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    Do CMIP models capture long-term observed annual precipitation trends?


    Vicente-Serrano, S. M. and García-Herrera, R. and Peña-Angulo, D. and Tomas-Burguera, M. and Domínguez-Castro, F. and Noguera, I. and Calvo, N. and Murphy, C. and Nieto, R. and Gimeno, L. and Gutierrez, J. M. and Azorin-Molina, C. and El Kenawy, A. (2022) Do CMIP models capture long-term observed annual precipitation trends? Climate Dynamics, 58 (9-10). pp. 2825-2842. ISSN 0930-7575

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    Abstract

    This study provides a long-term (1891–2014) global assessment of precipitation trends using data from two station-based gridded datasets and climate model outputs evolved through the fifth and sixth phases of the Coupled Model Intercomparison Project (CMIP5 and CMIP6, respectively). Our analysis employs a variety of modeling groups that incorporate low- and high-top level members, with the aim of assessing the possible effects of including a well-resolved stratosphere on the model’s ability to reproduce long-term observed annual precipitation trends. Results demonstrate that only a few regions show statistically significant differences in precipitation trends between observations and models. Nevertheless, this pattern is mostly caused by the strong interannual variability of precipitation in most of the world regions. Thus, statistically significant model-observation differences on trends (1891–2014) are found at the zonal mean scale. The different model groups clearly fail to reproduce the spatial patterns of annual precipitation trends and the regions where stronger increases or decreases are recorded. This study also stresses that there are no significant differences between low- and high-top models in capturing observed precipitation trends, indicating that having a well-resolved stratosphere has a low impact on the accuracy of precipitation projections.

    Item Type: Article
    Additional Information: Cite as: Vicente-Serrano, S.M., García-Herrera, R., Peña-Angulo, D. et al. Do CMIP models capture long-term observed annual precipitation trends?. Clim Dyn 58, 2825–2842 (2022). https://doi.org/10.1007/s00382-021-06034-x
    Keywords: Observed precipitation; Historical simulations; CMIP; Trends; Stratosphere;
    Academic Unit: Faculty of Social Sciences > Geography
    Faculty of Social Sciences > Research Institutes > Irish Climate Analysis and Research Units, ICARUS
    Item ID: 17774
    Identification Number: https://doi.org/10.1007/s00382-021-06034-x
    Depositing User: Conor Murphy
    Date Deposited: 02 Nov 2023 11:33
    Journal or Publication Title: Climate Dynamics
    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

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