2nd International Workshop on

Cloud Turbulence

March 8-10, 2017
Nagoya Institute of Technology, Nagoya, Japan

Program of 2nd International Workshop on Cloud Turbulence
March 8-10, 2017, Hall, Building 4, Nagoya Institute of Technology
URL: http://comphys.web.nitech.ac.jp/cloud2

March 89:00

9:20

Registration

9:20

9:30

Opening

9:30 10:30

Wang PK

10:30 10:50

Keynote Lecture
Turbulent Phenomena at the Top of Convective Storms:
Observations, Modeling and Implications
Coﬀee Break

10:50 11:40

Wang LPInterface-Resolving Simulation of Collision Eﬃciency of Cloud Droplets

11:40 12:30

OnishiTowards full Lagrangian cloud simulation

12:30 14:00
14:00 15:00

Lunch
Falkovich

15:00 15:20

Keynote Lecture
Inertial particles in non-uniform turbulenceCoﬀee Break

15:20 16:10

Toschi

Settling of (non-)heavy inertial particles in turbulence

16:10 17:00

Murakami

Aerosol Eﬀects on Microphysical Properties of Clouds and Precipitation-Laboratory and Numerical Experiments Mainly on CCN Activation-

Shaw

Keynote Lecture
Turbulence-induced broadening of cloud-droplet size distributions:
Implications for aerosol eﬀects on climate

March 99:30 10:30

10:30 10:50

Coﬀee Break

10:50 11:40

Xu

Turbulence and cloud microphysics at a mountaintop research station

11:40 12:30

Shima

Grid convergence of the large-eddy simulation of shallow maritime cumuli field:
A case study using the super-droplet method as the cloud microphysics model

12:30 13:00

Photo Session

13:00 14:30

Lunch

14:30 15:30

Grabowski

15:30 15:50

Keynote LectureDiﬀusional growth of cloud droplets in turbulent clouds
Coﬀee Break

15:50 16:40

Gotoh

Droplets and Turbulence in Cloud Microphysics Simulator

16:40 17:30

Stratmann
Niedermeier

The new turbulent Leipzig Aerosol Cloud Interaction Simulator (LACIS-T):
Design and first results

18:00 20:00

BanquetMarch 10
9:30 10:30

Tomita10:30 10:50

Keynote Lecture
Future direction of turbulence and cloud modelingCoﬀee Break

10:50 11:40

MelladoResolving submeter-scale processes at the top of stratocumulus clouds

11:40 12:30

Horiuti

Nonequilibrium subgrid-scale models in LES alternative to the Smagorinsky model

12:30 14:00

Lunch

14:00 14:30

TsubokiA research plan of typhoon observation using an aircraft in Japan

14:30 15:00

Moriki

Numerical experiments of aerosol impacts on warm clouds
using a cloud-resolving model with the super droplet method

15:00 15:50

Takemi

Environmental stability control of the organization of atmospheric moist convection

15:50 16:00

Closing

Turbulent Phenomena at the Top of Convective Storms:
Observations, Modeling and Implications
Pao K. Wang1,2

1Research Center for Environmental Changes, Academia Sinica, Taipei, Taiwan
2Department of Atmospheric and Oceanic Sciences, University of Wisconsin-

Madison, Wisconsin, USA

pkwang@gate.sinica.edu.tw
Observations of thunderstorms by meteorological satellites in both visible andinfrared bands in the past few decades have revealed many interesting phenomena
at the storm top. These phenomena include above anvil cirrus plumes (an example
is shown in the figure below), cold-V, close-in warm area, warm-cold couplet, andstorm-top ship waves. Initially mysterious, it is now understood that they areassociated with turbulent processes at the top of the storm. In this presentation, I
will first show typical examples of these phenomena. Then I will use a cloud
resolving model with proper cloud microphysics to simulate thunderstorm processes
and show that these turbulent phenomena can be modeled successfully and can be
explained satisfactorily by the model physics. It turns out that they are associatedwith the quasi-mountain waves generated by the storm and the breaking of internal
gravity waves at the storm top. The most fundamental physics is the interaction
between ambient wind and the updraft due to the deep convection. It also turns outthat the so-called “jumping cirrus” reported by Fujita in the mid-20th century can be
explained by the same physics. Some recent aircraft observations with the parallel
satellite data that provide further evidence will also be shown.

(Courtesy of Martin Setvak)

Interface-Resolving Simulation of Collision Efficiencyof Cloud Droplets
Lian-Ping Wang1,3 , Cheng Peng1 , Nick Geneva1 , Bogdan Rosa2 , and Ryo
Onishi3
12

Department of Mechanical Engineering, University of Delaware, USA
Institute of Meteorology and Water Management, National Research Institute, Poland
3
Japan Agency for Marine-Earth Science and Technology, Japanlwang@udel.edu

In the last 20 years, it has been shown that small-scale air turbulence could enhance
the geometric collision rate of cloud droplets while large-scale air turbulence could augment the diffusional growth of cloud droplets [1]. It has also been demonstrated that air
turbulence could enhance the collision efficiency of cloud droplet [2]. Accurate simulation of collision efficiency, however, requires capture of the multi-scale droplet-turbulenceand droplet-droplet interactions, which has only been partially achieved in the recent
past using the hybrid direct numerical simulation approach (HDNS) [3]. In HDNS, thebackground air turbulence is resolved numerically while the disturbance flows aroundeach droplet is represented analytically by a localized Stokes flow solution. The HDNS
approach has two major drawbacks: (1) the short-range droplet-droplet interaction [4]is not treated rigorously; (2) the finite-Reynolds number correction to the collision efficiency [5] is not included. In this talk, using two independent numerical methods, wewill develop an interface-resolved simulation approach in which the disturbance flows are
directly resolved numerically, combined with a rigorous lubrication correction model fornear-field droplet-droplet interaction. As a first step, this multi-scale direct simulation
approach will be used to study the effect of finite flow Reynolds numbers on the droplet
collision efficiency in still air. Our simulation results show a significant finite-Re effecton collision efficiency when the droplets are of similar sizes. Preliminary results on integrating this approach in a turbulent flow laden with droplets, to study droplet collision
efficiency in a turbulent air, will also be presented.
References[1] W.W. Grabowski and L.-P. Wang, Growth of cloud droplets in a turbulent environment, Annu. Rev. Fluid Mech. 45, 293 (2013).
[2] L.-P. Wang, O. Ayala, B. Rosa, W.W. Grabowski, Turbulent collision efficiency ofheavy particles relevant to cloud droplets, New J. Physics 10, 075013 (2008).
[3] O. Ayala, W.W. Grabowski, and L.-P. Wang, A hybrid approach for simulating turbulent collisions of hydrodynamically-interacting particles, J. Comp. Phys. 225, 51(2007).
[4] D.J. Jeffrey and Y. Onishi, Calculation of the resistance and mobility functions for
two unequal rigid spheres in low-Reynolds-number flow, J. Fluid Mech. 139, 261(1984).
[5] J.D. Klett and M.H. Davis, Theoretical collision efficiencies of cloud droplets at small
Reynolds numbers, J. Fluid Mech. 139, 261 (1973).

Towards full Lagrangian cloud simulation
Ryo Onishi1 , Yuichi Kunishima1 , Keigo Matsuda1 and Lian-Ping Wang2
1

Center for Earth Information Science and Technology, Japan Agency for Marine-Earth
Science and Technology, Japan2
Department of Mechanical Engineering, University of Delaware, USA
onishi.ryo@jamstec.go.jp

We have been developing the Lagrangian Cloud Simulator (LCS)[1, 2], which follows theso-called Euler-Lagrangian framework, where flow motion is computed with the Euler
method and particle motion with the Lagrangian method. We have so far achieved toperform collision growth simulation based on the hybrid DNS aproach [3] and shown a
new kind of Lagrangian information [2]. We have recently developed a cloud droplet
activation component for LCS, with a condensation growth component. The LCS is thus
now capable of treating all the growth processes for cloud droplets including the droplet
initiation process.
In this talk, we introduce the recent development on LCS and show preliminary results
regarding the droplet initiation process as well as growth processes for a periodic box
domain. We also show our strategy towards full Lagrangian cloud simulations, in which
all the particle motion and growth are tracked for cloud.
Acknowledgement This research was supported by MEXT as ”Exploratory Challenge
on Post-K computer” (Frontiers of Basic Science: Challenging the Limits).
References[1] R. Onishi, K. Takahashi and J.C. Vassilicos An efficient parallel simulation of interacting inertial particles in homogeneous isotropic turbulence, J. Comput. Phys. 242,
809-827 (2013).
[2] R. Onishi and K. Matsuda and K. Takahashi Lagrangian Tracking Simulation ofDroplet Growth in Turbulence - Turbulence Enhancement of Autoconversion Rate, J.
Atmos. Sci. 72, 2591-2607 (2015).
[3] O. Ayala and W.W. Grabowski and L.-P. Wang A hybrid approach for simulating
turbulent collisions of hydrodynamically-interacting particles, J. Comput. Phys. 225,
51-73 (2007).

Inertial particles in non-uniform turbulence
Gregory Falkovich
Weizmann Intsitute of Sciencegregory.falkovich@weizmann.ac.il
I review theoretical results on the statistics of inertial particles in the wall turbulence
and inter-particle distance in random flows. I describe the fundamental phenomenon ofturbophoresis, when particles moving down the kinetic energy gradient must concentratein minima and explain that escaping minima is possible for inertial particles whose timeof equilibration is longer than the time to reach the minimum. The problem of a particle
near minima of turbulence intensity is related to that of two particles in a random flow,
so that the localization-delocalization transition in the former corresponds to the pathcoalescence transition in the latter. I then present an analytical solution of the generalized
problem with inelastic collisions and derive the phase diagram for the transition in theinertia-inelasticity plane. An important feature of the diagram is the region of inelastic
collapse: if the restitution coeﬃcient β of particle velocity is smaller than the universal
critical value, then the particle is localized for any inertia. I also present theoreticaldescription of non-stationary particle dispersion in the lower atmosphere, derive a closeform solution for the downwind surface density of deposited particles and find how thenumber of airborne particles decreases with time and how turbophoresis modifies themean settling velocity of particles in the neutral atmospheric surface layer.

Settling of (non-)heavy inertial particles inturbulence
Federico Toschi, Michel van Hinsberg and Herman Clercx
Fluid Dynamics Laboratory, Eindhoven University of Technology, PO Box 513, 5600MB
Eindhoven, The Netherlands
F.Toschi@tue.nl
In this contribution we will address two aspects of settling processes of small inertial
particles in turbulent flows. First we address the role of the pressure gradient and theBasset history force on settling non-heavy particles in homogenous isotropic turbulence[1]. Subsequently we will focus on heavy particles in homogeneous shear turbulence anddiscuss the phenomenon of symmetry breaking of horizontal drift of the settling particles. The Stokes drag force and the gravity force are usually suﬃcient to describe thebehavior of heavy particles in turbulence, in particular when the particle-to-fluid density
ratio R is very large, R = O(1000) or larger. This is in general not the case for smaller
particle-to-fluid density ratios, in particular not for R = O(100) or smaller. In that casethe pressure gradient force, added mass eﬀects and the Basset history force also play animportant role. We focus on the understanding of the role of these additional forces, allof hydrodynamic origin, on the settling of particles in turbulence. In general we foundthat the pressure gradient force leads to a decrease in the settling velocity. This can bequalitatively understood by the fact that this force prevents the particles from sweeping
out of vortices, a mechanism known as preferential sweeping which causes enhanced settling. Additionally, we found that the Basset history force can both increase and decrease
the enhanced settling, depending on the particle Stokes number. The influence of shear
on the gravitational settling of heavy inertial particles in homogeneous shear turbulence(HST) is remarkable. In addition to the well-known enhanced settling velocity, observedfor heavy inertial particles in homogeneous isotropic turbulence (HIT), a horizontal drift
velocity is also observed in the shearing direction due to the presence of a nonzero meanvorticity (introducing symmetry breaking due to the mean shear) [2]. This drift velocity is the result of the combination of shear, gravity, and turbulence, and all three ofthese elements are needed for this eﬀect to occur. We extend the mechanism responsible
for the enhanced settling velocity in HIT to the case of HST. Two separate regimes areobserved, characterized by positive or negative drift velocity, depending on the particle
settling velocity and these regimes will briefly be discussed during this contribution.
References[1] M.A.T. van Hinsberg, H.J.H. Clercx, H.J.H. and F. Toschi, Enhanced settling of nonheavy inertial particles in homogeneous isotropic turbulence: The role of the pressure
gradient and the Basset history force, Phys. Rev. E, (2017).
[2] M.A.T. van Hinsberg, H.J.H. Clercx and F. Toschi, Phys. Rev. Lett. 117, 064501(2016).

Aerosol Effects on Microphysical Properties of Clouds andPrecipitation －Laboratory and Numerical Experiments Mainly on
CCN Activation－
Masataka Murakami1,2, Takuya Tajiri2, Katsuya Yamashita3,
and Naomi Kuba4
1 Institute for Space-Earth Environmental Research, Nagoya University
Furo-cho, Chikusa-ku, Nagoya 464-8601, Japan
2 Meteorological research Institute, Japan meteorological Agency
Nagamine 1-1, Tsukuba, 305-0052, Japan
3 National Research Institute for Earth Science and Disaster Resilience
Suyoshi, Nagaoka, 940-0821, Japan
4 Atmosphere and Ocean Research Institute, University of Tokyo
5-1-5 Kashiwanoha, Kashiwa, 277-8568, Japanmamuraka@isee.nagoya-u.ac.jp, mamuraka@mri-jma.go.jp
For a better understanding of the effects of aerosol particles on clouds andprecipitation, and a consequent improvement in short-range precipitation
forecasts and climate change projections, it is important to understand therelationship between the microphysical properties of various kinds of clouds
and the physico-chemical properties (CCN and IN abilities) of aerosol
particles in the air ingested by clouds. We have been conducted laboratory
experiments using MRI cloud simulation chamber, numerical simulation
using a parcel model with a detailed bin microphysical scheme and 2domensional kinetic model with a detailed bin microphysical scheme, groundbased monitoring of physico-chemical properties of atmospheric aerosols andin-situ measurements of aerosols, clouds and precipitation using an
instrumented aircraft.
In this talk, the aerosol effects on clouds and precipitation obtained from MRI
cloud simulation chamber experiments and numerical simulations will be
discussed.

Turbulence-induced broadening of cloud-droplet size
distributions: Implications for aerosol effects on
climateR. A. Shaw1 , W. Cantrell1 , K. K. Chandrakar1 , K. Chang1 , D.
Ciochetto1 , D. Niedermeier1,2 , M. Ovchinnikov3 , F. Yang1
1

Department of Physics, Michigan Technological University, Houghton, MI 49931, USA
2
Leibniz Institute for Tropospheric Research, 04318 Leipzig, Germany
3
Pacific Northwest National Laboratory, Richland, WA 99352, USA
rashaw@mtu.edu

Aerosol particles, such as sea salt, dust and anthropogenic pollution, influence the opticalproperties of clouds and the tendency of a cloud to form precipitation through droplet
collisions. Thus, a variety of ‘aerosol indirect effects’ on clouds are considered some ofthe primary uncertainties in the ability to quantify how climate will change in the future.
We have investigated cloud droplet growth in a turbulent environment under varying
levels of aerosol concentration [1]. The results reveal a surprising role of turbulence incloud droplet formation and growth that leads to two regimes: a polluted cloud regime inwhich thermodynamic conditions are rather uniform and cloud droplet sizes are similar,
and a clean cloud regime in which thermodynamic conditions are highly variable andcloud droplet sizes are very diverse. The narrowing of droplet size range under polluted
conditions introduces a new stabilizing factor by which increased aerosol concentration
can suppress precipitation and enhance cloud brightness.
Cloud droplet growth in a turbulent environment is studied by creating turbulent moist
Rayleigh-Bénard convection in a laboratory chamber [2]. Cloud formation is achievedby injecting aerosols into the water-supersaturated environment created by the isobaric
mixing of saturated air at different temperatures. In steady state, the injection andactivation of aerosol particles to form cloud droplets is balanced by cloud droplet growththrough vapor condensation and loss by gravitational settling. A range of steady-state
cloud droplet number concentrations is achieved by supplying aerosols at different rates.
As steady-state droplet number concentration is decreased the mean droplet size increases
as expected, but also the width of the size distribution increases. This increase in the width
is associated with larger supersaturation fluctuations due to the slow droplet microphysicalresponse (sink of the water vapor) compared to the fast turbulent mixing (source of thewater vapor). The boundary between the two regimes can be conveniently diagnosed witha cloud Damköhler number.
References[1] K. K. Chandrakar, W. Cantrell, K. Chang, D. Ciochetto, D. Niedermeier, M. Ovchinnikov, R. A. Shaw and F. Yang, Aerosol indirect effect from turbulence-induced
broadening of cloud-droplet size distributions, Proc. Nat. Acad. Sci. USA 113, 14243(2016).
[2] K. Chang, J. Bench, M. Brege, W. Cantrell, K. Chandrakar, D. Ciochetto, C. Mazzoleni, L. R. Mazzoleni, D. Niedermeier and R. A. Shaw, A laboratory facility to
study gas–aerosol–cloud interactions in a turbulent environment: The Π Chamber,
Bull. Amer. Met. Soc. 97, 2343 (2016).

Turbulence and cloud microphysics at a mountaintop
research station
S. Risius1 , H. Xu1,2 , F. Di Lorenzo1 , H. Xi1 , H. Siebert3 , R. A. Shaw4 ,and E. Bodenschatz1,51

Max Planck Institute for Dynamics and Self-Organization, 37077 Göttingen, Germany
2
Center for Combustion Energy and Department of Thermal Engineering, Tsinghua
University, 100084 Beijing, China
3
Leibniz Institute for Tropospheric Research, 04318 Leipzig, Germany
4
Department of Physics, Michigan Technological University, Houghton, MI 49931, USA
5
Laboratory of Atomic and Solid State Physics and Sibley School of Mechanical andAerospace Engineering, Cornell University, Ithaca, NY 14853, USA
haitao.xu@ds.mpg.de, hxu@tsinghua.edu.cn
Ground based measurements at high-altitude research stations play an important rolein cloud study, complementary to airborne campaigns. Using the meteorological datacollected by the German Weather Service (DWD) from 2000 to 2012 and turbulencemeasurements recorded by multiple ultrasonic sensors in 2010, we show that the Umweltforschungsstation Schneefernerhaus (UFS) located at a height of 2650 m, is a well-suitedstation for cloud-turbulence research. The wind at UFS is dominantly in the east-west
direction and nearly horizontal. The clouds are either from convection originating in thevalley in the east, or associated with synoptic-scale weather systems typically advectedfrom the west. The composite frequency spectrum of the air velocity shows a very wide
range of scales. “Small-scale turbulence”, which is often refers to air flow with timescales less than 1 hour or less, exhibits well-developed inertial ranges as measured fromthe velocity structure functions and possesses Taylor-microscale Reynolds numbers up to
104 , with the most probable value at ∼ 3000. In spite of the complex topography, theturbulence appears to be nearly as isotropic as many laboratory flows [1]. Measurementsof cloud microphysics also indicate that the mountaintop clouds are similar to elevatedclouds in continental conditions [2].
510

DWD data, saved every 1 minsonic sensor sampled at 10Hz
hot−wire, sampled at 1kHzsmoothed

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Fig. 1: Composite frequency spectrum
at UFS (symbols) and a smooth spectrum(solid line). The inset shows the local slopeof the smoothed spectrum, which shows arange where E(f ) ∼ f −5/3 .

References[1] S. Risius, et al. Schneefernerhaus as a mountain research station for clouds andturbulence, Atmos. Meas. Tech. 8, 3209 (2015).
[2] H. Siebert, et al. High-resolution measurement of cloud microphysics and turbulence
at a mountaintop station, Atmos. Meas. Tech. 8, 3219 (2015).

Grid convergence of the large-eddy simulation ofshallow maritime cumuli field: a case study using thesuper-droplet method as the cloud microphysics
model
Yousuke Sato1,2 , Shin-ichiro Shima2,1,∗ , Hirofumi Tomita1
1

2

RIKEN Advanced Institute for Computational Science, Japan
Graduated School of Simulation Studies, University of Hyogo, Japan∗
presenters shima@sim.u-hyogo.ac.jp

A number of numerical studies of shallow maritime cumuli field using a large-eddy simulation (LES) model have been reported. However, it is still not clear how small the spatial
grid must be to obtain an accurate numerical solution of a shallow maritime cumuli field.
In this study, a series of simulations are carried out to investigate the sensitivity of thenumerical results to the grid resolution of LES models. The experimental setup is basedon Barbados Oceanographic and Meteorological Experiment (BOMEX) [1]. The LES
model is constructed from the Scalable Computing for Advanced Library and Environment(SCALE) [2, 3]. For the cloud microphysics, the super-droplet method (SDM) [4, 5]
is used, which is a particle-based scheme to solve the mesoscopic governing equationsof the aerosol/cloud/precipitation particles. Therefore, the use of SDM can reduce theuncertainty and numerical diﬀusion of the cloud microphysical processes.
The results indicate that a grid resolution less than 10 m is necessary to accurately
simulate a shallow maritime cumuli field. Our grid refinement analysis shows that there
is a significant contribution from small cumulus clouds to the total cloud cover, and such
cumuli are generated by small-scale updrafts that can only be resolved at a fine resolution.
References[1] A. Siebesma et al., A Large-eddy simulation intercomparison study of shallow cumulus
convection, J. Atmos. Sci. 60, 1201-1219 (2003).
[2] S. Nishizawa, H. Yashiro, Y. Sato , Y. Miyamoto and H.Tomita, Influence of grid
aspect ratio on planetary boundary layer turbulence in large-eddy simulations, Geosci.
Model Dev. 8, 3393-3419 (2015).
[3] Y. Sato, S. Nishizawa, H. Yashiro, Y. Miyamoto, Y. Kajikawa and H. Tomita, Impactsof cloud microphysics on trade wind cumulus: which cloud microphysics processes
contribute to the diversity in a large eddy simulation, Prog. Earth Planet. Sc. 2, 23(2015).
[4] S. Shima, Estimation of the computational cost of Super-Droplet Method, RIMS
Kokyuroku 1666, 110-118 (2008).
[5] S. Shima, K. Kusano, A. Kawano, T. Sugiyama and S. Kawahara, The super-droplet
method for the numerical simulation of clouds and precipitation: a particle-based
and probabilistic microphysics model coupled with a non-hydrostatic model. Q.J.R.
Meteorol. Soc. 135, 1307-1320 (2009).

Diffusional growth of cloud droplets in turbulent clouds
Wojciech W. Grabowski1,2
12

National Center for Atmospheric Research, Boulder, USA
Institute of Geophysics, Faculty of Physics, University of Warsaw, Warsaw, Poland
grabow@ucar.edu

Cloud droplets grow by the diffusion of water vapor before collisional growth turns cloud
droplets into drizzle and rain drops. A simple model of droplet growth inside an adiabatic air
parcel rising through a cloud gives extremely narrow unimodal droplet size distributions. At thesame time, observed distributions are typically wide and multimodal. Cloud turbulence andturbulent entrainment are often invoked to explain this discrepancy. This study investigates themechanism affecting diffusional growth of cloud droplets referred to as the "large-eddy hopping"[1]. The key idea is that droplets arriving at a given location within a cloud follow different
trajectories through a cloud. Variability of the supersaturation along those trajectories results inthe width of the resulting droplet distribution. The supersaturation variability comes fromturbulent eddies, often resulting from cloud-edge instabilities and entrainment. Cloud droplets"hop" these eddies and grow in response to fluctuations of the supersaturation. This mechanism
was suggested a few decades ago [2], and was investigated using a cumbersome numericalapproach in subsequent studies [3,4]. We are developing a novel numerical model that merges
Eulerian approach for the cloud-scale flow with Lagrangian approach for cloud droplets
following the "super-droplet" method of Shima et al. [5]. The key element of the model is the
subgrid-scale (SGS) scheme that affects super-droplet motion and includes prediction of the SGS
supersaturation fluctuations along the droplet trajectory in addition to the supersaturation
predicted by the resolved cloud-scale flow model. A Langevin equation is formulated for the
SGS velocity and supersaturation fluctuations and its discrete-in-time Monte Carlo solutions areused in the SGS scheme. The most recent simulation results will be presented at the meeting.
References[1] W. W. Grabowski, and L.-P. Wang. Growth of cloud droplet in a turbulent environment.
Ann. Rev. Fluid Mech. 45, 293 (2013).
[2] W. Cooper. Effects of variable droplet growth histories on droplet size distributions. Part I:
Theory. J. Atmos. Sci. 46, 1301 (1989).
[3] S. G. Lasher-Trapp, W. A. Cooper, and A. M. Blyth. Broadening of droplet size distributions
from entrainment and mixing in a cumulus cloud. Q. J. R. Meteorol. Soc. 131, 220 (2005).
[4] W. A. Cooper, S. G. Lasher-Trapp, and A. M. Blyth, The influence of entrainment andmixing on the initial formation of rain in a warm cumulus cloud. J. Atmos. Sci. 70, 1727
(2013).
[5] S. Shima, K. Kusano, A. Kawano, T. Sugiyama, and S. Kawahara. The super-droplet method
for the numerical simulation of clouds and precipitation: A particle-based and probabilistic
microphysics model coupled with a non-hydrostatic model. Q. J. R. Meteorol. Soc. 135, 1307
(2009).

Droplets and Turbulence in Cloud Microphysics
Simulator
Toshiyuki Gotoh, Izumi Saito and Takeshi Watanabe
Department of Physical Science and Engineering, Nagoya Institute of Technology,
Gokiso, Showa-ku, Nagoya 466-8555, Japan
gotoh.toshiyuki@nitech.ac.jp
Direct numerical simulation of turbulent air ﬂow and the detailed computation of Lagrangian dynamics of cloud droplets with cloud microphysical processes are very usefuland powerful to obtain new knowledge about the fundamental cloud physics. However,the space-time range of the phenomena studied by this approach has still been limited
and not enough to link with the macroscopic numerical prediction of the evolution of awhole cloud because the computational barrier is very high. Therefore, in order to bridge
the computational gap between the microscopic and macroscopic approaches, the spacetime range of the numerical computation from the microscopic view points needs to beoverlapped with the smallest space-time resolution scale in the macroscopic computation.
For this purpose, we have developed a new method that enables us to seamlessly simulate
the continuous growth of cloud droplets to rain drops from the microscopic view points forlong time comparable with the time of the macroscopic evolution of cloud. A cubic box ascending with a mean updraft was introduced and the updraft velocity was self-consistently
determined in such a way that the mean turbulent velocity within the box vanished[1].
All the degrees of freedom were numerically integrated by using the Lagrangian dynamics
for the droplets and the Eulerian direct numerical simulation for the turbulence. The key
processes included were turbulent transport, condensation/evaporation, Reynolds number
dependent drag, collision-coalescence, and entrainment. We have examined the evolutionof the droplet spectrum over 400 s for the single-peaked initial droplet spectra, which
had the initial mean radius 10µm and the mean droplet density np = 125 cm−1 . The
turbulence was in steady state at Rλ = 130 and ϵ = 100 cm2 s−3 . It is found that the mass
spectrum peak moves slowly toward the larger radius in the early stage and then quickly
evolves to have the second peak through the autoconversion to the accretion state. Eﬀects
of the condensation and coalescence and the turbulence on the droplet evolution are also
discussed.
Acknowledgements This work is supported by Grants-in-Aid for Scientiﬁc Research Japan,
Nos.15H02218 and 26420106. The computer resourceswere supported by HPCI (Riken)
No. hp150088 and JHPCN No. jh160012. This work is partially supported by ”Nagoya
University HPC Research Project”.
References[1] Gotoh,T., Suehiro, T. and Saito, I. Continuous growth of cloud droplets in cumulus
cloud, New J. Phys. 18, 043042 (2016).

The new turbulent Leipzig Aerosol Cloud Interaction
Simulator (LACIS-T): Design and first results
Frank Stratmann1 , Dennis Niedermeier1 , Jens Voigtländer1 , DanielBusch1 , Jörg Schumacher2 , and Raymond A. Shaw3
1

Department of Experimental Aerosol and Cloud Microphysics, Leibniz Institute for
Tropospheric Research, 04318 Leipzig, Germany
2
Institute of Thermodynamics and Fluid Mechanics, Technical University Ilmenau,
98684 Ilmenau, Germany
3
Department of Physics, Michigan Technological University, Houghton, MI 49931 USA
stratmann@tropos.de, niederm@tropos.deOver 55 years ago, Henry Houghton published an essay in Science entitled ”Cloud physics:
Not all questions about nucleation, growth, and precipitation of water particles are yetanswered“ [1]. Since then, understanding of cloud processes has advanced tremendously,
yet we still face some of the basic questions Houghton drew attention to and many ofthem are related to the turbulent nature of atmospheric clouds.
Atmospheric clouds are highly non-stationary, inhomogeneous, and intermittent, and embody an enormous range of spatial and temporal scales. Strong couplings across thosescales between turbulent fluid dynamics and microphysical processes are integral to cloud
evolution. Turbulence drives entrainment, stirring, and mixing in clouds, resulting instrong fluctuations in temperature, humidity, aerosol concentration, and cloud particle
growth and decay. It couples to phase transition processes (such as nucleation, condensation, and freezing) as well as particle collisions and breakup. All these processes may feedback on the turbulent flow by buoyancy and drag forces and affect cloud dynamical processes up to the largest scales. Due to this, the examination of individual cloud processes
in the laboratory is mandatory for increasing our understanding of physical processes
occurring in clouds.
Therefore, at the Leibniz Institute for Tropospheric Research (TROPOS) in Leipzig, Germany, we have been building a moist air wind tunnel with precisely controlled turbulent
temperature and humidity fields i.e., adjustable supersaturation levels. This wind tunnel
will allow for the detailed investigations of the interactions between cloud microphysicalprocesses (e.g., particle activation to droplets and droplet freezing) under well-defined andreproducible laboratory conditions.
We are currently in the process of characterizing the tunnel with respect to the prevailingflow and thermodynamic conditions. Furthermore, we are installing a holographic system
for the determination of both, droplet sizes and trajectories. During the workshop, we
will introduce the wind tunnel itself, present very first results from the ongoing investigations (e.g., CFD simulations as well as measurements indicate that we can achieveatmospherically relevant dissipation rates on the order of 10−3 – 10−2 m2 s−3 ), and give asummary of the workshop on cloud microphysics-turbulence interaction held at TROPOS(28.02. – 01.03.17).
References[1] H. G. Houghton, Cloud Physics, Science 129, 307 (1959).

Future direction of turbulence and cloud modeling
H. Tomita1 , S. Nishizawa1 , Y. Sato1 , Y. Miyamoto1,3 , H. Yashiro1 , T.
Yamaura1 , R. Yoshida1,2 , S. A. Adachi1 , Y. Kajikawa1,2
1

RIKEN/ Advanced Institute for Computational Science
Research Center for Urban Safety and Security, Kobe University
3
Rosenstiel school of Marine and Atmospheric Science, University of Miami
2

htomita@riken.jp
Clouds are organized as a large-scale cloud disturbance, which plays an important role todetermine the global climate through the energy budget balance. Cloud resolving model(CRM) has been a vital tool for investigation of such mechanism, because it explicitly
represents the life-cycle of an individual cloud. Recently, a global CRM simulation withsuper-high resolution was conducted, focusing on the numerical convergence of statistics
of deep convection [1, 2].
This simulation brought several epoch making discoveries, it employed a Reynolds-Averaged
Naiver-Stokes approach as the turbulence expression within its limit of application. To
more precisely represent the cloud dynamics with much higher resolution, the turbulencescheme, particularly, should be more sophisticated. Large Eddy Simulation (LES) is apromising approach for this problem. However, some ambiguities in LES used in themeteorological research has remained in terms of limit of application. Our research groupclarified it, based on a theoretical reconsideration[3]. As well as the turbulence scheme,
more detail microphysics scheme also is been developed, based on more theoretical principle. The impact of its complexity level, e.g., one-, two-moment, and spectral bin schemes
was inspected on the stratocumulus with high resolution simulations [4].
For more precise evaluation of global climate, the establishment of global LES is necessary.
However, it is still difficult, even if we use the current highest performance computer, Thisdifficulty comes from both of poor computational power and premature of theory, e.g.,
moist LES; the way to true global LES is long and tough. In this talk, we show several
issues that should be resolved toward the goal and discuss the strategy to tackle them,
reviewing our recent achievements for cloud and turbulence.
References[1] Y. Miyamoto, Y. Kajikawa, R. Yoshida, T. Yamaura, H. Yashiro, H. Tomita Deepmoist atmospheric convection in a sub-kilometer global simulation, Geophys. Res. Lett.,
doi:10.1002/grl.50944 (2013).
[2] Y. Kajikawa, Y. Miyamoto, R. Yoshida, T. Yamaura, H. Yashiro, H.Tomita, Resolution dependence of deep convections in a global simulation from over 10-kilometer to sub-kilometer
grid spacing, Prog Earth Planet Sci, 3:16 (2016).
[3] S. Nishizawa, H. Yashiro, Y. Sato, Y. Miyamoto,H. Tomita, Influence of grid aspect ratio
on planetary boundary layer turbulence in large-eddy simulations, Geosci. Model Dev., 8,3393-3419 (2015).
[4] Y. Sato, S. Nishizawa, H. Yashiro, Y. Miyamoto, Y. Kajikawa, H. Tomita, Impacts of cloud
microphysics on trade wind cumulus: which cloud microphysics processes contribute to thediversity in a large eddy simulation?, Prog Earth Planet Sci, 2:23 (2015).

Resolving Submeter-Scale Processes
at the Top of Stratocumulus Clouds
Juan Pedro Mellado
Max Planck Institute for Meteorology, Hamburg, D-20243 Germany.
juan-pedro.mellado@mpimet.mpg.de
Besides their importance for climate research and numerical weather prediction, stratocumulus provide an excellent paradigm to study cloud turbulence, for several reasons.
First, meter- and submeter scale processes in the cloud-top region play crucial roles in theevolution of whole cloud systems. These include not only cloud microphysics but also turbulence entrainment in a stratified medium, shear instabilities, and convective instabilities
induced by radiative transfer and droplet evaporation. The problem is very rich. Second,
they are often statistically quasi-steady and quasi-homogeneous in the horizontal directions, to a good approximation. Hence, the number of independent variables necessary
to characterize statistical properties is still manageable. Third, as shown in the figure,high-resolution simulations and measurements have started to provide accurate data on
submeter scales [1, 2, 3]. This allows us to perform detailed and systematic analyses of
the cloud-top region. In this talk, I will illustrate how some of these analyses, based on
direct numerical simulations, are shedding new light about the relevance of meter- andsubmeter scale processes, like droplet evaporation and gravitational settling.

Fig. 1: Vertical cross-sections illustrating the meter- and submeter-scale structure of thecloud-top region. Different properties define different interfacial layers: enstrophy defines
the entrainment zone, buoyancy the capping inversion, and liquid the cloud boundary.
From [3].
References[1] S. P. Malinowski, et al., Physics of Stratocumulus Top (POST): turbulent mixing
across capping inversion, Atmos. Chem. Phys., 13, 15234–15269 (2013).
[2] M. J. Beals, et, al., Holographic measurements of inhomogeneous cloud mixing at thecentimeter scale, Science, 350, 87–90 (2015).
[3] J. P. Mellado. Cloud-top entrainment in stratocumulus clouds, Annu. Rev. Fluid
Mech. 41, 145–169 (2017).

Nonequilibrium subgrid-scale models in LES
alternative to the Smagorinsky model
Kiyosi Horiuti
Department of Mechano-Aerospace Engineering, Tokyo Institute of Technology,
2-12-1 O-okayama, Meguro-ku, Tokyo 152-8552, Japankhoriuti@mes.titech.ac.jp
Turbulence consists of eddies with an extensive range of its size and exhibits strongly
unsteady behaviors. In large-eddy simulation (LES), reduction of the number of freedom
is achieved by applying the coarse graining of the small scales. The subgrid-scale (SGS)
stress τij (= ui uj − ui uj ) results from the coarse graining. The governing equation for
the SGS energy Ksgs (= τii /2) is given as K̇sgs = P − εsgs + · · ·, where f˙ is material
derivative of f , P = −τij S ij is the SGS production term, εsgs the SGS dissipation andS ij the strain-rate tensor. Approximation of τij has been commonly carried out using
the eddy viscosity coeﬃcient model. When the equilibrium state P ≈ εsgs is assumed,
the Smagorinsky model [1] is obtained. In this talk, we review the recent developmentin the SGS modeling which accounts for unsteadiness and nonequilibrium state in the
SGS. Spectral counterpart of the Smagorinsky model is the Kolmogorov −5/3 spectrum.
We consider incorporation of the nonequilibrium state in the energy spectrum using theone-equation model [2]. Decomposition of the SGS energy in the one-equation model
is derived as a solution of the perturbation expansion in the ratio of the characteristic
time over which the SGS statistics vary and the large-eddy turnover time. Deviationfrom the base state yields the terms whose spectral counterparts are those with the −7/3
and −9/3 powers. We consider the non-equilibrium Smagorinsky model, in which Ksgs
corresponding to the −7/3 spectrum is added to the Smagorinsky model. It is shown that
this model provides correct direction of the energy cascade and is capable of predicting
the time-lag in the temporal variations in the grid-scale energy, Ksgs , P and εsgs [2].
An alternative SGS model which is capable of incorporation of nonequilibrium state is2
the nonlinear model [3], τij ≃ ∆ {(S ik S kj − Ωik Ωkj ) − (S ik Ωkj + S jk Ωki )}/12, where Ωij
the vorticity tensor. τij is expanded in the velocity-gradient tensors. The governing
equation for τij is transformed into the algebraic equation for τij by approximating τ̇ij ∝(P − εsgs ). This algebraic SGS stress model (ASM) represents nonequilibrium state, andits approximate solution yields the nonlinear model. Filtered DNS data shows that the
eigenvectors of the exact τij and S ij shows nonalignment, whereas they are aligned in the
eddy-viscosity model. In the nonlinear model, nonalignment is achieved due to the second
term in the model. It is shown that this term makes no contribution to the production
term for Ksgs , but it is relevant for the generation of the SGS enstrophy. The nonlinear
model yielded the result which is in the closest agreement with the filtered DNS data.
References[1] J. Smagorinsky, General circulation experiments with the primitive equations,
Monthly Weather Rev. 91, 99 (1963).
[2] K. Horiuti and T. Tamaki, Nonequilibrium energy spectrum in the subgrid-scale oneequation model in large-eddy simulation, Phys. Fluids 25, 125104 (2013).
[3] K. Horiuti, Roles of nonaligned eigenvectors of strain-rate and subgrid-scale stresstensors in turbulence generation, J. Fluid Mech. 491, 65 (2003).

A research plan of typhoon observation using an aircraft in Japan
Kazuhisa Tsuboki
Institute for Space-Earth Environmental Research (ISEE), Nagoya University
Furo-cho, Chikusa-ku, Nagoya, 464-8601 Japane-mail: tsuboki@nagoya-u.jp

Typhoons are the most devastating weather system occurring in the western North Pacific and
the South China Sea. Violent wind and heavy rainfall associated with a typhoon cause huge disasterin East Asia including Japan. In 2013, Supertyphoon Haiyan struck the Philippines caused a very
high storm surge and more than 7000 people were killed. In 2015, two typhoons approached themain islands of Japan and severe flood occurred in the northern Kanto region. Typhoons are still thelargest cause of natural disaster in East Asia. Moreover, many researches have projected increase of
typhoon intensity with the climate change. This suggests that a typhoon risk is increasing in East
Asia. However, the historical data of typhoon include large uncertainty. In particular, intensity dataof the most intense typhoon category have larger error after the US aircraft reconnaissance of
typhoon was terminated in 1987.The main objective of the present study is improvements of typhoon
intensity estimations and of forecasts of intensity and track. We will perform aircraft observation of
typhoon and the observed data are assimilated to numerical models to improve intensity estimation.
Using radars and balloons, observations of thermodynamical and cloud-microphysical processes oftyphoons will be also performed to improve physical processes of numerical model.
In typhoon seasons (mostly in August and September), we will perform aircraft observations of
typhoons. Using dropsondes from the aircraft, temperature, humidity, pressure, and wind aremeasured in surroundings of the typhoon inner core region. The dropsonde data are assimilated to a
cloud-resolving model which has been developed in Nagoya University and named the Cloud
Resolving Storm Simulator (CReSS). Then, more accurate estimations and forecasts of the typhoon
intensity will be made as well as typhoon tracks. Furthermore, we will utilize a ground-based
balloon with microscope camera, X-band precipitation radar, Ka-band cloud radar, aerosol sonde,
and a drone to observe typhoon-associated clouds and precipitation. After a test flight in March 2017,
typhoon observations will be made for next 4 years; 2017-2020. The main target area of observationis the south of Okinawa where a typhoon reaches the maximum intensity and often changes its
moving direction.
This research will advance aircraft observation technique of typhoon in Japan. The aircraft
observation will be a breakthrough to improve typhoon intensity estimations. Assimilation of theaircraft observation data to the cloud-resolving model will improve intensity estimations andforecasts of typhoons. This is the first step for the future advanced aircraft observation and willcontribute to prevention or reduction of typhoon disasters.

Numerical experiments of aerosol impacts on warm clouds using acloud-resolving model with the super droplet method
Kazuya Moriki1, Shin-ichiro Shima2, and Kazuhisa Tsuboki1
1: Institute for Space-Earth Environmental Research, Nagoya University, Nagoya, Japane-mail: moriki@rain.isee.nagoya-u.ac.jp
2: Graduate School of Simulation Studies, University of Hyogo, Kobe, Japan

Aerosol affects formation and behavior of clouds. A well-known hypothesis is that precipitation amountdecreases and the cloud lifetime increases with high number concentration of aerosol while precipitation
amount increases and cloud lifetime decreases with smaller number concentration of aerosol. On the other hand,clouds also affect amount and distribution of aerosol. When the cloud evaporates, aerosol is discharged to theatmosphere and the state of the aerosol changes through the rain-out, wash-out and liquid-phase chemical
reaction. To properly consider the interaction of aerosol and clouds, a detailed numerical experiment based on abasic physical law is necessary. In particular, an impact of aerosol on a very intense rainfall of about 100 mm
hr-1 from a warm cloud should be studied using a detailed cloud model with resolving size-distribution ofparticles.
Takahashi et al. (1989) investigated precipitation process off the Hawaii Island using a numerical modelwith bin method of cloud. They found that the process of drizzle is important for heavy rain formation. In thepresent study, the Super Droplet Method is used to calculate the behavior of aerosol, cloud, and precipitation
particles. Atmospheric flow field is calculated by the Cloud Resolving Storm Simulator (CReSS). The sounding
data of the atmosphere was provided by Wyoming University.
As a result of numerical experiments, precipitation decreased while cloud increased with the increase of
initial aerosol number concentration. Particle growth was observed around a radius of 0.3 mm. This indicatesformation of drizzle particles and their growth. When the initial aerosol number concentration decreased,
precipitation increased. Particle growth was observed around 0.6 mm while the formation of drizzles was
suppressed.
From the present results, the effect of aerosol on cloud lifetime was suggested for a warm clouds such as therainband formed off the Hawaii Island. When the initial aerosol number concentration is low, precipitation was
remarkably large. The lifetime of cloud becomes long with increase of aerosol number concentration. If it is toolarge, evaporation of cloud droplets becomes dominant and the lifetime of cloud decreases.

Environmental stability control of the organization of atmosphericmoist convection
Tetsuya Takemi
Disaster Prevention Research Institute, Kyoto University, Gokasho, Uji, Kyoto 611-0011, Japan

takemi@storm.dpri.kyoto-u.ac.jp
Moist convection in the atmosphere has a variety of organization modes at mesoscales: multi-cell storms,
supercell storms, squall lines, rainbands, cloud clusters, etc., which are generally referred to as mesoscaleconvective systems (MCSs). Moist convection acquires such an organization mode from spontaneously
organizing processes and at the same time depends critically on its environmental conditions. Both the internal
physical processes in cumulus clouds and the interaction between convection and environmental atmosphere
are keys to understand the mechanisms for the organization of moist convection at mesoscales.
In this presentation, I will firstly overview the recent advances in numerical modeling studies on theorganization of MCSs.
Next, based on our studies [1, 2], I will talk about the results of the convection-resolving simulations ofconvection and MCSs with the use of a nonhydrostatic atmospheric model, the Weather Research andForecasting (WRF) model [3]. In our studies, we investigated the sensitivity of the structure and intensity ofsquall lines, one of the major organization mode among MCSs, to the vertical profile of temperature andmoisture that are intended to represent a tropical, oceanic, and a midlatitude, continental environment byconducting a set of numerical experiments at a convection-resolving resolution. In the experiments the vertical
distributions of convective available potential energy (CAPE) for air parcels originating at various heights
were controlled by changing relative humidity for the tropical and the midlatitude condition. It was shown thatthe strength and areal extent of updrafts within the simulated squall lines are significantly regulated byenvironmental temperature lapse rate. A condition with a larger lapse rate led to the development of widespread,strong updrafts. The difference in the vertical profile of buoyancy for lifted air parcels was identified as a key
to delineate the difference in the updraft statistics under different thermodynamic conditions. In contrast, it
was found that the precipitation amount is controlled by the vertical distribution of CAPE. The precipitation
amount increases with the increase in the depth of the layer having a significant amount of CAPE.
Furthermore, the relationship between cumulus convection and environmental moisture in a tropical oceanic
region was investigated by conducting convection-resolving simulations at the 100-m grid resolution. It was
shown that the cloud cover whose tops exceed a middle level sharply increases with the increase in precipitablewater vapor over about 55 mm. The increase in relative humidity in a lower layer resulted in the increase incloud cover at a level above the humid layer. The existence of updraft cores that were less diluted with theenvironment was demonstrated. It is considered that cloud-core parcels are less susceptible to the negative
effects of dilution with the environment and survive to penetrate to upper levels, which contributes to themoistening of the environmental atmosphere. The existence of updraft cores plays a key role in the interrelationship between cumulus convection and its environment.
References[1] T. Takemi, Convection and precipitation under various stability and shear conditions: Squall lines in tropicalversus midlatitude environment, Atmos. Res. 142, 111 (2014).
[2] T. Takemi, Relationship between cumulus activity and environmental moisture during the
CINDY2011/DYNAMO field experiment as revealed from convection-resolving simulations, J. Meteor. Soc.
Japan 93A, 41 (2015).
[3] W. C. Skamarock, J. B. Klemp, J. Dudhia, D. O. Gill, D. M. Barker, M. G. Duda, X. Y. Huang, W. Wang, J.
G. Powers, A Description of the Advanced Research WRF Version 3, NCAR Tech. Note, NCAR/TN-47+ STR
113 pp., (2008)

Campus Map
Hall (1F, Building 4)

JR Tsurumai St.

Café Sala (Banquet)Lunch Map
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① 大学生協会館 (レストラン, コンビニ) / University hall Cafeteria (1F, 2F) & food shop (1F)
② 大学生協コンビニ＆軽食(2F) / University convenience store & restaurant (2F, light meal)③ Café Sala (cafe)④ さぼてん （定食） / Saboten (restaurant, set meal)⑤ カフェハウスリーベ （喫茶） / Café hause LIEBE (Cafe)⑥ みやこ （うどん, 定食） / Miyako (restaurant, udon noodle & set meal )⑦ サークルＫサンクス （コンビニ） / Circle-K Sankus (convenience store)⑧ 古味煮亭 （定食） / Komini-tei (restaurant, a set meal)⑨ 清水庵曙店 （そば, うどん） / Shimizu-an (restaurant, buckwheat noodles (soba), udon )⑩ カフェドカプチーノ （喫茶） / Cafe’d Cappuccino (Cafe)⑪ ソレイユ（レストラン、喫茶） 名大病院最上階 / Soleiyu (restaurant, cafe) in Nagoya Uni. Hospital (14F)⑫ イオン千種ショッピングセンター （レストラン街，フードコートあり） / AEON Chikusa shopping center(many restaurants & food court)⑬ 浩養園（ビアガーデン，レストラン） / Kouyouen (Beer restaurant)

How to access Internet using wireless LAN
1．Using “eduroam”
Easiest way to accessinternet is to use“eduroam” if you have anexperience to use it.
Please see the map which
represents the area you
can use eduroam in
NITech campus (Area islimited).

Front gate

Information for eduroam : https://www.cc.nitech.ac.jp/eduroam/index-en.html#

2．Using our campus network
If you want to access Internet on your PC via our campus network,
please get a sheet stating security key and ID/PW at an information
clerk, and try to access by following the below procedure.
i.

ii.

Connect to the access point of
wireless LAN (needs to entersecurity key that stated in asheet)
Execute WEB authentication(Activate WEB browser, enter
ID/PW in blank and click
log-on bottom )ID
PW
log-onNote: If you do not access Internet during 10～15 minutes, the WEB authentication is
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Organized by
Toshiyuki Gotoh
Takeshi Watanabe
Takashi Naitoh
Izumi Saito
Graduate School of Engineering, Nagoya Institute of Technology
Tel: +81-(0)52-735-5377
URL : http://comphys.web.nitech.ac.jp/cloud2

Supported by
Grant-in-Aid for Scientific Research (A) 15H02218