On Climate Predictability of the Summer Monsoon Rainfall Bin Wang

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

MCZ: BOB-SCS-PS

JJA precipitation, 850 hPa winds, 200hPa STR

Source of predictability for EASM Wang, Wu and Lau 2001

Why do we care about the rainfall in MCZ?

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)

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)

AAM and El Nino domain

Wang, Kang, Lee 2003, JC

El Nino region

A-AM region

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

-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

0.2

0.4

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

0.8

1.0

COLA DNM GEOS GFDL IAP IITM MRI NCAR NCEP SNU SUNY Comp

MCZ

Rest of A-AM

Prediction skill for JJA rainfall (2 years) 11-model ensemble mean

Prediction skill for JJA rainfall (21 years) 5-model ensemble mean

Why do Nearly All Atmospheric Models Fail to Simulate Seasonal

Rainfall Anomalies in Summer Monsoon

Convergence Zones?

Bad model?Poor strategy?

Fig.3

Observed Rainfall-SST correlation (1979-2002)

RainfallLeads SST by 1-month

SST leads Rainfall by 1-month

Concurrent

Fig.4

Rainfall-SST correlation from Coupled model )

Simultatious

RainfallLeads SST by 1-month

SST leads Rainfall by 1-month

Fig.5

Rainfall-SST correlation from AMIP-type run

Concurrent

RainfallLeads SST by 1-month

SST leads Rainfall by 1-month

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

1979

CMAP Rainfall

Coupled

Daily Forced

Mean Forced

Phase Relationships between Rainfall and SST

Arabian Sea

Bay of Bengal

Kemball-Cook and Wang (2001)

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.

Thank You

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.

Fig.2

Is ISO a noise or signal?

Cadet 1986

Monsoon climate prediction must deal with ISO

Anomalous SST-Model precipitation Correlation

OBS-Model correlation: sample size 22

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

Anomalous SST-Model precipitation Correlation

OBS-Model correlation: sample size 22

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

Fig. 4. Same as in Fig. 2 except the results are obtained from MME (5-model) output for the period 1979-1999.

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

UH 2.5 layer Ocean Model

(Wang, Li, Chang 1995, JPO; Fu and Wang 2001, JC)