Articles | Volume 21, issue 4
https://doi.org/10.5194/acp-21-2765-2021
© Author(s) 2021. 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-21-2765-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| Highlight paper
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24 Feb 2021
Research article | Highlight paper |
| 24 Feb 2021
| 24 Feb 2021
A-Train estimates of the sensitivity of the cloud-to-rainwater ratio to cloud size, relative humidity, and aerosols
Department of Atmospheric Sciences, Texas A&M University, College Station, Texas, USA
Anita D. Rapp
Department of Atmospheric Sciences, Texas A&M University, College Station, Texas, USA
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Marcin J. Kurowski, Matthew D. Lebsock, and Kevin M. Smalley
EGUsphere, https://doi.org/10.5194/egusphere-2025-714, https://doi.org/10.5194/egusphere-2025-714, 2025
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This study explores how clouds respond to pollution throughout the day using high-resolution simulations. Polluted clouds show stronger daily changes: thicker clouds at night and in the morning but faster thinning in the afternoon. Pollution reduces rainfall but enhances drying, deepening the cloud layer. While the pollution initially brightens clouds, the daily cycle of cloudiness slightly reduces this brightening effect.
Kevin M. Smalley, Matthew D. Lebsock, Ryan Eastman, Mark Smalley, and Mikael K. Witte
Atmos. Chem. Phys., 22, 8197–8219, https://doi.org/10.5194/acp-22-8197-2022, https://doi.org/10.5194/acp-22-8197-2022, 2022
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We use geostationary satellite observations to track pockets of open-cell (POC) stratocumulus and analyze how precipitation, cloud microphysics, and the environment change. Precipitation becomes more intense, corresponding to increasing effective radius and decreasing number concentrations, while the environment remains relatively unchanged. This implies that changes in cloud microphysics are more important than the environment to POC development.
Kevin M. Smalley, Andrew E. Dessler, Slimane Bekki, Makoto Deushi, Marion Marchand, Olaf Morgenstern, David A. Plummer, Kiyotaka Shibata, Yousuke Yamashita, and Guang Zeng
Atmos. Chem. Phys., 17, 8031–8044, https://doi.org/10.5194/acp-17-8031-2017, https://doi.org/10.5194/acp-17-8031-2017, 2017
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This paper explains a new way to evaluate simulated lower-stratospheric water vapor. We use a multivariate linear regression to predict 21st century lower stratospheric water vapor within 12 chemistry climate models using tropospheric warming, the Brewer–Dobson circulation, and the quasi-biennial oscillation as predictors. This methodology produce strong fits to simulated water vapor, and potentially represents a superior method to evaluate model trends in lower-stratospheric water vapor.
Marcin J. Kurowski, Matthew D. Lebsock, and Kevin M. Smalley
EGUsphere, https://doi.org/10.5194/egusphere-2025-714, https://doi.org/10.5194/egusphere-2025-714, 2025
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This study explores how clouds respond to pollution throughout the day using high-resolution simulations. Polluted clouds show stronger daily changes: thicker clouds at night and in the morning but faster thinning in the afternoon. Pollution reduces rainfall but enhances drying, deepening the cloud layer. While the pollution initially brightens clouds, the daily cycle of cloudiness slightly reduces this brightening effect.
Bo Chen, Seth A. Thompson, Brianna H. Matthews, Milind Sharma, Ron Li, Christopher J. Nowotarski, Anita D. Rapp, and Sarah D. Brooks
EGUsphere, https://doi.org/10.5194/egusphere-2024-3363, https://doi.org/10.5194/egusphere-2024-3363, 2024
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This study presents a new method combining ground-based measurements and lidar to track how aerosols are distributed at different heights in the atmosphere. By correcting for humidity, which causes aerosols to grow and intensify the lidar signal, the method provides more accurate aerosol vertical profiles. Our results show that aerosol profiles can vary significantly over short distances. This technique can help improve understanding of aerosol-cloud interactions.
Kevin M. Smalley, Matthew D. Lebsock, Ryan Eastman, Mark Smalley, and Mikael K. Witte
Atmos. Chem. Phys., 22, 8197–8219, https://doi.org/10.5194/acp-22-8197-2022, https://doi.org/10.5194/acp-22-8197-2022, 2022
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We use geostationary satellite observations to track pockets of open-cell (POC) stratocumulus and analyze how precipitation, cloud microphysics, and the environment change. Precipitation becomes more intense, corresponding to increasing effective radius and decreasing number concentrations, while the environment remains relatively unchanged. This implies that changes in cloud microphysics are more important than the environment to POC development.
Kevin M. Smalley, Andrew E. Dessler, Slimane Bekki, Makoto Deushi, Marion Marchand, Olaf Morgenstern, David A. Plummer, Kiyotaka Shibata, Yousuke Yamashita, and Guang Zeng
Atmos. Chem. Phys., 17, 8031–8044, https://doi.org/10.5194/acp-17-8031-2017, https://doi.org/10.5194/acp-17-8031-2017, 2017
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This paper explains a new way to evaluate simulated lower-stratospheric water vapor. We use a multivariate linear regression to predict 21st century lower stratospheric water vapor within 12 chemistry climate models using tropospheric warming, the Brewer–Dobson circulation, and the quasi-biennial oscillation as predictors. This methodology produce strong fits to simulated water vapor, and potentially represents a superior method to evaluate model trends in lower-stratospheric water vapor.
Related subject area
Subject: Clouds and Precipitation | Research Activity: Remote Sensing | Altitude Range: Troposphere | Science Focus: Physics (physical properties and processes)
Analysis of ship emission effects on clouds over the southeastern Atlantic using geostationary satellite observations
Relationship between latent and radiative heating fields of tropical cloud systems using synergistic satellite observations
Shallow cloud variability in Houston, Texas, during the ESCAPE and TRACER field experiments
How does the lifetime of detrained cirrus impact the high-cloud radiative effect in the tropics?
Anvil–radiation diurnal interaction: shortwave radiative-heating destabilization driving the diurnal variation of convective anvil outflow and its modulation on the radiative cancellation
Impact of wildfire smoke on Arctic cirrus formation – Part 1: Analysis of MOSAiC 2019–2020 observations
A new aggregation and riming discrimination algorithm based on polarimetric weather radars
Study of optical scattering properties and direct radiative effects of high-altitude cirrus clouds in Barcelona, Spain, with 4 years of lidar measurements
Co-variability drives the inverted-V sensitivity between liquid water path and droplet concentrations
Lightning declines over shipping lanes following regulation of fuel sulfur emissions
Post-return stroke VHF electromagnetic activity in north-western Mediterranean cloud-to-ground lightning flashes
A machine learning-based perspective on deep convective clouds and their organisation in 3D. Part I: Influence of deep convective cores on the cloud life-cycle
A machine learning-based perspective on deep convective clouds and their organisation in 3D. Part II: Spatial-temporal patterns of convective organisation
Technical note: Applicability of physics-based and machine-learning-based algorithms of a geostationary satellite in retrieving the diurnal cycle of cloud base height
Observing convective activities in complex convective organizations and their contributions to precipitation and anvil cloud amounts
Weak liquid water path response in ship tracks
Multi-year precipitation characteristics based on in-situ and remote sensing observations at Ny-Ålesund, Svalbard
Air mass history linked to the development of Arctic mixed-phase clouds
Distinct structure, radiative effects, and precipitation characteristics of deep convection systems in the Tibetan Plateau compared to the tropical Indian Ocean
The correlation between Arctic sea ice, cloud phase and radiation using A-Train satellites
Technical note: Retrieval of the supercooled liquid fraction in mixed-phase clouds from Himawari-8 observations
Characterisation of low-base and mid-base clouds and their thermodynamic phase over the Southern Ocean and Arctic marine regions
A survey of radiative and physical properties of North Atlantic mesoscale cloud morphologies from multiple identification methodologies
Extensive coverage of ultrathin tropical tropopause layer cirrus clouds revealed by balloon-borne lidar observations
The effects of warm-air intrusions in the high Arctic on cirrus clouds
The characteristics of cloud macro-parameters caused by the seeder–feeder process inside clouds measured by millimeter-wave cloud radar in Xi'an, China
Shallow- and deep-convection characteristics in the greater Houston, Texas, area using cell tracking methodology
Observations of the macrophysical properties of cumulus cloud fields over the tropical western Pacific and their connection to meteorological variables
A Lagrangian perspective on the lifecycle and cloud radiative effect of deep convective clouds over Africa
Daytime variation in the aerosol indirect effect for warm marine boundary layer clouds in the eastern North Atlantic
Technical note: Bimodal parameterizations of in situ ice cloud particle size distributions
Inter-relations of precipitation, aerosols, and clouds over Andalusia, southern Spain, revealed by the Andalusian Global ObseRvatory of the Atmosphere (AGORA)
On the relationship between mesoscale cellular convection and meteorological forcing: comparing the Southern Ocean against the North Pacific
Aerosol-related effects on the occurrence of heterogeneous ice formation over Lauder, New Zealand ∕ Aotearoa
Low-level Arctic clouds: a blind zone in our knowledge of the radiation budget
Climatologically invariant scale invariance seen in distributions of cloud horizontal sizes
Variability and properties of liquid-dominated clouds over the ice-free and sea-ice-covered Arctic Ocean
Asymmetries in cloud microphysical properties ascribed to sea ice leads via water vapour transport in the central Arctic
Quantifying the dependence of drop spectrum width on cloud drop number concentration for cloud remote sensing
The evolution of deep convective systems and their associated cirrus outflows
Wildfire smoke triggers cirrus formation: lidar observations over the eastern Mediterranean
Rapid saturation of cloud water adjustments to shipping emissions
Sensitivities of cloud radiative effects to large-scale meteorology and aerosols from global observations
Distinct secondary ice production processes observed in radar Doppler spectra: insights from a case study
Investigating the development of clouds within marine cold-air outbreaks
Detection of large-scale cloud microphysical changes within a major shipping corridor after implementation of the International Maritime Organization 2020 fuel sulfur regulations
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Influence of cloud microphysics schemes on weather model predictions of heavy precipitation
Convective organization and 3D structure of tropical cloud systems deduced from synergistic A-Train observations and machine learning
Seasonal controls on isolated convective storm drafts, precipitation intensity, and life cycle as observed during GoAmazon2014/5
Nikos Benas, Jan Fokke Meirink, Rob Roebeling, and Martin Stengel
Atmos. Chem. Phys., 25, 6957–6973, https://doi.org/10.5194/acp-25-6957-2025, https://doi.org/10.5194/acp-25-6957-2025, 2025
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This study examines how ship emissions affect clouds over a shipping corridor in the southeastern Atlantic. Using satellite data from 2004 to 2023, we find that ship emissions increase the number of cloud droplets while reducing their size and slightly decrease cloud water content. Effects on seasonal and daily patterns vary based on regional factors. The impact of emissions weakened after stricter regulations were implemented in 2020.
Xiaoting Chen, Claudia J. Stubenrauch, and Giulio Mandorli
Atmos. Chem. Phys., 25, 6857–6880, https://doi.org/10.5194/acp-25-6857-2025, https://doi.org/10.5194/acp-25-6857-2025, 2025
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Strongly precipitating mesoscale convective systems produce a large amount of diabatic heating of the atmosphere, influencing atmospheric circulation. Their complete 3D description, attained by machine learning techniques in combination with satellite observations, has enabled a detailed study of the relationship between latent and radiative heating in these cloud systems. Convective organization increases both the average and the vertical gradient of radiative effects of the mesoscale convective systems.
Zackary Mages, Pavlos Kollias, Bernat Puigdomènech Treserras, Paloma Borque, and Mariko Oue
Atmos. Chem. Phys., 25, 6025–6045, https://doi.org/10.5194/acp-25-6025-2025, https://doi.org/10.5194/acp-25-6025-2025, 2025
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Convective clouds are a key component of the climate system. Using remote sensing observations during two field experiments in Houston, Texas, we identify four diurnal patterns of shallow convective clouds. We find areas more frequently experiencing shallow convective clouds, and we find areas where the vertical extent of shallow convective clouds is higher and where they are more likely to precipitate. This provides insight into the complicated environment that forms these clouds in Houston.
George Horner and Edward Gryspeerdt
Atmos. Chem. Phys., 25, 5617–5631, https://doi.org/10.5194/acp-25-5617-2025, https://doi.org/10.5194/acp-25-5617-2025, 2025
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This work tracks the life cycle of thin cirrus clouds that flow out of tropical convective storms. These cirrus clouds are found to have a warming effect on the atmosphere over their whole lifetime. Thin cirrus that originate from land origin convection warm more than those of ocean origin. Moreover, if the lifetime of these cirrus clouds increase, the warming they exert over their whole lifetime also increases. These results help us understand how these clouds might change in a future climate.
Zhenquan Wang
Atmos. Chem. Phys., 25, 5021–5039, https://doi.org/10.5194/acp-25-5021-2025, https://doi.org/10.5194/acp-25-5021-2025, 2025
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Convective anvil outflow directly driven by the shortwave radiative-heating destabilization is strong during the daytime, whereas the outflow contributed by the longwave radiative cooling through radiative destabilization and circulation is weak. This leads to the diurnal variation in the convection-producing anvil clouds, which in turn can influence the radiative energy budget.
Albert Ansmann, Cristofer Jimenez, Johanna Roschke, Johannes Bühl, Kevin Ohneiser, Ronny Engelmann, Martin Radenz, Hannes Griesche, Julian Hofer, Dietrich Althausen, Daniel A. Knopf, Sandro Dahlke, Tom Gaudek, Patric Seifert, and Ulla Wandinger
Atmos. Chem. Phys., 25, 4847–4866, https://doi.org/10.5194/acp-25-4847-2025, https://doi.org/10.5194/acp-25-4847-2025, 2025
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In this study, we focus on the potential impact of wildfire smoke on cirrus formation. For the first time, state-of-the-art aerosol and cirrus observations with lidar and radar, presented in this paper (Part 1 of a series of two articles), are closely linked to the comprehensive modeling of gravity-wave-induced ice nucleation in cirrus evolution processes, presented in a companion paper (Part 2). We found a clear impact of wildfire smoke on cirrus evolution.
Armin Blanke, Mathias Gergely, and Silke Trömel
Atmos. Chem. Phys., 25, 4167–4184, https://doi.org/10.5194/acp-25-4167-2025, https://doi.org/10.5194/acp-25-4167-2025, 2025
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The area-wide radar-based distinction between riming and aggregation is crucial for model microphysics and data assimilation. This study introduces a discrimination algorithm based on polarimetric radar networks only. Exploiting the unique opportunity to link fall velocities from Doppler spectra to polarimetric variables in an operational setting enables us to set up and evaluate a well-performing machine learning algorithm.
Cristina Gil-Díaz, Michäel Sicard, Odran Sourdeval, Athulya Saiprakash, Constantino Muñoz-Porcar, Adolfo Comerón, Alejandro Rodríguez-Gómez, and Daniel Camilo Fortunato dos Santos Oliveira
Atmos. Chem. Phys., 25, 3445–3464, https://doi.org/10.5194/acp-25-3445-2025, https://doi.org/10.5194/acp-25-3445-2025, 2025
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This study presents a comprehensive analysis of optical scattering properties and direct radiative effects of cirrus clouds based on 4 years of continuous ground-based lidar measurements with the Barcelona MPLNET lidar. A novel approach of the self-consistent scattering model for cirrus clouds is presented to determine their optical scattering properties at different wavelengths, and their direct radiative effects are calculated with the discrete ordinates method embedded in the ARTDECO package.
Tom Goren, Goutam Choudhury, Jan Kretzschmar, and Isabel McCoy
Atmos. Chem. Phys., 25, 3413–3423, https://doi.org/10.5194/acp-25-3413-2025, https://doi.org/10.5194/acp-25-3413-2025, 2025
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Many studies have identified an inverted-V relationship between the liquid water path (LWP) and droplet concentration (Nd), where LWP increases and then decreases with Nd. Using satellite observations and meteorological data, we demonstrate that the inverted V primarily reflects co-variability between LWP and Nd. We suggest taking a holistic approach that considers this co-variability when assessing the climatological sensitivity of LWP to anthropogenic aerosols.
Chris J. Wright, Joel A. Thornton, Lyatt Jaeglé, Yang Cao, Yannian Zhu, Jihu Liu, Randall Jones II, Robert Holzworth, Daniel Rosenfeld, Robert Wood, Peter Blossey, and Daehyun Kim
Atmos. Chem. Phys., 25, 2937–2946, https://doi.org/10.5194/acp-25-2937-2025, https://doi.org/10.5194/acp-25-2937-2025, 2025
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Aerosol particles influence clouds, which exert a large forcing on solar radiation and freshwater. To better understand the mechanisms by which aerosol influences thunderstorms, we look at the two busiest shipping lanes in the world, where recent regulations have reduced sulfur emissions by nearly an order of magnitude. We find that the reduction in emissions has been accompanied by a dramatic decrease in both lightning and the number of droplets in clouds over the shipping lanes.
Andrea Kolínská, Ivana Kolmašová, Eric Defer, Ondřej Santolík, and Stéphane Pédeboy
Atmos. Chem. Phys., 25, 1791–1803, https://doi.org/10.5194/acp-25-1791-2025, https://doi.org/10.5194/acp-25-1791-2025, 2025
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We contribute to understanding differences in lightning flashes of opposite polarity by explaining distinct in-cloud processes after return strokes. Using data from multiple sensors, including individual Lightning Mapping Array stations, we reveal that positive flashes sustain strong high-frequency radiation due to the recharging of their in-cloud leader; this is in contrast to negative flashes, for which this activity declines rapidly.
Sarah Brüning and Holger Tost
EGUsphere, https://doi.org/10.5194/egusphere-2025-374, https://doi.org/10.5194/egusphere-2025-374, 2025
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This study analyses the temporal variability and life-cycle of spatially organised convective clouds, frequently associated with severe weather. We derive the data from a machine learning-based 3D extrapolation of 2D satellite data. The results highlight the impact of convective organisation on horizontal and vertical cloud properties and a prolonged cloud life-cycle. Overall, our findings emphasise a more intense activity over land but enhanced seasonal changes over the ocean.
Sarah Brüning and Holger Tost
EGUsphere, https://doi.org/10.5194/egusphere-2025-376, https://doi.org/10.5194/egusphere-2025-376, 2025
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The connection between convective cloud organisation and severe weather demands a robust characterisation of hazardous clouds. This study sets on to investigate spatio-temporal patterns and regional hotspots of convective organisation using machine learning-based 3D data and combining different organisation indices. While limitations arise due to overlapping effects of isolated and clustered convection, we emphasise the impact of a surface-specific seasonality that depends on the hemisphere.
Mengyuan Wang, Min Min, Jun Li, Han Lin, Yongen Liang, Binlong Chen, Zhigang Yao, Na Xu, and Miao Zhang
Atmos. Chem. Phys., 24, 14239–14256, https://doi.org/10.5194/acp-24-14239-2024, https://doi.org/10.5194/acp-24-14239-2024, 2024
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Although machine learning technology is advanced in the field of satellite remote sensing, the physical inversion algorithm based on cloud base height can better capture the daily variation in the characteristics of the cloud base.
Zhenquan Wang and Jian Yuan
Atmos. Chem. Phys., 24, 13811–13831, https://doi.org/10.5194/acp-24-13811-2024, https://doi.org/10.5194/acp-24-13811-2024, 2024
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Tropical convection organizations are normally connected complexes of many convective activities. In this work, a novel variable-brightness-temperature segment tracking algorithm is established to partition the complex convective organizations into structural components of single cold cores for tracking separately. The duration, precipitation and anvil amount of the tracked organization segments have strong loglinear relationships with brightness temperature structures.
Anna Tippett, Edward Gryspeerdt, Peter Manshausen, Philip Stier, and Tristan W. P. Smith
Atmos. Chem. Phys., 24, 13269–13283, https://doi.org/10.5194/acp-24-13269-2024, https://doi.org/10.5194/acp-24-13269-2024, 2024
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Ship emissions can form artificially brightened clouds, known as ship tracks, and provide us with an opportunity to investigate how aerosols interact with clouds. Previous studies that used ship tracks suggest that clouds can experience large increases in the amount of water (LWP) from aerosols. Here, we show that there is a bias in previous research and that, when we account for this bias, the LWP response to aerosols is much weaker than previously reported.
Kerstin Ebell, Christian Buhren, Rosa Gierens, Giovanni Chellini, Melanie Lauer, Andreas Walbröl, Sandro Dahlke, Pavel Krobot, and Mario Mech
EGUsphere, https://doi.org/10.5194/egusphere-2024-3368, https://doi.org/10.5194/egusphere-2024-3368, 2024
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Ground-based observations of precipitation are rare in the Arctic. In 2017, additional precipitation measurements by a precipitation gauge, a laser disdrometer, and a micro rain radar were established at the Arctic station AWIPEV in Ny-Ålesund, Svalbard. We present statistics on precipitation amount, frequency, and type for the first years of data. Large-scale systems like atmospheric rivers and cyclones strongly contribute to precipitation and, in particular, to extreme precipitation events.
Rebecca J. Murray-Watson and Edward Gryspeerdt
Atmos. Chem. Phys., 24, 11115–11132, https://doi.org/10.5194/acp-24-11115-2024, https://doi.org/10.5194/acp-24-11115-2024, 2024
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The formation of mixed-phase clouds during marine cold-air outbreaks is not well understood. Our study, using satellite data and Lagrangian trajectories, reveals that the occurrence of these clouds depends on both time and temperature, influenced partly by the presence of biological ice-nucleating particles. This highlights the importance of comprehending local aerosol dynamics for precise modelling of cloud-phase transitions in the Arctic.
Yuxin Zhao, Jiming Li, Deyu Wen, Yarong Li, Yuan Wang, and Jianping Huang
Atmos. Chem. Phys., 24, 9435–9457, https://doi.org/10.5194/acp-24-9435-2024, https://doi.org/10.5194/acp-24-9435-2024, 2024
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This study identifies deep convection systems (DCSs), including deep convection cores and anvils, over the Tibetan Plateau (TP) and tropical Indian Ocean (TO). The DCSs over the TP are less frequent, showing narrower and thinner cores and anvils compared to those over the TO. TP DCSs show a stronger longwave cloud radiative effect at the surface and in the low-level atmosphere. Distinct aerosol–cloud–precipitation interaction is found in TP DCSs, probably due to the cold cloud bases.
Grégory V. Cesana, Olivia Pierpaoli, Matteo Ottaviani, Linh Vu, Zhonghai Jin, and Israel Silber
Atmos. Chem. Phys., 24, 7899–7909, https://doi.org/10.5194/acp-24-7899-2024, https://doi.org/10.5194/acp-24-7899-2024, 2024
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Better characterizing the relationship between sea ice and clouds is key to understanding Arctic climate because clouds and sea ice affect surface radiation and modulate Arctic surface warming. Our results indicate that Arctic liquid clouds robustly increase in response to sea ice decrease. This increase has a cooling effect on the surface because more solar radiation is reflected back to space, and it should contribute to dampening future Arctic surface warming.
Ziming Wang, Husi Letu, Huazhe Shang, and Luca Bugliaro
Atmos. Chem. Phys., 24, 7559–7574, https://doi.org/10.5194/acp-24-7559-2024, https://doi.org/10.5194/acp-24-7559-2024, 2024
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The supercooled liquid fraction (SLF) in mixed-phase clouds is retrieved for the first time using passive geostationary satellite observations based on differences in liquid droplet and ice particle radiative properties. The retrieved results are comparable to global distributions observed by active instruments, and the feasibility of the retrieval method to analyze the observed trends of the SLF has been validated.
Barbara Dietel, Odran Sourdeval, and Corinna Hoose
Atmos. Chem. Phys., 24, 7359–7383, https://doi.org/10.5194/acp-24-7359-2024, https://doi.org/10.5194/acp-24-7359-2024, 2024
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Uncertainty with respect to cloud phases over the Southern Ocean and Arctic marine regions leads to large uncertainties in the radiation budget of weather and climate models. This study investigates the phases of low-base and mid-base clouds using satellite-based remote sensing data. A comprehensive analysis of the correlation of cloud phase with various parameters, such as temperature, aerosols, sea ice, vertical and horizontal cloud extent, and cloud radiative effect, is presented.
Ryan Eastman, Isabel L. McCoy, Hauke Schulz, and Robert Wood
Atmos. Chem. Phys., 24, 6613–6634, https://doi.org/10.5194/acp-24-6613-2024, https://doi.org/10.5194/acp-24-6613-2024, 2024
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Cloud types are determined using machine learning image classifiers applied to satellite imagery for 1 year in the North Atlantic. This survey of these cloud types shows that the climate impact of a cloud scene is, in part, a function of cloud type. Each type displays a different mix of thick and thin cloud cover, with the fraction of thin cloud cover having the strongest impact on the clouds' radiative effect. Future studies must account for differing properties and processes among cloud types.
Thomas Lesigne, François Ravetta, Aurélien Podglajen, Vincent Mariage, and Jacques Pelon
Atmos. Chem. Phys., 24, 5935–5952, https://doi.org/10.5194/acp-24-5935-2024, https://doi.org/10.5194/acp-24-5935-2024, 2024
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Upper tropical clouds have a strong impact on Earth's climate but are challenging to observe. We report the first long-duration observations of tropical clouds from lidars flying on board stratospheric balloons. Comparisons with spaceborne observations reveal the enhanced sensitivity of balloon-borne lidar to optically thin cirrus. These clouds, which have a significant coverage and lie in the uppermost troposphere, are linked with the dehydration of air masses on their way to the stratosphere.
Georgios Dekoutsidis, Martin Wirth, and Silke Groß
Atmos. Chem. Phys., 24, 5971–5987, https://doi.org/10.5194/acp-24-5971-2024, https://doi.org/10.5194/acp-24-5971-2024, 2024
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For decades the earth's temperature has been rising. The Arctic regions are warming faster. Cirrus clouds can contribute to this phenomenon. During warm-air intrusions, air masses are transported into the Arctic from the mid-latitudes. The HALO-(AC)3 campaign took place to measure cirrus during intrusion events and under normal conditions. We study the two cloud types based on these measurements and find differences in their geometry, relative humidity distribution and vertical structure.
Huige Di and Yun Yuan
Atmos. Chem. Phys., 24, 5783–5801, https://doi.org/10.5194/acp-24-5783-2024, https://doi.org/10.5194/acp-24-5783-2024, 2024
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We observed the seeder–feeder process among double-layer clouds using a cloud radar and microwave radiometer. By defining the parameters of the seeding depth and seeding time of the upper cloud affecting the lower cloud, we find that the cloud particle terminal velocity is significantly enhanced during the seeder–feeder period, and the lower the height and thinner the thickness of the height difference between double-layer clouds, the lower the height and thicker the thickness of seeding depth.
Kristofer S. Tuftedal, Bernat Puigdomènech Treserras, Mariko Oue, and Pavlos Kollias
Atmos. Chem. Phys., 24, 5637–5657, https://doi.org/10.5194/acp-24-5637-2024, https://doi.org/10.5194/acp-24-5637-2024, 2024
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This study analyzed coastal convective cells from June through September 2018–2021. The cells were classified and their lifecycles were analyzed to better understand their characteristics. Features such as convective-core growth, for example, are shown. The study found differences in the initiation location of shallow convection and in the aerosol loading in deep convective environments. This work provides a foundation for future analyses of convection or other tracked events elsewhere.
Michie Vianca De Vera, Larry Di Girolamo, Guangyu Zhao, Robert M. Rauber, Stephen W. Nesbitt, and Greg M. McFarquhar
Atmos. Chem. Phys., 24, 5603–5623, https://doi.org/10.5194/acp-24-5603-2024, https://doi.org/10.5194/acp-24-5603-2024, 2024
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Tropical oceanic low clouds remain a dominant source of uncertainty in cloud feedback in climate models due to their macrophysical properties (fraction, size, height, shape, distribution) being misrepresented. High-resolution satellite imagery over the Philippine oceans is used here to characterize cumulus macrophysical properties and their relationship to meteorological variables. Such information can act as a benchmark for cloud models and can improve low-cloud generation in climate models.
William K. Jones, Martin Stengel, and Philip Stier
Atmos. Chem. Phys., 24, 5165–5180, https://doi.org/10.5194/acp-24-5165-2024, https://doi.org/10.5194/acp-24-5165-2024, 2024
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Storm clouds cover large areas of the tropics. These clouds both reflect incoming sunlight and trap heat from the atmosphere below, regulating the temperature of the tropics. Over land, storm clouds occur in the late afternoon and evening and so exist both during the daytime and at night. Changes in this timing could upset the balance of the respective cooling and heating effects of these clouds. We find that isolated storms have a larger effect on this balance than their small size suggests.
Shaoyue Qiu, Xue Zheng, David Painemal, Christopher R. Terai, and Xiaoli Zhou
Atmos. Chem. Phys., 24, 2913–2935, https://doi.org/10.5194/acp-24-2913-2024, https://doi.org/10.5194/acp-24-2913-2024, 2024
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The aerosol indirect effect (AIE) depends on cloud states, which exhibit significant diurnal variations in the northeastern Atlantic. Yet the AIE diurnal cycle remains poorly understood. Using satellite retrievals, we find a pronounced “U-shaped” diurnal variation in the AIE, which is contributed to by the transition of cloud states combined with the lagged cloud responses. This suggests that polar-orbiting satellites with overpass times at noon underestimate daytime mean values of the AIE.
Irene Bartolomé García, Odran Sourdeval, Reinhold Spang, and Martina Krämer
Atmos. Chem. Phys., 24, 1699–1716, https://doi.org/10.5194/acp-24-1699-2024, https://doi.org/10.5194/acp-24-1699-2024, 2024
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How many ice crystals of each size are in a cloud is a key parameter for the retrieval of cloud properties. The distribution of ice crystals is obtained from in situ measurements and used to create parameterizations that can be used when analyzing the remote-sensing data. Current parameterizations are based on data sets that do not include reliable measurements of small crystals, but in our study we use a data set that includes very small ice crystals to improve these parameterizations.
Wenyue Wang, Klemens Hocke, Leonardo Nania, Alberto Cazorla, Gloria Titos, Renaud Matthey, Lucas Alados-Arboledas, Agustín Millares, and Francisco Navas-Guzmán
Atmos. Chem. Phys., 24, 1571–1585, https://doi.org/10.5194/acp-24-1571-2024, https://doi.org/10.5194/acp-24-1571-2024, 2024
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The south-central interior of Andalusia experiences complex precipitation patterns as a result of the semi-arid Mediterranean climate and the influence of Saharan dust. This study monitored the inter-relations between aerosols, clouds, meteorological variables, and precipitation systems using ground-based remote sensing and in situ instruments.
Francisco Lang, Steven T. Siems, Yi Huang, Tahereh Alinejadtabrizi, and Luis Ackermann
Atmos. Chem. Phys., 24, 1451–1466, https://doi.org/10.5194/acp-24-1451-2024, https://doi.org/10.5194/acp-24-1451-2024, 2024
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Marine low-level clouds play a crucial role in the Earth's energy balance, trapping heat from the surface and reflecting sunlight back into space. These clouds are distinguishable by their large-scale spatial structures, primarily characterized as hexagonal patterns with either filled (closed) or empty (open) cells. Utilizing satellite observations, these two cloud type patterns have been categorized over the Southern Ocean and North Pacific Ocean through a pattern recognition program.
Julian Hofer, Patric Seifert, J. Ben Liley, Martin Radenz, Osamu Uchino, Isamu Morino, Tetsu Sakai, Tomohiro Nagai, and Albert Ansmann
Atmos. Chem. Phys., 24, 1265–1280, https://doi.org/10.5194/acp-24-1265-2024, https://doi.org/10.5194/acp-24-1265-2024, 2024
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An 11-year dataset of polarization lidar observations from Lauder, New Zealand / Aotearoa, was used to distinguish the thermodynamic phase of natural clouds. The cloud dataset was separated to assess the impact of air mass origin on the frequency of heterogeneous ice formation. Ice formation efficiency in clouds above Lauder was found to be lower than in the polluted Northern Hemisphere midlatitudes but higher than in very clean and pristine environments, such as Punta Arenas in southern Chile.
Hannes Jascha Griesche, Carola Barrientos-Velasco, Hartwig Deneke, Anja Hünerbein, Patric Seifert, and Andreas Macke
Atmos. Chem. Phys., 24, 597–612, https://doi.org/10.5194/acp-24-597-2024, https://doi.org/10.5194/acp-24-597-2024, 2024
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The Arctic is strongly affected by climate change and the role of clouds therein is not yet completely understood. Measurements from the Arctic expedition PS106 were used to simulate radiative fluxes with and without clouds at very low altitudes (below 165 m), and their radiative effect was calculated to be 54 Wm-2. The low heights of these clouds make them hard to observe. This study shows the importance of accurate measurements and simulations of clouds and gives suggestions for improvements.
Thomas D. DeWitt, Timothy J. Garrett, Karlie N. Rees, Corey Bois, Steven K. Krueger, and Nicolas Ferlay
Atmos. Chem. Phys., 24, 109–122, https://doi.org/10.5194/acp-24-109-2024, https://doi.org/10.5194/acp-24-109-2024, 2024
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Viewed from space, a defining feature of Earth's atmosphere is the wide spectrum of cloud sizes. A recent study predicted the distribution of cloud sizes, and this paper compares the prediction to observations. Although there is nuance in viewing perspective, we find robust agreement with theory across different climatological conditions, including land–ocean contrasts, time of year, or latitude, suggesting a minor role for Coriolis forces, aerosol loading, or surface temperature.
Marcus Klingebiel, André Ehrlich, Elena Ruiz-Donoso, Nils Risse, Imke Schirmacher, Evelyn Jäkel, Michael Schäfer, Kevin Wolf, Mario Mech, Manuel Moser, Christiane Voigt, and Manfred Wendisch
Atmos. Chem. Phys., 23, 15289–15304, https://doi.org/10.5194/acp-23-15289-2023, https://doi.org/10.5194/acp-23-15289-2023, 2023
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In this study we explain how we use aircraft measurements from two Arctic research campaigns to identify cloud properties (like droplet size) over sea-ice and ice-free ocean. To make sure that our measurements make sense, we compare them with other observations. Our results show, e.g., larger cloud droplets in early summer than in spring. Moreover, the cloud droplets are also larger over ice-free ocean than compared to sea ice. In the future, our data can be used to improve climate models.
Pablo Saavedra Garfias, Heike Kalesse-Los, Luisa von Albedyll, Hannes Griesche, and Gunnar Spreen
Atmos. Chem. Phys., 23, 14521–14546, https://doi.org/10.5194/acp-23-14521-2023, https://doi.org/10.5194/acp-23-14521-2023, 2023
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An important Arctic climate process is the release of heat fluxes from sea ice openings to the atmosphere that influence the clouds. The characterization of this process is the objective of this study. Using synergistic observations from the MOSAiC expedition, we found that single-layer cloud properties show significant differences when clouds are coupled or decoupled to the water vapour transport which is used as physical link between the upwind sea ice openings and the cloud under observation.
Matthew D. Lebsock and Mikael Witte
Atmos. Chem. Phys., 23, 14293–14305, https://doi.org/10.5194/acp-23-14293-2023, https://doi.org/10.5194/acp-23-14293-2023, 2023
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This paper evaluates measurements of cloud drop size distributions made from airplanes. We find that as the number of cloud drops increases the distribution of the cloud drop sizes narrows. The data are used to develop a simple equation that relates the drop number to the width of the drop sizes. We then use this equation to demonstrate that existing approaches to observe the drop number from satellites contain errors that can be corrected by including the new relationship.
George Horner and Edward Gryspeerdt
Atmos. Chem. Phys., 23, 14239–14253, https://doi.org/10.5194/acp-23-14239-2023, https://doi.org/10.5194/acp-23-14239-2023, 2023
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Tropical deep convective clouds, and the thin cirrus (ice) clouds that flow out from them, are important for modulating the energy budget of the tropical atmosphere. This work uses a new method to track the evolution of the properties of these clouds across their entire lifetimes. We find these clouds cool the atmosphere in the first 6 h before switching to a warming regime after the deep convective core has dissipated, which is sustained beyond 120 h from the initial convective event.
Rodanthi-Elisavet Mamouri, Albert Ansmann, Kevin Ohneiser, Daniel A. Knopf, Argyro Nisantzi, Johannes Bühl, Ronny Engelmann, Annett Skupin, Patric Seifert, Holger Baars, Dragos Ene, Ulla Wandinger, and Diofantos Hadjimitsis
Atmos. Chem. Phys., 23, 14097–14114, https://doi.org/10.5194/acp-23-14097-2023, https://doi.org/10.5194/acp-23-14097-2023, 2023
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For the first time, rather clear evidence is found that wildfire smoke particles can trigger strong cirrus formation. This finding is of importance because intensive and large wildfires may occur increasingly often in the future as climate change proceeds. Based on lidar observations in Cyprus in autumn 2020, we provide detailed insight into the cirrus formation at the tropopause in the presence of aged wildfire smoke (here, 8–9 day old Californian wildfire smoke).
Peter Manshausen, Duncan Watson-Parris, Matthew W. Christensen, Jukka-Pekka Jalkanen, and Philip Stier
Atmos. Chem. Phys., 23, 12545–12555, https://doi.org/10.5194/acp-23-12545-2023, https://doi.org/10.5194/acp-23-12545-2023, 2023
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Aerosol from burning fuel changes cloud properties, e.g., the number of droplets and the content of water. Here, we study how clouds respond to different amounts of shipping aerosol. Droplet numbers increase linearly with increasing aerosol over a broad range until they stop increasing, while the amount of liquid water always increases, independently of emission amount. These changes in cloud properties can make them reflect more or less sunlight, which is important for the earth's climate.
Hendrik Andersen, Jan Cermak, Alyson Douglas, Timothy A. Myers, Peer Nowack, Philip Stier, Casey J. Wall, and Sarah Wilson Kemsley
Atmos. Chem. Phys., 23, 10775–10794, https://doi.org/10.5194/acp-23-10775-2023, https://doi.org/10.5194/acp-23-10775-2023, 2023
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This study uses an observation-based cloud-controlling factor framework to study near-global sensitivities of cloud radiative effects to a large number of meteorological and aerosol controls. We present near-global sensitivity patterns to selected thermodynamic, dynamic, and aerosol factors and discuss the physical mechanisms underlying the derived sensitivities. Our study hopes to guide future analyses aimed at constraining cloud feedbacks and aerosol–cloud interactions.
Anne-Claire Billault-Roux, Paraskevi Georgakaki, Josué Gehring, Louis Jaffeux, Alfons Schwarzenboeck, Pierre Coutris, Athanasios Nenes, and Alexis Berne
Atmos. Chem. Phys., 23, 10207–10234, https://doi.org/10.5194/acp-23-10207-2023, https://doi.org/10.5194/acp-23-10207-2023, 2023
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Secondary ice production plays a key role in clouds and precipitation. In this study, we analyze radar measurements from a snowfall event in the Jura Mountains. Complex signatures are observed, which reveal that ice crystals were formed through various processes. An analysis of multi-sensor data suggests that distinct ice multiplication processes were taking place. Both the methods used and the insights gained through this case study contribute to a better understanding of snowfall microphysics.
Rebecca J. Murray-Watson, Edward Gryspeerdt, and Tom Goren
Atmos. Chem. Phys., 23, 9365–9383, https://doi.org/10.5194/acp-23-9365-2023, https://doi.org/10.5194/acp-23-9365-2023, 2023
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Clouds formed in Arctic marine cold air outbreaks undergo a distinct evolution, but the factors controlling their transition from high-coverage to broken cloud fields are poorly understood. We use satellite and reanalysis data to study how these clouds develop in time and the different influences on their evolution. The aerosol concentration is correlated with cloud break-up; more aerosol is linked to prolonged coverage and a stronger cooling effect, with implications for a more polluted Arctic.
Michael S. Diamond
Atmos. Chem. Phys., 23, 8259–8269, https://doi.org/10.5194/acp-23-8259-2023, https://doi.org/10.5194/acp-23-8259-2023, 2023
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Fuel sulfur regulations were implemented for ships in 2020 to improve air quality but may also accelerate global warming. We use spatial statistics and satellite retrievals to detect changes in the size of cloud droplets and find evidence for a resulting decrease in cloud brightness within a major shipping corridor after the sulfur limits went into effect. Our results confirm both that the regulations are being followed and that they are having a warming influence via their effect on clouds.
Hao Luo, Johannes Quaas, and Yong Han
Atmos. Chem. Phys., 23, 8169–8186, https://doi.org/10.5194/acp-23-8169-2023, https://doi.org/10.5194/acp-23-8169-2023, 2023
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Clouds exhibit a wide range of vertical structures with varying microphysical and radiative properties. We show a global survey of spatial distribution, vertical extent and radiative effect of various classified cloud vertical structures using joint satellite observations from the new CCCM datasets during 2007–2010. Moreover, the long-term trends in CVSs are investigated based on different CMIP6 future scenarios to capture the cloud variations with different, increasing anthropogenic forcings.
Gregor Köcher, Tobias Zinner, and Christoph Knote
Atmos. Chem. Phys., 23, 6255–6269, https://doi.org/10.5194/acp-23-6255-2023, https://doi.org/10.5194/acp-23-6255-2023, 2023
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Polarimetric radar observations of 30 d of convective precipitation events are used to statistically analyze 5 state-of-the-art microphysics schemes of varying complexity. The frequency and area of simulated heavy-precipitation events are in some cases significantly different from those observed, depending on the microphysics scheme. Analysis of simulated particle size distributions and reflectivities shows that some schemes have problems reproducing the correct particle size distributions.
Claudia J. Stubenrauch, Giulio Mandorli, and Elisabeth Lemaitre
Atmos. Chem. Phys., 23, 5867–5884, https://doi.org/10.5194/acp-23-5867-2023, https://doi.org/10.5194/acp-23-5867-2023, 2023
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Organized convection leads to large convective cloud systems and intense rain and may change with a warming climate. Their complete 3D description, attained by machine learning techniques in combination with various satellite observations, together with a cloud system concept, link convection to anvil properties, while convective organization can be identified by the horizontal structure of intense rain.
Scott E. Giangrande, Thiago S. Biscaro, and John M. Peters
Atmos. Chem. Phys., 23, 5297–5316, https://doi.org/10.5194/acp-23-5297-2023, https://doi.org/10.5194/acp-23-5297-2023, 2023
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Our study tracks thunderstorms observed during the wet and dry seasons of the Amazon Basin using weather radar. We couple this precipitation tracking with opportunistic overpasses of a wind profiler and other ground observations to add unique insights into the upwards and downwards air motions within these clouds at various stages in the storm life cycle. The results of a simple updraft model are provided to give physical explanations for observed seasonal differences.
Cited articles
Abel, S. J. and Shipway, B. J.: A comparison of cloud-resolving model
simulations of trade wind cumulus with aircraft observations taken during
RICO, Q. J. Roy. Meteor. Soc., 133, 781–794, https://doi.org/10.1002/qj.55, 2007. a
Albrecht, B. A.: Aerosols, Cloud Microphysics, and Fractional Cloudiness,
Science, 245, 1227–1230, https://doi.org/10.1126/science.245.4923.1227, 1989. a, b, c
Austin, R. T., Heymsfield, A. J., and Stephens, G. L.: Retrieval of ice cloud
microphysical parameters using the CloudSat millimeter-wave radar and
temperature, J. Geophys. Res.-Atmos., 114, D00A23, https://doi.org/10.1029/2008JD010049, 2009. a
Bailey, A., Nusbaumer, J., and Noone, D.: Precipitation efficiency derived from isotope ratios in water vapor distinguishes dynamical and microphysical
influences on subtropical atmospheric constituents, J. Geophys. Res.-Atmos., 120, 9119–9137, https://doi.org/10.1002/2015JD023403, 2015. a, b
Battaglia, A., Kollias, P., Dhillon, R., Lamer, K., Khairoutdinov, M., and Watters, D.: Mind the gap – Part 2: Improving quantitative estimates of cloud and rain water path in oceanic warm rain using spaceborne radars, Atmos. Meas. Tech., 13, 4865–4883, https://doi.org/10.5194/amt-13-4865-2020, 2020. a
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
Blyth, A. M., Lowenstein, J. H., Huang, Y., Cui, Z., Davies, S., and Carslaw,
K. S.: The production of warm rain in shallow maritime cumulus clouds,
Q. J. Roy. Meteor. Soc., 139, 20–31, https://doi.org/10.1002/qj.1972, 2013. a
Bony, S. and Dufresne, J.-L.: Marine boundary layer clouds at the heart of
tropical cloud feedback uncertainties in climate models,
Geophys. Res. Lett., 32, L20806, https://doi.org/10.1029/2005GL023851, 2005. a
Boutle, I. A., Abel, S. J., Hill, P. G., and Morcrette, C. J.: Spatial
variability of liquid cloud and rain: observations and microphysical effects,
Q. J. Roy. Meteor. Soc., 140, 583–594,
https://doi.org/10.1002/qj.2140, 2014. a
Brenguier, J.-L. and Chaumat, L.: Droplet Spectra Broadening in Cumulus
Clouds, Part I: Broadening in Adiabatic Cores, J. Atmos. Sci., 58, 628–641,
https://doi.org/10.1175/1520-0469(2001)058<0628:DSBICC>2.0.CO;2, 2001. a
Bretherton, C. S., McCaa, J. R., and Grenier, H.: A New Parameterization for
Shallow Cumulus Convection and Its Application to Marine Subtropical
Cloud-Topped Boundary Layers, Part I: Description and 1D Results,
Mon. Weather Rev., 132, 864–882,
https://doi.org/10.1175/1520-0493(2004)132<0864:ANPFSC>2.0.CO;2, 2004. a
Burnet, F. and Brenguier, J.-L.: The onset of precipitation in warm cumulus
clouds: An observational case-study, Q. J. Roy. Meteor. Soc., 136, 374–381, https://doi.org/10.1002/qj.552, 2010. a, b, c, d
Chen, B. and Liu, C.: Warm Organized Rain Systems over the Tropical Eastern
Pacific, J. Climate, 29, 3403–3422, https://doi.org/10.1175/jcli-d-15-0177.1, 2016. a
Chen, S., Yau, M. K., and Bartello, P.: Turbulence Effects of Collision
Efficiency and Broadening of Droplet Size Distribution in Cumulus Clouds, J. Atmos. Sci., 75, 203–217, https://doi.org/10.1175/JAS-D-17-0123.1, 2018. a
Cho, H.-M., Zhang, Z., Meyer, K., Lebsock, M., Platnick, S., Ackerman, A. S.,
Di Girolamo, L., C.-Labonnote, L., Cornet, C., Riedi, J., and Holz, R. E.:
Frequency and causes of failed MODIS cloud property retrievals for liquid
phase clouds over global oceans, J. Geophys. Res.-Atmos., 120, 4132–4154, https://doi.org/10.1002/2015JD023161, 2015. a
Chong, M. and Hauser, D.: A Tropical Squall Line Observed during the COPT 81
Experiment in West Africa, Part II: Water Budget, Mon. Weather Rev.,
117, 728–744, https://doi.org/10.1175/1520-0493(1989)117<0728:ATSLOD>2.0.CO;2, 1989. a
Christensen, M. W., Stephens, G. L., and Lebsock, M. D.: Exposing biases in
retrieved low cloud properties from CloudSat: A guide for evaluating
observations and climate data, J. Geophys. Res.-Atmos.,
118, 12120–12131, https://doi.org/10.1002/2013JD020224, 2013. a
Dagan, G., Koren, I., Altaratz, O., and Heiblum, R. H.: Aerosol effect on the
evolution of the thermodynamic properties of warm convective cloud fields,
Sci. Rep.-UK, 6, 38769, https://doi.org/10.1038/srep38769, 2016. a
Del Genio, A. D., Kovari, W., Yao, M.-S., and Jonas, J.: Cumulus Microphysics
and Climate Sensitivity, J. Climate, 18, 2376–2387,
https://doi.org/10.1175/JCLI3413.1, 2005. a
de Rooy, W. C., Bechtold, P., Fröhlich, K., Hohenegger, C., Jonker, H.,
Mironov, D., Pier Siebesma, A., Teixeira, J., and Yano, J.-I.: Entrainment
and detrainment in cumulus convection: an overview, Q. J. Roy. Meteor. Soc., 139, 1–19, https://doi.org/10.1002/qj.1959, 2013. a, b
Dufresne, J.-L. and Bony, S.: An Assessment of the Primary Sources of Spread of Global Warming Estimates from Coupled Atmosphere–Ocean Models, J. Climate, 21, 5135–5144, https://doi.org/10.1175/2008JCLI2239.1, 2008. a
Franklin, C. N.: The effects of turbulent collision–coalescence on precipitation formation and precipitation-dynamical feedbacks in simulations of stratocumulus and shallow cumulus convection, Atmos. Chem. Phys., 14, 6557–6570, https://doi.org/10.5194/acp-14-6557-2014, 2014. a, b
Gao, W., Liu, L., Li, J., and Lu, C.: The Microphysical Properties of
Convective Precipitation Over the Tibetan Plateau by a Subkilometer
Resolution Cloud-Resolving Simulation, J. Geophys. Res.-Atmos., 123, 3212–3227, https://doi.org/10.1002/2017JD027812,
2018. a
Gerber, H. E., Frick, G. M., Jensen, J. B., and Hudson, J. G.: Entrainment,
Mixing, and Microphysics in Trade-Wind Cumulus,
J. Meteorol. Soc. Jpn., 86A, 87–106, https://doi.org/10.2151/jmsj.86A.87, 2008. a, b
Haynes, J. M., Lecuyer, T. S., Stephens, G. L., Miller, S. D., Mitrescu, C.,
Wood, N. B., and Tanelli, S.: Rainfall retrieval over the ocean with
spaceborne W-band radar, J. Geophys. Res., 114, D00A22,
https://doi.org/10.1029/2008jd009973, 2009. a, b, c
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
Hoffmann, F., Noh, Y., and Raasch, S.: The Route to Raindrop Formation in a
Shallow Cumulus Cloud Simulated by a Lagrangian Cloud Model, J. Atmos. Sci., 74, 2125–2142, https://doi.org/10.1175/JAS-D-16-0220.1, 2017. a
Jiang, H. and Feingold, G.: Effect of aerosol on warm convective clouds:
Aerosol-cloud-surface flux feedbacks in a new coupled large eddy model,
J. Geophys. Res.-Atmos., 111, D01202, https://doi.org/10.1029/2005JD006138, 2006. a
Jolivet, D. and Feijt, A. J.: Quantification of the accuracy of liquid water
path fields derived from NOAA 16 advanced very high resolution radiometer
over three ground stations using microwave radiometers, J. Geophys. Res.-Atmos., 110, D11204, https://doi.org/10.1029/2004JD005205, 2005. a
Jung, E., Albrecht, B. A., Feingold, G., Jonsson, H. H., Chuang, P., and Donaher, S. L.: Aerosols, clouds, and precipitation in the North Atlantic trades observed during the Barbados aerosol cloud experiment – Part 1: Distributions and variability, Atmos. Chem. Phys., 16, 8643–8666, https://doi.org/10.5194/acp-16-8643-2016, 2016a. a
Jung, E., Albrecht, B. A., Sorooshian, A., Zuidema, P., and Jonsson, H. H.: Precipitation susceptibility in marine stratocumulus and shallow cumulus from airborne measurements, Atmos. Chem. Phys., 16, 11395–11413, https://doi.org/10.5194/acp-16-11395-2016, 2016b. a, b
Klein, S. A. and Hartmann, D. L.: The Seasonal Cycle of Low Stratiform Clouds, J. Climate, 6, 1587–1606,
https://doi.org/10.1175/1520-0442(1993)006<1587:TSCOLS>2.0.CO;2, 1993. a
Kollias, P., Albrecht, B. A., and Marks Jr., F. D.: Cloud radar observations of vertical drafts and microphysics in convective rain, J. Geophys. Res.-Atmos., 108, 4053, https://doi.org/10.1029/2001JD002033, 2003. a
Koren, I., Dagan, G., and Altaratz, O.: From aerosol-limited to invigoration of warm convective clouds, Science, 344, 1143–1146,
https://doi.org/10.1126/science.1252595, 2014. a, b
Korolev, A., Khain, A., Pinsky, M., and French, J.: Theoretical study of mixing in liquid clouds – Part 1: Classical concepts, Atmos. Chem. Phys., 16, 9235–9254, https://doi.org/10.5194/acp-16-9235-2016, 2016. a
Lamer, K., Kollias, P., Battaglia, A., and Preval, S.: Mind the gap – Part 1: Accurately locating warm marine boundary layer clouds and precipitation using spaceborne radars, Atmos. Meas. Tech., 13, 2363–2379, https://doi.org/10.5194/amt-13-2363-2020, 2020. a
Lebsock, M. D.: Level 2C RAIN-PROFILE Product Process Description and Interface
Control Document, Tech. Rep. D-20308, Jet Propulsion Laboratory, California
Institute of Technology, Pasadena, California, USA, 2018. a
Lebsock, M. D. and L'Ecuyer, T. S.: The retrieval of warm rain from CloudSat,
J. Geophys. Res.-Atmos., 116, D20209, https://doi.org/10.1029/2011JD016076, 2011. a, b, c
Lebsock, M. D. and Su, H.: Application of active spaceborne remote sensing for
understanding biases between passive cloud water path retrievals, J. Geophys. Res.-Atmos., 119, 8962–8979, https://doi.org/10.1002/2014JD021568, 2014. a
Lebsock, M. D., L'Ecuyer, T. S., and Stephens, G. L.: Detecting the Ratio of
Rain and Cloud Water in Low-Latitude Shallow Marine Clouds,
J. Appl. Meteorol. Clim., 50, 419–432, https://doi.org/10.1175/2010JAMC2494.1, 2011. a, b, c
Lebsock, M. D., Morrison, H., and Gettelman, A.: Microphysical implications of
cloud-precipitation covariance derived from satellite remote sensing, J. Geophys. Res.-Atmos., 118, 6521–6533, https://doi.org/10.1002/jgrd.50347, 2013. a
L'Ecuyer, T. S. and Stephens, G. L.: An Estimation-Based Precipitation
Retrieval Algorithm for Attenuating Radars, J. Appl. Meteorol.,
41, 272–285, https://doi.org/10.1175/1520-0450(2002)041<0272:AEBPRA>2.0.CO;2, 2002. a
Lee, H. and Baik, J.-J.: A Physically Based Autoconversion Parameterization, J. Atmos. Sci., 74, 1599–1616, https://doi.org/10.1175/JAS-D-16-0207.1, 2017. a
Li, X., Sui, C.-H., and Lau, K.-M.: Precipitation Efficiency in the Tropical
Deep Convective Regime: A 2D Cloud Resolving Modeling Study, J. Meteorol. Soc. Jpn., 80, 205–212, https://doi.org/10.2151/jmsj.80.205, 2002. a
Lim, K.-S. S. and Hong, S.-Y.: Development of an Effective Double-Moment Cloud Microphysics Scheme with Prognostic Cloud Condensation Nuclei (CCN) for
Weather and Climate Models, Mon. Weather Rev., 138, 1587–1612,
https://doi.org/10.1175/2009MWR2968.1, 2010. a
Liu, J. and Li, Z.: Significant Underestimation in the Optically Based
Estimation of the Aerosol First Indirect Effect Induced by the Aerosol
Swelling Effect, Geophys. Res. Lett., 45, 5690–5699,
https://doi.org/10.1029/2018GL077679, 2018. a, b
Liu, Y. and Daum, P. H.: Parameterization of the Autoconversion Process, Part I: Analytical Formulation of the Kessler-Type Parameterizations, J. Atmos. Sci., 61, 1539–1548, https://doi.org/10.1175/1520-0469(2004)061<1539:POTAPI>2.0.CO;2, 2004. a
Lohmann, U. and Roeckner, E.: Design and performance of a new cloud
microphysics scheme developed for the ECHAM general circulation
model, Clim. Dynam., 12, 557–572, https://doi.org/10.1007/BF00207939, 1996. a
Lu, C., Liu, Y., Niu, S., and Vogelmann, A. M.: Lateral entrainment rate in
shallow cumuli: Dependence on dry air sources and probability density
functions, Geophys. Res. Lett., 39, L20812, https://doi.org/10.1029/2012GL053646,
2012. a
Lutsko, N. J. and Cronin, T. W.: Increase in Precipitation Efficiency With
Surface Warming in Radiative-Convective Equilibrium,
J. Adv. Model. Earth Sy., 10, 2992–3010, https://doi.org/10.1029/2018MS001482, 2018. a, b, c
Marchand, R., Mace, G. G., Ackerman, T., and Stephens, G.: Hydrometeor
Detection Using Cloudsat – An Earth-Orbiting 94 GHz Cloud Radar,
J. Atmos. Ocean. Tech., 25, 519–533, https://doi.org/10.1175/2007JTECHA1006.1, 2008. a, b, c
Medeiros, B. and Stevens, B.: Revealing differences in GCM representations of
low clouds, Clim. Dynam., 36, 385–399, https://doi.org/10.1007/s00382-009-0694-5,
2011. a
Michel Flores, J., Bar-Or, R. Z., Bluvshtein, N., Abo-Riziq, A., Kostinski, A., Borrmann, S., Koren, I., Koren, I., and Rudich, Y.: Absorbing aerosols at high relative humidity: linking hygroscopic growth to optical properties, Atmos. Chem. Phys., 12, 5511–5521, https://doi.org/10.5194/acp-12-5511-2012, 2012. a
Mieslinger, T., Horvath, A., Buehler, S. A., and Sakradzija, M.: The Dependence of Shallow Cumulus Macrophysical Properties on Large-Scale Meteorology as Observed in ASTER Imagery, J. Geophys. Res.-Atmos., 124,
11477–11505, https://doi.org/10.1029/2019JD030768, 2019. a
Minor, H. A., Rauber, R. M., Göke, S., and Di Girolamo, L.: Trade Wind Cloud
Evolution Observed by Polarization Radar: Relationship to Giant Condensation
Nuclei Concentrations and Cloud Organization, J. Atmos. Sci., 68, 1075–1096, https://doi.org/10.1175/2010JAS3675.1, 2011. a
Mitrescu, C., L'Ecuyer, T., Haynes, J., Miller, S., and Turk, J.: CloudSat
Precipitation Profiling Algorithm–Model Description, J. Appl. Meteorol. Clim., 49, 991–1003, https://doi.org/10.1175/2009JAMC2181.1, 2010. a
Morrison, H., Curry, J. A., and Khvorostyanov, V. I.: A New Double-Moment
Microphysics Parameterization for Application in Cloud and Climate Models,
Part I: Description, J. Atmos. Sci., 62, 1665–1677, https://doi.org/10.1175/JAS3446.1, 2005. a
Moser, D. H. and Lasher-Trapp, S.: The Influence of Successive Thermals on
Entrainment and Dilution in a Simulated Cumulus Congestus, J. Atmos. Sci., 74, 375–392, https://doi.org/10.1175/JAS-D-16-0144.1, 2017. a, b, c, d
Nam, C., Bony, S., Dufresne, J.-L., and Chepfer, H.: The “too few, too
bright” tropical low-cloud problem in CMIP5 models, Geophys. Res. Lett., 39, L21801, https://doi.org/10.1029/2012GL053421, 2012. a, b
Neubauer, D., Christensen, M. W., Poulsen, C. A., and Lohmann, U.: Unveiling aerosol–cloud interactions – Part 2: Minimising the effects of aerosol swelling and wet scavenging in ECHAM6-HAM2 for comparison to satellite data, Atmos. Chem. Phys., 17, 13165–13185, https://doi.org/10.5194/acp-17-13165-2017, 2017. a
Pinsky, M., Khain, A., and Korolev, A.: Theoretical analysis of mixing in liquid clouds – Part 3: Inhomogeneous mixing, Atmos. Chem. Phys., 16, 9273–9297, https://doi.org/10.5194/acp-16-9273-2016, 2016a. a
Pinsky, M., Khain, A., Korolev, A., and Magaritz-Ronen, L.: Theoretical investigation of mixing in warm clouds – Part 2: Homogeneous mixing, Atmos. Chem. Phys., 16, 9255–9272, https://doi.org/10.5194/acp-16-9255-2016, 2016b. a
Platnick, S. and Valero, F. P. J.: A Validation of a Satellite Cloud Retrieval during ASTEX, J. Atmos. Sci., 52, 2985–3001,
https://doi.org/10.1175/1520-0469(1995)052<2985:AVOASC>2.0.CO;2, 1995. a
Platnick, S., King, M. D., Ackerman, S. A., Menzel, W. P., Baum,
B. A., Riedi, J. C., and Frey, R. A.: The MODIS cloud products:
algorithms and examples from Terra, IEEE T. Geosci. Remote, 41, 459–473, 2003. a
Rauber, R. M., Stevens, B., Ochs, H. T., Knight, C., Albrecht, B. A., Blyth,
A. M., Fairall, C. W., Jensen, J. B., Lasher-Trapp, S. G., Mayol-Bracero,
O. L., Vali, G., Anderson, J. R., Baker, B. A., Bandy, A. R., Burnet, E.,
Brenguier, J.-L., Brewer, W. A., Brown, P. R. A., Chuang, R., Cotton, W. R.,
Girolamo, L. D., Geerts, B., Gerber, H., Göke, S., Gomes, L., Heikes,
B. G., Hudson, J. G., Kollias, P., Lawson, R. R., Krueger, S. K., Lenschow,
D. H., Nuijens, L., O'Sullivan, D. W., Rilling, R. A.,
Rogers, D. C., Siebesma, A. P., Snodgrass, E., Stith, J. L., Thornton, D. C.,
Tucker, S., Twohy, C. H., and Zuidema, P.: Rain in Shallow Cumulus Over the
Ocean: The RICO Campaign, B. Am. Meteorol. Soc.,
88, 1912–1928, https://doi.org/10.1175/bams-88-12-1912, 2007. a, b
Rennó, N. O., Emanuel, K. A., and Stone, P. H.: Radiative-convective model
with an explicit hydrologic cycle: 1. Formulation and sensitivity to model
parameters, J. Geophys. Res.-Atmos., 99,
14429–14441, https://doi.org/10.1029/94JD00020, 1994. a
Romps, D. M.: An Analytical Model for Tropical Relative Humidity, J. Climate, 27, 7432–7449, https://doi.org/10.1175/JCLI-D-14-00255.1, 2014. a
Ruiz-Arias, J. A., Dudhia, J., Gueymard, C. A., and Pozo-Vázquez, D.: Assessment of the Level-3 MODIS daily aerosol optical depth in the context of surface solar radiation and numerical weather modeling, Atmos. Chem. Phys., 13, 675–692, https://doi.org/10.5194/acp-13-675-2013, 2013. a
Saleeby, S. M., Herbener, S. R., van den Heever, S. C., and L'Ecuyer, T.:
Impacts of Cloud Droplet–Nucleating Aerosols on Shallow Tropical
Convection, J. Atmos. Sci., 72, 1369–1385,
https://doi.org/10.1175/JAS-D-14-0153.1, 2015. a, b
Schmeissner, T., Shaw, R. A., Ditas, J., Stratmann, F., Wendisch, M., and
Siebert, H.: Turbulent Mixing in Shallow Trade Wind Cumuli: Dependence on
Cloud Life Cycle, J. Atmos. Sci., 72, 1447–1465,
https://doi.org/10.1175/jas-d-14-0230.1, 2015. a, b
Seethala, C. and Horvath, A.: Global assessment of AMSR-E and MODIS cloud
liquid water path retrievals in warm oceanic clouds, J. Geophys. Res.-Atmos., 115, D13202, https://doi.org/10.1029/2009JD012662, 2010. a, b
Seifert, A. and Onishi, R.: Turbulence effects on warm-rain formation in precipitating shallow convection revisited, Atmos. Chem. Phys., 16, 12127–12141, https://doi.org/10.5194/acp-16-12127-2016, 2016. a
Seifert, A., Nuijens, L., and Stevens, B.: Turbulence effects on warm-rain
autoconversion in precipitating shallow convection, Q. J. Roy. Meteor. Soc., 136, 1753–1762, https://doi.org/10.1002/qj.684, 2010. a, b
Short, D. A. and Nakamura, K.: TRMM Radar Observations of Shallow Precipitation
over the Tropical Oceans, J. Climate, 13, 4107–4124,
https://doi.org/10.1175/1520-0442(2000)013<4107:TROOSP>2.0.CO;2, 2000. a
Squires, P.: The Microstructure and Colloidal Stability of Warm Clouds, Tellus, 10, 256–261, https://doi.org/10.1111/j.2153-3490.1958.tb02011.x, 1958. a
Stevens, D. E., Ackerman, A. S., and Bretherton, C. S.: Effects of domain size and numerical resolution on the simulation of shallow cumulus convection, J. Atmos. Sci., 59, 3285–3301,
https://doi.org/10.1175/1520-0469(2002)059<3285:EODSAN>2.0.CO;2, 2002. a
Su, W., Schuster, G. L., Loeb, N. G., Rogers, R. R., Ferrare, R. A., Hostetler, C. A., Hair, J. W., and Obland, M. D.: Aerosol and cloud interaction observed from high spectral resolution lidar data, J. Geophys. Res.-Atmos., 113, D24202, https://doi.org/10.1029/2008JD010588, 2008. a
Sui, C.-H., Li, X., Yang, M.-J., and Huang, H.-L.: Estimation of
Oceanic Precipitation Efficiency in Cloud
Models, J. Atmos. Sci., 62, 4358–4370, https://doi.org/10.1175/JAS3587.1, 2005. a, b
Sui, C.-H., Li, X., and Yang, M.-J.: On the Definition of Precipitation
Efficiency, J. Atmos. Sci., 64, 4506–4513,
https://doi.org/10.1175/2007JAS2332.1, 2007. a, b
Tanelli, S., Durden, S. L., Im, E., Pak, K. S., Reinke, D. G.,
Partain, P., Haynes, J. M., and Marchand, R. T.: CloudSat's Cloud
Profiling Radar After Two Years in Orbit: Performance, Calibration, and
Processing, IEEE T. Geosci. Remote, 46,
3560–3573, https://doi.org/10.1109/TGRS.2008.2002030, 2008. a
Tao, W.-K., Johnson, D., Shie, C.-L., and Simpson, J.: The Atmospheric Energy Budget and Large-Scale Precipitation Efficiency of Convective Systems during TOGA COARE, GATE, SCSMEX, and ARM: Cloud-Resolving Model Simulations, J. Atmos. Sci., 61, 2405–2423,
https://doi.org/10.1175/1520-0469(2004)061<2405:TAEBAL>2.0.CO;2, 2004. a
Tian, Y. and Kuang, Z.: Dependence of entrainment in shallow cumulus convection on vertical velocity and distance to cloud edge, Geophys. Res. Lett., 43, 4056–4065, https://doi.org/10.1002/2016gl069005, 2016. a, b, c
Tiedtke, M.: A Comprehensive Mass Flux Scheme for Cumulus Parameterization in
Large-Scale Models, Mon. Weather Rev., 117, 1779–1800,
https://doi.org/10.1175/1520-0493(1989)117<1779:ACMFSF>2.0.CO;2, 1989. a
Trivej, P. and Stevens, B.: The Echo Size Distribution of Precipitating Shallow Cumuli, J. Atmos. Sci., 67, 788–804,
https://doi.org/10.1175/2009JAS3178.1, 2010. a, b, c
Twomey, S.: Pollution and the planetary albedo, Atmos. Environ., 8,
1251–1256, https://doi.org/10.1016/0004-6981(74)90004-3, 1974. a, b
van Zanten, M. C., Stevens, B., Nuijens, L., Siebesma, A. P., Ackerman, A. S., Burnet, F., Cheng, A., Couvreux, F., Jiang, H., Khairoutdinov, M., Kogan, Y., Lewellen, D. C., Mechem, D., Nakamura, K., Noda, A., Shipway, B. J., Slawinska, J., Wang, S., and Wyszogrodzki, A.: Controls on precipitation and cloudiness in simulations of trade-wind cumulus as observed during RICO, J. Adv. Model. Earth Sy., 3, M06001, https://doi.org/10.1029/2011MS000056, 2011. a
Vial, J., Dufresne, J.-L., and Bony, S.: On the interpretation of inter-model
spread in CMIP5 climate sensitivity estimates, Clim. Dynam., 41,
3339–3362, https://doi.org/10.1007/s00382-013-1725-9, 2013. a
Waliser, D. E. and Gautier, C.: A Satellite-derived Climatology of the ITCZ, J. Climate, 6, 2162–2174,
https://doi.org/10.1175/1520-0442(1993)006<2162:ASDCOT>2.0.CO;2, 1993. a
Wang, Y., Chen, Y., Fu, Y., and Liu, G.: Identification of precipitation onset based on Cloudsat observations,
J. Quant. Spectrosc. Ra., 188, 142–147, https://doi.org/10.1016/j.jqsrt.2016.06.028, 2017. a, b
Watson, C. D., Smith, R. B., and Nugent, A. D.: Processes Controlling
Precipitation in Shallow, Orographic, Trade Wind Convection, J. Atmos. Sci., 72, 3051–3072, https://doi.org/10.1175/JAS-D-14-0333.1, 2015. a, b
Witkowski, M., Vane, D., Livermore, T., Rokey, M., Barthuli, M., Gravseth,
I. J., Pieper, B., Rodzinak, A., Silva, S., and Woznick, P.: CloudSat anomaly
recovery and operational lessons learned, Tech. Rep., Jet Propulsion
Laboratory, National Aeronautics and Space Administration, Pasadena, California, USA, 2012. a
Witte, M. K., Morrison, H., Jensen, J. B., Bansemer, A., and Gettelman, A.: On the Covariability of Cloud and Rain Water as a Function of Length Scale, J. Atmos. Sci., 76, 2295–2308, https://doi.org/10.1175/JAS-D-19-0048.1, 2019. a
Wood, R. and Bretherton, C. S.: Boundary Layer Depth, Entrainment, and
Decoupling in the Cloud-Capped Subtropical and Tropical Marine Boundary
Layer, J. Climate, 17, 3576–3588,
https://doi.org/10.1175/1520-0442(2004)017<3576:BLDEAD>2.0.CO;2, 2004. a, b
Wyant, M. C., Khairoutdinov, M., and Bretherton, C. S.: Climate sensitivity and cloud response of a GCM with a superparameterization, Geophys. Res. Lett., 33, L06714, https://doi.org/10.1029/2005GL025464, 2006. a
Wyszogrodzki, A. A., Grabowski, W. W., Wang, L.-P., and Ayala, O.: Turbulent collision-coalescence in maritime shallow convection, Atmos. Chem. Phys., 13, 8471–8487, https://doi.org/10.5194/acp-13-8471-2013, 2013.
a
Zhang, G. and McFarlane, N. A.: Sensitivity of climate simulations to the
parameterization of cumulus convection in the Canadian climate centre general
circulation model, Atmos. Ocean, 33, 407–446,
https://doi.org/10.1080/07055900.1995.9649539, 1995. a
Zhao, M.: An Investigation of the Connections among Convection, Clouds, and
Climate Sensitivity in a Global Climate Model, J. Climate, 27,
1845–1862, https://doi.org/10.1175/JCLI-D-13-00145.1, 2014. a
Short summary
We use satellite observations of shallow cumulus clouds to investigate the influence of cloud size on the ratio of cloud water path to rainwater (WRR) in different environments. For a fixed temperature and relative humidity, WRR increases with cloud size, but it varies little with aerosols. These results imply that increasing WRR with rising temperature relates not only to deeper clouds but also to more frequent larger clouds.
We use satellite observations of shallow cumulus clouds to investigate the influence of cloud...
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