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Now showing 1 - 6 of 6
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    Increasing the spatial resolution of cloud property retrievals from Meteosat SEVIRI by use of its high-resolution visible channel: implementation and examples
    (Katlenburg-Lindau : European Geosciences Union, 2021) Deneke, Hartwig; Barrientos-Velasco, Carola; Bley, Sebastian; Hünerbein, Anja; Lenk, Stephan; Macke, Andreas; Meirink, Jan Fokke; Schroedter-Homscheidt, Marion; Senf, Fabian; Wang, Ping; Werner, Frank; Witthuhn, Jonas
    The modification of an existing cloud property retrieval scheme for the Spinning Enhanced Visible and Infrared Imager (SEVIRI) instrument on board the geostationary Meteosat satellites is described to utilize its high-resolution visible (HRV) channel for increasing the spatial resolution of its physical outputs. This results in products with a nadir spatial resolution of 1×1ĝ€¯km2 compared to the standard 3×3ĝ€¯km2 resolution offered by the narrowband channels. This improvement thus greatly reduces the resolution gap between current geostationary and polar-orbiting meteorological satellite imagers. In the first processing step, cloudiness is determined from the HRV observations by a threshold-based cloud masking algorithm. Subsequently, a linear model that links the 0.6ĝ€¯μm, 0.8ĝ€¯μm, and HRV reflectances provides a physical constraint to incorporate the spatial high-frequency component of the HRV observations into the retrieval of cloud optical depth. The implementation of the method is described, including the ancillary datasets used. It is demonstrated that the omission of high-frequency variations in the cloud-absorbing 1.6ĝ€¯μm channel results in comparatively large uncertainties in the retrieved cloud effective radius, likely due to the mismatch in channel resolutions. A newly developed downscaling scheme for the 1.6ĝ€¯μm reflectance is therefore applied to mitigate the effects of this scale mismatch. Benefits of the increased spatial resolution of the resulting SEVIRI products are demonstrated for three example applications: (i) for a convective cloud field, it is shown that significantly better agreement between the distributions of cloud optical depth retrieved from SEVIRI and from collocated MODIS observations is achieved. (ii) The temporal evolution of cloud properties for a growing convective storm at standard and HRV spatial resolutions are compared, illustrating an improved contrast in growth signatures resulting from the use of the HRV channel. (iii) An example of surface solar irradiance, determined from the retrieved cloud properties, is shown, for which the HRV channel helps to better capture the large spatiotemporal variability induced by convective clouds. These results suggest that incorporating the HRV channel into the retrieval has potential for improving Meteosat-based cloud products for several application domains.
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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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    Cloud mask algorithm from the EarthCARE Multi-Spectral Imager: the M-CM products
    (Katlenburg-Lindau : Copernicus, 2023) Hünerbein, Anja; Bley, Sebastian; Horn, Stefan; Deneke, Hartwig; Walther, Andi
    The EarthCARE (Earth Clouds, Aerosols and Radiation Explorer) satellite mission will provide new insights into aerosol-cloud-radiation interactions by means of synergistic observations of the Earth's atmosphere from a collection of active and passive remote sensing instruments, flying on a single satellite platform. The Multi-Spectral Imager (MSI) will provide visible and infrared images in the cross-track direction with a 150km swath and a pixel sampling at 500m. The suite of MSI cloud algorithms will deliver cloud macro- and microphysical properties complementary to the vertical profiles measured from the Atmospheric Lidar (ATLID) and the Cloud Profiling Radar (CPR) instruments. This paper provides an overview of the MSI cloud mask algorithm (M-CM) being developed to derive the cloud flag, cloud phase and cloud type products, which are essential inputs to downstream EarthCARE algorithms providing cloud optical and physical properties (M-COP) and aerosol optical properties (M-AOT). The MSI cloud mask algorithm has been applied to simulated test data from the EarthCARE end-to-end simulator and satellite data from the Moderate Resolution Imaging Spectroradiometer (MODIS) as well as from the Spinning Enhanced Visible InfraRed Imager (SEVIRI). Verification of the MSI cloud mask algorithm to the simulated test data and the official cloud products from SEVIRI and MODIS demonstrates a good performance of the algorithm. Some discrepancies are found, however, for the detection of thin cirrus clouds over bright surfaces like desert or snow. This will be improved by tuning of the thresholds once real observations are available.
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    Californian Wildfire Smoke Over Europe: A First Example of the Aerosol Observing Capabilities of Aeolus Compared to Ground‐Based Lidar
    (Hoboken, NJ : Wiley, 2021) Baars, Holger; Radenz, Martin; Floutsi, Athena Augusta; Engelmann, Ronny; Althausen, Dietrich; Heese, Birgit; Ansmann, Albert; Flament, Thomas; Dabas, Alain; Trapon, Dimitri; Reitebuch, Oliver; Bley, Sebastian; Wandinger, Ulla
    In September 2020, extremely strong wildfires in the western United States of America (i.e., mainly in California) produced large amounts of smoke, which was lifted into the free troposphere. These biomass-burning-aerosol (BBA) layers were transported from the US west coast toward central Europe within 3–4 days turning the sky milky and receiving high media attention. The present study characterizes this pronounced smoke plume above Leipzig, Germany, using a ground-based multiwavelength-Raman-polarization lidar and the aerosol/cloud product of ESA’s wind lidar mission Aeolus. An exceptional high smoke-AOT >0.4 was measured, yielding to a mean mass concentration of 8 μg m−3. The 355 nm lidar ratio was moderate at around 40–50 sr. The Aeolus-derived backscatter, extinction and lidar ratio profiles agree well with the observations of the ground-based lidar PollyXT considering the fact that Aeolus’ aerosol and cloud products are still preliminary and subject to ongoing algorithm improvements.
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    Metrics for the evaluation of warm convective cloud fields in a large-eddy simulation with Meteosat images
    (Weinheim [u.a.] : Wiley, 2017) Bley, Sebastian; Deneke, Hartwig; Senf, Fabian; Scheck, Leonhard
    The representation of warm convective clouds in atmospheric models and satellite observations can considerably deviate from each other partly due to different spatial resolutions. This study aims to establish appropriate metrics to evaluate high-resolution simulations of convective clouds by the ICON Large-Eddy Model (ICON-LEM) with observations from Meteosat SEVIRI over Germany. The time series and frequency distributions of convective cloud fraction and liquid water path (LWP) are analyzed. Furthermore, the study focuses on size distributions and decorrelation scales of warm convective cloud fields. The investigated metrics possess a pronounced sensitivity to the apparent spatial resolution. At the fine spatial scale, the simulations show higher occurrence frequencies of large LWP values and a factor of two to four smaller convective cloud fractions. Coarse-graining of simulated fields to the optical resolution of Meteosat essentially removes the differences between the observed and simulated metrics. The distribution of simulated cloud sizes compares well with the observations and can be represented by a power law, with a moderate resolution sensitivity. A lower limit of cloud sizes is identified, which is 8–10 times the native grid resolution of the model. This likely marks the effective model resolution beyond which the scaling behaviour of considered metrics is not reliable, implying that a further increase in spatial resolution would be desirable to better resolve cloud processes below 1 km. It is finally shown that ICON-LEM is consistent with spatio-temporal decorrelation scales observed with Meteosat having values of 30 min and 7 km, if transferred to the true optical satellite resolution. However, the simulated Lagrangian decorrelation times drop to 10 min at 1 km resolution, a scale covered by the upcoming generation of geostationary satellites.
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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.