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Guomin Wang
,
Richard Kleeman
,
Neville Smith
, and
Faina Tseitkin

Abstract

An El Niño–Southern Oscillation (ENSO) prediction system with a coupled general circulation model and an ocean data assimilation scheme has been developed at the Australian Bureau of Meteorology Research Centre (BMRC). The coupled model consists of an R21L9 version of the BMRC climate model and a global version of the Geophysical Fluid Dynamics Laboratory modular ocean general circulation model with resolution focused in the tropical region and 25 vertical levels. A univariate statistical interpolation method, with 10-day data ingestion windows, is used to assimilate ocean temperature data and initialize the coupled model. The coupling procedure does not use any flux corrections. Hindcasts have been carried out for the period 1981–95 for each season (60 in all), for up to a lead time of 12 months. This paper will describe these initial experiments and show that the skill of sea surface temperature (SST) hindcasts in the tropical Pacific is comparable to other published coupled models. The skill of the model is strongest in the central Pacific. SST skill tends to be lower during the earlier 1990s than during 1980s in the eastern Pacific but not in the central Pacific. Since the ENSO SST anomaly in the central Pacific is the most important forcing of regional and global climate anomalies, the high SST prediction skill and its insensitivity over the hindcast period in this region in this model give grounds for optimism in the use of coupled general circulation models.

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Eun-Pa Lim
,
Harry H. Hendon
,
Debra Hudson
,
Guomin Wang
, and
Oscar Alves

Abstract

The relationship between variations of Indo-Pacific sea surface temperatures (SSTs) and Australian springtime rainfall over the last 30 years is investigated with a focus on predictability of inter–El Niño variations of SST and associated rainfall anomalies. Based on observed data, the leading empirical orthogonal function (EOF) of Indo-Pacific SST represents mature El Niño conditions, while the second and fourth modes depict major east–west shifts of individual El Niño events. These higher-order EOFs of SST explain more rainfall variance in Australia, especially in the southeast, than does the El Niño mode. Furthermore, intense springtime droughts tend to be associated with peak warming in the central Pacific, as captured by EOFs 2 and 4, together with warming in the eastern Pacific as depicted by EOF1.

The ability to predict these inter–El Niño variations of SST and Australian rainfall is assessed with the Australian Bureau of Meteorology dynamical coupled model seasonal forecast system, the Predictive Ocean and Atmospheric Model for Australia (POAMA). A 10-member ensemble of 9-month hindcasts was generated for the period 1980–2006. For the September–November season, the leading 2 EOFs of SST are predictable with lead times of 3–6 months, while SST EOF4 is predictable out to a lead time of 1 month. The teleconnection between the leading EOFs of SST and Australian rainfall is also well depicted in the model. Based on this ability to predict major east–west variations of El Niño and the teleconnection to Australian rainfall, springtime rainfall over eastern Australia, and major drought events are predictable up to a season in advance.

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