Seasonal Prediction Research and Development at the Australian

Bureau of Meteorology

Guomin Wang

With contributions from Harry Hendon, Oscar Alves, Eun-Pa Lim and Claire Spillman

Centre for Australian Weather and Climate Research:A partnership between the Bureau of Meteorology and CSIRO

Outline

POAMA (Predictive Ocean Atmosphere Model for Australia)

Australian Rainfall Prediction

Leeuwin Current Prediction

POAMA Overview

•The Bureau Dynamical Seasonal Prediction System POAMA

•First version went operational in 2002

•A new version (POAMA1.5) became operational recently and a newer version is in development

•POAMA development evolves as part of Australian Earth System Modelling project ACCESS

•Webpage POAMA.BOM.GOV.AUPOAMA.BOM.GOV.AU

POAMA Model Components

Atmospheric ModelBAM T47L17 -> T63L17 -> ACCESS(UKMO+LSM)

Ocean ModelACOM2 lat/lon/lev=0.5~1.5/2/25 -> AusCOM

3h

OASIS Coupler10( )surfacef U u

Heat flux, P-E

, surfaceSST u

time

Hindcasts Design

• Control run initialized at 00Z on the first day of each

month, 1980-2006

• Extra 9 members initialized prior to control run initial

time in progressively 6 hours interval

• Each hindcast is integrated for 9 months (lead 1-9)

Skill Assessment: ACC for SST and Heat Content

+1

+3

+5

SST H300

Nino3.4 IOD

ACC

RMS

Skill Assessment: ACC for SST Pacific & Indian Ocean Indices

Wang and Hendon (2007)

Correlation between Australian drought index and SST

1997 2002

El Nino Vintage and Impact on Australian Rainfall

• Classic El Nino Nino 3 Index – SSTA

over the Nino3 region (210E-270E, 5S-5N)

• El Nino Modoki EMI = [SSTA]Central –

(0.5[SSTA]East + 0.5[SSTA]West)

(from Weng et al. 2007)

El Nino: Classic vs Modoki

Nino 3

0

0.2

0.4

0.6

0.8

1

0 1 2 3 4 5 6

Lead Time (months)

Co

rr.

Co

eff.

POAMA

Persistence

EMI

0

0.2

0.4

0.6

0.8

1

0 1 2 3 4 5 6

Lead Time (months)

Co

rr.

Co

eff.

POAMA

Persistence

El Nino Skill: Classic vs Modoki

NINO3

-3

-2

-1

0

1

2

3

4

OBS

POAMA LT1

POAMA LT3

EMI

-3.5

-2.8

-2.1

-1.4

-0.7

0

0.7

1.4

2.1

OBS

POAMA LT1

POAMA LT3

• El Nino Modoki events (EMI >= 0.7 STD): 86, 90, 91, 93, 94, 02, 04

• Classic El Nino events: 82, 87, 97

R ~ 0.86 at LT1

R ~ 0.83 at LT1

OBS (SON)

POAMA LT 1 (1st Sep Start)

POAMA LT 3 (1st Jun Start)

SST Forecast CompositesClassic El Nino El Nino Modoki

OBS (SON)

Australian Rainfall Forecast CompositesClassic El Nino El Nino Modoki

POAMA LT 1

POAMA LT 3

Cases 1997 vs 2002

1997 2002

Seasonal Prediction of the Leeuwin Current: Observed Features

Freemantle sea level (FSL) is indicative of volume transport variation of the leeuwin current (M. Feng).

Use FSL as a proxy for Leeuwin Current strength.

90ºE 120ºE

Eq

20ºS

40ºS

POAMA SST and UV300 clim 1982-2003

90ºE 120ºE

GODAS SST and UV300 clim 1982-2003 ECOR SST and UV300 clim 1982-2003

Annual Mean of SST & top 300m Currents from Reanalyses

90ºE 120ºE POAMA GOGAS/NCEP ODA/ECMWF

Fremantle Sea Level and Ocean Heat Content Observation vs Forecast Skill

Obs relationship between H300 and SLA at Freo

H300 ACC Skill at leadtime=7

HCNW = 15-25ºS,112-120ºE

Fremantle Sea Level and SST Observation vs Forecast Skill

N34 = 5ºS-5ºN; 170º-120ºW

Downscaling POAMA Forecasts to Fremantle SLA

Nino4NWHCBoth CombinedPersist

Skill of Fremantle SLA Prediction from Downscaling Scheme

82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 00 01 02 03 04 05 06

Years

FSLA ObsFSLA Lead 3FSLA Lead 6FSLA Lead 9

FSLA Forecasts 1982-2006

Summary

• Introduction of The Australian Bureau’s Dynamical

Seasonal Prediction System POAMA.

• POAMA has higher skill for SST in Pacific and for heat

content along NW Australia.

• POAMA can predict short term El Nino vintage and

respective Australian rainfall responses.

• Using POAMA forecasts a downscaling scheme

shows useful seasonal forecast skill for Leeuwin

Current strength.

Summary• Each El Nino event has different flavour

• The impact of the central Pacific warming El Nino (represented by El Nino Modoki Index) is as important as the traditional eastern Pacific warming El Nino for Australian rainfall

• POAMA has good skill to predict:

- the occurrence and the detailed SST structure of the central Pacific El Nino and the traditional El Nino events

- the Australian rainfall difference affected by these two types of El Nino events

- 97 and 02 El Nino events and associated Australian rainfall the skill stems from the improved the skill stems from the improved atmospheric initial conditions by ALI and the model’s atmospheric initial conditions by ALI and the model’s atmosphere-ocean coupling ability.atmosphere-ocean coupling ability.