Standard assessments of climate forecast skill can be misleading

James S. Risbey (), Dougal T. Squire, Amanda S. Black, Timothy DelSole, Chiara Lepore, Richard J. Matear, Didier P. Monselesan, Thomas S. Moore, Doug Richardson, Andrew Schepen, Michael K. Tippett and Carly R. Tozer
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James S. Risbey: CSIRO Oceans & Atmosphere
Dougal T. Squire: CSIRO Oceans & Atmosphere
Amanda S. Black: CSIRO Oceans & Atmosphere
Timothy DelSole: George Mason University
Chiara Lepore: Columbia University
Richard J. Matear: CSIRO Oceans & Atmosphere
Didier P. Monselesan: CSIRO Oceans & Atmosphere
Thomas S. Moore: CSIRO Oceans & Atmosphere
Doug Richardson: CSIRO Oceans & Atmosphere
Andrew Schepen: CSIRO Land & Water
Michael K. Tippett: Columbia University
Carly R. Tozer: CSIRO Oceans & Atmosphere

Nature Communications, 2021, vol. 12, issue 1, 1-14

Abstract: Abstract Assessments of climate forecast skill depend on choices made by the assessor. In this perspective, we use forecasts of the El Niño-Southern-Oscillation to outline the impact of bias-correction on skill. Many assessments of skill from hindcasts (past forecasts) are probably overestimates of attainable forecast skill because the hindcasts are informed by observations over the period assessed that would not be available to real forecasts. Differences between hindcast and forecast skill result from changes in model biases from the period used to form forecast anomalies to the period over which the forecast is made. The relative skill rankings of models can change between hindcast and forecast systems because different models have different changes in bias across periods.

Date: 2021
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DOI: 10.1038/s41467-021-23771-z

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