Bureau of Meteorology Activities as a GPC of Long Range Forecasts

Dr David Jonesd.jones@bom.gov.au

Australian Bureau of Meteorology

CBS Expert Team on Extended and Long Range Forecasting

Geneva, Switzerland, 26-30 March 2012Acknowledgement

Oscar Alves, Andrew Watkins, Lynette Bettio, Elise Chandler & Andrew Charles

Long Range Forecast Service

• Current seasonal outlooks for Australia based on a statistical model

• Probability of rainfall/temperature in Tercile/Above Below Median categories

• Trial of dynamical model forecasts.

• Statistical monitoring and prediction of Intraseasonal Variability• Current phase and amplitude of the MJO• Prediction for winds, rainfall, convection, pressure for the coming weeks

• Dynamical model predictions for ocean conditions & experimentally for climate variables over land

• Focus on the Pacific and Indian Oceans• Developing direct model forecasts for rainfall and temperature

Delivering useful long range predictions for Australia and WMO member countries

Recent POAMA 2.4 improvements

• POAMA2.4 became fully operational in October 2011

• T47L17 + improved physics (land surface, radiation, gravity wave drag, cloud microphysics, etc)

• Land surface scheme (ALI) is more realistic and initialized daily

• Increased number of ensemble members of hind-cast (30 member) over the last 30 years (updated in real-time), providing better hindcast skill estimates

• Real-time forecasts (30 ensemble members per month) since July 2011 run twice monthly. Moving to a 1981 to 2010 base period

• Improved accessibility – OpenDAP server http://opendap.bom.gov.au:8080/thredds/bmrc-poama-catalog.html

• Pseudo multimodel ensemble

• POAMA=Predictive Ocean Atmosphere Model for Australia

• Forecasts run for 9 months• Atmospheric model:

• Horizontal resolution ~250km • 17 vertical levels

• Ocean model:• Zonal resolution ~220 km • Meridional resolution ~55km (tropics) to ~165 km (poles) • 25 vertical levels

The Coupled Model: Predictive Ocean Atmosphere Model for Australia

POAMABoM

Atmospheric Model (BAM) v3

Australian Community

Ocean Model (ACOM) v2

Simple land-surface

model= + +

P2.4P2.4

M2.4Enhanced ensemble

generation

M2.4Enhanced ensemble

generation

Plans for POAMA/ACCESS versions

Done

Operational P2.4 Full Seasonal System

Operational P2.4 Full Seasonal System

M2.4 multi-week system in

operations

M2.4 multi-week system in

operations

Operational M2.4 Seamless Multi-week/Full Seasonal System

Operational M2.4 Seamless Multi-week/Full Seasonal System

P2.5Coupled

DA/ensemble generation

P2.5Coupled

DA/ensemble generation

P3.0ACCESS Based higher

resolution system

P3.0ACCESS Based higher

resolution system

Future?

Operational P2.5 multi-week system in

operations (may bipass)

Operational P2.5 multi-week system in

operations (may bipass)

Operational P2.5 Seamless multiweek/seasonal

Operational P2.5 Seamless multiweek/seasonal

Operational P3.0 multi-week system

Operational P3.0 multi-week system

Operational P3.0 Seamless multiweek/seasonal

Operational P3.0 Seamless multiweek/seasonal

~1-3 months

~6-9 months

~6-12months

~2 years

~4 years

M2.4 Seamless Multi-week/First Seasonal only System in operations

M2.4 Seamless Multi-week/First Seasonal only System in operations

Operational Products:

SSTs, NINO 3,3.4,4 & IOD available

Public Website

Pacific SST skill: Temporal correlation of monthly SSTA

POAMA 1.5 & 2NCEP Climate forecast system

V1 & 2

Frontier Research Centre

Model (Japan)

ECMWF System 3

Forecast Lead time (months)

Cor

rela

tion

POAMA-2

POAMA-1.5

POAMA skill - RainfallCorrelation with (CMAP) Rainfall

How well does POAMA do with the rainfall patterns?

Highest correlation is found in the equatorial Pacific and parts of the southwest Pacific…..

MJO index forecast skill (RMSE = 1.4)

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29

ALL

DJF

MAM

JJA

SON

Se

as

on

Lead time (days)

POAMA-2 (m24m) POAMA-1.5 (p15b)

POAMA-1.5POAMA-2

Predicting the MJO Index

All seasons:Skillful prediction of the MJO out to….

Producing Reliable Forecasts: Calibration

Raw rainfall forecasts (lower Tercile) across the tropical Pacific

Calibrated (IOV) forecasts – better reliability but lower skill.

Architecture for Seasonal Forecast Generation and Publication System

The Bureau as a GPC

Hindcasts verified following the LRFVS

Real time forecasts

Developing a GPC Seasonal Prediction Portal

The Seasonal Prediction Portal provides access to outlooks for• Broad scale fields• Climate drivers (ENSO)• Rainfall and temperature tercile probabilities for selected

sites• Hindcast skill scores for all outlooks• Focus on the Pacific

http://poama.bom.gov.au/experimental/pasap/

Capacity Building

• Extensive training of the Pacific NMS personnel during in-country visits•PASAP/PI-CPP joint workshops – Auckland, New Zealand (Sept 2010) and Port Vila, Vanuatu (Sept 2011)

The Bureau as a GPC• The BoM is a producer of LRFs, following a fixed time schedule• Products are available to other GPCs, RCCs and NMHSs• Forecasts provided to the LRF Lead Centre and APCC• Hindcasts have been verified following the Standardized Verification System• Systems are scientifically documented• The Bureau does not yet have a GPC website• The BoM is heavily involved in training and capacity building activities in the

South Pacific: • Pacific Islands Climate Prediction Project • Pacific Adaptation Strategy Assistance Program (delivering dynamical

season outlooks for Pacific Island countries)• Pacific Climate Change Science Program• Opportunity for additional supported projects• Developing forecasts for extreme events – TCs, Coral Bleaching, high sea

level