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When and where do ECMWF seasonal forecast systems exhibit anomalously low signal‐to‐noise ratio?
Author(s) -
CharltonPerez Andrew J.,
Bröcker Jochen,
Stockdale Timothy N.,
Johnson Stephanie
Publication year - 2019
Publication title -
quarterly journal of the royal meteorological society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.744
H-Index - 143
eISSN - 1477-870X
pISSN - 0035-9009
DOI - 10.1002/qj.3631
Subject(s) - predictability , noise (video) , environmental science , signal to noise ratio (imaging) , middle latitudes , signal (programming language) , climatology , meteorology , geology , statistics , computer science , mathematics , geography , artificial intelligence , image (mathematics) , programming language
Seasonal predictions of wintertime climate in the Northern Hemisphere midlatitudes, while showing clear correlation skill, suffer from anomalously low signal‐to‐noise ratio. The low signal‐to‐noise ratio means that forecasts need to be made with large ensemble sizes and require significant post‐processing to correct the forecast distribution. In this study, a recently introduced statistical model of seasonal climate predictability is adapted so that it can be used to examine the signal‐to‐noise ratio in two versions of the ECMWF seasonal forecast system. Three novel features of the low signal‐to‐noise ratio are revealed. The low signal‐to‐noise ratio is present only for forecasts initialized on 1 November and not for forecasts initialized on 1 December. The low signal‐to‐noise ratio is predominantly a feature of the lower and middle troposphere and is not present in the stratosphere. The low signal‐to‐noise ratio is linked to low signal amplitude of the forecast systems in early winter. Future studies attempting to examine the signal‐to‐noise ratio should focus on the extent to which this early winter variability is predictable.