Particle-based cloud models use Lagrangian approaches to represent cloud microphysics and its interaction with cloud dynamics. Unlike traditional Eulerian frameworks, which apply mixing ratios for various predefined cloud condensate and precipitation categories (cloud water, rain, cloud ice, snow, graupel, hail), particle-based models applies point particles, often referred to as super-droplets or super-particles, to represent the enormous number of aerosol, cloud, and precipitation particles present inside the simulated domain of a cloud model.
The Lagrangian particle-based approach offers significant advantages over Eulerian approaches typically used in cloud models, but it took a long time for the idea to gain acceptance within the atmospheric science community, and the methodology continues to evolve.
This workshop provides an opportunity to meet researchers in related fields, and exchange ideas to explore the capabilities of the methodology.
Date and time: 26th September 2025, 9:40-17:30 (tentative)
Venue: Zoom and University of Hyogo, Kobe Campus for Information Science, Computational Science Center Building, room 720
HP: https://s-shima-lab.sakura.ne.jp/events/ws_pbcm2509/
Registration(free): https://forms.gle/A23fywWqBwcCBHLy9
Registration deadline: 22nd September
Invited speakers (tentative):
- Manhal Alhilali (University of Hyogo)
- Hiroki Ando (Kyoto Sangyo University)
- Sylwester Arabas (AGH University of Kraków)
- Wojciech W. Grabowski (NCAR)
- Samar Prakash Khatiwala (Waseda University)
- Rakesh Teja Konduru (JAXA)
- Hiroyuki Kusaka (University of Tsukuba)
- Tim Lüttmer (Johannes Gutenberg University Mainz)
- Agnieszka Makulska (University of Warsaw)
- Dai Nakai (Kyoto Institute of Technology)
- Yutaro Nirasawa (University of Tokyo)
- Hayatomo Ohashi (University of Hyogo)
- Megumi Okazaki (Kyoto University)
- Anna Rufas (University of Oxford)
- Kazumasa Ueno (University of Tokyo)
- Chongzhi Yin (Nanjing University of Information Science and Technology)
- about 2 more?
Program:
| 9:40 | Opening Remarks |
| Chair: | |
| 9:45-10:05 | Broadening of adiabatic droplet spectra through eddy hopping: Polluted versus pristine environments, Wojciech W. Grabowski (NCAR) (abstract) |
| 10:05-10:25 | A Lagrangian Particle Tracking Framework for the Super-Droplet Method: Development, Implementation, and Application of Backward and Forward Algorithms in SCALE-SDM, Chongzhi Yin (Nanjing University of Information Science and Technology) (abstract) |
| 10:25-10:45 | Sensitivity of Cumulonimbus Clouds to Background Aerosol Levels: Insights from the Super-Droplet Method, Manhal Alhilali (University of Hyogo) (abstract) |
| 10:45-11:05 | Line Shape Converging systems representation across scales from Direct Numerical Simulations, Large Eddy Simulations, and Mesoscale Simulations, Rakesh Teja Konduru (JAXA) (abstract) |
| 11:05-11:25 | Holographic particle tracking for cloud microphysics: from 3D trajectories to collision kernel statistics, Dai Nakai (Kyoto Institute of Technology) (abstract) |
| 11:25-11:45 | TBA, Agnieszka Makulska (University of Warsaw) (abstract) |
| 11:45-13:00 | Lunch Break |
| Chair: | |
| 13:00-13:20 | TBA, Hiroyuki Kusaka (University of Tsukuba) (abstract) |
| 13:20-13:40 | A study on bifurcation and stability in the co-condensation dynamics of Venus’s sulfuric acid clouds using a box model, Hiroki Ando (Kyoto Sangyo University) (abstract) |
| 13:40-14:00 | Immersion freezing in particle-based cloud microphysics models, Sylwester Arabas (AGH University of Kraków) (abstract) |
| 14:00-14:20 | Applying a Radar Simulator to the Super-Droplet Method: Current Status with BIN-type Data, Yutaro Nirasawa (University of Tokyo) (abstract) |
| 14:20-14-40 | TBA, Tim Lüttmer (Johannes Gutenberg University Mainz) (abstract) |
| 14:40-15:00 | Bimodal raindrop size distributions with a bin microphysics mode, Megumi Okazaki (Kyoto University) (abstract) |
| 15:00-15:30 | Break |
| Chair: | |
| 15:30-15:50 | Two-Stage Freezing Model of Wet and Dry Growth in Riming for the Super-Droplet Method, Hayatomo Ohashi (University of Hyogo) (abstract) |
| 15:50-16:10 | Quantum Computing for Stochastic Cloud Representation, Kazumasa Ueno (University of Tokyo) (abstract) |
| 16:10-16:30 | TBA |
| 16:30-16:50 | TBA |
| 16:50-17:10 | TBA |
| 17:10-17:30 | Toward a Mechanistic Understanding of the Ocean Biological Carbon Pump, Anna Rufas (University of Oxford) and Samar Prakash Khatiwala (Waseda University) (abstract) |
| 17:30 | Closing |
| 18:30-20:30 | Dinner gathering at Kobe Sannomiya Tokyu REI Hotel |
Organizers: Shima Research Group, Graduate School of Information Science, University of Hyogo
Sponsors:
JST Moonshot R and D (JPMJMS2283)
JSPS KAKENHI Grant-in-Aid (23H00149, 23K03265, 25K01071)
HPCI (hp250099, hp250136)
Contact: Shin-ichiro Shima, e-mail: s_shima@gsis.u-hyogo.ac.jp
Abstracts:
Toward a Mechanistic Understanding of the Ocean Biological Carbon Pump
Anna Rufas1 and Samar Khatiwala2
1. Department of Earth Sciences, University of Oxford, Oxford, UK
2. School of International Liberal Studies, Waseda University, Tokyo, Japan
Abstract:
Photosynthetic production of organic matter by phytoplankton absorbs atmospheric carbon dioxide from the atmosphere. This organic matter subsequently aggregates into sinking particles that are consumed by microbes and zooplankton, remineralizing it back into CO2 which can stay dissolved in the ocean for centuries. These processes are collectively known as the biological carbon pump (BCP) and the depth to which the particles sink controls its “efficiency” in sequestering carbon in the ocean. However, despite its importance for the carbon cycle and climate, the BCP is poorly constrained by sparse observations, and current biogeochemical models embedded within the climate models used to predict future climate change do not have a mechanistic representation of the complex, small-scale processes that drive the BCP, often reducing them to one or two globally uniform parameters. The ability of climate models to respond to environmental changes and realistically project how the BCP will evolve in the future is therefore limited. Here, we present a novel mechanistic model – Stochastic Lagrangian Aggregate Model of Sinking particles (SLAMS) – that explicitly simulates and tracks the formation, interactions and transformations of a large number of biogenic particles in the BCP. Uniquely, the fundamental characteristics of the BCP, such as its sequestration efficiency, are “emergent” properties of this model and not simply prescribed through fixed parameterisation as in existing biogeochemical models. SLAMS uses numerical methods developed in the fields of astrophysics and cloud microphysics to make the computation tractable. We will briefly describe the architecture of SLAMS, preliminary results from a global-ocean simulation, and future plans for how SLAMS can be used to better understand the BCP in the present-day climate and its response to future climate change.