1. Peter M.K. Yau and Badrinath Nagarajan McGill University
A Numerical Study of a TOGA COARE Super Cloud Cluster – Preliminary results
Peter M.K. Yau and Badrinath Nagarajan
McGill University

2. Outline
Motivation & Objectives
Case Overview
Modeling Strategy
Results & Conclusions
Future work

3. Motivation
MJO associated with supercloud clusters. Processes organizing warm-pool convection a “zeroth-order problem” (Webster & Lucas 1992)
Organizing mechanisms (OM) particularely at meso-and synoptic scale not well understood (Yanai et al 2000, Gabrowksi 2003).
Improved understanding of OM on various scales should lead to:
better representation of convection in models
reduced forecast errors at the medium range
better representation and understanding of the role of convection on water vapor distribution in the vertical

4. Objective
Use a real data multi-grid ( km) numerical modeling approach to
simulate supercloud clusters (SCCs) over TOGA COARE
diagnose the processes that:
organize MCSs,
cause clustering of MCSs, and
study the impact of convection on water vapor distribution in the vertical

5. Case Overview – IOP of TOGA COARE
OLR (W m-2)
Once a day
Averaged
5S - 5N
OLR < 215
W m-2
Shaded
Focus of this study on SCC A
1Nov 92
1Dec 92
1Jan 93
1Feb 93
28 Feb 93
Yanai et al (2000)

6. The 6 DEC. 92 – 6 JAN. 93 SUPER CLOUDCLUSTER
IFA
Longitude
Time
Time cluster
MCSs
Time cluster:
Lifetime > 24 h
MCS:
Lifetime < 24 h
Data Used:
Hourly GMS
Infrared data
0-10S average
Areas < 235 K
precipitating
(GATE/COARE
convection)

7. EVOLUTION of IFA time cluster (11-13 DEC 92)
mm h-1
Data Used:
Precipitation retrieved from
SSM/I, VIS/IR satellite data
Sheu et al (1996), Curry et al
(1999)
3 hourly/ 30 km resolution

8. EVOLUTION of IFA time cluster (11-13 DEC 92)
mm/h
Data Used:
Precipitation retrieved from
SSM/I, VIS/IR satellite data
Sheu et al (1996), Curry et al
(1999)
3 hourly/ 30 km resolution

9. Schematics of Nakazawa (1988)
Madden & Julian (1994)

10. Propagation of Time Clusters Time cluster: IFA Lifetime > 24 h Time
Longitude
Time 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
Time cluster:
Lifetime > 24 h
Westward
propagating
Eastward
Propagation
of Time
Clusters

11. PROPAGATION OF TIME CLUSTERS
200 hPa
IFA
Longitude
Time 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
Westward propagating
Eastward propagating

12. Time Evolution of Domain Average Brightness Temperature
Early
morning
minimum
Afternoon
minimum
(land)
Afternoon
minimum
(ocean)

13. Brightness temperature minimum occurs:
Early morning for 8 time clusters,
Afternoon for 4 time clusters
Suggests that most of the time clusters are indeed MCSs

14. Organizing Mechanisms
Large scale flow features (e.g., 2-day waves)
Vertical wind shear (Le Mone et al 1999)
Mid-level mesovortices (Nagarajan et al 2004) – Dec. 15, 1992
Mapes gravity-wave mechanism

15. 1-4, 7-9, 11-13 associated with 2-day wave
TIME CLUSTERS & 2-DAY PERIODICITY
IFA 1 2 3 4
1-4, 7-9, 11-13
associated with
2-day wave
(Chen et. al 1996,
Takayabu et. al 1996) 5 6 7
Time 8 9 10 11 12 13 14 15 16
Longitude K
Westward propagating
Eastward propagating

16. TIME CLUSTERS & VERTICAL SHEAR* (wind speed)
DATE
hPa
hPa
6 – 19 Dec. 92
Dec. 92
1, Jan. 93
< 3.0 m s-1
< 5.0 m s-1
Dec. 92
> 3.0 m s-1
> 5.0 m s-1
27 Dec. 92
2-3 Jan. 93
*Areal & Temporal Averages
Temporal average: Duration of the time cluster
Areal average: 0-10S, longitudinal extent of time cluster

17. Summary During the lifetime of the SCC (6Dec-6Jan):
Identified 16 time clusters consisting of eastward & westward propagating cloud clusters.
Convection generally associated with 2-day wave activity
Convection occurred in a weak vertical wind shear environment except between Dec 1992.

18. The Model Canadian mc2 model (Benoit et al. 1997)
Fully compressible equations
Semi-Lagrangian, semi-implicit numerics
One-way nesting of lateral boundary conditions
RPN1 physics package
1 Recherche en Prevision du Numerique

19. 1-month long time series
Time series based on last 24 h of each 27h long simulation.
00 UTC/6 Dec. 92
03UTC/7 Dec. 92
00 UTC/7 Dec. 92
03 UTC/8 Dec. 92
00 UTC/6 Jan. 93
00 UTC chosen because of high availability of
rainfall data for assimilation
Time integration strategy follows guichard et al.
(2003)

20. MC2 MODEL DOMAIN
3900 km
130E
160E
190E
10N EQ
10S
IFA
Grid Size: 549 x 279 x 40, Horizontal grid length: 15 km
Model Top: 26 km

21. Modeling Strategy Model Parameters: Initial Conditions:
KF CPS (deep convection), BM CPS (shallow convection), Kong and Yau (1997) explicit bulk 2-ice microphysics, time step(90 s)
Initial Conditions:
ECMWF operational analysis (0.5 o) enhanced:
radiosonde data (Cieleski et al 2003),
temperature & moisture profiles modified by 1D-VAR rainfall rate assimilation scheme (Nagarajan et al. 2006) and
ABL moistening due to diurnal SST warming (Nagarajan et al 2001, 2004).
6-hourly lateral boundary conditions

22. IFA averaged surface precipitation rate
Missing data

23. IFA averaged surface sensible and latent heat flux

24. Horizontal size distribution of clouds (Model Domain)
Missing data
Wielicki & Welch (1986)

25. Domain-averaged surface precipitation rate (140-180E, 0-10S)
Missing data

26. IFA
Av. RH RH
Height (km)
(h)

27. Conclusions The IFA-mean and temporal variability of: Large scale :
surface fluxes of latent and sensible heat, surface precipitation reasonable
Large scale :
Simulated surface precipitation overpredicted
Horizontal size of cloud clusters are reasonably simulated.
Month long mesoscale simulation captures reasonably the life cycle of the super cloud cluster.

28. Future Work
Nesting to higher resolutions (5 km and 1 km) with new three-moment 4 - ice microphysics (Milbrandt and Yau 2005a,b)
Diagnose mechanisms that organized the super cloud cluster
Diagnose processes for water vapor and temperature distributions