Articles | Volume 24, issue 23
https://doi.org/10.5194/acp-24-13811-2024
© Author(s) 2024. 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-24-13811-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
12 Dec 2024
Research article |
| 12 Dec 2024
| 12 Dec 2024
Observing convective activities in complex convective organizations and their contributions to precipitation and anvil cloud amounts
Zhenquan Wang
CORRESPONDING AUTHOR
School of Atmospheric Sciences, Nanjing University, Nanjing, China
Jian Yuan
School of Atmospheric Sciences, Nanjing University, Nanjing, China
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Zhenquan Wang
EGUsphere, https://doi.org/10.5194/egusphere-2024-2347, https://doi.org/10.5194/egusphere-2024-2347, 2024
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This study develops a novel upper-tropospheric stability metric based on the ERA5 to better control anvil clouds than the previous metric. With the stronger linear relationship between stability and anvil clouds, it would be helpful for understanding the anvil climate feedback processes.
Zhenquan Wang, Jian Yuan, Robert Wood, Yifan Chen, and Tiancheng Tong
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This study develops a novel profile-based algorithm based on the ERA5 to estimate the inversion strength in the planetary boundary layer better than the previous inversion index, which is a key low-cloud-controlling factor. This improved measure is more effective at representing the meteorological influence on low-cloud variations. It can better constrain the meteorological influence on low clouds to better isolate cloud responses to aerosols or to estimate low cloud feedbacks in climate models.
Zhenquan Wang
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This study develops a novel upper-tropospheric stability metric based on the ERA5 to better control anvil clouds than the previous metric. With the stronger linear relationship between stability and anvil clouds, it would be helpful for understanding the anvil climate feedback processes.
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This study develops a novel profile-based algorithm based on the ERA5 to estimate the inversion strength in the planetary boundary layer better than the previous inversion index, which is a key low-cloud-controlling factor. This improved measure is more effective at representing the meteorological influence on low-cloud variations. It can better constrain the meteorological influence on low clouds to better isolate cloud responses to aerosols or to estimate low cloud feedbacks in climate models.
Yuliang Liu, Wei Nie, Yuanyuan Li, Dafeng Ge, Chong Liu, Zhengning Xu, Liangduo Chen, Tianyi Wang, Lei Wang, Peng Sun, Ximeng Qi, Jiaping Wang, Zheng Xu, Jian Yuan, Chao Yan, Yanjun Zhang, Dandan Huang, Zhe Wang, Neil M. Donahue, Douglas Worsnop, Xuguang Chi, Mikael Ehn, and Aijun Ding
Atmos. Chem. Phys., 21, 14789–14814, https://doi.org/10.5194/acp-21-14789-2021, https://doi.org/10.5194/acp-21-14789-2021, 2021
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Oxygenated organic molecules (OOMs) are crucial intermediates linking volatile organic compounds to secondary organic aerosols. Using nitrate time-of-flight chemical ionization mass spectrometry in eastern China, we performed positive matrix factorization (PMF) on binned OOM mass spectra. We reconstructed over 1000 molecules from 14 derived PMF factors and identified about 72 % of the observed OOMs as organic nitrates, highlighting the decisive role of NOx in OOM formation in populated areas.
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Subject: Clouds and Precipitation | Research Activity: Remote Sensing | Altitude Range: Troposphere | Science Focus: Physics (physical properties and processes)
Weak liquid water path response in ship tracks
Air mass history linked to the development of Arctic mixed-phase clouds
Post-Return Stroke VHF Electromagnetic Activity in North-Western Mediterranean Cloud-to-Ground Lightning Flashes
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
Technical note: Applicability of physics-based and machine-learning-based algorithms of geostationary satellite in retrieving the diurnal cycle of cloud base height
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
How does the lifetime of detrained cirrus impact the high cloud radiative effect in the tropics?
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)
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Aerosol-related effects on the occurrence of heterogeneous ice formation over Lauder, New Zealand ∕ Aotearoa
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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
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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
Examining cloud vertical structure and radiative effects from satellite retrievals and evaluation of CMIP6 scenarios
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Natural marine cloud brightening in the Southern Ocean
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.
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.
Andrea Kolínská, Ivana Kolmašová, Eric Defer, Ondřej Santolík, and Stéphane Pédeboy
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We contribute to the knowledge about the differences in lightning flashes of opposite polarity. We found and explained a distinct behaviour of in-cloud processes happening immediately after return strokes of cloud-to-ground lightning flashes, considering a recharging of in-cloud part of bidirectional leader.
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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
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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
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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.
Mengyuan Wang, Min Min, Jun Li, Han Lin, Yongen Liang, Binlong Chen, Zhigang Yao, Na Xu, and Miao Zhang
EGUsphere, https://doi.org/10.5194/egusphere-2024-1516, https://doi.org/10.5194/egusphere-2024-1516, 2024
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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.
George Horner and Edward Gryspeerdt
EGUsphere, https://doi.org/10.5194/egusphere-2024-1090, https://doi.org/10.5194/egusphere-2024-1090, 2024
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This work tracks the lifecycle 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.
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.
Edward Gryspeerdt, Adam C. Povey, Roy G. Grainger, Otto Hasekamp, N. Christina Hsu, Jane P. Mulcahy, Andrew M. Sayer, and Armin Sorooshian
Atmos. Chem. Phys., 23, 4115–4122, https://doi.org/10.5194/acp-23-4115-2023, https://doi.org/10.5194/acp-23-4115-2023, 2023
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The impact of aerosols on clouds is one of the largest uncertainties in the human forcing of the climate. Aerosol can increase the concentrations of droplets in clouds, but observational and model studies produce widely varying estimates of this effect. We show that these estimates can be reconciled if only polluted clouds are studied, but this is insufficient to constrain the climate impact of aerosol. The uncertainty in aerosol impact on clouds is currently driven by cases with little aerosol.
Zackary Mages, Pavlos Kollias, Zeen Zhu, and Edward P. Luke
Atmos. Chem. Phys., 23, 3561–3574, https://doi.org/10.5194/acp-23-3561-2023, https://doi.org/10.5194/acp-23-3561-2023, 2023
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Cold-air outbreaks (when cold air is advected over warm water and creates low-level convection) are a dominant cloud regime in the Arctic, and we capitalized on ground-based observations, which did not previously exist, from the COMBLE field campaign to study them. We characterized the extent and strength of the convection and turbulence and found evidence of secondary ice production. This information is useful for model intercomparison studies that will represent cold-air outbreak processes.
Maria P. Cadeddu, Virendra P. Ghate, David D. Turner, and Thomas E. Surleta
Atmos. Chem. Phys., 23, 3453–3470, https://doi.org/10.5194/acp-23-3453-2023, https://doi.org/10.5194/acp-23-3453-2023, 2023
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We analyze the variability in marine boundary layer moisture at the Eastern North Atlantic site on a monthly and daily temporal scale and examine its fundamental role in the control of boundary layer cloudiness and precipitation. The study also highlights the complex interaction between large-scale and local processes controlling the boundary layer moisture and the importance of the mesoscale spatial distribution of vapor to support convection and precipitation.
Zhenquan Wang, Jian Yuan, Robert Wood, Yifan Chen, and Tiancheng Tong
Atmos. Chem. Phys., 23, 3247–3266, https://doi.org/10.5194/acp-23-3247-2023, https://doi.org/10.5194/acp-23-3247-2023, 2023
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This study develops a novel profile-based algorithm based on the ERA5 to estimate the inversion strength in the planetary boundary layer better than the previous inversion index, which is a key low-cloud-controlling factor. This improved measure is more effective at representing the meteorological influence on low-cloud variations. It can better constrain the meteorological influence on low clouds to better isolate cloud responses to aerosols or to estimate low cloud feedbacks in climate models.
Georgios Dekoutsidis, Silke Groß, Martin Wirth, Martina Krämer, and Christian Rolf
Atmos. Chem. Phys., 23, 3103–3117, https://doi.org/10.5194/acp-23-3103-2023, https://doi.org/10.5194/acp-23-3103-2023, 2023
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Cirrus clouds affect Earth's atmosphere, deeming our study important. Here we use water vapor measurements by lidar and study the relative humidity (RHi) within and around midlatitude cirrus clouds. We find high supersaturations in the cloud-free air and within the clouds, especially near the cloud top. We study two cloud types with different formation processes. Finally, we conclude that the shape of the distribution of RHi can be used as an indicator of different cloud evolutionary stages.
Huazhe Shang, Souichiro Hioki, Guillaume Penide, Céline Cornet, Husi Letu, and Jérôme Riedi
Atmos. Chem. Phys., 23, 2729–2746, https://doi.org/10.5194/acp-23-2729-2023, https://doi.org/10.5194/acp-23-2729-2023, 2023
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We find that cloud profiles can be divided into four prominent patterns, and the frequency of these four patterns is related to intensities of cloud-top entrainment and precipitation. Based on these analyses, we further propose a cloud profile parameterization scheme allowing us to represent these patterns. Our results shed light on how to facilitate the representation of cloud profiles and how to link them to cloud entrainment or precipitating status in future remote-sensing applications.
Luca Lelli, Marco Vountas, Narges Khosravi, and John Philipp Burrows
Atmos. Chem. Phys., 23, 2579–2611, https://doi.org/10.5194/acp-23-2579-2023, https://doi.org/10.5194/acp-23-2579-2023, 2023
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Arctic amplification describes the recent period in which temperatures have been rising twice as fast as or more than the global average and sea ice and the Greenland ice shelf are approaching a tipping point. Hence, the Arctic ability to reflect solar energy decreases and absorption by the surface increases. Using 2 decades of complementary satellite data, we discover that clouds unexpectedly increase the pan-Arctic reflectance by increasing their liquid water content, thus cooling the Arctic.
Yabin Gou, Haonan Chen, Hong Zhu, and Lulin Xue
Atmos. Chem. Phys., 23, 2439–2463, https://doi.org/10.5194/acp-23-2439-2023, https://doi.org/10.5194/acp-23-2439-2023, 2023
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This article investigates the complex precipitation microphysics associated with super typhoon Lekima using a host of in situ and remote sensing observations, including rain gauge and disdrometer data, as well as polarimetric radar observations. The impacts of precipitation microphysics on multi-source data consistency and radar precipitation estimation are quantified. It is concluded that the dynamical precipitation microphysical processes must be considered in radar precipitation estimation.
Hongxia Zhu, Rui Li, Shuping Yang, Chun Zhao, Zhe Jiang, and Chen Huang
Atmos. Chem. Phys., 23, 2421–2437, https://doi.org/10.5194/acp-23-2421-2023, https://doi.org/10.5194/acp-23-2421-2023, 2023
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The impacts of atmospheric dust aerosols and cloud dynamic conditions on precipitation vertical development in southeastern China were studied using multiple satellite observations. It was found that the precipitating drops under dusty conditions grow faster in the middle layer but slower in the upper and lower layers compared with their pristine counterparts. Quantitative estimation of the sensitivity of the precipitation top temperature to the dust aerosol optical depth is also provided.
Zane Dedekind, Jacopo Grazioli, Philip H. Austin, and Ulrike Lohmann
Atmos. Chem. Phys., 23, 2345–2364, https://doi.org/10.5194/acp-23-2345-2023, https://doi.org/10.5194/acp-23-2345-2023, 2023
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Simulations allowing ice particles to collide with one another producing more ice particles represented surface observations of ice particles accurately. An increase in ice particles formed through collisions was related to sharp changes in the wind direction and speed with height. Changes in wind speed and direction can therefore cause more enhanced collisions between ice particles and alter how fast and how much precipitation forms. Simulations were conducted with the atmospheric model COSMO.
Ramon Padullés, Estel Cardellach, and F. Joseph Turk
Atmos. Chem. Phys., 23, 2199–2214, https://doi.org/10.5194/acp-23-2199-2023, https://doi.org/10.5194/acp-23-2199-2023, 2023
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The results of comparing the polarimetric radio occultation observables and the ice water content retrieved from the CloudSat radar in a global and statistical way show a strong correlation between the geographical patterns of both quantities for a wide range of heights. This implies that horizontally oriented hydrometeors are systematically present through the whole globe and through all vertical levels, which could provide insights on the physical processes leading to precipitation.
Ziming Wang, Luca Bugliaro, Tina Jurkat-Witschas, Romy Heller, Ulrike Burkhardt, Helmut Ziereis, Georgios Dekoutsidis, Martin Wirth, Silke Groß, Simon Kirschler, Stefan Kaufmann, and Christiane Voigt
Atmos. Chem. Phys., 23, 1941–1961, https://doi.org/10.5194/acp-23-1941-2023, https://doi.org/10.5194/acp-23-1941-2023, 2023
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Differences in the microphysical properties of contrail cirrus and natural cirrus in a contrail outbreak situation during the ML-CIRRUS campaign over the North Atlantic flight corridor can be observed from in situ measurements. The cirrus radiative effect in the area of the outbreak, derived from satellite observation-based radiative transfer modeling, is warming in the early morning and cooling during the day.
Gerald G. Mace, Sally Benson, Ruhi Humphries, Peter M. Gombert, and Elizabeth Sterner
Atmos. Chem. Phys., 23, 1677–1685, https://doi.org/10.5194/acp-23-1677-2023, https://doi.org/10.5194/acp-23-1677-2023, 2023
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The number of cloud droplets per unit volume is a significantly important property of clouds that controls their reflective properties. Computer models of the Earth's atmosphere and climate have low skill at predicting the reflective properties of Southern Ocean clouds. Here we investigate the properties of those clouds using satellite data and find that the cloud droplet number and cloud albedo in the Southern Ocean are related to the oceanic phytoplankton abundance near Antarctica.
Cited articles
Amidror, I.: Scattered data interpolation methods for electronic imaging systems: a survey, J. Electron. Imaging, 11, 157–176, https://doi.org/10.1117/1.1455013, 2002.
Atlas, R. L., Bretherton, C. S., Sokol, A. B., Blossey, P. N., and Khairoutdinov, M. F.: Tropical Cirrus Are Highly Sensitive to Ice Microphysics Within a Nudged Global Storm-Resolving Model, Geophys. Res. Lett., 51, e2023GL105868, https://doi.org/10.1029/2023GL105868, 2024.
Bao, J. and Sherwood, S. C.: The Role of Convective Self-Aggregation in Extreme Instantaneous Versus Daily Precipitation, J. Adv. Model. Earth Sy., 11, 19–33, https://doi.org/10.1029/2018MS001503, 2019.
Berry, E. and Mace, G. G.: Cloud properties and radiative effects of the Asian summer monsoon derived from A-Train data, J. Geophys. Res.-Atmos., 119, 9492–9508, https://doi.org/10.1002/2014JD021458, 2014.
Blackman, S. S.: Multiple hypothesis tracking for multiple target tracking, IEEE Aero. El. Sys. Mag., 19, 5–18, https://doi.org/10.1109/maes.2004.1263228, 2004.
Blossey, P. N., Bretherton, C. S., and Khairoutdinov, M.: An Energy-Balance Analysis of Deep Convective Self-Aggregation above Uniform SST, J. Atmos. Sci., 62, 4273–4292, https://doi.org/10.1175/jas3614.1, 2005.
Blossey, P. N., Bretherton, C. S., Cetrone, J., and Kharoutdinov, M.: Cloud-Resolving Model Simulations of KWAJEX: Model Sensitivities and Comparisons with Satellite and Radar Observations, J. Atmos. Sci., 64, 1488–1508, https://doi.org/10.1175/jas3982.1, 2007.
Bony, S., Semie, A., Kramer, R. J., Soden, B., Tompkins, A. M., and Emanuel, K. A.: Observed Modulation of the Tropical Radiation Budget by Deep Convective Organization and Lower-Tropospheric Stability, AGU Advances, 1, e2019AV000155, https://doi.org/10.1029/2019av000155, 2020.
Bouniol, D., Roca, R., Fiolleau, T., and Poan, D. E.: Macrophysical, Microphysical, and Radiative Properties of Tropical Mesoscale Convective Systems over Their Life Cycle, J. Climate, 29, 3353–3371, https://doi.org/10.1175/jcli-d-15-0551.1, 2016.
Bresky, W. C., Daniels, J. M., Bailey, A. A., and Wanzong, S. T.: New Methods toward Minimizing the Slow Speed Bias Associated with Atmospheric Motion Vectors, J. Appl. Meteorol. Clim., 51, 2137–2151, https://doi.org/10.1175/jamc-d-11-0234.1, 2012.
Bretherton, C. S.: Insights into low-latitude cloud feedbacks from high-resolution models, Philos. T. Roy. Soc. A, 373, 20140415, https://doi.org/10.1098/rsta.2014.0415, 2015.
Bretherton, C. S., Widmann, M., Dymnikov, V. P., Wallace, J. M., and Bladé, I.: The Effective Number of Spatial Degrees of Freedom of a Time-Varying Field, J. Climate, 12, 1990–2009, https://doi.org/10.1175/1520-0442(1999)012<1990:TENOSD>2.0.CO;2, 1999.
Chen, S. S. and Houze, R. A.: Diurnal variation and life-cycle of deep convective systems over the tropical pacific warm pool, Q. J. Roy. Meteor. Soc., 123, 357–388, https://doi.org/10.1002/qj.49712353806, 1997.
Clement, A. C. and Soden, B.: The Sensitivity of the Tropical-Mean Radiation Budget, J. Climate, 18, 3189–3203, https://doi.org/10.1175/jcli3456.1, 2005.
Coppin, D. and Bony, S.: Physical mechanisms controlling the initiation of convective self-aggregation in a General Circulation Model, J. Adv. Model. Earth Sy., 7, 2060–2078, https://doi.org/10.1002/2015ms000571, 2015.
Daniels, J., Bresky, W., Bailey, A., Allegrino, A., Velden, C. S., and Wanzong, S.: Chapter 8 - Winds from ABI on the GOES-R Series, in: The GOES-R Series, edited by: Goodman, S. J., Schmit, T. J., Daniels, J., and Redmon, R. J., Elsevier, 79–94, https://doi.org/10.1016/B978-0-12-814327-8.00008-1, 2020.
de Laat, A., Defer, E., Delanoë, J., Dezitter, F., Gounou, A., Grandin, A., Guignard, A., Meirink, J. F., Moisselin, J.-M., and Parol, F.: Analysis of geostationary satellite-derived cloud parameters associated with environments with high ice water content, Atmos. Meas. Tech., 10, 1359–1371, https://doi.org/10.5194/amt-10-1359-2017, 2017.
Deng, M., Mace, G. G., and Wang, Z.: Anvil Productivities of Tropical Deep Convective Clusters and Their Regional Differences, J. Atmos. Sci., 73, 3467–3487, https://doi.org/10.1175/jas-d-15-0239.1, 2016.
Doelling, D. R., Loeb, N. G., Keyes, D. F., Nordeen, M. L., Morstad, D., Nguyen, C., Wielicki, B. A., Young, D. F., and Sun, M.: Geostationary Enhanced Temporal Interpolation for CERES Flux Products, J. Atmos. Ocean. Tech., 30, 1072–1090, https://doi.org/10.1175/jtech-d-12-00136.1, 2013.
Doelling, D. R., Sun, M., Nguyen, L. T., Nordeen, M. L., Haney, C. O., Keyes, D. F., and Mlynczak, P. E.: Advances in Geostationary-Derived Longwave Fluxes for the CERES Synoptic (SYN1deg) Product, J. Atmos. Ocean. Tech., 33, 503–521, https://doi.org/10.1175/jtech-d-15-0147.1, 2016.
Feidas, H. and Cartalis, C.: Application of an automated cloud-tracking algorithm on satellite imagery for tracking and monitoring small mesoscale convective cloud systems, Int. J. Remote Sens., 26, 1677–1698, https://doi.org/10.1080/01431160512331338023, 2007.
Feng, Z., Dong, X., Xi, B., Schumacher, C., Minnis, P., and Khaiyer, M.: Top-of-atmosphere radiation budget of convective core/stratiform rain and anvil clouds from deep convective systems, J. Geophys. Res.-Atmos., 116, D23202, https://doi.org/10.1029/2011jd016451, 2011.
Feng, Z., Leung, L. R., Houze, R. A., Hagos, S., Hardin, J., Yang, Q., Han, B., and Fan, J.: Structure and Evolution of Mesoscale Convective Systems: Sensitivity to Cloud Microphysics in Convection-Permitting Simulations Over the United States, J. Adv. Model. Earth Sy., 10, 1470–1494, https://doi.org/10.1029/2018ms001305, 2018.
Feng, Z., Hardin, J., Barnes, H. C., Li, J., Leung, L. R., Varble, A., and Zhang, Z.: PyFLEXTRKR: a flexible feature tracking Python software for convective cloud analysis, Geosci. Model Dev., 16, 2753–2776, https://doi.org/10.5194/gmd-16-2753-2023, 2023.
Fiolleau, T. and Roca, R.: An Algorithm for the Detection and Tracking of Tropical Mesoscale Convective Systems Using Infrared Images From Geostationary Satellite, IEEE T. Geosci. Remote, 51, 4302–4315, https://doi.org/10.1109/tgrs.2012.2227762, 2013.
Fu, R., Del Genio, A. D., and Rossow, W. B.: Behavior of Deep Convective Clouds in the Tropical Pacific Deduced from ISCCP Radiances, J. Climate, 3, 1129–1152, https://doi.org/10.1175/1520-0442(1990)003<1129:Bodcci>2.0.CO;2, 1990.
Fu, Y., Sun, J., Fu, S., Zhang, Y., and Ma, Z.: Initiations of Mesoscale Convective Systems in the Middle Reaches of the Yangtze River Basin Based on FY-4A Satellite Data: Statistical Characteristics and Environmental Conditions, J. Geophys. Res.-Atmos., 128, e2023JD038630, https://doi.org/10.1029/2023jd038630, 2023.
Gasparini, B., Sokol, A. B., Wall, C. J., Hartmann, D. L., and Blossey, P. N.: Diurnal Differences in Tropical Maritime Anvil Cloud Evolution, J. Climate, 35, 1655–1677, https://doi.org/10.1175/jcli-d-21-0211.1, 2022.
Giangrande, S., Clothiaux, E., and Kollias, P.: Active Remote Sensing of CLouds (ARSCL1CLOTH), ARM Data Center [data set], https://doi.org/10.5439/1996113, 1999.
Goyens, C., Lauwaet, D., Schröder, M., Demuzere, M., and Van Lipzig, N. P. M.: Tracking mesoscale convective systems in the Sahel: relation between cloud parameters and precipitation, Int. J. Climatol., 32, 1921–1934, https://doi.org/10.1002/joc.2407, 2011.
Heikenfeld, M., Marinescu, P. J., Christensen, M., Watson-Parris, D., Senf, F., van den Heever, S. C., and Stier, P.: tobac 1.2: towards a flexible framework for tracking and analysis of clouds in diverse datasets, Geosci. Model Dev., 12, 4551–4570, https://doi.org/10.5194/gmd-12-4551-2019, 2019.
Hendon, H. H. and Woodberry, K.: The diurnal cycle of tropical convection, J. Geophys. Res., 98, 16623–16637, https://doi.org/10.1029/93jd00525, 1993.
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., Chiara, G., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J. N.: The ERA5 global reanalysis, Q. J. Roy. Meteor. Soc., 146, 1999–2049, https://doi.org/10.1002/qj.3803, 2020.
Hollars, S., Fu, Q., Comstock, J., and Ackerman, T.: Comparison of cloud-top height retrievals from ground-based 35 GHz MMCR and GMS-5 satellite observations at ARM TWP Manus site, Atmos. Res., 72, 169-186, https://doi.org/10.1016/j.atmosres.2004.03.015, 2004.
Holloway, C. E., Wing, A. A., Bony, S., Muller, C., Masunaga, H., L'Ecuyer, T. S., Turner, D. D., and Zuidema, P.: Observing Convective Aggregation, Surv. Geophys., 38, 1199–1236, https://doi.org/10.1007/s10712-017-9419-1, 2017.
Houze, R. A.: Mesoscale convective systems, Rev. Geophys., 42, RG4003, https://doi.org/10.1029/2004rg000150, 2004.
Huang, X., Hu, C., Huang, X., Chu, Y., Tseng, Y.-h., Zhang, G. J., and Lin, Y.: A long-term tropical mesoscale convective systems dataset based on a novel objective automatic tracking algorithm, Clim. Dynam., 51, 3145–3159, https://doi.org/10.1007/s00382-018-4071-0, 2018.
Huffman, G. J., Adler, R. F., Arkin, P., Chang, A., Ferraro, R., Gruber, A., Janowiak, J., McNab, A., Rudolf, B., and Schneider, U.: The Global Precipitation Climatology Project (GPCP) Combined Precipitation Dataset, B. Am. Meteorol. Soc., 78, 5–20, https://doi.org/10.1175/1520-0477(1997)078<0005:Tgpcpg>2.0.CO;2, 1997.
Huffman, G. J., Adler, R. F., Bolvin, D. T., Gu, G., Nelkin, E. J., Bowman, K. P., Hong, Y., Stocker, E. F., and Wolff, D. B.: The TRMM Multisatellite Precipitation Analysis (TMPA): Quasi-Global, Multiyear, Combined-Sensor Precipitation Estimates at Fine Scales, J. Hydrometeorol., 8, 38–55, https://doi.org/10.1175/jhm560.1, 2007.
Huffman, G. J., Stocker, E. F., Bolvin, D. T., Nelkin, E. J., and Tan, J.: GPM IMERG Final Precipitation L3 Half Hourly 0.1 degree x 0.1 degree V07, Goddard Earth Sciences Data and Information Services Center (GES DISC) [data set], https://doi.org/10.5067/GPM/IMERG/3B-HH/07, 2023.
Igel, M. R., Drager, A. J., and van den Heever, S. C.: A CloudSat cloud object partitioning technique and assessment and integration of deep convective anvil sensitivities to sea surfac e temperature, J. Geophys. Res.-Atmos., 119, 10515–10535, https://doi.org/10.1002/2014jd021717, 2014.
Keeler, E., Burk, K., and Kyrouac, J.: Balloon-Borne Sounding System (SONDEWNPN), ARM user facility [data set], https://doi.org/10.5439/1595321, 2001.
Kolios, S. and Feidas, H.: A warm season climatology of mesoscale convective systems in the Mediterranean basin using satellite data, Theor. Appl. Climatol., 102, 29–42, https://doi.org/10.1007/s00704-009-0241-7, 2009.
La, T. V. and Messager, C.: Convective System Observations by LEO and GEO Satellites in Combination, IEEE J. Sel. Top. Appl., 14, 11814–11823, https://doi.org/10.1109/jstars.2021.3127401, 2021.
Laing, A. G., Carbone, R., Levizzani, V., and Tuttle, J.: The propagation and diurnal cycles of deep convection in northern tropical Africa, Q. J. Roy. Meteor. Soc., 134, 93–109, https://doi.org/10.1002/qj.194, 2008.
Leese, J. A., Novak, C. S., and Clark, B. B.: An Automated Technique for Obtaining Cloud Motion from Geosynchronous Satellite Data Using Cross Correlation, J. Appl. Meteorol., 10, 118–132, https://doi.org/10.1175/1520-0450(1971)010<0118:AATFOC>2.0.CO;2, 1971.
Lindzen, R. S., Chou, M.-D., and Hou, A. Y.: Does the Earth Have an Adaptive Infrared Iris?, B. Am. Meteorol. Soc., 82, 417–432, https://doi.org/10.1175/1520-0477(2001)082<0417:Dtehaa>2.3.Co;2, 2001.
Matsui, T., Zeng, X., Tao, W.-K., Masunaga, H., Olson, W. S., and Lang, S.: Evaluation of Long-Term Cloud-Resolving Model Simulations Using Satellite Radiance Observations and Multifrequency Satellite Simulators, J. Atmos. Ocean. Tech., 26, 1261–1274, https://doi.org/10.1175/2008jtecha1168.1, 2009.
Mauritsen, T. and Stevens, B.: Missing iris effect as a possible cause of muted hydrological change and high climate sensitivity in models, Nat. Geosci., 8, 346–351, https://doi.org/10.1038/ngeo2414, 2015.
Merrill, R. T., Menzel, W. P., Baker, W., Lynch, J., and Legg, E.: A Report on the Recent Demonstration of NOAA's Upgraded Capability to Derive Cloud Motion Satellite Winds, B. Am. Meteorol. Soc., 72, 372–376, https://doi.org/10.1175/1520-0477-72.3.372, 1991.
Minnis, P., Trepte, Q. Z., Sun-Mack, S., Chen, Y., Doelling, D. R., Young, D. F., Spangenberg, D. A., Miller, W. F., Wielicki, B. A., Brown, R. R., Gibson, S. C., and Geier, E. B.: Cloud Detection in Nonpolar Regions for CERES Using TRMM VIRS and Terra and Aqua MODIS Data, IEEE T. Geosci. Remote, 46, 3857–3884, https://doi.org/10.1109/TGRS.2008.2001351, 2008.
Minnis, P., Sun-Mack, S., Young, D. F., Heck, P. W., Garber, D. P., Chen, Y., Spangenberg, D. A., Arduini, R. F., Trepte, Q. Z., Smith, W. L., Ayers, J. K., Gibson, S. C., Miller, W. F., Hong, G., Chakrapani, V., Takano, Y., Liou, K.-N., Xie, Y., and Yang, P.: CERES Edition-2 Cloud Property Retrievals Using TRMM VIRS and Terra and Aqua MODIS Data–Part I: Algorithms, IEEE T. Geosci. Remote, 49, 4374–4400, https://doi.org/10.1109/tgrs.2011.2144601, 2011.
Muller, C. and Bony, S.: What favors convective aggregation and why?, Geophys. Res. Lett., 42, 5626–5634, https://doi.org/10.1002/2015GL064260, 2015.
NASA/LARC/SD/ASDC: SatCORPS CERES GEO Edition 4 MTSAT-1R, Version 1.0, NASA Langley Atmospheric Science Data Center DAAC [data set], https://doi.org/10.5067/MTS01/CERES, 2017.
Nieman, S. J., Menzel, W. P., Hayden, C. M., Gray, D., Wanzong, S. T., Velden, C. S., and Daniels, J.: Fully Automated Cloud-Drift Winds in NESDIS Operations, B. Am. Meteorol. Soc., 78, 1121–1133, https://doi.org/10.1175/1520-0477(1997)078<1121:FACDWI>2.0.CO;2, 1997.
Powell, S. W., Houze, R. A., Kumar, A., and McFarlane, S. A.: Comparison of Simulated and Observed Continental Tropical Anvil Clouds and Their Radiative Heating Profiles, J. Atmos. Sci., 69, 2662–2681, https://doi.org/10.1175/jas-d-11-0251.1, 2012.
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.
Richards, F. and Arkin, P.: On the Relationship between Satellite-Observed Cloud Cover and Precipitation, Mon. Weather Rev., 109, 1081–1093, https://doi.org/10.1175/1520-0493(1981)109<1081:Otrbso>2.0.CO;2, 1981.
Ruppert, J. H. and Hohenegger, C.: Diurnal Circulation Adjustment and Organized Deep Convection, J. Climate, 31, 4899–4916, https://doi.org/10.1175/jcli-d-17-0693.1, 2018.
Salonen, K. and Bormann, N.: Atmospheric Motion Vector observations in the ECMWF system: Fifth year report, ECMWF, https://doi.org/10.13140/RG.2.1.3767.6404, 2016.
Santek, D., Dworak, R., Nebuda, S., Wanzong, S., Borde, R., Genkova, I., García-Pereda, J., Galante Negri, R., Carranza, M., Nonaka, K., Shimoji, K., Oh, S. M., Lee, B.-I., Chung, S.-R., Daniels, J., and Bresky, W.: 2018 Atmospheric Motion Vector (AMV) Intercomparison Study, Remote Sensing, 11, 2240, https://doi.org/10.3390/rs11192240, 2019.
Schröder, M., König, M., and Schmetz, J.: Deep convection observed by the Spinning Enhanced Visible and Infrared Imager on board Meteosat 8: Spatial distribution and temporal evolution over Africa in summer and winter 2006, J. Geophys. Res.-Atmos., 114, D05109, https://doi.org/10.1029/2008jd010653, 2009.
Sokol, A. B. and Hartmann, D. L.: Tropical Anvil Clouds: Radiative Driving Toward a Preferred State, J. Geophys. Res.-Atmos., 125, e2020JD033107, https://doi.org/10.1029/2020jd033107, 2020.
Sokol, A. B. and Hartmann, D. L.: Congestus Mode Invigoration by Convective Aggregation in Simulations of Radiative-Convective Equilibrium, J. Adv. Model Earth Sy., 14, e2022MS003045, https://doi.org/10.1029/2022MS003045, 2022.
Suzuki, K., Golaz, J. C., and Stephens, G. L.: Evaluating cloud tuning in a climate model with satellite observations, Geophys. Res. Lett., 40, 4464–4468, https://doi.org/10.1002/grl.50874, 2013.
Takahashi, H. and Luo, Z.: Where is the level of neutral buoyancy for deep convection?, Geophys. Res. Lett., 39, L15809, https://doi.org/10.1029/2012GL052638, 2012.
Tian, Y. D., Peters-Lidard, C. D., Eylander, J. B., Joyce, R. J., Huffman, G. J., Adler, R. F., Hsu, K. L., Turk, F. J., Garcia, M., and Zeng, J.: Component analysis of errors in satellite-based precipitation estimates, J. Geophys. Res.-Atmos., 114, D24101, https://doi.org/10.1029/2009JD011949, 2009.
Tobin, I., Roca, R., and Bony, S.: Observational Evidence for Relationships between the Degree of Aggregation of Deep Convection, Water Vapor, Surface Fluxes, and Radiation, J. Climate, 25, 6885–6904, https://doi.org/10.1175/jcli-d-11-00258.1, 2012.
Tsakraklides, G. and Evans, J. L.: Global and regional diurnal variations of organized convection, J. Climate, 16, 1562–1572, https://doi.org/10.1175/1520-0442(2003)016<1562:GARDVO>2.0.CO;2, 2003.
Velden, C. S., Olander, T. L., and Wanzong, S.: The Impact of Multispectral GOES-8 Wind Information on Atlantic Tropical Cyclone Track Forecasts in 1995. Part I: Dataset Methodology, Description, and Case Analysis, Mon. Weather Rev., 126, 1202–1218, https://doi.org/10.1175/1520-0493(1998)126<1202:TIOMGW>2.0.CO;2, 1998.
Wall, C. J., Hartmann, D. L., Thieman, M. M., Smith Jr., W. L., and Minnis, P.: The Life Cycle of Anvil Clouds and the Top-of-Atmosphere Radiation Balance over the Tropical West Pacific, J. Climate, 31, 10059–10080, https://doi.org/10.1175/JCLI-D-18-0154.1, 2018.
Williams, M. and Houze Jr., R. A.: Satellite-Observed Characteristics of Winter Monsoon Cloud Clusters, Mon. Weather Rev., 115, 505–519, https://doi.org/10.1175/1520-0493(1987)115<0505:SOCOWM>2.0.CO;2, 1987.
Wing, A. A. and Emanuel, K. A.: Physical mechanisms controlling self-aggregation of convection in idealized numerical modeling simulations, J. Adv. Model. Earth Sy., 6, 59–74, https://doi.org/10.1002/2013ms000269, 2014.
Wing, A. A., Emanuel, K., Holloway, C. E., and Muller, C.: Convective Self-Aggregation in Numerical Simulations: A Review, Surv. Geophys., 38, 1173–1197, https://doi.org/10.1007/s10712-017-9408-4, 2017.
Yang, K., Wang, Z., Deng, M., and Dettmann, B.: Combining CloudSat/CALIPSO and MODIS measurements to reconstruct tropical convective cloud structure, Remote Sens. Environ., 287, 113478, https://doi.org/10.1016/j.rse.2023.113478, 2023.
Yang, R., Zhang, Y., Sun, J., and Li, J.: The comparison of statistical features and synoptic circulations between the eastward-propagating and quasi-stationary MCSs during the warm season around the second-step terrain along the middle reaches of the Yangtze River, Sci. China Earth Sci., 63, 1209–1222, https://doi.org/10.1007/s11430-018-9385-3, 2020.
Yuan, J. and Houze Jr., R. A.: Global Variability of Mesoscale Convective System Anvil Structure from A-Train Satellite Data, J. Climate, 23, 5864–5888, https://doi.org/10.1175/2010jcli3671.1, 2010.
Yuan, J. and Houze Jr., R. A.: Deep Convective Systems Observed by A-Train in the Tropical Indo-Pacific Region Affected by the MJO, J. Atmos. Sci., 70, 465–486, https://doi.org/10.1175/JAS-D-12-057.1, 2013.
Yuan, J., Houze Jr., R. A., and Heymsfield, A. J.: Vertical Structures of Anvil Clouds of Tropical Mesoscale Convective Systems Observed by CloudSat, J. Atmos. Sci., 68, 1653–1674, https://doi.org/10.1175/2011jas3687.1, 2011.
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.
Zhao, M., Golaz, J. C., Held, I. M., Ramaswamy, V., Lin, S. J., Ming, Y., Ginoux, P., Wyman, B., Donner, L. J., Paynter, D., and Guo, H.: Uncertainty in Model Climate Sensitivity Traced to Representations of Cumulus Precipitation Microphysics, J. Climate, 29, 543–560, https://doi.org/10.1175/jcli-d-15-0191.1, 2016.
Zhao, W., Marchand, R., and Fu, Q.: The diurnal cycle of clouds and precipitation at the ARM SGP site: Cloud radar observations and simulations from the multiscale modeling framework, J. Geophys. Res.-Atmos., 122, 7519–7536, https://doi.org/10.1002/2016jd026353, 2017.
Zinner, T., Mannstein, H., and Tafferner, A.: Cb-TRAM: Tracking and monitoring severe convection from onset over rapid development to mature phase using multi-channel Meteosat-8 SEVIRI data, Meteorol. Atmos. Phys., 101, 191–210, https://doi.org/10.1007/s00703-008-0290-y, 2008.
Zinner, T., Forster, C., de Coning, E., and Betz, H.-D.: Validation of the Meteosat storm detection and nowcasting system Cb-TRAM with lightning network data – Europe and South Africa, Atmos. Meas. Tech., 6, 1567–1583, https://doi.org/10.5194/amt-6-1567-2013, 2013.
Short summary
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.
Tropical convection organizations are normally connected complexes of many convective...
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