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ENSO Prediction in Project Minerva: Sensitivity to Atmospheric Horizontal Resolution and Ensemble Size
Author(s) -
Jieshun Zhu,
Bohua Huang,
Benjamin A. Cash,
James L. Kinter,
Julia V. Manganello,
Rondrotiana Barimalala,
Eric L. Altshuler,
Frédéric Vitart,
Franco Molteni,
Peter Towers
Publication year - 2014
Publication title -
journal of climate
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.315
H-Index - 287
eISSN - 1520-0442
pISSN - 0894-8755
DOI - 10.1175/jcli-d-14-00302.1
Subject(s) - anomaly (physics) , climatology , environmental science , forecast skill , probabilistic logic , mean squared error , atmospheric model , categorical variable , atmospheric research , atmosphere (unit) , meteorology , mathematics , statistics , geology , geography , physics , condensed matter physics
This study examines El Nino–Southern Oscillation (ENSO) prediction in Project Minerva, a recent collaboration between the Center for Ocean–Land–Atmosphere Studies (COLA) and the European Centre for Medium-Range Weather Forecasts (ECMWF). The focus is primarily on the impact of the atmospheric horizontal resolution on ENSO prediction, but the effect from different ensemble sizes is also discussed. Particularly, three sets of 7-month hindcasts performed with ECMWF prediction system are compared, starting from 1 May (1 November) during 1982–2011 (1982–2010): spectral T319 atmospheric resolution with 15 ensembles, spectral T639 with 15 ensembles, and spectral T319 with 51 ensembles. The analysis herein shows that simply increasing either ensemble size from 15 to 51 or atmospheric horizontal resolution from T319 to T639 does not necessarily lead to major improvement in the ENSO prediction skill with current climate models. For deterministic prediction skill metrics, the three sets of predictions do not...

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