4 results
Search Results
Now showing 1 - 4 of 4
- 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.
- 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.
- ItemThe HD(CP)2 Observational Prototype Experiment (HOPE) - An overview(Katlenburg-Lindau : EGU, 2017) Macke, Andreas; Seifert, Patric; Baars, Holger; Barthlott, Christian; Beekmans, Christoph; Behrendt, Andreas; Bohn, Birger; Brueck, Matthias; Bühl, Johannes; Crewell, Susanne; Damian, Thomas; Deneke, Hartwig; Düsing, Sebastian; Foth, Andreas; Di Girolamo, Paolo; Hammann, Eva; Heinze, Rieke; Hirsikko, Anne; Kalisch, John; Kalthoff, Norbert; Kinne, Stefan; Kohler, Martin; Löhnert, Ulrich; Madhavan, Bomidi Lakshmi; Maurer, Vera; Muppa, Shravan Kumar; Schween, Jan; Serikov, Ilya; Siebert, Holger; Simmer, Clemens; Späth, Florian; Steinke, Sandra; Träumner, Katja; Trömel, Silke; Wehner, Birgit; Wieser, Andreas; Wulfmeyer, Volker; Xie, XinxinThe HD(CP)2 Observational Prototype Experiment (HOPE) was performed as a major 2-month field experiment in Jülich, Germany, in April and May 2013, followed by a smaller campaign in Melpitz, Germany, in September 2013. HOPE has been designed to provide an observational dataset for a critical evaluation of the new German community atmospheric icosahedral non-hydrostatic (ICON) model at the scale of the model simulations and further to provide information on land-surface-atmospheric boundary layer exchange, cloud and precipitation processes, as well as sub-grid variability and microphysical properties that are subject to parameterizations. HOPE focuses on the onset of clouds and precipitation in the convective atmospheric boundary layer. This paper summarizes the instrument set-ups, the intensive observation periods, and example results from both campaigns.
HOPE-Jülich instrumentation included a radio sounding station, 4 Doppler lidars, 4 Raman lidars (3 of them provide temperature, 3 of them water vapour, and all of them particle backscatter data), 1 water vapour differential absorption lidar, 3 cloud radars, 5 microwave radiometers, 3 rain radars, 6 sky imagers, 99 pyranometers, and 5 sun photometers operated at different sites, some of them in synergy. The HOPE-Melpitz campaign combined ground-based remote sensing of aerosols and clouds with helicopter- and balloon-based in situ observations in the atmospheric column and at the surface.
HOPE provided an unprecedented collection of atmospheric dynamical, thermodynamical, and micro- and macrophysical properties of aerosols, clouds, and precipitation with high spatial and temporal resolution within a cube of approximately 10 × 10 × 10km3. HOPE data will significantly contribute to our understanding of boundary layer dynamics and the formation of clouds and precipitation. The datasets have been made available through a dedicated data portal.
First applications of HOPE data for model evaluation have shown a general agreement between observed and modelled boundary layer height, turbulence characteristics, and cloud coverage, but they also point to significant differences that deserve further investigations from both the observational and the modelling perspective. - ItemVertical aerosol distribution in the southern hemispheric midlatitudes as observed with lidar in Punta Arenas, Chile (53.2° and 70.9° W), during ALPACA(Katlenburg-Lindau : EGU, 2019) Foth, Andreas; Kanitz, Thomas; Engelmann, Ronny; Baars, Holger; Radenz, Martin; Seifert, Patric; Barja, Boris; Fromm, Michael; Kalesse, Heike; Ansmann, AlbertWithin this publication, lidar observations of the vertical aerosol distribution above Punta Arenas, Chile (53.2 S and 70.9 W), which have been performed with the Raman lidar PollyXT from December 2009 to April 2010, are presented. Pristine marine aerosol conditions related to the prevailing westerly circulation dominated the measurements. Lofted aerosol layers could only be observed eight times during the whole measurement period. Two case studies are presented showing long-range transport of smoke from biomass burning in Australia and regionally transported dust from the Patagonian Desert, respectively. The aerosol sources are identified by trajectory analyses with the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) and FLEXible PARTicle dispersion model (FLEXPART). However, seven of the eight analysed cases with lofted layers show an aerosol optical thickness of less than 0.05. From the lidar observations, a mean planetary boundary layer (PBL) top height of 1150 350m was determined. An analysis of particle backscatter coefficients confirms that the majority of the aerosol is attributed to the PBL, while the free troposphere is characterized by a very low background aerosol concentration. The ground-based lidar observations at 532 and 1064 nm are supplemented by the Aerosol Robotic Network (AERONET) Sun photometers and the space-borne Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) aboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO). The averaged aerosol optical thickness (AOT) determined by CALIOP was 0:02 0:01 in Punta Arenas from 2009 to 2010. © Author(s) 2019. This work is distributed under the Creative Commons Attribution 4.0 License.