The GloSea4 Ensemble Prediction System for Seasonal Forecasting

Alberto Arribas Met Office Hadley Centre, Exeter, United Kingdom

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M. Glover Met Office Hadley Centre, Exeter, United Kingdom

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A. Maidens Met Office Hadley Centre, Exeter, United Kingdom

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K. Peterson Met Office Hadley Centre, Exeter, United Kingdom

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M. Gordon Met Office Hadley Centre, Exeter, United Kingdom

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C. MacLachlan Met Office Hadley Centre, Exeter, United Kingdom

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R. Graham Met Office Hadley Centre, Exeter, United Kingdom

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D. Fereday Met Office Hadley Centre, Exeter, United Kingdom

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J. Camp Met Office Hadley Centre, Exeter, United Kingdom

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A. A. Scaife Met Office Hadley Centre, Exeter, United Kingdom

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P. Xavier Met Office Hadley Centre, Exeter, United Kingdom

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P. McLean Met Office Hadley Centre, Exeter, United Kingdom

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A. Colman Met Office Hadley Centre, Exeter, United Kingdom

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S. Cusack Met Office Hadley Centre, Exeter, United Kingdom

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Abstract

Seasonal forecasting systems, and related systems for decadal prediction, are crucial in the development of adaptation strategies to climate change. However, despite important achievements in this area in the last 10 years, significant levels of skill are only generally found over regions strongly connected with the El Niño–Southern Oscillation. With the aim of improving the skill of regional climate predictions in tropical and extratropical regions from intraseasonal to interannual time scales, a new Met Office global seasonal forecasting system (GloSea4) has been developed. This new system has been designed to be flexible and easy to upgrade so it can be fully integrated within the Met Office model development infrastructure. Overall, the analysis here shows an improvement of GloSea4 when compared to its predecessor. However, there are exceptions, such as the increased model biases that contribute to degrade the skill of Niño-3.4 SST forecasts starting in November. Global ENSO teleconnections and Madden–Julian oscillation anomalies are well represented in GloSea4. Remote forcings of the North Atlantic Oscillation by ENSO and the quasi-biennial oscillation are captured albeit the anomalies are weaker than those found in observations. Hindcast length issues and their implications for seasonal forecasting are also discussed.

Corresponding author address: Alberto Arribas, Met Office Hadley Centre, Exeter, EX1 3PB, United Kingdom. E-mail: alberto.arribas@metoffice.gov.uk

Abstract

Seasonal forecasting systems, and related systems for decadal prediction, are crucial in the development of adaptation strategies to climate change. However, despite important achievements in this area in the last 10 years, significant levels of skill are only generally found over regions strongly connected with the El Niño–Southern Oscillation. With the aim of improving the skill of regional climate predictions in tropical and extratropical regions from intraseasonal to interannual time scales, a new Met Office global seasonal forecasting system (GloSea4) has been developed. This new system has been designed to be flexible and easy to upgrade so it can be fully integrated within the Met Office model development infrastructure. Overall, the analysis here shows an improvement of GloSea4 when compared to its predecessor. However, there are exceptions, such as the increased model biases that contribute to degrade the skill of Niño-3.4 SST forecasts starting in November. Global ENSO teleconnections and Madden–Julian oscillation anomalies are well represented in GloSea4. Remote forcings of the North Atlantic Oscillation by ENSO and the quasi-biennial oscillation are captured albeit the anomalies are weaker than those found in observations. Hindcast length issues and their implications for seasonal forecasting are also discussed.

Corresponding author address: Alberto Arribas, Met Office Hadley Centre, Exeter, EX1 3PB, United Kingdom. E-mail: alberto.arribas@metoffice.gov.uk
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