Decadal Predictability of Seasonal Temperature Distributions

• Published in: Geophysical Research Letters
• Main Authors: André Düsterhus, Sebastian Brune
• Format: Article in Journal/Newspaper
• Language: English
• Published: Wiley 2024
• Subjects: decadal prediction; temperature distribution; probability density function; prediction skill; verification; Geophysics. Cosmic physics; QC801-809; North Atlantic
• Online Access: https://doi.org/10.1029/2023GL107838; https://doaj.org/article/59c96cce9d4645d6b7580b13f65888f9

Abstract 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.