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- ItemMapping the aerosol over Eurasia from the Zotino tall tower(Milton Park : Taylor & Francis, 2013) Heintzenberg, Jost; Birmili, Wolfram; Seifert, Patric; Panov, Alexey; Chi, Xuguang; Andreae, Meinrat O.The present study covers more than 5 yr corresponding to more than 40 000 hours of particle and gas data measured at the Siberian tall tower Zotino Tall Tower (ZOTTO) (60.8°N; 89.35°E). Extrapolated along 10-d back trajectories, the ZOTTO measurements cover large parts of the Eurasian land mass. Mapping the extrapolated ZOTTO data points to major anthropogenic source regions and Siberian fire regions, consistent with emission data for CO and vegetation fires. Middle East mid-latitude sources stand out strongly and possibly emissions from Northern China may be seen at times from ZOTTO. The maps of measured light scattering and absorption characteristics support the interpretation of different source types. Three clusters of substantially different submicrometer particle size distributions were found, the maps of which also could be related to major aerosol source regions.
- ItemInfluence of low-level blocking and turbulence on the microphysics of a mixed-phase cloud in an inner-Alpine valley(Katlenburg-Lindau : European Geosciences Union, 2021) Ramelli, Fabiola; Henneberger, Jan; David, Robert O.; Lauber, Annika; Pasquier, Julie T.; Wieder, Jörg; Bühl, Johannes; Seifert, Patric; Engelmann, Ronny; Hervo, Maxime; Lohmann, UlrikePrevious studies that investigated orographic precipitation have primarily focused on isolated mountain barriers. Here we investigate the influence of low-level blocking and shear-induced turbulence on the cloud microphysics and precipitation formation in a complex inner-Alpine valley. The analysis focuses on a mid-level cloud in a post-frontal environment and a low-level feeder cloud induced by an in-valley circulation. Observations were obtained from an extensive set of instruments including ground-based remote sensing instrumentation, in situ instrumentation on a tethered-balloon system and ground-based precipitation measurements. During this event, the boundary layer was characterized by a blocked low-level flow and enhanced turbulence in the region of strong vertical wind shear at the boundary between the blocked layer in the valley and the stronger cross-barrier flow aloft. Cloud radar observations indicated changes in the microphysical cloud properties within the turbulent shear layer including enhanced linear depolarization ratio (i.e., change in particle shape or density) and increased radar reflectivity (i.e., enhanced ice growth). Based on the ice particle habits observed at the surface, we suggest that riming, aggregation and needle growth occurred within the turbulent layer. Collisions of fragile ice crystals (e.g., dendrites, needles) and the Hallett-Mossop process might have contributed to secondary ice production. Additionally, in situ instrumentation on the tethered-balloon system observed the presence of a low-level feeder cloud above a small-scale topographic feature, which dissipated when the low-level flow turned from a blocked to an unblocked state. Our observations indicate that the low-level blocking (due to the downstream mountain barrier) created an in-valley circulation, which led to the production of local updrafts and the formation of a low-level feeder cloud. Although the feeder cloud did not enhance precipitation in this particular case (since the majority of the precipitation sublimated when falling through a subsaturated layer above), we propose that local flow effects such as low-level blocking can induce the formation of feeder clouds in mountain valleys and on the leeward slope of foothills upstream of the main mountain barrier, where they can act to enhance orographic precipitation through the seeder-feeder mechanism.
- ItemTropospheric and stratospheric wildfire smoke profiling with lidar: mass, surface area, CCN, and INP retrieval(Katlenburg-Lindau : European Geosciences Union, 2021) Ansmann, Albert; Ohneiser, Kevin; Mamouri, Rodanthi-Elisavet; Knopf, Daniel A.; Veselovskii, Igor; Baars, Holger; Engelmann, Ronny; Foth, Andreas; Jimenez, Cristofer; Seifert, Patric; Barja, BorisWe present retrievals of tropospheric and stratospheric height profiles of particle mass, volume, surface area, and number concentrations in the case of wildfire smoke layers as well as estimates of smoke-related cloud condensation nuclei (CCN) and ice-nucleating particle (INP) concentrations from backscatter lidar measurements on the ground and in space. Conversion factors used to convert the optical measurements into microphysical properties play a central role in the data analysis, in addition to estimates of the smoke extinction-to-backscatter ratios required to obtain smoke extinction coefficients. The set of needed conversion parameters for wildfire smoke is derived from AERONET observations of major smoke events, e.g., in western Canada in August 2017, California in September 2020, and southeastern Australia in January-February 2020 as well as from AERONET long-term observations of smoke in the Amazon region, southern Africa, and Southeast Asia. The new smoke analysis scheme is applied to CALIPSO observations of tropospheric smoke plumes over the United States in September 2020 and to ground-based lidar observation in Punta Arenas, in southern Chile, in aged Australian smoke layers in the stratosphere in January 2020. These case studies show the potential of spaceborne and ground-based lidars to document large-scale and long-lasting wildfire smoke events in detail and thus to provide valuable information for climate, cloud, and air chemistry modeling efforts performed to investigate the role of wildfire smoke in the atmospheric system. © 2021 Albert Ansmann et al.
- ItemOzone depletion in the Arctic and Antarctic stratosphere induced by wildfire smoke(Katlenburg-Lindau : EGU, 2022) Ansmann, Albert; Ohneiser, Kevin; Chudnovsky, Alexandra; Knopf, Daniel A.; Eloranta, Edwin W.; Villanueva, Diego; Seifert, Patric; Radenz, Martin; Barja, Boris; Zamorano, Félix; Jimenez, Cristofer; Engelmann, Ronny; Baars, Holger; Griesche, Hannes; Hofer, Julian; Althausen, Dietrich; Wandinger, UllaA record-breaking stratospheric ozone loss was observed over the Arctic and Antarctica in 2020. Strong ozone depletion occurred over Antarctica in 2021 as well. The ozone holes developed in smoke-polluted air. In this article, the impact of Siberian and Australian wildfire smoke (dominated by organic aerosol) on the extraordinarily strong ozone reduction is discussed. The study is based on aerosol lidar observations in the North Pole region (October 2019-May 2020) and over Punta Arenas in southern Chile at 53.2°S (January 2020-November 2021) as well as on respective NDACC (Network for the Detection of Atmospheric Composition Change) ozone profile observations in the Arctic (Ny-Ålesund) and Antarctica (Neumayer and South Pole stations) in 2020 and 2021. We present a conceptual approach on how the smoke may have influenced the formation of polar stratospheric clouds (PSCs), which are of key importance in the ozone-depleting processes. The main results are as follows: (a) the direct impact of wildfire smoke below the PSC height range (at 10-12 km) on ozone reduction seems to be similar to well-known volcanic sulfate aerosol effects. At heights of 10-12 km, smoke particle surface area (SA) concentrations of 5-7 μm2 cm-3 (Antarctica, spring 2021) and 6-10 μm2 cm-3 (Arctic, spring 2020) were correlated with an ozone reduction in terms of ozone partial pressure of 0.4-1.2 mPa (about 30 % further ozone reduction over Antarctica) and of 2-3.5 mPa (Arctic, 20 %-30 % reduction with respect to the long-term springtime mean). (b) Within the PSC height range, we found indications that smoke was able to slightly increase the PSC particle number and surface area concentration. In particular, a smoke-related additional ozone loss of 1-2 mPa (10 %-20 % contribution to the total ozone loss over Antarctica) was observed in the 14-23 km PSC height range in September-October 2020 and 2021. Smoke particle number concentrations ranged from 10 to 100 cm-3 and were about a factor of 10 (in 2020) and 5 (in 2021) above the stratospheric aerosol background level. Satellite observations indicated an additional mean column ozone loss (deviation from the long-term mean) of 26-30 Dobson units (9 %-10 %, September 2020, 2021) and 52-57 Dobson units (17 %-20 %, October 2020, 2021) in the smoke-polluted latitudinal Antarctic belt from 70-80°S. Copyright:
- ItemThe dual-field-of-view polarization lidar technique: a new concept in monitoring aerosol effects in liquid-water clouds – theoretical framework(Katlenburg-Lindau : EGU, 2021) Jimenez, Cristofer; Ansmann, Albert; Engelmann, Ronny; Donovan, David; Malinka, Aleksey; Schmidt, Jörg; Seifert, Patric; Wandinger, UllaIn a series of two articles, a novel, robust, and practicable lidar approach is presented that allows us to derive microphysical properties of liquid-water clouds (cloud extinction coefficient, droplet effective radius, liquid-water content, cloud droplet number concentration) at a height of 50–100 m above the cloud base. The temporal resolution of the observations is on the order of 30–120 s. Together with the aerosol information (aerosol extinction coefficients, cloud condensation nucleus concentration) below the cloud layer, obtained with the same lidar, in-depth aerosol–cloud interaction studies can be performed. The theoretical background and the methodology of the new cloud lidar technique is outlined in this article (Part 1), and measurement applications are presented in a companion publication (Part 2) (Jimenez et al., 2020a). The novel cloud retrieval technique is based on lidar observations of the volume linear depolarization ratio at two different receiver fields of view (FOVs). Extensive simulations of lidar returns in the multiple scattering regime were conducted to investigate the capabilities of a dual-FOV polarization lidar to measure cloud properties and to quantify the information content in the measured depolarization features regarding the basic retrieval parameters (cloud extinction coefficient, droplet effective radius). Key simulation results and the overall data analysis scheme developed to obtain the aerosol and cloud products are presented.
- ItemWildfire smoke, Arctic haze, and aerosol effects on mixed-phase and cirrus clouds over the North Pole region during MOSAiC: an introduction(Katlenburg-Lindau : European Geosciences Union, 2021) Engelmann, Ronny; Ansmann, Albert; Ohneiser, Kevin; Griesche, Hannes; Radenz, Martin; Hofer, Julian; Althausen, Dietrich; Dahlke, Sandro; Maturilli, Marion; Veselovskii, Igor; Jimenez, Cristofer; Wiesen, Robert; Baars, Holger; Bühl, Johannes; Gebauer, Henriette; Haarig, Moritz; Seifert, Patric; Wandinger, Ulla; Macke, AndreasAn advanced multiwavelength polarization Raman lidar was operated aboard the icebreaker Polarstern during the MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate) expedition to continuously monitor aerosol and cloud layers in the central Arctic up to 30gkm height. The expedition lasted from September 2019 to October 2020 and measurements were mostly taken between 85 and 88.5ggN. The lidar was integrated into a complex remote-sensing infrastructure aboard the Polarstern. In this article, novel lidar techniques, innovative concepts to study aerosol-cloud interaction in the Arctic, and unique MOSAiC findings will be presented. The highlight of the lidar measurements was the detection of a 10gkm deep wildfire smoke layer over the North Pole region between 7-8gkm and 17-18gkm height with an aerosol optical thickness (AOT) at 532gnm of around 0.1 (in October-November 2019) and 0.05 from December to March. The dual-wavelength Raman lidar technique allowed us to unambiguously identify smoke as the dominating aerosol type in the aerosol layer in the upper troposphere and lower stratosphere (UTLS). An additional contribution to the 532gnm AOT by volcanic sulfate aerosol (Raikoke eruption) was estimated to always be lower than 15g%. The optical and microphysical properties of the UTLS smoke layer are presented in an accompanying paper . This smoke event offered the unique opportunity to study the influence of organic aerosol particles (serving as ice-nucleating particles, INPs) on cirrus formation in the upper troposphere. An example of a closure study is presented to explain our concept of investigating aerosol-cloud interaction in this field. The smoke particles were obviously able to control the evolution of the cirrus system and caused low ice crystal number concentration. After the discussion of two typical Arctic haze events, we present a case study of the evolution of a long-lasting mixed-phase cloud layer embedded in Arctic haze in the free troposphere. The recently introduced dual-field-of-view polarization lidar technique was applied, for the first time, to mixed-phase cloud observations in order to determine the microphysical properties of the water droplets. The mixed-phase cloud closure experiment (based on combined lidar and radar observations) indicated that the observed aerosol levels controlled the number concentrations of nucleated droplets and ice crystals.
- ItemRelationship between temperature and apparent shape of pristine ice crystals derived from polarimetric cloud radar observations during the ACCEPT campaign(München : European Geopyhsical Union, 2016) Myagkov, Alexander; Seifert, Patric; Wandinger, Ulla; Bühl, Johannes; Engelmann, RonnyThis paper presents first quantitative estimations of apparent ice particle shape at the top of liquid-topped clouds. Analyzed ice particles were formed under mixed-phase conditions in the presence of supercooled water and in the temperature range from −20 to −3 °C. The estimation is based on polarizability ratios of ice particles measured by a Ka-band cloud radar MIRA-35 with hybrid polarimetric configuration. Polarizability ratio is a function of the geometrical axis ratio and the dielectric properties of the observed hydrometeors. For this study, 22 cases observed during the ACCEPT (Analysis of the Composition of Clouds with Extended Polarization Techniques) field campaign were used. Polarizability ratios retrieved for cloud layers with the cloud-top temperatures of ∼ −5, ∼ −8, ∼ −15, and ∼ −20 °C were 1.6, 0.9, 0.6, and 0.9, respectively. Such values correspond to prolate, quasi-isotropic, oblate, and quasi-isotropic particles, respectively. Data from a free-fall chamber were used for the comparison. A good agreement of detected apparent shapes with well-known shape–temperature dependencies observed in laboratories was found. Polarizability ratios used for the analysis were estimated for areas located close to the cloud top, where aggregation and riming processes do not strongly affect ice particles. We concluded that, in microwave scattering models, ice particles detected in these areas can be assumed to have pristine shapes. It was also found that even slight variations of ambient conditions at the cloud top with temperatures warmer than ∼ −5 °C can lead to rapid changes of ice crystal shape.
- ItemCalibration of Raman lidar water vapor profiles by means of AERONET photometer observations and GDAS meteorological data(München : European Geopyhsical Union, 2018) Dai, Guangyao; Althausen, Dietrich; Hofer, Julian; Engelmann, Ronny; Seifert, Patric; Bühl, Johannes; Mamouri, Rodanthi-Elisavet; Wu, Songhua; Ansmann, AlbertWe present a practical method to continuously calibrate Raman lidar observations of water vapor mixing ratio profiles. The water vapor profile measured with the multiwavelength polarization Raman lidar PollyXT is calibrated by means of co-located AErosol RObotic NETwork (AERONET) sun photometer observations and Global Data Assimilation System (GDAS) temperature and pressure profiles. This method is applied to lidar observations conducted during the Cyprus Cloud Aerosol and Rain Experiment (CyCARE) in Limassol, Cyprus. We use the GDAS temperature and pressure profiles to retrieve the water vapor density. In the next step, the precipitable water vapor from the lidar observations is used for the calibration of the lidar measurements with the sun photometer measurements. The retrieved calibrated water vapor mixing ratio from the lidar measurements has a relative uncertainty of 11 % in which the error is mainly caused by the error of the sun photometer measurements. During CyCARE, nine measurement cases with cloud-free and stable meteorological conditions are selected to calculate the precipitable water vapor from the lidar and the sun photometer observations. The ratio of these two precipitable water vapor values yields the water vapor calibration constant. The calibration constant for the PollyXT Raman lidar is 6.56 g kg−1 ± 0.72 g kg−1 (with a statistical uncertainty of 0.08 g kg−1 and an instrumental uncertainty of 0.72 g kg−1). To check the quality of the water vapor calibration, the water vapor mixing ratio profiles from the simultaneous nighttime observations with Raman lidar and Vaisala radiosonde sounding are compared. The correlation of the water vapor mixing ratios from these two instruments is determined by using all of the 19 simultaneous nighttime measurements during CyCARE. Excellent agreement with the slope of 1.01 and the R2 of 0.99 is found. One example is presented to demonstrate the full potential of a well-calibrated Raman lidar. The relative humidity profiles from lidar, GDAS (simulation) and radiosonde are compared, too. It is found that the combination of water vapor mixing ratio and GDAS temperature profiles allow us to derive relative humidity profiles with the relative uncertainty of 10–20 %.
- 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.
- 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.