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Author: Seifert, Patric × End date: 2023 × Start date: 2020 × End date: 2022 × Start date: 2020 × Subject: lidar ×

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Now showing 1 - 4 of 4
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    Tropospheric 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, Boris
    We 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.
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    Identifying 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, Patric
    In 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.
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    The 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, Ulla
    In 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.
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    Aerosol 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-Paul
    Infrared 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.