MURAL - Maynooth University Research Archive Library



    Decadal Predictability of Seasonal Temperature Distributions


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

    [img] Download (3MB)
    Official URL: https://doi.org/10.1029/2023GL107838


    Share your research

    Twitter Facebook LinkedIn GooglePlus Email more...



    Add this article to your Mendeley library


    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

    Item Type: Article
    Additional Information: A.D. is supported by A4 (Aigéin, Aeráid, agus athrú Atlantaigh), funded by the Marine Institute (grant: PBA/CC/18/01) and received funding from the Danish state through the National Centre for Climate Research (NCKF). S.B. is supported by the German Ministry of Education and Research (BMBF) under Grant 01LP2327A (project Coming Decade), and by Copernicus Climate Change Service, funded by the EU, under contract C3S2‐ 370. We thank the staff at the German Climate Computing Center (DKRZ), Hamburg and the Max Planck Institute for Meteorologie, Hamburg for their support. All simulations analyzed in this study have been run and processed on DKRZ high performance computers.
    Keywords: decadal predictions; distribution of temperature values; climate models;
    Academic Unit: Faculty of Social Sciences > Research Institutes > Irish Climate Analysis and Research Units, ICARUS
    Item ID: 18603
    Identification Number: https://doi.org/10.1029/2023GL107838
    Depositing User: André Düsterhus
    Date Deposited: 04 Jun 2024 08:37
    Journal or Publication Title: Geophysical Research Letters
    Publisher: American Geophysical Union
    Refereed: Yes
    URI:
    Use Licence: This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

    Repository Staff Only(login required)

    View Item Item control page

    Downloads

    Downloads per month over past year

    Origin of downloads