September 11, 2023 (Mon) 3:00 - 4:00 pm JST

Relationship between hail, differential reflectivity and atmospheric aerosols in a mid-latitude hail storm

Alexander Khain (1), Eyal Ilotoviz (1), Vaughan Phillips (2) and Alexander Ryzhkov (3)
(1) The Hebrew University of Jerusalem, Israel
(2) Lund University, Sweden
(3) National Severe Storm Laboratory, USA

A midlatitude hail storm was simulated using the spectral bin microphysics Hebrew University Cloud Model (HUCM) with a detailed description of time-dependent melting and freezing. In addition to size distributions of drops, plate-, columnar-, and branch-type ice crystals, snow, graupel, and hail, new mass distributions for freezing drops as well as for liquid water mass within precipitating ice particles were implemented to describe time-dependent freezing and wet growth of hail, graupel, and freezing drops.

Simulations carried out using different aerosol loadings show that an increase in aerosol loading leads to a decrease in the total mass of hail but also to a substantial increase in the maximum size of hailstones. Cumulative rain strongly increases with an increase in aerosol concentration from 100 to about 1000 cm-3. The main effect of the increase in the aerosol concentration is the increase in the supercooled cloud water content at high levels. Accordingly, at high aerosol concentration, the hail grows largely by accretion of cloud droplets in the course of recycling in the cloud updraft zone. The main mechanism of hail formation in the case of low aerosol concentration is freezing of raindrops.

A polarimetric radar forward operator is used to calculate radar reflectivity and differential reflectivity ZDR. It is shown that ZDR columns are associated with raindrops and with hail particles growing in a wet growth regime within convective updrafts. The height and volume of ZDR columns increases with an increase in aerosol concentration. Small hail forming under clean conditions grows in updrafts largely in a dry growth regime corresponding to low ZDR. Parameters of ZDR columns (heights, ZDR values) are highly correlated with vertical velocity, hail size, and aerosol concentration. These correlations can be used for short range forecasts of hail.

Location (hybrid): Zoom and University of Hyogo, Kobe Campus for Information Science, Computational Science Center Building, room 313502 (兵庫県立大学神戸情報科学キャンパス 313502),

Contact: Shin-ichiro Shima (島伸一郎), e-mail:

September 8, 2023 (Fri) 3:00 - 4:00 pm JST

Combined effect of the Weber-Bergeron-Findeisen mechanism and large eddies on Arctic clouds: Why are Arctic stratocumulus clouds mixed-phase and stable?

Alexander Khaina, Mark Pinskya, and Alexei Korolevb
a The Hebrew University of Jerusalem, Jerusalem, Israel
b Environment and Climate Change Canada, Toronto, Ontario, Canada

The process of glaciation in mixed-phase stratiform clouds was investigated by a novel Lagrangian–Eulerian model (LEM) in which thousands of adjoining Lagrangian parcels with characteristic size of ~ 10 m moved within a turbulent-like velocity field with statistical parameters typical of the Arctic boundary layer. We used detailed bin microphysics to describe the condensation/evaporation processes in each parcel, in which droplets, aerosols, and ice particles were described using size distributions of 500 mass bins. The model also calculated aerosol mass inside droplets and ice particles. Gravitational sedimentation of droplets and ice particles was also accounted for. Assuming that droplet freezing is the primary source of ice particles, the Arctic clouds observed in Indirect and Semi-Direct Aerosol Campaign (ISDAC) were successfully simulated. The model showed that at a low ice particle concentration typical of ISDAC, large vortices (eddies) led to a quasi-stationary regime, in which mixed-phase St existed for a long time. The large eddies controlled the water partitioning in the mixed-phase clouds. Droplets formed and grew in updrafts, typically reaching the cloud top, and evaporated in downdrafts. Ice particles grew in updrafts and downdrafts. The Wegener–Bergeron–Findeisen (WBF) mechanism was efficient in downdrafts, near cloud top, and some part of updrafts depending on ice concentration and vertical velocity. At low ice concentrations, the effect of ice on the phase partitioning was negligible. In this regime, liquid droplets were found near the cloud top, whereas ice particles precipitated through the cloud base. When ice concentration exceeded about ten per liter, the WBF mechanism led to glaciation of almost the entire cloud, with the exception of narrow cloud regions associated with strong updrafts. The microphysical structure of mixed-phase St forms as a combined effect of cloud dynamics (large eddies) and the WBF mechanism.

Location (hybrid): Zoom and University of Hyogo, Kobe Campus for Information Science, Computational Science Center Building, room 313 (兵庫県立大学神戸情報科学キャンパス 313),

Contact: Shin-ichiro Shima (島伸一郎), e-mail:

Date and time: June 21, 2023 (Wed) 4:00 - 5:00 pm

Numerical convergence properties of the superdroplet model in a 2-D prescribed flow with fixed thermodynamics

Presenter: Clara Bayley
IMPRS-ESM, Max Planck Institute for Meteorology

Location (hybrid): Zoom and University of Hyogo, Kobe Campus for Information Science, Computational Science Center Building, room 313 (兵庫県立大学神戸情報科学キャンパス 313),

Contact: Shin-ichiro Shima (島伸一郎), e-mail:

Date and time: May 26, 2023 (Fri) 4:30 - 5:30 pm

How EUREC4A and BCO observations advanced understanding of the cloud-circulation coupling, the diurnal cycle and cold pools in the trade-wind region

Presenter: Raphaela Vogel
Meteorologisches Institut, Faculty of Physics, Universität Hamburg

Shallow trade cumulus clouds populate most of the subtropical oceans and cool the planet by reflecting the incoming solar radiation. The response of trade cumuli to climate change is a key uncertainty in climate projections. This uncertainty motivated the establishment of the Barbados Cloud Observatory (BCO), which measures trade cumuli and their environment with a large suite of in-situ and remote sensing instruments since 2010. And it also motivated the recent EUREC4A field campaign, which took place upstream Barbados in January and February 2020. In this presentation, I will first give an overview of the available BCO and EUREC4A data. And then I’ll show three examples how we used the data to (a) refute a mechanism for a strongly positive trade cumulus feedback, (b) explore the diurnal cycle of cloudiness and mesoscale cloud organization, and (c) compile a climatology of trade cumulus cold pools and their associated dynamical and thermodynamical changes. As an outlook, I’ll briefly discuss ideas to retrieve profiles of rain evaporation rates and downdrafts, and the planned setups for the LES and SRM intercomparison of the EUREC4A-MIP.

Location (hybrid): Zoom from Hamburg; and University of Hyogo, Kobe Campus for Information Science, Computational Science Center Building, room 313 (兵庫県立大学神戸情報科学キャンパス 313),

Contact: Shin-ichiro Shima (島伸一郎), e-mail:

Date and time: Dec 21, 2022 (Wed) 1:30 - 2:30 pm

Implementation and deployment of the piggybacking method to SCALE

Presenter: Piotr Żmijewski
Institute of Geophysics, Faculty of Physics, University of Warsaw

Location (hybrid): Zoom; and University of Hyogo, Kobe Campus for Information Science, Computational Science Center Building, room 501 (兵庫県立大学神戸情報科学キャンパス 501 小講義室),

Contact: Shin-ichiro Shima (島伸一郎), e-mail:

Date and time: Nov 15, 2019 (Fri) 3:00 - 4:00 pm

Title: Comparison of Eulerian bin and Lagrangian particle-based schemes in simulations of Pi Chamber dynamics and microphysics

Presenter: Wojciech W. Grabowski
Mesoscale and Microscale Meteorology Laboratory, NCAR

This presentation will discuss a comparison of simulations applying traditional Eulerian bin microphysics scheme with simulations using a novel particle-based Lagrangian approach to simulate CCN activation and droplet growth. The Eulerian bin microphysics solve the evolution equation for the spectral density function, whereas Lagrangian approach follows evolution in time and space of computational particles referred to as super-droplets. Each super-droplet represents a multiplicity of natural droplets that makes the Lagrangian approach computationally feasible. The two schemes apply identical representation of CCN activation and use the same droplet growth equation; these make the direct comparison between the two schemes practical. The study, the first of its kind, applies an idealized simulation setup motivated by laboratory experiments with the Pi Chamber and previous model simulations of the Pi Chamber dynamics and microphysics. Pi Chamber laboratory apparatus considers interaction between turbulence, CCN activation, and cloud droplet growth in moist Rayleigh-Bénard convection driven by the temperature and moisture difference between homogeneous horizontal boundaries. Steady-state droplet spectra averaged over the entire chamber are similar, with the mean droplet concentration, mean radius and spectral width close in Eulerian and Lagrangian simulations. Small differences are explained by the inherent differences between the two schemes and their numerical implementation. However, as one might expect, the local droplet spectra differ substantially, again in agreement with the inherent limitations of the theoretical foundation behind each approach. Comparison between simulations, laboratory experiments, and previous theoretical studies of droplet growth in the turbulent environment will be discussed.

Location: University of Hyogo, Kobe Campus for Information Science, Computational Science Center Building, room 502 (兵庫県立大学神戸情報科学キャンパス 502 小講義室),

Contact: Shin-ichiro Shima (島伸一郎), e-mail:

Date and time: Aug 23, 2019 (Fri) 4:00 - 5:00 pm

Title: PySDM: exploring novel tools from the Python ecosystem for super-droplet simulation studies

Presenters:  Piotr Bartman1 and *Sylwester Arabas1
1. Division of Computational Mathematics, Jagiellonian Univ., Cracow, Poland
* speaker

PySDM ( is a new Python implementation of the Super-Droplet Method (SDM, Shima et al. 2009) algorithm for representing particle collisional growth in numerical models of atmospheric clouds. It is being built on top of Numba, Pythran and ThrustRTC - packages offering high-performance CPU and GPU computing capabilities at little-to-no trade-off to Python's code clarity and testability. This opens up possibilities to embrace state-of-the-art productivity-oriented software engineering and dissemination practices established in the Python ecosystem. To highlight the attainable level of agility, the talk will feature a demo during which everyone will be encouraged to try out a simple simulation using PySDM through a Jupyter notebook executed on a cloud-computing platform (i.e., a browser is the only requirement). Please bring your laptops.

Location: University of Hyogo, Kobe Campus for Information Science, Computational Science Center Building, room 313 (兵庫県立大学神戸情報科学キャンパス 313セミナー室),

Contact: Shin-ichiro Shima (島伸一郎), e-mail: