Search Results
The HD(CP)2 Observational Prototype Experiment (HOPE) - An overview
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, Xinxin
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 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.
EUREC4A
2021, Stevens, Bjorn, Bony, Sandrine, Farrell, David, Ament, Felix, Blyth, Alan, Fairall, Christopher, Karstensen, Johannes, Quinn, Patricia K., Speich, Sabrina, Acquistapace, Claudia, Aemisegger, Franziska, Crewell, Susanne, Cronin, Timothy, Cui, Zhiqiang, Cuypers, Yannis, Daley, Alton, Damerell, Gillian M., Dauhut, Thibaut, Deneke, Hartwig, Desbios, Jean-Philippe, Dörner, Steffen, Albright, Anna Lea, Donner, Sebastian, Douet, Vincent, Drushka, Kyla, Dütsch, Marina, Ehrlich, André, Emanuel, Kerry, Emmanouilidis, Alexandros, Etienne, Jean-Claude, Etienne-Leblanc, Sheryl, Faure, Ghislain, Bellenger, Hugo, Feingold, Graham, Ferrero, Luca, Fix, Andreas, Flamant, Cyrille, Flatau, Piotr Jacek, Foltz, Gregory R., Forster, Linda, Furtuna, Iulian, Gadian, Alan, Galewsky, Joseph, Bodenschatz, Eberhard, Gallagher, Martin, Gallimore, Peter, Gaston, Cassandra, Gentemann, Chelle, Geyskens, Nicolas, Giez, Andreas, Gollop, John, Gouirand, Isabelle, Gourbeyre, Christophe, de Graaf, Dörte, Caesar, Kathy-Ann, de Groot, Geiske E., Grosz, Robert, Güttler, Johannes, Gutleben, Manuel, Hall, Kashawn, Harris, George, Helfer, Kevin C., Henze, Dean, Herbert, Calvert, Holanda, Bruna, Chewitt-Lucas, Rebecca, Ibanez-Landeta, Antonio, Intrieri, Janet, Iyer, Suneil, Julien, Fabrice, Kalesse, Heike, Kazil, Jan, Kellman, Alexander, Kidane, Abiel T., Kirchner, Ulrike, Klingebiel, Marcus, de Boer, Gijs, Körner, Mareike, Kremper, Leslie Ann, Kretzschmar, Jan, Krüger, Ovid, Kumala, Wojciech, Kurz, Armin, L'Hégaret, Pierre, Labaste, Matthieu, Lachlan-Cope, Tom, Laing, Arlene, Delanoë, Julien, Landschützer, Peter, Lang, Theresa, Lange, Diego, Lange, Ingo, Laplace, Clément, Lavik, Gauke, Laxenaire, Rémi, Le Bihan, Caroline, Leandro, Mason, Lefevre, Nathalie, Denby, Leif, Lena, Marius, Lenschow, Donald, Li, Qiang, Lloyd, Gary, Los, Sebastian, Losi, Niccolò, Lovell, Oscar, Luneau, Christopher, Makuch, Przemyslaw, Malinowski, Szymon, Ewald, Florian, Manta, Gaston, Marinou, Eleni, Marsden, Nicholas, Masson, Sebastien, Maury, Nicolas, Mayer, Bernhard, Mayers-Als, Margarette, Mazel, Christophe, McGeary, Wayne, McWilliams, James C., Fildier, Benjamin, Mech, Mario, Mehlmann, Melina, Meroni, Agostino Niyonkuru, Mieslinger, Theresa, Minikin, Andreas, Minnett, Peter, Möller, Gregor, Morfa Avalos, Yanmichel, Muller, Caroline, Musat, Ionela, Forde, Marvin, Napoli, Anna, Neuberger, Almuth, Noisel, Christophe, Noone, David, Nordsiek, Freja, Nowak, Jakub L., Oswald, Lothar, Parker, Douglas J., Peck, Carolyn, Person, Renaud, George, Geet, Philippi, Miriam, Plueddemann, Albert, Pöhlker, Christopher, Pörtge, Veronika, Pöschl, Ulrich, Pologne, Lawrence, Posyniak, Michał, Prange, Marc, Quiñones Meléndez, Estefanía, Radtke, Jule, Gross, Silke, Ramage, Karim, Reimann, Jens, Renault, Lionel, Reus, Klaus, Reyes, Ashford, Ribbe, Joachim, Ringel, Maximilian, Ritschel, Markus, Rocha, Cesar B., Rochetin, Nicolas, Hagen, Martin, Röttenbacher, Johannes, Rollo, Callum, Royer, Haley, Sadoulet, Pauline, Saffin, Leo, Sandiford, Sanola, Sandu, Irina, Schäfer, Michael, Schemann, Vera, Schirmacher, Imke, Hausold, Andrea, Schlenczek, Oliver, Schmidt, Jerome, Schröder, Marcel, Schwarzenboeck, Alfons, Sealy, Andrea, Senff, Christoph J., Serikov, Ilya, Shohan, Samkeyat, Siddle, Elizabeth, Smirnov, Alexander, Heywood, Karen J., Späth, Florian, Spooner, Branden, Stolla, M. Katharina, Szkółka, Wojciech, de Szoeke, Simon P., Tarot, Stéphane, Tetoni, Eleni, Thompson, Elizabeth, Thomson, Jim, Tomassini, Lorenzo, Hirsch, Lutz, Totems, Julien, Ubele, Alma Anna, Villiger, Leonie, von Arx, Jan, Wagner, Thomas, Walther, Andi, Webber, Ben, Wendisch, Manfred, Whitehall, Shanice, Wiltshire, Anton, Jacob, Marek, Wing, Allison A., Wirth, Martin, Wiskandt, Jonathan, Wolf, Kevin, Worbes, Ludwig, Wright, Ethan, Wulfmeyer, Volker, Young, Shanea, Zhang, Chidong, Zhang, Dongxiao, Jansen, Friedhelm, Ziemen, Florian, Zinner, Tobias, Zöger, Martin, Kinne, Stefan, Klocke, Daniel, Kölling, Tobias, Konow, Heike, Lothon, Marie, Mohr, Wiebke, Naumann, Ann Kristin, Nuijens, Louise, Olivier, Léa, Pincus, Robert, Pöhlker, Mira, Reverdin, Gilles, Roberts, Gregory, Schnitt, Sabrina, Schulz, Hauke, Siebesma, A. Pier, Stephan, Claudia Christine, Sullivan, Peter, Touzé-Peiffer, Ludovic, Vial, Jessica, Vogel, Raphaela, Zuidema, Paquita, Alexander, Nicola, Alves, Lyndon, Arixi, Sophian, Asmath, Hamish, Bagheri, Gholamhossein, Baier, Katharina, Bailey, Adriana, Baranowski, Dariusz, Baron, Alexandre, Barrau, Sébastien, Barrett, Paul A., Batier, Frédéric, Behrendt, Andreas, Bendinger, Arne, Beucher, Florent, Bigorre, Sebastien, Blades, Edmund, Blossey, Peter, Bock, Olivier, Böing, Steven, Bosser, Pierre, Bourras, Denis, Bouruet-Aubertot, Pascale, Bower, Keith, Branellec, Pierre, Branger, Hubert, Brennek, Michal, Brewer, Alan, Brilouet, Pierre-Etienne, Brügmann, Björn, Buehler, Stefan A., Burke, Elmo, Burton, Ralph, Calmer, Radiance, Canonici, Jean-Christophe, Carton, Xavier, Cato Jr., Gregory, Charles, Jude Andre, Chazette, Patrick, Chen, Yanxu, Chilinski, Michal T., Choularton, Thomas, Chuang, Patrick, Clarke, Shamal, Coe, Hugh, Cornet, Céline, Coutris, Pierre, Couvreux, Fleur
The science guiding the EUREC4A campaign and its measurements is presented. EUREC4A comprised roughly 5 weeks of measurements in the downstream winter trades of the North Atlantic – eastward and southeastward of Barbados. Through its ability to characterize processes operating across a wide range of scales, EUREC4A marked a turning point in our ability to observationally study factors influencing clouds in the trades, how they will respond to warming, and their link to other components of the earth system, such as upper-ocean processes or the life cycle of particulate matter. This characterization was made possible by thousands (2500) of sondes distributed to measure circulations on meso- (200 km) and larger (500 km) scales, roughly 400 h of flight time by four heavily instrumented research aircraft; four global-class research vessels; an advanced ground-based cloud observatory; scores of autonomous observing platforms operating in the upper ocean (nearly 10 000 profiles), lower atmosphere (continuous profiling), and along the air–sea interface; a network of water stable isotopologue measurements; targeted tasking of satellite remote sensing; and modeling with a new generation of weather and climate models. In addition to providing an outline of the novel measurements and their composition into a unified and coordinated campaign, the six distinct scientific facets that EUREC4A explored – from North Brazil Current rings to turbulence-induced clustering of cloud droplets and its influence on warm-rain formation – are presented along with an overview of EUREC4A's outreach activities, environmental impact, and guidelines for scientific practice. Track data for all platforms are standardized and accessible at https://doi.org/10.25326/165 (Stevens, 2021), and a film documenting the campaign is provided as a video supplement.
Detection and attribution of aerosol-cloud interactions in large-domain large-eddy simulations with the ICOsahedral Non-hydrostatic model
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).
The Arctic Cloud Puzzle: Using ACLOUD/PASCAL Multiplatform Observations to Unravel the Role of Clouds and Aerosol Particles in Arctic Amplification
2019, Wendisch, Manfred, Macke, Andreas, Ehrlich, André, Lüpkes, Christof, Mech, Mario, Chechin, Dmitry, Dethloff, Klaus, Velasco, Carola Barrientos, Bozem, Heiko, Brückner, Marlen, Clemen, Hans-Christian, Crewell, Susanne, Donth, Tobias, Dupuy, Regis, Ebell, Kerstin, Egerer, Ulrike, Engelmann, Ronny, Engler, Christa, Eppers, Oliver, Gehrmann, Martin, Gong, Xianda, Gottschalk, Matthias, Gourbeyre, Christophe, Griesche, Hannes, Hartmann, Jörg, Hartmann, Markus, Heinold, Bernd, Herber, Andreas, Herrmann, Hartmut, Heygster, Georg, Hoor, Peter, Jafariserajehlou, Soheila, Jäkel, Evelyn, Järvinen, Emma, Jourdan, Olivier, Kästner, Udo, Kecorius, Simonas, Knudsen, Erlend M., Köllner, Franziska, Kretzschmar, Jan, Lelli, Luca, Leroy, Delphine, Maturilli, Marion, Mei, Linlu, Mertes, Stephan, Mioche, Guillaume, Neuber, Roland, Nicolaus, Marcel, Nomokonova, Tatiana, Notholt, Justus, Palm, Mathias, van Pinxteren, Manuela, Quaas, Johannes, Richter, Philipp, Ruiz-Donoso, Elena, Schäfer, Michael, Schmieder, Katja, Schnaiter, Martin, Schneider, Johannes, Schwarzenböck, Alfons, Seifert, Patric, Shupe, Matthew D., Siebert, Holger, Spreen, Gunnar, Stapf, Johannes, Stratmann, Frank, Vogl, Teresa, Welti, André, Wex, Heike, Wiedensohler, Alfred, Zanatta, Marco, Zeppenfeld, Sebastian
Clouds play an important role in Arctic amplification. This term represents the recently observed enhanced warming of the Arctic relative to the global increase of near-surface air temperature. However, there are still important knowledge gaps regarding the interplay between Arctic clouds and aerosol particles, and surface properties, as well as turbulent and radiative fluxes that inhibit accurate model simulations of clouds in the Arctic climate system. In an attempt to resolve this so-called Arctic cloud puzzle, two comprehensive and closely coordinated field studies were conducted: the Arctic Cloud Observations Using Airborne Measurements during Polar Day (ACLOUD) aircraft campaign and the Physical Feedbacks of Arctic Boundary Layer, Sea Ice, Cloud and Aerosol (PASCAL) ice breaker expedition. Both observational studies were performed in the framework of the German Arctic Amplification: Climate Relevant Atmospheric and Surface Processes, and Feedback Mechanisms (AC) project. They took place in the vicinity of Svalbard, Norway, in May and June 2017. ACLOUD and PASCAL explored four pieces of the Arctic cloud puzzle: cloud properties, aerosol impact on clouds, atmospheric radiation, and turbulent dynamical processes. The two instrumented Polar 5 and Polar 6 aircraft; the icebreaker Research Vessel (R/V) Polarstern; an ice floe camp including an instrumented tethered balloon; and the permanent ground-based measurement station at Ny-Ålesund, Svalbard, were employed to observe Arctic low- and mid-level mixed-phase clouds and to investigate related atmospheric and surface processes. The Polar 5 aircraft served as a remote sensing observatory examining the clouds from above by downward-looking sensors; the Polar 6 aircraft operated as a flying in situ measurement laboratory sampling inside and below the clouds. Most of the collocated Polar 5/6 flights were conducted either above the R/V Polarstern or over the Ny-Ålesund station, both of which monitored the clouds from below using similar but upward-looking remote sensing techniques as the Polar 5 aircraft. Several of the flights were carried out underneath collocated satellite tracks. The paper motivates the scientific objectives of the ACLOUD/PASCAL observations and describes the measured quantities, retrieved parameters, and the applied complementary instrumentation. Furthermore, it discusses selected measurement results and poses critical research questions to be answered in future papers analyzing the data from the two field campaigns.
Meteorological conditions during the ACLOUD/PASCAL field campaign near Svalbard in early summer 2017
2018, Knudsen, Erlend M., Heinold, Bernd, Dahlke, Sandro, Bozem, Heiko, Crewell, Susanne, Gorodetskaya, Irina V., Heygster, Georg, Kunkel, Daniel, Maturilli, Marion, Mech, Mario, Viceto, Carolina, Rinke, Annette, Schmithüsen, Holger, Ehrlich, André, Macke, Andreas, Lüpkes, Christof, Wendisch, Manfred
The two concerted field campaigns, Arctic CLoud Observations Using airborne measurements during polar Day (ACLOUD) and the Physical feedbacks of Arctic planetary boundary level Sea ice, Cloud and AerosoL (PASCAL), took place near Svalbard from 23 May to 26 June 2017. They were focused on studying Arctic mixed-phase clouds and involved observations from two airplanes (ACLOUD), an icebreaker (PASCAL) and a tethered balloon, as well as ground-based stations. Here, we present the synoptic development during the
Large-eddy simulations over Germany using ICON: A comprehensive evaluation
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.