Do seasonal‐to‐decadal climate predictions underestimate the predictability of the real world?. Issue 15 (8th August 2014)

• Record Type: Journal Article
• Authors: Eade, Rosie; Smith, Doug; Scaife, Adam; Wallace, Emily; Dunstone, Nick; Hermanson, Leon; Robinson, Niall
• Is Part Of: Geophysical research letters. Volume 41:Issue 15(2014:Aug.)
• Page Start: 5620
• Page End: 5628
• Publication Date: 2014-08-08
• Subjects: Geophysics -- Periodicals; Planets -- Periodicals; Lunar geology -- Periodicals; 550
• DOI: 10.1002/2014GL061146
• Languages: English
• ISSNs: 0094-8276

Abstract

<abstract abstract-type="main"> <title>Abstract</title> <p>Seasonal‐to‐decadal predictions are inevitably uncertain, depending on the size of the predictable signal relative to unpredictable chaos. Uncertainties can be accounted for using ensemble techniques, permitting quantitative probabilistic forecasts. In a perfect system, each ensemble member would represent a potential realization of the true evolution of the climate system, and the predictable components in models and reality would be equal. However, we show that the predictable component is sometimes lower in models than observations, especially for seasonal forecasts of the North Atlantic Oscillation and multiyear forecasts of North Atlantic temperature and pressure. In these cases the forecasts are underconfident, with each ensemble member containing too much noise. Consequently, most deterministic and probabilistic measures underestimate potential skill and idealized model experiments underestimate predictability. However, skilful and reliable predictions may be achieved using a large ensemble to reduce noise and adjusting the forecast variance through a postprocessing technique proposed here.</p> </abstract>