Introduction
The Predictive Ocean Atmosphere Model for Australia (POAMA) is a state-of-the-art seasonal to inter-annual seasonal forecast system based on a coupled ocean/ atmosphere model and ocean/atmosphere/land observation assimilation systems.
The start of POAMA
The first version of POAMA (POAMA-1) was developed in a joint project involving the Bureau of Meteorology Research Centre (BMRC) and CSIRO Marine Research, with support providedby the Climate Variability in Agriculture Program (CVAP), a consortium of rural research and development corporations managed by Land and Water Australia. The core of the research was carried out by scientists from the Oceanography Group at BMRC and scientist from the Oceans and Climate Group at CSIRO Marine Research. This first version went operational in October 2002 and produced routine forecasts of El Nino conditions.
Present (POAMA-1.5/2)
Since POAMA-1 operational BMRC scientists have continued to work on a new and improved version POAMA-2. This research involved improvements to the coupled model, particularly in the representaition of coupling processes. A new atmosphere/land initialisation system was developed, in part funded by the SEACI project. The SEACI project also funded research to develop statistical downscaling and bridging techniques to add value to POAMA rainfall and temperature forecasts. Through collaboration with scientists working on a new joint BMRC, CSIRO and Australian Navy project called BLUElink, a new state of the art ocean data assimilation system (PEODAS: POAMA Ensemble Ocean Data Assimilation System) as an extension of the BLUElink data assimilation system (BODAS).
A preliminary version of the POAMA-2 system (called POAMA-1.5) is being made operational in 2007 and the complete POAMA-2 system will be operational in 2008. A key focus of the new system is the generation of regional products such as rainfall and temperature over Australia.
Another focus of the POAMA-1.5/2 systems is the provision of intra-seasonal or weekly forecasts. These provide more detail on time scales of weeks, a time scale between weather forecasting and seasonal forecasting that has received little attention in the past.
Future (POAMA-3 and beyond, ACCESS)
Like the development of models for weather forecasting, the development of models for seasonal prediction is a long term activity with the development of sequential versions of the system.
The core development of the main modules of the future versions of POAMA will be carried out in a project called ACCESS. ACCESS involves POAMA scientists as well as scientists from weather forecasting, climate change and ocean predicition. ACCESS brings together the modelling activities of the BMRC and CSIRO into the development of one common earth system model. POAMA-3 and beyond will be the seasonal prediction configuration of the ACCESS system.
As part of ACCESS a new coupled model will be built. The atmospheric model will be based on the atmospheric model developed by the UK Met Office. The ocean model will still be based on the GFDL MOM models, but based on their latest version (MOM4) and will be built in a new configuraiton with higher resolution and improved physics. The new ocean model configuration is called the Australian Climate Ocean Model (AusCOM).
The development of ocean assimilation systems is also part of the ACCESS project, and will be lead by POAMA and BLUElink scientists. Present plans are to develop coupled data assimilation systems and POAMA is aiming to take a lead in this field internationally. The BODAS system developed as part of BLUElink and its extension into PEODAS will be further developed as the core ocean data assimilation systems with the ACCESS project.
Why Coupled Models ?
Coupled models are now much closer to delivering better seasonal forecasts and at longer lead times —six months or more ahead. They couple the ocean and atmosphere and can use all the latest observations from ships, satellites,ground stations etc to construct a picture of what the ocean, land and atmosphere look like today. A picture of how the state of the ocean, land and atmosphere is evolving is then generated using the coupled model.This model uses mathematical equations representing the laws of physics.
Unlike existing statistical forecasting systems, coupled models are not limited by historical relationships and can forecast a new set of climatic conditions. For example, because they simulate the real world they have the potential to predict how the impacts of one El Niño might be different to those of another.
One of the benefits of coupled models is that many forecasts (an ensemble) can be produced. If these are all close together then we can have confidence in the forecast. If they all differ significantly they can tell us that there is considerable uncertainty in the future and they give us the range of possibilities.
Compared to weather forecasting, coupled model seasonal forecasting is still in its infancy.
Still, great potential lies ahead.
By continuing this collaborative work and investing in further improving our system we will reap the full benefits of coupled models and provide Australia with a seasonal forecasting capability second to none.
For further information: email the POAMA group
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