Articles | Volume 24, issue 18
https://doi.org/10.5194/acp-24-10793-2024
© 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-24-10793-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
26 Sep 2024
Research article |
| 26 Sep 2024
| 26 Sep 2024
A thermal-driven graupel generation process to explain dry-season convective vigor over the Amazon
Toshi Matsui
CORRESPONDING AUTHOR
Mesoscale Atmospheric Processes Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD, USA
Earth System Science Interdisciplinary Center – ESSIC, University of Maryland, College Park, MD, USA
Daniel Hernandez-Deckers
Grupo de Investigación en Ciencias Atmosféricas, Departamento de Geociencias, Universidad Nacional de Colombia, Bogotá, Colombia
Scott E. Giangrande
Environmental and Climate Sciences Department, Brookhaven National Laboratory, Upton, NY, USA
Thiago S. Biscaro
Meteorological Satellites and Sensors Division, National Institute for Space Research, Cachoeira Paulista, São Paulo, Brazil
Ann Fridlind
NASA Goddard Institute for Space Studies, New York, NY, USA
Scott Braun
Mesoscale Atmospheric Processes Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD, USA
Related authors
McKenna Stanford, Ann Fridlind, Andrew Ackerman, Bastiaan van Diedenhoven, Qian Xiao, Jian Wang, Toshihisa Matsui, Daniel Hernandez-Deckers, and Paul Lawson
EGUsphere, https://doi.org/10.5194/egusphere-2024-2413, https://doi.org/10.5194/egusphere-2024-2413, 2024
Short summary
Short summary
The evolution of cloud droplets, from the point they are activated by atmospheric aerosol to the formation of precipitation, is an important process relevant to understanding cloud-climate feedbacks. This study demonstrates a benchmark framework for using novel airborne measurements and retrievals to constrain high-resolution simulations of moderately deep cumulus clouds and pathways for scaling results to large-scale models and space-based observational platforms.
Daniel Hernandez-Deckers, Toshihisa Matsui, and Ann M. Fridlind
Atmos. Chem. Phys., 22, 711–724, https://doi.org/10.5194/acp-22-711-2022, https://doi.org/10.5194/acp-22-711-2022, 2022
Short summary
Short summary
We investigate how the concentration of aerosols (small particles that serve as seeds for cloud droplets) affect the dynamics of simulated clouds using two different frameworks, i.e., the traditional selection of cloudy rising grid points and tracking small-scale coherent rising features (cumulus thermals). By doing so, we find that these cumulus thermals reveal useful information about the coupling between internal cloud circulations and cloud droplet and raindrop formation.
Tamanna Subba, Michael P. Jensen, Min Deng, Scott E. Giangrande, Mark C. Harvey, Ashish Singh, Die Wang, Maria Zawadowicz, and Chongai Kuang
EGUsphere, https://doi.org/10.5194/egusphere-2025-2659, https://doi.org/10.5194/egusphere-2025-2659, 2025
Short summary
Short summary
This study highlights how sea breeze circulations influence aerosol concentrations and radiative effects in Southern Texas region. Using TRacking Aerosol Convection Interactions Experiment field campaign observations and model simulations, we show that sea breeze–aerosol interactions significantly impact cloud-relevant aerosols and regional air quality. These findings improve understanding of mesoscale controls on aerosols in complex coastal urban environments.
Andrew M. Sayer, Brian Cairns, Kirk D. Knobelspiesse, Luca Lelli, Chamara Rajapakshe, Scott E. Giangrande, Gareth E. Thomas, and Damao Zhang
EGUsphere, https://doi.org/10.5194/egusphere-2025-2005, https://doi.org/10.5194/egusphere-2025-2005, 2025
Short summary
Short summary
Satellites can estimate cloud height in several ways: two include a thermal technique (colder clouds being higher up), and another looking at colours of light that oxygen in the atmosphere absorbs (darker clouds being lower down). It can also be measured (from ground or space) by radar and lidar. We compare satellite data we developed using the oxygen method with other estimates to help us refine our technique.
Florian Tornow, Ann Fridlind, George Tselioudis, Brian Cairns, Andrew Ackerman, Seethala Chellappan, David Painemal, Paquita Zuidema, Christiane Voigt, Simon Kirschler, and Armin Sorooshian
Atmos. Chem. Phys., 25, 5053–5074, https://doi.org/10.5194/acp-25-5053-2025, https://doi.org/10.5194/acp-25-5053-2025, 2025
Short summary
Short summary
The recent NASA campaign ACTIVATE (Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment) performed 71 tandem flights in mid-latitude marine cold-air outbreaks off the US eastern seaboard. We provide meteorological and cloud transition stage context, allowing us to identify days that are most suitable for Lagrangian modeling and analysis. Surveyed cloud properties show signatures of cloud microphysical processes, such as cloud-top entrainment and secondary ice formation.
Min Deng, Scott E. Giangrande, Michael P. Jensen, Karen Johnson, Christopher R. Williams, Jennifer M. Comstock, Ya-Chien Feng, Alyssa Matthews, Iosif A. Lindenmaier, Timothy G. Wendler, Marquette Rocque, Aifang Zhou, Zeen Zhu, Edward Luke, and Die Wang
Atmos. Meas. Tech., 18, 1641–1657, https://doi.org/10.5194/amt-18-1641-2025, https://doi.org/10.5194/amt-18-1641-2025, 2025
Short summary
Short summary
A relative calibration technique is developed for the cloud radar by monitoring the intercept of the wet-radome attenuation log-linear behavior as a function of rainfall rates in light and moderate rain conditions. This resulting reflectivity offset during the recent field campaign is compared favorably with the traditional disdrometer comparison near the rain onset, while it also demonstrates similar trends with respect to collocated and independently calibrated reference radars.
Kaiden Sookdar, Scott Edward Giangrande, John Rausch, Lihong Ma, Meng Wang, Dié Wang, Michael Jensen, Ching-Shu Hung, and J. Christine Chiu
EGUsphere, https://doi.org/10.5194/egusphere-2025-694, https://doi.org/10.5194/egusphere-2025-694, 2025
Short summary
Short summary
Photometer observations of stratocumulus cloud properties are evaluated for a multiyear archive. Retrievals for cloud optical depth, cloud droplet effective radius, and liquid water path show solid agreement with collocated references. Continental stratocumulus clouds sorted by cloud thickness indicate double the cloud optical depth and liquid water path of their marine counterparts, while exhibiting similar bulk cloud droplet effective radius.
Johannes Mülmenstädt, Andrew S. Ackerman, Ann M. Fridlind, Meng Huang, Po-Lun Ma, Naser Mahfouz, Susanne E. Bauer, Susannah M. Burrows, Matthew W. Christensen, Sudhakar Dipu, Andrew Gettelman, L. Ruby Leung, Florian Tornow, Johannes Quaas, Adam C. Varble, Hailong Wang, Kai Zhang, and Youtong Zheng
Atmos. Chem. Phys., 24, 13633–13652, https://doi.org/10.5194/acp-24-13633-2024, https://doi.org/10.5194/acp-24-13633-2024, 2024
Short summary
Short summary
Stratocumulus clouds play a large role in Earth's climate by reflecting incoming solar energy back to space. Turbulence at stratocumulus cloud top mixes in dry, warm air, which can lead to cloud dissipation. This process is challenging for coarse-resolution global models to represent. We show that global models nevertheless agree well with our process understanding. Global models also think the process is less important for the climate than other lines of evidence have led us to conclude.
Camila da Cunha Lopes, Rachel Ifanger Albrecht, Douglas Messias Uba, Thiago Souza Biscaro, and Ivan Saraiva
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-438, https://doi.org/10.5194/essd-2024-438, 2024
Revised manuscript accepted for ESSD
Short summary
Short summary
This study used observations collected during The Observations and Modeling of the Green Ocean Amazon (GoAmazon2014/5) Experiment to create a database of storms and thunderstorms characteristics with weather radar and lightning measurements. These storms have different sizes and durations between wet and dry seasons as well as throughout the day, with the most intense ones occurring in the dry-to-wet transition. This database is useful in future studies on Amazonian clouds.
Alexei Korolev, Zhipeng Qu, Jason Milbrandt, Ivan Heckman, Mélissa Cholette, Mengistu Wolde, Cuong Nguyen, Greg M. McFarquhar, Paul Lawson, and Ann M. Fridlind
Atmos. Chem. Phys., 24, 11849–11881, https://doi.org/10.5194/acp-24-11849-2024, https://doi.org/10.5194/acp-24-11849-2024, 2024
Short summary
Short summary
The phenomenon of high ice water content (HIWC) occurs in mesoscale convective systems (MCSs) when a large number of small ice particles with typical sizes of a few hundred micrometers is found at high altitudes. It was found that secondary ice production in the vicinity of the melting layer plays a key role in the formation and maintenance of HIWC. This study presents a conceptual model of the formation of HIWC in tropical MCSs based on in situ observations and numerical simulation.
Abigail S. Williams, Jeramy L. Dedrick, Lynn M. Russell, Florian Tornow, Israel Silber, Ann M. Fridlind, Benjamin Swanson, Paul J. DeMott, Paul Zieger, and Radovan Krejci
Atmos. Chem. Phys., 24, 11791–11805, https://doi.org/10.5194/acp-24-11791-2024, https://doi.org/10.5194/acp-24-11791-2024, 2024
Short summary
Short summary
The measured aerosol size distribution modes reveal distinct properties characteristic of cold-air outbreaks in the Norwegian Arctic. We find higher sea spray number concentrations, smaller Hoppel minima, lower effective supersaturations, and accumulation-mode particle scavenging during cold-air outbreaks. These results advance our understanding of cold-air outbreak aerosol–cloud interactions in order to improve their accurate representation in models.
McKenna Stanford, Ann Fridlind, Andrew Ackerman, Bastiaan van Diedenhoven, Qian Xiao, Jian Wang, Toshihisa Matsui, Daniel Hernandez-Deckers, and Paul Lawson
EGUsphere, https://doi.org/10.5194/egusphere-2024-2413, https://doi.org/10.5194/egusphere-2024-2413, 2024
Short summary
Short summary
The evolution of cloud droplets, from the point they are activated by atmospheric aerosol to the formation of precipitation, is an important process relevant to understanding cloud-climate feedbacks. This study demonstrates a benchmark framework for using novel airborne measurements and retrievals to constrain high-resolution simulations of moderately deep cumulus clouds and pathways for scaling results to large-scale models and space-based observational platforms.
Johannes Mülmenstädt, Edward Gryspeerdt, Sudhakar Dipu, Johannes Quaas, Andrew S. Ackerman, Ann M. Fridlind, Florian Tornow, Susanne E. Bauer, Andrew Gettelman, Yi Ming, Youtong Zheng, Po-Lun Ma, Hailong Wang, Kai Zhang, Matthew W. Christensen, Adam C. Varble, L. Ruby Leung, Xiaohong Liu, David Neubauer, Daniel G. Partridge, Philip Stier, and Toshihiko Takemura
Atmos. Chem. Phys., 24, 7331–7345, https://doi.org/10.5194/acp-24-7331-2024, https://doi.org/10.5194/acp-24-7331-2024, 2024
Short summary
Short summary
Human activities release copious amounts of small particles called aerosols into the atmosphere. These particles change how much sunlight clouds reflect to space, an important human perturbation of the climate, whose magnitude is highly uncertain. We found that the latest climate models show a negative correlation but a positive causal relationship between aerosols and cloud water. This means we need to be very careful when we interpret observational studies that can only see correlation.
Siddhant Gupta, Dié Wang, Scott E. Giangrande, Thiago S. Biscaro, and Michael P. Jensen
Atmos. Chem. Phys., 24, 4487–4510, https://doi.org/10.5194/acp-24-4487-2024, https://doi.org/10.5194/acp-24-4487-2024, 2024
Short summary
Short summary
We examine the lifecycle of isolated deep convective clouds (DCCs) in the Amazon rainforest. Weather radar echoes from the DCCs are tracked to evaluate their lifecycle. The DCC size and intensity increase, reach a peak, and then decrease over the DCC lifetime. Vertical profiles of air motion and mass transport from different seasons are examined to understand the transport of energy and momentum within DCC cores and to address the deficiencies in simulating DCCs using weather and climate models.
Kamil Mroz, Alessandro Battaglia, and Ann M. Fridlind
Atmos. Meas. Tech., 17, 1577–1597, https://doi.org/10.5194/amt-17-1577-2024, https://doi.org/10.5194/amt-17-1577-2024, 2024
Short summary
Short summary
In this study, we examine the extent to which radar measurements from space can inform us about the properties of clouds and precipitation. Surprisingly, our analysis showed that the amount of ice turning into rain was lower than expected in the current product. To improve on this, we came up with a new way to extract information about the size and concentration of particles from radar data. As long as we use this method in the right conditions, we can even estimate how dense the ice is.
Yang Wang, Chanakya Bagya Ramesh, Scott E. Giangrande, Jerome Fast, Xianda Gong, Jiaoshi Zhang, Ahmet Tolga Odabasi, Marcus Vinicius Batista Oliveira, Alyssa Matthews, Fan Mei, John E. Shilling, Jason Tomlinson, Die Wang, and Jian Wang
Atmos. Chem. Phys., 23, 15671–15691, https://doi.org/10.5194/acp-23-15671-2023, https://doi.org/10.5194/acp-23-15671-2023, 2023
Short summary
Short summary
We report the vertical profiles of aerosol properties over the Southern Great Plains (SGP), a region influenced by shallow convective clouds, land–atmosphere interactions, boundary layer turbulence, and the aerosol life cycle. We examined the processes that drive the aerosol population and distribution in the lower troposphere over the SGP. This study helps improve our understanding of aerosol–cloud interactions and the model representation of aerosol processes.
McKenna W. Stanford, Ann M. Fridlind, Israel Silber, Andrew S. Ackerman, Greg Cesana, Johannes Mülmenstädt, Alain Protat, Simon Alexander, and Adrian McDonald
Atmos. Chem. Phys., 23, 9037–9069, https://doi.org/10.5194/acp-23-9037-2023, https://doi.org/10.5194/acp-23-9037-2023, 2023
Short summary
Short summary
Clouds play an important role in the Earth’s climate system as they modulate the amount of radiation that either reaches the surface or is reflected back to space. This study demonstrates an approach to robustly evaluate surface-based observations against a large-scale model. We find that the large-scale model precipitates too infrequently relative to observations, contrary to literature documentation suggesting otherwise based on satellite measurements.
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
Short summary
Short summary
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.
Christopher R. Williams, Joshua Barrio, Paul E. Johnston, Paytsar Muradyan, and Scott E. Giangrande
Atmos. Meas. Tech., 16, 2381–2398, https://doi.org/10.5194/amt-16-2381-2023, https://doi.org/10.5194/amt-16-2381-2023, 2023
Short summary
Short summary
This study uses surface disdrometer observations to calibrate 8 years of 915 MHz radar wind profiler deployed in the central United States in northern Oklahoma. This study had two key findings. First, the radar wind profiler sensitivity decreased approximately 3 to 4 dB/year as the hardware aged. Second, this drift was slow enough that calibration can be performed using 3-month intervals. Calibrated radar wind profiler observations and Python processing code are available on public repositories.
Frederic Tridon, Israel Silber, Alessandro Battaglia, Stefan Kneifel, Ann Fridlind, Petros Kalogeras, and Ranvir Dhillon
Atmos. Chem. Phys., 22, 12467–12491, https://doi.org/10.5194/acp-22-12467-2022, https://doi.org/10.5194/acp-22-12467-2022, 2022
Short summary
Short summary
The role of ice precipitation in the Earth water budget is not well known because ice particles are complex, and their formation involves intricate processes. Riming of ice crystals by supercooled water droplets is an efficient process, but little is known about its importance at high latitudes. In this work, by exploiting the deployment of an unprecedented number of remote sensing systems in Antarctica, we find that riming occurs at much lower temperatures compared with the mid-latitudes.
Michael S. Diamond, Pablo E. Saide, Paquita Zuidema, Andrew S. Ackerman, Sarah J. Doherty, Ann M. Fridlind, Hamish Gordon, Calvin Howes, Jan Kazil, Takanobu Yamaguchi, Jianhao Zhang, Graham Feingold, and Robert Wood
Atmos. Chem. Phys., 22, 12113–12151, https://doi.org/10.5194/acp-22-12113-2022, https://doi.org/10.5194/acp-22-12113-2022, 2022
Short summary
Short summary
Smoke from southern Africa blankets the southeast Atlantic from June-October, overlying a major transition region between overcast and scattered clouds. The smoke affects Earth's radiation budget by absorbing sunlight and changing cloud properties. We investigate these effects in regional climate and large eddy simulation models based on international field campaigns. We find that large-scale circulation changes more strongly affect cloud transitions than smoke microphysical effects in our case.
Israel Silber, Robert C. Jackson, Ann M. Fridlind, Andrew S. Ackerman, Scott Collis, Johannes Verlinde, and Jiachen Ding
Geosci. Model Dev., 15, 901–927, https://doi.org/10.5194/gmd-15-901-2022, https://doi.org/10.5194/gmd-15-901-2022, 2022
Short summary
Short summary
The Earth Model Column Collaboratory (EMC2) is an open-source ground-based (and air- or space-borne) lidar and radar simulator and subcolumn generator designed for large-scale models, in particular climate models, applicable also for high-resolution models. EMC2 emulates measurements while remaining faithful to large-scale models' physical assumptions implemented in their cloud or radiation schemes. We demonstrate the use of EMC2 to compare AWARE measurements with the NASA GISS ModelE3 and LES.
Daniel Hernandez-Deckers, Toshihisa Matsui, and Ann M. Fridlind
Atmos. Chem. Phys., 22, 711–724, https://doi.org/10.5194/acp-22-711-2022, https://doi.org/10.5194/acp-22-711-2022, 2022
Short summary
Short summary
We investigate how the concentration of aerosols (small particles that serve as seeds for cloud droplets) affect the dynamics of simulated clouds using two different frameworks, i.e., the traditional selection of cloudy rising grid points and tracking small-scale coherent rising features (cumulus thermals). By doing so, we find that these cumulus thermals reveal useful information about the coupling between internal cloud circulations and cloud droplet and raindrop formation.
Michael P. Jensen, Virendra P. Ghate, Dié Wang, Diana K. Apoznanski, Mary J. Bartholomew, Scott E. Giangrande, Karen L. Johnson, and Mandana M. Thieman
Atmos. Chem. Phys., 21, 14557–14571, https://doi.org/10.5194/acp-21-14557-2021, https://doi.org/10.5194/acp-21-14557-2021, 2021
Short summary
Short summary
This work compares the large-scale meteorology, cloud, aerosol, precipitation, and thermodynamics of closed- and open-cell cloud organizations using long-term observations from the astern North Atlantic. Open-cell cases are associated with cold-air outbreaks and occur in deeper boundary layers, with stronger winds and higher rain rates compared to closed-cell cases. These results offer important benchmarks for model representation of boundary layer clouds in this climatically important region.
Florian Tornow, Andrew S. Ackerman, and Ann M. Fridlind
Atmos. Chem. Phys., 21, 12049–12067, https://doi.org/10.5194/acp-21-12049-2021, https://doi.org/10.5194/acp-21-12049-2021, 2021
Short summary
Short summary
Cold air outbreaks affect the local energy budget by forming bright boundary layer clouds that, once it rains, evolve into dimmer, broken cloud fields that are depleted of condensation nuclei – an evolution consistent with closed-to-open cell transitions. We find that cloud ice accelerates this evolution, primarily via riming prior to rain onset, which (1) reduces liquid water, (2) reduces condensation nuclei, and (3) leads to early precipitation cooling and moistening below cloud.
Christopher R. Williams, Karen L. Johnson, Scott E. Giangrande, Joseph C. Hardin, Ruşen Öktem, and David M. Romps
Atmos. Meas. Tech., 14, 4425–4444, https://doi.org/10.5194/amt-14-4425-2021, https://doi.org/10.5194/amt-14-4425-2021, 2021
Short summary
Short summary
In addition to detecting clouds, vertically pointing cloud radars detect individual insects passing over head. If these insects are not identified and removed from raw observations, then radar-derived cloud properties will be contaminated. This work identifies clouds in radar observations due to their continuous and smooth structure in time, height, and velocity. Cloud masks are produced that identify cloud vertical structure that are free of insect contamination.
Thiago S. Biscaro, Luiz A. T. Machado, Scott E. Giangrande, and Michael P. Jensen
Atmos. Chem. Phys., 21, 6735–6754, https://doi.org/10.5194/acp-21-6735-2021, https://doi.org/10.5194/acp-21-6735-2021, 2021
Short summary
Short summary
This study suggests that there are two distinct modes driving diurnal precipitating convective clouds over the central Amazon. In the wet season, local factors such as turbulence and nighttime cloud coverage are the main controls of daily precipitation, while dry-season daily precipitation is modulated primarily by the mesoscale convective pattern. The results imply that models and parameterizations must consider different formulations based on the seasonal cycle to correctly resolve convection.
Israel Silber, Ann M. Fridlind, Johannes Verlinde, Andrew S. Ackerman, Grégory V. Cesana, and Daniel A. Knopf
Atmos. Chem. Phys., 21, 3949–3971, https://doi.org/10.5194/acp-21-3949-2021, https://doi.org/10.5194/acp-21-3949-2021, 2021
Short summary
Short summary
Long-term ground-based radar and sounding measurements over Alaska (Antarctica) indicate that more than 85 % (75 %) of supercooled clouds are precipitating at cloud base and that 75 % (50 %) are precipitating to the surface. Such high prevalence is reconciled with lesser spaceborne estimates by considering radar sensitivity. Results provide a strong observational constraint for polar cloud processes in large-scale models.
Jens Redemann, Robert Wood, Paquita Zuidema, Sarah J. Doherty, Bernadette Luna, Samuel E. LeBlanc, Michael S. Diamond, Yohei Shinozuka, Ian Y. Chang, Rei Ueyama, Leonhard Pfister, Ju-Mee Ryoo, Amie N. Dobracki, Arlindo M. da Silva, Karla M. Longo, Meloë S. Kacenelenbogen, Connor J. Flynn, Kristina Pistone, Nichola M. Knox, Stuart J. Piketh, James M. Haywood, Paola Formenti, Marc Mallet, Philip Stier, Andrew S. Ackerman, Susanne E. Bauer, Ann M. Fridlind, Gregory R. Carmichael, Pablo E. Saide, Gonzalo A. Ferrada, Steven G. Howell, Steffen Freitag, Brian Cairns, Brent N. Holben, Kirk D. Knobelspiesse, Simone Tanelli, Tristan S. L'Ecuyer, Andrew M. Dzambo, Ousmane O. Sy, Greg M. McFarquhar, Michael R. Poellot, Siddhant Gupta, Joseph R. O'Brien, Athanasios Nenes, Mary Kacarab, Jenny P. S. Wong, Jennifer D. Small-Griswold, Kenneth L. Thornhill, David Noone, James R. Podolske, K. Sebastian Schmidt, Peter Pilewskie, Hong Chen, Sabrina P. Cochrane, Arthur J. Sedlacek, Timothy J. Lang, Eric Stith, Michal Segal-Rozenhaimer, Richard A. Ferrare, Sharon P. Burton, Chris A. Hostetler, David J. Diner, Felix C. Seidel, Steven E. Platnick, Jeffrey S. Myers, Kerry G. Meyer, Douglas A. Spangenberg, Hal Maring, and Lan Gao
Atmos. Chem. Phys., 21, 1507–1563, https://doi.org/10.5194/acp-21-1507-2021, https://doi.org/10.5194/acp-21-1507-2021, 2021
Short summary
Short summary
Southern Africa produces significant biomass burning emissions whose impacts on regional and global climate are poorly understood. ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) is a 5-year NASA investigation designed to study the key processes that determine these climate impacts. The main purpose of this paper is to familiarize the broader scientific community with the ORACLES project, the dataset it produced, and the most important initial findings.
Robert Jackson, Scott Collis, Valentin Louf, Alain Protat, Die Wang, Scott Giangrande, Elizabeth J. Thompson, Brenda Dolan, and Scott W. Powell
Atmos. Meas. Tech., 14, 53–69, https://doi.org/10.5194/amt-14-53-2021, https://doi.org/10.5194/amt-14-53-2021, 2021
Short summary
Short summary
About 4 years of 2D video disdrometer data in Darwin are used to develop and validate rainfall retrievals for tropical convection in C- and X-band radars in Darwin. Using blended techniques previously used for Colorado and Manus and Gan islands, with modified coefficients in each estimator, provided the most optimal results. Using multiple radar observables to develop a rainfall retrieval provided a greater advantage than using a single observable, including using specific attenuation.
Johannes Quaas, Antti Arola, Brian Cairns, Matthew Christensen, Hartwig Deneke, Annica M. L. Ekman, Graham Feingold, Ann Fridlind, Edward Gryspeerdt, Otto Hasekamp, Zhanqing Li, Antti Lipponen, Po-Lun Ma, Johannes Mülmenstädt, Athanasios Nenes, Joyce E. Penner, Daniel Rosenfeld, Roland Schrödner, Kenneth Sinclair, Odran Sourdeval, Philip Stier, Matthias Tesche, Bastiaan van Diedenhoven, and Manfred Wendisch
Atmos. Chem. Phys., 20, 15079–15099, https://doi.org/10.5194/acp-20-15079-2020, https://doi.org/10.5194/acp-20-15079-2020, 2020
Short summary
Short summary
Anthropogenic pollution particles – aerosols – serve as cloud condensation nuclei and thus increase cloud droplet concentration and the clouds' reflection of sunlight (a cooling effect on climate). This Twomey effect is poorly constrained by models and requires satellite data for better quantification. The review summarizes the challenges in properly doing so and outlines avenues for progress towards a better use of aerosol retrievals and better retrievals of droplet concentrations.
Cited articles
Arakawa, A. and Schubert, W. H.: Interaction of a cumulus cloud ensemble with the large–scale environment, Part I, J. Atmos. Sci., 31, 674–701, https://doi.org/10.1175/1520-0469(1974)031<0674>2.0.CO;2, 1974.
Bang, S. D. and Cecil, D. J.: Constructing a Multifrequency Passive Microwave Hail Retrieval and Climatology in the GPM Domain, J. Appl. Meteorol. Clim., 58, 1889–1904, https://doi.org/10.1175/JAMC-D-19-0042.1, 2019.
Bergeron, T.: On the physics of cloud and precipitation, Proc. 5th Assembly U.G.G.I., Lisbon, 2, 156, 1935.
Biscaro, T. S., Machado, L. A. T., Giangrande, S. E., and Jensen, M. P.: What drives daily precipitation over the central Amazon? Differences observed between wet and dry seasons, Atmos. Chem. Phys., 21, 6735–6754, https://doi.org/10.5194/acp-21-6735-2021, 2021.
Blyth, A. M. and Latham, J.: Development of ice and precipitation in New Mexican summertime cumulus clouds, Q. J. Roy. Meteor. Soc., 119, 91–120, https://doi.org/10.1002/qj.49711950905, 1993.
Blyth, A. M., Lasher-Trapp, S. G., and Cooper, W. A.: A study of thermals in cumulus clouds, Q. J. Roy. Meteor. Soc., 131, 1171–1190, https://doi.org/10.1256/qj.03.180, 2005.
Borque, P., Vidal, L., Rugna, M., Lang, T. J., Nicora, M. G., and Nesbitt, S. W.: Distinctive Signals in 1-min Observations of Overshooting Tops and Lightning Activity in a Severe Supercell Thunderstorm, J. Geophys. Res.-Atmos., 125, e2020JD032856, https://doi.org/10.1029/2020JD032856, 2020.
Chou, M.-D. and Suarez, M. J.: A solar radiation parameterization for atmospheric studies, NASA Tech. Rep. NASA/TM-1999-10460, NASA GSFC, Vol. 15, p. 38, 1999.
Chou, M.-D. and Suarez, M. J.: A thermal infrared radiation parameterization for atmospheric studies, NASA Tech. Rep. NASA/TM-2001-104606, NASA GSFC, Vol. 19, p. 55, 2001.
Coulter, R., Muradyan, P., and Martin, T.: Radar Wind Profiler (1290RWPPRECIPMOM), Atmospheric Radiation Measurement (ARM) User Facility, mao1290precipmomM1.a0, ARM [data set], https://doi.org/10.5439/1256461, 2024.
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A. C. M., Bidlot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., and Vitart, F.: The ERA-Interim reanalysis: Configuration and performance of the data assimilation system, Q. J. Roy. Meteor. Soc., 137, 553–597, https://doi.org/10.1002/qj.828, 2011.
Dolan, B., Fuchs, B., Rutledge, S. A., Barnes, E. A., and Thompson, E. J.: Primary Modes of Global Drop Size Distributions, J. Atmos. Sci., 75, 1453–1476, https://doi.org/10.1175/JAS-D-17-0242.1, 2018.
Emanuel, K. A., Neelin, J. D., and Bretherton, C. S.: On large-scale circulations in convecting atmospheres, Q. J. Roy. Meteor. Soc., 120, 1111–1143, https://doi.org/10.1002/qj.49712051902, 1994.
Ghate, V. P. and Kollias, P.: On the Controls of Daytime Precipitation in the Amazonian Dry Season, J. Hydrometeorol., 17, 3079–3097, https://doi.org/10.1175/JHM-D-16-0101.1, 2016.
Giangrande, S. E., Luke, E. P., and Kollias, P.: Characterization of Vertical Velocity and Drop Size Distribution Parameters in Widespread Precipitation at ARM Facilities, J. Appl. Meteorol. Clim., 51, 380–391, https://doi.org/10.1175/JAMC-D-10-05000.1, 2012.
Giangrande, S. E., Collis, S., Straka, J., Protat, A., Williams, C., and Krueger, S.: A Summary of Convective-Core Vertical Velocity Properties Using ARM UHF Wind Profilers in Oklahoma, J. Appl. Meteorol. Clim., 52, 2278–2295, https://doi.org/10.1175/JAMC-D-12-0185.1, 2013.
Giangrande, S. E., Toto, T., Jensen, M. P., Bartholomew, M. J., Feng, Z., Protat, A., Williams, C. R., Schumacher, C., and Machado, L.: Convective cloud vertical velocity and mass-flux characteristics from radar wind profiler observations during GoAmazon2014/5, J. Geophys. Res.-Atmos., 121, 12891–12913, https://doi.org/10.1002/2016JD025303, 2016.
Giangrande, S. E., Feng, Z., Jensen, M. P., Comstock, J. M., Johnson, K. L., Toto, T., Wang, M., Burleyson, C., Bharadwaj, N., Mei, F., Machado, L. A. T., Manzi, A. O., Xie, S., Tang, S., Silva Dias, M. A. F., de Souza, R. A. F., Schumacher, C., and Martin, S. T.: Cloud characteristics, thermodynamic controls and radiative impacts during the Observations and Modeling of the Green Ocean Amazon (GoAmazon2014/5) experiment, Atmos. Chem. Phys., 17, 14519–14541, https://doi.org/10.5194/acp-17-14519-2017, 2017.
Giangrande, S. E., Wang, D., and Mechem, D. B.: Cloud regimes over the Amazon Basin: perspectives from the GoAmazon2014/5 campaign, Atmos. Chem. Phys., 20, 7489–7507, https://doi.org/10.5194/acp-20-7489-2020, 2020.
Giangrande, S. E., Biscaro, T. S., and Peters, J. M.: Seasonal controls on isolated convective storm drafts, precipitation intensity, and life cycle as observed during GoAmazon2014/5, Atmos. Chem. Phys., 23, 5297–5316, https://doi.org/10.5194/acp-23-5297-2023, 2023.
Grabowski, W. W. and Petch, J.: Deep Convective Clouds, in: Clouds in the Perturbed Climate System: Their Relationship to Energy Balance, MIT Press, 197–215, https://doi.org/10.7551/mitpress/9780262012874.003.0009, 2009.
Gu, J.-F., Plant, R. S., Holloway, C. E., and Muetzelfeldt, M. R.: Pressure drag for shallow cumulus clouds: From thermals to the cloud ensemble, Geophys. Res. Lett., 47, e2020GL090460, https://doi.org/10.1029/2020GL090460, 2020.
Hartmann, D. L.: Global Physical Climatology, 2nd edn., Academic Press, Cambridge, UK, https://doi.org/10.1016/C2009-0-00030-0, 2016.
Hernandez-Deckers, D. and Sherwood, S. C.: A Numerical Investigation of Cumulus Thermals, J. Atmos. Sci., 73, 4117–4136, https://doi.org/10.1175/JAS-D-15-0385.1, 2016.
Hernandez-Deckers, D. and Sherwood, S. C.: On the Role of Entrainment in the Fate of Cumulus Thermals, J. Atmos. Sci., 75, 3911–3924, https://doi.org/10.1175/JAS-D-18-0077.1, 2018.
Hernandez-Deckers, D., Matsui, T., and Fridlind, A. M.: Updraft dynamics and microphysics: on the added value of the cumulus thermal reference frame in simulations of aerosol–deep convection interactions, Atmos. Chem. Phys., 22, 711–724, https://doi.org/10.5194/acp-22-711-2022, 2022.
Heymsfield, A. J.: Case Study of a Halistorm in Colorado. Part IV: Graupel and Hail Growth Mechanisms Deduced through Particle Trajectory Calculations, J. Atmos. Sci., 40, 1482–1509, https://doi.org/10.1175/1520-0469(1983)040<1482:CSOAHI>2.0.CO;2, 1983.
Holland, G. J., John, L., McBride, R. K., Smith, D. J., Jasper, D., and Keenan, T. D.: The BMRC Australian Monsoon Experiment: AMEX, B. Am. Meteorol. Soc., 67, 1466–1472, https://doi.org/10.1175/1520-0477(1986)067<1466:TBAMEA>2.0.CO;2, 1986.
Iguchi, T., Matsui, T., Tao, W., Khain, A., Phillips, V., Kidd, C., L'Ecuyer, T., Braun, S., and Hou, A.: WRF-SBM simulations of melting layer structure in mixed-phase precipitation events observed during LPVEx, J. Appl. Meteorol. Clim., 53, 2710–2731, https://doi.org/10.1175/JAMC-D-13-0334.1, 2014.
Jeyaratnam, J., Luo, Z. J., Giangrande, S. E., Wang, D., and Masunaga, H.: A satellite-based estimate of convective vertical velocity and convective mass flux: Global survey and comparison with radar wind profiler observations, Geophys. Res. Lett., 48, e2020GL090675, https://doi.org/10.1029/2020GL090675, 2021.
Kanji, Z. A., Ladino, L. A., Wex, H., Boose, Y., Burkert-Kohn, M., Cziczo, D. J., and Krämer, M.: Overview of Ice Nucleating Particles, Meteor. Mon., 58, 1.1–1.33, https://doi.org/10.1175/AMSMONOGRAPHS-D-16-0006.1, 2017.
Keenan, T. D. and Carbone, R. E.: A Preliminary Morphology of Precipitation Systems In Tropical Northern Australia, Q. J. Roy. Meteor. Soc., 118, 283–326, https://doi.org/10.1002/qj.49711850406, 1992.
Kikuchi, H., Suezawa, T., Ushio, T., Takahashi, N., Hanado, H., Nakagawa, K., Osada, M., Maesaka, T., Iwanami, K., Yoshimi, K., and Mizutani, F.: Initial observations for precipitation cores with X-band dual polarized phased array weather radar, IEEE T. Geosci. Remote, 58, 3657–3666, https://doi.org/10.1109/TGRS.2019.2959628, 2020.
Kollias, P., Luke, E. P., Tuftedal, K., Dubois, M., and Knapp, E. J.: Agile Weather Observations using a Dual-Polarization X-band Phased Array Radar, 2022 IEEE Radar Conference (RadarConf22), 21–25 March 2022, New York City, NY, USA, 1–6, https://doi.org/10.1109/RadarConf2248738.2022.9764308, 2022a.
Kollias, P., Palmer, R., Bodine, D., Adachi, T., Bluestein, H., Cho, J., Griffin, C., Houser, J., Kirstetter, P., Kumjian, M., Kurdzo, J., Lee, W., Luke, E., Nesbitt, S., Oue, M., Shapiro, A., Rowe, A., Salazar, J., Tanamachi, R., Tuftedal, K., Wang, X., Zrnić, D., and Treserras, B.: Science Applications of Phased Array Radars, B. Am. Meteorol. Soc., 103, E2370–E2390, https://doi.org/10.1175/BAMS-D-21-0173.1, 2022b.
Korolev, A. and Leisner, T.: Review of experimental studies of secondary ice production, Atmos. Chem. Phys., 20, 11767–11797, https://doi.org/10.5194/acp-20-11767-2020, 2020.
Korolev, A., Heckman, I., Wolde, M., Ackerman, A. S., Fridlind, A. M., Ladino, L. A., Lawson, R. P., Milbrandt, J., and Williams, E.: A new look at the environmental conditions favorable to secondary ice production, Atmos. Chem. Phys., 20, 1391–1429, https://doi.org/10.5194/acp-20-1391-2020, 2020.
Lang, S. E., Tao, W.-K., Chern, J.-D., Wu, D., and Li, X.: Benefits of a fourth ice class in the simulated radar reflectivities of convective systems using a bulk microphysics scheme, J. Atmos. Sci., 71, 3583–3612, https://doi.org/10.1175/JAS-D-13-0330.1, 2014.
Lin, J. C., Matsui, T., Pielke Sr., R. A., and Kummerow, C.: Effects of biomass burning-derived aerosols on precipitation and clouds in the Amazon Basin: A satellite-based empirical study, J. Geophys. Res., 111, D19204, https://doi.org/10.1029/2005JD006884, 2006.
Liu, C. and Zipser, E. J.: The global distribution of largest, deepest, and most intense precipitation systems, Geophys. Res. Lett., 42, 3591–3595, https://doi.org/10.1002/2015GL063776, 2015.
Lucas, C., Zipser, E. J., and Lemone, M. A.: Vertical velocity in oceanic convection off tropical Australia, J. Atmos. Sci., 51, 3183–3193, https://doi.org/10.1175/1520-0469(1994)051<3183:VVIOCO>2.0.CO;2, 1994.
Martin, S., Artaxo, P., Machado, L., Manzi, A., Souza, R., Schumacher, C., Wang, J., Biscaro, T., Brito, J., Calheiros, A., Jardine, K., Medeiros, A., Portela, B., de Sá, S., Adachi, K., Aiken, A., Albrecht, R., Alexander, L., Andreae, M., Barbosa, H., Buseck, P., Chand, D., Comstock, J., Day, D., Dubey, M., Fan, J., Fast, J., Fisch, G., Fortner, E., Giangrande, S., Gilles, M., Goldstein, A., Guenther, A., Hubbe, J., Jensen, M., Jimenez, J., Keutsch, F., Kim, S., Kuang, C., Laskin, A., McKinney, K., Mei, F., Miller, M., Nascimento, R., Pauliquevis, T., Pekour, M., Peres, J., Petäjä, T., Pöhlker, C., Pöschl, U., Rizzo, L., Schmid, B., Shilling, J., Dias, M., Smith, J., Tomlinson, J., Tóta, J., and Wendisch, M. : The Green Ocean Amazon Experiment (GoAmazon2014/5) Observes Pollution Affecting Gases, Aerosols, Clouds, and Rainfall over the Rain Forest, B. Am. Meteorol. Soc., 98, 981–997, https://doi.org/10.1175/BAMS-D-15-00221.1, 2017.
Matsui, T. and Mocko, D. M.: Transpiration and Physical Evaporation: Regional and Seasonal Variability Over the Conterminous United States, in: Encyclopedia of Natural Resources, edited by: Wang, Y. Q., Taylor & Francis Group, New York, 1086 pp., ISBN 9781439852583, 2014.
Matsui, T., Ichoku, C., Randles, C., Yuan, T., da Silva, A., Colarco, P., Kim, D., Levy, R., Sayer, A., Chin, M., Giles, D., Holben, B., Welton, E., Eck, T., and Remer, L.: Current and Future Perspectives of Aerosol Research at NASA Goddard Space Flight Center, BAMS Meeting Summary, 95, ES203–ES207, https://doi.org/10.1175/BAMS-D-13-00153.1, 2014a.
Matsui, T., Santanello, J., Shi, J. J., Tao, K., Wu, D., Peters-Lidard, C., Kemp, E., Chin, M., Starr, D., Sekiguchi, M., and Aires, F.: Introducing multisensor satellite radiance-based evaluation for regional Earth System modeling, J. Geophys. Res.-Atmos., 119, 8450–8475, https://doi.org/10.1002/2013JD021424, 2014b.
Matsui, T., Chern, J., Tao, W., Lang, S., Satoh, M., Hashino, T., and Kubota, T.: On the land–ocean contrast of tropical convection and microphysics statistics derived from TRMM satellite signals and global storm-resolving models, J. Hydrometeorol., 17, 1425–1445, https://doi.org/10.1175/JHM-D-15-0111.1, 2016.
Matsui, T., Zhang, S. Q., Lang, S. E., Tao, W.-K., Liu, Y., Shige, S., and Takayabu, Y. N.: Impact of radiation frequency, precipitation radiative forcing, and radiation column aggregation on convection-permitting West African monsoon simulations, Clim. Dynam., 55, 193–213, https://doi.org/10.1007/s00382-018-4187-2, 2018.
Matsui, T., Dolan, B., Iguchi, T., Rutledge, S. A., Tao, W., and Lang, S.: Polarimetric radar characteristics of simulated and observed intense convective cores for a midlatitude continental and tropical maritime environment, J. Hydrometeorol., 21, 501–517, https://doi.org/10.1175/JHM-D-19-0185.1, 2020.
Matsui, T., Wolff, D. B., Lang, S., Mohr, K., Zhang, M., Xie, S., Tang, S., Saleeby, S. M., Posselt, D. J., Braun, S. A., Chern, D., Dolan, B., Pippitt, J. L., and Loftus, A. M.: Systematic validation of ensemble cloud-process simulations using polarimetric radar observations and simulator over the NASA Wallops Flight Facility, J. Geophys. Res.-Atmos., 128, e2022JD038134, https://doi.org/10.1029/2022JD038134, 2023.
Morrison, H., Peters, J. M., Varble, A. C., Hannah, W. M., and Giangrande, S. E.: Thermal chains and entrainment in cumulus updrafts. Part I: Theoretical description, J. Atmos. Sci., 77, 3637–3660, https://doi.org/10.1175/JAS-D-19-0243.1, 2020.
Morrison, H., Peters, J. M., and Sherwood, S. C.: Comparing Growth Rates of Simulated Moist and Dry Convective Thermals, J. Atmos. Sci., 78, 797–816, https://doi.org/10.1175/JAS-D-20-0166.1, 2021.
Morrison, H., Jeevanjee, N., Lecoanet, D., and Peters, J. M.: What controls the entrainment rate of dry buoyant thermals with varying initial aspect ratio?, J. Atmos. Sci., 80, 2711–2728, https://doi.org/10.1175/JAS-D-23-0063.1, 2023.
Morton, B. R., Taylor, G. I., and Turner, J. S.: Turbulent gravitational convection from maintained and instantaneous sources, Proc. Roy. Soc. London, 234A, 1–23, https://doi.org/10.1098/RSPA.1956.0011, 1956.
NCCS: Code, Goddard [code], https://portal.nccs.nasa.gov/datashare/cloudlibrary/PUB_DATA/GoAmazon_ACP/Code/ (last access: 16 September 2024), 2024a.
NCCS: Data, Goddard [data set], https://portal.nccs.nasa.gov/datashare/cloudlibrary/PUB_DATA/GoAmazon_ACP/Data/ (last access: 16 September 2024), 2024b.
Nelson, S. P.: The influence of storm flow structure on hail growth, J. Atmos. Sci., 40, 1965–1983, https://doi.org/10.1175/1520-0469(1983)040<1965:TIOSFS>2.0.CO;2, 1983.
Öktem, R., Romps, D. M., and Varble, A. C.: No warm-phase invigoration of convection detected during GoAmazon, J. Atmos. Sci., 80, 2345–2364, https://doi.org/10.1175/JAS-D-22-0241.1, 2023.
Peters, J. M., Morrison, H., Varble, A. C., Hannah, W. M., and Giangrande, S. E.: Thermal chains and entrainment in cumulus updrafts. Part II: Analysis of idealized simulations, J. Atmos. Sci., 77, 3661–3681, https://doi.org/10.1175/JAS-D-19-0244.1, 2020.
Pielke, R. A.: Influence of the spatial distribution of vegetation and soils on the prediction of cumulus convective rainfall, Rev. Geophys., 39, 151–177, https://doi.org/10.1029/1999RG000072, 2001.
Pope, M., Jakob, C., and Reeder, M. J.: Regimes of the North Australian wet season, J. Climate, 22, 6699–6715, https://doi.org/10.1175/2009JCLI3057.1, 2009.
Prein, A. F., Ge, M., Valle, A. R., Wang, D., and Giangrande, S. E.: Towards a unified setup to simulate mid-latitude and tropical mesoscale convective systems at kilometer-scales, Earth Space Sci., 9, https://doi.org/10.1029/2022EA002295, 2022.
Ramos-Valle, A. N., Prein, A. F., Ge, M., Wang, D., and Giangrande, S. E.: Grid spacing sensitivities of simulated mid-latitude and tropical mesoscale convective systems in the convective gray zone, J. Geophys. Res.-Atmos., 128, https://doi.org/10.1029/2022JD037043, 2023.
Robinson, F., Sherwood, S., Gerstle, D., Liu, C., and Kirshbaum, D.: Exploring the land-ocean contrast in convective vigor using islands, J. Atmos. Sci., 68, 602–618, https://doi.org/10.1175/2010JAS3558.1, 2011.
Rocha, H. R., Goulden, M., Miller, S. D., Menton, M. C., Pinto, L. D. V. O., Freitas, H. C., and Figueira, A. M. S.: Seasonality of water and heat fluxes over a tropical forest in eastern Amazonia, Ecol. Appl., 14, 22–32, 2004.
Romps, D. M. and Charn, A. B.: Sticky thermals: Evidence for a dominant balance between buoyancy and drag in cloud updrafts, J. Atmos. Sci., 72, 2890–2901, https://doi.org/10.1175/JAS-D-15-0042.1, 2015.
Sherwood, S. C., Hernández-Deckers, D., Colin, M., and Robinson, F.: Slippery thermals and the cumulus entrainment paradox, J. Atmos. Sci., 70, 2426–2442, https://doi.org/10.1175/JAS-D-12-0220.1, 2013.
Steiner, M., Houze Jr., R. A., and Yuter, S. E.: Climatological characterization of three-dimensional storm structure from operational radar and rain gauge data, J. Appl. Meteorol., 34, 1978–2007, 1995.
Stephens, G. L., Vane, D. G., Boain, R. J., Mace, G. G., Sassen, K., Wang, Z., and the CloudSat Science Team: The CloudSat mission and the A-Train: A new dimension of space-based observations of clouds and precipitation, B. Am. Meteorol. Soc., 83, 1771–1790, https://doi.org/10.1175/BAMS-83-12-1771, 2002.
Stolz, D. C., Rutledge, S. A., and Pierce, J. R.: Simultaneous influences of thermodynamics and aerosols on deep convection and lightning in the tropics, J. Geophys. Res.-Atmos., 120, 6207–6231, https://doi.org/10.1002/2014JD023033, 2015.
Sullivan, S. C. and Voigt, A.: Ice microphysical processes exert a strong control on the simulated radiative energy budget in the tropics, Commun. Earth Environ., 2, 137, https://doi.org/10.1038/s43247-021-00206-7, 2021.
Takahashi, H., Luo, Z. J., and Stephens, G. L.: Level of neutral buoyancy, deep convective outflow, and convective core: New perspectives based on 5 years of CloudSat data, J. Geophys. Res.-Atmos., 122, 2958–2969, 2017.
Takahashi, N., Ushio, T., Nakagawa, K.,, Mizutani, F., Iwanami, K., Yamaji, A., Kawagoe, T., Osada, T., Ohta, T., and Kawasaki, M.: Development of multi-parameter phased array weather radar (MP-PAWR) and early detection of torrential rainfall and tornado risk, J. Disaster Res., 14, 235–247, https://doi.org/10.20965/jdr.2019.p0235, 2019.
Takahashi, H., Luo, Z. J., and Stephens, G. L.: Revisiting the entrainment relationship of convective plumes: A perspective from global observations, Geophys. Res. Lett., 48, https://doi.org/10.1029/2020GL092349, 2021.
Tang, S., Xie, S., Zhang, Y., Zhang, M., Schumacher, C., Upton, H., Jensen, M. P., Johnson, K. L., Wang, M., Ahlgrimm, M., Feng, Z., Minnis, P., and Thieman, M.: Large-scale vertical velocity, diabatic heating and drying profiles associated with seasonal and diurnal variations of convective systems observed in the GoAmazon2014/5 experiment, Atmos. Chem. Phys., 16, 14249–14264, https://doi.org/10.5194/acp-16-14249-2016, 2016.
Tao, W.-K., Lang, S., Zeng, X., Li, X., Matsui, T., Mohr, K., Posselt, D., Chern, J., Peters-Lidard, C., Norris, P. M., Kang, I.-S., Choi, I., Hou, A., Lau, K.-M., and Yang, Y.-M.: The Goddard Cumulus Ensemble model (GCE): Improvements and applications for studying precipitation processes, Atmos. Res., 143, 392–424, https://doi.org/10.1016/j.atmosres.2014.03.005, 2014.
Tao, W.-K., Wu, D., Lang, S., Chern, J.-D., Peters-Lidard, C., Fridlind, A., and Matsui, T.: High-resolution NU-WRF simulations of a deep convective-precipitation system during MC3E: Further improvements and comparisons between Goddard microphysics schemes and observations, J. Geophys. Res.-Atmos., 121, 1278–1305, https://doi.org/10.1002/2015JD023986, 2016.
Tao, K., Iguchi, T., Lang, S., Li, X., Mohr, K., Matsui, T., and Braun, S.: Relating vertical velocity and cloud/precipitation properties: A numerical cloud ensemble modeling study of tropical convection, J. Adv. Model. Earth Syst., 14, e2021MS002677, https://doi.org/10.1029/2021MS002677, 2022.
Tokay, A. and Short, D. A.: Evidence from Tropical Raindrop Spectra of the Origin of Rain from Stratiform versus Convective Clouds, J. Appl. Meteorol. Clim., 35, 355–371, https://doi.org/10.1175/1520-0450(1996)035<0355:EFTRSO>2.0.CO;2, 1996.
Wang, D., Giangrande, S. E., Bartholomew, M. J., Hardin, J., Feng, Z., Thalman, R., and Machado, L. A. T.: The Green Ocean: precipitation insights from the GoAmazon2014/5 experiment, Atmos. Chem. Phys., 18, 9121–9145, https://doi.org/10.5194/acp-18-9121-2018, 2018.
Wang, D., Giangrande, S. E., Schiro, K., Jensen, M. P., and Houze, R. A.: The characteristics of tropical and midlatitude mesoscale convective systems as revealed by radar wind profilers, J. Geophys. Res.-Atmos., 124, 4601–4619, https://doi.org/10.1029/2018JD030087, 2019.
Wehr, T., Kubota, T., Tzeremes, G., Wallace, K., Nakatsuka, H., Ohno, Y., Koopman, R., Rusli, S., Kikuchi, M., Eisinger, M., Tanaka, T., Taga, M., Deghaye, P., Tomita, E., and Bernaerts, D.: The EarthCARE mission – science and system overview, Atmos. Meas. Tech., 16, 3581–3608, https://doi.org/10.5194/amt-16-3581-2023, 2023.
Williams, E. and Stanfill, S.: The physical origin of the land–ocean contrast in lightning activity, C. R. Phys., 3, 1277–1292, https://doi.org/10.1016/S1631-0705(02)01407-X, 2002.
Williams, E., Rosenfeld, D., Madden, N., Gerlach, J., Gears, N., Atkinson, L., Dunnemann, N., Frostrom, G., Antonio, M., Biazon, B., Camargo, R., Franca, H., Gomes, A., Lima, M., Machado, R., Manhaes, S., Nachtigall, L., Piva, H., Quintiliano, W., Machado, L., Artaxo, P., Roberts, G., Renno, N., Blakeslee, R., Bailey, J., Boccippio, D., Betts, A., Wolff, D., Roy, B., Halverson, J., Rickenbach, T., Fuentes, J., and Avelino, E.: Contrasting convective regimes over the Amazon: implications for cloud electrification, J. Geophys. Res.-Atmos., 107, 8082, https://doi.org/10.1029/2001JD000380, 2002.
Williams, E., Chan, T., and Boccippio, D.: Islands as miniature continents: Another look at the land–ocean lightning contrast, J. Geophys. Res., 109, D16206, https://doi.org/10.1029/2003JD003833, 2004.
Williams, E., Mushtak, V., Rosenfeld, D., Goodman, S., and Boccippio, D.: Thermodynamic conditions favorable to superlative thunderstorm updraft, mixed phase microphysics and lightning flash rate, Atmos. Res., 76, 288–306, https://doi.org/10.1016/j.atmosres.2004.11.009, 2005.
Williams, C. R., Barrio, J., Johnston, P. E., Muradyan, P., and Giangrande, S. E.: Calibrating radar wind profiler reflectivity factor using surface disdrometer observations, Atmos. Meas. Tech., 16, 2381–2398, https://doi.org/10.5194/amt-16-2381-2023, 2023.
Wu, J., Del Genio, A. D., Yao, M.-S., and Wolf, A. B.: WRF and GISS SCM simulations of convective updraft properties during TWP-ICE, J. Geophys. Res., 114, D04206, https://doi.org/10.1029/2008JD010851, 2009.
Xie, S., Cederwall, R. T., and Zhang, M.: Developing long-term single-column model/cloud system–resolving model forcing data using numerical weather prediction products constrained by surface and top of the atmosphere observations, J. Geophys. Res., 109, D01104, https://doi.org/10.1029/2003JD004045, 2004.
Xie, S., Tao, C., and Zhang, M.: Constrained Variational Analysis (180VARANAECMWFANARADAR), Atmospheric Radiation Measurement (ARM) User Facility, ARM [data set], https://doi.org/10.5439/1879988, 2024.
Xu, X., Sun, C., Lu, C., Liu, Y., Zhang, G. J., and Chen, Q.: Factors affecting entrainment rate in deep convective clouds and parameterizations, J. Geophys. Res.-Atmos., 126, e2021JD034881, https://doi.org/10.1029/2021JD034881, 2021.
Yanai, M., Esbensen, S., and Chu, J.: Determination of Bulk Properties of Tropical Cloud Clusters from Large-Scale Heat and Moisture Budgets, J. Atmos. Sci., 30, 611–627, https://doi.org/10.1175/1520-0469(1973)030<0611:DOBPOT>2.0.CO;2, 1973.
Yuter, S. E. and Houze Jr., R. A.: Three-dimensional kinematic and microphysical evolution of Florida cumulonimbus. Part II: Frequency distribution of vertical velocity, reflectivity, and differential reflectivity, Mon. Weather Rev., 123, 1941–1963, 1995.
Zhang, M. and Lin, J.: Constrained variational analysis of sounding data based on column-integrated budgets of mass, heat, moisture, and momentum: Approach and application to ARM measurements, J. Atmos. Sci., 54, 1503–1524, https://doi.org/10.1175/1520-0469(1997)054<1503:CVAOSD>2.0.CO;2, 1997.
Zhang, M., Lin, J., Cederwall, R. T., Yio, J. J., and Xie, S. C.: Objective analysis of ARM IOP data: Method and sensitivity, Mon. Weather Rev., 129, 295–311, https://doi.org/10.1175/1520-0493(2001)129<0295:OAOAID>2.0.CO;2, 2001.
Ziegler, C. L., Ray, P. S., and Knight, N. C.: Hail growth in an Oklahoma multicell storm, J. Atmos. Sci., 40, 1768–1791, https://doi.org/10.1175/1520-0469(1983)040<1768:HGIAOM>2.0.CO;2, 1983.
Zipser, E. J., Liu, C., Cecil, D. J., Nesbitt, S. W., and Yorty, D. P.: Where are the most intense thunderstorms on Earth?, B. Am. Meteorol. Soc., 87, 1057–1071, https://doi.org/10.1175/BAMS-87-8-1057, 2006.
Short summary
Using computer simulations and real measurements, we discovered that storms over the Amazon were narrower but more intense during the dry periods, producing heavier rain and more ice particles in the clouds. Our research showed that cumulus bubbles played a key role in creating these intense storms. This study can improve the representation of the effect of continental and ocean environments on tropical regions' rainfall patterns in simulations.
Using computer simulations and real measurements, we discovered that storms over the Amazon were...
Altmetrics
Final-revised paper
Preprint