On the Dynamical Predictability of Summer Monsoon Depressions over South Asia
On Climate Predictability of the Summer Monsoon Rainfall Bin Wang
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On Climate Predictability of the Summer Monsoon Rainfall
Bin WangDepartment of Meteorology and IPRC
University of Hawaii
Acknowledging contribution from
Q. H. Ding, X. H. Fu,I.-S. Kang, J.-Y. Lee, K. Jin
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MCZ: BOB-SCS-PS
JJA precipitation, 850 hPa winds, 200hPa STR
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Source of predictability for EASM Wang, Wu and Lau 2001
Why do we care about the rainfall in MCZ?
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Assessment of 11 AGCMs ensemble
simulations of summer monsoon rainfall
Data: CLIVAR/ Monsoon panel Intercomparison project) (Kang et al. 2002)
AMIP type design10-member ensembleFocus on 1997 ElNino (Sept 1 1996-
August 31 1998)
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Climatological Pentad Mean Precipitation
(a) Indian Monsoon Region
(b) Western North Pacific Region
Month
mm
/da
ym
m/d
ay
Month
AGCMs climatology is poor in WNP heat source region
ISM (5-30N, 65-105E)
WNPSM(5-25N, 110-150E)
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AAM and El Nino domain
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Wang, Kang, Lee 2003, JC
El Nino region
A-AM region
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Precipitation (shading) and SST (contour)
Observation All-Model Composite
J J A1997
SON1997
J J A1998
J J A1997
SON1997
J J A1998
J J A1997
SON1997
J J A1998
J J A1997
SON1997
J J A1998
mm/day
Latitu
de
Latitu
de
Latitu
de
Longitude Longitude
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-0.6
-0.4
-0.2
0.0
0.2
0.4
0.6
COLA DNM GEOS GFDL IAP IITM MRI NCAR NCEP SNU SUNY Comp
- 0.6
- 0.4
- 0.2
0
0.2
0.4
0.6
- 0.6
- 0.4
- 0.2
0
0.2
0.4
0.6
- 0.6
- 0.4
- 0.2
0
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0.6
(a) Southeast Asian and WNP region
J J A97 SON97 J J A98
(b) The rest of the A- AM domain
J J A97 SON97 J J A98
-0.2
0.0
0.2
0.4
0.6
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1.0
COLA DNM GEOS GFDL IAP IITM MRI NCAR NCEP SNU SUNY Comp
MCZ
Rest of A-AM
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Prediction skill for JJA rainfall (2 years) 11-model ensemble mean
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Prediction skill for JJA rainfall (21 years) 5-model ensemble mean
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Why do Nearly All Atmospheric Models Fail to Simulate Seasonal
Rainfall Anomalies in Summer Monsoon
Convergence Zones?
Bad model?Poor strategy?
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Fig.3
Observed Rainfall-SST correlation (1979-2002)
RainfallLeads SST by 1-month
SST leads Rainfall by 1-month
Concurrent
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Fig.4
Rainfall-SST correlation from Coupled model )
Simultatious
RainfallLeads SST by 1-month
SST leads Rainfall by 1-month
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Fig.5
Rainfall-SST correlation from AMIP-type run
Concurrent
RainfallLeads SST by 1-month
SST leads Rainfall by 1-month
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Are MJO or boreal summer ISO reproducible in forced AGCM simulations (AMIP-type)?
How important is the air-sea interaction in prediction of ISO?
Predictability of the ISO
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1979
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CMAP Rainfall
Coupled
Daily Forced
Mean Forced
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Phase Relationships between Rainfall and SST
Arabian Sea
Bay of Bengal
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Kemball-Cook and Wang (2001)
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SummaryAGCM alone can not reproduce realistic
seasonal rainfall anomalies in summer Monsoon Convergence Zone (MCZ).
Caution should be taken when validating model or determining upper limit of predictability using AMIP approach.
Two-tier approach may be inherently inadequate for monsoon rainfall anomalies.
Atmospheric only model may loss significant amount of predictability on MJO.
Coupled and forced ISO solutions are two distinguished solutions. Chaos can be induced by both IC and BC errors.
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Thank You
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Main PointsCurrent AGCMs forced by SSTA have
little skill in simulation and prediction of seasonal rainfall anomalies over summer Monsoon Convergence Zone (MCZ).
Cautions must be taken when validating model or determining the upper limit of the predictability using AMIP approach.
Two-tier approach may be inherently inadequate for monsoon rainfall anomalies.
Atmospheric only model may loss significant amount of predictability of MJO.
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Fig.2
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Is ISO a noise or signal?
Cadet 1986
Monsoon climate prediction must deal with ISO
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Anomalous SST-Model precipitation Correlation
OBS-Model correlation: sample size 22
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Correlation coefficients: Local SST-Precipitation AnomaliesIn the MCZ region: sample size: 222 or 2220
OBS
11-COMPOS.
COLA DNM GEOS GFDL IAP IITM MRI NCAR NCEP SNU SUNY
JJA97
-0.15 0.59 0.42 0.49 0.38 0.19 0.02 0.15 0.49 0.43 0.39 0.36 0.33
SON97
-0.33 0.71 0.59 0.7 0.5 0.35 0.45 0.49 0.44 0.66 0.37 0.34 0.37
JJA98
-0.45 0.56 0.19 0.77 0.24 0.52 0.59 0.44 0.5 0.51 0.57 -0.12 0.38
TO-TAL
-0.35 0.58 0.33 0.65 0.32 0.42 0.42 0.37 0.47 0.51 0.47 0.04 0.35
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Anomalous SST-Model precipitation Correlation
OBS-Model correlation: sample size 22
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Prediction Skill of JJA Precipitation during 21 years
(a) MME1(Model Composite)
(d) NASA
(b) SNU
(e) NCEP
(c) KMA
(f) JMA
Temporal Correlation with Observed Rainfall
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Fig. 4. Same as in Fig. 2 except the results are obtained from MME (5-model) output for the period 1979-1999.
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Atmospheric Model: ECHAM4.6 T30 (3.75o).Ocean Model: UH 2.5-layer Intermediate Model, 2ox1o
Coupling: daily, Full, No flux correction; Warm pool only
Regional Coupled Model: ECHAM-UHIO
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UH 2.5 layer Ocean Model
(Wang, Li, Chang 1995, JPO; Fu and Wang 2001, JC)
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