Brief description
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. This project will establish the limits of predictability of large-scale variations of the marine environment in Western Australia using POAMA.POAMA-1.5 hindcast and realtime data consists of three types output.
1. Hindcasts
Comprehensive set of hind-casts with a 10 member ensemble
2. Forecasts
These are realtime forecasts, which are run one per day. Most products involve putting together forecasts for the last 30 days to form an ensemble.
3. Model Climatologies
Model climatologies in same format as the forecasts and hindcasts. These can be used to creat forecast anomalies and therefore removing model biases. Each set starts on the first of the month. Note, for realtime forecasts starting on different days of the month, one should interpolate the two surrounding climatologies starting on the first of the month.
Forecast model output includes monthly means of global fields of upper ocean temperatures, currents, and salinity. Atmospheric fields include global fields of all surface fluxes (momentum, radiation, sensible and latent heat), and winds, temperatures, humidity, clouds, etc.
A subset of daily data, suitable for driving offline mixed layer models and downscaled models, including surface fluxes, surface winds, surface currents and temperature, is also archived.
Lineage
Statement: Coupled model output and forecasts are generated from the POAMA seasonal forecast model. The version used is the POAMA-1.5 system which is a preliminary version of the POAMA-2 system being developed.Further information is given on POAMA homepage - http://poama.bom.gov.au/dataserver/index.htm
Statement: POAMA-1.5 hindcast and realtime data consists of three types output.
1. Hindcasts
Comprehensive set of hind-casts with a 10 member ensemble
2. Forecasts
These are realtime forecasts, which are run one per day. Most products involve putting together forecasts for the last 30 days to form an ensemble.
3. Model Climatologies
Model climatologies in same format as the forecasts and hindcasts. These can be used to create forecast anomalies and therefore removing model biases. Each set starts on the first of the month. Note, for realtime forecasts starting on different days of the month, one should interpolate the two surrounding climatologies starting on the first of the month.
1. Hindcasts
Comprehensive set of hind-casts with a 10 member ensemble
2. Forecasts
These are realtime forecasts, which are run one per day. Most products involve putting together forecasts for the last 30 days to form an ensemble.
3. Model Climatologies
Model climatologies in same format as the forecasts and hindcasts. These can be used to create forecast anomalies and therefore removing model biases. Each set starts on the first of the month. Note, for realtime forecasts starting on different days of the month, one should interpolate the two surrounding climatologies starting on the first of the month.
Notes
PurposeThis project will provide an increased understanding of the of large-scale control of the year-to-year variations of the Western Australian marine environment by elucidating the relative contributions of the atmospheric and oceanic teleconnections of ENSO, IOD and the subtropical and subantarctic oceans to the large-scale wind, rainfall, sea surface temperature and ocean current variability that affect Western Australia. Mechanisms for the interaction of the IOD with ENSO will also be elucidated. Such an understanding will underpin assessment of climate change simulation for the region.
Modified: 15 08 2011
text: westlimit=112; southlimit=-44; eastlimit=154; northlimit=-9
Subjects
Climate Model Forecasts |
Climate Model Predictions |
EARTH SCIENCE |
OCEAN CIRCULATION |
Ocean Currents |
OCEAN TEMPERATURE |
OCEANS |
Salinity |
SALINITY/DENSITY |
Seasonal Forecasts |
Seasonal Prediction |
Water Temperature |
climatologyMeteorologyAtmosphere |
oceans |
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Other Information
(POAMA home page)
uri :
http://poama.bom.gov.au/
(Real time prediction of Fremantle sea level anomaly)
uri :
http://poama.bom.gov.au/wamsi/wamsi.shtml
(Link to journal article - Hendon, H.H., and G. Wang, 2009. Climate Dynamics. Seasonal prediction of the Leeuwin Current using the POAMA dynamical seasonal forecast model. 34(7-8). 1129-1137)
Identifiers
- global : 6ab77971-0efc-41fe-bb61-54de16d6e065
