Articles | Volume 21, issue 21
https://doi.org/10.5194/acp-21-16143-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-21-16143-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
02 Nov 2021
Research article |
| 02 Nov 2021
| 02 Nov 2021
Impact of hygroscopic seeding on the initiation of precipitation formation: results of a hybrid bin microphysics parcel model
Istvan Geresdi
Faculty of Science Pécs, University of Pécs, Pécs, Hungary
National Center for Atmospheric Research, Boulder, USA
Hua Xin Chuang Zhi Sci. & Tech. LLC, Beijing, China
Sisi Chen
National Center for Atmospheric Research, Boulder, USA
Youssef Wehbe
National Center of Meteorology, Abu Dhabi 4815, UAE
Roelof Bruintjes
National Center for Atmospheric Research, Boulder, USA
Jared A. Lee
National Center for Atmospheric Research, Boulder, USA
Roy M. Rasmussen
National Center for Atmospheric Research, Boulder, USA
Wojciech W. Grabowski
National Center for Atmospheric Research, Boulder, USA
Noemi Sarkadi
Faculty of Science Pécs, University of Pécs, Pécs, Hungary
Sarah A. Tessendorf
National Center for Atmospheric Research, Boulder, USA
Related authors
No articles found.
Patrick C. Taylor, Armin Sorooshian, Rei Ueyama, Sebastian Schmidt, Ihab Abboud, Quincy Allison, Kevin Barry, Sebastian Becker, Holly A. Bender, Joseph R. Bennett, James B. Blair, Niklas Bohn, Linette Boisvert, Matthew D. Brown, Roelof Bruintjes, Anthony Bucholtz, Megan Buzanowicz, Brian Cairns, Filippo Calì Quaglia, Eduard Chemyakin, Bo Chen, Gao Chen, Hong Chen, Yu-Wen Chen, Zezhen Cheng, Swarup China, Dan Chirica, Yonghoon Choi, Peter Colarco, Brian Collister, Ewan Crosbie, Maurice J. Cross, Janet Daniels, Paul DeMott, Joshua P. DiGangi, Alcide Giorgio di Sarra, Glenn S. Diskin, Erica K. Dolinar, Eva-Lou Edwards, Samuel Ephraim, Nikolaos Evangeliou, Romanos Foskinis, Francesca Gallo, Lan Gao, José Luis Gómez-Amo, Daisy Gonzalez, Christine Groot Zwaaftink, Pawan Gupta, Ivan Heckman, Michael Hendrickson, Miguel Ricardo A. Hilario, Ken Hirata, Michelle Hofton, Andrew L. Holen, Ulas Im, Alia L. Khan, Ralph Kahn, Alexei V. Korolev, Sonia Kreidenweis, Thomas Krumpen, Nathan Kurtz, Leslie Lait, Bradley Lamkin, Jack Landy, Nurun Nahar Lata, Paul Lawson, Samuel LeBlanc, Sean Leavor, Jing Li, Thorsten Markus, Hal Maring, Andreas H. Massling, Camille Mavis, Flynn McGinnity, Kerry Meyer, Gabriel Mojica, Richard H. Moore, Parker Morris, Giovanni Muscari, Vikas Nataraja, Amin R. Nehrir, Athanasios Nenes, Edward P. Nowottnick, Matteo Ottaviani, Chelsea Parker, Ryan Patnaude, Michael Perez, Russell J. Perkins, Colten Peterson, Alek Petty, Stevie Phothisane, Chris Polashenski, Kerri A. Pratt, Kayla M. Preisler, John Prytherch, David Rabine, Jens Redemann, Ju-Mee Ryoo, Joseph S. Schlosser, Vanessa Selimovic, Michael A. Shook, Morgan Silverman, Henrik Skov, Alexander Smirnov, Cassidy Soloff, Amy Solomon, Snorre Stamnes, Azusa Takeishi, David R. Thompson, K. Lee Thornhill, Rachel Tilling, Michael Tjernström, Monica Tosco, Pedro C. Valdelomar, David Van Gilst, Jian Wang, Zhien Wang, Andrzej Wasilewski, Manfred Wendisch, Brent Wilder, Edward L. Winstead, Albert Wu, Peng Xian, Lauren M. Zamora, Jiaoshi Zhang, Lei Zhang, Lu Zhang, Luke Ziemba, and Paquita Zuidema
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2026-241, https://doi.org/10.5194/essd-2026-241, 2026
Preprint under review for ESSD
Short summary
Short summary
This article summarizes the data sets collected during the Arctic Radiation Cloud aerosol Sea ice Interaction eXperiment (ARCSIX), NASA's most comprehensive Arctic field campaign to date. The overarching goal was to quantify the contributions of surface, clouds, aerosol particles, and precipitation to summer sea ice melt. This paper describes the ARCSIX implementation including the flight strategy, instruments, complementary data sets, access, and usage details.
Sisi Chen, Lulin Xue, Michelle Harrold, Sarah Tessendorf, Jamie Wolff, Nick Dawson, and Darcy Jacobson
EGUsphere, https://doi.org/10.5194/egusphere-2026-3289, https://doi.org/10.5194/egusphere-2026-3289, 2026
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
Glaciogenic seeding is used in winter mountains to enhance snowpack and address water scarcity. Liquid propane seeding, a type of glaciogenic seeding, generates ice in relatively warm conditions where silver iodide is less effective, yet no models exist to simulate its impacts. We built a liquid propane seeding module in a weather model and tested it over idealized mountains. Simulations show snow enhancement is strongest where clouds are rich in supercooled liquid and rain formation is weak.
Inyeob La, Wojciech W. Grabowski, Yongjoon Kim, Sanggyeom Kim, and Seong Soo Yum
Atmos. Chem. Phys., 26, 5213–5235, https://doi.org/10.5194/acp-26-5213-2026, https://doi.org/10.5194/acp-26-5213-2026, 2026
Short summary
Short summary
We ask how the amount of aerosol particles shapes cloud structure. Using computer simulations of a laboratory cloud chamber, we varied aerosol levels and tracked droplet growth. When aerosols are few, cloud water increases with height; when many, it becomes almost uniform because vapor is used up near the bottom. These findings clarify when upward motions matter and guide chamber design and better cloud treatment in weather and climate models.
Timothy W. Juliano, Florian Tornow, Ann M. Fridlind, Andrew S. Ackerman, Gregory S. Elsaesser, Bart Geerts, Christian P. Lackner, David Painemal, Israel Silber, Mikhail Ovchinnikov, Gunilla Svensson, Michael Tjernström, Peng Wu, Alejandro Baró Pérez, Peter Bogenschutz, Dmitry Chechin, Kamal Kant Chandrakar, Jan Chylik, Andrey Debolskiy, Rostislav Fadeev, Anu Gupta, Luisa Ickes, Michail Karalis, Martin Köhler, Branko Kosovic, Peter Kuma, Weiwei Li, Evgeny Mortikov, Hugh Morrison, Roel A. J. Neggers, Anna Possner, Tomi Raatikainen, Lea Raillard, Sami Romakkaniemi, Niklas Schnierstein, Shin-ichiro Shima, Nikita Silin, Mikhail Tolstykh, Étienne Vignon, Lulin Xue, Meng Zhang, and Xue Zheng
EGUsphere, https://doi.org/10.5194/egusphere-2026-1237, https://doi.org/10.5194/egusphere-2026-1237, 2026
Short summary
Short summary
Models struggle to capture cloud and precipitation processes and their radiative effects in marine cold-air outbreaks. We use a quasi-Lagrangian framework to compare large-eddy simulation (LES) and single-column model (SCM) output with field and satellite observations. With fixed droplet and ice numbers, LES and SCM agree in liquid-only tests. In mixed-phase conditions, LES plausibly capture cloud thinning and breakup, while SCMs largely remain overcast and thereby miss cloud radiative effects.
Yufei Chu, Guo Lin, Min Deng, Lulin Xue, Weiwei Li, Hyeyum Hailey Shin, Jun A. Zhang, Hanqing Guo, and Zhien Wang
Atmos. Chem. Phys., 26, 1415–1434, https://doi.org/10.5194/acp-26-1415-2026, https://doi.org/10.5194/acp-26-1415-2026, 2026
Short summary
Short summary
We developed a new machine learning approach to estimate the height of the mixing layer in the lower atmosphere, which is important for predicting weather and air quality. By using daily temperature and heat patterns, the model learns how the atmosphere changes throughout the day. It gives accurate results across different locations and seasons, helping improve future climate and weather forecasts through better understanding of surface–atmosphere interactions.
Timothy W. Juliano, Florian Tornow, Ann M. Fridlind, Andrew S. Ackerman, Gregory S. Elsaesser, Bart Geerts, Christian P. Lackner, David Painemal, Israel Silber, Mikhail Ovchinnikov, Gunilla Svensson, Michael Tjernström, Peng Wu, Alejandro Baró Pérez, Peter Bogenschutz, Dmitry Chechin, Kamal Kant Chandrakar, Jan Chylik, Andrey Debolskiy, Rostislav Fadeev, Anu Gupta, Luisa Ickes, Michail Karalis, Martin Köhler, Branko Kosović, Peter Kuma, Weiwei Li, Evgeny Mortikov, Hugh Morrison, Roel A. J. Neggers, Anna Possner, Tomi Raatikainen, Sami Romakkaniemi, Niklas Schnierstein, Shin-ichiro Shima, Nikita Silin, Mikhail Tolstykh, Lulin Xue, Meng Zhang, and Xue Zheng
EGUsphere, https://doi.org/10.5194/egusphere-2025-6217, https://doi.org/10.5194/egusphere-2025-6217, 2026
Preprint archived
Short summary
Short summary
Models struggle to capture cloud and precipitation processes and their radiative effects in marine cold-air outbreaks. We use a quasi-Lagrangian framework to compare large-eddy simulation (LES) and single-column model (SCM) output with field and satellite observations. With fixed droplet and ice numbers, LES and SCM agree in liquid-only tests. In mixed-phase conditions, LES plausibly capture cloud thinning and breakup, while SCMs largely remain overcast and thereby miss cloud radiative effects.
Damian K. Wójcik, Michał Z. Ziemiański, and Wojciech W. Grabowski
Weather Clim. Dynam., 6, 1769–1795, https://doi.org/10.5194/wcd-6-1769-2025, https://doi.org/10.5194/wcd-6-1769-2025, 2025
Short summary
Short summary
Representation of severe convection is a challenge for numerical weather prediction models. We show that an explicit stochastic convection initiation scheme, mimicking effects of initial convective cells, allows representation of the isolated bow echo, exposing its cold-pool-driven dynamics, formation of the rear inflow jet, and strong surface winds. The reconstruction delays the strongest gusts by almost an hour, and insufficiently represents continuous linear arrangement of convective cells.
Meilian Chen, Xiaoqin Jing, Jiaojiao Li, Jing Yang, Xiaobo Dong, Bart Geerts, Yan Yin, Baojun Chen, Lulin Xue, Mengyu Huang, Ping Tian, and Shaofeng Hua
Atmos. Chem. Phys., 25, 7581–7596, https://doi.org/10.5194/acp-25-7581-2025, https://doi.org/10.5194/acp-25-7581-2025, 2025
Short summary
Short summary
Several recent studies have reported complete cloud glaciation induced by airborne-based glaciogenic cloud seeding over plains. Since turbulence is an important factor to maintain clouds in a mixed phase, it is hypothesized that turbulence may have an impact on the seeding effect. This hypothesis is evident in the present study, which shows that turbulence can accelerate the impact of airborne glaciogenic seeding of stratiform clouds.
Sisi Chen, Lulin Xue, Sarah A. Tessendorf, Thomas Chubb, Andrew Peace, Suzanne Kenyon, Johanna Speirs, Jamie Wolff, and Bill Petzke
Atmos. Chem. Phys., 25, 6703–6724, https://doi.org/10.5194/acp-25-6703-2025, https://doi.org/10.5194/acp-25-6703-2025, 2025
Short summary
Short summary
This study aims to investigate how cloud seeding affects snowfall in Australia's Snowy Mountains. By running simulations with different setups, we found that seeding impact varies greatly with weather conditions. Seeding increased snow in stable weather but sometimes reduced it in stormy weather. This helps us to better understand when seeding works best to boost water supplies.
Wojciech W. Grabowski and Hanna Pawlowska
Atmos. Chem. Phys., 25, 5273–5285, https://doi.org/10.5194/acp-25-5273-2025, https://doi.org/10.5194/acp-25-5273-2025, 2025
Short summary
Short summary
A simple diagram to depict cloud droplets' formation via the activation of cloud condensation nuclei (CCN) as well as their subsequent growth and evaporation is presented.
Aaron Wang, Steve Krueger, Sisi Chen, Mikhail Ovchinnikov, Will Cantrell, and Raymond A. Shaw
Atmos. Chem. Phys., 24, 10245–10260, https://doi.org/10.5194/acp-24-10245-2024, https://doi.org/10.5194/acp-24-10245-2024, 2024
Short summary
Short summary
We employ two methods to examine a laboratory experiment on clouds with both ice and liquid phases. The first assumes well-mixed properties; the second resolves the spatial distribution of turbulence and cloud particles. Results show that while the trends in mean properties generally align, when turbulence is resolved, liquid droplets are not fully depleted by ice due to incomplete mixing. This underscores the threshold of ice mass fraction in distinguishing mixed-phase clouds from ice clouds.
Chongzhi Yin, Shin-ichiro Shima, Lulin Xue, and Chunsong Lu
Geosci. Model Dev., 17, 5167–5189, https://doi.org/10.5194/gmd-17-5167-2024, https://doi.org/10.5194/gmd-17-5167-2024, 2024
Short summary
Short summary
We investigate numerical convergence properties of a particle-based numerical cloud microphysics model (SDM) and a double-moment bulk scheme for simulating a marine stratocumulus case, compare their results with model intercomparison project results, and present possible explanations for the different results of the SDM and the bulk scheme. Aerosol processes can be accurately simulated using SDM, and this may be an important factor affecting the behavior and morphology of marine stratocumulus.
Adam C. Varble, Adele L. Igel, Hugh Morrison, Wojciech W. Grabowski, and Zachary J. Lebo
Atmos. Chem. Phys., 23, 13791–13808, https://doi.org/10.5194/acp-23-13791-2023, https://doi.org/10.5194/acp-23-13791-2023, 2023
Short summary
Short summary
As atmospheric particles called aerosols increase in number, the number of droplets in clouds tends to increase, which has been theorized to increase storm intensity. We critically evaluate the evidence for this theory, showing that flaws and limitations of previous studies coupled with unaddressed cloud process complexities draw it into question. We provide recommendations for future observations and modeling to overcome current uncertainties.
Cenlin He, Prasanth Valayamkunnath, Michael Barlage, Fei Chen, David Gochis, Ryan Cabell, Tim Schneider, Roy Rasmussen, Guo-Yue Niu, Zong-Liang Yang, Dev Niyogi, and Michael Ek
Geosci. Model Dev., 16, 5131–5151, https://doi.org/10.5194/gmd-16-5131-2023, https://doi.org/10.5194/gmd-16-5131-2023, 2023
Short summary
Short summary
Noah-MP is one of the most widely used open-source community land surface models in the world, designed for applications ranging from uncoupled land surface and ecohydrological process studies to coupled numerical weather prediction and decadal climate simulations. To facilitate model developments and applications, we modernize Noah-MP by adopting modern Fortran code and data structures and standards, which substantially enhance model modularity, interoperability, and applicability.
Sisi Chen, Lulin Xue, Sarah Tessendorf, Kyoko Ikeda, Courtney Weeks, Roy Rasmussen, Melvin Kunkel, Derek Blestrud, Shaun Parkinson, Melinda Meadows, and Nick Dawson
Atmos. Chem. Phys., 23, 5217–5231, https://doi.org/10.5194/acp-23-5217-2023, https://doi.org/10.5194/acp-23-5217-2023, 2023
Short summary
Short summary
The possible mechanism of effective ice growth in the cloud-top generating cells in winter orographic clouds is explored using a newly developed ultra-high-resolution cloud microphysics model. Simulations demonstrate that a high availability of moisture and liquid water is critical for producing large ice particles. Fluctuations in temperature and moisture down to millimeter scales due to cloud turbulence can substantially affect the growth history of the individual cloud particles.
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
Short summary
Short summary
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.
Wojciech W. Grabowski and Hugh Morrison
Atmos. Chem. Phys., 21, 13997–14018, https://doi.org/10.5194/acp-21-13997-2021, https://doi.org/10.5194/acp-21-13997-2021, 2021
Short summary
Short summary
The paper provides a discussion of key elements of moist convective dynamics: cloud buoyancy, latent heating, precipitation, and entrainment. The motivation comes from recent discussions concerning differences in convective dynamics in polluted and pristine environments.
Youssef Wehbe, Sarah A. Tessendorf, Courtney Weeks, Roelof Bruintjes, Lulin Xue, Roy Rasmussen, Paul Lawson, Sarah Woods, and Marouane Temimi
Atmos. Chem. Phys., 21, 12543–12560, https://doi.org/10.5194/acp-21-12543-2021, https://doi.org/10.5194/acp-21-12543-2021, 2021
Short summary
Short summary
The role of dust aerosols as ice-nucleating particles is well established in the literature, whereas their role as cloud condensation nuclei is less understood, particularly in polluted desert environments. We analyze coincident aerosol size distributions and cloud particle imagery collected over the UAE with a research aircraft. Despite the presence of ultra-giant aerosol sizes associated with dust, an active collision–coalescence process is not observed within the limited depths of warm cloud.
Trude Eidhammer, Adam Booth, Sven Decker, Lu Li, Michael Barlage, David Gochis, Roy Rasmussen, Kjetil Melvold, Atle Nesje, and Stefan Sobolowski
Hydrol. Earth Syst. Sci., 25, 4275–4297, https://doi.org/10.5194/hess-25-4275-2021, https://doi.org/10.5194/hess-25-4275-2021, 2021
Short summary
Short summary
We coupled a detailed snow–ice model (Crocus) to represent glaciers in the Weather Research and Forecasting (WRF)-Hydro model and tested it on a well-studied glacier. Several observational systems were used to evaluate the system, i.e., satellites, ground-penetrating radar (used over the glacier for snow depth) and stake observations for glacier mass balance and discharge measurements in rivers from the glacier. Results showed improvements in the streamflow projections when including the model.
Cited articles
Abade, G. C., Grabowski, W. W., and Pawlowska, H.: Broadening of cloud
droplet spectra through eddy hopping: turbulent entraining parcel
simulations, J. Atmos. Sci., 74, 1485–1493, https://doi.org/10.1175/JAS-D-18-0078.1, 2018.
Bermeo, M., Hadri, N. E., Ravaux, F., Zaki, A., Zou, L., and Jouiad, M.: Adsorption Capacities of Hygroscopic Materials Based on NaCl−TiO2 and NaCl−SiO2 Core/Shell Particles, Journal of Nanotechnology, 2020, 1–16, https://doi.org/10.1155/2020/3683629, 2020.
Blyth, A. M. and Latham, J.: An airborne study of vertical structure and microphysical variability within a small cumulus, Q. J. R. Meteorol. Soc., 111, 773-–792, https://doi.org/10.1002/qj.49711146907, 1985.
Brooks, S., Wise, M., Cushing, M., and Tolbert, M. A.: Deliquescence behavior of organic/ammonium sulfate aerosol, Geophys. Res. Lett., 29,
23-1–23-4, https://doi.org/10.1029/2002GL014733, 2002.
Bruintjes, R. T.: A Review of Cloud Seeding Experiments to Enhance
Precipitation and Some New Prospects, Bull. Am. Meteorol. Soc., 80,
805–820, https://doi.org/10.1175/1520-0477(1999)080<0805:AROCSE>2.0.CO;2, 1999.
Bruintjes, R. T., Salazar, V., Semeniuk, T. A., Buseck, P., Breed, D. W., and
Gunkelman, J.: Evaluation of Hygroscopic Cloud Seeding Flares,
Journal of Weather Modification, 44, 69–94, 2012.
Cooper, W. A., Bruintjes, R. T., and Mather, G. K.: Some calculations
pertaining to hygroscopic seeding with flares, J. Appl. Meteor., 36,
1449–1469, https://doi.org/10.1175/1520-0450(1997)036<1449:CPTHSW>2.0.CO;2, 1997.
Flossmann, A. I. and Wobrock, W.: A review of our understanding of the
aerosol–cloud interaction from the perspective of a bin resolved cloud
scale modelling, Atmos. Res., 97, 478–497,
https://doi.org/10.1016/j.atmosres.2010.05.008, 2010.
Flossmann, A. I., Manton, M., Abshaev, A., Bruintjes, R., Murakami, M.,
Prabhakaran, T., and Yao, Z.: Review of Advances in Precipitation Enhancement
Research, Bull. Am. Meteor. Soc., 100, 1465–1480,
https://doi.org/10.1175/BAMS-D-18-0160.1, 2019.
Geresdi, I. and Rasmussen, R.: Freezing drizzle formation in stably
stratified layer clouds, Part II: The role of giant nuclei and aerosol
particle size distribution, J. Atmos. Sci., 62, 2037–2057, https://doi.org/10.1175/JAS3452.1, 2005.
Geresdi, I., Xue, L., and Rasmussen, R.: Evaluation of Orographic Cloud Seeding
Using Bin Microphysics Scheme: Two-dimensional approach, J. Appl. Met.
Clim., 56, 1443–1462, https://doi.org/10.1175/JAMC-D-16-0045.1, 2017.
Grabowski, W. W. and Abade, G. C.: Broadening of cloud droplet spectra
through eddy hopping: Turbulent adiabatic parcel simulations, J. Atmos.
Sci., 74, 1485–1493, https://doi.org/10.1175/JAS-D-17-0043.1, 2017.
Grabowski, W. W. and Wang, L.-P.: Diffusional and accretional growth of water drops in a rising adiabatic parcel: effects of the turbulent collision kernel, Atmos. Chem. Phys., 9, 2335–2353, https://doi.org/10.5194/acp-9-2335-2009, 2009.
Grabowski, W. W., Morrison, H., Shima, S. I., Abade, G. C., Dziekan, P., and
Pawlowska, H.: Modeling of Cloud Microphysics: Can We Do Better?, Bull.
Am. Meteor. Soc., 100, 655–672, https://doi.org/10.1175/BAMS-D-18-0005.1,
2019.
Jensen, J. B. and Lee, S.: Giant sea-salt aerosols and warm rain formation
in marine stratocumulus, J. Atmos. Sci. 65, 3678–3694, https://doi.org/10.1175/2008JAS2617.1, 2008.
Klinger, C., Feingold, G., and Yamaguchi, T.: Cloud droplet growth in shallow cumulus clouds considering 1-D and 3-D thermal radiative effects, Atmos. Chem. Phys., 19, 6295–6313, https://doi.org/10.5194/acp-19-6295-2019, 2019.
Kogan, Y. L.: The simulation of a convective cloud in a 3D model with
explicit microphysics. Part I: Model description and sensitivity
experiments, J. Atmos. Sci., 48, 1160–1189, https://doi.org/10.1175/1520-0469(1991)048<1160:TSOACC>2.0.CO;2, 1991.
Kuba, N. and Murakami, M.: Effect of hygroscopic seeding on warm rain clouds – numerical study using a hybrid cloud microphysical model, Atmos. Chem. Phys., 10, 3335–3351, https://doi.org/10.5194/acp-10-3335-2010, 2010.
Lasher-Trapp, S. G., Cooper, W. A., and Blyth, A. M.: Broadening of droplet
size distributions from entrainment and mixing in a cumulus cloud, Q. J. Roy.
Meteorol. Soc., 131, 195–220, https://doi.org/10.1256/qj.03.199, 2005.
Lee, J. A., Wehbe, Y., Liu, C., Tessendorf, S. A., Weeks, C., Chen, S.,
Bruintjes, R., Rasmussen, R. M., and Xue, L.: Sensitivity study of 1 km
WRF configurations and aerosol loading on convective initiation over the Al
Hajar Mountains, 13th Symp. on Aerosol-Cloud-Climate Interactions, Amer. Meteor. Soc. [Virtual Meeting], 6.9, available at: https://ams.confex.com/ams/101ANNUAL/meetingapp.cgi/Paper/383772 (last access: 19 October 2021), 2021.
Lompar, M., Ćurić, M., Romanic, D., Zou, L., and Liang, H.: Precipitation enhancement by cloud seeding using the shell structured
Mather, G. K., Terblanche, D. E., Steffens, F. E., and Fletcher, L.: Results
of the South African cloud-seeding experiments using hygroscopic flares, J.
Appl. Meteor., 36, 1433–1447, 1997.
Mazroui, A. A. and Farrah, S.: The UAE seeks leading position in global rain
enhancement research, Journal of Weather Modification, 49, 54–59, 2017.
Morrison, H., van Lier-Walqui, M., Fridlind, A. M., Grabowski, W. W.,
Harrington, J. Y., Hoose, C., Korolev, A., Kumjian, M. R., Milbrandt, J. A.,
Pawlowska, H., Posselt, D. J., Prat, O. P., Reimel, K. J., Shima, S., van
Diedenhoven, B., and Xue, L.: Confronting the challenge of modeling cloud and
precipitation microphysics, J. Adv. Model. Earth Sy., 12, 1–68,
https://doi.org/10.1029/2019MS001689, 2020.
Petters, M. D. and Kreidenweis, S. M.: A single parameter representation of hygroscopic growth and cloud condensation nucleus activity, Atmos. Chem. Phys., 7, 1961–1971, https://doi.org/10.5194/acp-7-1961-2007, 2007.
Rasmussen, R., Geresdi, I., Thompson, G., Manning, K., and Karplus, E.: Freezing drizzle formation in stably stratified layer clouds, Part I:
The role of radiative cooling of cloud droplets, cloud condensation nuclei,
and ice initiation, J. Atmos. Sci., 59, 837–860,
https://doi.org/10.1175/1520-0469(2002)059<0837:FDFISS>2.0.CO;2, 2002.
Reisin, T., Levin, Z., and Tzivion, S.: Rain production in convective clouds
as simulated in an axisymmetric model with detailed microphysics, Part I:
description of the model, J. Atmos. Sci. 53, 497–519,
https://doi.org/10.1175/1520-0469(1996)053<0497:RPICCA>2.0.CO;2, 1996.
Rogers, R. R. and Yau, M. K.: A short course in cloud physics, 3rd edition, Elsevier, Oxford, UK, ISBN 0-7506-3215-1, 1996.
Segal, Y., Khain, A., Pinsky, M., and Rosenfeld, D.: Effects of hygroscopic
seeding on raindrop formation as seen from simulations using a 2000-bin
spectral cloud parcel model, Atmos. Res., 71, 3–34,
https://doi.org/10.1016/j.atmosres.2004.03.003, 2004.
Segal, Y., Pinsky, M., and Khain, A.: The role of competition effect in the
raindrop formation, Atmos. Res., 83, 106–118,
https://doi.org/10.1016/j.atmosres.2006.03.007, 2007.
Semeniuk, T. A., Bruintjes, R. T., Salazar, V., Breed, D. W., Jensen, T. L.,
and Buseck, P. R.: Individual aerosol particles in ambient and updraft
conditions below convective cloud bases in the Oman mountain region, J.
Geophys. Res.-Atmos., 119, 2511–2528, https://doi.org/10.1002/2013JD021165, 2014.
Tai, Y., Liang, H., Zaki, A., El Hadri, N., Abshaev, A. M., Huchunaev, B. M.,
Griffiths, S., Jouiad, M., and Zou, L.: Core/shell microstructure induced
synergistic effect for efficient water-droplet formation and cloud-seeding
application, ACS Nano, 11, 12318–12325,
https://doi.org/10.1021/acsnano.7b06114, 2017.
Tessendorf, S. A., Bruintjes, R. T., Weeks, C., Wilson, J. W., Knight, C. A., Roberts, R. D., Peter, J. R., Collis, S., Buseck, P. R., Freney, E., Dixon, M., Pocernich, M., Ikeda, K., Axisa, D., Nelson, E., May, P. T., Richter, H., Piketh, S., Burger, R. P., Wilson, L., Siems, S. T., Manton, M., Stone, R. C., Pepler, A., Collins, D. R., Bringi, V. N., Thurai, M., Turner, L., and McRae, D.: The Queensland Cloud Seeding Research Program, B. Am. Meteorol. Soc., 93, 75–90, https://doi.org/10.1175/BAMS-D-11-00060.1, 2012.
Tessendorf, S. A., Chen, S., Weeks, C., Bruintjes, R., Rasmussen, R. M., and
Xue, L.: The influence of hygroscopic flare seeding on drop
size distribution over southeast Queensland, J. Geophys. Res.-Atmos.,
126, 1–15, https://doi.org/10.1029/2020JD033771, 2021.
Tölle, M. H. and Krueger, S. K.: Effects of entrainment and mixing on
droplet size distributions in warm cumulus clouds, J. Adv. Model. Earth
Sys., 6, 281–299, https://doi.org/10.1002/2012MS000209, 2014
Wehbe, Y., Tessendorf, S. A., Weeks, C., Bruintjes, R., Xue, L., Rasmussen, R., Lawson, P., Woods, S., and Temimi, M.: Analysis of aerosol–cloud interactions and their implications for precipitation formation using aircraft observations over the United Arab Emirates, Atmos. Chem. Phys., 21, 12543–12560, https://doi.org/10.5194/acp-21-12543-2021, 2021.
Wise, M. E., Semeniuk, T. A., Bruintjes, R., Martin, S. T., Russell, L. M.,
and Buseck, P. R.: Hygroscopic behavior of NaCl-bearing natural aerosol
particles using environmental transmission electron microscopy, J. Geophys.
Res., 112, D10224, https://doi.org/10.1029/2006JD007678, 2007.
Witte, M. K., Ayala, O., Wang, L.-P., Bott, A., and Chuang, P. Y.: Estimating
collision-coalescence rates from in situ observations of marine
stratocumulus, Q. J. Roy. Meteor. Soc., 143, 2755–2763, https://doi.org/10.1002/qj.3124, 2017.
Xue, L., Teller, A., Rasmussen, R., Geresdi, I., and Pan, Z.: Effects of
solubility and regenerated aerosols on warm-phase orographic clouds and
precipitation simulated by a detailed bin microphysical scheme coupled with
WRF, J. Atmos. Sci., 67, 3336–3354, https://doi.org/10.1175/2010JAS3511.1,
2010.
Xue, L., Teller, A., Rasmussen, R., Geresdi, I., Pan, Z., and Xiaodong, L.:
Effects of solubility and regenerated aerosols on mixed-phase orographic
clouds and precipitation simulated by a detailed bin microphysical scheme
coupled with WRF, J. Atmos. Sci., 69, 1994–2010,
https://doi.org/10.1175/JAS-D-11-098.1, 2012.
Yang, F., Kollias, P., Shaw, R. A., and Vogelmann, A. M.: Cloud droplet size distribution broadening during diffusional growth: ripening amplified by deactivation and reactivation, Atmos. Chem. Phys., 18, 7313–7328, https://doi.org/10.5194/acp-18-7313-2018, 2018.
Yin, Y., Levin, Z., Reisin, T. G., and Tzivion, S.: The effects of giant
cloud condensation nuclei on the development of precipitation in convective
clouds–A numerical study, Atmos. Res., 53, 93–116, https://doi.org/10.1016/S0169-8095(99)00046-0, 2000.
Yum, S. S. and Hudson, J. G.: Cloud microphysical relationships in warm
clouds, Atmos. Res., 57, 81–104, 2001.
Yum, S. S. and Hudson, J. G.: Adiabatic predictions and observations of
cloud droplet spectral broadness, Atmos. Res., 73, 203–223, 2005.
Short summary
By releasing soluble aerosols into the convective clouds, cloud seeding potentially enhances rainfall. The seeding impacts are hard to quantify with observations only. Numerical models that represent the detailed physics of aerosols, cloud and rain formation are used to investigate the seeding impacts on rain enhancement under different natural aerosol backgrounds and using different seeding materials. Our results indicate that seeding may enhance rainfall under certain conditions.
By releasing soluble aerosols into the convective clouds, cloud seeding potentially enhances...
Altmetrics
Final-revised paper
Preprint