LACROS: the Leipzig Aerosol and Cloud Remote Observations System

Bühl, Johannes; Seifert, Patric; Wandinger, Ulla; Baars, Holger; Kanitz, Thomas; Schmidt, Jörg; Myagkov, Alexander; Engelmann, Ronny; Skupin, Annett; Heese, Birgit; Klepel, André; Althausen, Dietrich; Ansmann, Albert

doi:10.1117/12.2030911

Cited by 40 publications

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“…Continuous observations with the TROPOS mobile facility LACROS (Bühl et al, 2013) were performed at the supersite KRA. LACROS employs a 35 GHz cloud radar, a multiwavelength Raman polarization lidar, a ceilometer, a Doppler lidar, a microwave radiometer, an optical disdrometer, and an all-sky imager.…”

Section: Krauthausen Supersitementioning

confidence: 99%

The HD(CP)<sup>2</sup> Observational Prototype Experiment (HOPE) – an overview

et al. 2017

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Abstract. The 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 providePublished by Copernicus Publications on behalf of the European Geosciences Union. 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 HOPEMelpitz 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 × 10 km 3 . 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.

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Section: Krauthausen Supersitementioning

confidence: 99%

The HD(CP)<sup>2</sup> Observational Prototype Experiment (HOPE) – an overview

et al. 2017

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“…), near Jülich, western Germany, in April and May 2013 as part of the LACROS facility (Bühl et al, 2013). A detailed description of the campaign together with the prevailing meteorological conditions can be found in Macke et al (2016).…”

Section: Hopementioning

confidence: 99%

“…The MWL Polly XT and the Cloudnet instruments (cloud radar, ceilometer, MWR) were deployed in the frame of the Leipzig Aerosol and Cloud Remote Observations System (LACROS, Bühl et al, 2013) next to each other at Krauthausen, Germany, continuously for 2 months in Spring 2013. Polly XT is a sophisticated, compact, scientific multiwavelength lidar to which the quality-assurance procedures proposed by EAR-LINET (European Aerosol Research Lidar Network; Pappalardo et al, 2013) are applied.…”

Section: Introductionmentioning

confidence: 99%

Target categorization of aerosol and clouds by continuous multiwavelength-polarization lidar measurements

et al. 2017

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Abstract. Absolute 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 Polly XT 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.

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“…In recent years, the Leipzig Aerosol and Cloud Remote Observations System (LACROS) (Bühl et al, 2013), installed a combination of ground-based remote sensing systems. The synergy of complementary information from both active and passive instruments can provide a more comprehensive understanding of atmospheric processes (Stankov, 1998;Furumoto et al, 2003;Bianco et al, 2005;Delanoë and Hogan, 2008).…”

mentioning

confidence: 99%

“…The Cloudnet project is comprised of a number of algorithms for the continuous analysis of cloud properties by means of remote sensing with lidar, MWR and cloud radar (Illingworth et al, 2007). The instruments synergy allows for a continuous evaluation of the representation of clouds in climate and weather forecast models (Sengupta et al, 2004;Hogan et al, 2009;Bouniol et al, 2010). Additionally, the data set enables the development and validation of new cloud remote sensing synergy algorithms.…”

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confidence: 99%

Optimal estimation of water vapour profiles using a combination of Raman lidar and microwave radiometer

Foth

Pospichal

2017

Atmos. Meas. Tech.

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Abstract. In this work, a two-step algorithm to obtain water vapour profiles from a combination of Raman lidar and microwave radiometer is presented. Both instruments were applied during an intensive 2-month measurement campaign (HOPE) close to Jülich, western Germany, during spring 2013. To retrieve reliable water vapour information from inside or above the cloud a two-step algorithm is applied. The first step is a Kalman filter that extends the profiles, truncated at cloud base, to the full height range (up to 10 km) by combining previous information and current measurement. Then the complete water vapour profile serves as input to the one-dimensional variational (1D-VAR) method, also known as optimal estimation. A forward model simulates the brightness temperatures which would be observed by the microwave radiometer for the given atmospheric state. The profile is iteratively modified according to its error bars until the modelled and the actually measured brightness temperatures sufficiently agree. The functionality of the retrieval is presented in detail by means of case studies under different conditions. A statistical analysis shows that the availability of Raman lidar data (night) improves the accuracy of the profiles even under cloudy conditions. During the day, the absence of lidar data results in larger differences in comparison to reference radiosondes. The data availability of the full-height water vapour lidar profiles of 17 % during the 2-month campaign is significantly enhanced to 60 % by applying the retrieval. The bias with respect to radiosonde and the retrieved a posteriori uncertainty of the retrieved profiles clearly show that the application of the Kalman filter considerably improves the accuracy and quality of the retrieved mixing ratio profiles.

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LACROS: the Leipzig Aerosol and Cloud Remote Observations System

Cited by 40 publications

References 0 publications

The HD(CP)<sup>2</sup> Observational Prototype Experiment (HOPE) – an overview

The HD(CP)<sup>2</sup> Observational Prototype Experiment (HOPE) – an overview

Target categorization of aerosol and clouds by continuous multiwavelength-polarization lidar measurements

Optimal estimation of water vapour profiles using a combination of Raman lidar and microwave radiometer

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LACROS: the Leipzig Aerosol and Cloud Remote Observations System

Cited by 40 publications

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The HD(CP)&lt;sup&gt;2&lt;/sup&gt; Observational Prototype Experiment (HOPE) – an overview

The HD(CP)&lt;sup&gt;2&lt;/sup&gt; Observational Prototype Experiment (HOPE) – an overview

Target categorization of aerosol and clouds by continuous multiwavelength-polarization lidar measurements

Optimal estimation of water vapour profiles using a combination of Raman lidar and microwave radiometer

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Product

Resources

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The HD(CP)<sup>2</sup> Observational Prototype Experiment (HOPE) – an overview

The HD(CP)<sup>2</sup> Observational Prototype Experiment (HOPE) – an overview