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Author Sally Langford |
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CAWCR technical report, 51. Improvements in POAMA2 for the prediction of major climate drivers and south eastern Australian rainfall
Lim Eun-Pa; Hendon Harry H.; Langford Sally; et al. - Centre for Australian Weather and Climate Research, 2012Ocean-atmosphere interactions are key processes that drive seasonal climate variability. In the global sense, the atmosphere drives the upper ocean via heat flux, fresh water flux and wind stress (Anderson 2008). But in the tropics where the ocean surface temperature (hereafter, sea surface temperature, SST) is warm enough to trigger deep atmospheric convection, the ocean exerts strong controls on the atmosphere especially at longer time scales because of its slow variations and strong thermal inertia. Consequently, the highest predictability of atmospheric climate (e.g. temperature and rainfa ...Improvements in POAMA2 for the prediction of major climate drivers and south eastern Australian rainfall
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Available online: https://www.cawcr.gov.au/publications/
Published by: Centre for Australian Weather and Climate Research ; 2012
Ocean-atmosphere interactions are key processes that drive seasonal climate variability. In the global sense, the atmosphere drives the upper ocean via heat flux, fresh water flux and wind stress (Anderson 2008). But in the tropics where the ocean surface temperature (hereafter, sea surface temperature, SST) is warm enough to trigger deep atmospheric convection, the ocean exerts strong controls on the atmosphere especially at longer time scales because of its slow variations and strong thermal inertia. Consequently, the highest predictability of atmospheric climate (e.g. temperature and rainfall) on seasonal timescales is found predominantly across and directly surrounding the tropical ocean basins and in those extratropical regions of the globe that are directly influenced by atmospheric Rossby waves which are excited by variations of tropical deep convection that develop in response to variations in tropical SST (e.g. Hoskins and Schopf 2008) [...]
Collection(s) and Series: CAWCR technical report- No. 51
Language(s): English
Format: Digital (Free), Hard copyTags: Observations ; Climate model ; Precipitation forecasting ; Australia
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CAWCR technical report, 48. Seasonal Climate Prediction in the Pacific using the POAMA coupled model forecast system
Cottrill A.; Hendon Harry H.; Lim Eun-Pa; et al. - Centre for Australian Weather and Climate Research, 2012The tropical Pacific Ocean basin is home to over 20 Pacific Island nations, many of which are sensitive to climate extremes from the El Niño-Southern Oscillation (ENSO) and rainfall variability associated the Inter-Tropical Convergence Zone and the South Pacific Convergence Zone. These Pacific Island countries are highly dependent on agriculture, fishing and tourism as a major source of food production and income, which can vary greatly depending on the weather and climate experienced from year to year. Hence, the provision of skilful seasonal forecasts is important to allow these countries to ...
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Available online: https://www.cawcr.gov.au/publications/
A. Cottrill ; Harry H. Hendon ; Eun-Pa Lim ; Sally Langford ; Y. Kuleshov ; Andrew Charles ; David Jones
Published by: Centre for Australian Weather and Climate Research ; 2012The tropical Pacific Ocean basin is home to over 20 Pacific Island nations, many of which are sensitive to climate extremes from the El Niño-Southern Oscillation (ENSO) and rainfall variability associated the Inter-Tropical Convergence Zone and the South Pacific Convergence Zone. These Pacific Island countries are highly dependent on agriculture, fishing and tourism as a major source of food production and income, which can vary greatly depending on the weather and climate experienced from year to year. Hence, the provision of skilful seasonal forecasts is important to allow these countries to prepare for changes in rainfall and impending droughts associated with the changes in ENSO. The Australian Bureau of Meteorology has developed a dynamical seasonal forecast system POAMA (Predictive Ocean-Atmosphere Model for Australia), which is a state of the art seasonal to inter-annual forecast system based on a coupled model of the ocean and atmosphere. The model has good skill at predicting El Niño and La Niña up to 9 months in advance and it is capable of simulating the spatial and temporal variability of tropical rainfall associated with ENSO. Consequently, the variability of rainfall patterns across the Pacific region is skilfully predicted by POAMA at short lead times. The availability of seasonal forecasts from dynamical models will aid Pacific Island countries to improve economic returns in agriculture and other industries and reduce impacts from storms, floods and droughts associated with the extremes of El Niño and La Niña.
Collection(s) and Series: CAWCR technical report- No. 48
Language(s): English
Format: Digital (Free)Tags: Observations ; Seasonal change ; Climate ; Climate model ; Climate prediction ; Weather forecasting ; Region V - South-West Pacific
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CAWCR technical report, 39. Assessment of international seasonal rainfall forecasts for Australia and the benefit of multi-model ensembles for improving reliability
In this report we assess forecasts from Predictive Ocean Atmosphere Model for Australia (POAMA) in comparison to international dynamical coupled model forecast systems, which are archived as part of the ENSEMBLES project. We investigate how universal the lack of reliability is in dynamical forecasts of regional rainfall, in order to highlight any potential for improvement of the POAMA system. The systems assessed in this report show that overconfidence and lack of reliability for regional rainfall forecasts is a common problem. Due to the clear need for improved reliability and more accurate s ...Assessment of international seasonal rainfall forecasts for Australia and the benefit of multi-model ensembles for improving reliability
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Available online: https://www.cawcr.gov.au/technical-reports/CTR_039.pdf
Published by: Centre for Australian Weather and Climate Research ; 2011
In this report we assess forecasts from Predictive Ocean Atmosphere Model for Australia (POAMA) in comparison to international dynamical coupled model forecast systems, which are archived as part of the ENSEMBLES project. We investigate how universal the lack of reliability is in dynamical forecasts of regional rainfall, in order to highlight any potential for improvement of the POAMA system. The systems assessed in this report show that overconfidence and lack of reliability for regional rainfall forecasts is a common problem. Due to the clear need for improved reliability and more accurate seasonal rainfall forecasts for hydrological applications, we have explored the benefit of combining a range of operationally available models into a multi-model ensemble, which can cancel uncorrelated error, increase spread and reduce model error. Our results indicate that there is benefit in adding POAMA version P24 to the operational models from the European Centre for Medium-Range Weather Forecasts (ECMWF), the UK Meteorological Office (UKMO) and Météo France (MF), into an equally weighted multi-model ensemble, to increase the reliability and consistency of accurate regional rainfall forecasts.
Collection(s) and Series: CAWCR technical report- No. 39
Language(s): English
Format: Digital (Free), Hard copy (ill., charts, maps)ISBN (or other code): 978-1-921826-56-6
Tags: Water ; Hydrological forecast ; Modelling ; Precipitation forecasting ; Australia
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