Articles | Volume 20, issue 17
https://doi.org/10.5194/acp-20-10211-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-20-10211-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
03 Sep 2020
Research article |
| 03 Sep 2020
| 03 Sep 2020
Size dependence in chord characteristics from simulated and observed continental shallow cumulus
Philipp J. Griewank
CORRESPONDING AUTHOR
University of Cologne, Cologne, Germany
Thijs Heus
Cleveland State University, Cleveland, Ohio, USA
Neil P. Lareau
University of Nevada, Reno, Nevada, USA
Roel A. J. Neggers
University of Cologne, Cologne, Germany
Related authors
Tobias Necker, David Hinger, Philipp Johannes Griewank, Takemasa Miyoshi, and Martin Weissmann
Nonlin. Processes Geophys., 30, 13–29, https://doi.org/10.5194/npg-30-13-2023, https://doi.org/10.5194/npg-30-13-2023, 2023
Short summary
Short summary
This study investigates vertical localization based on a convection-permitting 1000-member ensemble simulation. We derive an empirical optimal localization (EOL) that minimizes sampling error in 40-member sub-sample correlations assuming 1000-member correlations as truth. The results will provide guidance for localization in convective-scale ensemble data assimilation systems.
Tessa E. Rosenberger, David D. Turner, Thijs Heus, Girish N. Raghunathan, Timothy J. Wagner, and Julia Simonson
Atmos. Meas. Tech., 17, 6595–6602, https://doi.org/10.5194/amt-17-6595-2024, https://doi.org/10.5194/amt-17-6595-2024, 2024
Short summary
Short summary
This work used model output to show that considering the changes in boundary layer depth over time in the calculations of variables such as fluxes and variance yields more accurate results than cases where calculations were done at a constant height. This work was done to improve future observations of these variables at the top of the boundary layer.
Tessa E. Rosenberger, Thijs Heus, Girish N. Raghunathan, David D. Turner, Timothy J. Wagner, and Julia M. Simonson
EGUsphere, https://doi.org/10.5194/egusphere-2024-2894, https://doi.org/10.5194/egusphere-2024-2894, 2024
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
Short summary
Short summary
Entrainment is key in understanding temperature and moisture changes within the boundary layer, but it is difficult to observe using ground-based observations. This work used simulations to verify an assumption that simplifies entrainment estimations from ground-based observational data, recognizing that entrainment is the combination of the transfer of heat and moisture from above the boundary layer into it and the change in concentration of heat and moisture as boundary layer depth changes.
Manfred Wendisch, Susanne Crewell, André Ehrlich, Andreas Herber, Benjamin Kirbus, Christof Lüpkes, Mario Mech, Steven J. Abel, Elisa F. Akansu, Felix Ament, Clémantyne Aubry, Sebastian Becker, Stephan Borrmann, Heiko Bozem, Marlen Brückner, Hans-Christian Clemen, Sandro Dahlke, Georgios Dekoutsidis, Julien Delanoë, Elena De La Torre Castro, Henning Dorff, Regis Dupuy, Oliver Eppers, Florian Ewald, Geet George, Irina V. Gorodetskaya, Sarah Grawe, Silke Groß, Jörg Hartmann, Silvia Henning, Lutz Hirsch, Evelyn Jäkel, Philipp Joppe, Olivier Jourdan, Zsofia Jurányi, Michail Karalis, Mona Kellermann, Marcus Klingebiel, Michael Lonardi, Johannes Lucke, Anna E. Luebke, Maximilian Maahn, Nina Maherndl, Marion Maturilli, Bernhard Mayer, Johanna Mayer, Stephan Mertes, Janosch Michaelis, Michel Michalkov, Guillaume Mioche, Manuel Moser, Hanno Müller, Roel Neggers, Davide Ori, Daria Paul, Fiona M. Paulus, Christian Pilz, Felix Pithan, Mira Pöhlker, Veronika Pörtge, Maximilian Ringel, Nils Risse, Gregory C. Roberts, Sophie Rosenburg, Johannes Röttenbacher, Janna Rückert, Michael Schäfer, Jonas Schaefer, Vera Schemann, Imke Schirmacher, Jörg Schmidt, Sebastian Schmidt, Johannes Schneider, Sabrina Schnitt, Anja Schwarz, Holger Siebert, Harald Sodemann, Tim Sperzel, Gunnar Spreen, Bjorn Stevens, Frank Stratmann, Gunilla Svensson, Christian Tatzelt, Thomas Tuch, Timo Vihma, Christiane Voigt, Lea Volkmer, Andreas Walbröl, Anna Weber, Birgit Wehner, Bruno Wetzel, Martin Wirth, and Tobias Zinner
Atmos. Chem. Phys., 24, 8865–8892, https://doi.org/10.5194/acp-24-8865-2024, https://doi.org/10.5194/acp-24-8865-2024, 2024
Short summary
Short summary
The Arctic is warming faster than the rest of the globe. Warm-air intrusions (WAIs) into the Arctic may play an important role in explaining this phenomenon. Cold-air outbreaks (CAOs) out of the Arctic may link the Arctic climate changes to mid-latitude weather. In our article, we describe how to observe air mass transformations during CAOs and WAIs using three research aircraft instrumented with state-of-the-art remote-sensing and in situ measurement devices.
Andreas Walbröl, Janosch Michaelis, Sebastian Becker, Henning Dorff, Kerstin Ebell, Irina Gorodetskaya, Bernd Heinold, Benjamin Kirbus, Melanie Lauer, Nina Maherndl, Marion Maturilli, Johanna Mayer, Hanno Müller, Roel A. J. Neggers, Fiona M. Paulus, Johannes Röttenbacher, Janna E. Rückert, Imke Schirmacher, Nils Slättberg, André Ehrlich, Manfred Wendisch, and Susanne Crewell
Atmos. Chem. Phys., 24, 8007–8029, https://doi.org/10.5194/acp-24-8007-2024, https://doi.org/10.5194/acp-24-8007-2024, 2024
Short summary
Short summary
To support the interpretation of the data collected during the HALO-(AC)3 campaign, which took place in the North Atlantic sector of the Arctic from 7 March to 12 April 2022, we analyze how unusual the weather and sea ice conditions were with respect to the long-term climatology. From observations and ERA5 reanalysis, we found record-breaking warm air intrusions and a large variety of marine cold air outbreaks. Sea ice concentration was mostly within the climatological interquartile range.
Timothy W. Juliano, Fernando Szasdi-Bardales, Neil P. Lareau, Kasra Shamsaei, Branko Kosović, Negar Elhami-Khorasani, Eric P. James, and Hamed Ebrahimian
Nat. Hazards Earth Syst. Sci., 24, 47–52, https://doi.org/10.5194/nhess-24-47-2024, https://doi.org/10.5194/nhess-24-47-2024, 2024
Short summary
Short summary
Following the destructive Lahaina Fire in Hawaii, our team has modeled the wind and fire spread processes to understand the drivers of this devastating event. The simulation results show that extreme winds with high variability, a fire ignition close to the community, and construction characteristics led to continued fire spread in multiple directions. Our results suggest that available modeling capabilities can provide vital information to guide decision-making during wildfire events.
Olivia Linke, Johannes Quaas, Finja Baumer, Sebastian Becker, Jan Chylik, Sandro Dahlke, André Ehrlich, Dörthe Handorf, Christoph Jacobi, Heike Kalesse-Los, Luca Lelli, Sina Mehrdad, Roel A. J. Neggers, Johannes Riebold, Pablo Saavedra Garfias, Niklas Schnierstein, Matthew D. Shupe, Chris Smith, Gunnar Spreen, Baptiste Verneuil, Kameswara S. Vinjamuri, Marco Vountas, and Manfred Wendisch
Atmos. Chem. Phys., 23, 9963–9992, https://doi.org/10.5194/acp-23-9963-2023, https://doi.org/10.5194/acp-23-9963-2023, 2023
Short summary
Short summary
Lapse rate feedback (LRF) is a major driver of the Arctic amplification (AA) of climate change. It arises because the warming is stronger at the surface than aloft. Several processes can affect the LRF in the Arctic, such as the omnipresent temperature inversion. Here, we compare multimodel climate simulations to Arctic-based observations from a large research consortium to broaden our understanding of these processes, find synergy among them, and constrain the Arctic LRF and AA.
Jan Chylik, Dmitry Chechin, Regis Dupuy, Birte S. Kulla, Christof Lüpkes, Stephan Mertes, Mario Mech, and Roel A. J. Neggers
Atmos. Chem. Phys., 23, 4903–4929, https://doi.org/10.5194/acp-23-4903-2023, https://doi.org/10.5194/acp-23-4903-2023, 2023
Short summary
Short summary
Arctic low-level clouds play an important role in the ongoing warming of the Arctic. Unfortunately, these clouds are not properly represented in weather forecast and climate models. This study tries to cover this gap by focusing on clouds over open water during the spring, observed by research aircraft near Svalbard. The study combines the high-resolution model with sets of observational data. The results show the importance of processes that involve both ice and the liquid water in the clouds.
Tobias Necker, David Hinger, Philipp Johannes Griewank, Takemasa Miyoshi, and Martin Weissmann
Nonlin. Processes Geophys., 30, 13–29, https://doi.org/10.5194/npg-30-13-2023, https://doi.org/10.5194/npg-30-13-2023, 2023
Short summary
Short summary
This study investigates vertical localization based on a convection-permitting 1000-member ensemble simulation. We derive an empirical optimal localization (EOL) that minimizes sampling error in 40-member sub-sample correlations assuming 1000-member correlations as truth. The results will provide guidance for localization in convective-scale ensemble data assimilation systems.
David E. Kingsmill, Jeffrey R. French, and Neil P. Lareau
Atmos. Chem. Phys., 23, 1–21, https://doi.org/10.5194/acp-23-1-2023, https://doi.org/10.5194/acp-23-1-2023, 2023
Short summary
Short summary
This study uses in situ aircraft measurements to characterize the size and shape distributions of 10 µm to 6 mm diameter particles observed during six penetrations of wildfire-induced pyroconvection. Particles sampled in one penetration of a smoke plume are most likely pyrometeors composed of ash. The other penetrations are through pyrocumulus clouds where particle composition is most likely a combination of hydrometeors (ice particles) and pyrometeors (ash).
Ulrike Egerer, André Ehrlich, Matthias Gottschalk, Hannes Griesche, Roel A. J. Neggers, Holger Siebert, and Manfred Wendisch
Atmos. Chem. Phys., 21, 6347–6364, https://doi.org/10.5194/acp-21-6347-2021, https://doi.org/10.5194/acp-21-6347-2021, 2021
Short summary
Short summary
This paper describes a case study of a three-day period with a persistent humidity inversion above a mixed-phase cloud layer in the Arctic. It is based on measurements with a tethered balloon, complemented with results from a dedicated high-resolution large-eddy simulation. Both methods show that the humidity layer acts to provide moisture to the cloud layer through downward turbulent transport. This supply of additional moisture can contribute to the persistence of Arctic clouds.
Jan Chylik, Stephan Mertes, and Roel A. J. Neggers
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2019-637, https://doi.org/10.5194/acp-2019-637, 2019
Preprint withdrawn
Short summary
Short summary
Arctic low-levels clouds play an important role in the Arctic warming, however they are not properly represented in weather and climate models. Among other issues, there are difficulties with balance of ice and liquid in clouds, as well as interaction between clouds and aerosols. In this model study, we focus on the way that variation in the concentration of aerosols affect the evolution of clouds and the turbulence. Model scenarios are based on the observations during the ACLOUD campaign.
Chiel C. van Heerwaarden, Bart J. H. van Stratum, Thijs Heus, Jeremy A. Gibbs, Evgeni Fedorovich, and Juan Pedro Mellado
Geosci. Model Dev., 10, 3145–3165, https://doi.org/10.5194/gmd-10-3145-2017, https://doi.org/10.5194/gmd-10-3145-2017, 2017
Short summary
Short summary
MicroHH (www.microhh.org) is a new and open-source computational fluid dynamics code for the simulation of turbulent flows in the atmosphere. It is made to simulate atmospheric flows up to the finest detail levels at very high resolution. It has been designed from scratch in C++ in order to use a modern design that allows the code to run on more than 10 000 cores, as well as on a graphical processing unit.
Related subject area
Subject: Clouds and Precipitation | Research Activity: Atmospheric Modelling and Data Analysis | Altitude Range: Troposphere | Science Focus: Physics (physical properties and processes)
Correction of ERA5 temperature and relative humidity biases by bivariate quantile mapping for contrail formation analysis
Can pollen affect precipitation?
Potential impacts of marine fuel regulations on an Arctic stratocumulus case and its radiative response
The impact of the mesh size and microphysics scheme on the representation of mid-level clouds in the ICON model in hilly and complex terrain
The role of ascent timescales for warm conveyor belt (WCB) moisture transport into the upper troposphere and lower stratosphere (UTLS)
Estimating the concentration of silver iodide needed to detect unambiguous signatures of glaciogenic cloud seeding
Ice-nucleating particle concentration impacts cloud properties over Dronning Maud Land, East Antarctica, in COSMO-CLM2
Numerical simulation of aerosol concentration effects on cloud droplet size spectrum evolutions of warm stratiform clouds in Jiangxi, China
The impact of aerosol on cloud water: a heuristic perspective
The presence of clouds lowers climate sensitivity in the MPI-ESM1.2 climate model
Diurnal variation in an amplified canopy urban heat island during heat wave periods in the megacity of Beijing: roles of mountain–valley breeze and urban morphology
Diurnal evolution of non-precipitating marine stratocumuli in a large-eddy simulation ensemble
High ice water content in tropical mesoscale convective systems (a conceptual model)
Evolution of cloud droplet temperature and lifetime in spatiotemporally varying subsaturated environments with implications for ice nucleation at cloud edges
Effect of secondary ice production processes on the simulation of ice pellets using the Predicted Particle Properties microphysics scheme
Simulated particle evolution within a winter storm: contributions of riming to radar moments and precipitation fallout
A thermal-driven graupel generation process to explain dry-season convective vigor over the Amazon
Modeling homogeneous ice nucleation from drop-freezing experiments: impact of droplet volume dispersion and cooling rates
Cloud water adjustments to aerosol perturbations are buffered by solar heating in non-precipitating marine stratocumuli
Glaciation of mixed-phase clouds: insights from bulk model and bin-microphysics large-eddy simulation informed by laboratory experiment
Microphysical processes involving the vapour phase dominate in simulated low-level Arctic clouds
Understanding aerosol–cloud interactions using a single-column model for a cold-air outbreak case during the ACTIVATE campaign
Investigating ice formation pathways using a novel two-moment multi-class cloud microphysics scheme
On the sensitivity of aerosol–cloud interactions to changes in sea surface temperature in radiative–convective equilibrium
Exploring aerosol–cloud interactions in liquid-phase clouds over eastern China and its adjacent ocean using the WRF-Chem–SBM model
How the representation of microphysical processes affects tropical condensate in a global storm-resolving model
Impact of secondary ice production on thunderstorm electrification under different aerosol conditions
Finite domains cause bias in measured and modeled distributions of cloud sizes
A systematic evaluation of high-cloud controlling factors
Tracking precipitation features and associated large-scale environments over southeastern Texas
Revisiting the evolution of downhill thunderstorms over Beijing: a new perspective from a radar wind profiler mesonet
How well can persistent contrails be predicted? An update
Model analysis of biases in satellite diagnosed aerosol effect on cloud liquid water path
Dynamical imprints on precipitation cluster statistics across a hierarchy of high-resolution simulations
Present-day correlations are insufficient to predict cloud albedo change by anthropogenic aerosols in E3SM v2
Simulations of primary and secondary ice production during an Arctic mixed-phase cloud case from the Ny-Ålesund Aerosol Cloud Experiment (NASCENT) campaign
Microphysical characteristics of precipitation within convective overshooting over East China observed by GPM DPR and ERA5
Effects of radiative cooling on advection fog over the northwest Pacific Ocean: observations and large-eddy simulations
Evaluating the Wegener–Bergeron–Findeisen process in ICON in large-eddy mode with in situ observations from the CLOUDLAB project
Aerosol-induced closure of marine cloud cells: enhanced effects in the presence of precipitation
Impact of ice multiplication on the cloud electrification of a cold-season thunderstorm: a numerical case study
Developing a climatological simplification of aerosols to enter the cloud microphysics of a global climate model
Interactions between trade wind clouds and local forcings over the Great Barrier Reef: a case study using convection-permitting simulations
Variability in the properties of the distribution of the relative humidity with respect to ice: implications for contrail formation
Simulating the seeder–feeder impacts on cloud ice and precipitation over the Alps
Cloud response to co-condensation of water and organic vapors over the boreal forest
Distribution and morphology of non-persistent contrail and persistent contrail formation areas in ERA5
Connection of Surface Snowfall Bias to Cloud Phase Bias – Satellite Observations, ERA5, and CMIP6
Above-cloud concentrations of cloud condensation nuclei help to sustain some Arctic low-level clouds
Contrail formation on ambient aerosol particles for aircraft with hydrogen combustion: a box model trajectory study
Kevin Wolf, Nicolas Bellouin, Olivier Boucher, Susanne Rohs, and Yun Li
Atmos. Chem. Phys., 25, 157–181, https://doi.org/10.5194/acp-25-157-2025, https://doi.org/10.5194/acp-25-157-2025, 2025
Short summary
Short summary
ERA5 atmospheric reanalysis and airborne in situ observations from IAGOS are compared in terms of the representation of the contrail formation potential and the presence of supersaturation. Differences are traced back to biases in ERA5 relative humidity fields. Those biases are addressed by applying a quantile mapping technique that significantly improved contrail estimation based on post-processed ERA5 data.
Marje Prank, Juha Tonttila, Xiaoxia Shang, Sami Romakkaniemi, and Tomi Raatikainen
Atmos. Chem. Phys., 25, 183–197, https://doi.org/10.5194/acp-25-183-2025, https://doi.org/10.5194/acp-25-183-2025, 2025
Short summary
Short summary
Large primary bioparticles such as pollen can be abundant in the atmosphere. In humid conditions pollen can rupture and release a large number of fine sub-pollen particles (SPPs). The paper investigates what kind of birch pollen concentrations are needed for the pollen and SPPs to start playing a noticeable role in cloud processes and alter precipitation formation. In the studied cases only the largest observed pollen concentrations were able to noticeably alter the precipitation formation.
Luís Filipe Escusa dos Santos, Hannah C. Frostenberg, Alejandro Baró Pérez, Annica M. L. Ekman, Luisa Ickes, and Erik S. Thomson
Atmos. Chem. Phys., 25, 119–142, https://doi.org/10.5194/acp-25-119-2025, https://doi.org/10.5194/acp-25-119-2025, 2025
Short summary
Short summary
The Arctic is experiencing enhanced surface warming. The observed decline in Arctic sea-ice extent is projected to lead to an increase in Arctic shipping activity, which may lead to further climatic feedbacks. Using an atmospheric model and results from marine engine experiments that focused on fuel sulfur content reduction and exhaust wet scrubbing, we investigate how ship exhaust particles influence the properties of Arctic clouds. Implications for radiative surface processes are discussed.
Nadja Omanovic, Brigitta Goger, and Ulrike Lohmann
Atmos. Chem. Phys., 24, 14145–14175, https://doi.org/10.5194/acp-24-14145-2024, https://doi.org/10.5194/acp-24-14145-2024, 2024
Short summary
Short summary
We evaluated the numerical weather model ICON in two horizontal resolutions with two bulk microphysics schemes over hilly and complex terrain in Switzerland and Austria, respectively. We focused on the model's ability to simulate mid-level clouds in summer and winter. By combining observational data from two different field campaigns, we show that an increase in the horizontal resolution and a more advanced cloud microphysics scheme is strongly beneficial for cloud representation.
Cornelis Schwenk and Annette Miltenberger
Atmos. Chem. Phys., 24, 14073–14099, https://doi.org/10.5194/acp-24-14073-2024, https://doi.org/10.5194/acp-24-14073-2024, 2024
Short summary
Short summary
Warm conveyor belts (WCBs) transport moisture into the upper atmosphere, where it acts as a greenhouse gas. This transport is not well understood, and the role of rapidly rising air is unclear. We simulate a WCB and look at fast- and slow-rising air to see how moisture is (differently) transported. We find that for fast-ascending air more ice particles reach higher into the atmosphere and that frozen cloud particles are removed differently than during slow ascent, which has more water vapour.
Jing Yang, Jiaojiao Li, Meilian Chen, Xiaoqin Jing, Yan Yin, Bart Geerts, Zhien Wang, Yubao Liu, Baojun Chen, Shaofeng Hua, Hao Hu, Xiaobo Dong, Ping Tian, Qian Chen, and Yang Gao
Atmos. Chem. Phys., 24, 13833–13848, https://doi.org/10.5194/acp-24-13833-2024, https://doi.org/10.5194/acp-24-13833-2024, 2024
Short summary
Short summary
Detecting unambiguous signatures is vital for examining cloud-seeding impacts, but often, seeding signatures are immersed in natural variability. In this study, reflectivity changes induced by glaciogenic seeding using different AgI concentrations are investigated under various conditions, and a method is developed to estimate the AgI concentration needed to detect unambiguous seeding signatures. The results aid in operational seeding-based decision-making regarding the amount of AgI dispersed.
Florian Sauerland, Niels Souverijns, Anna Possner, Heike Wex, Preben Van Overmeiren, Alexander Mangold, Kwinten Van Weverberg, and Nicole van Lipzig
Atmos. Chem. Phys., 24, 13751–13768, https://doi.org/10.5194/acp-24-13751-2024, https://doi.org/10.5194/acp-24-13751-2024, 2024
Short summary
Short summary
We use a regional climate model, COSMO-CLM², enhanced with a module resolving aerosol processes, to study Antarctic clouds. We prescribe different concentrations of ice-nucleating particles to our model to assess how these clouds respond to concentration changes, validating results with cloud and aerosol observations from the Princess Elisabeth Antarctica station. Our results show that aerosol–cloud interactions vary with temperature, providing valuable insights into Antarctic cloud dynamics.
Yi Li, Xiaoli Liu, and Hengjia Cai
Atmos. Chem. Phys., 24, 13525–13540, https://doi.org/10.5194/acp-24-13525-2024, https://doi.org/10.5194/acp-24-13525-2024, 2024
Short summary
Short summary
The influence of different aerosol modes on cloud processes remains controversial. We modified the aerosol spectra and concentrations to simulate a warm stratiform cloud process in Jiangxi, China, using the WRF-SBM scheme. Research shows that different aerosol spectra have diverse effects on cloud droplet spectra, cloud development, and the correlation between dispersion (ε) and cloud physics quantities. Compared to cloud droplet concentration, ε is more sensitive to the volume radius.
Fabian Hoffmann, Franziska Glassmeier, and Graham Feingold
Atmos. Chem. Phys., 24, 13403–13412, https://doi.org/10.5194/acp-24-13403-2024, https://doi.org/10.5194/acp-24-13403-2024, 2024
Short summary
Short summary
Clouds constitute a major cooling influence on Earth's climate system by reflecting a large fraction of the incident solar radiation back to space. This ability is controlled by the number of cloud droplets, which is governed by the number of aerosol particles in the atmosphere, laying the foundation for so-called aerosol–cloud–climate interactions. In this study, a simple model to understand the effect of aerosol on cloud water is developed and applied.
Andrea Mosso, Thomas Hocking, and Thorsten Mauritsen
Atmos. Chem. Phys., 24, 12793–12806, https://doi.org/10.5194/acp-24-12793-2024, https://doi.org/10.5194/acp-24-12793-2024, 2024
Short summary
Short summary
Clouds play a crucial role in the Earth's energy balance, as they can either warm up or cool down the area they cover depending on their height and depth. They are expected to alter their behaviour under climate change, affecting the warming generated by greenhouse gases. This paper proposes a new method to estimate their overall effect on this warming by simulating a climate where clouds are transparent. Results show that with the model used, clouds have a stabilising effect on climate.
Tao Shi, Yuanjian Yang, Ping Qi, and Simone Lolli
Atmos. Chem. Phys., 24, 12807–12822, https://doi.org/10.5194/acp-24-12807-2024, https://doi.org/10.5194/acp-24-12807-2024, 2024
Short summary
Short summary
This paper explored the formation mechanisms of the amplified canopy urban heat island intensity (ΔCUHII) during heat wave (HW) periods in the megacity of Beijing from the perspectives of mountain–valley breeze and urban morphology. During the mountain breeze phase, high-rise buildings with lower sky view factors (SVFs) had a pronounced effect on the ΔCUHII. During the valley breeze phase, high-rise buildings exerted a dual influence on the ΔCUHII.
Yao-Sheng Chen, Jianhao Zhang, Fabian Hoffmann, Takanobu Yamaguchi, Franziska Glassmeier, Xiaoli Zhou, and Graham Feingold
Atmos. Chem. Phys., 24, 12661–12685, https://doi.org/10.5194/acp-24-12661-2024, https://doi.org/10.5194/acp-24-12661-2024, 2024
Short summary
Short summary
Marine stratocumulus cloud is a type of shallow cloud that covers the vast areas of Earth's surface. It plays an important role in Earth's energy balance by reflecting solar radiation back to space. We used numerical models to simulate a large number of marine stratocumuli with different characteristics. We found that how the clouds develop throughout the day is affected by the level of humidity in the air above the clouds and how closely the clouds connect to the ocean surface.
Alexei Korolev, Zhipeng Qu, Jason Milbrandt, Ivan Heckman, Mélissa Cholette, Mengistu Wolde, Cuong Nguyen, Greg M. McFarquhar, Paul Lawson, and Ann M. Fridlind
Atmos. Chem. Phys., 24, 11849–11881, https://doi.org/10.5194/acp-24-11849-2024, https://doi.org/10.5194/acp-24-11849-2024, 2024
Short summary
Short summary
The phenomenon of high ice water content (HIWC) occurs in mesoscale convective systems (MCSs) when a large number of small ice particles with typical sizes of a few hundred micrometers is found at high altitudes. It was found that secondary ice production in the vicinity of the melting layer plays a key role in the formation and maintenance of HIWC. This study presents a conceptual model of the formation of HIWC in tropical MCSs based on in situ observations and numerical simulation.
Puja Roy, Robert M. Rauber, and Larry Di Girolamo
Atmos. Chem. Phys., 24, 11653–11678, https://doi.org/10.5194/acp-24-11653-2024, https://doi.org/10.5194/acp-24-11653-2024, 2024
Short summary
Short summary
Cloud droplet temperature and lifetime impact cloud microphysical processes such as the activation of ice-nucleating particles. We investigate the thermal and radial evolution of supercooled cloud droplets and their surrounding environments with an aim to better understand observed enhanced ice formation at supercooled cloud edges. This analysis shows that the magnitude of droplet cooling during evaporation is greater than estimated from past studies, especially for drier environments.
Mathieu Lachapelle, Mélissa Cholette, and Julie M. Thériault
Atmos. Chem. Phys., 24, 11285–11304, https://doi.org/10.5194/acp-24-11285-2024, https://doi.org/10.5194/acp-24-11285-2024, 2024
Short summary
Short summary
Hazardous precipitation types such as ice pellets and freezing rain are difficult to predict because they are associated with complex microphysical processes. Using Predicted Particle Properties (P3), this work shows that secondary ice production processes increase the amount of ice pellets simulated while decreasing the amount of freezing rain. Moreover, the properties of the simulated precipitation compare well with those that were measured.
Andrew DeLaFrance, Lynn A. McMurdie, Angela K. Rowe, and Andrew J. Heymsfield
Atmos. Chem. Phys., 24, 11191–11206, https://doi.org/10.5194/acp-24-11191-2024, https://doi.org/10.5194/acp-24-11191-2024, 2024
Short summary
Short summary
Using a numerical model, the process whereby falling ice crystals accumulate supercooled liquid water droplets is investigated to elucidate its effects on radar-based measurements and surface precipitation. We demonstrate that this process accounted for 55% of the precipitation during a wintertime storm and is uniquely discernable from other ice crystal growth processes in Doppler velocity measurements. These results have implications for measurements from airborne and spaceborne platforms.
Toshi Matsui, Daniel Hernandez-Deckers, Scott E. Giangrande, Thiago S. Biscaro, Ann Fridlind, and Scott Braun
Atmos. Chem. Phys., 24, 10793–10814, https://doi.org/10.5194/acp-24-10793-2024, https://doi.org/10.5194/acp-24-10793-2024, 2024
Short summary
Short summary
Using computer simulations and real measurements, we discovered that storms over the Amazon were narrower but more intense during the dry periods, producing heavier rain and more ice particles in the clouds. Our research showed that cumulus bubbles played a key role in creating these intense storms. This study can improve the representation of the effect of continental and ocean environments on tropical regions' rainfall patterns in simulations.
Ravi Kumar Reddy Addula, Ingrid de Almeida Ribeiro, Valeria Molinero, and Baron Peters
Atmos. Chem. Phys., 24, 10833–10848, https://doi.org/10.5194/acp-24-10833-2024, https://doi.org/10.5194/acp-24-10833-2024, 2024
Short summary
Short summary
Ice nucleation from supercooled droplets is important in many weather and climate modeling efforts. For experiments where droplets are steadily supercooled from the freezing point, our work combines nucleation theory and survival probability analysis to predict the nucleation spectrum, i.e., droplet freezing probabilities vs. temperature. We use the new framework to extract approximately consistent rate parameters from experiments with different cooling rates and droplet sizes.
Jianhao Zhang, Yao-Sheng Chen, Takanobu Yamaguchi, and Graham Feingold
Atmos. Chem. Phys., 24, 10425–10440, https://doi.org/10.5194/acp-24-10425-2024, https://doi.org/10.5194/acp-24-10425-2024, 2024
Short summary
Short summary
Quantifying cloud response to aerosol perturbations presents a major challenge in understanding the human impact on climate. Using a large number of process-resolving simulations of marine stratocumulus, we show that solar heating drives a negative feedback mechanism that buffers the persistent negative trend in cloud water adjustment after sunrise. This finding has implications for the dependence of the cloud cooling effect on the timing of deliberate aerosol perturbations.
Aaron Wang, Steve Krueger, Sisi Chen, Mikhail Ovchinnikov, Will Cantrell, and Raymond A. Shaw
Atmos. Chem. Phys., 24, 10245–10260, https://doi.org/10.5194/acp-24-10245-2024, https://doi.org/10.5194/acp-24-10245-2024, 2024
Short summary
Short summary
We employ two methods to examine a laboratory experiment on clouds with both ice and liquid phases. The first assumes well-mixed properties; the second resolves the spatial distribution of turbulence and cloud particles. Results show that while the trends in mean properties generally align, when turbulence is resolved, liquid droplets are not fully depleted by ice due to incomplete mixing. This underscores the threshold of ice mass fraction in distinguishing mixed-phase clouds from ice clouds.
Theresa Kiszler, Davide Ori, and Vera Schemann
Atmos. Chem. Phys., 24, 10039–10053, https://doi.org/10.5194/acp-24-10039-2024, https://doi.org/10.5194/acp-24-10039-2024, 2024
Short summary
Short summary
Microphysical processes impact the phase-partitioning of clouds. In this study we evaluate these processes while focusing on low-level Arctic clouds. To achieve this we used an extensive simulation set in combination with a new diagnostic tool. This study presents our findings on the relevance of these processes and their behaviour under different thermodynamic regimes.
Shuaiqi Tang, Hailong Wang, Xiang-Yu Li, Jingyi Chen, Armin Sorooshian, Xubin Zeng, Ewan Crosbie, Kenneth L. Thornhill, Luke D. Ziemba, and Christiane Voigt
Atmos. Chem. Phys., 24, 10073–10092, https://doi.org/10.5194/acp-24-10073-2024, https://doi.org/10.5194/acp-24-10073-2024, 2024
Short summary
Short summary
We examined marine boundary layer clouds and their interactions with aerosols in the E3SM single-column model (SCM) for a case study. The SCM shows good agreement when simulating the clouds with high-resolution models. It reproduces the relationship between cloud droplet and aerosol particle number concentrations as produced in global models. However, the relationship between cloud liquid water and droplet number concentration is different, warranting further investigation.
Tim Lüttmer, Peter Spichtinger, and Axel Seifert
EGUsphere, https://doi.org/10.5194/egusphere-2024-2157, https://doi.org/10.5194/egusphere-2024-2157, 2024
Short summary
Short summary
We investigate ice formation pathways in idealized convective clouds using a novel microphysics scheme, that distinguishes between five ice classes each with their unique formation mechanism. Ice crystals from rime splintering forms the lowermost layer of ice crystals around the updraft core. The majority of ice crystals in the anvil of the convective cloud stems from frozen droplets. Ice stemming from homogeneous and deposition nucleation was only relevant in the overshoot.
Suf Lorian and Guy Dagan
Atmos. Chem. Phys., 24, 9323–9338, https://doi.org/10.5194/acp-24-9323-2024, https://doi.org/10.5194/acp-24-9323-2024, 2024
Short summary
Short summary
We examine the combined effect of aerosols and sea surface temperature (SST) on clouds under equilibrium conditions in cloud-resolving radiative–convective equilibrium simulations. We demonstrate that the aerosol–cloud interaction's effect on top-of-atmosphere energy gain strongly depends on the underlying SST, while the shortwave part of the spectrum is significantly more sensitive to SST. Furthermore, increasing aerosols influences upper-troposphere stability and thus anvil cloud fraction.
Jianqi Zhao, Xiaoyan Ma, Johannes Quaas, and Hailing Jia
Atmos. Chem. Phys., 24, 9101–9118, https://doi.org/10.5194/acp-24-9101-2024, https://doi.org/10.5194/acp-24-9101-2024, 2024
Short summary
Short summary
We explore aerosol–cloud interactions in liquid-phase clouds over eastern China and its adjacent ocean in winter based on the WRF-Chem–SBM model, which couples a spectral-bin microphysics scheme and an online aerosol module. Our study highlights the differences in aerosol–cloud interactions between land and ocean and between precipitation clouds and non-precipitation clouds, and it differentiates and quantifies their underlying mechanisms.
Ann Kristin Naumann, Monika Esch, and Bjorn Stevens
EGUsphere, https://doi.org/10.5194/egusphere-2024-2268, https://doi.org/10.5194/egusphere-2024-2268, 2024
Short summary
Short summary
This study explores how uncertainties in the representation of microphysical processes affect the tropical condensate distribution in the global storm-resolving model ICON. The results point to the importance of the fall speed of hydrometeor particles and to a simple relationship: the faster a condensate falls, the less there is of it. Implications for the energy balance and precipitation properties are discussed.
Shiye Huang, Jing Yang, Qian Chen, Jiaojiao Li, Qilin Zhang, and Fengxia Guo
EGUsphere, https://doi.org/10.5194/egusphere-2024-2013, https://doi.org/10.5194/egusphere-2024-2013, 2024
Short summary
Short summary
Aerosol and secondary ice production are both vital to charge separation in thunderstorms, but the relative importance of different SIP processes to cloud electrification under different aerosol conditions is not well understood. In this study, we show in a clean environment, the shattering of freezing drops has the greatest effect on the charging rate, while in a polluted environment, both rime splintering and the shattering of freezing drops have a significant effect on cloud electrification.
Thomas D. DeWitt and Timothy J. Garrett
Atmos. Chem. Phys., 24, 8457–8472, https://doi.org/10.5194/acp-24-8457-2024, https://doi.org/10.5194/acp-24-8457-2024, 2024
Short summary
Short summary
There is considerable disagreement on mathematical parameters that describe the number of clouds of different sizes as well as the size of the largest clouds. Both are key defining characteristics of Earth's atmosphere. A previous study provided an incorrect explanation for the disagreement. Instead, the disagreement may be explained by prior studies not properly accounting for the size of their measurement domain. We offer recommendations for how the domain size can be accounted for.
Sarah Wilson Kemsley, Paulo Ceppi, Hendrik Andersen, Jan Cermak, Philip Stier, and Peer Nowack
Atmos. Chem. Phys., 24, 8295–8316, https://doi.org/10.5194/acp-24-8295-2024, https://doi.org/10.5194/acp-24-8295-2024, 2024
Short summary
Short summary
Aiming to inform parameter selection for future observational constraint analyses, we incorporate five candidate meteorological drivers specifically targeting high clouds into a cloud controlling factor framework within a range of spatial domain sizes. We find a discrepancy between optimal domain size for predicting locally and globally aggregated cloud radiative anomalies and identify upper-tropospheric static stability as an important high-cloud controlling factor.
Ye Liu, Yun Qian, Larry K. Berg, Zhe Feng, Jianfeng Li, Jingyi Chen, and Zhao Yang
Atmos. Chem. Phys., 24, 8165–8181, https://doi.org/10.5194/acp-24-8165-2024, https://doi.org/10.5194/acp-24-8165-2024, 2024
Short summary
Short summary
Deep convection under various large-scale meteorological patterns (LSMPs) shows distinct precipitation features. In southeastern Texas, mesoscale convective systems (MCSs) contribute significantly to precipitation year-round, while isolated deep convection (IDC) is prominent in summer and fall. Self-organizing maps (SOMs) reveal convection can occur without large-scale lifting or moisture convergence. MCSs and IDC events have distinct life cycles influenced by specific LSMPs.
Xiaoran Guo, Jianping Guo, Tianmeng Chen, Ning Li, Fan Zhang, and Yuping Sun
Atmos. Chem. Phys., 24, 8067–8083, https://doi.org/10.5194/acp-24-8067-2024, https://doi.org/10.5194/acp-24-8067-2024, 2024
Short summary
Short summary
The prediction of downhill thunderstorms (DSs) remains elusive. We propose an objective method to identify DSs, based on which enhanced and dissipated DSs are discriminated. A radar wind profiler (RWP) mesonet is used to derive divergence and vertical velocity. The mid-troposphere divergence and prevailing westerlies enhance the intensity of DSs, whereas low-level divergence is observed when the DS dissipates. The findings highlight the key role that an RWP mesonet plays in the evolution of DSs.
Sina Hofer, Klaus Gierens, and Susanne Rohs
Atmos. Chem. Phys., 24, 7911–7925, https://doi.org/10.5194/acp-24-7911-2024, https://doi.org/10.5194/acp-24-7911-2024, 2024
Short summary
Short summary
We try to improve the forecast of ice supersaturation (ISS) and potential persistent contrails using data on dynamical quantities in addition to temperature and relative humidity in a modern kind of regression model. Although the results are improved, they are not good enough for flight routing. The origin of the problem is the strong overlap of probability densities conditioned on cases with and without ice-supersaturated regions (ISSRs) in the important range of 70–100 %.
Harri Kokkola, Juha Tonttila, Silvia Calderón, Sami Romakkaniemi, Antti Lipponen, Aapo Peräkorpi, Tero Mielonen, Edward Gryspeerdt, Timo H. Virtanen, Pekka Kolmonen, and Antti Arola
EGUsphere, https://doi.org/10.5194/egusphere-2024-1964, https://doi.org/10.5194/egusphere-2024-1964, 2024
Short summary
Short summary
Understanding how atmospheric aerosols affect clouds is a scientific challenge. One question is how aerosols affects the amount cloud water. We used a cloud-scale model to study these effects on marine clouds. The study showed that variations in cloud properties and instrument noise can cause bias in satellite derived cloud water content. However, our results suggest that for similar weather conditions with well-defined aerosol concentrations, satellite data can reliably track these effects.
Claudia Christine Stephan and Bjorn Stevens
EGUsphere, https://doi.org/10.5194/egusphere-2024-2020, https://doi.org/10.5194/egusphere-2024-2020, 2024
Short summary
Short summary
Tropical precipitation cluster area and intensity distributions follow power laws, but the physical processes responsible for this behavior remain unknown. We analyze global simulations that realistically represent precipitation processes. We consider Earth-like planets as well as virtual planets to realize different types of large-scale dynamics. Our finding is that power laws in Earth’s precipitation cluster statistics stem from the robust power laws in Earth’s atmospheric wind field.
Naser Mahfouz, Johannes Mülmenstädt, and Susannah Burrows
Atmos. Chem. Phys., 24, 7253–7260, https://doi.org/10.5194/acp-24-7253-2024, https://doi.org/10.5194/acp-24-7253-2024, 2024
Short summary
Short summary
Climate models are our primary tool to probe past, present, and future climate states unlike the more recent observation record. By constructing a hypothetical model configuration, we show that present-day correlations are insufficient to predict a persistent uncertainty in climate projection (how much sun because clouds will reflect in a changing climate). We hope our result will contribute to the scholarly conversation on better utilizing observations to constrain climate uncertainties.
Britta Schäfer, Robert Oscar David, Paraskevi Georgakaki, Julie Thérèse Pasquier, Georgia Sotiropoulou, and Trude Storelvmo
Atmos. Chem. Phys., 24, 7179–7202, https://doi.org/10.5194/acp-24-7179-2024, https://doi.org/10.5194/acp-24-7179-2024, 2024
Short summary
Short summary
Mixed-phase clouds, i.e., clouds consisting of ice and supercooled water, are very common in the Arctic. However, how these clouds form is often not correctly represented in standard weather models. We show that both ice crystal concentrations in the cloud and precipitation from the cloud can be improved in the model when aerosol concentrations are prescribed from observations and when more processes for ice multiplication, i.e., the production of new ice particles from existing ice, are added.
Nan Sun, Gaopeng Lu, and Yunfei Fu
Atmos. Chem. Phys., 24, 7123–7135, https://doi.org/10.5194/acp-24-7123-2024, https://doi.org/10.5194/acp-24-7123-2024, 2024
Short summary
Short summary
Microphysical characteristics of convective overshooting are essential but poorly understood, and we examine them by using the latest data. (1) Convective overshooting events mainly occur over NC (Northeast China) and northern MEC (Middle and East China). (2) Radar reflectivity of convective overshooting over NC accounts for a higher proportion below the zero level, while the opposite is the case for MEC and SC (South China). (3) Droplets of convective overshooting are large but sparse.
Liu Yang, Saisai Ding, Jing-Wu Liu, and Su-Ping Zhang
Atmos. Chem. Phys., 24, 6809–6824, https://doi.org/10.5194/acp-24-6809-2024, https://doi.org/10.5194/acp-24-6809-2024, 2024
Short summary
Short summary
Advection fog occurs when warm and moist air moves over a cold sea surface. In this situation, the temperature of the foggy air usually drops below the sea surface temperature (SST), particularly at night. High-resolution simulations show that the cooling effect of longwave radiation from the top of the fog layer permeates through the fog, resulting in a cooling of the surface air below SST. This study emphasizes the significance of monitoring air temperature to enhance sea fog forecasting.
Nadja Omanovic, Sylvaine Ferrachat, Christopher Fuchs, Jan Henneberger, Anna J. Miller, Kevin Ohneiser, Fabiola Ramelli, Patric Seifert, Robert Spirig, Huiying Zhang, and Ulrike Lohmann
Atmos. Chem. Phys., 24, 6825–6844, https://doi.org/10.5194/acp-24-6825-2024, https://doi.org/10.5194/acp-24-6825-2024, 2024
Short summary
Short summary
We present simulations with a high-resolution numerical weather prediction model to study the growth of ice crystals in low clouds following glaciogenic seeding. We show that the simulated ice crystals grow slower than observed and do not consume as many cloud droplets as measured in the field. This may have implications for forecasting precipitation, as the ice phase is crucial for precipitation at middle and high latitudes.
Matthew W. Christensen, Peng Wu, Adam C. Varble, Heng Xiao, and Jerome D. Fast
Atmos. Chem. Phys., 24, 6455–6476, https://doi.org/10.5194/acp-24-6455-2024, https://doi.org/10.5194/acp-24-6455-2024, 2024
Short summary
Short summary
Clouds are essential to keep Earth cooler by reflecting sunlight back to space. We show that an increase in aerosol concentration suppresses precipitation in clouds, causing them to accumulate water and expand in a polluted environment with stronger turbulence and radiative cooling. This process enhances their reflectance by 51 %. It is therefore prudent to account for cloud fraction changes in assessments of aerosol–cloud interactions to improve predictions of climate change.
Jing Yang, Shiye Huang, Tianqi Yang, Qilin Zhang, Yuting Deng, and Yubao Liu
Atmos. Chem. Phys., 24, 5989–6010, https://doi.org/10.5194/acp-24-5989-2024, https://doi.org/10.5194/acp-24-5989-2024, 2024
Short summary
Short summary
This study contributes to filling the dearth of understanding the impacts of different secondary ice production (SIP) processes on the cloud electrification in cold-season thunderstorms. The results suggest that SIP, especially the rime-splintering process and the shattering of freezing drops, has significant impacts on the charge structure of the storm. In addition, the modeled radar composite reflectivity and flash rate are improved after implementing the SIP processes in the model.
Ulrike Proske, Sylvaine Ferrachat, and Ulrike Lohmann
Atmos. Chem. Phys., 24, 5907–5933, https://doi.org/10.5194/acp-24-5907-2024, https://doi.org/10.5194/acp-24-5907-2024, 2024
Short summary
Short summary
Climate models include treatment of aerosol particles because these influence clouds and radiation. Over time their representation has grown increasingly detailed. This complexity may hinder our understanding of model behaviour. Thus here we simplify the aerosol representation of our climate model by prescribing mean concentrations, which saves run time and helps to discover unexpected model behaviour. We conclude that simplifications provide a new perspective for model study and development.
Wenhui Zhao, Yi Huang, Steven Siems, Michael Manton, and Daniel Harrison
Atmos. Chem. Phys., 24, 5713–5736, https://doi.org/10.5194/acp-24-5713-2024, https://doi.org/10.5194/acp-24-5713-2024, 2024
Short summary
Short summary
We studied how shallow clouds and rain behave over the Great Barrier Reef (GBR) using a detailed weather model. We found that the shape of the land, especially mountains, and particles in the air play big roles in influencing these clouds. Surprisingly, the sea's temperature had a smaller effect. Our research helps us understand the GBR's climate and how various factors can influence it, where the importance of the local cloud in thermal coral bleaching has recently been identified.
Sidiki Sanogo, Olivier Boucher, Nicolas Bellouin, Audran Borella, Kevin Wolf, and Susanne Rohs
Atmos. Chem. Phys., 24, 5495–5511, https://doi.org/10.5194/acp-24-5495-2024, https://doi.org/10.5194/acp-24-5495-2024, 2024
Short summary
Short summary
Relative humidity relative to ice (RHi) is a key variable in the formation of cirrus clouds and contrails. This study shows that the properties of the probability density function of RHi differ between the tropics and higher latitudes. In line with RHi and temperature variability, aircraft are likely to produce more contrails with bioethanol and liquid hydrogen as fuel. The impact of this fuel change decreases with decreasing pressure levels but increases from high latitudes to the tropics.
Zane Dedekind, Ulrike Proske, Sylvaine Ferrachat, Ulrike Lohmann, and David Neubauer
Atmos. Chem. Phys., 24, 5389–5404, https://doi.org/10.5194/acp-24-5389-2024, https://doi.org/10.5194/acp-24-5389-2024, 2024
Short summary
Short summary
Ice particles precipitating into lower clouds from an upper cloud, the seeder–feeder process, can enhance precipitation. A numerical modeling study conducted in the Swiss Alps found that 48 % of observed clouds were overlapping, with the seeder–feeder process occurring in 10 % of these clouds. Inhibiting the seeder–feeder process reduced the surface precipitation and ice particle growth rates, which were further reduced when additional ice multiplication processes were included in the model.
Liine Heikkinen, Daniel G. Partridge, Sara Blichner, Wei Huang, Rahul Ranjan, Paul Bowen, Emanuele Tovazzi, Tuukka Petäjä, Claudia Mohr, and Ilona Riipinen
Atmos. Chem. Phys., 24, 5117–5147, https://doi.org/10.5194/acp-24-5117-2024, https://doi.org/10.5194/acp-24-5117-2024, 2024
Short summary
Short summary
The organic vapor condensation with water vapor (co-condensation) in rising air below clouds is modeled in this work over the boreal forest because the forest air is rich in organic vapors. We show that the number of cloud droplets can increase by 20 % if considering co-condensation. The enhancements are even larger if the air contains many small, naturally produced aerosol particles. Such conditions are most frequently met in spring in the boreal forest.
Kevin Wolf, Nicolas Bellouin, and Olivier Boucher
Atmos. Chem. Phys., 24, 5009–5024, https://doi.org/10.5194/acp-24-5009-2024, https://doi.org/10.5194/acp-24-5009-2024, 2024
Short summary
Short summary
The contrail formation potential and its tempo-spatial distribution are estimated for the North Atlantic flight corridor. Meteorological conditions of temperature and relative humidity are taken from the ERA5 re-analysis and IAGOS. Based on IAGOS flight tracks, crossing length, size, orientation, frequency of occurrence, and overlap of persistent contrail formation areas are determined. The presented conclusions might provide a guide for statistical flight track optimization to reduce contrails.
Franziska Hellmuth, Tim Carlsen, Anne Sophie Daloz, Robert Oscar David, and Trude Storelvmo
EGUsphere, https://doi.org/10.5194/egusphere-2024-754, https://doi.org/10.5194/egusphere-2024-754, 2024
Short summary
Short summary
This article compares the occurrence of supercooled liquid-containing clouds (sLCCs) and their link to surface snowfall in CloudSat-CALIPSO, ERA5, and CMIP6 models. Significant discrepancies were found, with ERA5 and CMIP6 consistently overestimating sLCC and snowfall frequency. This bias is likely due to cloud microphysics parameterization. This conclusion has implications for accurately representing cloud phase and snowfall in future climate projections.
Lucas J. Sterzinger and Adele L. Igel
Atmos. Chem. Phys., 24, 3529–3540, https://doi.org/10.5194/acp-24-3529-2024, https://doi.org/10.5194/acp-24-3529-2024, 2024
Short summary
Short summary
Using idealized large eddy simulations, we find that clouds forming in the Arctic in environments with low concentrations of aerosol particles may be sustained by mixing in new particles through the cloud top. Observations show that higher concentrations of these particles regularly exist above cloud top in concentrations that are sufficient to promote this sustenance.
Andreas Bier, Simon Unterstrasser, Josef Zink, Dennis Hillenbrand, Tina Jurkat-Witschas, and Annemarie Lottermoser
Atmos. Chem. Phys., 24, 2319–2344, https://doi.org/10.5194/acp-24-2319-2024, https://doi.org/10.5194/acp-24-2319-2024, 2024
Short summary
Short summary
Using hydrogen as aviation fuel affects contrails' climate impact. We study contrail formation behind aircraft with H2 combustion. Due to the absence of soot emissions, contrail ice crystals are assumed to form only on ambient particles mixed into the plume. The ice crystal number, which strongly varies with temperature and aerosol number density, is decreased by more than 80 %–90 % compared to kerosene contrails. However H2 contrails can form at lower altitudes due to higher H2O emissions.
Cited articles
Abma, D., Heus, T., and Mellado, J. P.: Direct Numerical Simulation of
Evaporative Cooling at the Lateral Boundary of Shallow Cumulus Clouds,
J. Atmos. Sci., 70, 2088–2102,
https://doi.org/10.1175/jas-d-12-0230.1, 2013. a
Ansmann, A., Fruntke, J., and Engelmann, R.: Updraft and downdraft characterization with Doppler lidar: cloud-free versus cumuli-topped mixed layer, Atmos. Chem. Phys., 10, 7845–7858, https://doi.org/10.5194/acp-10-7845-2010, 2010. a, b
Arakawa, A. and Schubert, W. H.: Interaction of a Cumulus Cloud Ensemble with
the Large-Scale Environment, Part I, J. Atmos. Sci., 31,
674–701, https://doi.org/10.1175/1520-0469(1974)031<0674:ioacce>2.0.co;2, 1974. a, b, c
ARM: Lasso Bundle Browser, available at: https://adc.arm.gov/lassobrowser,
last access: 26 August 2020a. a
ARM: ARM Data archive, available at: https://adc.arm.gov/data/,
last access: 26 August 2020b. a
Barron, N., Ryan, S. D., and Heus, T.: Reconciling Chord Length Distributions and Area Distributions for Fields of Fractal Cumulus Clouds, Atmosphere, 11, 824, https://doi.org/10.3390/atmos11080824, 2020. a, b
Benner, T. C. and Curry, J. A.: Characteristics of small tropical cumulus
clouds and their impact on the environment, J. Geophys. Res.-Atmos., 103, 28753–28767, https://doi.org/10.1029/98jd02579, 1998. a, b
Böing, S. J., Jonker, H. J. J., Siebesma, A. P., and Grabowski, W. W.:
Influence of the Subcloud Layer on the Development of a Deep Convective
Ensemble, J. Atmos. Sci., 69, 2682–2698,
https://doi.org/10.1175/jas-d-11-0317.1, 2012. a
Bony, S., Stevens, B., Frierson, D. M. W., Jakob, C., Kageyama, M., Pincus, R.,
Shepherd, T. G., Sherwood, S. C., Siebesma, A. P., Sobel, A. H., Watanabe,
M., and Webb, M. J.: Clouds, circulation and climate sensitivity, Nat.
Geosci., 8, 261–268, https://doi.org/10.1038/ngeo2398, 2015. a
Brient, F. and Schneider, T.: Constraints on Climate Sensitivity from
Space-Based Measurements of Low-Cloud Reflection, J. Climate, 29,
5821–5835, https://doi.org/10.1175/jcli-d-15-0897.1, 2016. a
Brooks, M. E., Hogan, R. J., and Illingworth, A. J.: Parameterizing the
Difference in Cloud Fraction Defined by Area and by Volume as Observed with
Radar and Lidar, J. Atmos. Sci., 62, 2248–2260,
https://doi.org/10.1175/jas3467.1, 2005. a
Brown, A. R., Cederwall, R. T., Chlond, A., Duynkerke, P. G., Golaz, J. C.,
Khairoutdinov, M., Lewellen, D. C., Lock, A. P., MacVean, M. K., Moeng,
C.-H., Neggers, R. A. J., Siebesma, A. P., and Stevens, B.: Large-eddy
simulation of the diurnal cycle of shallow cumulus convection over land,
Q. J. Roy. Meteor. Soc., 128, 1075–1093,
https://doi.org/10.1256/003590002320373210, 2002. a
Dawe, J. T. and Austin, P. H.: Statistical analysis of an LES shallow cumulus cloud ensemble using a cloud tracking algorithm, Atmos. Chem. Phys., 12, 1101–1119, https://doi.org/10.5194/acp-12-1101-2012, 2012. a, b, c
Endo, S., Zhang, D., Vogelmann, A. M., Kollias, P., Lamer, K., Oue, M., Xiao,
H., Gustafson, W. I., and Romps, D. M.: Reconciling Differences Between
Large‐Eddy Simulations and Doppler Lidar Observations of Continental
Shallow Cumulus Cloud‐Base Vertical Velocity, Geophys. Res. Lett.,
46, 11539–11547, https://doi.org/10.1029/2019gl084893, 2019. a, b, c, d, e, f, g
Espy, J. P.: Essays on meteorology. No. IV, J. Franklin I.,
22, 239–246, https://doi.org/10.1016/S0016-0032(36)91215-2, 1836. a
Fast, J. D., Berg, L. K., Feng, Z., Mei, F., Newsom, R., Sakaguchi, K., and
Xiao, H.: The Impact of Variable Land-Atmosphere Coupling on Convective Cloud
Populations Observed During the 2016 HI-SCALE Field Campaign, J.
Adv. Model. Earth Sy., 11, 2629–2654,
https://doi.org/10.1029/2019ms001727, 2019. a, b, c
French, J. R., Vali, G., and Kelly, R. D.: Evolution of small cumulus clouds in
Florida: observations of pulsating growth, Atmos. Res., 52,
143–165, https://doi.org/10.1016/s0169-8095(99)00024-1, 1999. a, b
Griewank, P. J., Heus, T., Lareau, N., and Neggers, R. A. J.: Size-dependence in chord characteristics from simulated and observed continental shallow cumulus, Zenodo, https://doi.org/10.5281/zenodo.3731944, 2020. a
Gustafson, W., Vogelmann, A., Cheng, X., Endo, S., Johnson, K., Krishna, B.,
Li, Z., Toto, T., and Xiao., H.: Atmospheric Radiation Measurement (ARM)
Research Facility. LASSO Data Bundles, Southern Great Plains Central Facility
(C1), ARM Data Archive: Oak Ridge, Tennessee, USA,
https://doi.org/10.5439/1342961, 2017. a
Gustafson, W. I., Vogelmann, A. M., Cheng, X., Dumas, K. K., Endo, S.,
Johnson, K. L., Krishna, B., Li, Z., Toto, T., and Xiao, H.: Description of
the LASSO Data Bundles Product, Tech. rep., Department of Energy's Office
of Scientific and Technical Information, https://doi.org/10.2172/1469590, 2018. a, b
Gustafson, W. I., Vogelmann, A. M., Li, Z., Cheng, X., Dumas, K. K., Endo, S.,
Johnson, K. L., Krishna, B., Toto, T., and Xiao, H.: The Large-Eddy
Simulation (LES) Atmospheric Radiation Measurement (ARM) Symbiotic
Simulation and Observation (LASSO) Activity for Continental Shallow
Convection, B. Am. Meteorol. Soc., 101, E462–E479,
https://doi.org/10.1175/bams-d-19-0065.1, 2020. a, b, c, d, e, f, g
Hagos, S., Feng, Z., Plant, R. S., Houze, R. A., and Xiao, H.: A Stochastic
Framework for Modeling the Population Dynamics of Convective Clouds, J. Adv. Model. Earth Sy., 10, 448–465,
https://doi.org/10.1002/2017ms001214, 2018. a
Heus, T. and Jonker, H. J. J.: Subsiding Shells around Shallow Cumulus Clouds,
J. Atmos. Sci., 65, 1003–1018,
https://doi.org/10.1175/2007jas2322.1, 2008. a, b, c
Heus, T.: microhh release 1.9.1, available at: https://github.com/microhh/microhh2/releases/tag/1.9.1,
last access: 26 August 2020. a
Heus, T. and Seifert, A.: Automated tracking of shallow cumulus clouds in large domain, long duration large eddy simulations, Geosci. Model Dev., 6, 1261–1273, https://doi.org/10.5194/gmd-6-1261-2013, 2013. a
Hoffmann, F., Siebert, H., Schumacher, J., Riechelmann, T., Katzwinkel, J.,
Kumar, B., Götzfried, P., and Raasch, S.: Entrainment and mixing at the
interface of shallow cumulus clouds: Results from a combination of
observations and simulations, Meteorol. Z., 23, 349–368,
https://doi.org/10.1127/0941-2948/2014/0597, 2014. a
Illingworth, A. J., Hogan, R. J., O'Connor, E., Bouniol, D.,
Brooks, M. E., Delanoé, J., Donovan, D. P., Eastment, J. D., Gaussiat,
N., Goddard, J. W. F., Haeffelin, M., Baltink, H. K., Krasnov, O. A., Pelon,
J., Piriou, J.-M., Protat, A., Russchenberg, H. W. J., Seifert, A., Tompkins,
A. M., van Zadelhoff, G.-J., Vinit, F., Willén, U., Wilson, D. R., and
Wrench, C. L.: Cloudnet, B. Am. Meteorol. Soc., 88,
883–898, https://doi.org/10.1175/bams-88-6-883, 2007. a
Jung, E. and Albrecht, B.: Use of Radar Chaff for Studying Circulations in and
around Shallow Cumulus Clouds, J. Appl. Meteorol.
Clim., 53, 2058–2071, https://doi.org/10.1175/jamc-d-13-0255.1, 2014. a
Katzwinkel, J., Siebert, H., Heus, T., and Shaw, R. A.: Measurements of
Turbulent Mixing and Subsiding Shells in Trade Wind Cumuli, J.
Atmos. Sci., 71, 2810–2822, https://doi.org/10.1175/jas-d-13-0222.1, 2014. a
Kitchen, M. and Caughey, S. J.: Tethered-balloon observations of the structure
of small cumulus clouds, Q. J. Roy. Meteor.
Soc., 107, 853–874, https://doi.org/10.1002/qj.49710745407, 2007. a
Laird, N. F., Ochs, H. T., Rauber, R. M., and Miller, L. J.: Initial
Precipitation Formation in Warm Florida Cumulus, J. Atmos.
Sci., 57, 3740–3751,
https://doi.org/10.1175/1520-0469(2000)057<3740:ipfiwf>2.0.co;2, 2000. a
Mallaun, C., Giez, A., Mayr, G. J., and Rotach, M. W.: Subsiding shells and the distribution of up- and downdraughts in warm cumulus clouds over land, Atmos. Chem. Phys., 19, 9769–9786, https://doi.org/10.5194/acp-19-9769-2019, 2019. a
Nair, U. S., Weger, R. C., Kuo, K. S., and Welch, R. M.: Clustering,
randomness, and regularity in cloud fields: 5. The nature of regular cumulus
cloud fields, J. Geophys. Res.-Atmos., 103,
11363–11380, https://doi.org/10.1029/98jd00088, 1998. a
Nam, C. C. W., Quaas, J., Neggers, R., Drian, C. S.-L., and Isotta, F.:
Evaluation of boundary layer cloud parameterizations in the ECHAM5 general
circulation model using CALIPSO and CloudSat satellite data, J.
Adv. Model. Earth Sy., 6, 300–314, https://doi.org/10.1002/2013ms000277,
2014. a
Neggers, R. A. J. and Siebesma, A. P.: Constraining a System of Interacting
Parameterizations through Multiple-Parameter Evaluation: Tracing a
Compensating Error between Cloud Vertical Structure and Cloud Overlap,
J. Climate, 26, 6698–6715, https://doi.org/10.1175/jcli-d-12-00779.1, 2013. a
Neggers, R. A. J., Jonker, H. J. J., and Siebesma, A. P.: Size Statistics of
Cumulus Cloud Populations in Large-Eddy Simulations, J.
Atmos. Sci., 60, 1060–1074,
https://doi.org/10.1175/1520-0469(2003)60<1060:ssoccp>2.0.co;2, 2003. a
Neggers, R. A. J., Duynkerke, P. G., and Rodts, S. M. A.: Shallow cumulus
convection: A validation of large-eddy simulation against aircraft and
Landsat observations, Q. J. Roy. Meteor. Soc.,
129, 2671–2696, https://doi.org/10.1256/qj.02.93, 2006. a, b
Neggers, R. A. J., Siebesma, A. P., and Heus, T.: Continuous Single-Column
Model Evaluation at a Permanent Meteorological Supersite, B.
Am. Meteorol. Soc., 93, 1389–1400,
https://doi.org/10.1175/bams-d-11-00162.1, 2012. a, b
Newsom, R.: Doppler Lidar (DLFPT), Atmospheric Radiation Measurement (ARM) User
Facility, https://doi.org/10.5439/1025185, 2010. a
Olson, J. B., Kenyon, J. S., Angevine, W. A., Brown, J. M., Pagowski, M., and
Sušelj, K.: A Description of the MYNN-EDMF Scheme and the Coupling to Other
Components in WRF–ARW, https://doi.org/10.25923/N9WM-BE49, 2019. a, b
Park, S.: A Unified Convection Scheme (UNICON), Part I: Formulation, J. Atmos. Sci., 71, 3902–3930, https://doi.org/10.1175/jas-d-13-0233.1,
2014. a
Peters, J. M., Nowotarski, C. J., and Mullendore, G. L.: Are Supercells
Resistant to Entrainment because of Their Rotation?, J.
Atmos. Sci., 77, 1475–1495, https://doi.org/10.1175/JAS-D-19-0316.1,
2020. a
Plank, V. G.: The Size Distribution of Cumulus Clouds in Representative Florida
Populations, J. Appl. Meteorol., 8, 46–67,
https://doi.org/10.1175/1520-0450(1969)008<0046:tsdocc>2.0.co;2, 1969. a
Raga, G. B., Jensen, J. B., and Baker, M. B.: Characteristics of Cumulus Band
Clouds off the Coast of Hawaii, J. Atmos. Sci., 47,
338–356, https://doi.org/10.1175/1520-0469(1990)047<0338:cocbco>2.0.co;2, 1990. a, b
Rodts, S. M. A., Duynkerke, P. G., and Jonker, H. J. J.: Size Distributions and
Dynamical Properties of Shallow Cumulus Clouds from Aircraft Observations and
Satellite Data, J. Atmos. Sci., 60, 1895–1912,
https://doi.org/10.1175/1520-0469(2003)060<1895:sdadpo>2.0.co;2, 2003. a, b, c, d
Romps, D. M.: Exact Expression for the Lifting Condensation Level, J. Atmos. Sci., 74, 3891–3900, https://doi.org/10.1175/JAS-D-17-0102.1,
2017. a
Rossow, W. B.: Measuring Cloud Properties from Space: A Review, J.
Climate, 2, 201–213, https://doi.org/10.1175/1520-0442(1989)002<0201:mcpfsa>2.0.co;2,
1989. a
Sakradzija, M. and Klingebiel, M.: Comparing ground-based observations and a
large-eddy simulation of shallow cumuli by isolating the main controlling
factors of the mass flux distribution, Q. J. Roy.
Meteor. Soc., 146, 254–266, https://doi.org/10.1002/qj.3671,
2020. a, b, c
Schalkwijk, J., Jonker, H. J. J., Siebesma, A. P., and Bosveld, F. C.: A
Year-Long Large-Eddy Simulation of the Weather over Cabauw: An Overview,
Mon. Weather Rev., 143, 828–844, https://doi.org/10.1175/mwr-d-14-00293.1, 2015. a, b, c
Sengupta, S. K., Welch, R. M., Navar, M. S., Berendes, T. A., and Chen, D. W.:
Cumulus Cloud Field Morphology and Spatial Patterns Derived from High Spatial
Resolution Landsat Imagery, J. Appl. Meteorol., 29, 1245–1267,
https://doi.org/10.1175/1520-0450(1990)029<1245:ccfmas>2.0.co;2, 1990. a
Sherwood, S. C., Bony, S., and Dufresne, J.-L.: Spread in model climate
sensitivity traced to atmospheric convective mixing, Nature, 505, 37–42,
https://doi.org/10.1038/nature12829, 2014. a
Siebert, H., Franke, H., Lehmann, K., Maser, R., Saw, E. W., Schell, D., Shaw,
R., and Wendisch, M.: Probing Finescale Dynamics and Microphysics of Clouds
with Helicopter-Borne Measurements, B. Am. Meteorol.
Soc., 87, 1727–1738, https://doi.org/10.1175/BAMS-87-12-1727, 2006. a
Siebesma, A. P., Bretherton, C. S., Brown, A., Chlond, A., Cuxart, J.,
Duynkerke, P. G., Jiang, H. L., Khairoutdinov, M., Lewellen, D., Moeng,
C. H., Sanchez, E., Stevens, B., and Stevens, D. E.: A large eddy
simulation intercomparison study of shallow cumulus convection, J. Atmos.
Sci., 60, 1201–1219, https://doi.org/10.1175/1520-0469(2003)60, 2003. a
Simpson, J. and Wiggert, V.: Models odf precipitating cumulus towers,
Mon. Weather Rev., 97, 471–489,
https://doi.org/10.1175/1520-0493(1969)097<0471:mopct>2.3.co;2, 1969. a, b
Tucker, S. C., Senff, C. J., Weickmann, A. M., Brewer, W. A., Banta, R. M.,
Sandberg, S. P., Law, D. C., and Hardesty, R. M.: Doppler Lidar Estimation of
Mixing Height Using Turbulence, Shear, and Aerosol Profiles, J.
Atmos. Ocean. Tech., 26, 673–688,
https://doi.org/10.1175/2008jtecha1157.1, 2009. a
Turner, D. D., Ferrare, R. A., Wulfmeyer, V., and Scarino, A. J.: Aircraft
Evaluation of Ground-Based Raman Lidar Water Vapor Turbulence Profiles in
Convective Mixed Layers, J. Atmos. Ocean. Tech., 31,
1078–1088, https://doi.org/10.1175/jtech-d-13-00075.1, 2014a. a
Turner, D. D., Wulfmeyer, V., Berg, L. K., and Schween, J. H.: Water vapor
turbulence profiles in stationary continental convective mixed layers,
J. Geophys. Res.-Atmos., 119, 11151–11165,
https://doi.org/10.1002/2014jd022202, 2014b. a
Turner, J. S.: The “starting plume” in neutral surroundings, J. Fluid
Mech., 13, 356–368, https://doi.org/10.1017/s0022112062000762, 1962.
a
van Heerwaarden, C. C., van Stratum, B. J. H., Heus, T., Gibbs, J. A., Fedorovich, E., and Mellado, J. P.: MicroHH 1.0: a computational fluid dynamics code for direct numerical simulation and large-eddy simulation of atmospheric boundary layer flows, Geosci. Model Dev., 10, 3145–3165, https://doi.org/10.5194/gmd-10-3145-2017, 2017. a, b
van Laar, T. W., Schemann, V., and Neggers, R. A. J.: Investigating the Diurnal
Evolution of the Cloud Size Distribution of Continental Cumulus Convection
Using Multiday LES, J. Atmos. Sci., 76, 729–747,
https://doi.org/10.1175/jas-d-18-0084.1, 2019. a, b, c
Wang, Y. and Geerts, B.: Humidity variations across the edge of trade wind
cumuli: Observations and dynamical implications, Atmos. Res., 97,
144–156, https://doi.org/10.1016/j.atmosres.2010.03.017, 2010. a, b
Wang, Y. and Geerts, B.: Observations of detrainment signatures from
non-precipitating orographic cumulus clouds, Atmos. Res., 99,
302–324, https://doi.org/10.1016/j.atmosres.2010.10.023, 2011. a
Warner, J.: On Steady-State One-Dimensional Models of Cumulus Convection,
J. Atmos. Sci., 27, 1035–1040,
https://doi.org/10.1175/1520-0469(1970)027<1035:ossodm>2.0.co;2, 1970a. a
Warner, J.: The Microstructure of Cumulus Cloud. Part III. The Nature of the
Updraft, J. Atmos. Sci., 27, 682–688,
https://doi.org/10.1175/1520-0469(1970)027<0682:TMOCCP>2.0.CO;2,
1970b. a, b
Wood, R. and Field, P. R.: The Distribution of Cloud Horizontal Sizes, J. Climate, 24, 4800–4816, https://doi.org/10.1175/2011jcli4056.1, 2011. a, b, c, d
Wulfmeyer, V., Pal, S., Turner, D. D., and Wagner, E.: Can Water Vapour Raman
Lidar Resolve Profiles of Turbulent Variables in the Convective Boundary
Layer?, Bound.-Lay. Meteorol., 136, 253–284,
https://doi.org/10.1007/s10546-010-9494-z, 2010. a, b
Yano, J.-I.: Basic convective element: bubble or plume? A historical review,
Atmospheric Chemistry and Physics, 14, 7019–7030,
https://doi.org/10.5194/acp-14-7019-2014, 2014. a
Yuan, T.: Cloud macroscopic organization: order emerging from randomness, Atmos. Chem. Phys., 11, 7483–7490, https://doi.org/10.5194/acp-11-7483-2011, 2011. a
Zhang, Y., Klein, S. A., Fan, J., Chandra, A. S., Kollias, P., Xie, S., and
Tang, S.: Large-Eddy Simulation of Shallow Cumulus over Land: A Composite
Case Based on ARM Long-Term Observations at Its Southern Great Plains Site,
J. Atmos. Sci., 74, 3229–3251,
https://doi.org/10.1175/jas-d-16-0317.1, 2017. a, b
Zhao, G. and Girolamo, L. D.: Statistics on the macrophysical properties of
trade wind cumuli over the tropical western Atlantic, J. Geophys.
Res.-Atmos., 112, D10204, https://doi.org/10.1029/2006jd007371, 2007. a, b
Zhao, M. and Austin, P. H.: Life Cycle of Numerically Simulated Shallow Cumulus
Clouds. Part II: Mixing Dynamics, J. Atmos. Sci., 62,
1291–1310, https://doi.org/10.1175/jas3415.1, 2005. a, b
Short summary
The idea that larger shallow cumulus clouds have stronger updrafts than small shallow cumulus clouds is as intuitive as it is old. In this paper we gather years of upward-pointing laser measurements from a plain in Oklahoma and combine them with 28 d of high-resolution simulations. Our approach, which has much more data than previous studies, confirms that updraft strength and cloud size are linked and that the simulations reproduce the observed cloud wind and moisture structure.
The idea that larger shallow cumulus clouds have stronger updrafts than small shallow cumulus...
Altmetrics
Final-revised paper
Preprint