Decadal Predictability of Seasonal Temperature Distributions
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 Pla...
Published in: | Geophysical Research Letters |
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Main Authors: | , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
American Geophysical Union
2024
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Subjects: | |
Online Access: | https://mural.maynoothuniversity.ie/18603/ https://doi.org/10.1029/2023GL107838 https://mural.maynoothuniversity.ie/18603/1/Geophysical%20Research%20Letters%20-%202024%20-%20D%C3%BCsterhus%20-%20Decadal%20Predictability%20of%20Seasonal%20Temperature%20Distributions.pdf |
Summary: | 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 |
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