Predictability and Prediction of Tropical Intra-Seasonal Oscillation (TISO)
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Transcript of 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
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Intra-Seasonal Variability
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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
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+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)?
NOAA 32nd CDPW, Tallahassee, Oct 22-26, 2007
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)
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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)
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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
NOAA 32nd CDPW, Tallahassee, Oct 22-26, 2007
Boreal-summer Rainfall over (65oE-120oE)
Targets
Coupled Forecasts (CPL)
Atmosphere-only Forecasts (ATM)
Ten-ensemble-mean
Event-I Event-II
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Ensemble means
ATM/ATMp: 30 days CPL/ATMd: 42 days
ACC
TISO Predictability Measured by ACC
NOAA 32nd CDPW, Tallahassee, Oct 22-26, 2007
(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
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OLRU-850VP-200
MJO Events Observed during TOGA-COARE
1992
1993
Vitart et al. (2007)
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VP-200Vitart et al. (2007)
Dec. 31,1992
Feb. 1,1993
MJO Forecasted by ECMWF Operational Seasonal Forecast System
NOAA 32nd CDPW, Tallahassee, Oct 22-26, 2007
Rainfall
MJO Forecasted by the IPRC_HcGCM
Observation With default cumulus scheme
With revised cumulus scheme
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OLR
(U850 -U200)
MJO Forecasted by the IPRC_HcGCM
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NOAA 32nd CDPW, Tallahassee, Oct 22-26, 2007
Atmosphere-only Forecast With revised cumulus scheme
An Experimental Forecast of Monsoon ISO
Boreal-summer Rainfall over (65oE-120oE)
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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.
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Thanks
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Air-sea coupling enhances the northward propagating monsoon ISO (IPRC_HcGCM)
Fu et al. 2003, Fu and Wang 2004 (65oE-95oE)
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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
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Model Observation
Wheeler-Hendon Phase-space MJO Diagram
PC-1 PC-1
PC
-2 P
C-
2
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Filtered rainfall over (80oE–100oE, 5oS-5oN)
Phase 1
Phase 2
Phase 3
Phase 4 Fu et al. 2006, JAS
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TISO Predictability Measured by Signal-to-Error Ratio
ATM/ATMp: 24 days CPL/ATMd: 34 days
Signal
ATM Forecast Error
CPL Forecast Error
Individual ensembles
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ATM/ATMp: 21 days CPL/ATMd: 30 days
Individual ensembles
ACC
TISO Predictability Measured by ACC
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MJO Forecasted by the IPRC_HcGCM
OBS
Atmosphere only
Revised
Default
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(Signal) L=25 days for TISO
(Forecast Error)
Control run Perturbed Forecasts
Signal-to-Error Method
Waliser et al. (2003)
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SSTs in Five Experiments
Control
Coupled/Daily
Mixed-layer
Damped persistent
“Smoothed”
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