Skill improvement from increased ensemble size and model diversity

Geophysical Research Letters - Tập 41 Số 20 - Trang 7331-7342 - 2014
Timothy DelSole1, Jyothi Nattala1, Michael K. Tippett2,3
1Center for Ocean-Land-Atmosphere Studies, George Mason University,#N#Fairfax, Virginia, USA
2Center of Excellence for Climate Change Research/ Department of Meteorology, King Abdulaziz University, Jeddah, Saudi Arabia
3Department of Applied Physics and Applied Mathematics, Columbia University, New York, New York, USA

Tóm tắt

Abstract

This paper proposes an objective procedure for deciding if the skill of a combination of forecasts is significantly larger than that of a single forecast, and for deciding if the observed improvement is dominated by reduction of noise associated with ensemble averaging, or by addition of new predictable signals. Information theory provides an attractive framework for addressing these questions. The procedure is applied to El Niño–Southern Oscillation hindcasts from the North American Multimodel Ensemble (NMME) and reveals that the observed skill advantage of the NMME compared to individual models is substantially greater than that expected from increased ensemble size alone and is more consistent with the addition of new signals.

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Tài liệu tham khảo

10.1007/s00382‐013‐1845‐2

10.1175/BAMS-84-12-1783

10.1175/2009MWR2893.1

Cover T. M. andJ. A.Thomas(1991) Elements of information theory 576 pp.

10.1175/JAS3522.1

10.1175/JCLI4179.1

10.1175/MWR‐D‐14‐00045.1

10.1002/qj.1961

10.1175/JCLI-D-13-00030.1

10.1002/2014GL061146

10.1111/j.1600‐0870.2005.00103.x

10.1007/s00382-005-0074-8

10.1175/1520-0442(2002)015<0793:CPWME>2.0.CO;2

10.1175/2009MWR2672.1

10.1175/BAMS-D-12-00050.1

10.1175/1520-0442(2000)013<4196:MEFFWA>2.0.CO;2

10.1175/MWR-D-11-00335.1

Muirhead R. J., 2009, Aspects of Multivariate Statistical Theory, 704

10.1007/s003820000063

10.1175/2008JCLI2226.1

10.1175/2007JCLI1824.1

10.1175/JCLI-D-12-00823.1

10.1175/JCLI-D-12-00462.1

Scheffe H., 1959, The Analysis of Variance, 477

10.1002/9780471722199

10.1002/wics.62

10.1098/rsta.2007.2076

10.1029/2004GL021276

10.1029/97JC01444

10.1007/s00382-012-1313-4

10.1175/2010JCLI3594.1