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 POAMA.BOM.GOV.AUWebpage POAMA.BOM.GOV.AU

POAMA Model Components Atmospheric Model BAM T47L17 -> T63L17 -> ACCESS(UKMO+LSM) Ocean Model ACOM2 lat/lon/lev=0.5~1.5/2/25 -> AusCOM 3h OASIS Coupler Heat flux, P-E time

Hindcasts Design Control run initialized at 00Z on the first day of each month, 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 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 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

El Nino Skill: Classic vs Modoki

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 (1 st Sep Start) POAMA LT 3 (1 st Jun Start) SST Forecast Composites Classic El Nino El Nino Modoki

OBS (SON) Australian Rainfall Forecast Composites Classic El Nino El Nino Modoki POAMA LT 1 POAMA LT 3

Cases 1997 vs

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.

90 º E 120 º E Eq 20ºS 40 º S POAMA SST and UV300 clim º E 120 º E GODAS SST and UV300 clim ECOR SST and UV300 clim Annual Mean of SST & top 300m Currents from Reanalyses 90 º E 120 º E 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, ºE

Fremantle Sea Level and SST Observation vs Forecast Skill N34 = 5ºS-5ºN; 170º-120ºW

Downscaling POAMA Forecasts to Fremantle SLA

Nino4 NWHC Both Combined Persist Skill of Fremantle SLA Prediction from Downscaling Scheme

Years FSLA Obs FSLA Lead 3 FSLA Lead 6 FSLA Lead 9 FSLA Forecasts

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