conversion parameters are determined from Aerosol Robotic Network (AERONET) aerosol climatologies of optical and microphysical properties. In this article, we focus on the dust-related POLIPHON retrieval products and present an extended set of dust conversion factors considering all relevant deserts around the globe. We apply the new conversion factor set to a dust measurement with polarization lidar in Dushanbe, Tajikistan, in central Asia. Strong aerosol layering was observed with mineral dust advected from Kazakhstan (0-2km height), Iran (2-5km), the Arabian peninsula (5-7km), and the Sahara (8-10km). POLIPHON results obtained with different sets of conversion parameters were contrasted in this central Asian case study and permitted an estimation of the conversion uncertainties.
EARLINET Single Calculus Chain – technical – Part 1: Pre-processing of raw lidar data
In this paper we describe an automatic tool for the pre-processing of aerosol lidar data called ELPP (EARLINET Lidar Pre-Processor). It is one of two calculus modules of the EARLINET Single Calculus Chain (SCC), the automatic tool for the analysis of EARLINET data. ELPP is an open source module that executes instrumental corrections and data handling of the raw lidar signals, making the lidar data ready to be processed by the optical retrieval algorithms. According to the specific lidar configuration, ELPP automatically performs dead-time correction, atmospheric and electronic background subtraction, gluing of lidar signals, and trigger-delay correction. Moreover, the signal-to-noise ratio of the pre-processed signals can be improved by means of configurable time integration of the raw signals and/or spatial smoothing. ELPP delivers the statistical uncertainties of the final products by means of error propagation or Monte Carlo simulations. During the development of ELPP, particular attention has been payed to make the tool flexible enough to handle all lidar configurations currently used within the EARLINET community. Moreover, it has been designed in a modular way to allow an easy extension to lidar configurations not yet implemented. The primary goal of ELPP is to enable the application of quality-assured procedures in the lidar data analysis starting from the raw lidar data. This provides the added value of full traceability of each delivered lidar product. Several tests have been performed to check the proper functioning of ELPP. The whole SCC has been tested with the same synthetic data sets, which were used for the EARLINET algorithm inter-comparison exercise. ELPP has been successfully employed for the automatic near-real-time pre-processing of the raw lidar data measured during several EARLINET inter-comparison campaigns as well as during intense field campaigns.
3+2 + X : what is the most useful depolarization input for retrieving microphysical properties of non-spherical particles from lidar measurements using the spheroid model of Dubovik et al. (2006)?
The typical multiwavelength aerosol lidar data set for inversion of optical to microphysical parameters is composed of three backscatter coefficients (β) at 355, 532, and 1064 nm and two extinction coefficients (α) at 355 and 532 nm. This data combination is referred to as a 3β C 2α or 3 + 2 data set. This set of data is sufficient for retrieving some important microphysical particle parameters if the particles have spherical shape. Here, we investigate the effect of including the particle linear depolarization ratio (δ) as a third input parameter for the inversion of lidar data. The inversion algorithm is generally not used if measurements show values of d that exceed 0.10 at 532 nm, i.e. in the presence of nonspherical particles such as desert dust, volcanic ash, and, under special circumstances, biomass-burning smoke. We use experimental data collected with instruments that are capable of measuring d at all three lidar wavelengths with an inversion routine that applies the spheroidal light-scattering model of Dubovik et al. (2006) with a fixed axis-ratio distribution to replicate scattering properties of non-spherical particles. The inversion gives the fraction of spheroids required to replicate the optical data as an additional output parameter. This is the first systematic test of the effect of using all theoretically possible combinations of d taken at 355, 532, and 1064 nm as input in the lidar data inversion. We find that depolarization information of at least one wavelength already provides useful information for the inversion of optical data that have been collected in the presence of non-spherical mineral dust particles. However, any choice of d will give lower values of the single-scattering albedo than the traditional 3 + 2 data set. We find that input data sets that include d355 give a spheroid fraction that closely resembles the dust ratio we obtain from using β532 and d532 in a methodology applied in aerosol-type separation. The use of d355 in data sets of two or three d? reduces the spheroid fraction that is retrieved when using d532 and d1064. Use of the latter two parameters without accounting for d355 generally leads to high spheroid fractions that we consider not trustworthy. The use of three d instead of two δ, including the constraint that one of these is measured at 355 nm does not provide any advantage over using 3 + 2 + d355 for the observations with varying contributions of mineral dust considered here. However, additional measurements at wavelengths different from 355 nm would be desirable for application to a wider range of aerosol scenarios that may include non-spherical smoke particles, which can have values of d355 that are indistinguishable from those found for mineral dust. We therefore conclude that - depending on measurement capability - the future standard input for inversion of lidar data taken in the presence of mineral dust particles and using the spheroid model of Dubovik et al. (2006) might be 3+2Cδ355 or 3 + 2 + δ355 + δ532. © 2019 The Author(s).