A080
Processes of (Sub) Cloud Scales: Modeling, Observations and Parameterizations
Session ID#: 158844
Session Description:
Clouds continue to challenge our understanding and are major sources of uncertainty in numerical weather prediction and climate projection. Key to addressing such outstanding challenges associated with clouds are to understand the processes that occur at space-time scales of individual clouds or smaller, including entrainment/detrainment, turbulent mixing, turbulence, cloud microphysics, radiation, aerosol activation/deactivation, and boundary layer processes. The temporal and spatial scales of these processes are essentially smaller compared to the time and grid scales employed in numerical models. These sub-grid cloud processes pose particular challenges to numerical simulations, observations, as well as parameterization development. Representations of these sub-grid cloud processes in models will likely become more important as weather and climate models increase their resolutions. This session focuses on process-level modeling (e.g., CRM, LES and DNS), observations (both laboratory and field), and parameterizations of such (sub) cloud processes. Also invited are studies on unified treatment of different processes, process coupling, and integration from observations, theories to models.
Index Terms:
3311 Clouds and aerosols [ATMOSPHERIC PROCESSES]
3314 Convective processes [ATMOSPHERIC PROCESSES]
3323 Large eddy simulation [ATMOSPHERIC PROCESSES]
3379 Turbulence [ATMOSPHERIC PROCESSES]
Primary Convener: Chunsong Lu, NUIST Nanjing University of Information Science and Technology, Nanjing, China
Conveners: Yangang Liu, Brookhaven National Laboratory, Upton, NY, United States, Lulin Xue, NCAR, RAL, Boulder, United States and Alexei Korolev, Environment Canada Toronto, Cloud Physics and Severe Weather Section, Toronto, ON, Canada
Influence of entrainment on centimeter-scale cloud microphysics in marine stratocumulus clouds observed during CSET (1154218)
Seong Soo Yum, Yonsei University, Seoul, South Korea, Inyeob La, Yonsei University, Seoul, Korea, Republic of (South), Jae Min Yeom, Michigan Tech University, Houghton, United States and Raymond A Shaw, Michigan Technological University, Houghton, MI, United States
Effects of turbulence on autoconversion processes: through collision or diffusion? (1155024)
Yangang Liu, Brookhaven National Laboratory, Upton, NY, United States, Neel Desai, San Jose State University, San Jose, United States, Sinan Gao, Nanjing University of Information Science & Technology, Nanjing, China, Chunsong Lu, ; Nanjing University of Information Science and Technology, Nanjing, China, Robert L McGraw, Brookhaven Lab, Upton, NY, United States and Zhibo Zhang, University of Maryland Baltimore County, Baltimore, United States
The non-monotonic response of cumulus congestus to the concentration of cloud condensation nuclei (1155521)
Xin Deng, Fujian Agriculture and Forestry University, Fuzhou, China, Shizuo Fu, Fujian Normal University, School of Geographical Sciences, Fuzhou, China and Huiwen Xue, Department of Atmospheric and Oceanic Sciences, Peking University, Beijing, China
Lagrangian Supersaturation Statistics in Turbulent Cloudy Rayleigh–Bénard Convection: Applications for LES Subgrid Modeling (1157871)
Kamal Kant Chandrakar, National Center for Atmospheric Research, Boulder, CO, United States, Hugh Morrison, NCAR, MMM Laboratory, Boulder, United States and Raymond A Shaw, Michigan Technological University, Houghton, MI, United States
Simulation of latent heating rate from the microphysical process associated with Mesoscale Convective System over Korean Peninsula (1164711)
Akkisetti Madhulatha, Korea Institute of Atmospheric Prediction Systems, Seoul, South Korea; Indian Meteorological Department, Ministry of Earth Sciences, New Delhi, India, Jimy Dudhia, NCAR, MMM, Boulder, United States, Rae-Seol Park, KIAPS, Seoul, South Korea and M. Rajeevan, Ministry of Earth Sciences, New Delhi, India
Bulking Up with the BOSS: Accurate Emulation of the TAU Bin Model's Liquid Microphysics Using Simple Bulk Schemes (1181019)
Sean Patrick Santos, Columbia University, Center for Climate Systems Research, New York, United States; NASA Goddard Institute for Space Studies, New York, United States, Marcus van Lier-Walqui, Columbia University, Center for Climate Systems Research, New York, NY, United States and Hugh Morrison, NCAR, MMM Laboratory, Boulder, United States
Are Cloud Droplet Sizes Gamma Distributed at Centimeter scales? (1183911)
Nithin Allwayin1, Michael Larsen2, Susanne Glienke3 and Raymond A Shaw1, (1)Michigan Technological University, Houghton, MI, United States, (2)College of Charleston, Physics and Astronomy, Charleston, United States, (3)Pacific Northwest National Laboratory, Richland, United States
Numerical model to enable ultra-high-resolution simulations of shallow clouds using the super-droplet method (1190442)
Toshiki Matsushima1, Seiya Nishizawa2, Shin-ichiro Shima3 and Hirofumi Tomita2, (1)Kobe University, Center for Planetary Science, Kobe, Japan, (2)RIKEN Center for Computational Science, Kobe, Japan, (3)University of Hyogo and RIKEN Center for Computational Science, Kobe, Japan
Neural network emulator for melting processes in a bulk-type cloud microphysics parameterization (1193871)
JeongSu Ko1, Kyo-Sun Lim1, Sung-Bin Jang1 and Joong-Hyun Jo2, (1)Kyungpook National University, Department of Atmospheric Sciences, Center for Atmospheric REmote sensing (CARE), Daegu, South Korea, (2)Kyungpook National University, Department of Earth System Sciences, Daegu, South Korea
Sources of stochasticity in the growth of cloud droplets: supersaturation fluctuations versus turbulent transport (1197775)
Prasanth Prabhakaran1, Subin Thomas1, Will H Cantrell2, Raymond A Shaw1 and Fan Yang3, (1)Michigan Technological University, Houghton, MI, United States, (2)Michigan Technological University, Atmospheric Sciences Program, Houghton, MI, United States, (3)Brookhaven National Laboratory, Upton, United States
Diverse dispersion effects and parameterization of relative dispersion in urban fogs in Eastern China (1047471)
Yuan Wang1, Chunsong Lu2, Shengjie Niu3, Jingjing Lü4, Xiaoqi Xu5, Yuqi Xue3 and Yang Wang1, (1)Lanzhou University, Lanzhou, China, (2)Nanjing Univerisity of Information Science and Technology (NUIST), Nanjing, China, (3)Nanjing University of Information Science and Technology, Nanjing, China, (4)Nanjing University of Information Science & Technology, Nanjing, China, (5)Nanjing Joint Institute for Atmospheric Sciences, Nanjing, China
Convective updrafts near sea-breeze fronts (1047527)
Shizuo Fu, Fujian Normal University, School of Geographical Sciences, Fuzhou, China, Richard Rotunno, National Center for Atmospheric Research, Mesoscale & Microscale Meteorology Division, Boulder, CO, United States and Huiwen Xue, Department of Atmospheric and Oceanic Sciences, Peking University, Beijing, China
A Quasi-steady-state approximation of Droplet Growth Equation (QDGE) Scheme for Aerosol Activation: Description, Evaluation, and Optimization (1058368)
Hengqi Wang1, Yiran Peng1, Knut von Salzen2, Yan Yang3, Wei Zhou3 and Delong Zhao4, (1)Tsinghua University, Department of Earth System Science, Beijing, China, (2)CCCma, Environment Canada, Victoria, BC, Canada, (3)Beijing Weather Modification Office, Beijing, China, (4)Beijing Weather Modification Center, Beijing, China
Understanding the impacts of subgrid cloud property variations on warm rain simulations in climate models based on satellite observations, in situ measurements and large-eddy simulations (1064678)
Zhibo Zhang, University of Maryland Baltimore County, Baltimore, United States, David B Mechem, University of Kansas, Lawrence, KS, United States, Vincent E Larson, University of Wisconsin-Milwaukee, Milwaukee, WI, United States, Yangang Liu, Brookhaven National Laboratory, Upton, NY, United States, Mikael Witte, Naval Postgraduate School, Monterey, CA, United States and Xiquan Dong, University of North Dakota, Grand Forks, ND, United States; University of Arizona, Hydrology and Atmospheric Sciences, Tucson, United States
Supercooled liquid water and secondary ice production in Kelvin–Helmholtz instability as revealed by radar Doppler spectra observations (1077592)
Haoran Li, CAMS Chinese Academy of Meteorological Sciences, Beijing, China, Alexei Korolev, Environment Canada Toronto, Cloud Physics and Severe Weather Section, Toronto, ON, Canada and Dmitri N Moisseev, University of Helsinki, Helsinki, Finland
Satellite retrieval of cloud overlap properties,parameterization, and its application in the models (1077604)
Bida Jian1, Qi Chen2, Jiming Li1 and ZhanShan Ma3, (1)Lanzhou University, Lanzhou, China, (2)Chinese Academy of Meteorological Sciences, State Key Laboratory of Severe Weather, Beijing, China, (3)BNU Beijing Normal University, Numerical Weather Predication Center of China Meteorological Administration, Beijing, China
A Comparison of Spectral Bin Microphysics versus Bulk Parameterization in Forecasting Typhoon In-Fa (2021) before, during, and after Its Landfall (1083146)
Wu Zuhang1, Yun Zhang2, Lifeng Zhang3 and Hepeng Zheng3, (1)College of Meteorology and Oceanography, National University of Defense Technology, Department of Atmosphere Science, Changsha, China, (2)National University of Defense Technology, Changsha, China, (3)College of Meteorology and Oceanography, National University of Defense Technology, Department of Atmosphere Science, Nanjing, China
New insight on the interaction between dynamics and microphysics in warm convective clouds (1084700)
Alexander Khain, Hebrew University of Jerusalem, Department of Atmospheric Sciences, Jerusalem, Israel, Eshkol Eytan, Weizmann Institute of Science, Rehovot, Israel, Mark Pinsky, Hebrew University in Jerusalem, Jerusalem, Israel, Ilan Koren, Weizmann Institute of Science, Earth and Planetary Sciences, Rehovot, Israel and Ehud Gavze, Hebrew University of Jerusalem, Jerusalem, Israel
Parameterization of Turbulent Entrainment-Mixing Process and its Influences on Simulations of Cumulus and Stratocumulus Clouds (1086730)
Chunsong Lu1, Xiaoqi Xu2, Yangang Liu3, Shi Luo4, Xin Zhou3, Satoshi Endo3, Lei Zhu4 and Yuan Wang5, (1)NUIST Nanjing University of Information Science and Technology, Nanjing, China, (2)Nanjing Joint Institute for Atmospheric Sciences, Nanjing, China, (3)Brookhaven National Laboratory, Upton, NY, United States, (4)Nanjing University of Information Science and Technology, Nanjing, China, (5)Nanjing University of Information Science & Technology, Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing, China
Stratocumulus profiles characterization for the Multi-viewing, Multi-channel, Multi-polarization Imager (3MI) liquid cloud algorithm (1087454)
Huazhe Shang1, Jérôme Riedi2, Letu Husi1, Guillaume Penide2 and Souichiro Hioki2, (1)State Key Laboratory of Remote Sensing Science, The Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China, (2)Univ. Lille, CNRS, UMR 8518 - LOA - Laboratoire d’Optique Atmosphérique, Lille, France
Entrainment Rate in Shallow Cumuli: Aircraft Observations and Large-Eddy Simulations (1087486)
Lei Zhu1, Chunsong Lu1, Shuqi Yan1, Yangang Liu2, Guangjun Zhang3, Fan Mei4, Bin Zhu1, Xiaoqi Xu5, Xin He1 and Junjun Li1, (1)Nanjing University of Information Science and Technology, Nanjing, China, (2)Brookhaven National Laboratory, Upton, NY, United States, (3)Scripps Institution of Oceanography, La Jolla, United States, (4)Pacific Northwest National Laboratory, Richland, WA, United States, (5)Nanjing Joint Institute for Atmospheric Sciences, Nanjing, China
Parameterizing Transitions from Shallow to Deep and to Organized Convection via Entrainment and Moisture Distributions in Climate Models (1088511)
Ben Yang1, Minghuai Wang1, Guang Jun Zhang2, Zhun Guo3, Anning Huang1, Yong Wang4, Xin Xu1, Guoqing Dai1, Yaocun Zhang1 and Yun Qian5, (1)Nanjing University, Nanjing, China, (2)Scripps Institution of Oceanography, La Jolla, CA, United States, (3)Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China, (4)Tsinghua University, Department for Earth System Science, Beijing, China, (5)Pacific Northwest National Laboratory, Richland, United States
Investigation of Turbulent Entrainment Mixing Processes in Shallow Cumulus Clouds with High Resolution Datasets in HISCALE and LES with Lagrangian Microphysics (1099431)
Yayun Qiao1, Kamal Kant Chandrakar2, Greg M McFarquhar3, Wojciech Grabowski2, Hugh Morrison4, Fan Mei5, Alla Zelenyuk5 and Jake Carter6, (1)University of Oklahoma Norman Campus, Norman, OK, United States, (2)National Center for Atmospheric Research, Boulder, CO, United States, (3)Cooperative Institute for Severe and High-Impact Weather Research and Operations, University of Oklahoma, Norman, OK, United States, (4)NCAR, MMM Laboratory, Boulder, United States, (5)Pacific Northwest National Laboratory, Richland, WA, United States, (6)University of Oklahoma Norman Campus, Norman, United States
Simulation of Marine Stratocumulus Using the Super-Droplet Method: Numerical Convergence and Comparison to a Double-Moment Bulk Scheme (1103536)
Chongzhi Yin1, Shin-ichiro Shima2, Chunsong Lu1 and Lulin Xue3, (1)NUIST Nanjing University of Information Science and Technology, Nanjing, China, (2)University of Hyogo and RIKEN Center for Computational Science, Kobe, Japan, (3)NCAR, RAL, Boulder, United States
Impact of Cloud Microphysics Parameterization on Weather Prediction: Particle Size Distribution and Aerosol (1107538)
Linjiong Zhou1, Lucas Harris2, Jan-Huey Chen3, Kun Gao4, Huan Guo3, Baoqiang Xiang3, Mingjing Tong5 and Matt Morin6, (1)Princeton University, Princeton, NJ, United States, (2)Geophysical Fluid Dynamics Laboratory, NOAA, Princeton, United States, (3)NOAA/Geophysical Fluid Dynamics Laboratory, Princeton, NJ, United States, (4)Princeton University, Atmospheric and Oceanic Sciences, Princeton, NJ, United States, (5)NOAA Geophysical Fluid Dynamics Laboratory, Princeton, United States, (6)Geophysical Fluid Dynamics Laboratory, Princeton, NJ, United States
The Springtime Ice Nuclei Properties in Beijing (1108440)
Yangze Ren1, Kai Bi2, Shizuo Fu3, Ping Tian4, Mengyu Huang5, Ruihao Zhu1 and Huiwen Xue6, (1)Peking University, Beijing, China, (2)Beijing Weather Modification Office, Beijing, China, (3)Fujian Normal University, School of Geographical Sciences, Fuzhou, China, (4)Beijing Weather Modification Center, Beijing, China, (5)Beijing Key Laboratory of Cloud, Precipitation and Atmospheric Water Resources, Beijing, China, (6)Department of Atmospheric and Oceanic Sciences, Peking University, Beijing, China
Machine learning optimal prognostic moments for single-category cloud microphysics parameterizations (1120878)
Ryan A Anselm, Columbia University, New York, United States, Kara Lamb, Columbia University, Earth and Environmental Engineering, New York, United States, Hugh Morrison, NCAR, MMM Laboratory, Boulder, United States, Sean Patrick Santos, Columbia University, Center for Climate Systems Research, New York, United States and Marcus van Lier-Walqui, Columbia University, Center for Climate Systems Research, New York, NY, United States
In situ observations and numerical simulations of spatial inhomogeneity of mixed-phase clouds (1129100)
Alexei Korolev, Environment and Climate Change Canada, Atmospheric Science and Technology Directorate, Toronto, ON, Canada and Jason Milbrandt, Environment and Climate Change Canada, Atmospheric Numerical Weather Prediction Research, Dorval, QC, Canada
Prognostic approach for graupel density in Weather Research and Forecasting (WRF) Double-Moment 6-class (WDM6). (1141824)
Sun Young Park, Kyungpook National University, Department of Atmospheric Sciences, Center for Atmospheric Remote sensing (CARE), Daegu, Korea, Republic of (South), Kyo-Sun Lim, Kyungpook National University, Department of Astronomy and Atmospheric Sciences, Daegu, South Korea and Jason Milbrandt, Environment and Climate Change Canada, Atmospheric Numerical Weather Prediction Research, Dorval, QC, Canada
Implementation of a Unified Convection scheme (UNICON)Into the Met Office Unified Model (UM) (1142750)
Juwon Kim1, Sungsu Park1, Chanwoo Song1, Siyun Kim1, Johan Lee2, Beomcheol Shin3 and Kyung-On Boo4, (1)Seoul National University, Seoul, Korea, Republic of (South), (2)National Institute of Meteorological Sciences, Seogwipo-si, South Korea, (3)National Institute of Meteorological Research, Environmental Meteorology Division, Seoul, South Korea, (4)Numerical modeling Center, Seoul, South Korea
Updating CLUBB PDF Closure Scheme to Improve Low Cloud Simulation in CAM6 (1149259)
Te Li1, Minghuai Wang1, Zhun Guo2, Ben Yang1, Jianning SUN3 and Yifei Xu4, (1)Nanjing University, Nanjing, China, (2)Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China, (3)Nanjing University, School of Atmospheric Sciences, Nanjing, China, (4)Jiangsu Provincial Meteorological Bureau, Nanjing, China
Unsupervised learning of microphysical process rates using generative machine learning models (1151431)
Kara Lamb, Columbia University, Earth and Environmental Engineering, New York, United States, Marcus van Lier-Walqui, Columbia University, Center for Climate Systems Research, New York, NY, United States, Sean Patrick Santos, Columbia University, Center for Climate Systems Research, New York, United States and Hugh Morrison, NCAR, MMM Laboratory, Boulder, United States
Direct Numerical Simulation of Cloud Droplet Growth by Condensation (1151612)
Dimitrios K Fytanidis1,2, Yan Feng1, Fan Yang3, Virendra P Ghate1, Veerabhadra Rao Kotamarthi1, Ramesh Balakrishnan1 and Paul Fischer2, (1)Argonne National Laboratory, Lemont, IL, United States, (2)University of Illinois at Urbana Champaign, Urbana, IL, United States, (3)Brookhaven National Laboratory, Upton, United States
