Climate Dynamics

, Volume 46, Issue 7–8, pp 2423–2434 | Cite as

Predictability of the tropospheric circulation in the Southern Hemisphere from CHFP models

Article

Abstract

An assessment of the predictability and prediction skill of the tropospheric circulation in the Southern Hemisphere was done. The analysis is based on seasonal forecasts of geopotential heights at 200, 500 and 850 hPa, for austral summer and winter from 11 models participating in the Climate Historical Forecast Project. It is found that predictability (signal-to-variance ratio) and prediction skill (anomaly correlation) in the tropics is higher than in the extratropics and is also higher in summer than in winter. Both predictability and skill are higher at high than at low altitudes. Modest values of predictability and skill are found at polar latitudes in the Bellinghausen-Amundsen Seas. The analysis of the changes in predictability and prediction skill in ENSO events reveals that both are slightly higher in the El Niño-Southern Oscillation (ENSO) years than in all years, while the spatial patterns of maxima and minima remain unchanged. Changes in signal-to-noise ratio observed are mainly due to signal changes rather than changes in noise. Composites of geopotential heights anomalies for El Niño and La Niña years are in agreement with observations.

Keywords

Southern Hemisphere El niño southern oscillation Seasonal predictability Geopotential heights 

Notes

Acknowledgments

We acknowledge the WCRP/CLIVAR Working Group on Seasonal to Interannual Prediction (WGSIP) for establishing the Climate-system Historical Forecast Project (CHFP, see Kirtman and Pirani 2009) and the Centro de Investigaciones del Mar y la Atmosfera (CIMA) for providing the model output http://chfps.cima.fcen.uba.ar/DS. We also thank the data providers for making the model output available through CHFP. This research was supported by UBACyT 20020100100434, ANPCyTPICT-2010-2110, European Union’s FP7-funded SPECS (GA 308378) project and the Catalan Government. M.O. is supported by a Ph.D grant from CONICET, Argentina.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  1. 1.Centro de Investigaciones del Mar y la Atmósfera (CIMA) CONICET-UBA, DCAO/FCEN, UMIIFAECI/CNRSBuenos AiresArgentina
  2. 2.Institucio Catalana de Recerca i EstudisAvançats (ICREA)BarcelonaSpain
  3. 3.Institut Català de Ciències del Clima (IC3)BarcelonaSpain
  4. 4.Barcelona Supercomputing Center-Centro Nacional de Supercomputación (BSC-CNS)BarcelonaSpain

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