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- Item3+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)?(Katlenburg-Lindau : Copernicus, 2019) Tesche, Matthias; Kolgotin, Alexei; Haarig, Moritz; Burton, Sharon P.; Ferrare, Richard A.; Hostetler, Chris A.; Müller, DetlefThe 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).
- ItemIdentifying cloud droplets beyond lidar attenuation from vertically pointing cloud radar observations using artificial neural networks(Katlenburg-Lindau : Copernicus, 2022) Schimmel, Willi; Kalesse-Los, Heike; Maahn, Maximilian; Vogl, Teresa; Foth, Andreas; Garfias, Pablo Saavedra; Seifert, PatricIn mixed-phase clouds, the variable mass ratio between liquid water and ice as well as the spatial distribution within the cloud plays an important role in cloud lifetime, precipitation processes, and the radiation budget. Data sets of vertically pointing Doppler cloud radars and lidars provide insights into cloud properties at high temporal and spatial resolution. Cloud radars are able to penetrate multiple liquid layers and can potentially be used to expand the identification of cloud phase to the entire vertical column beyond the lidar signal attenuation height, by exploiting morphological features in cloud radar Doppler spectra that relate to the existence of supercooled liquid. We present VOODOO (reVealing supercOOled liquiD beyOnd lidar attenuatiOn), a retrieval based on deep convolutional neural networks (CNNs) mapping radar Doppler spectra to the probability of the presence of cloud droplets (CD). The training of the CNN was realized using the Cloudnet processing suite as supervisor. Once trained, VOODOO yields the probability for CD directly at Cloudnet grid resolution. Long-term predictions of 18 months in total from two mid-latitudinal locations, i.e., Punta Arenas, Chile (53.1 S, 70.9 W), in the Southern Hemisphere and Leipzig, Germany (51.3 N, 12.4 E), in the Northern Hemisphere, are evaluated. Temporal and spatial agreement in cloud-droplet-bearing pixels is found for the Cloudnet classification to the VOODOO prediction. Two suitable case studies were selected, where stratiform, multi-layer, and deep mixed-phase clouds were observed. Performance analysis of VOODOO via classification-evaluating metrics reveals precision > 0.7, recall ≈ 0.7, and accuracy ≈ 0.8. Additionally, independent measurements of liquid water path (LWP) retrieved by a collocated microwave radiometer (MWR) are correlated to the adiabatic LWP, which is estimated using the temporal and spatial locations of cloud droplets from VOODOO and Cloudnet in connection with a cloud parcel model. This comparison resulted in stronger correlation for VOODOO (≈ 0.45) compared to Cloudnet (≈ 0.22) and indicates the availability of VOODOO to identify CD beyond lidar attenuation. Furthermore, the long-term statistics for 18 months of observations are presented, analyzing the performance as a function of MWR-LWP and confirming VOODOO's ability to identify cloud droplets reliably for clouds with LWP > 100 g m-2. The influence of turbulence on the predictive performance of VOODOO was also analyzed and found to be minor. A synergy of the novel approach VOODOO and Cloudnet would complement each other perfectly and is planned to be incorporated into the Cloudnet algorithm chain in the near future.
- ItemAn automatic observation-based aerosol typing method for EARLINET(Katlenburg-Lindau : EGU, 2018) Papagiannopoulos, Nikolaos; Mona, Lucia; Amodeo, Aldo; D'Amico, Giuseppe; Gumà Claramunt, Pilar; Pappalardo, Gelsomina; Alados-Arboledas, Lucas; Guerrero-Rascado, Juan LuÃs; Amiridis, Vassilis; Kokkalis, Panagiotis; Apituley, Arnoud; Baars, Holger; Schwarz, Anja; Wandinger, Ulla; Binietoglou, Ioannis; Nicolae, Doina; Bortoli, Daniele; Comerón, Adolfo; RodrÃguez-Gómez, Alejandro; Sicard, Michaël; Papayannis, Alex; Wiegner, MatthiasWe present an automatic aerosol classification method based solely on the European Aerosol Research Lidar Network (EARLINET) intensive optical parameters with the aim of building a network-wide classification tool that could provide near-real-time aerosol typing information. The presented method depends on a supervised learning technique and makes use of the Mahalanobis distance function that relates each unclassified measurement to a predefined aerosol type. As a first step (training phase), a reference dataset is set up consisting of already classified EARLINET data. Using this dataset, we defined 8 aerosol classes: clean continental, polluted continental, dust, mixed dust, polluted dust, mixed marine, smoke, and volcanic ash. The effect of the number of aerosol classes has been explored, as well as the optimal set of intensive parameters to separate different aerosol types. Furthermore, the algorithm is trained with literature particle linear depolarization ratio values. As a second step (testing phase), we apply the method to an already classified EARLINET dataset and analyze the results of the comparison to this classified dataset. The predictive accuracy of the automatic classification varies between 59% (minimum) and 90% (maximum) from 8 to 4 aerosol classes, respectively, when evaluated against pre-classified EARLINET lidar. This indicates the potential use of the automatic classification to all network lidar data. Furthermore, the training of the algorithm with particle linear depolarization values found in the literature further improves the accuracy with values for all the aerosol classes around 80%. Additionally, the algorithm has proven to be highly versatile as it adapts to changes in the size of the training dataset and the number of aerosol classes and classifying parameters. Finally, the low computational time and demand for resources make the algorithm extremely suitable for the implementation within the single calculus chain (SCC), the EARLINET centralized processing suite.
- ItemProfiling water vapor mixing ratios in Finland by means of a Raman lidar, a satellite and a model(Katlenburg-Lindau : Copernicus, 2017) Filioglou, Maria; Nikandrova, Anna; Niemelä, Sami; Baars, Holger; Mielonen, Tero; Leskinen, Ari; Brus, David; Romakkaniemi, Sami; Giannakaki, Elina; Komppula, MikaWe present tropospheric water vapor profiles measured with a Raman lidar during three field campaigns held in Finland. Co-located radio soundings are available throughout the period for the calibration of the lidar signals. We investigate the possibility of calibrating the lidar water vapor profiles in the absence of co-existing on-site soundings using water vapor profiles from the combined Advanced InfraRed Sounder (AIRS) and the Advanced Microwave Sounding Unit (AMSU) satellite product; the Aire Limitée Adaptation dynamique Développement INternational and High Resolution Limited Area Model (ALADIN/HIRLAM) numerical weather prediction (NWP) system, and the nearest radio sounding station located 100 km away from the lidar site (only for the permanent location of the lidar). The uncertainties of the calibration factor derived from the soundings, the satellite and the model data are < 2.8, 7.4 and 3.9 %, respectively. We also include water vapor mixing ratio intercomparisons between the radio soundings and the various instruments/model for the period of the campaigns. A good agreement is observed for all comparisons with relative errors that do not exceed 50 % up to 8 km altitude in most cases. A 4-year seasonal analysis of vertical water vapor is also presented for the Kuopio site in Finland. During winter months, the air in Kuopio is dry (1.15±0.40 †kg-1); during summer it is wet (5.54±1.02 †kg-1); and at other times, the air is in an intermediate state. These are averaged values over the lowest 2 km in the atmosphere. Above that height a quick decrease in water vapor mixing ratios is observed, except during summer months where favorable atmospheric conditions enable higher mixing ratio values at higher altitudes. Lastly, the seasonal change in disagreement between the lidar and the model has been studied. The analysis showed that, on average, the model underestimates water vapor mixing ratios at high altitudes during spring and summer.
- ItemExtreme levels of Canadian wildfire smoke in the stratosphere over central Europe on 21-22 August 2017(Katlenburg-Lindau : EGU, 2018) Ansmann, Albert; Baars, Holger; Chudnovsky, Alexandra; Mattis, Ina; Veselovskii, Igor; Haarig, Moritz; Seifert, Patric; Engelmann, Ronny; Wandinger, UllaLight extinction coefficients of 500 Mm1, about 20 times higher than after the Pinatubo volcanic eruptions in 1991, were observed by European Aerosol Research Lidar Network (EARLINET) lidars in the stratosphere over central Europe on 21-22 August 2017. Pronounced smoke layers with a 1-2 km vertical extent were found 2-5 km above the local tropopause. Optically dense layers of Canadian wildfire smoke reached central Europe 10 days after their injection into the upper troposphere and lower stratosphere which was caused by rather strong pyrocumulonimbus activity over western Canada. The smoke-related aerosol optical thickness (AOT) identified by lidar was close to 1.0 at 532 nm over Leipzig during the noon hours on 22 August 2017. Smoke particles were found throughout the free troposphere (AOT of 0.3) and in the pronounced 2 km thick stratospheric smoke layer at an altitude of 14-16 km (AOT of 0.6). The lidar observations indicated peak mass concentrations of 70-100 μgm-3 in the stratosphere. In addition to the lidar profiles, we analyzed Moderate Resolution Imaging Spectroradiometer (MODIS) fire radiative power (FRP) over Canada, and the distribution of MODIS AOT and Ozone Monitoring Instrument (OMI) aerosol index across the North Atlantic. These instruments showed a similar pattern and a clear link between the western Canadian fires and the aerosol load over Europe. In this paper, we also present Aerosol Robotic Network (AERONET) sun photometer observations, compare photometer and lidar-derived AOT, and discuss an obvious bias (the smoke AOT is too low) in the photometer observations. Finally, we compare the strength of this recordbreaking smoke event (in terms of the particle extinction coefficient and AOT) with major and moderate volcanic events observed over the northern midlatitudes.
- ItemTarget categorization of aerosol and clouds by continuous multiwavelength-polarization lidar measurements(Katlenburg-Lindau : Copernicus, 2017) Baars, Holger; Seifert, Patric; Engelmann, Ronny; Wandinger, UllaAbsolute calibrated signals at 532 and 1064 nm and the depolarization ratio from a multiwavelength lidar are used to categorize primary aerosol but also clouds in high temporal and spatial resolution. Automatically derived particle backscatter coefficient profiles in low temporal resolution (30 min) are applied to calibrate the lidar signals. From these calibrated lidar signals, new atmospheric parameters in temporally high resolution (quasi-particle-backscatter coefficients) are derived. By using thresholds obtained from multiyear, multisite EARLINET (European Aerosol Research Lidar Network) measurements, four aerosol classes (small; large, spherical; large, non-spherical; mixed, partly nonspherical) and several cloud classes (liquid, ice) are defined. Thus, particles are classified by their physical features (shape and size) instead of by source. The methodology is applied to 2 months of continuous observations (24 h a day, 7 days a week) with the multiwavelength-Raman-polarization lidar PollyXT during the High-Definition Clouds and Precipitation for advancing Climate Prediction (HD(CP)2) Observational Prototype Experiment (HOPE) in spring 2013. Cloudnet equipment was operated continuously directly next to the lidar and is used for comparison. By discussing three 24 h case studies, it is shown that the aerosol discrimination is very feasible and informative and gives a good complement to the Cloudnet target categorization. Performing the categorization for the 2-month data set of the entire HOPE campaign, almost 1 million pixel (5 min×30 m) could be analysed with the newly developed tool. We find that the majority of the aerosol trapped in the planetary boundary layer (PBL) was composed of small particles as expected for a heavily populated and industrialized area. Large, spherical aerosol was observed mostly at the top of the PBL and close to the identified cloud bases, indicating the importance of hygroscopic growth of the particles at high relative humidity. Interestingly, it is found that on several days non-spherical particles were dispersed from the ground into the atmosphere.
- ItemQuantification of waves in lidar observations of noctilucent clouds at scales from seconds to minutes(Göttingen : Copernicus, 2013) Kaifler, N.; Baumgarten, G.; Fiedler, J.We present small-scale structures and waves observed in noctilucent clouds (NLC) by lidar at an unprecedented temporal resolution of 30 s or less. The measurements were taken with the Rayleigh/Mie/Raman lidar at the ALOMAR observatory in northern Norway (69 N) in the years 2008-2011. We find multiple layer NLC in 7.9% of the time for a brightness threshold of δ β 12 × 10-10 m-1 sr-1. In comparison to 10 min averaged data, the 30 s dataset shows considerably more structure. For limited periods, quasi-monochromatic waves in NLC altitude variations are common, in accord with ground-based NLC imagery. For the combined dataset, on the other hand, we do not find preferred periods but rather significant periods at all timescales observed (1 min to 1 h). Typical wave amplitudes in the layer vertical displacements are 0.2 km with maximum amplitudes up to 2.3 km. Average spectral slopes of temporal altitude and brightness variations are-2.01 ± 0.25 for centroid altitude,-1.41 ± 0.24 for peak brightness and-1.73 ± 0.25 for integrated brightness. Evaluating a new single-pulse detection system, we observe altitude variations of 70 s period and spectral slopes down to a scale of 10 s. We evaluate the suitability of NLC parameters as tracers for gravity waves.
- ItemAerosol and cloud top height information of Envisat MIPAS measurements(Katlenburg-Lindau : Copernicus, 2020) Griessbach, Sabine; Hoffmann, Lars; Spang, Reinhold; Achtert, Peggy; von Hobe, Marc; Mateshvili, Nina; Müller, Rolf; Riese, Martin; Rolf, Christian; Seifert, Patric; Vernier, Jean-PaulInfrared limb emission instruments have a long history in measuring clouds and aerosol. In particular, the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) instrument aboard ESA's Envisat provides 10 years of altitude-resolved global measurements. Previous studies found systematic overestimations and underestimations of cloud top heights for cirrus and polar stratospheric clouds. To assess the cloud top height information and to characterise its uncertainty for the MIPAS instrument we performed simulations for ice clouds, volcanic ash, and sulfate aerosol. From the simulation results we found that in addition to the known effects of the field-of-view that can lead to a cloud top height overestimation, and broken cloud conditions that can lead to underestimation, the cloud extinction also plays an important role. While for optically thick clouds the possible cloud top height overestimation for MIPAS reaches up to 1.6 km due to the field-of-view, for optically thin clouds and aerosol the systematic underestimation reaches 5.1 km. For the detection sensitivity and the degree of underestimation of the MIPAS measurements, the cloud layer thickness also plays a role; 1 km thick clouds are detectable down to extinctions of 5×10-4 km-1 and 6 km thick clouds are detectable down to extinctions of 1×10-4 km-1, where the largest underestimations of the cloud top height occur for the optically thinnest clouds with a vertical extent of 6 km. The relation between extinction coefficient, cloud top height estimate, and layer thickness is confirmed by a comparison of MIPAS cloud top heights of the volcanic sulfate aerosol from the Nabro eruption in 2011 with space-and ground-based lidar measurements and twilight measurements between June 2011 and February 2012. For plumes up to 2 months old, where the extinction was between 1×10-4 and 7×10-4 km-1 and the layer thickness mostly below 4 km, we found for MIPAS an average underestimation of 1.1 km. In the aged plume with extinctions down to 5 × 10-5 km-1 and layer thicknesses of up to 9.5 km, the underestimation was higher, reaching up to 7.2 km. The dependency of the cloud top height overestimations or underestimations on the extinction coefficient can explain seemingly contradictory results of previous studies. In spite of the relatively large uncertainty range of the cloud top height, the comparison of the detection sensitivity towards sulfate aerosol between MIPAS and a suite of widely used UV/VIS limb and IR nadir satellite aerosol measurements shows that MIPAS provides complementary information in terms of detection sensitivity. © Author(s) 2020.
- ItemCoincident measurements of PMSE and NLC above ALOMAR (69° N, 16° E) by radar and lidar from 1999-2008(Göttingen : Copernicus, 2011) Kaifler, N.; Baumgarten, G.; Fiedler, J.; Latteck, R.; Lübken, F.-J.; Rapp, M.Polar Mesosphere Summer Echoes (PMSE) and Noctilucent Clouds (NLC) have been routinely measured at the ALOMAR research facility in Northern Norway (69° N, 16° E) by lidar and radar, respectively. 2900 h of lidar measurements by the ALOMAR Rayleigh/Mie/Raman lidar were combined with almost 18 000 h of radar measurements by the ALWIN VHF radar, all taken during the years 1999 to 2008, to study simultaneous and common-volume observations of both phenomena. PMSE and NLC are known from both theory and observations to be positively linked. We quantify the occurrences of PMSE and/or NLC and relations in altitude, especially with respect to the lower layer boundaries. The PMSE occurrence rate is with 75.3% considerably higher than the NLC occurrence rate of 19.5%. For overlapping PMSE and NLC observations, we confirm the coincidence of the lower boundaries and find a standard deviation of 1.26 km, hinting at very fast sublimation rates. However, 10.1% of all NLC measurements occur without accompanying PMSE. Comparison of occurrence rates with solar zenith angle reveals that NLC without PMSE mostly occur around midnight indicating that the ice particles were not detected by the radar due to the reduced electron density.
- ItemThe dual-field-of-view polarization lidar technique: A new concept in monitoring aerosol effects in liquid-water clouds - Case studies(Katlenburg-Lindau : EGU, 2020) Jimenez, Cristofer; Ansmann, Albert; Engelmann, Ronny; Donovan, David; Malinka, Aleksey; Seifert, Patric; Wiesen, Robert; Radenz, Martin; Yin, Zhenping; Bühl, Johannes; Schmidt, Jörg; Barja, Boris; Wandinger, UllaIn a companion article (Jimenez et al., 2020), we introduced a new lidar method to derive microphysical properties of liquid-water clouds (cloud extinction coefficient, droplet effective radius, liquid-water content, cloud droplet number concentration Nd) at a height of 50-100m above the cloud base together with aerosol information (aerosol extinction coefficients, cloud condensation nuclei concentration NCCN) below the cloud layer so that detailed studies of the influence of given aerosol conditions on the evolution of liquid-water cloud layers with high temporal resolution solely based on lidar observations have become possible now. The novel cloud retrieval technique makes use of lidar observations of the volume linear depolarization ratio at two different receiver field of views (FOVs). In this article, Part 2, the new dual-FOV polarization lidar technique is applied to cloud measurements in pristine marine conditions at Punta Arenas in southern Chile. A multiwavelength polarization Raman lidar, upgraded by integrating a second polarization-sensitive channel to permit depolarization ratio observations at two FOVs, was used for these measurements at the southernmost tip of South America. Two case studies are presented to demonstrate the potential of the new lidar technique. Successful aerosol-cloud-interaction (ACI) studies based on measurements with the upgraded aerosol-cloud lidar in combination with a Doppler lidar of the vertical wind component could be carried out with 1 min temporal resolution at these pristine conditions. In a stratocumulus layer at the top of the convective boundary layer, we found values of Nd and NCCN (for 0.2% water supersaturation) ranging from 15-100 and 75-200 cm-3, respectively, during updraft periods. The studies of the aerosol impact on cloud properties yielded ACI values close to 1. The impact of aerosol water uptake on the ACI studies was analyzed with the result that the highest ACI values were obtained when considering aerosol proxies (light-extinction coefficient par or NCCN) measured at heights about 500m below the cloud base (and thus for dry aerosol conditions). © 2020 BMJ Publishing Group. All rights reserved.