Pac ific Adaptatio n Strategy Assistanc e Pro gram Seasonal Forecasts in the Pacific Region using POAMA 1.5b Australia Greenhouse Conference 4 ‐ 8 th April (2011) ‐ Cairns, Queensland, Australia. Andrew Cottrill 1 , Eun ‐ Pa Lim 1 and Harry Hendon 1 1 Bureau of Meteorology (CAWCR) , Melbourne, Victoria.
Outline of Presentation • Location Map of the Fifteen Pacific Island Nations involved in the PASAP project; • Show the Seasonal Rainfall Patterns across the Tropical Pacific; • Show some typical ENSO Patterns in Rainfall Composites at three stations; • Briefly describe the POAMA Seasonal Prediction System and its Correlation to Tropical SSTs with various lead times; • Show patterns of Hit Rates of Above Median Rainfall between CMAP and POAMA over the equatorial Pacific; • Show Calibration of Seasonal Rainfall at Tarawa as a technique to improve seasonal forecast outlooks and • Short Summary Pac ific Adaptatio n Strate gy Assistanc e Pro gram
Pacific Island Countries and PASAP – Fifteen Partner Countries Cook Islands East Timor Federated States of Micronesia Fiji Kiribati Niue Palau Papua New Guinea Republic of Marshall Islands Republic of Nauru Samoa Solomon Islands PASAP – Pacific Adaptation Strategy Assistance Program. Tonga The PASAP project has been developed under the International Tuvalu Climate Change Adaptation Initiative to help Pacific Island Vanuatu Countries (PICs) prepare for climate change in coming decades. The PASAP project aims to deliver seasonal climate outlooks to PICs based on POAMA. More information on PASAP can be found at the Department of Climate Change and Pac ific Adaptatio n Strate gy Assistanc e Pro gram Energy Efficiency (DCCEE). Map: Yuri Kuleshov - BoM
Patterns of Seasonal Rainfall Across the Tropical Pacific Using Data from CMAP Units =mm/day CMAP Data: 1979-2006 NE Trades Australian Monsoon Summer Shows the Mean State Rainfall of Seasonal Rainfall SE Trades along the Equator SPCZ ITCZ (ITCZ) and the SPCZ in the southwest Pacific. Autumn The ITCZ migrates Rainfall north and south with Indian and East the change of seasons Asian Monsoon and the SPCZ migrates Winter northeast and Rainfall southwest depending SPCZ on the state of ENSO. ITCZ CMAP =CPC Merged Analysis of Spring Precipitation. Rainfall Pac ific Adaptatio n Strate gy Assistanc e Pro gram
ENSO Composites for Three PICs: Tarawa, Port Vila and Nadi Airport (1980 ‐ 2006) El Niño (x8): Tarawa Port Vila Nadi Airport La Niña (x4): El Niño – High Rainfall All Seasons El Niño – Low Rainfall All Seasons El Niño – Lower Rainfall Spr, Sum, Aut La Niña – Low Rainfall All Seasons La Niña – High Rainfall All Seasons La Niña – Higher Rainfall Spr, Sum, Aut Pac ific Adaptatio n Strate gy Assistanc e Pro gram Note: Composite Years (El Niño): = 1982, 1986, 1987, 1991, 1994, 1997, 2002 and 2004; and La Niña: 1984, 1988, 1998 and 1999.
The POAMA 1.5b Seasonal Prediction System •Initially developed by the BMRC and the CSIRO • Consists of the for the prediction of SST anomalies associated ocean model with ENSO over the Pacific. (ACOM2) and the atmospheric model Ocean BAM3 Atmosphere • It also has a new Atmosphere Land Sea Ice Soil Initialisation scheme (OASIS) coupler or ALI • The Forecasts are based on 10 member ensemble hindcasts Australia run over 27 years BAM3.0d Community (1980-2006) Ocean Model Spectral transform ( T47L17 ) version 2 Pac ific Adaptatio n Strate gy Assistanc e Pro gram
POAMA Forecast of Tropical Pacific SST LT= 0 and 2 months LT= 5 and 8 months Correlation Pac ific Adaptatio n Strate gy Assistanc e Pro gram From Maggie Zhao - BoM
Hit Rates of Above Median Rainfall using POAMA over the Tropical Pacific Region Observed: Yes No Yes Hits (A) False Alarms (B) Forecast Correct Misses (C) Rejection (D) No Hit Rate = A/(A+C) Pac ific Adaptatio n Strate gy Assistanc e Pro gram
Hit Rates of Median Rainfall from POAMA and Observations (CMAP) for DJF LT=2 LT=0 LT=4 LT=6 Pac ific Adaptatio n Strate gy Assistanc e Pro gram
Calibration of Seasonal Rainfall in Ensemble Forecasts using POAMA 1.5b • The calibration method used here is described in detail in the paper by Johnson and Bowler (2009) in Monthly Weather Review ; • It is known as the “variance inflation method” and is based on two conditions; • The technique adjusts the forecasts so the climatological variance of the forecasts is the same as the observations and • The correlation of observations with the unadjusted ensemble mean is the same as the correlation of the adjusted ensemble members with the unadjusted ensemble mean. Pac ific Adaptatio n Strate gy Assistanc e Pro gram
Calibration of Seasonal Rainfall at Tarawa – Kiribati Rainfall Anomaly with LT= 0 JJA MAM r=0.71 r=0.89 SON DJF r=0.81 r=0.71 Pac ific Adaptatio n Strate gy Assistanc e Pro gram
Correlation Skill and Lead Times at 14 Pacific Island Stations Stations: Nadi Airport, Suva, Rarawai, Nabouwalu, Rotuma, Port Vila, Tarawa, Funafuti, Apia, Nuku’alofa, Alofa, Honiara, Port Moresby, Rarotonga Pac ific Adaptatio n Strate gy Assistanc e Pro gram
RMSE Skill and Lead Times at 14 Pacific Island Stations Stations: Nadi Airport, Suva, Rarawai, Nabouwalu, Rotuma, Port Vila, Tarawa, Funafuti, Apia, Nuku’alofa, Alofa, Honiara, Port Moresby, Rarotonga Pac ific Adaptatio n Strate gy Assistanc e Pro gram
Summary • Seasonal Rainfall over the PICs is mostly controlled by the ITCZ and the SPCZ; • Strong rainfall changes associated with the different phases of ENSO over the tropical Pacific region provide coupled models, with the skill to produce seasonal forecasts with up to 6 months or more lead time; • Hit Rates using POAMA1.5b are typically 60 ‐ 80% across the equatorial Pacific and parts of the southwest Pacific; • Calibration of seasonal rainfall will be used in seasonal forecasting products, and is planned to compliment “SCOPIC”, which is currently used in many PICs . • Models, like POAMA, have the ability to produce better season forecasts than statistical models, as they can account for aspects of climate change and climate variability not represented in the historical record. Pac ific Adaptatio n Strate gy Assistanc e Pro gram
Acknowledgements: The Bureau of Meteorology would like to thank all the PIC nations involved in the PASAP project for providing valuable rainfall data from a number of stations across the region, and to AUSAID, who provided the funds for this PASAP project. The PASAP website can be found at the following address http://poama.bom.gov.au/experimenttal/pasap Username: pasap Password:pacifica Pac ific Adaptatio n Strate gy Assistanc e Pro gram
Pac ific Adaptatio n Strate gy Assistanc e Pro gram Spares
POAMA 1.5b Pac ific Adaptatio n Strate gy Assistanc e Pro gram CMAP
ENSO Composites for Three PICs: Tarawa, Port Vila and Nadi Airport (1980 ‐ 2006) El Niño (x8): Tarawa Port Vila Nadi Airport La Niña (x4): El Niño – High Rainfall All Seasons El Niño – Low Rainfall All Seasons El Niño – Lower Rainfall Spr, Sum, Aut La Niña – Low Rainfall All Seasons La Niña – High Rainfall All Seasons La Niña – Higher Rainfall Spr, Sum, Aut Pac ific Adaptatio n Strate gy Assistanc e Pro gram Note: Composite Years (El Niño): = 1982, 1986, 1987, 1991, 1994, 1997, 2002 and 2004; and La Niña: 1984, 1988, 1998 and 1999.
Seasonal Correlation between CMAP Rainfall and Reynolds SSTs Across the Tropical Pacific (1982 ‐ 2006) ITCZ SPCZ SPCZ ITCZ SPCZ SPCZ Correlation Pac ific Adaptatio n Strate gy Assistanc e Pro gram
Typical ENSO SST Patterns – Warm and Cold Events Modoki ‐ December 2009 ‘Classic’ El Niño ‐ Feb 1998 La Niña ‐ January 1999 La Niña ‐ December 2010 Images from: www.LongPaddock.qld.gov.au Pac ific Adaptatio n Strate gy Assistanc e Pro gram
Seasonal Correlation of CMAP and POAMA Rain and Station Correlation to POAMA Rain Summer LT=0 Autumn LT=0 Winter LT=0 Spring LT=0 Pac ific Adaptatio n Strate gy Assistanc e Pro gram
Hit Rates Plots of POAMA and CMAP (MAM) Above Median Rainfall LT=2 LT=0 LT=4 LT=6 Pac ific Adaptatio n Strate gy Assistanc e Pro gram
Hit Rates Plots of POAMA and CMAP (JJA) Above Median Rainfall LT=2 LT=0 LT=4 LT=6 Pac ific Adaptatio n Strate gy Assistanc e Pro gram
Hit Rates Plots of POAMA and CMAP (SON) Above Median Rainfall LT=2 LT=0 LT=4 LT=6 Pac ific Adaptatio n Strate gy Assistanc e Pro gram
LT=2 LT=6 Reliability Diagrams - DJF Pac ific Adaptatio n Strate gy Assistanc e Pro gram LT=0 LT=4
Reliability Diagrams Pac ific Adaptatio n Strate gy Assistanc e Pro gram Autumn Winter
Reliability Diagrams Pac ific Adaptatio n Strate gy Assistanc e Pro gram Summer Spring
Calibration of Seasonal Rainfall to Pacific Island Stations using POAMA 1.5b at Nadi Airport-Fiji (LT= 0) JJA MAM r=0.61 r=0.26 SON DJF r=0.67 r=0.62 Pac ific Adaptatio n Strate gy Assistanc e Pro gram
Calibration of Seasonal Rainfall to Pacific Island Stations using POAMA 1.5b at Port Vila - Vanuatu (LT= 0) JJA MAM r=0.53 r=0.51 SON DJF r=0.65 r=0.59 Pac ific Adaptatio n Strate gy Assistanc e Pro gram
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