Impact of hindcast length on estimates of seasonal climate predictability.

Geophys Res Lett

Department of Physics, Atmospheric, Oceanic and Planetary Physics, University of Oxford Oxford, UK ; Department of Physics, National Centre for Atmospheric Science (NCAS), University of Oxford Oxford, UK ; European Centre for Medium-Range Weather Forecasts Reading, UK.

Published: March 2015

Unlabelled: It has recently been argued that single-model seasonal forecast ensembles are overdispersive, implying that the real world is more predictable than indicated by estimates of so-called perfect model predictability, particularly over the North Atlantic. However, such estimates are based on relatively short forecast data sets comprising just 20 years of seasonal predictions. Here we study longer 40 year seasonal forecast data sets from multimodel seasonal forecast ensemble projects and show that sampling uncertainty due to the length of the hindcast periods is large. The skill of forecasting the North Atlantic Oscillation during winter varies within the 40 year data sets with high levels of skill found for some subperiods. It is demonstrated that while 20 year estimates of seasonal reliability can show evidence of overdispersive behavior, the 40 year estimates are more stable and show no evidence of overdispersion. Instead, the predominant feature on these longer time scales is underdispersion, particularly in the tropics.

Key Points: Predictions can appear overdispersive due to hindcast length sampling errorLonger hindcasts are more robust and underdispersive, especially in the tropicsTwenty hindcasts are an inadequate sample size to assess seasonal forecast skill.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4459196PMC
http://dx.doi.org/10.1002/2014GL062829DOI Listing

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