Articles | Volume 20, issue 17
Atmos. Chem. Phys., 20, 10211–10230, 2020
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.
Atmos. Chem. Phys., 20, 10211–10230, 2020
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
Size dependence in chord characteristics from simulated and observed continental shallow cumulus
Philipp J. Griewank et al.
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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
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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Preprint withdrawn
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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
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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.
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Subject: Clouds and Precipitation | Research Activity: Atmospheric Modelling | Altitude Range: Troposphere | Science Focus: Physics (physical properties and processes)
Impacts of secondary ice production on Arctic mixed-phase clouds based on ARM observations and CAM6 single-column model simulations
The temperature dependence of ice-nucleating particle concentrations affects the radiative properties of tropical convective cloud systems
The behavior of high-CAPE (convective available potential energy) summer convection in large-domain large-eddy simulations with ICON
Cloud droplet diffusional growth in homogeneous isotropic turbulence: bin microphysics versus Lagrangian super-droplet simulations
The importance of Aitken mode aerosol particles for cloud sustenance in the summertime high Arctic – a simulation study supported by observational data
Sensitivity of mixed-phase moderately deep convective clouds to parameterizations of ice formation – an ensemble perspective
Shallow cumulus cloud feedback in large eddy simulations – bridging the gap to storm-resolving models
Impacts of cloud microphysics parameterizations on simulated aerosol–cloud interactions for deep convective clouds over Houston
Cold cloud microphysical process rates in a global chemistry–climate model
Air traffic and contrail changes during COVID-19 over Europe: A model study
Precipitation enhancement in stratocumulus clouds through airborne seeding: sensitivity analysis by UCLALES-SALSA
Secondary ice production in summer clouds over the Antarctic coast: an underappreciated process in atmospheric models
Opinion: Cloud-phase climate feedback and the importance of ice-nucleating particles
On the ice-nucleating potential of warm hydrometeors in mixed-phase clouds
The enhancement of droplet collision by electric charges and atmospheric electric fields
Cloud adjustments dominate the overall negative aerosol radiative effects of biomass burning aerosols in UKESM1 climate model simulations over the south-eastern Atlantic
Dependence of predictability of precipitation in the northwestern Mediterranean coastal region on the strength of synoptic control
The decomposition of cloud–aerosol forcing in the UK Earth System Model (UKESM1)
Sensitivity of warm clouds to large particles in measured marine aerosol size distributions – a theoretical study
Hectometric-scale simulations of a Mediterranean heavy-precipitation event during the Hydrological cycle in the Mediterranean Experiment (HyMeX) first Special Observation Period (SOP1)
Soot-PCF: Pore condensation and freezing framework for soot aggregates
Urbanization-induced land and aerosol impacts on sea-breeze circulation and convective precipitation
Snow-induced buffering in aerosol–cloud interactions
Environmental sensitivities of shallow-cumulus dilution – Part 1: Selected thermodynamic conditions
Employing airborne radiation and cloud microphysics observations to improve cloud representation in ICON at kilometer-scale resolution in the Arctic
Microphysical Processes Producing High Ice Water Contents (HIWCs) in Tropical Convective Clouds during the HAIC-HIWC Field Campaign: Evaluation of Simulations Using Bulk Microphysical Schemes
An idealized model sensitivity study on Dead Sea desertification with a focus on the impact on convection
Modelling mixed-phase clouds with the large-eddy model UCLALES–SALSA
Development of aerosol activation in the double-moment Unified Model and evaluation with CLARIFY measurements
Is a more physical representation of aerosol activation needed for simulations of fog?
Impact of aerosols and turbulence on cloud droplet growth: an in-cloud seeding case study using a parcel–DNS (direct numerical simulation) approach
Diffusional growth of cloud droplets in homogeneous isotropic turbulence: DNS, scaled-up DNS, and stochastic model
Differences in tropical high clouds among reanalyses: origins and radiative impacts
Vertical redistribution of moisture and aerosol in orographic mixed-phase clouds
Improving the Southern Ocean cloud albedo biases in a general circulation model
Evaluation of Southern Ocean cloud in the HadGEM3 general circulation model and MERRA-2 reanalysis using ship-based observations
Ensemble daily simulations for elucidating cloud–aerosol interactions under a large spread of realistic environmental conditions
Aerosol indirect effects on the temperature–precipitation scaling
The vertical structure and spatial variability of lower-tropospheric water vapor and clouds in the trades
Detection and attribution of aerosol–cloud interactions in large-domain large-eddy simulations with the ICOsahedral Non-hydrostatic model
To what extents do urbanization and air pollution affect fog?
The effects of cloud–aerosol interaction complexity on simulations of presummer rainfall over southern China
Global response of parameterised convective cloud fields to anthropogenic aerosol forcing
Atmospheric energy budget response to idealized aerosol perturbation in tropical cloud systems
Untangling causality in midlatitude aerosol–cloud adjustments
Technical note: Fundamental aspects of ice nucleation via pore condensation and freezing including Laplace pressure and growth into macroscopic ice
The relationship between low-level cloud amount and its proxies over the globe by cloud type
Impact of poleward heat and moisture transports on Arctic clouds and climate simulation
Impact of resolution on large-eddy simulation of midlatitude summertime convection
The diurnal stratocumulus-to-cumulus transition over land in southern West Africa
Xi Zhao, Xiaohong Liu, Vaughan T. J. Phillips, and Sachin Patade
Atmos. Chem. Phys., 21, 5685–5703, https://doi.org/10.5194/acp-21-5685-2021, https://doi.org/10.5194/acp-21-5685-2021, 2021
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Arctic mixed-phase clouds significantly influence the energy budget of the Arctic. We show that a climate model considering secondary ice production (SIP) can explain the observed cloud ice number concentrations, vertical distribution pattern, and probability density distribution of ice crystal number concentrations. The mixed-phase cloud occurrence and phase partitioning are also improved.
Rachel E. Hawker, Annette K. Miltenberger, Jonathan M. Wilkinson, Adrian A. Hill, Ben J. Shipway, Zhiqiang Cui, Richard J. Cotton, Ken S. Carslaw, Paul R. Field, and Benjamin J. Murray
Atmos. Chem. Phys., 21, 5439–5461, https://doi.org/10.5194/acp-21-5439-2021, https://doi.org/10.5194/acp-21-5439-2021, 2021
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The impact of aerosols on clouds is a large source of uncertainty for future climate projections. Our results show that the radiative properties of a complex convective cloud field in the Saharan outflow region are sensitive to the temperature dependence of ice-nucleating particle concentrations. This means that differences in the aerosol source or composition, for the same aerosol size distribution, can cause differences in the outgoing radiation from regions dominated by tropical convection.
Harald Rybka, Ulrike Burkhardt, Martin Köhler, Ioanna Arka, Luca Bugliaro, Ulrich Görsdorf, Ákos Horváth, Catrin I. Meyer, Jens Reichardt, Axel Seifert, and Johan Strandgren
Atmos. Chem. Phys., 21, 4285–4318, https://doi.org/10.5194/acp-21-4285-2021, https://doi.org/10.5194/acp-21-4285-2021, 2021
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Estimating the impact of convection on the upper-tropospheric water budget remains a problem for models employing resolutions of several kilometers or more. A sub-kilometer high-resolution model is used to study summertime convection. The results suggest mostly close agreement with ground- and satellite-based observational data while slightly overestimating total frozen water path and anvil lifetime. The simulations are well suited to supplying information for parameterization development.
Wojciech W. Grabowski and Lois Thomas
Atmos. Chem. Phys., 21, 4059–4077, https://doi.org/10.5194/acp-21-4059-2021, https://doi.org/10.5194/acp-21-4059-2021, 2021
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This paper presents a modeling study that investigates the impact of cloud turbulence on the diffusional growth of cloud droplets and compares modeling results to analytic solutions published in the past. The focus is on comparing the two microphysics modeling methodologies – the Eulerian bin microphysics and Lagrangian particle-based microphysics – and exposing their limitations.
Ines Bulatovic, Adele L. Igel, Caroline Leck, Jost Heintzenberg, Ilona Riipinen, and Annica M. L. Ekman
Atmos. Chem. Phys., 21, 3871–3897, https://doi.org/10.5194/acp-21-3871-2021, https://doi.org/10.5194/acp-21-3871-2021, 2021
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We use detailed numerical modelling to show that small aerosol particles (diameters ~25–80 nm; so-called Aitken mode particles) significantly influence low-level cloud properties in the clean summertime high Arctic. The small particles can help sustain clouds when the concentration of larger particles is low (<10–20 cm-3). Measurements from four different observational campaigns in the high Arctic support the modelling results as they indicate that Aitken mode aerosols are frequently activated.
Annette K. Miltenberger and Paul R. Field
Atmos. Chem. Phys., 21, 3627–3642, https://doi.org/10.5194/acp-21-3627-2021, https://doi.org/10.5194/acp-21-3627-2021, 2021
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The formation of ice in clouds is an important processes in mixed-phase and ice-phase clouds. However, the representation of ice formation in numerical models is highly uncertain. In the last decade, several new parameterizations for heterogeneous freezing have been proposed. Here, we investigate the impact of the parameterization choice on the representation of the convective cloud field and compare the impact to that of initial condition uncertainty.
Jule Radtke, Thorsten Mauritsen, and Cathy Hohenegger
Atmos. Chem. Phys., 21, 3275–3288, https://doi.org/10.5194/acp-21-3275-2021, https://doi.org/10.5194/acp-21-3275-2021, 2021
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Shallow trade wind clouds are a key source of uncertainty to projections of the Earth's changing climate. We perform high-resolution simulations of trade cumulus and investigate how the representation and climate feedback of these clouds depend on the specific grid spacing. We find that the cloud feedback is positive when simulated with kilometre but near zero when simulated with hectometre grid spacing. These findings suggest that storm-resolving models may exaggerate the trade cloud feedback.
Yuwei Zhang, Jiwen Fan, Zhanqing Li, and Daniel Rosenfeld
Atmos. Chem. Phys., 21, 2363–2381, https://doi.org/10.5194/acp-21-2363-2021, https://doi.org/10.5194/acp-21-2363-2021, 2021
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Impacts of anthropogenic aerosols on deep convective clouds (DCCs) and precipitation are examined using both the Morrison bulk and spectral bin microphysics (SBM) schemes. With the SBM scheme, anthropogenic aerosols notably invigorate convective intensity and precipitation, causing better agreement between the simulated DCCs and observations; this effect is absent with the Morrison scheme, mainly due to limitations of the saturation adjustment approach for droplet condensation and evaporation.
Sara Bacer, Sylvia C. Sullivan, Odran Sourdeval, Holger Tost, Jos Lelieveld, and Andrea Pozzer
Atmos. Chem. Phys., 21, 1485–1505, https://doi.org/10.5194/acp-21-1485-2021, https://doi.org/10.5194/acp-21-1485-2021, 2021
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We investigate the relative importance of the rates of both microphysical processes and unphysical correction terms that act as sources or sinks of ice crystals in cold clouds. By means of numerical simulations performed with a global chemistry–climate model, we assess the relevance of these rates at global and regional scales. This estimation is of fundamental importance to assign priority to the development of microphysics parameterizations and compare model output with observations.
Ulrich Schumann, Ian Poll, Roger Teoh, Rainer Koelle, Enrico Spinielli, Jarlath Molloy, George S. Koudis, Robert Baumann, Luca Bugliaro, Marc Stettler, and Christiane Voigt
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2021-62, https://doi.org/10.5194/acp-2021-62, 2021
Revised manuscript accepted for ACP
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The about 70 % reduction of air traffic during the COVID-19 pandemic in March–August in 2020 compared to 2019 provides a test case for the relation between air traffic density, contrails, and their radiative forcing of climate change. This paper investigates the induced traffic and contrail changes in a model study. Besides strong weather changes, the model results indicate aviation induced cirrus and top-of-the atmosphere irradiance changes which may be tested in observations.
Juha Tonttila, Ali Afzalifar, Harri Kokkola, Tomi Raatikainen, Hannele Korhonen, and Sami Romakkaniemi
Atmos. Chem. Phys., 21, 1035–1048, https://doi.org/10.5194/acp-21-1035-2021, https://doi.org/10.5194/acp-21-1035-2021, 2021
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The focus of this study is on rain enhancement by deliberate injection of small particles into clouds (
cloud seeding). The particles, usually released from an aircraft, are expected to enhance cloud droplet growth, but its practical feasibility is somewhat uncertain. To improve upon this, we simulate the seeding effects with a numerical model. The model reproduces the main features seen in field observations, with a strong sensitivity to the total mass of the injected particle material.
Georgia Sotiropoulou, Étienne Vignon, Gillian Young, Hugh Morrison, Sebastian J. O'Shea, Thomas Lachlan-Cope, Alexis Berne, and Athanasios Nenes
Atmos. Chem. Phys., 21, 755–771, https://doi.org/10.5194/acp-21-755-2021, https://doi.org/10.5194/acp-21-755-2021, 2021
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Summer clouds have a significant impact on the radiation budget of the Antarctic surface and thus on ice-shelf melting. However, these are poorly represented in climate models due to errors in their microphysical structure, including the number of ice crystals that they contain. We show that breakup from ice particle collisions can substantially magnify the ice crystal number concentration with significant implications for surface radiation. This process is currently missing in climate models.
Benjamin J. Murray, Kenneth S. Carslaw, and Paul R. Field
Atmos. Chem. Phys., 21, 665–679, https://doi.org/10.5194/acp-21-665-2021, https://doi.org/10.5194/acp-21-665-2021, 2021
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The balance between the amounts of ice and supercooled water in clouds over the world's oceans strongly influences how much these clouds can dampen or amplify global warming. Aerosol particles which catalyse ice formation can dramatically reduce the amount of supercooled water in clouds; hence we argue that we need a concerted effort to improve our understanding of these ice-nucleating particles if we are to improve our predictions of climate change.
Michael Krayer, Agathe Chouippe, Markus Uhlmann, Jan Dušek, and Thomas Leisner
Atmos. Chem. Phys., 21, 561–575, https://doi.org/10.5194/acp-21-561-2021, https://doi.org/10.5194/acp-21-561-2021, 2021
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We address the phenomenon of ice enhancement in the vicinity of warm hydrometeors using highly accurate flow simulation techniques. It is found that the transiently supersaturated zones induced by the hydrometeor's wake are by far larger than what has been previously estimated. The ice enhancement is quantified on the micro- and macroscale, and its relevance is discussed. The results provided may contribute to a (currently unavailable) parametrization of the phenomenon.
Shian Guo and Huiwen Xue
Atmos. Chem. Phys., 21, 69–85, https://doi.org/10.5194/acp-21-69-2021, https://doi.org/10.5194/acp-21-69-2021, 2021
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Observations in previous studies show that cloud droplets carry electric charges. We are curious about whether the electric interaction enhances the collision of cloud droplets. The effect of the electric charge and atmospheric electric field on the raindrop-formation process is studied numerically. Results indicate that a cloud with a small droplet size is more sensitive to an electric charge and field, which could significantly trigger droplet collision and accelerate raindrop formation.
Haochi Che, Philip Stier, Hamish Gordon, Duncan Watson-Parris, and Lucia Deaconu
Atmos. Chem. Phys., 21, 17–33, https://doi.org/10.5194/acp-21-17-2021, https://doi.org/10.5194/acp-21-17-2021, 2021
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The south-eastern Atlantic is semi-permanently covered by some of the largest stratocumulus clouds and is influenced by one-third of the biomass burning emissions from African fires. A UKEMS1 model simulation shows that the absorption effect of biomass burning aerosols is the most significant on clouds and radiation. The dominate cooling and rapid adjustments induced by the radiative effects of biomass burning aerosols result in an overall cooling in the south-eastern Atlantic.
Christian Keil, Lucie Chabert, Olivier Nuissier, and Laure Raynaud
Atmos. Chem. Phys., 20, 15851–15865, https://doi.org/10.5194/acp-20-15851-2020, https://doi.org/10.5194/acp-20-15851-2020, 2020
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During strong synoptic control, which dominates the weather on 80 % of the days in the 2-month HyMeX-SOP1 period, the domain-integrated precipitation predictability assessed with the normalized ensemble standard deviation is above average, the wet bias is smaller and the forecast quality is generally better. In contrast, the spatial forecast quality of the most intense precipitation in the afternoon, as quantified with its 95th percentile, is superior during weakly forced synoptic regimes.
Daniel P. Grosvenor and Kenneth S. Carslaw
Atmos. Chem. Phys., 20, 15681–15724, https://doi.org/10.5194/acp-20-15681-2020, https://doi.org/10.5194/acp-20-15681-2020, 2020
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Particles arising from human activity interact with clouds and affect how much of the Sun's energy is reflected away. Lack of understanding about how to represent this in models leads to large uncertainties in climate predictions. We quantify cloud responses to particles in the latest UK Met Office climate model over the North Atlantic Ocean, showing that, in contrast to suggestions elsewhere, increases in cloud coverage and thickness are important over large areas.
Tom Dror, J. Michel Flores, Orit Altaratz, Guy Dagan, Zev Levin, Assaf Vardi, and Ilan Koren
Atmos. Chem. Phys., 20, 15297–15306, https://doi.org/10.5194/acp-20-15297-2020, https://doi.org/10.5194/acp-20-15297-2020, 2020
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We used in situ aerosol measurements over the Atlantic, Caribbean, and Pacific to initialize a cloud model and study the impact of aerosol concentration and sizes on warm clouds. We show that high aerosol concentration increases cloud mass and reduces surface rain when giant particles (diameter > 9 µm) are present. The large aerosols changed the timing and magnitude of internal cloud processes and resulted in an enhanced evaporation below cloud base and dramatically reduced surface rain.
Olivier Nuissier, Fanny Duffourg, Maxime Martinet, Véronique Ducrocq, and Christine Lac
Atmos. Chem. Phys., 20, 14649–14667, https://doi.org/10.5194/acp-20-14649-2020, https://doi.org/10.5194/acp-20-14649-2020, 2020
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This present article demonstrates how numerical simulations with very high horizontal resolution (150 m) can contribute to better understanding the key physical processes (turbulence and microphysics) that lead to Mediterranean heavy precipitation.
Claudia Marcolli, Fabian Mahrt, and Bernd Kärcher
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2020-1134, https://doi.org/10.5194/acp-2020-1134, 2020
Revised manuscript accepted for ACP
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Pores are aerosol particle features that trigger ice nucleation, as they take up water by capillary condensation below water saturation that freezes at low temperatures. The pore ice can then grow into macroscopic ice crystals making up cirrus clouds. Here, we investigate the pores in soot aggregates responsible for pore condensation and freezing (PCF). Moreover, we present a framework to parameterize soot-PCF that is able to predict the ice nucleation activity based on soot properties.
Jiwen Fan, Yuwei Zhang, Zhanqing Li, Jiaxi Hu, and Daniel Rosenfeld
Atmos. Chem. Phys., 20, 14163–14182, https://doi.org/10.5194/acp-20-14163-2020, https://doi.org/10.5194/acp-20-14163-2020, 2020
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We investigate the urbanization-induced land and aerosol impacts on convective clouds and precipitation over Houston. We find that Houston urbanization notably enhances storm intensity and precipitation, with the anthropogenic aerosol effect more significant. Urban land effect strengthens sea-breeze circulation, leading to a faster development of warm cloud into mixed-phase cloud and earlier rain. The anthropogenic aerosol effect accelerates the development of storms into deep convection.
Takuro Michibata, Kentaroh Suzuki, and Toshihiko Takemura
Atmos. Chem. Phys., 20, 13771–13780, https://doi.org/10.5194/acp-20-13771-2020, https://doi.org/10.5194/acp-20-13771-2020, 2020
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This work reveals that prognostic precipitation significantly reduces the magnitude of aerosol–cloud interactions (ERFaci), mainly due to the collection process associated with snowflakes and underlying cloud droplets. This precipitation-driven buffering effect, which is missing in traditional GCMs, can explain the model–observation discrepancy in ERFaci. These results underscore the necessity for a prognostic precipitation framework in GCMs for more reliable climate simulations.
Sonja Drueke, Daniel J. Kirshbaum, and Pavlos Kollias
Atmos. Chem. Phys., 20, 13217–13239, https://doi.org/10.5194/acp-20-13217-2020, https://doi.org/10.5194/acp-20-13217-2020, 2020
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This numerical study provides insights into selected environmental sensitivities of shallow-cumulus dilution. Among the parameters under consideration, the dilution of the cloud cores is strongly sensitive to continentality and cloud-layer relative humidity and weakly sensitive to subcloud- and cloud-layer depths. The impacts of all four parameters are interpreted using a similarity theory of shallow cumulus and buoyancy-sorting arguments.
Jan Kretzschmar, Johannes Stapf, Daniel Klocke, Manfred Wendisch, and Johannes Quaas
Atmos. Chem. Phys., 20, 13145–13165, https://doi.org/10.5194/acp-20-13145-2020, https://doi.org/10.5194/acp-20-13145-2020, 2020
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This study compares simulations with the ICON model at the kilometer scale to airborne radiation and cloud microphysics observations that have been derived during the ACLOUD aircraft campaign around Svalbard, Norway, in May/June 2017. We find an overestimated surface warming effect of clouds compared to the observations in our setup. This bias was reduced by considering subgrid-scale vertical motion in the activation of cloud condensation nuclei in the two-moment microphysical scheme used.
Yongjie Huang, Wei Wu, Greg M. McFarquhar, Xuguang Wang, Hugh Morrison, Alexander Ryzhkov, Yachao Hu, Mengistu Wolde, Cuong Nguyen, Alfons Schwarzenboeck, Jason Milbrandt, Alexei V. Korolev, and Ivan Heckman
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2020-1045, https://doi.org/10.5194/acp-2020-1045, 2020
Revised manuscript accepted for ACP
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Numerous small ice crystals in the tropical convective storms are difficult to detect and could be potentially hazardous for commercial aircraft. This study evaluated the numerical models against the airborne observations and investigated the potential cloud processes that could lead to the production of these large numbers of small ice crystals. It is found that key microphysical processes are still lacking or misrepresented in current numerical models to realistically simulate the phenomenon.
Samiro Khodayar and Johannes Hoerner
Atmos. Chem. Phys., 20, 12011–12031, https://doi.org/10.5194/acp-20-12011-2020, https://doi.org/10.5194/acp-20-12011-2020, 2020
Jaakko Ahola, Hannele Korhonen, Juha Tonttila, Sami Romakkaniemi, Harri Kokkola, and Tomi Raatikainen
Atmos. Chem. Phys., 20, 11639–11654, https://doi.org/10.5194/acp-20-11639-2020, https://doi.org/10.5194/acp-20-11639-2020, 2020
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In this study, we present an improved cloud model that reproduces the behaviour of mixed-phase clouds containing liquid droplets and ice crystals in more detail than before. This model is a convenient computational tool that enables the study of phenomena that cannot fit into a laboratory. These clouds have a significant role in climate, but they are not yet properly understood. Here, we show the advantages of the new model in a case study focusing on Arctic mixed-phase clouds.
Hamish Gordon, Paul R. Field, Steven J. Abel, Paul Barrett, Keith Bower, Ian Crawford, Zhiqiang Cui, Daniel P. Grosvenor, Adrian A. Hill, Jonathan Taylor, Jonathan Wilkinson, Huihui Wu, and Ken S. Carslaw
Atmos. Chem. Phys., 20, 10997–11024, https://doi.org/10.5194/acp-20-10997-2020, https://doi.org/10.5194/acp-20-10997-2020, 2020
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The Met Office's Unified Model is widely used both for weather forecasting and climate prediction. We present the first version of the model in which both aerosol and cloud particle mass and number concentrations are allowed to evolve separately and independently, which is important for studying how aerosols affect weather and climate. We test the model against aircraft observations near Ascension Island in the Atlantic, focusing on how aerosols can "activate" to become cloud droplets.
Craig Poku, Andrew N. Ross, Adrian A. Hill, Alan M. Blyth, and Ben Shipway
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2020-904, https://doi.org/10.5194/acp-2020-904, 2020
Revised manuscript accepted for ACP
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We present a new aerosol activation scheme that is suitable for modelling both fog and convective clouds. Most current activation schemes are designed for convective cloud and we demonstrate that using them to model fog can negatively impact its lifecycle. Our scheme has been used to model an observed fog case in the UK, where we demonstrate that a more physically based representation of aerosol activation is required to capture the transition to a deeper layer; more inline with observations.
Sisi Chen, Lulin Xue, and Man-Kong Yau
Atmos. Chem. Phys., 20, 10111–10124, https://doi.org/10.5194/acp-20-10111-2020, https://doi.org/10.5194/acp-20-10111-2020, 2020
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This study employs a parcel–DNS (direct numerical simulation) modeling framework to accurately resolve the aerosol–droplet–turbulence interactions in an ascending air parcel. The effect of turbulence, aerosol hygroscopicity, and aerosol mass loading on droplet growth and rain formation is investigated through a series of in-cloud seeding experiments in which hygroscopic particles were seeded near the cloud base.
Lois Thomas, Wojciech W. Grabowski, and Bipin Kumar
Atmos. Chem. Phys., 20, 9087–9100, https://doi.org/10.5194/acp-20-9087-2020, https://doi.org/10.5194/acp-20-9087-2020, 2020
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This work presents an extension of a classical small-scale modeling approach, direct numerical simulation (DNS), to large computational volumes, tens and hundreds of meters on the side. Diffusional growth of cloud droplets is more significantly affected by large scales of turbulent motions because vertical velocity perturbations associated with those scales result in larger and longer-lasting supersaturation perturbations that affect the spread of the droplet spectrum.
Jonathon S. Wright, Xiaoyi Sun, Paul Konopka, Kirstin Krüger, Bernard Legras, Andrea M. Molod, Susann Tegtmeier, Guang J. Zhang, and Xi Zhao
Atmos. Chem. Phys., 20, 8989–9030, https://doi.org/10.5194/acp-20-8989-2020, https://doi.org/10.5194/acp-20-8989-2020, 2020
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High clouds are influential in tropical climate. Although reanalysis cloud fields are essentially model products, they are indirectly constrained by observations and offer global coverage with direct links to advanced water and energy cycle metrics, giving them many useful applications. We describe how high cloud fields are generated in reanalyses, assess their realism and reliability in the tropics, and evaluate how differences in these fields affect other aspects of the reanalysis state.
Annette K. Miltenberger, Paul R. Field, Adrian H. Hill, and Andrew J. Heymsfield
Atmos. Chem. Phys., 20, 7979–8001, https://doi.org/10.5194/acp-20-7979-2020, https://doi.org/10.5194/acp-20-7979-2020, 2020
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Orographic wave clouds offer a natural laboratory to investigate cloud microphysical processes and their representation in atmospheric models. They impact the larger-scale flow by a vertical redistribution of moisture and aerosol. We use detailed observations from the ICE-L campaign to evaluate the representation of these clouds in a state-of-the-art numerical weather prediction model and explore the impact of environmental conditions on the vertical redistribution of moisture.
Vidya Varma, Olaf Morgenstern, Paul Field, Kalli Furtado, Jonny Williams, and Patrick Hyder
Atmos. Chem. Phys., 20, 7741–7751, https://doi.org/10.5194/acp-20-7741-2020, https://doi.org/10.5194/acp-20-7741-2020, 2020
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The present generation of global climate models has an insufficiently reflected short-wave radiation, especially over the Southern Ocean. This leads to an excessive heating of the ocean surface in the model, creating sea surface temperature biases and subsequent problems with atmospheric dynamics. Misrepresentation of clouds could be attributed to this radiation bias; we try to address this issue by slowing the growth rate of ice crystals and improving the supercooled liquid clouds in the model.
Peter Kuma, Adrian J. McDonald, Olaf Morgenstern, Simon P. Alexander, John J. Cassano, Sally Garrett, Jamie Halla, Sean Hartery, Mike J. Harvey, Simon Parsons, Graeme Plank, Vidya Varma, and Jonny Williams
Atmos. Chem. Phys., 20, 6607–6630, https://doi.org/10.5194/acp-20-6607-2020, https://doi.org/10.5194/acp-20-6607-2020, 2020
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We evaluate clouds over the Southern Ocean in the climate model HadGEM3 and reanalysis MERRA-2 using ship-based ceilometer and radiosonde observations. We find the models underestimate cloud cover by 18–25 %, with clouds below 2 km dominant in reality but lacking in the models. We find a strong link between clouds, atmospheric stability and sea surface temperature in observations but not in the models, implying that sub-grid processes do not generate enough cloud in response to these conditions.
Guy Dagan and Philip Stier
Atmos. Chem. Phys., 20, 6291–6303, https://doi.org/10.5194/acp-20-6291-2020, https://doi.org/10.5194/acp-20-6291-2020, 2020
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Ensemble daily simulations for two separate month-long periods over a region near Barbados were conducted to investigate aerosol effects on cloud properties and the atmospheric energy budget. For each day, two simulations were conducted with low and high cloud droplet number concentrations representing clean and polluted conditions, respectively. These simulations are used to distinguish between properties that are robustly affected by changes in aerosol concentrations and those that are not.
Nicolas Da Silva, Sylvain Mailler, and Philippe Drobinski
Atmos. Chem. Phys., 20, 6207–6223, https://doi.org/10.5194/acp-20-6207-2020, https://doi.org/10.5194/acp-20-6207-2020, 2020
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Microphysical effects of aerosols were found to weaken precipitation in a Euro-Mediterranean area. The present numerical study quantifies the processes that may be involved through the use of the temperature–precipitation relationship. It shows larger aerosol effects at low temperatures. At these temperatures, the process that contributes most is the increase in atmospheric stability through an enhanced aerosol cooling effect in the lower troposphere compared to the upper troposphere.
Ann Kristin Naumann and Christoph Kiemle
Atmos. Chem. Phys., 20, 6129–6145, https://doi.org/10.5194/acp-20-6129-2020, https://doi.org/10.5194/acp-20-6129-2020, 2020
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The interaction of water vapor and cloudiness poses challenges for weather and climate models. In this study we compare airborne lidar measurements from two field campaigns in the tropical Atlantic with high-resolution simulations. We find that at kilometer-scale grid spacing, the simulations show good skill in reproducing the water vapor distribution in the trades but struggle to capture the transition from cloud-free to low cloud fraction with increasing moisture.
Montserrat Costa-Surós, Odran Sourdeval, Claudia Acquistapace, Holger Baars, Cintia Carbajal Henken, Christa Genz, Jonas Hesemann, Cristofer Jimenez, Marcel König, Jan Kretzschmar, Nils Madenach, Catrin I. Meyer, Roland Schrödner, Patric Seifert, Fabian Senf, Matthias Brueck, Guido Cioni, Jan Frederik Engels, Kerstin Fieg, Ksenia Gorges, Rieke Heinze, Pavan Kumar Siligam, Ulrike Burkhardt, Susanne Crewell, Corinna Hoose, Axel Seifert, Ina Tegen, and Johannes Quaas
Atmos. Chem. Phys., 20, 5657–5678, https://doi.org/10.5194/acp-20-5657-2020, https://doi.org/10.5194/acp-20-5657-2020, 2020
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The impact of anthropogenic aerosols on clouds is a key uncertainty in climate change. This study analyses large-domain simulations with a new high-resolution model to investigate the differences in clouds between 1985 and 2013 comparing multiple observational datasets. The differences in aerosol and in cloud droplet concentrations are clearly detectable. For other quantities, the detection and attribution proved difficult, despite a substantial impact on the Earth's energy budget.
Shuqi Yan, Bin Zhu, Yong Huang, Jun Zhu, Hanqing Kang, Chunsong Lu, and Tong Zhu
Atmos. Chem. Phys., 20, 5559–5572, https://doi.org/10.5194/acp-20-5559-2020, https://doi.org/10.5194/acp-20-5559-2020, 2020
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The development of China has caused rapid urbanization and severe air pollution. However, the extent of their individual and combined effects on fog is not well understood. Through numerical experiments, we find that urbanization suppresses low-level fog but probably promotes upper-level fog. Additional aerosols generally promote fog. Urbanization affects fog to a much larger extent than aerosols do.
Kalli Furtado, Paul Field, Yali Luo, Tianjun Zhou, and Adrian Hill
Atmos. Chem. Phys., 20, 5093–5110, https://doi.org/10.5194/acp-20-5093-2020, https://doi.org/10.5194/acp-20-5093-2020, 2020
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By combining observations with simulations from a weather forecasting model, new insights are obtained into extreme rainfall processes. We use a model which includes the effects of aerosols on clouds in a fully consistent way. This greater complexity improves realism but raises the computational cost. We address the cost–benefit relationship of this and show that cloud–aerosol interactions have important, measurable benefits for simulating climate extremes.
Zak Kipling, Laurent Labbouz, and Philip Stier
Atmos. Chem. Phys., 20, 4445–4460, https://doi.org/10.5194/acp-20-4445-2020, https://doi.org/10.5194/acp-20-4445-2020, 2020
Guy Dagan, Philip Stier, Matthew Christensen, Guido Cioni, Daniel Klocke, and Axel Seifert
Atmos. Chem. Phys., 20, 4523–4544, https://doi.org/10.5194/acp-20-4523-2020, https://doi.org/10.5194/acp-20-4523-2020, 2020
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In order to better understand the physical processes behind aerosol effects on the atmospheric energy budget, we analyse numerical simulations of tropical cloud systems. Two sets of simulations, at different dates during the NARVAL 2 field campaign, are simulated with different dominant cloud modes. Our results demonstrate that under different environmental conditions, the response of the atmospheric energy budget to aerosol perturbation could be different.
Daniel T. McCoy, Paul Field, Hamish Gordon, Gregory S. Elsaesser, and Daniel P. Grosvenor
Atmos. Chem. Phys., 20, 4085–4103, https://doi.org/10.5194/acp-20-4085-2020, https://doi.org/10.5194/acp-20-4085-2020, 2020
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Incomplete understanding of how aerosol affects clouds degrades our ability to predict future climate. In particular, it is unclear how aerosol affects the lifetime of clouds. Does it increase or decrease it? This confusion is partially because causality flows from aerosol to clouds and clouds to aerosol, and it is hard to tell what is happening in observations. Here, we use simulations to tell us about how clouds affect aerosol and use this to interpret observations, showing increased lifetime.
Claudia Marcolli
Atmos. Chem. Phys., 20, 3209–3230, https://doi.org/10.5194/acp-20-3209-2020, https://doi.org/10.5194/acp-20-3209-2020, 2020
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Pore condensation and freezing (PCF) is an ice nucleation mechanism explaining ice formation at low ice supersaturation. It is assumed that liquid water condenses in pores of solid aerosol particles below water saturation followed by ice nucleation within the pores. This study discusses conditions of pore filling, homogeneous ice nucleation within the volume of porewater, and growth of ice out of the pores, taking the effect of negative pressure within pores below water saturation into account.
Jihoon Shin and Sungsu Park
Atmos. Chem. Phys., 20, 3041–3060, https://doi.org/10.5194/acp-20-3041-2020, https://doi.org/10.5194/acp-20-3041-2020, 2020
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In this work, we show that the previously identified strong spatiotemporal correlation relationship between the low-level cloud amount (LCA) and its large-scale environmental proxy, the estimated low-level cloud fraction (ELF), holds for various low-level cloud types over the globe rather than for a specific cloud type. However, we also identify several weaknesses of the ELF and suggest a potential pathway to further improve it in the future as a global proxy for LCA.
Eun-Hyuk Baek, Joo-Hong Kim, Sungsu Park, Baek-Min Kim, and Jee-Hoon Jeong
Atmos. Chem. Phys., 20, 2953–2966, https://doi.org/10.5194/acp-20-2953-2020, https://doi.org/10.5194/acp-20-2953-2020, 2020
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Many general circulation models (GCMs) have difficulty simulating Arctic clouds and climate, causing substantial inter-model spread. By analyzing various model simulation results, we found that the association between the enhanced poleward transports of heat and moisture and an increase in liquid clouds over the Arctic is evident in GCMs. Our study demonstrates that enhanced poleward heat and moisture transport in a model can improve simulations of Arctic clouds and climate.
Christopher Moseley, Ieda Pscheidt, Guido Cioni, and Rieke Heinze
Atmos. Chem. Phys., 20, 2891–2910, https://doi.org/10.5194/acp-20-2891-2020, https://doi.org/10.5194/acp-20-2891-2020, 2020
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In this paper, we analyze a climate simulation over Germany of a continuous period in May and June 2016, with resolutions of 600 m, 300 m, and 150 m. This resolution is high enough that strong convective rain events like rain showers and thunderstorms are sufficiently resolved. Our analysis shows that the tendency of convection to organize is improved at higher resolution and that the highest-resolution simulation is closest to weather radar data.
Xabier Pedruzo-Bagazgoitia, Stephan R. de Roode, Bianca Adler, Karmen Babić, Cheikh Dione, Norbert Kalthoff, Fabienne Lohou, Marie Lothon, and Jordi Vilà-Guerau de Arellano
Atmos. Chem. Phys., 20, 2735–2754, https://doi.org/10.5194/acp-20-2735-2020, https://doi.org/10.5194/acp-20-2735-2020, 2020
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Using a high-resolution model we simulate the transition from night to day clouds on southern West Africa using observations from the DACCIWA project. We find that the radiative effects of clouds help mantain a thick cloud layer in the night, while the mixing of cloud air with air above during the day, aided by moisture and heat fluxes at the surface, thins this layer and promotes its transition to other clouds. The effect of changing wind with height accelerates the transition.
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...
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