Transcript Sensitivity of A Squall Line Simulation to Model and Initial Errors in South China Zhiyong Meng Duochang Wu Department of Atmospheric and Oceanic.

Sensitivity of A Squall Line Simulation to
Model and Initial Errors in South China
Zhiyong Meng Duochang Wu
Department of Atmospheric and Oceanic Sciences
School of Physics, Peking University
Nov.1, 2012, Kunming
Background: Conceptual Model of Squall Line
Features:
Quick development, fast movement,
large affecting area, severe
disastrous weathers
( adapted from Markowski and Richardson 2010 )
Background: Squall line cases
Guangzhou 7 May 2010
Beijing 23 June 2011
Maximum hourly rainfall 128mm
Background: Mesoscale Predictability
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Impact of model resolution and physical parameterization schemes (Kuo et al. 1995)
TC
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Sensitivity of forecast to initial field (Kuo et al. 1995)
mesoscale cyclone
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Error growth due to moist processes (Ehrendorfer et al. 1999)
Winter cyclone , trough
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Upscale growth of smaller scale error (Zhang et al. 2002, 2003)
Winter cyclone
Studies on the predictability of squall line has been very few
(Melhauser & Zhang, 2012)
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Questions
For squall line in China:
• How sensitive is the simulation to model error?
• How sensitive is the simulation to initial error?
• How to improve the predictability of the squall line?
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The Squall Line over South China on 23 April 2007
GZ Radar Reflectivity at 0.5 Elevation
Features: fast (17m/s)
long lasting (about 11 h)，
and widespread impact.
- trailing stratiform
- transition zone
- V shape stratiform
- bow echo
- backbuilding
- line behind the stratiform
Impact: Widespread heavy rain
(186.3mm,), strong wind
(30m/s at Huadu) and
thunderstorm (hail at
Qujiang）
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Synoptic overview: Guangdong squall line on 23 April 2007
23/00Z e/Wind/V 850hPa
23/06Z e/Wind/V 850hPa
23/12Z e/Wind/V 850hPa
23/18Z e/Wind/V 850hPa
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Model and Data
Model: WRFV3
Vertical: 35 levels
Physics: Grell, YSU, WSM-6
Initialized at 23/1200UTC for a
24-h run
D1 40.5km
D2 13.5km
D3 4.5km
Initial and boundary conditions:
NCEP/FNL (1  1 )
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Control experiment
Isochrones
(Meng et al. 2012 JAS)
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Sensitivity to model error:physical parameterization scheme
CNTL
KFcum
THmps
CNTL: Grell,
YSU,
WSM-6
NTM
MRFpbl
EHSlws
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Sensitivity to model error: grid size & cumulus scheme
R20_None
R13.5_None
R10_None
R5_None
R20_Grell
R13.5_Grell
R10_Grell
R5_Grell
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Sensitivity to initial error
Setup of ensemble forecast
Initial ensemble ：WRF-3DVar
Ensemble size：40
STD: 1K for T, 2m/s for u and v, 0.5g/kg for qv
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The CNTL ensemble, reflectivity valid at 24/00z
60% 15%
Grouping into
A: the center of the 40 dBZ
band is 200 km within the
observed position
25%
 B: Got a squall line with a
larger location error
 C: No squall line formed
during the whole forecast
period.
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Evolution of ensemble spread in horizontal
Vertically mean STD of T（contour，the shaded: dBZ）
1400UTC_23
1700UTC_23
2100UTC_23
2300UTC_23
0000UTC_24
0400UTC_24
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Evolution of ensemble spread in vertical
U
T
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How can the improvement in the
initial error affect the simulation?
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Splitting experiments
∆={initialgood – initialbad}/10
All_1= initialbad+ ∆*1
All_2= initialbad+ ∆*2
..
..
..
..
..
..
..
..
..
All_9= initialbad+ ∆*9
(Melhauser & Zhang 2012)
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Sensitivity to the initial error: all variables
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Sensitivity to the initial error: all variables
2003.6.9 event in the U.S.
(Melhauser et al. 2012)
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Sensitivity to the initial error: different variables
Only UV
Only T
(g)
(h)
(i)
Only Qv
(j)
(k)
(l)
All but Qv
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Sensitivity to the initial error: different pairs
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How to improve the predictability?
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The performance of the Ensemble forecast
Single scheme
Multi-scheme
A: the exact squall line
15%
15%
B: squall line with large location
60%
70%
C: no squall line
25 %
15%
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Summary
 Model error apparently affect the predictability of the squall line
• Physical parameterization
• Grid size
• Cumulus parameterization
 Initial error apparently affect the predictability of the squall line
• Linear impact
• The moisture condition and moist processes played an
important role
 Adding physical perturbation helped to improve the predictability
of the squall line
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Error in the formation and lasting time
A
All
B
A
All
All
B
What may have caused the differences?
Precipitable water at 23/21z (Shaded), Terrain is contoured
Good member
Bad member
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Outline
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Background
Model and data
Sensitivity to model error
Sensitivity to initial error
Summary
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Ensemble spread of Multi vs. Single
U(m/s), 24/00z
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