Post on 05-Jul-2020
Progress in the Development of Quasi-3D Multiscale Modeling Frameworkas a Physics Option in CAM-SE Joon-Hee Jung, Celal S. Konor, David A. Randall,
Department of Atmospheric Sciences, Colorado State University, USA
Peter Lauritzen, and Steve GoldhaberNational Center for Atmospheric Research, Boulder, Colorado, USA
CESM: Atmosphere Model Working Group Meeting NCAR, Mesa Lab, Boulder, CO, February 19-21, 2019
This research has been supported by NSF AGS-1500187 (and partly by DOE ACME DE-SC0016273 and DOE CMDV DE-SC0016305).
Quasi-3D Multiscale Modeling Framework
z
x
y
z
x
y
GCM grid CRM grid GCM grid cell CRM ghost grid
Q3D MMF MMF
CRMs in GCM grid columns are seamlessly connected;
CRMs are three-dimensional, although covering only channel-like domains.
Two segments of CRMs perpendicularly pass each other (but don’t intersect) at the center of each GCM cell;
Jung and Arakawa (2010, 2014), Jung (2016)
Quasi-3D Multiscale Modeling Framework
z
x
y
z
x
y
GCM grid CRM grid GCM grid cell CRM ghost grid
Q3D MMF MMF
Surface orography can be resolved by the CRMs;Cloud systems travel freely along the CRM channels;
Subgrid-scale vertical momentum transport can be directly simulated.
CRMs in GCM grid columns are seamlessly connected;
CRMs are three-dimensional, although covering only channel-like domains.
Two segments of CRMs perpendicularly pass each other (but don’t intersect) at the center of each GCM cell;
Jung and Arakawa (2010, 2014), Jung (2016)
Development of a Global Q3D MMF
GCM component: dynamical core based on the cubed sphere grid
Quadrilateral geometry allows a straightforward extension to the sphere of our limited-area model based on rectangular Cartesian coordinate. Cubed sphere grid has relatively uniform horizontal grid spacings almost everywhere, allowing the CRM channels to be almost uniformly distributed.
CRM component: the CRM used in the limited-area Q3D MMF
A global version of Q3D MMF has been created.
Development of a Global Q3D MMF
Group 1
Group 2
Group 3 CAM-SE CSLAM dynamical core
Vector Vorticity Model(CRM developed at CSU/UCLA)
+
GCM component: dynamical core based on the cubed sphere grid
Quadrilateral geometry allows a straightforward extension to the sphere of our limited-area model based on rectangular Cartesian coordinate. Cubed sphere grid has relatively uniform horizontal grid spacings almost everywhere, allowing the CRM channels to be almost uniformly distributed.
CRM component: the CRM used in the limited-area Q3D MMF
A global version of Q3D MMF has been created.
Vector Vorticity Modelas a CRM Component of the Q3D MMF
3D nonhydrostatic anelastic model;
Pressure gradient force is eliminated from the governing Eqs;
Vertical velocity is a solution of a 3D elliptic equation;
CRM-type physics parameterizations are included.
The prognostic dynamical variables are vorticity components;
Vector Vorticity Modelas a CRM Component of the Q3D MMF
3D nonhydrostatic anelastic model;
Pressure gradient force is eliminated from the governing Eqs;
Vertical velocity is a solution of a 3D elliptic equation;
CRM-type physics parameterizations are included.
Suitable for the Q3D MMF It is convenient to formulate the lateral boundary conditions required by the narrow CRM channels and the lower boundary condition over steep topography.
The prognostic dynamical variables are vorticity components;
Implementation of the Vector Vorticity Dynamical Core on Cubed Sphere
for Use in the Q3D MMFJoon-Hee Jung, Celal S. Konor, and David Randall
J. Adv. Model. Earth Syst. (in press)
Implementation of the Vector Vorticity Dynamical Core on Cubed Sphere
for Use in the Q3D MMFJoon-Hee Jung, Celal S. Konor, and David Randall
J. Adv. Model. Earth Syst. (in press)
100
10-1
10-2
10-3
10-4
10-5
100 2550 6.2512.5
Nor
mal
ized
Erro
rs
Grid Size (km)
day 12
Rotation of a cosine bell along the equatorFollowing Williamson et al. (1992)
90 180 270 0 90135 225 315 45Longitude (degrees)
3525
45
155
-35-25
-45
-15-5
Latit
ude
(deg
rees
)
VVM: Barotropic Instability Test (Case 1)Initial Vorticity
Similar to Galewsky et al. (2004)
90 180 270 0 90135 225 315 45Longitude (degrees)
3525
45
155
-35-25
-45
-15-5
Latit
ude
(deg
rees
)
VVM: Barotropic Instability Test (Case 1)Initial Vorticity
3525
45
155
-35-25
-45
-15-5
90 180 270 0 90135 225 315 45
3525
45
155
-35-25
-45
-15-5
90 180 270 0 90135 225 315 45Longitude (degrees)
Latit
ude
(deg
rees
) Longitude-latitude grids
Longitude (degrees)
Cubed-sphere grids
3525
45
155
-35-25
-45
-15-5
90 180 270 0 90135 225 315 45
3525
45
155
-35-25
-45
-15-5
90 180 270 0 90135 225 315 45Longitude (degrees)
Latit
ude
(deg
rees
) Longitude-latitude grids
Longitude (degrees)
Cubed-sphere gridst = 168 h
dx = dy ~ 100 km
dx = dy ~ 6 km
-8 -7 -6 -5 -4 -3 -2 -1 1 2 3 4 5 6 7 8 10-5 (s-1)
Similar to Galewsky et al. (2004)
-45
3525
45
155
-35-25-15-5
90 180 270 0 90135 225 315 45-45
3525
45
155
-35-25-15-5
90 180 270 0 90135 225 315 45Longitude (degrees)
Latit
ude
(deg
rees
) Longitude-latitude grids
Longitude (degrees)
Cubed-sphere grids
90 180 270 0 90135 225 315 45Longitude (degrees)
3525
45
155
-35-25
-45
-15-5
Latit
ude
(deg
rees
)
VVM: Barotropic Instability Test (Case 2)Initial Vorticity
t = 120 hdx = dy ~ 100 km
-16 -14 -12 -10 -8 -6 -4 -2 2 4 6 8 10 12 14 16 10-5 (s-1)
-45
3525
45
155
-35-25-15-5
90 180 270 0 90135 225 315 45-45
3525
45
155
-35-25-15-5
90 180 270 0 90135 225 315 45Longitude (degrees)
Latit
ude
(deg
rees
) Longitude-latitude grids
Longitude (degrees)
Cubed-sphere grids
90 180 270 0 90135 225 315 45Longitude (degrees)
3525
45
155
-35-25
-45
-15-5
Latit
ude
(deg
rees
)
VVM: Barotropic Instability Test (Case 2)Initial Vorticity
t = 120 hdx = dy ~ 100 km
-45
3525
45
155
-35-25-15-5
90 180 270 0 90135 225 315 45-45
3525
45
155
-35-25-15-5
90 180 270 0 90135 225 315 45Longitude (degrees)
Latit
ude
(deg
rees
) Longitude-latitude grids
Longitude (degrees)
Cubed-sphere gridsdx = dy ~ 6 km
-16 -14 -12 -10 -8 -6 -4 -2 2 4 6 8 10 12 14 16 10-5 (s-1)
VVM: Baroclinic Instability TestIdealized setting: f = 2Ωsin ϕ +π 4( )
Zonally Uniform Initial State
252015105 30 35 40
(m/s)
Latitude (deg)
45 15 -45-15
20
15
10
5
0
25
He
igh
t (k
m)
320
720
290
300
270
280
3525
45
155
-35-25
-45
-15-5
-180 0 180-90 90
Latit
ude
(deg
)
Longitude (deg)
302 300
266
Initial Perturbation on Potential Temperature
VVM: Baroclinic Instability TestIdealized setting: f = 2Ωsin ϕ +π 4( )
Zonally Uniform Initial State
252015105 30 35 40
(m/s)
Latitude (deg)
45 15 -45-15
20
15
10
5
0
25
He
igh
t (k
m)
320
720
290
300
270
280
3525
45
155
-35-25
-45
-15-5
-180 0 180-90 90
Latit
ude
(deg
)
Longitude (deg)
302 300
266
Initial Perturbation on Potential Temperature
3525
45
155
-35-25
-45
-15-5
-180 -90 0 90 180-135 -45 45 135
3525
45
155
-35-25
-45
-15-5
-180 -90 0 90 180-135 -45 45 135
3525
45
155
-35-25
-45
-15-5
-180 -90 0 90 180-135 -45 45 135
3525
45
155
-35-25
-45
-15-5
-180 -90 0 90 180-135 -45 45 135
Longitude (degrees) Longitude (degrees)
Latit
ude
(deg
rees
)
Longitude-latitude grids Cubed-sphere grids
dx = dy ~ 100 km
dx = dy ~ 12 km
t = 288 h
Horizontal Grid Structure of the Q3D MMF
GLL grid & physics grid (CSLAM configuration)
x
y
x
y
Low-resolution GCM grid High-resolution CRM grid
The CRMs are coupled with the physics grids.
Two Grid Systems
For communication, horizontal interpolation and cell-average are needed.
Example of Horizontal Grid Distribution
CRM grid channels
Group 1
Group 2 Group 3
Group 1
Group 2
Group 3
Nphy = 3, Ne = 5, Nc = 25 (dxGCM ~ 660 km, dxCRM ~ 26 km)
# of CRM-grid columns on the sphere = (# of physics-grid columns) x Nc x 2 = 67,500# of physics-grid columns on the sphere = (Nphy x Ne) x 6 = 1,3502
Example of Horizontal Grid Distribution
CRM grid channels
Group 1
Group 2 Group 3
Group 1
Group 2
Group 3
Nphy = 3, Ne = 5, Nc = 25 (dxGCM ~ 660 km, dxCRM ~ 26 km)
# of CRM-grid columns on the sphere = (# of physics-grid columns) x Nc x 2 = 67,500# of physics-grid columns on the sphere = (Nphy x Ne) x 6 = 1,3502
(dxGCM ~ 100 km, dxCRM ~ 4 km) 48,600 / 2,430,000
vGCM
k=nLevelk=nLevel+1
k=1 (layer)k=1 (interface)
....
....
32 la
yers
(~2.3 mb)u v Τ
ω
ω
ω
ω
ω
ω
u v Τ
u v Τ
u v Τ
pressure vertical coordinate (hybrid)
height vertical coordinate
Vertical Grid Structure of the Q3D MMF
VVM
....
u v θζη wξ
η wξ
u v θζη wξ
η wξ
u v θζη wξ
η wξ
....
k=2 (layer)
k=nk2
k=1 (interface)
k=nk2
k=2
k=nk2-1
k=nk2_extk=nk2_ext
....
acti
ve d
omai
n(d
ynam
ics
& a
ll ph
ysic
s)ex
tra
dom
ain
(onl
y ra
diat
ion)
(30 km)
(46 km)
30 la
yers
6 la
yers
θ
For communication, vertical interpolation is needed.
Ge
ne
ratio
n o
f d
ata
on
ph
ysic
s g
rid
s
vG
CM
co
mm
un
ica
tio
ns (m
ovin
g da
ta to
cha
nnel
dec
ompo
sitio
n)
Inte
rpo
latio
n o
f vG
CM
da
ta t
o C
RM
po
ints
CR
M C
OM
PU
TE
CR
M C
OM
PU
TE
Ca
lcu
latio
n o
f m
ea
n C
RM
fe
ed
ba
cks (p
hysi
cs te
nden
cies
)
POST-CRM
ProceduresCRM PREDICTION
PRE-CRM
Procedures
DY
CO
RE
CO
MP
UT
E
with
ph
ysic
s t
en
de
ncie
s
PREDICTION
CR
M C
OM
PU
TE
Dis
trib
utio
n o
f C
RM
fe
ed
ba
cks t
o D
yco
re p
oin
ts
vG
CM
co
mm
un
ica
tio
ns (m
ovin
g da
ta to
phy
sics
dec
ompo
sitio
n)
CR
M C
OM
PU
TE
t
Q3D MMF Computation Algorithm
t0
“physics”
Similar to the coupling approach of CAM-SE
t1
Hybrid Dynamics/Physics
coupling
x
y
GCM GLL grid
CRM grid
Input to CRM: GCM-scale solutions
interpolated to CRM grids
Output from CRM: Eddy transport
& diabatic effects(cell averages)
Communication between Dycore & CRMs
x
y
x
y
GCM physics grid
“Interface”
Two model components are coupledat every GCM time step.
Test of Q3D MMF InterfacesThe GCM-scale input data are distributed to CRM grids through horizontal and vertical interpolations and gathered back to physics grids without performing the CRM-prediction.
Qv_in Qv_out
Actual Output Actual Output
Plotted on uniform grid Plotted on uniform grid
Longitude (deg)
Latit
ude
(deg
)La
titud
e (d
eg)
Latit
ude
(deg
)La
titud
e (d
eg)
Longitude (deg)
k = 15
Actual Output Actual Output
Plotted on uniform grid Plotted on uniform grid
Longitude (deg)
Latit
ude
(deg
)La
titud
e (d
eg)
Latit
ude
(deg
)La
titud
e (d
eg)
Longitude (deg)
k = 32 (Lowest model layer)
Short-Term Simulation of the Q3D MMF
Latit
ude
(deg
)
t = 0 t = 24 hWithout CRM Feedback
Surface Pressure
Longitude (deg) Longitude (deg)La
titud
e (d
eg)
Longitude (deg) Longitude (deg)
Latit
ude
(deg
)La
titud
e (d
eg)
T
Qv
Qr
(Lowest model layer)
995
1006
1017
1028
1039
1050
(mb)
Latit
ude
(deg
)
t = 0 t = 24 hWith CRM Feedback (Microphysical effect)
Surface Pressure
Longitude (deg) Longitude (deg)La
titud
e (d
eg)
Longitude (deg) Longitude (deg)
Latit
ude
(deg
)La
titud
e (d
eg)
T
Qv
Qr
(Lowest model layer)
995
1006
1017
1028
1039
1050
(mb)
Short-Term Simulation of the Q3D MMF
Latit
ude
(deg
)
t = 0 t = 24 hWith CRM Feedback (Microphysical effect)
Surface Pressure
Longitude (deg) Longitude (deg)La
titud
e (d
eg)
Longitude (deg) Longitude (deg)
Latit
ude
(deg
)La
titud
e (d
eg)
T
Qv
Qr
(Lowest model layer)
995
1006
1017
1028
1039
1050
(mb)
Short-Term Simulation of the Q3D MMF
We are making progress in testing and debugging the new global Q3D MMF with short-term simulations.
SummaryA global version of Q3D MMF has been created by coupling the VVM on cubed-sphere grids with the CAM-SE-CSLAM dynamical core (https://svn-ccsm-models.cgd.ucar.edu/cam1/branches/Q3D).
We are making progress in testing and debugging the new global Q3D MMF with short-term simulations.
SummaryA global version of Q3D MMF has been created by coupling the VVM on cubed-sphere grids with the CAM-SE-CSLAM dynamical core (https://svn-ccsm-models.cgd.ucar.edu/cam1/branches/Q3D).
- Finish up the code development;- Make improvement to numerical methods and parameterizations;- Speed up the computing time (hybrid MPI/OpenMP)
We will continue to evaluate and improve the model for its application to long-term simulations.