Predictability and Prediction of Tropical Intra-Seasonal Oscillation (TISO)

Predictability and Prediction of Tropical Intra-Seasonal Oscillation (TISO)

Xiouhua (Joshua) Fu

International Pacific Research Center (IPRC) University of Hawaii at Manoa, Honolulu, Hawaii

Collaborators: Bin Wang, Bo Yang, Qing Bao

NOAA 32nd CDPW, Tallahassee, Oct 22-26, 2007

Global Impacts of TISO

The TISO

Boreal-winter MJO

Boreal-summer ISO

Eastward


Intra-Seasonal Variability


Signal CPL Forecast Error

[ATM: 17 days; CPL: 24 days]Fu and Wang et al. 2007, JAS

Air-sea Coupling Extends the Predictability of TISO

ATM Forecast Error



+Wang and Xie (1998)

Air-Sea Coupling Processes

Specific Questions to be Addressed

How will different surface boundary conditions (five different SST settings) affect the TISO predictability (with “perfect” model assumption)? What are the best SST configurations for TISO hindcasts and operational forecasts? What is the “practical” predictability of TISO in a dynamical model (IPRC_HcGCM)?


Fu et al. (2007), MWR, In press

IPRC/UH Hybrid coupled GCM (IPRC_HcGCM)

Atmospheric component: ECHAM-4 T30L19 AGCM (Roeckner et al. 1996) Ocean component: Wang-Li-Fu intermediate upper ocean model (0.5ox0.5o) (Wang et al. 1995; Fu and Wang 2001)

Wang, Li, and Chang (1995): upper-ocean thermodynamics McCreary and Yu (1992): upper-ocean dynamics Jin (1997) : mean and ENSO (intermediate fully coupled model) Zebiak and Cane (1987): ENSO (intermediate anomaly coupled model)

Fully coupling without heat flux correction Coupling region: Tropical Indian and Pacific Oceans (30oS-30oN) Coupling interval: Once per dayFu et al. 2003; Fu and Wang 2004 (TISO)


Ensemble ExperimentsWith Five Different SST Settings

Experiment Name

SSTs Used in 90-day Forecasts

CPL SST directly forecasted by interactive air-sea coupling (Tier-one)

ATM Daily SST from the coupled control run after removing 20-90-day variability ( “smoothed” SST)

ATMp Daily SST from the coupled control run is linearly interpolated to the “smoothed” SST within first 10-day forecast (damped persistent SST)

ATMf Daily SST anomaly from coupling to a slab mixed-layer ocean (ML depth = 30 m) is added to the “smoothed” SST

ATMd Ensemble-mean daily SST from the CPL forecasts (Tier-two)


Experimental Design 2 TISO events (boreal-summer) in a coupled control run (Targets) 4 phases for each TISO event (Starting points) 10 ensemble forecasts starting from each phase of selected events under five different SST settings (80 forecasts per SST setting)

Data Processing TISO: 20-90-day filtered daily rainfall


Boreal-summer Rainfall over (65oE-120oE)

Targets

Coupled Forecasts (CPL)

Atmosphere-only Forecasts (ATM)

Ten-ensemble-mean

Event-I Event-II


Ensemble means

ATM/ATMp: 30 days CPL/ATMd: 42 days

ACC

TISO Predictability Measured by ACC


(Tier-1/Tier-2)

An MJO event observed during TOGA-COARE1993, Jan. 01-Feb. 10 (boreal-winter)

A monsoon ISO event2006, Jun. 11-Jul. 11 (boreal-summer)

Initialized with NCEP reanalysis 100-ensemble forecasts for each event

TISO Forecast Experiments with IPRC_HcGCM


OLRU-850VP-200

MJO Events Observed during TOGA-COARE

1992

1993

Vitart et al. (2007)


VP-200Vitart et al. (2007)

Dec. 31,1992

Feb. 1,1993

MJO Forecasted by ECMWF Operational Seasonal Forecast System


Rainfall

MJO Forecasted by the IPRC_HcGCM

Observation With default cumulus scheme

With revised cumulus scheme


OLR

(U850 -U200)




Atmosphere-only Forecast With revised cumulus scheme

An Experimental Forecast of Monsoon ISO

Boreal-summer Rainfall over (65oE-120oE)


Summary

The TISO predictability in IPRC/UH_HcGCM reaches about 40 days averaged over the Southeast Asia. The predictability in the atmosphere-only model is about 30 days. Interactive air-sea coupling extends the TISO predictability by about 10 days.

Tier-two system could reach similar TISO predictability as tier-one system, suggesting that using observed high-frequency SST for TISO hindcasts and using interactive air-sea coupling and forecasted daily SST for real-time forecasts are good options. The optimistic side of this TISO forecast experiment suggests that some current dynamical models are ready to carry out intraseasonal forecast and will provide useful information for extended weather forecast.


Thanks


http://www.tonyandkitty.com/gallery/album01/Diamond_Head?full=1

Air-sea coupling enhances the northward propagating monsoon ISO (IPRC_HcGCM)

Fu et al. 2003, Fu and Wang 2004 (65oE-95oE)


Coupling also extends the predictability of weather

ATM/(Negative): 8 days CPL/(Positive): 16 days

ATM Forecast Error

CPL Forecast Error

Signal

(During break-to-active transition) NOAA 32nd CDPW, Tallahassee, Oct 22-26, 2007

Two Methods to Measure the Predictability Ratio of Signal- to- Forecast Error

Anomaly Correlation Coefficient (ACC)

Forecast Time

0.5

1.0

Forecast Time


Model Observation

Wheeler-Hendon Phase-space MJO Diagram

PC-1 PC-1

PC

-2 P

C-

2


Filtered rainfall over (80oE–100oE, 5oS-5oN)

Phase 1

Phase 2

Phase 3

Phase 4 Fu et al. 2006, JAS


TISO Predictability Measured by Signal-to-Error Ratio


Signal

ATM Forecast Error

CPL Forecast Error

Individual ensembles



Individual ensembles

ACC

TISO Predictability Measured by ACC



OBS

Atmosphere only

Revised

Default


(Signal) L=25 days for TISO

(Forecast Error)

Control run Perturbed Forecasts

Signal-to-Error Method

Waliser et al. (2003)


SSTs in Five Experiments

Control

Coupled/Daily

Mixed-layer

Damped persistent

“Smoothed”


Predictability and Prediction of Tropical Intra-Seasonal Oscillation (TISO)

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