Workshop on Japanese-French Model Studies of Planetary Atmospheres
CPS, Kobe University, Kobe, Japan, 11-15 May 2015

Numerical Experiments on DustDevils, Atmospheric Vortices, andDust Transport on Earth
Tetsuya Takemi
Disaster Prevention Research InstituteKyoto University
Collaborators: Hiroshi Ohno, Yuhei Hayashi,
Yoshiaki Miyamoto

Atmospheric vortices: dust devils(Balme and Greeley 2006)(Gu et al. 2008)

Atmospheric vortices: tornadoes(Rotunno 2013)
Single cell

Double cell

Multiplevortices(Fiedler 2009)(Rotunno 2013 [Adapted from Davies-Jones(1986)])

Motivation and purpose• Dynamics of vortices has been investigated by laboratory
experiments and numerical models.
• Numerical models are a useful tool to investigate thedynamics of vortices.
• Previous numerical models mostly are based on an
incompressible fluid; however, this assumption is not valid incases with very high wind speeds and density stratification.
• Therefore, we investigate the dynamics of vortices with nonhydrostatic, compressbile atmospheric models.

1.5kmLarge-eddy simulation of dust devils

1km

•••••
•
•

Numerical model: WRF/ARW
Domain: 1 km x 1 km x 1.5 km
Resolution: 3 m (horizontal)
Lateral boundaries: periodic
Surface: momentum & heat fluxes
SGS model: Smagorinky
Base-state: initially at rest

Vertical profile of potential temperature at
Initial and 3600 s times.
(Ohno and Takemi 2010a)

Convective cell and vortices
Horizontal cross section of vertical velocity andvertical vorticity at the 50-m height

Y(m)

(m/s)

X(m)
(Ohno and Takemi 2010a)

Intensification of vortices by merger
5050s

5060s

5070s

5080s

(Ohno and Takemi 2010a)

Merger + Tilting and Stretching = Intense dust devilsTemporal evolution of vorticess 1|p’| > 10 Pa|ζ| > 0.15 s-1(Ohno and Takemi 2010a)

Sensitivity of dust devils to mean winds
Mean wind: U0=0, 5, 10, 15 (m/s)
1.5km

Initial mean winds

2km(Ohno and Takemi 2010b)

Dependence of CBL structure on mean wind

Vertical velocity at
z=50 m (color) andvorticity (sold lines)

U0=0

U0=5

U0=10

U0=15

Temporal evolution of vortices
Definition of vortices:|p’| > 25 Pa, |ζ| > 0.15 s 1(a) U0 = 0(b) U0 = 5(c) U0 = 10(d) U0 = 15(Ohno and Takemi 2010b)

Vortex chambers in tornadoes studies
Ward (1972) type

Fiedler (1994) typeCirculation induced by rotating disk
and prescribed updraft forcing
𝑧Upwardforcing

𝐹𝑧𝑟inflow

Ω=𝑓2rotation(Church et al., 1979)

Both for laboratory andnumerical studies

For numerical studies

Numerical models• 2D model: Nonhydrostatic axisymmetric model (Miyamotoand Takemi 2010, Miyamoto 2010)• 3D model: Nonhydrostatic meteorological model, WRF/ARW(Skamarock et al. 2008)– Dry atmosphere– Turbulence: Smagorinsky-Lilly (Lilly 1962)– Surface friction: With friction (Garratt 1977) or None
– Base state: Supercell-storm environment (Weisman andKlemp 1982)– Upward forcing at the vortex center– Computational domain size
† 𝑅 = 6000 m, 𝐻 = 12000 m (2D)
† 𝐿𝑥 = 𝐿𝑦 = 6000 m, 𝐻 = 15000 m (3D)

Evolution and transition of vortex (2D & 3D)
Surface friction

Garratt (1977)

Rotation rate parameter𝑓 = 0.02 (s-1)

2D model(Axisymmetric model)

3D model (WRF)∆𝑟 = 30 m, Δ𝑧 = 5 m

Δ𝑥 = ∆𝑦 = 30 m, Δ𝑧 = 4.5 m

Vectors: velocity (m s-1)
color shading: tangential wind (m s-1)

Vectors: surface winds (m s-1)
Color shagging: vorticity (s-1)

Dependence on surface friction (3D)
Resolution∆𝑥, ∆𝑦, ∆𝑧min = 30, 30, 4.5 [m]Rotation rate parameter𝑓 = 0.02 (s-1)

Surface friction

With friction, No friction

Radial and vertical cross section

With surface friction

No friction
Color shading & contours: tangential wind (m/s)
Vectors: radial and vertical wind (m/s)

Transition to multiple vortices
Resolution∆𝑥, ∆𝑦, ∆𝑧min = 30, 30, 4.5 [m]Surface friction

With friction, No friction

Rotation rate parameter

𝑓 =0.10 (s-1)

Asymmetric component of nearsurface vortex

3D view of vorticity

𝑡 = 800 s𝒛 = 𝟏𝟎𝟎 m
Vector: asymmetric component ofsurface wind (m/s)
Color shading: asymmetric componentof pressure perturbation (Pa)

Vector: surface wind (m/s)
Color shading: vorticity (s-1)

Diurnal variation of dust layer over Gobi Desert
Surface meteorology
Temp

Temporal change of vertical profile of dust
content observed by lidar during 11-12
April 2002 in ADEC IOPWind speedRelativehumidity(Yasui et al. 2005)

ADEC: Asian Dust Experiment on
Climate Impact (2000-2005)
11 April

12 April

13 April(Takemi et al. 2005)(Picture by Dr. M. Yasui, NICT)Initial stability profiles• EXP1: 00 UTC (06 LT) 13 April
2002 sounding at a Gobi
desert; w/strongly stablesurface inversion capped by astable PBL• EXP2: created by 3-day spinup run from EXP1 sounding;w/surface inversion layer
capped by a residual neutrallayer(Takemi 2008, 2012)

Diurnal variation of the atmosphere
Numerical experiments with a nonhydrostatic model, ARPS
Diurnal variation of the horizontally averaged virtual potential
temperature & cloud mixing ratios;
no cloud formation in EXP1, while active cloud development in EXP2

EXP1

EXP2

PBL
growthSunrise

SunsetCumuluscloudPBL
growthSunsetSunrise(Takemi 2008, 2012)

Diurnal variation of dust transport: 100-m grid
Numerical experiments with a nonhydrostatic model, ARPS
EXP1
EXP2

Column dust content - EXP1:1.2 mg/m2- EXP2: 0.63 g/m2
(Takemi et al. 2006; Takemi 2008, 2012)

Color: Upward dust flux（mg/m2/s）
Black contour: Dust conc （mg/m3）
Dotted contour: Cloud boundary

Severe dust storm case
5 May 1993 Dust Storm over Gobi

(Mitsuta et al. 1995; Takemi 1999)• Dust transport by squall line
• High concentration within surface coldair pool
• Moderate concentration within updraft
and system’s rearward• Low concentration at upper levels(Takemi 2005)

Dust concentration

Column dust content• Severe storm case: 12.5 g/m2
• Fair-weather condition (with shallow surface stablelayer): 0.63 g/m2
• Fair-weather condition (with deep surface stablelayer): 1.2 mg/m2

Concluding remarks• The intensification of vortices through mergers and thetransition of vortex structure are successfully simulated withhigh-resolution simulations by non-hydrostatic
meteorological models.
• A grid spacing of 100 m seems to capture the diurnal cycle of
PBL and dust transport associated with not only shallow
convection but also deep convection rooted in PBL.
• Nonhydrostatic modeling as a vortex chamber can be used
for studies on dust devils on Earth and Mars.
• Dust transport associated with dust devils and its
consequences on larger-scales under realistic meteorologicalconditions should be further investigated.