Decadal Predictability of Seasonal Temperature Distributions

American Geophysical Union 2024

Decadal predictions focus regularly on the predictability of single values, like means or extremes. In this study we investigate the prediction skill of the full underlying surface temperature distributions on global and European scales. We investigate initialized hindcast simulations of the Max Planck Institute Earth system model decadal prediction system and compare the distribution of seasonal daily temperatures with estimates of the climatology and uninitialized historical simulations. In the analysis we show that the initialized prediction system has advantages in particular in the North Atlantic area and allow so to make reliable predictions for the whole temperature spectrum for two to 10 years ahead. We also demonstrate that the capability of initialized climate predictions to predict the temperature distribution depends on the season

Article; PeerReviewed

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text
Düsterhus, Andre and Brune, Sebastian (2024) Decadal Predictability of Seasonal Temperature Distributions. Geophysical Research Letters, 51 (11). ISSN 0094-8276
English

EIS oai:mural.maynoothuniversity.ie:18603
https://mural.maynoothuniversity.ie/id/eprint/18603/1/Geophysical%20Research%20Letters%20-%202024%20-%20D%C3%BCsterhus%20-%20Decadal%20Predictability%20of%20Seasonal%20Temperature%20Distributions.pdf
Düsterhus, Andre and Brune, Sebastian (2024) Decadal Predictability of Seasonal Temperature Distributions. Geophysical Research Letters, 51 (11). ISSN 0094-8276
1482749824

MAYNOOTH UNIV
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