A Numerical Study of a TOGA COARE Super Cloud Cluster –
Preliminary results
Peter M.K. Yau and Badrinath Nagarajan
McGill University
Outline
•Motivation & Objectives•Case Overview•Modeling Strategy•Results & Conclusions•Future work
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
Objective Use a real data multi-grid (15-5-1 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
Case Overview – IOP of TOGA COARE
Yanai et al (2000)
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
28 Feb 93
1Dec 92
1Jan 93
1Feb 93
IFA
Longitude
Tim
e
Time cluster
MCSs
Time cluster:•Lifetime > 24 h
MCS:•Lifetime < 24 h
The 6 DEC. 92 – 6 JAN. 93 SUPER CLOUDCLUSTER
Data Used:•Hourly GMS Infrared data•0-10S average
•Areas < 235 K precipitating (GATE/COARE convection)
EVOLUTION of IFA time cluster (11-13 DEC 92)
Data Used:•Precipitation retrieved from SSM/I, VIS/IR satellite data Sheu et al (1996), Curry et al (1999)•3 hourly/ 30 km resolution
mm h-1
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
EVOLUTION of IFA time cluster (11-13 DEC 92)
Madden & Julian (1994)
Schematics of Nakazawa (1988)
IFA
Longitude
Tim
e
1
2
3 4
5
6
7
89
1011
12 13
14
15
16
Time cluster:•Lifetime > 24 h
Westwardpropagating
Eastwardpropagating
Propagation of Time Clusters
IFA
Longitude
Tim
e
1
2
3 4
5
6
7
89 1
011
12
1314
15
16
Westward propagating Eastward propagating
IFA
200 hPaPROPAGATION OF TIME CLUSTERS
Time Evolution of Domain Average Brightness Temperature
Early morning minimum
Afternoon minimum(land)
Afternoon minimum(ocean)
• 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
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
Longitude
Tim
e
1
2
3 4
5
6
7
89
1011
12 13
14
15
16
Westward propagating Eastward propagating
IFA
TIME CLUSTERS & 2-DAY PERIODICITY
K
1-4, 7-9, 11-13associated with2-day wave (Chen et. al 1996,Takayabu et. al 1996)
TIME CLUSTERS & VERTICAL SHEAR* (wind speed)
DATE 1000-850 hPa
800-400 hPa
6 – 19 Dec. 9228 - 31 Dec. 921, 4-6 Jan. 93
< 3.0 m s-1 < 5.0 m s-1
20 - 28 Dec. 92
> 3.0 m s-1 > 5.0 m s-1
27 Dec. 922-3 Jan. 93
< 3.0 m s-1 > 5.0 m s-1
*Areal & Temporal AveragesTemporal average: Duration of the time clusterAreal average: 0-10S, longitudinal extent of time cluster
SummaryDuring 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 20-28 Dec 1992.
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
1-month long time series
00 UTC/6 Dec. 92
03UTC/7 Dec. 92
00 UTC/7 Dec. 92 03 UTC/8 Dec. 92
00 UTC/6 Jan. 93
Time series based on last 24 h of each 27h long simulation.
•00 UTC chosen because of high availability of rainfall data for assimilation •Time integration strategy follows guichard et al. (2003)
3900 km
3900 km
130E 160E 190E
10N
EQ
10S
MC2 MODEL DOMAIN
Grid Size: 549 x 279 x 40, Horizontal grid length: 15 kmModel Top: 26 km
IFA
Modeling Strategy• Model Parameters:
– 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
IFA averaged surface precipitation rate
Missing data
IFA averaged surface sensible and latent heat flux
Horizontal size distribution of clouds (Model Domain)
Wielicki & Welch (1986)
Missing data
Domain-averaged surface precipitation rate (140-180E, 0-10S)
Missing data
RH
(h)
Heig
ht
(km
)IFA Av. RH
• The IFA-mean and temporal variability of:– 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.
Conclusions
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