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226 results on '"Siebesma, A. Pier"'

1. Clouds dissipate quickly during solar eclipses as the land surface cools

Author

Trees, Victor J. H., de Roode, Stephan R., Wiltink, Job I., Meirink, Jan Fokke, Wang, Ping, Stammes, Piet, and Siebesma, A. Pier

Subjects
Physics - Atmospheric and Oceanic Physics, Astrophysics - Earth and Planetary Astrophysics, Astrophysics - Solar and Stellar Astrophysics, Physics - Geophysics
Abstract

Clouds affected by solar eclipses could influence the reflection of sunlight back into space and might change local precipitation patterns. Satellite cloud retrievals have so far not taken into account the lunar shadow, hindering a reliable spaceborne assessment of the eclipse-induced cloud evolution. Here we use satellite cloud measurements during three solar eclipses between 2005 and 2016 that have been corrected for the partial lunar shadow together with large-eddy simulations to analyze the eclipse-induced cloud evolution. Our corrected data reveal that, over cooling land surfaces, shallow cumulus clouds start to disappear at very small solar obscurations. Our simulations explain that the cloud response was delayed and was initiated at even smaller solar obscurations. We demonstrate that neglecting the disappearance of clouds during a solar eclipse could lead to a considerable overestimation of the eclipse-related reduction of net incoming solar radiation. These findings should spur cloud model simulations of the direct consequences of sunlight-intercepting geoengineering proposals, for which our results serve as a unique benchmark.

Published
2024
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2. Shallow Cumulus Cloud Fields Are Optically Thicker When They Are More Clustered

Author

Alinaghi, Pouriya, Janssens, Martin, Choudhury, Goutam, Goren, Tom, Siebesma, A. Pier, and Glassmeier, Franziska

Subjects
Physics - Atmospheric and Oceanic Physics
Abstract

Shallow trade cumuli over subtropical oceans are a persistent source of uncertainty in climate projections. Mesoscale organization of trade cumulus clouds has been shown to influence their cloud radiative effect (CRE) through cloud cover. We investigate whether organization can explain CRE variability independently of cloud cover variability. By analyzing satellite observations and high-resolution simulations, we show that increased clustering leads to geometrically thicker clouds with larger domain-averaged liquid water paths, smaller cloud droplets, and consequently, larger cloud optical depths. The relationships between these variables are shaped by the mixture of deep cloud cores and shallower interstitial clouds or anvils that characterize cloud organization. Eliminating cloud cover effects, more clustered clouds reflect up to 20 W/m$^2$ more instantaneous shortwave radiation back to space.

Published
2023

3. Non-precipitating shallow cumulus convection is intrinsically unstable to length-scale growth

Author

Janssens, Martin, de Arellano, Jordi Vilà-Guerau, van Heerwaarden, Chiel C., de Roode, Stephan R., Siebesma, A. Pier, and Glassmeier, Franziska

Subjects
Physics - Atmospheric and Oceanic Physics
Abstract

Condensation in cumulus clouds plays a key role in structuring the mean, non-precipitating trade-wind boundary layer. Here, we summarise how this role also explains the spontaneous growth of mesoscale ($>O(10)$ km) fluctuations in clouds and moisture around the mean state in a minimal-physics, large-eddy simulation of the undisturbed period during BOMEX on a large ($O(100)$ km) domain. Small, spatial anomalies in latent heating in cumulus clouds, which form on top of small moisture fluctuations, give rise to circulations that transport moisture, but not heat, from dry to moist regions, and thus reinforce the latent heating anomaly. We frame this positive feedback as a linear instability in mesoscale moisture fluctuations, whose time-scale depends only on i) a vertical velocity scale and ii) the mean environment's vertical structure. In our minimal-physics setting, we show both ingredients are provided by the shallow cumulus convection itself: It is intrinsically unstable to length scale growth. The upshot is that energy released by clouds at kilometre scales may play a more profound and direct role in shaping the mesoscale trade-wind environment than is generally appreciated, motivating further research into the mechanism's relevance.

Published
2022
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6. Open boundary conditions for atmospheric large-eddy simulations and their implementation in DALES4.4.

Author

Liqui Lung, Franciscus, Jakob, Christian, Siebesma, A. Pier, and Jansson, Fredrik

Subjects
WEATHER, TURBULENCE, LARGE eddy simulation models, EDDIES
Abstract

Open boundary conditions were developed for atmospheric large-eddy simulation (LES) models and implemented into the Dutch Atmospheric Large-Eddy Simulation model. The implementation was tested in a "Big Brother"-like setup, in which the simulation with open boundary conditions was forced by an identical control simulation with periodic boundary conditions. The results show that the open boundary implementation has minimal influence on the solution. Both the mean state and the turbulent structures are close to the control simulation, and disturbances at the in- and outflow boundaries are negligible. To emulate a setup in which the LES is coupled to a coarser model, the influence of coarse boundary input was tested by smoothing the output of the periodic control simulation both temporally and spatially before feeding it as input to the simulation with open boundary conditions. When smoothing is applied over larger spatial and longer temporal scales, disturbances start to form at the inflow boundary and an area exists where turbulence needs to develop. Adding synthetic turbulence to the smoothed input reduces the size of this area and the magnitude of the disturbances. [ABSTRACT FROM AUTHOR]

Published
2024
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7. Cancellation of cloud shadow effects in the absorbing aerosol index retrieval algorithm of TROPOMI.

Author

Trees, Victor J. H., Wang, Ping, Stammes, Piet, Tilstra, Lieuwe G., Donovan, David P., and Siebesma, A. Pier

Subjects
BIG data, AEROSOLS, ALGORITHMS, ALBEDO, RADIATIVE transfer, AIR quality, PHASE-shifting interferometry
Abstract

Cloud shadows can be detected in the radiance measurements of the TROPOMI instrument on board the Sentinel-5P satellite due to its high spatial resolution, and could possibly affect its air quality products. The cloud shadow induced signatures are, however, not always apparent and may depend on various cloud and scene parameters. Hence, the quantification of the cloud shadow impact requires the analysis of large data sets. Here we use the cloud shadow detection algorithm DARCLOS to detect cloud shadow pixels in the TROPOMI absorbing aerosol index (AAI) product over Europe during 8 months. For every shadow pixel, we automatically select cloud- and shadow-free neighbour pixels, in order to estimate the cloud shadow induced signature. In addition, we simulate the measured cloud shadow impact on the AAI with our newly developed 3D radiative transfer algorithm MONKI. Both the measurements and simulations show that the average cloud shadow impact on the AAI is close to zero (0.06 and 0.16, respectively). However, the top-of-atmosphere reflectance ratio between 340 and 380 nm, which is used to compute the AAI, is significantly increased in 95 % of the shadow pixels. So, cloud shadows are bluer than surrounding non-shadow pixels. Our simulations explain that the traditional AAI formula intrinsically already corrects for this cloud shadow effect, via the lower retrieved scene albedo. This cancellation of cloud shadow signatures is not always perfect, sometimes yielding second order low and high biases in the AAI which we also successfully reproduce with our simulations. We show that the magnitude of those second order cloud shadow effects depends on various cloud parameters which are difficult to determine for the shadows measured with TROPOMI. We conclude that a potential cloud shadow correction strategy for the TROPOMI AAI would therefore be complicated if not unnecessary. [ABSTRACT FROM AUTHOR]

Published
2024
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12. EUREC 4 A

Author

Massachusetts Institute of Technology. Department of Earth, Atmospheric, and Planetary Sciences, Stevens, Bjorn, Bony, Sandrine, Farrell, David, Ament, Felix, Blyth, Alan, Fairall, Christopher, Karstensen, Johannes, Quinn, Patricia K., Speich, Sabrina, Acquistapace, Claudia, Aemisegger, Franziska, Albright, Anna Lea, Bellenger, Hugo, Bodenschatz, Eberhard, Caesar, Kathy-Ann, Chewitt-Lucas, Rebecca, de Boer, Gijs, Delanoë, Julien, Denby, Leif, Ewald, Florian, Fildier, Benjamin, Forde, Marvin, George, Geet, Gross, Silke, Hagen, Martin, Hausold, Andrea, Heywood, Karen J., Hirsch, Lutz, Jacob, Marek, Jansen, Friedhelm, 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, Crewell, Susanne, Cronin, Timothy, Cui, Zhiqiang, Cuypers, Yannis, Daley, Alton, Damerell, Gillian M., Dauhut, Thibaut, Deneke, Hartwig, Desbios, Jean-Philippe, Dörner, Steffen, Donner, Sebastian, Douet, Vincent, Drushka, Kyla, Dütsch, Marina, Ehrlich, André, Emanuel, Kerry, Emmanouilidis, Alexandros, Etienne, Jean-Claude, Etienne-Leblanc, Sheryl, Faure, Ghislain, Feingold, Graham, Ferrero, Luca, Fix, Andreas, Flamant, Cyrille, Flatau, Piotr Jacek, Foltz, Gregory R., Forster, Linda, Furtuna, Iulian, Gadian, Alan, Galewsky, Joseph, Gallagher, Martin, Gallimore, Peter, Gaston, Cassandra, Gentemann, Chelle, Geyskens, Nicolas, Giez, Andreas, Gollop, John, Gouirand, Isabelle, Gourbeyre, Christophe, de Graaf, Dörte, de Groot, Geiske E., Grosz, Robert, Güttler, Johannes, Gutleben, Manuel, Hall, Kashawn, Harris, George, Helfer, Kevin C., Henze, Dean, Herbert, Calvert, Holanda, Bruna, Ibanez-Landeta, Antonio, Intrieri, Janet, Iyer, Suneil, Julien, Fabrice, Kalesse, Heike, Kazil, Jan, Kellman, Alexander, Kidane, Abiel T., Kirchner, Ulrike, Klingebiel, Marcus, Körner, Mareike, Kremper, Leslie Ann, Kretzschmar, Jan, Krüger, Ovid, Kumala, Wojciech, Kurz, Armin, L'Hégaret, Pierre, Labaste, Matthieu, Lachlan-Cope, Tom, Laing, Arlene, Landschützer, Peter, Lang, Theresa, Lange, Diego, Lange, Ingo, Laplace, Clément, Lavik, Gauke, Laxenaire, Rémi, Le Bihan, Caroline, Leandro, Mason, Lefevre, Nathalie, Lena, Marius, Lenschow, Donald, Li, Qiang, Lloyd, Gary, Los, Sebastian, Losi, Niccolò, Lovell, Oscar, Luneau, Christopher, Makuch, Przemyslaw, Malinowski, Szymon, Manta, Gaston, Marinou, Eleni, Marsden, Nicholas, Masson, Sebastien, Maury, Nicolas, Mayer, Bernhard, Mayers-Als, Margarette, Mazel, Christophe, McGeary, Wayne, McWilliams, James C., Mech, Mario, Mehlmann, Melina, Meroni, Agostino Niyonkuru, Mieslinger, Theresa, Minikin, Andreas, Minnett, Peter, Möller, Gregor, Morfa Avalos, Yanmichel, Muller, Caroline, Musat, Ionela, Napoli, Anna, Neuberger, Almuth, Noisel, Christophe, Noone, David, Nordsiek, Freja, Nowak, Jakub L., Oswald, Lothar, Parker, Douglas J., Peck, Carolyn, Person, Renaud, Philippi, Miriam, Plueddemann, Albert, Pöhlker, Christopher, Pörtge, Veronika, Pöschl, Ulrich, Pologne, Lawrence, Posyniak, Michał, Prange, Marc, Quiñones Meléndez, Estefanía, Radtke, Jule, Ramage, Karim, Reimann, Jens, Renault, Lionel, Reus, Klaus, Reyes, Ashford, Ribbe, Joachim, Ringel, Maximilian, Ritschel, Markus, Rocha, Cesar B., Rochetin, Nicolas, Röttenbacher, Johannes, Rollo, Callum, Royer, Haley, Sadoulet, Pauline, Saffin, Leo, Sandiford, Sanola, Sandu, Irina, Schäfer, Michael, Schemann, Vera, Schirmacher, Imke, Schlenczek, Oliver, Schmidt, Jerome, Schröder, Marcel, Schwarzenboeck, Alfons, Sealy, Andrea, Senff, Christoph J., Serikov, Ilya, Shohan, Samkeyat, Siddle, Elizabeth, Smirnov, Alexander, Späth, Florian, Spooner, Branden, Stolla, M. Katharina, Szkółka, Wojciech, de Szoeke, Simon P., Tarot, Stéphane, Tetoni, Eleni, Thompson, Elizabeth, Thomson, Jim, Tomassini, Lorenzo, Totems, Julien, Ubele, Alma Anna, Villiger, Leonie, von Arx, Jan, Wagner, Thomas, Walther, Andi, Webber, Ben, Wendisch, Manfred, Whitehall, Shanice, Wiltshire, Anton, Wing, Allison A., Wirth, Martin, Wiskandt, Jonathan, Wolf, Kevin, Worbes, Ludwig, Wright, Ethan, Wulfmeyer, Volker, Young, Shanea, Zhang, Chidong, Zhang, Dongxiao, Ziemen, Florian, Zinner, Tobias, Zöger, Martin, Massachusetts Institute of Technology. Department of Earth, Atmospheric, and Planetary Sciences, Stevens, Bjorn, Bony, Sandrine, Farrell, David, Ament, Felix, Blyth, Alan, Fairall, Christopher, Karstensen, Johannes, Quinn, Patricia K., Speich, Sabrina, Acquistapace, Claudia, Aemisegger, Franziska, Albright, Anna Lea, Bellenger, Hugo, Bodenschatz, Eberhard, Caesar, Kathy-Ann, Chewitt-Lucas, Rebecca, de Boer, Gijs, Delanoë, Julien, Denby, Leif, Ewald, Florian, Fildier, Benjamin, Forde, Marvin, George, Geet, Gross, Silke, Hagen, Martin, Hausold, Andrea, Heywood, Karen J., Hirsch, Lutz, Jacob, Marek, Jansen, Friedhelm, 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, Crewell, Susanne, Cronin, Timothy, Cui, Zhiqiang, Cuypers, Yannis, Daley, Alton, Damerell, Gillian M., Dauhut, Thibaut, Deneke, Hartwig, Desbios, Jean-Philippe, Dörner, Steffen, Donner, Sebastian, Douet, Vincent, Drushka, Kyla, Dütsch, Marina, Ehrlich, André, Emanuel, Kerry, Emmanouilidis, Alexandros, Etienne, Jean-Claude, Etienne-Leblanc, Sheryl, Faure, Ghislain, Feingold, Graham, Ferrero, Luca, Fix, Andreas, Flamant, Cyrille, Flatau, Piotr Jacek, Foltz, Gregory R., Forster, Linda, Furtuna, Iulian, Gadian, Alan, Galewsky, Joseph, Gallagher, Martin, Gallimore, Peter, Gaston, Cassandra, Gentemann, Chelle, Geyskens, Nicolas, Giez, Andreas, Gollop, John, Gouirand, Isabelle, Gourbeyre, Christophe, de Graaf, Dörte, de Groot, Geiske E., Grosz, Robert, Güttler, Johannes, Gutleben, Manuel, Hall, Kashawn, Harris, George, Helfer, Kevin C., Henze, Dean, Herbert, Calvert, Holanda, Bruna, Ibanez-Landeta, Antonio, Intrieri, Janet, Iyer, Suneil, Julien, Fabrice, Kalesse, Heike, Kazil, Jan, Kellman, Alexander, Kidane, Abiel T., Kirchner, Ulrike, Klingebiel, Marcus, Körner, Mareike, Kremper, Leslie Ann, Kretzschmar, Jan, Krüger, Ovid, Kumala, Wojciech, Kurz, Armin, L'Hégaret, Pierre, Labaste, Matthieu, Lachlan-Cope, Tom, Laing, Arlene, Landschützer, Peter, Lang, Theresa, Lange, Diego, Lange, Ingo, Laplace, Clément, Lavik, Gauke, Laxenaire, Rémi, Le Bihan, Caroline, Leandro, Mason, Lefevre, Nathalie, Lena, Marius, Lenschow, Donald, Li, Qiang, Lloyd, Gary, Los, Sebastian, Losi, Niccolò, Lovell, Oscar, Luneau, Christopher, Makuch, Przemyslaw, Malinowski, Szymon, Manta, Gaston, Marinou, Eleni, Marsden, Nicholas, Masson, Sebastien, Maury, Nicolas, Mayer, Bernhard, Mayers-Als, Margarette, Mazel, Christophe, McGeary, Wayne, McWilliams, James C., Mech, Mario, Mehlmann, Melina, Meroni, Agostino Niyonkuru, Mieslinger, Theresa, Minikin, Andreas, Minnett, Peter, Möller, Gregor, Morfa Avalos, Yanmichel, Muller, Caroline, Musat, Ionela, Napoli, Anna, Neuberger, Almuth, Noisel, Christophe, Noone, David, Nordsiek, Freja, Nowak, Jakub L., Oswald, Lothar, Parker, Douglas J., Peck, Carolyn, Person, Renaud, Philippi, Miriam, Plueddemann, Albert, Pöhlker, Christopher, Pörtge, Veronika, Pöschl, Ulrich, Pologne, Lawrence, Posyniak, Michał, Prange, Marc, Quiñones Meléndez, Estefanía, Radtke, Jule, Ramage, Karim, Reimann, Jens, Renault, Lionel, Reus, Klaus, Reyes, Ashford, Ribbe, Joachim, Ringel, Maximilian, Ritschel, Markus, Rocha, Cesar B., Rochetin, Nicolas, Röttenbacher, Johannes, Rollo, Callum, Royer, Haley, Sadoulet, Pauline, Saffin, Leo, Sandiford, Sanola, Sandu, Irina, Schäfer, Michael, Schemann, Vera, Schirmacher, Imke, Schlenczek, Oliver, Schmidt, Jerome, Schröder, Marcel, Schwarzenboeck, Alfons, Sealy, Andrea, Senff, Christoph J., Serikov, Ilya, Shohan, Samkeyat, Siddle, Elizabeth, Smirnov, Alexander, Späth, Florian, Spooner, Branden, Stolla, M. Katharina, Szkółka, Wojciech, de Szoeke, Simon P., Tarot, Stéphane, Tetoni, Eleni, Thompson, Elizabeth, Thomson, Jim, Tomassini, Lorenzo, Totems, Julien, Ubele, Alma Anna, Villiger, Leonie, von Arx, Jan, Wagner, Thomas, Walther, Andi, Webber, Ben, Wendisch, Manfred, Whitehall, Shanice, Wiltshire, Anton, Wing, Allison A., Wirth, Martin, Wiskandt, Jonathan, Wolf, Kevin, Worbes, Ludwig, Wright, Ethan, Wulfmeyer, Volker, Young, Shanea, Zhang, Chidong, Zhang, Dongxiao, Ziemen, Florian, Zinner, Tobias, and Zöger, Martin

Abstract

Abstract. 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.

Published
2023

13. Open Boundary Conditions for Atmospheric Large Eddy Simulations and the Implementation in DALES4.4.

Author

Liqui Lung, Franciscus, Jakob, Christian, Siebesma, A. Pier, and Jansson, Fredrik

Subjects
WEATHER, TURBULENCE
Abstract

Open boundary conditions were developed for atmospheric large eddy simulation (LES) models and implemented into the Dutch Atmospheric Large Eddy simulation model. The implementation was tested in a "Big Brother"-like setup, in which the simulation with open boundary conditions was forced by an identical control simulation with periodic boundary conditions. The results show that the open boundary implementation has minimal influence on the solution. Both the mean 5 state and the turbulent structures are close to the control simulation and disturbances at the in- and outflow boundaries are negligible. To emulate a setup in which the LES is coupled to a coarser model, the influence of coarse boundary input was tested by smoothing the output of the periodic control simulation both temporally and spatially before feeding it as input to the simulation with open boundary conditions. The results show that when the ratio between input and model resolution increases, disturbances start to form at the inflow boundary and an area exists where turbulence needs to develop. Adding synthetic 10 turbulence to the smoothed input reduces the size of this area and the magnitude of the disturbances. [ABSTRACT FROM AUTHOR]

Published
2023
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15. Turbulent Transport in the Gray Zone: A Large Eddy Model Intercomparison Study of the CONSTRAIN Cold Air Outbreak Case

Author

Roode, Stephan R. de, Frederikse, Thomas, Siebesma, A. Pier, Ackerman, Andrew S, Chylik, Jan, Field, Paul R, Fricke, Jens, Gryschka, Micha, Hill, Adrian, Honnert, Rachel, Krueger, Steve K, Lac, Christine, Lesage, Andrew T, and Tomassini, Lorenzo

Subjects
Meteorology And Climatology
Abstract

To quantify the turbulent transport at gray zone length scales between 1 and 10 km the Lagrangian evolution of the CONSTRAIN cold air outbreak (CAO) case was simulated with seven large eddy models. The case is characterized by rather large latent and sensible heat fluxes, and a rapid deepening rate of the boundary layer. In some models the entrainment velocity exceeds 4 cm/s. A significant fraction of this growth is attributed to a strong longwave radiative cooling of the inversion layer. The evolution and the timing of the breakup of the stratocumulus cloud deck differ significantly among the models. Sensitivity experiments demonstrate that a decrease in the prescribed cloud droplet number concentration, and the inclusion of ice microphysics, both act to speed up the thinning of the stratocumulus by enhancing the production of precipitation. In all models the formation of mesoscale fluctuations is clearly evident in the cloud fields but also in the horizontal wind velocity. Resolved vertical fluxes remain important for scales up to 10 km. The simulation results show that the resolved vertical velocity variance gradually diminishes with a coarsening of the horizontal mesh, but the total vertical fluxes of heat, moisture, and momentum are only weakly affected. This is a promising result as it demonstrates the potential use of a mesh size dependent turbulent length scale for convective boundary layers at gray zone model resolutions.

Published
2019
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20. Representing cloud mesoscale variability in superparameterized climate models

Author

Jansson, F.R. (Fredrik), Oord, G. (Gijs) van den, Pelupessy, F.I. (Inti), Chertova, M. (Maria), Grönqvist, J.H. (Johanna), Siebesma, A.P. (Pier), Crommelin, D.T. (Daan), Jansson, F.R. (Fredrik), Oord, G. (Gijs) van den, Pelupessy, F.I. (Inti), Chertova, M. (Maria), Grönqvist, J.H. (Johanna), Siebesma, A.P. (Pier), and Crommelin, D.T. (Daan)

Abstract

In atmospheric modeling, superparameterization (SP) has gained popularity as a technique to improve cloud and convection representations in large-scale models by coupling them locally to cloud-resolving models. We show how the different representations of cloud water in the local and the global models in SP lead to a suppression of cloud advection and ultimately to a systematic underrepresentation of the cloud amount in the large-scale model. We demonstrate this phenomenon in a regional SP experiment with the global model OpenIFS coupled to the local model Dutch Atmospheric Large Eddy Simulation, as well as in an idealized setup, where the large-scale model is replaced by a simple advection scheme. As a starting point for mitigating the problem of suppressed cloud advection, we propose a scheme where the spatial variability of the local model's total water content is enhanced in order to match the global model's cloud condensate amount. The proposed scheme enhances the cloud condensate amount in the test cases, however a large discrepancy remains, caused by rapid dissipation of the clouds added by the proposed scheme.

Published
2022
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21. DALES - Dutch Atmospheric Large Eddy Simulation

Author

Arabas, S. (Sylwester), Axelsen, S. (Simon), Attema, J. (Jisk), Beets, C., Boeing, S.J., Bruine, M. (Marco) de, Chylik, J. (Jan), Cuijpers, H. (Hans), Dussen, J. (Johan) van der, Heerwaarden, C.C. (Chiel) van, Heus, T. (Thijs), Jansson, F.R. (Fredrik), Jonker, H.J.J. (Harm), Moene, A. (Arnold), Ouwersloot, H. (Huug), Oord, G. (Gijs) van den, Roode, S.R. (Stephan) de, Neggers, R. (Roel), Pedruzo, X. (Xabier), Siebesma, A.P. (Pier), Sikma, M. (Martin), Stratum, B. (Bart) van, Vila, J. (Jordi), Zanten, M. (Margreet) van, Arabas, S. (Sylwester), Axelsen, S. (Simon), Attema, J. (Jisk), Beets, C., Boeing, S.J., Bruine, M. (Marco) de, Chylik, J. (Jan), Cuijpers, H. (Hans), Dussen, J. (Johan) van der, Heerwaarden, C.C. (Chiel) van, Heus, T. (Thijs), Jansson, F.R. (Fredrik), Jonker, H.J.J. (Harm), Moene, A. (Arnold), Ouwersloot, H. (Huug), Oord, G. (Gijs) van den, Roode, S.R. (Stephan) de, Neggers, R. (Roel), Pedruzo, X. (Xabier), Siebesma, A.P. (Pier), Sikma, M. (Martin), Stratum, B. (Bart) van, Vila, J. (Jordi), and Zanten, M. (Margreet) van

Abstract

The version of DALES used on Fugaku for the Cloud Botany dataset.

Published
2022

27. EUREC<sup>4</sup>A

Author

Stevens, Bjorn, primary, Bony, Sandrine, additional, Farrell, David, additional, Ament, Felix, additional, Blyth, Alan, additional, Fairall, Christopher, additional, Karstensen, Johannes, additional, Quinn, Patricia K., additional, Speich, Sabrina, additional, Acquistapace, Claudia, additional, Aemisegger, Franziska, additional, Albright, Anna Lea, additional, Bellenger, Hugo, additional, Bodenschatz, Eberhard, additional, Caesar, Kathy-Ann, additional, Chewitt-Lucas, Rebecca, additional, de Boer, Gijs, additional, Delanoë, Julien, additional, Denby, Leif, additional, Ewald, Florian, additional, Fildier, Benjamin, additional, Forde, Marvin, additional, George, Geet, additional, Gross, Silke, additional, Hagen, Martin, additional, Hausold, Andrea, additional, Heywood, Karen J., additional, Hirsch, Lutz, additional, Jacob, Marek, additional, Jansen, Friedhelm, additional, Kinne, Stefan, additional, Klocke, Daniel, additional, Kölling, Tobias, additional, Konow, Heike, additional, Lothon, Marie, additional, Mohr, Wiebke, additional, Naumann, Ann Kristin, additional, Nuijens, Louise, additional, Olivier, Léa, additional, Pincus, Robert, additional, Pöhlker, Mira, additional, Reverdin, Gilles, additional, Roberts, Gregory, additional, Schnitt, Sabrina, additional, Schulz, Hauke, additional, Siebesma, A. Pier, additional, Stephan, Claudia Christine, additional, Sullivan, Peter, additional, Touzé-Peiffer, Ludovic, additional, Vial, Jessica, additional, Vogel, Raphaela, additional, Zuidema, Paquita, additional, Alexander, Nicola, additional, Alves, Lyndon, additional, Arixi, Sophian, additional, Asmath, Hamish, additional, Bagheri, Gholamhossein, additional, Baier, Katharina, additional, Bailey, Adriana, additional, Baranowski, Dariusz, additional, Baron, Alexandre, additional, Barrau, Sébastien, additional, Barrett, Paul A., additional, Batier, Frédéric, additional, Behrendt, Andreas, additional, Bendinger, Arne, additional, Beucher, Florent, additional, Bigorre, Sebastien, additional, Blades, Edmund, additional, Blossey, Peter, additional, Bock, Olivier, additional, Böing, Steven, additional, Bosser, Pierre, additional, Bourras, Denis, additional, Bouruet-Aubertot, Pascale, additional, Bower, Keith, additional, Branellec, Pierre, additional, Branger, Hubert, additional, Brennek, Michal, additional, Brewer, Alan, additional, Brilouet, Pierre-Etienne, additional, Brügmann, Björn, additional, Buehler, Stefan A., additional, Burke, Elmo, additional, Burton, Ralph, additional, Calmer, Radiance, additional, Canonici, Jean-Christophe, additional, Carton, Xavier, additional, Cato Jr., Gregory, additional, Charles, Jude Andre, additional, Chazette, Patrick, additional, Chen, Yanxu, additional, Chilinski, Michal T., additional, Choularton, Thomas, additional, Chuang, Patrick, additional, Clarke, Shamal, additional, Coe, Hugh, additional, Cornet, Céline, additional, Coutris, Pierre, additional, Couvreux, Fleur, additional, Crewell, Susanne, additional, Cronin, Timothy, additional, Cui, Zhiqiang, additional, Cuypers, Yannis, additional, Daley, Alton, additional, Damerell, Gillian M., additional, Dauhut, Thibaut, additional, Deneke, Hartwig, additional, Desbios, Jean-Philippe, additional, Dörner, Steffen, additional, Donner, Sebastian, additional, Douet, Vincent, additional, Drushka, Kyla, additional, Dütsch, Marina, additional, Ehrlich, André, additional, Emanuel, Kerry, additional, Emmanouilidis, Alexandros, additional, Etienne, Jean-Claude, additional, Etienne-Leblanc, Sheryl, additional, Faure, Ghislain, additional, Feingold, Graham, additional, Ferrero, Luca, additional, Fix, Andreas, additional, Flamant, Cyrille, additional, Flatau, Piotr Jacek, additional, Foltz, Gregory R., additional, Forster, Linda, additional, Furtuna, Iulian, additional, Gadian, Alan, additional, Galewsky, Joseph, additional, Gallagher, Martin, additional, Gallimore, Peter, additional, Gaston, Cassandra, additional, Gentemann, Chelle, additional, Geyskens, Nicolas, additional, Giez, Andreas, additional, Gollop, John, additional, Gouirand, Isabelle, additional, Gourbeyre, Christophe, additional, de Graaf, Dörte, additional, de Groot, Geiske E., additional, Grosz, Robert, additional, Güttler, Johannes, additional, Gutleben, Manuel, additional, Hall, Kashawn, additional, Harris, George, additional, Helfer, Kevin C., additional, Henze, Dean, additional, Herbert, Calvert, additional, Holanda, Bruna, additional, Ibanez-Landeta, Antonio, additional, Intrieri, Janet, additional, Iyer, Suneil, additional, Julien, Fabrice, additional, Kalesse, Heike, additional, Kazil, Jan, additional, Kellman, Alexander, additional, Kidane, Abiel T., additional, Kirchner, Ulrike, additional, Klingebiel, Marcus, additional, Körner, Mareike, additional, Kremper, Leslie Ann, additional, Kretzschmar, Jan, additional, Krüger, Ovid, additional, Kumala, Wojciech, additional, Kurz, Armin, additional, L'Hégaret, Pierre, additional, Labaste, Matthieu, additional, Lachlan-Cope, Tom, additional, Laing, Arlene, additional, Landschützer, Peter, additional, Lang, Theresa, additional, Lange, Diego, additional, Lange, Ingo, additional, Laplace, Clément, additional, Lavik, Gauke, additional, Laxenaire, Rémi, additional, Le Bihan, Caroline, additional, Leandro, Mason, additional, Lefevre, Nathalie, additional, Lena, Marius, additional, Lenschow, Donald, additional, Li, Qiang, additional, Lloyd, Gary, additional, Los, Sebastian, additional, Losi, Niccolò, additional, Lovell, Oscar, additional, Luneau, Christopher, additional, Makuch, Przemyslaw, additional, Malinowski, Szymon, additional, Manta, Gaston, additional, Marinou, Eleni, additional, Marsden, Nicholas, additional, Masson, Sebastien, additional, Maury, Nicolas, additional, Mayer, Bernhard, additional, Mayers-Als, Margarette, additional, Mazel, Christophe, additional, McGeary, Wayne, additional, McWilliams, James C., additional, Mech, Mario, additional, Mehlmann, Melina, additional, Meroni, Agostino Niyonkuru, additional, Mieslinger, Theresa, additional, Minikin, Andreas, additional, Minnett, Peter, additional, Möller, Gregor, additional, Morfa Avalos, Yanmichel, additional, Muller, Caroline, additional, Musat, Ionela, additional, Napoli, Anna, additional, Neuberger, Almuth, additional, Noisel, Christophe, additional, Noone, David, additional, Nordsiek, Freja, additional, Nowak, Jakub L., additional, Oswald, Lothar, additional, Parker, Douglas J., additional, Peck, Carolyn, additional, Person, Renaud, additional, Philippi, Miriam, additional, Plueddemann, Albert, additional, Pöhlker, Christopher, additional, Pörtge, Veronika, additional, Pöschl, Ulrich, additional, Pologne, Lawrence, additional, Posyniak, Michał, additional, Prange, Marc, additional, Quiñones Meléndez, Estefanía, additional, Radtke, Jule, additional, Ramage, Karim, additional, Reimann, Jens, additional, Renault, Lionel, additional, Reus, Klaus, additional, Reyes, Ashford, additional, Ribbe, Joachim, additional, Ringel, Maximilian, additional, Ritschel, Markus, additional, Rocha, Cesar B., additional, Rochetin, Nicolas, additional, Röttenbacher, Johannes, additional, Rollo, Callum, additional, Royer, Haley, additional, Sadoulet, Pauline, additional, Saffin, Leo, additional, Sandiford, Sanola, additional, Sandu, Irina, additional, Schäfer, Michael, additional, Schemann, Vera, additional, Schirmacher, Imke, additional, Schlenczek, Oliver, additional, Schmidt, Jerome, additional, Schröder, Marcel, additional, Schwarzenboeck, Alfons, additional, Sealy, Andrea, additional, Senff, Christoph J., additional, Serikov, Ilya, additional, Shohan, Samkeyat, additional, Siddle, Elizabeth, additional, Smirnov, Alexander, additional, Späth, Florian, additional, Spooner, Branden, additional, Stolla, M. Katharina, additional, Szkółka, Wojciech, additional, de Szoeke, Simon P., additional, Tarot, Stéphane, additional, Tetoni, Eleni, additional, Thompson, Elizabeth, additional, Thomson, Jim, additional, Tomassini, Lorenzo, additional, Totems, Julien, additional, Ubele, Alma Anna, additional, Villiger, Leonie, additional, von Arx, Jan, additional, Wagner, Thomas, additional, Walther, Andi, additional, Webber, Ben, additional, Wendisch, Manfred, additional, Whitehall, Shanice, additional, Wiltshire, Anton, additional, Wing, Allison A., additional, Wirth, Martin, additional, Wiskandt, Jonathan, additional, Wolf, Kevin, additional, Worbes, Ludwig, additional, Wright, Ethan, additional, Wulfmeyer, Volker, additional, Young, Shanea, additional, Zhang, Chidong, additional, Zhang, Dongxiao, additional, Ziemen, Florian, additional, Zinner, Tobias, additional, and Zöger, Martin, additional

Published
2021
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28. EUREC4A

Author

Stevens, Bjorn, Bony, Sandrine, Farrell, David, Ament, Felix, Blyth, Alan, Fairall, Christopher, Karstensen, Johannes, Quinn, Patricia K., Speich, Sabrina, Acquistapace, Claudia, Aemisegger, Franziska, Albright, Anna Lea, Bellenger, Hugo, Bodenschatz, Eberhard, Caesar, Kathy-ann, Chewitt-lucas, Rebecca, De Boer, Gijs, Delanoe, Julien, Denby, Leif, Ewald, Florian, Fildier, Benjamin, Forde, Marvin, George, Geet, Gross, Silke, Hagen, Martin, Hausold, Andrea, Heywood, Karen J., Hirsch, Lutz, Jacob, Marek, Jansen, Friedhelm, Kinne, Stefan, Klocke, Daniel, Kolling, Tobias, Konow, Heike, Lothon, Marie, Mohr, Wiebke, Naumann, Ann Kristin, Nuijens, Louise, Olivier, Lea, Pincus, Robert, Pohlker, Mira, Reverdin, Gilles, Roberts, Gregory, Schnitt, Sabrina, Schulz, Hauke, Siebesma, A. Pier, Stephan, Claudia Christine, Sullivan, Peter, Touze-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, Sebastien, Barrett, Paul A., Batier, Frederic, Behrendt, Andreas, Bendinger, Arne, Beucher, Florent, Bigorre, Sebastien, Blades, Edmund, Blossey, Peter, Bock, Olivier, Boing, Steven, Bosser, Pierre, Bourras, Denis, Bouruet-aubertot, Pascale, Bower, Keith, Branellec, Pierre, Branger, Hubert, Brennek, Michal, Brewer, Alan, Brilouet, Pierre Etienne, Brugmann, Bjorn, Buehler, Stefan A., Burke, Elmo, Burton, Ralph, Calmer, Radiance, Canonici, Jean-christophe, Carton, Xavier, Cato, Gregory, Jr., Charles, Jude Andre, Chazette, Patrick, Chen, Yanxu, Chilinski, Michal T., Choularton, Thomas, Chuang, Patrick, Clarke, Shamal, Coe, Hugh, Cornet, Celine, Coutris, Pierre, Couvreux, Fleur, Crewell, Susanne, Cronin, Timothy, Cui, Zhiqiang, Cuypers, Yannis, Daley, Alton, Damerell, Gillian M., Dauhut, Thibaut, Deneke, Hartwig, Desbios, Jean-philippe, Dorner, Steffen, Donner, Sebastian, Douet, Vincent, Drushka, Kyla, Dutsch, Marina, Ehrlich, Andre, Emanuel, Kerry, Emmanouilidis, Alexandros, Etienne, Jean-claude, Etienne-leblanc, Sheryl, Faure, Ghislain, Feingold, Graham, Ferrero, Luca, Fix, Andreas, Flamant, Cyrille, Flatau, Piotr Jacek, Foltz, Gregory R., Forster, Linda, Furtuna, Iulian, Gadian, Alan, Galewsky, Joseph, Gallagher, Martin, Gallimore, Peter, Gaston, Cassandra, Gentemann, Chelle, Geyskens, Nicolas, Giez, Andreas, Gollop, John, Gouirand, Isabelle, Gourbeyre, Christophe, De Graaf, Dorte, De Groot, Geiske E., Grosz, Robert, Guttler, Johannes, Gutleben, Manuel, Hall, Kashawn, Harris, George, Helfer, Kevin C., Henze, Dean, Herbert, Calvert, Holanda, Bruna, Ibanez-landeta, Antonio, Intrieri, Janet, Iyer, Suneil, Julien, Fabrice, Kalesse, Heike, Kazil, Jan, Kellman, Alexander, Kidane, Abiel T., Kirchner, Ulrike, Klingebiel, Marcus, Korner, Mareike, Kremper, Leslie Ann, Kretzschmar, Jan, Kruger, Ovid, Kumala, Wojciech, Kurz, Armin, L'Hegaret, Pierre, Labaste, Matthieu, Lachlan-cope, Tom, Laing, Arlene, Landschutzer, Peter, Lang, Theresa, Lange, Diego, Lange, Ingo, Laplace, Clement, Lavik, Gauke, Laxenaire, Remi, Le Bihan, Caroline, Leandro, Mason, Lefevre, Nathalie, Lena, Marius, Lenschow, Donald, Li, Qiang, Lloyd, Gary, Los, Sebastian, Losi, Niccolo, Lovell, Oscar, Luneau, Christopher, Makuch, Przemyslaw, Malinowski, Szymon, Manta, Gaston, Marinou, Eleni, Marsden, Nicholas, Masson, Sebastien, Maury, Nicolas, Mayer, Bernhard, Mayers-als, Margarette, Mazel, Christophe, Mcgeary, Wayne, Mcwilliams, James C., Mech, Mario, Mehlmann, Melina, Meroni, Agostino Niyonkuru, Mieslinger, Theresa, Minikin, Andreas, Minnett, Peter, Moller, Gregor, Avalos, Yanmichel Morfa, Muller, Caroline, Musat, Ionela, Napoli, Anna, Neuberger, Almuth, Noisel, Christophe, Noone, David, Nordsiek, Freja, Nowak, Jakub L., Oswald, Lothar, Parker, Douglas J., Peck, Carolyn, Person, Renaud, Philippi, Miriam, Plueddemann, Albert, Pohlker, Christopher, Portge, Veronika, Poschl, Ulrich, Pologne, Lawrence, Posyniak, Michal, Prange, Marc, Melendez, Estefania Quinones, Radtke, Jule, Ramage, Karim, Reimann, Jens, Renault, Lionel, Reus, Klaus, Reyes, Ashford, Ribbe, Joachim, Ringel, Maximilian, Ritschel, Markus, Rocha, Cesar B., Rochetin, Nicolas, Rottenbacher, Johannes, Rollo, Callum, Royer, Haley, Sadoulet, Pauline, Saffin, Leo, Sandiford, Sanola, Sandu, Irina, Schafer, Michael, Schemann, Vera, Schirmacher, Imke, Schlenczek, Oliver, Schmidt, Jerome, Schroder, Marcel, Schwarzenboeck, Alfons, Sealy, Andrea, Senff, Christoph J., Serikov, Ilya, Shohan, Samkeyat, Siddle, Elizabeth, Smirnov, Alexander, Spath, Florian, Spooner, Branden, Stolla, M. Katharina, Szkolka, Wojciech, De Szoeke, Simon P., Tarot, Stephane, Tetoni, Eleni, Thompson, Elizabeth, Thomson, Jim, Tomassini, Lorenzo, Totems, Julien, Ubele, Alma Anna, Villiger, Leonie, Von Arx, Jan, Wagner, Thomas, Walther, Andi, Webber, Ben, Wendisch, Manfred, Whitehall, Shanice, Wiltshire, Anton, Wing, Allison A., Wirth, Martin, Wiskandt, Jonathan, Wolf, Kevin, Worbes, Ludwig, Wright, Ethan, Wulfmeyer, Volker, Young, Shanea, Zhang, Chidong, Zhang, Dongxiao, Ziemen, Florian, Zinner, Tobias, Zoger, Martin, Stevens, Bjorn, Bony, Sandrine, Farrell, David, Ament, Felix, Blyth, Alan, Fairall, Christopher, Karstensen, Johannes, Quinn, Patricia K., Speich, Sabrina, Acquistapace, Claudia, Aemisegger, Franziska, Albright, Anna Lea, Bellenger, Hugo, Bodenschatz, Eberhard, Caesar, Kathy-ann, Chewitt-lucas, Rebecca, De Boer, Gijs, Delanoe, Julien, Denby, Leif, Ewald, Florian, Fildier, Benjamin, Forde, Marvin, George, Geet, Gross, Silke, Hagen, Martin, Hausold, Andrea, Heywood, Karen J., Hirsch, Lutz, Jacob, Marek, Jansen, Friedhelm, Kinne, Stefan, Klocke, Daniel, Kolling, Tobias, Konow, Heike, Lothon, Marie, Mohr, Wiebke, Naumann, Ann Kristin, Nuijens, Louise, Olivier, Lea, Pincus, Robert, Pohlker, Mira, Reverdin, Gilles, Roberts, Gregory, Schnitt, Sabrina, Schulz, Hauke, Siebesma, A. Pier, Stephan, Claudia Christine, Sullivan, Peter, Touze-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, Sebastien, Barrett, Paul A., Batier, Frederic, Behrendt, Andreas, Bendinger, Arne, Beucher, Florent, Bigorre, Sebastien, Blades, Edmund, Blossey, Peter, Bock, Olivier, Boing, Steven, Bosser, Pierre, Bourras, Denis, Bouruet-aubertot, Pascale, Bower, Keith, Branellec, Pierre, Branger, Hubert, Brennek, Michal, Brewer, Alan, Brilouet, Pierre Etienne, Brugmann, Bjorn, Buehler, Stefan A., Burke, Elmo, Burton, Ralph, Calmer, Radiance, Canonici, Jean-christophe, Carton, Xavier, Cato, Gregory, Jr., Charles, Jude Andre, Chazette, Patrick, Chen, Yanxu, Chilinski, Michal T., Choularton, Thomas, Chuang, Patrick, Clarke, Shamal, Coe, Hugh, Cornet, Celine, Coutris, Pierre, Couvreux, Fleur, Crewell, Susanne, Cronin, Timothy, Cui, Zhiqiang, Cuypers, Yannis, Daley, Alton, Damerell, Gillian M., Dauhut, Thibaut, Deneke, Hartwig, Desbios, Jean-philippe, Dorner, Steffen, Donner, Sebastian, Douet, Vincent, Drushka, Kyla, Dutsch, Marina, Ehrlich, Andre, Emanuel, Kerry, Emmanouilidis, Alexandros, Etienne, Jean-claude, Etienne-leblanc, Sheryl, Faure, Ghislain, Feingold, Graham, Ferrero, Luca, Fix, Andreas, Flamant, Cyrille, Flatau, Piotr Jacek, Foltz, Gregory R., Forster, Linda, Furtuna, Iulian, Gadian, Alan, Galewsky, Joseph, Gallagher, Martin, Gallimore, Peter, Gaston, Cassandra, Gentemann, Chelle, Geyskens, Nicolas, Giez, Andreas, Gollop, John, Gouirand, Isabelle, Gourbeyre, Christophe, De Graaf, Dorte, De Groot, Geiske E., Grosz, Robert, Guttler, Johannes, Gutleben, Manuel, Hall, Kashawn, Harris, George, Helfer, Kevin C., Henze, Dean, Herbert, Calvert, Holanda, Bruna, Ibanez-landeta, Antonio, Intrieri, Janet, Iyer, Suneil, Julien, Fabrice, Kalesse, Heike, Kazil, Jan, Kellman, Alexander, Kidane, Abiel T., Kirchner, Ulrike, Klingebiel, Marcus, Korner, Mareike, Kremper, Leslie Ann, Kretzschmar, Jan, Kruger, Ovid, Kumala, Wojciech, Kurz, Armin, L'Hegaret, Pierre, Labaste, Matthieu, Lachlan-cope, Tom, Laing, Arlene, Landschutzer, Peter, Lang, Theresa, Lange, Diego, Lange, Ingo, Laplace, Clement, Lavik, Gauke, Laxenaire, Remi, Le Bihan, Caroline, Leandro, Mason, Lefevre, Nathalie, Lena, Marius, Lenschow, Donald, Li, Qiang, Lloyd, Gary, Los, Sebastian, Losi, Niccolo, Lovell, Oscar, Luneau, Christopher, Makuch, Przemyslaw, Malinowski, Szymon, Manta, Gaston, Marinou, Eleni, Marsden, Nicholas, Masson, Sebastien, Maury, Nicolas, Mayer, Bernhard, Mayers-als, Margarette, Mazel, Christophe, Mcgeary, Wayne, Mcwilliams, James C., Mech, Mario, Mehlmann, Melina, Meroni, Agostino Niyonkuru, Mieslinger, Theresa, Minikin, Andreas, Minnett, Peter, Moller, Gregor, Avalos, Yanmichel Morfa, Muller, Caroline, Musat, Ionela, Napoli, Anna, Neuberger, Almuth, Noisel, Christophe, Noone, David, Nordsiek, Freja, Nowak, Jakub L., Oswald, Lothar, Parker, Douglas J., Peck, Carolyn, Person, Renaud, Philippi, Miriam, Plueddemann, Albert, Pohlker, Christopher, Portge, Veronika, Poschl, Ulrich, Pologne, Lawrence, Posyniak, Michal, Prange, Marc, Melendez, Estefania Quinones, Radtke, Jule, Ramage, Karim, Reimann, Jens, Renault, Lionel, Reus, Klaus, Reyes, Ashford, Ribbe, Joachim, Ringel, Maximilian, Ritschel, Markus, Rocha, Cesar B., Rochetin, Nicolas, Rottenbacher, Johannes, Rollo, Callum, Royer, Haley, Sadoulet, Pauline, Saffin, Leo, Sandiford, Sanola, Sandu, Irina, Schafer, Michael, Schemann, Vera, Schirmacher, Imke, Schlenczek, Oliver, Schmidt, Jerome, Schroder, Marcel, Schwarzenboeck, Alfons, Sealy, Andrea, Senff, Christoph J., Serikov, Ilya, Shohan, Samkeyat, Siddle, Elizabeth, Smirnov, Alexander, Spath, Florian, Spooner, Branden, Stolla, M. Katharina, Szkolka, Wojciech, De Szoeke, Simon P., Tarot, Stephane, Tetoni, Eleni, Thompson, Elizabeth, Thomson, Jim, Tomassini, Lorenzo, Totems, Julien, Ubele, Alma Anna, Villiger, Leonie, Von Arx, Jan, Wagner, Thomas, Walther, Andi, Webber, Ben, Wendisch, Manfred, Whitehall, Shanice, Wiltshire, Anton, Wing, Allison A., Wirth, Martin, Wiskandt, Jonathan, Wolf, Kevin, Worbes, Ludwig, Wright, Ethan, Wulfmeyer, Volker, Young, Shanea, Zhang, Chidong, Zhang, Dongxiao, Ziemen, Florian, Zinner, Tobias, and Zoger, Martin

Abstract

The science guiding the \EURECA campaign and its measurements are presented. \EURECA comprised roughly five weeks of measurements in the downstream winter trades of the North Atlantic — eastward and south-eastward of Barbados. Through its ability to characterize processes operating across a wide range of scales, \EURECA 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, 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 four hundred hours of flight time by four heavily instrumented research aircraft, four global-ocean class research vessels, an advanced ground-based cloud observatory, a flotilla of autonomous or tethered measurement devices operating in the upper ocean (nearly 10000 profiles), lower atmosphere (continuous profiling), and along the air-sea interface, a network of water stable isotopologue measurements, complemented by special programmes of satellite remote sensing and modeling with a new generation of weather/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 \EURECA explored — from Brazil Ring Current Eddies to turbulence induced clustering of cloud droplets and its influence on warm-rain formation — are presented along with an overview \EURECA’s outreach activities, environmental impact, and guidelines for scientific practice.

Published
2021
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29. Performance optimization and load-balancing modeling for superparametrization by 3D LES

Author

Oord, G. (Gijs) van den, Chertova, M. (Maria), Jansson, F.R. (Fredrik), Pelupessy, F.I. (Inti), Siebesma, A.P. (Pier), Crommelin, D.T. (Daan), Oord, G. (Gijs) van den, Chertova, M. (Maria), Jansson, F.R. (Fredrik), Pelupessy, F.I. (Inti), Siebesma, A.P. (Pier), and Crommelin, D.T. (Daan)

Abstract

In order to eliminate climate uncertainty w.r.t. cloud and convection parametrizations, superpramaterization (SP) [1] has emerged as one of the possible ways forward. We have implemented (regional) superparametrization of the ECMWF weather model OpenIFS [2] by cloud-resolving, three-dimensional large-eddy simulations. This setup, described in [3], contains a two-way coupling between a global meteorological model that resolves large-scale dynamics, with many local instances of the Dutch Atmospheric Large Eddy Simulation (DALES) [4], resolving cloud and boundary layer physics. The model is currently prohibitively expensive to run over climate or even seasonal time scales, and a global SP requires the allocation of millions of cores. In this paper, we study the performance and scaling behavior of the LES models and the coupling code and present our implemented optimizations. We mimic the observed load imbalance with a simple performance model and present strategies to improve hardware utilization in order to assess the feasibility of a world-covering superparametrization. We conclude that (quasi-)dynamical load-balancing can significantly reduce the runtime for such large-scale systems with wide variability in LES time-stepping speeds.

Published
2021
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30. The environment of precipitating shallow cumulus convection

Author

Nuijens, Louise, Stevens, Bjorn, and Siebesma, A. Pier

Subjects
Atmospheric physics -- Research, Cumulus convection -- Environmental aspects, Precipitation variability -- Observations, Earth sciences, Science and technology
Abstract

Quantitative estimates of precipitation in a typical undisturbed trade wind region are derived from 2 months of radar reflectivity data and compared to the meteorological environment determined from soundings, surface flux, and airborne-lidar data. Shallow precipitation was ubiquitous, covering on average about 2% of the region and contributing to at least half of the total precipitation. Echo fractions on the scale of the radar domain range between 0% and 10% and vary greatly within a period from a few hours to a day. Variability in precipitation relates most strongly to variability in humidity and the zonal wind speed, although greater inversion heights and deeper clouds are also evident at times of more rain. The analysis herein suggests that subtle fluctuations in both the strength of the easterlies and in subsidence play a major role in regulating humidity and hence precipitation, even within a given meteorological regime (here, the undisturbed trades).

Published
2009

31. Variability of local structure parameters in the convective boundary layer

Author

Cheinet, Sylvain and Siebesma, A. Pier

Subjects
Atmospheric physics -- Research, Heat -- Convection, Heat -- Environmental aspects, Earth sciences, Science and technology
Abstract

The propagation of optical and acoustical waves is affected by the atmospheric turbulence through the local instantaneous refractive index structure parameter in a volume of characteristic size r, denoted [C.sub.n,r.sup.2]. Often r is well within the inertial--convective range. In this study, a large-eddy simulation (LES) of spatial resolution [DELTA] is used to analyze the distribution of [C.sub.n,[DELTA].sup.2] in the convective boundary layer. The local formulation used to calculate [C.sub.n,[DELTA].sup.2] is described and is found to back up the subgrid parameterization of atmospheric LES. The mean vertical profile behaves according to the mixed layer similarity theory. The spatial organization relates to the presence of buoyant ascending plumes. This structure is associated with some bimodal probability density functions of the inertial-convective range variables, in agreement with experimental results. The standard model of jointly lognormal statistics is challenged. The intermittency of these variables is characterized, and its inertial-convective range component quantitatively agrees with experimental estimates. The present LES results are used to document the bias produced by averaging the dissipation rates of TKE and temperature variance to estimate the average structure parameters. Comparing with nonconvective turbulence measurements, the bias for [C.sub.T,r.sup.2] is found to depend on the stability. A physical explanation is offered that emphasizes the role of the large-scale turbulence under convective conditions.

Published
2009

32. A combined eddy-diffusivity mass-flux approach for the convective boundary layer

Author

Siebesma, A. Pier, Soares, Pedro M.M., and Teixeira, Joao

Subjects
Convection (Meteorology) -- Analysis, Eddies -- Analysis, Weather forecasting -- Models, Earth sciences, Science and technology
Abstract

A better conceptual understanding and more realistic parameterizations of convective boundary layers in climate and weather prediction models have been major challenges in meteorological research. In particular, parameterizations of the dry convective boundary layer, in spite of the absence of water phase-changes and its consequent simplicity as compared to moist convection, typically suffer from problems in attempting to represent realistically the boundary layer growth and what is often referred to as countergradient fluxes. The eddy-diffusivity (ED) approach has been relatively successful in representing some characteristics of neutral boundary layers and surface layers in general. The mass-flux (MF) approach, on the other hand, has been used for the parameterization of shallow and deep moist convection. In this paper, a new approach that relies on a combination of the ED and MF parameterizations (EDMF) is proposed for the dry convective boundary layer. It is shown that the EDMF approach follows naturally from a decomposition of the turbulent fluxes into 1) a part that includes strong organized updrafts, and 2) a remaining turbulent field. At the basis of the EDMF approach is the concept that nonlocal subgrid transport due to the strong updrafts is taken into account by the MF approach, while the remaining transport is taken into account by an ED closure. Large-eddy simulation (LES) results of the dry convective boundary layer are used to support the theoretical framework of this new approach and to determine the parameters of the EDMF model. The performance of the new formulation is evaluated against LES results, and it is shown that the EDMF closure is able to reproduce the main properties of dry convective boundary layers in a realistic manner. Furthermore, it will be shown that this approach has strong advantages over the more traditional countergradient approach, especially in the entrainment layer. As a result, this EDMF approach opens the way to parameterize the clear and cumulus-topped boundary layer in a simple and unified way.

Published
2007

33. A Python interface to the Dutch Atmospheric Large-Eddy Simulation

Author

Oord, G. (Gijs) van den, Jansson, F.R. (Fredrik), Pelupessy, F.I. (Inti), Chertova, M. (Maria), Grönqvist, J.H. (Johanna), Siebesma, A.P. (Pier), Crommelin, D.T. (Daan), Oord, G. (Gijs) van den, Jansson, F.R. (Fredrik), Pelupessy, F.I. (Inti), Chertova, M. (Maria), Grönqvist, J.H. (Johanna), Siebesma, A.P. (Pier), and Crommelin, D.T. (Daan)

Abstract

We present a Python interface for the Dutch Atmospheric Large Eddy Simulation (DALES), an existing Fortran code for high-resolution, turbulence-resolving simulation of atmospheric physics. The interface is based on an infrastructure for remote and parallel function calls and makes it possible to use and control the DALES weather simulations from a Python context. The interface is designed within the OMUSE framework, and allows the user to set up and control the simulation, apply perturbations and forcings, collect and analyse data in real time without exposing the user to the details of setting up and running the parallel Fortran DALES code. Another significant possibility is coupling the DALES simulation to other models, for example larger scale numerical weather prediction (NWP) models that can supply realistic lateral boundary conditions. Finally, the Python interface to DALES can serve as an educational tool for exploring weather dynamics, which we demonstrate with an example Jupyter notebook.

Published
2020
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36. A large eddy simulation intercomparison study of shallow cumulus convection

Author

Siebesma, A. Pier, Bretherton, Christopher S., Brown, Andrew, Chlond, Andreas, Cuxart, Joan, Duynkerke, Peter G., Jiang, Hongli, Khairoutdinov, Marat, Lewellen, David, Moeng, Chin-Hoh, Sanchez, Enrique, Stevens, Bjorn, and Stevens, David E.

Subjects
Cumulus convection -- Observations, Convection (Meteorology) -- Models, Earth sciences, Science and technology
Abstract

This paper reports an intercomparison study on undisturbed trade wind cumulus convection under steady-state conditions as observed during the Barbados Oceanographic and Meteorological Experiment (BOMEX) with 10 large eddy simulation (LES) models. A main objective of this study is to obtain a quantitative assessment of the quality of the turbulent dynamics for this type of boundary layer clouds as produced by the different LES codes. A 6-h simulation shows excellent model-to-model agreement of the observed vertical thermodynamical structure, reasonable agreement of variances and turbulent fluxes, and good agreement of quantities conditionally sampled within the model clouds, such as cloud cover, liquid water, and cloud updraft strength. In the second part of this paper the LES dataset is used to evaluate simple models that are used in parameterizations of current general circulation models (GCMs). Finally, the relation of this work to subsequent LES studies of more complicated regimes is discussed, and guidance is given for the design of future observational studies of shallow cumulus boundary layers.

Published
2003

37. Cloud-controlling Factors

Author

Siebesma, A. Pier, primary, Brenguier, Jean-Louis, additional, Bretherton, Christopher S., additional, Grabowski, Wojciech W., additional, Heintzenberg, Jost, additional, Kärcher, Bernd, additional, Lehmann, Katrin, additional, Petch, Jon C., additional, Spichtinger, Peter, additional, Stevens, Bjorn, additional, and Stratmann, Frank, additional

Published
2009
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40. DARCLOS: a cloud shadow detection algorithm for TROPOMI.

Author

Trees, Victor, Wang, Ping, Stammes, Piet, Tilstra, Lieuwe G., Donovan, David P., and Siebesma, A. Pier

Subjects
SPECTRAL reflectance, SPACE-based radar, TRACE gases, AIR quality, SPATIAL resolution, ALGORITHMS
Abstract

Cloud shadows are observed by the TROPOMI satellite instrument as a result of its high spatial resolution as compared to its predecessor instruments. These shadows contaminate TROPOMI's air quality measurements, because shadows are generally not taken into account in the models that are used for aerosol and trace gas retrievals. If the shadows are to be removed from the data, or if shadows are to be studied, an automatic detection of the shadow pixels is needed. We present the Detection AlgoRithm for CLOud Shadows (DARCLOS) for TROPOMI, which is the first cloud shadow detection algorithm for a spaceborne spectrometer. DARCLOS raises potential cloud shadow flags (PCSFs), and actual cloud shadow flags (ACSFs). The PCSFs indicate the TROPOMI ground pixels that are potentially affected by cloud shadows based on a geometric consideration with safety margins. The ACSFs are a refinement of the PCSFs using spectral reflectance information of the PCSF pixels, and identify the TROPOMI ground pixels that are confidently affected by cloud shadows. We validate DARCLOS with true color images made by the VIIRS instrument on board of Suomi NPP orbiting in close constellation with TROPOMI on board of Sentinel 5-P. We conclude that the PCSF can be used to exclude cloud shadow contamination from TROPOMI data, while the ACSF can be used to select pixels for the scientific analysis of cloud shadow effects. [ABSTRACT FROM AUTHOR]

Published
2021
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41. On the regional superparametrization of OpenIFS by 3D LES models

Author

Jansson, F.R. (Fredrik), Oord, G. (Gijs) van den, Pelupessy, F.I. (Inti), Chertova, M. (Maria), Siebesma, A.P. (Pier), Crommelin, D.T. (Daan), Jansson, F.R. (Fredrik), Oord, G. (Gijs) van den, Pelupessy, F.I. (Inti), Chertova, M. (Maria), Siebesma, A.P. (Pier), and Crommelin, D.T. (Daan)

Published
2019

42. Creating a reusable cross-disciplinary multi-scale and multi-physics framework: From AMUSE to OMUSE and beyond

Author

Pelupessy, F.I. (Inti), Portegies Zwart, S. (Simon), Van Elteren, A. (Arjen), Dijkstra, H.A., Jansson, F.R. (Fredrik), Crommelin, D.T. (Daan), Siebesma, A.P. (Pier), Werkhoven, B.J.C. (Ben) van, Oord, G. (Gijs) van den, Pelupessy, F.I. (Inti), Portegies Zwart, S. (Simon), Van Elteren, A. (Arjen), Dijkstra, H.A., Jansson, F.R. (Fredrik), Crommelin, D.T. (Daan), Siebesma, A.P. (Pier), Werkhoven, B.J.C. (Ben) van, and Oord, G. (Gijs) van den

Abstract

Here, we describe our efforts to create a multi-scale and multi-physics framework that can be retargeted across different disciplines. Currently we have implemented our approach in the astrophysical domain, for which we developed AMUSE (github.com/amusecode/amuse ), and generalized this to the oceanographic and climate sciences, which led to the development of OMUSE (bitbucket.org/omuse ). The objective of this paper is to document the design choices that led to the successful implementation of these frameworks as well as the future challenges in applying this approach to other domains.

Published
2019
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43. Regional superparameterization in a global circulation model using Large Eddy Simulations

Author

Jansson, F.R. (Fredrik), Oord, G. (Gijs) van den, Pelupessy, F.I. (Inti), Grönqvist, J.H. (Johanna), Siebesma, A.P. (Pier), Crommelin, D.T. (Daan), Jansson, F.R. (Fredrik), Oord, G. (Gijs) van den, Pelupessy, F.I. (Inti), Grönqvist, J.H. (Johanna), Siebesma, A.P. (Pier), and Crommelin, D.T. (Daan)

Abstract

As a computationally attractive alternative for global large eddy simulations (LESs), we investigate the possibility of using comprehensive three‐dimensional LESs as a superparameterization that can replace all traditional parameterizations of atmospheric processes that are currently used in global models. We present the technical design for a replacement of the parameterization for clouds, convection, and turbulence of the global atmospheric model of the European Centre for Medium‐Range Weather Forecasts by the Dutch Atmospheric Large Eddy Simulation model. The model coupling consists of bidirectional data exchange between the global model and the high‐resolution LES models embedded within the columns of the global model. Our setup allows for selective superparameterization, that is, for applying superparameterization in local regions selected by the user, while keeping the standard parameterization of the global model intact outside this region. Computationally, this setup can result in major geographic load imbalance, because of the large difference in computational load between superparameterized and nonsuperparameterized model columns. To resolve this issue, we use a modular design where the local and global models are kept as distinct model codes and organize the model coupling such that all the local models run in parallel, separate from the global model. First simulation results, employing this design, demonstrate the potential of our approach.

Published
2019
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44. Turbulent Transport in the Gray Zone: A Large Eddy Model Intercomparison Study of the CONSTRAIN Cold Air Outbreak Case

Author

Roode, Stephan R., Frederikse, Thomas, Siebesma, A. Pier, Ackerman, Andrew S., Chylik, Jan, Field, Paul R., Fricke, Jens, Gryschka, Micha, Hill, Adrian, Honnert, Rachel, Krueger, Steve K., Lac, Christine, Lesage, Andrew T., Tomassini, Lorenzo, Roode, Stephan R., Frederikse, Thomas, Siebesma, A. Pier, Ackerman, Andrew S., Chylik, Jan, Field, Paul R., Fricke, Jens, Gryschka, Micha, Hill, Adrian, Honnert, Rachel, Krueger, Steve K., Lac, Christine, Lesage, Andrew T., and Tomassini, Lorenzo

Published
2019

45. Turbulent transport in the Gray Zone: A large-eddy model intercomparison study of the CONSTRAIN cold air outbreak case.

Author

de Roode, Stephan R., Frederikse, Thomas, Siebesma, A. Pier, Ackerman, Andrew S., Chylik, Jan, Field, Paul R., Fricke, Jens, Gryschka, Micha, Hill, Adrian, Honnert, Rachel, Krueger, Steven K., Lac, Christine, Lesage, Andrew T., Tomassini, Lorenzo, de Roode, Stephan R., Frederikse, Thomas, Siebesma, A. Pier, Ackerman, Andrew S., Chylik, Jan, Field, Paul R., Fricke, Jens, Gryschka, Micha, Hill, Adrian, Honnert, Rachel, Krueger, Steven K., Lac, Christine, Lesage, Andrew T., and Tomassini, Lorenzo

Abstract

To quantify the turbulent transport at gray zone length scales between 1 and 10 km, the Lagrangian evolution of the CONSTRAIN cold air outbreak case was simulated with seven large eddy models. The case is characterized by rather large latent and sensible heat fluxes and a rapid deepening rate of the boundary layer. In some models the entrainment velocity exceeds 4 cm/s. A significant fraction of this growth is attributed to a strong longwave radiative cooling of the inversion layer. The evolution and the timing of the breakup of the stratocumulus cloud deck differ significantly among the models. Sensitivity experiments demonstrate that a decrease in the prescribed cloud droplet number concentration and the inclusion of ice microphysics both act to speed up the thinning of the stratocumulus by enhancing the production of precipitation. In all models the formation of mesoscale fluctuations is clearly evident in the cloud fields and also in the horizontal wind velocity. Resolved vertical fluxes remain important for scales up to 10 km. The simulation results show that the resolved vertical velocity variance gradually diminishes with a coarsening of the horizontal mesh, but the total vertical fluxes of heat, moisture, and momentum are only weakly affected. This is a promising result as it demonstrates the potential use of a mesh size‐dependent turbulent length scale for convective boundary layers at gray zone model resolutions.

Published
2019

49. CGILS: Results from the first phase of an international project to understand the physical mechanisms of low cloud feedbacks in single column models

Author

Zhang, Minghua, Blossey, Peter N., Khairoutdinov, Marat F., Austin, Phillip H., Bacmeister, Julio T., Bony, Sandrine, Brient, Florent, Cheedela, Suvarchal K., Del Genio, Anthony D., De Roode, Stephan R., Endo, Satoshi, Golaz, Jean-Christophe, Stevens, Bjorn, Isotta, Francesco Alessandro, Franklin, Charmaine N., Cheng, Anning, Kang, In-Sik, Kawai, Hideaki, Liu, Yangang, Xu, Kuan-Man, Koehler, Martin, Lock, Adrian P., Molod, Andrea M., Hannay, Cecile, Zhao, Ming, Lohmann, Ulrike, Neggers, Roel A. J., Rasch, Philip, Sandu, Irina, Siegenthaler-Le Drian, Colombe, Senkbeil, Ryan, Heus, Thijs, Bretherton, Christopher S., Suarez, Max J., Wolf, Audrey, Siebesma, A. Pier, von Salzen, Knut, Webb, Mark J., Larson, Vincent E., Dufresne, Jean-Louis, Institute for Terrestrial and Planetary Atmospheres [Stony Brook] (ITPA), School of Marine and Atmospheric Sciences [Stony Brook] (SoMAS), Stony Brook University [SUNY] (SBU), State University of New York (SUNY)-State University of New York (SUNY)-Stony Brook University [SUNY] (SBU), State University of New York (SUNY)-State University of New York (SUNY), Univ Washington, Dept Atmospher Sci, Seattle, WA 98195 USA, Univ British Columbia, Dept Earth & Ocean Sci, Vancouver, BC V5Z 1M9, Canada, NOAA Earth System Research Laboratory (ESRL), National Oceanic and Atmospheric Administration (NOAA), Laboratoire de Météorologie Dynamique (UMR 8539) (LMD), Département des Géosciences - ENS Paris, École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-École des Ponts ParisTech (ENPC)-École polytechnique (X)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC), Max-Planck-Institut für Meteorologie (MPI-M), Max-Planck-Gesellschaft, NASA Goddard Institute for Space Studies (GISS), NASA Goddard Space Flight Center (GSFC), Department of Geoscience and Remote Sensing [Delft], Delft University of Technology (TU Delft), Brookhaven Natl Lab, Dept Environm Sci, Upton, NY 11973 USA, NOAA Geophysical Fluid Dynamics Laboratory (GFDL), Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich] (ETH Zürich), CSIRO, Ctr Australian Weather & Climate Res, Aspendale, Vic, Australia, NASA Langley Research Center [Hampton] (LaRC), Seoul Natl Univ, Sch Earth & Environm Sci, Seoul, South Korea, Meteorol Res Inst, Tsukuba, Ibaraki 305, Japan, European Centre for Medium-Range Weather Forecasts (ECMWF), Met Off Hadley Ctr, Exeter, Devon, England, Global Modeling and Assimilation Office (GMAO), Royal Netherlands Meteorological Institute (KNMI), Pacific NW Natl Lab, Richland, WA 99352 USA, Univ Wisconsin, Dept Math Sci, Milwaukee, WI 53201 USA, Canadian Ctr Climate Modelling & Anal, Victoria, BC, Canada, Department of Atmospheric Sciences [Seattle], University of Washington [Seattle], Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-École des Ponts ParisTech (ENPC)-Centre National de la Recherche Scientifique (CNRS)-Département des Géosciences - ENS Paris, École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL), and Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)

Subjects
[SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, large eddy models, low cloud feedbacks, single column models, CGILS
Abstract

International audience; CGILS-the CFMIP-GASS Intercomparison of Large Eddy Models (LESs) and single column models (SCMs)-investigates the mechanisms of cloud feedback in SCMs and LESs under idealized climate change perturbation. This paper describes the CGILS results from 15 SCMs and 8 LES models. Three cloud regimes over the subtropical oceans are studied: shallow cumulus, cumulus under stratocumulus, and well-mixed coastal stratus/stratocumulus. In the stratocumulus and coastal stratus regimes, SCMs without activated shallow convection generally simulated negative cloud feedbacks, while models with active shallow convection generally simulated positive cloud feedbacks. In the shallow cumulus alone regime, this relationship is less clear, likely due to the changes in cloud depth, lateral mixing, and precipitation or a combination of them. The majority of LES models simulated negative cloud feedback in the well-mixed coastal stratus/stratocumulus regime, and positive feedback in the shallow cumulus and stratocumulus regime. A general framework is provided to interpret SCM results: in a warmer climate, the moistening rate of the cloudy layer associated with the surface-based turbulence parameterization is enhanced; together with weaker large-scale subsidence, it causes negative cloud feedback. In contrast, in the warmer climate, the drying rate associated with the shallow convection scheme is enhanced. This causes positive cloud feedback. These mechanisms are summarized as the "NESTS" negative cloud feedback and the "SCOPE" positive cloud feedback (Negative feedback from Surface Turbulence under weaker Subsidence-Shallow Convection PositivE feedback) with the net cloud feedback depending on how the two opposing effects counteract each other. The LES results are consistent with these interpretations.

Published
2013
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