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Now showing 1 - 10 of 42
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    Is the near-spherical shape the "new black" for smoke?
    (Katlenburg-Lindau : EGU, 2020) Gialitaki, Anna; Tsekeri, Alexandra; Amiridis, Vassilis; Ceolato, Romain; Paulien, Lucas; Kampouri, Anna; Gkikas, Antonis; Solomos, Stavros; Marinou, Eleni; Haarig, Moritz; Baars, Holger; Ansmann, Albert; Lapyonok, Tatyana; Lopatin, Anton; Dubovik, Oleg; Groß, Silke; Wirth, Martin; Tsichla, Maria; Tsikoudi, Ioanna; Balis, Dimitris
    We examine the capability of near-sphericalshaped particles to reproduce the triple-wavelength particle linear depolarization ratio (PLDR) and lidar ratio (LR) values measured over Europe for stratospheric smoke originating from Canadian wildfires. The smoke layers were detected both in the troposphere and the stratosphere, though in the latter case the particles presented PLDR values of almost 18% at 532 nm as well as a strong spectral dependence from the UV to the near-IR wavelength. Although recent simulation studies of rather complicated smoke particle morphologies have shown that heavily coated smoke aggregates can produce large PLDR, herein we propose a much simpler model of compact near-spherical smoke particles. This assumption allows for the reproduction of the observed intensive optical properties of stratospheric smoke, as well as their spectral dependence. We further examine whether an extension of the current Aerosol Robotic Network (AERONET) scattering model to include the near-spherical shapes could be of benefit to the AERONET retrieval for stratospheric smoke cases associated with enhanced PLDR. Results of our study illustrate the fact that triple-wavelength PLDR and LR lidar measurements can provide us with additional insight when it comes to particle characterization. © 2020 Author(s).
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    Experimental assessment of a micro-pulse lidar system in comparison with reference lidar measurements for aerosol optical properties retrieval
    (Katlenburg-Lindau : European Geosciences Union, 2021) Córdoba-Jabonero, Carmen; Ansmann, Albert; Jiménez, Cristofer; Baars, Holger; López-Cayuela, María-Ángeles; Engelmann, Ronny
    Simultaneous observations of a polarized micro-pulse lidar (P-MPL) system and two reference European Aerosol Research Lidar Network lidars running at the Leipzig site Germany, 51.4g gN, 12.4g gE; 125gmga.s.l.) were performed during a comprehensive 2-month field intercomparison campaign in summer 2019. An experimental assessment regarding both the overlap (OVP) correction of the P-MPL signal profiles and the volume linear depolarization ratio (VLDR) analysis, together with its impact on the retrieval of the aerosol optical properties, is achieved; the experimental procedure used is also described. The optimal lidar-specific OVP function is experimentally determined, highlighting that the one delivered by the P-MPL manufacturer cannot be used long. Among the OVP functions examined, the averaged function between those obtained from the comparison of the P-MPL observations with those of the other two reference lidars seems to be the best proxy at both near- and far-field ranges. In addition, the impact of the OVP function on the accuracy of the retrieved profiles of the total particle backscatter coefficient (PBC) and the particle linear depolarization ratio (PLDR) is examined. The VLDR profile is obtained and compared with that derived from the reference lidar, showing that it needs to be corrected by a small offset value with good accuracy. Once P-MPL measurements are optimally (OVP, VLDR) corrected, both the PBC and PLDR profiles can be accurately derived and are in good agreement with reference aerosol retrievals. Overall, as a systematic requirement for lidar systems, an adequate OVP function determination and VLDR testing analysis needs to be performed on a regular basis to correct the P-MPL measurements in order to derive suitable aerosol products. A dust event observed in Leipzig in June 2019 is used for illustration.
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    Target categorization of aerosol and clouds by continuous multiwavelength-polarization lidar measurements
    (Katlenburg-Lindau : Copernicus, 2017) Baars, Holger; Seifert, Patric; Engelmann, Ronny; Wandinger, Ulla
    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 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.
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    An overview of the first decade of PollyNET: An emerging network of automated Raman-polarization lidars for continuous aerosol profiling
    (München : European Geopyhsical Union, 2016) Baars, Holger; Kanitz, Thomas; Engelmann, Ronny; Althausen, Dietrich; Heese, Birgit; Komppula, Mika; Preißler, Jana; Tesche, Matthias; Ansmann, Albert; Wandinger, Ulla; Lim, Jae-Hyun; Ahn, Joon Young; Stachlewska, Iwona S.; Amiridis, Vassilis; Marinou, Eleni; Seifert, Patric; Hofer, Julian; Skupin, Annett; Schneider, Florian; Bohlmann, Stephanie; Foth, Andreas; Bley, Sebastian; Pfüller, Anne; Giannakaki, Eleni; Lihavainen, Heikki; Viisanen, Yrjö; Hooda, Rakesh Kumar; Pereira, Sérgio Nepomuceno; Bortol, Daniele; Wagner, Frank; Mattis, Ina; Janicka, Lucja; Markowicz, Krzysztof M.; Achtert, Peggy; Artaxo, Paulo; Pauliquevis, Theotonio; Souza, Rodrigo A.F.; Sharma, Ved Prakesh; van Zyl, Pieter Gideon; Beukes, Johan Paul; Sun, Junying; Rohwer, Erich G.; Deng, Ruru; Mamouri, Rodanthi-Elisavet; Zamorano, Felix
    A global vertically resolved aerosol data set covering more than 10 years of observations at more than 20 measurement sites distributed from 63° N to 52° S and 72° W to 124° E has been achieved within the Raman and polarization lidar network PollyNET. This network consists of portable, remote-controlled multiwavelength-polarization-Raman lidars (Polly) for automated and continuous 24/7 observations of clouds and aerosols. PollyNET is an independent, voluntary, and scientific network. All Polly lidars feature a standardized instrument design with different capabilities ranging from single wavelength to multiwavelength systems, and now apply unified calibration, quality control, and data analysis. The observations are processed in near-real time without manual intervention, and are presented online at http://polly.tropos.de/. The paper gives an overview of the observations on four continents and two research vessels obtained with eight Polly systems. The specific aerosol types at these locations (mineral dust, smoke, dust-smoke and other dusty mixtures, urban haze, and volcanic ash) are identified by their Ångström exponent, lidar ratio, and depolarization ratio. The vertical aerosol distribution at the PollyNET locations is discussed on the basis of more than 55 000 automatically retrieved 30 min particle backscatter coefficient profiles at 532 nm as this operating wavelength is available for all Polly lidar systems. A seasonal analysis of measurements at selected sites revealed typical and extraordinary aerosol conditions as well as seasonal differences. These studies show the potential of PollyNET to support the establishment of a global aerosol climatology that covers the entire troposphere.
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    Detection and attribution of aerosol-cloud interactions in large-domain large-eddy simulations with the ICOsahedral Non-hydrostatic model
    (Katlenburg-Lindau : EGU, 2020) Costa-Surós, Montserrat; Sourdeval, Odran; Acquistapace, Claudia; Baars, Holger; Carbajal Henken, Cintia; Genz, Christa; Hesemann, Jonas; Jimenez, Cristofer; König, Marcel; Kretzschmar, Jan; Madenach, Nils; Meyer, Catrin I.; Schrödner, Roland; Seifert, Patric; Senf, Fabian; Brueck, Matthias; Cioni, Guido; Engels, Jan Frederik; Fieg, Kerstin; Gorges, Ksenia; Heinze, Rieke; Kumar Siligam, Pavan; Burkhardt, Ulrike; Crewell, Susanne; Hoose, Corinna; Seifert, Axel; Tegen, Ina; Quaas, Johannes
    Clouds and aerosols contribute the largest uncertainty to current estimates and interpretations of the Earth's changing energy budget. Here we use a new-generation large-domain large-eddy model, ICON-LEM (ICOsahedral Non-hydrostatic Large Eddy Model), to simulate the response of clouds to realistic anthropogenic perturbations in aerosols serving as cloud condensation nuclei (CCN). The novelty compared to previous studies is that (i) the LEM is run in weather prediction mode and with fully interactive land surface over a large domain and (ii) a large range of data from various sources are used for the detection and attribution. The aerosol perturbation was chosen as peak-aerosol conditions over Europe in 1985, with more than fivefold more sulfate than in 2013. Observational data from various satellite and ground-based remote sensing instruments are used, aiming at the detection and attribution of this response. The simulation was run for a selected day (2 May 2013) in which a large variety of cloud regimes was present over the selected domain of central Europe. It is first demonstrated that the aerosol fields used in the model are consistent with corresponding satellite aerosol optical depth retrievals for both 1985 (perturbed) and 2013 (reference) conditions. In comparison to retrievals from groundbased lidar for 2013, CCN profiles for the reference conditions were consistent with the observations, while the ones for the 1985 conditions were not. Similarly, the detection and attribution process was successful for droplet number concentrations: the ones simulated for the 2013 conditions were consistent with satellite as well as new ground-based lidar retrievals, while the ones for the 1985 conditions were outside the observational range. For other cloud quantities, including cloud fraction, liquid water path, cloud base altitude and cloud lifetime, the aerosol response was small compared to their natural vari ability. Also, large uncertainties in satellite and ground-based observations make the detection and attribution difficult for these quantities. An exception to this is the fact that at a large liquid water path value (LWP > 200 g m-2), the control simulation matches the observations, while the perturbed one shows an LWP which is too large. The model simulations allowed for quantifying the radiative forcing due to aerosol-cloud interactions, as well as the adjustments to this forcing. The latter were small compared to the variability and showed overall a small positive radiative effect. The overall effective radiative forcing (ERF) due to aerosol-cloud interactions (ERFaci) in the simulation was dominated thus by the Twomey effect and yielded for this day, region and aerosol perturbation-2:6 W m-2. Using general circulation models to scale this to a global-mean present-day vs. pre-industrial ERFaci yields a global ERFaci of-0:8 W m-2 © 2020 Author(s).
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    Estimation of cloud condensation nuclei number concentrations and comparison to in situ and lidar observations during the HOPE experiments
    (Katlenburg-Lindau : EGU, 2020) Genz, Christa; Schrödner, Roland; Heinold, Bernd; Henning, Silvia; Baars, Holger; Spindler, Gerald; Tegen, Ina
    Atmospheric aerosol particles are the precondition for the formation of cloud droplets and therefore have large influence on the microphysical and radiative properties of clouds. In this work, four different methods to derive or measure number concentrations of cloud condensation nuclei (CCN) were analyzed and compared for presentday aerosol conditions: (i) a model parameterization based on simulated particle concentrations, (ii) the same parameterization based on gravimetrical particle measurements, (iii) direct CCN measurements with a CCN counter, and (iv) lidarderived and in situ measured vertical CCN profiles. In order to allow for sensitivity studies of the anthropogenic impact, a scenario to estimate the maximum CCN concentration under peak aerosol conditions of the mid-1980s in Europe was developed as well. In general, the simulations are in good agreement with the observations. At ground level, average values between 0.7 and 1:5 × 109 CCNm-3 at a supersaturation of 0.2 % were found with the different methods under present-day conditions. The discrimination of the chemical species revealed an almost equal contribution of ammonium sulfate and ammonium nitrate to the total number of CCN for present-day conditions. This was not the case for the peak aerosol scenario, in which it was assumed that no ammonium nitrate was formed while large amounts of sulfate were present, consuming all available ammonia during ammonium sulfate formation. The CCN number concentration at five different supersaturation values has been compared to the measurements. The discrepancies between model and in situ observations were lowest for the lowest (0.1 %) and highest supersaturations (0.7 %). For supersaturations between 0.3 % and 0.5 %, the model overestimated the potentially activated particle fraction by around 30 %. By comparing the simulation with observed profiles, the vertical distribution of the CCN concentration was found to be overestimated by up to a factor of 2 in the boundary layer. The analysis of the modern (year 2013) and the peak aerosol scenario (expected to be representative of the mid-1980s over Europe) resulted in a scaling factor, which was defined as the quotient of the average vertical profile of the peak aerosol and present-day CCN concentration. This factor was found to be around 2 close to the ground, increasing to around 3.5 between 2 and 5 km and approaching 1 (i.e., no difference between present-day and peak aerosol conditions) with further increasing height. © 2020 Author(s).
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    EARLINET Single Calculus Chain – technical – Part 2: Calculation of optical products
    (München : European Geopyhsical Union, 2016) Mattis, Ina; D'Amico, Giuseppe; Baars, Holger; Amodeo, Aldo; Madonna, Fabio; Iarlori, Marco
    In this paper we present the automated software tool ELDA (EARLINET Lidar Data Analyzer) for the retrieval of profiles of optical particle properties from lidar signals. This tool is one of the calculus modules of the EARLINET Single Calculus Chain (SCC) which allows for the analysis of the data of many different lidar systems of EARLINET in an automated, unsupervised way. ELDA delivers profiles of particle extinction coefficients from Raman signals as well as profiles of particle backscatter coefficients from combinations of Raman and elastic signals or from elastic signals only. Those analyses start from pre-processed signals which have already been corrected for background, range dependency and hardware specific effects. An expert group reviewed all algorithms and solutions for critical calculus subsystems which are used within EARLINET with respect to their applicability for automated retrievals. Those methods have been implemented in ELDA. Since the software was designed in a modular way, it is possible to add new or alternative methods in future. Most of the implemented algorithms are well known and well documented, but some methods have especially been developed for ELDA, e.g., automated vertical smoothing and temporal averaging or the handling of effective vertical resolution in the case of lidar ratio retrievals, or the merging of near-range and far-range products. The accuracy of the retrieved profiles was tested following the procedure of the EARLINET-ASOS algorithm inter-comparison exercise which is based on the analysis of synthetic signals. Mean deviations, mean relative deviations, and normalized root-mean-square deviations were calculated for all possible products and three height layers. In all cases, the deviations were clearly below the maximum allowed values according to the EARLINET quality requirements. The primary goal of ELPP is to enable the application of quality-assured procedures in the lidar data analysis starting from the raw lidar data. This provides the added value of full traceability of each delivered lidar product. Several tests have been performed to check the proper functioning of ELPP. The whole SCC has been tested with the same synthetic data sets, which were used for the EARLINET algorithm inter-comparison exercise. ELPP has been successfully employed for the automatic near-real-time pre-processing of the raw lidar data measured during several EARLINET inter-comparison campaigns as well as during intense field campaigns.
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    EARLINET instrument intercomparison campaigns: Overview on strategy and results
    (München : European Geopyhsical Union, 2016) Wandinger, Ulla; Freudenthaler, Volker; Baars, Holger; Amodeo, Aldo; Engelmann, Ronny; Mattis, Ina; Groß, Silke; Pappalardo, Gelsomina; Giunta, Aldo; D'Amico, Giuseppe; Chaikovsky, Anatoli; Osipenko, Fiodor; Slesar, Alexander; Nicolae, Doina; Belegante, Livio; Talianu, Camelia; Serikov, Ilya; Linné, Holger; Jansen, Friedhelm; Apituley, Arnoud; Wilson, Keith M.; de Graaf, Martin; Trickl, Thomas; Giehl, Helmut; Adam, Mariana; Comerón, Adolfo; Muñoz-Porcar, Constantino; Rocadenbosch, Francesc; Sicard, Michaël; Tomás, Sergio; Lange, Diego; Kumar, Dhiraj; Pujadas, Manuel; Molero, Francisco; Fernández, Alfonso J.; Alados-Arboledas, Lucas; Bravo-Aranda, Juan Antonio; Navas-Guzmán, Francisco; Guerrero-Rascado, Juan Luis; Granados-Muñoz, María José; Preißler, Jana; Wagner, Frank; Gausa, Michael; Grigorov, Ivan; Stoyanov, Dimitar; Iarlori, Marco; Rizi, Vincenco; Spinelli, Nicola; Boselli, Antonella; Wang, Xuan; Feudo, Teresa Lo; Perrone, Maria Rita; De Tomas, Ferdinando; Burlizzi, Pasquale
    This paper introduces the recent European Aerosol Research Lidar Network (EARLINET) quality-assurance efforts at instrument level. Within two dedicated campaigns and five single-site intercomparison activities, 21 EARLINET systems from 18 EARLINET stations were intercompared between 2009 and 2013. A comprehensive strategy for campaign setup and data evaluation has been established. Eleven systems from nine EARLINET stations participated in the EARLINET Lidar Intercomparison 2009 (EARLI09). In this campaign, three reference systems were qualified which served as traveling standards thereafter. EARLINET systems from nine other stations have been compared against these reference systems since 2009. We present and discuss comparisons at signal and at product level from all campaigns for more than 100 individual measurement channels at the wavelengths of 355, 387, 532, and 607 nm. It is shown that in most cases, a very good agreement of the compared systems with the respective reference is obtained. Mean signal deviations in predefined height ranges are typically below ±2 %. Particle backscatter and extinction coefficients agree within ±2  ×  10−4 km−1 sr−1 and ± 0.01 km−1, respectively, in most cases. For systems or channels that showed larger discrepancies, an in-depth analysis of deficiencies was performed and technical solutions and upgrades were proposed and realized. The intercomparisons have reinforced confidence in the EARLINET data quality and allowed us to draw conclusions on necessary system improvements for some instruments and to identify major challenges that need to be tackled in the future.
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    An 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 Luís; Amiridis, Vassilis; Kokkalis, Panagiotis; Apituley, Arnoud; Baars, Holger; Schwarz, Anja; Wandinger, Ulla; Binietoglou, Ioannis; Nicolae, Doina; Bortoli, Daniele; Comerón, Adolfo; Rodríguez-Gómez, Alejandro; Sicard, Michaël; Papayannis, Alex; Wiegner, Matthias
    We 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.
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    Large-eddy simulations over Germany using ICON: A comprehensive evaluation
    (Hoboken, NJ : Wiley, 2017) Heinze, Rieke; Dipankar, Anurag; Henken, Cintia Carbajal; Moseley, Christopher; Sourdeval, Odran; Trömel, Silke; Xie, Xinxin; Adamidis, Panos; Ament, Felix; Baars, Holger; Barthlott, Christian; Behrendt, Andreas; Blahak, Ulrich; Bley, Sebastian; Brdar, Slavko; Brueck, Matthias; Crewell, Susanne; Deneke, Hartwig; Di Girolamo, Paolo; Evaristo, Raquel; Fischer, Jürgen; Frank, Christopher; Friederichs, Petra; Göcke, Tobias; Gorges, Ksenia; Hande, Luke; Hanke, Moritz; Hansen, Akio; Hege, Hans-Christian; Hoose, Corinna; Jahns, Thomas; Kalthoff, Norbert; Klocke, Daniel; Kneifel, Stefan; Knippertz, Peter; Kuhn, Alexander; van Laar, Thriza; Macke, Andreas; Maurer, Vera; Mayer, Bernhard; Meyer, Catrin I.; Muppa, Shravan K.; Neggers, Roeland A.J.; Orlandi, Emiliano; Pantillon, Florian; Pospichal, Bernhard; Röber, Niklas; Scheck, Leonhard; Seifert, Axel; Seifert, Patric; Senf, Fabian; Siligam, Pavan; Simmer, Clemens; Steinke, Sandra; Stevens, Bjorn; Wapler, Kathrin; Weniger, Michael; Wulfmeyer, Volker; Zängl, Günther; Zhangl, Dan; Quaase, Johannes
    Large-eddy simulations (LES) with the new ICOsahedral Non-hydrostatic atmosphere model (ICON) covering Germany are evaluated for four days in spring 2013 using observational data from various sources. Reference simulations with the established Consortium for Small-scale Modelling (COSMO) numerical weather prediction model and further standard LES codes are performed and used as a reference. This comprehensive evaluation approach covers multiple parameters and scales, focusing on boundary-layer variables, clouds and precipitation. The evaluation points to the need to work on parametrizations influencing the surface energy balance, and possibly on ice cloud microphysics. The central purpose for the development and application of ICON in the LES configuration is the use of simulation results to improve the understanding of moist processes, as well as their parametrization in climate models. The evaluation thus aims at building confidence in the model's ability to simulate small- to mesoscale variability in turbulence, clouds and precipitation. The results are encouraging: the high-resolution model matches the observed variability much better at small- to mesoscales than the coarser resolved reference model. In its highest grid resolution, the simulated turbulence profiles are realistic and column water vapour matches the observed temporal variability at short time-scales. Despite being somewhat too large and too frequent, small cumulus clouds are well represented in comparison with satellite data, as is the shape of the cloud size spectrum. Variability of cloud water matches the satellite observations much better in ICON than in the reference model. In this sense, it is concluded that the model is fit for the purpose of using its output for parametrization development, despite the potential to improve further some important aspects of processes that are also parametrized in the high-resolution model.