EGU2020-13321
https://doi.org/10.5194/egusphere-egu2020-13321
EGU General Assembly 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Reconciling global projections of precipitation with CMIP6 and CMIP5 multi-model trends

Ralph Trancoso and Jozef Syktus
Ralph Trancoso and Jozef Syktus
  • School of Biological Sciences, University of Queensland, Brisbane, Australia (r.trancoso@uq.edu.au)

Changing precipitation patterns due to climate change is a critical concern affecting society and the environment. Projected changes in global seasonal precipitation are largely heterogeneous in space, time, magnitude and direction. Therefore, reconciling projected future precipitation is pivotal for climate change science and adaptation and mitigation schemes.

This research contributes to disentangle future precipitation uncertainty globally by exploring long-term trends in projected seasonal precipitation of 33 CMIP5 and 16 CMIP6 models for the period 1980-2100. We first estimate trend slopes and significance in long-term future seasonal precipitation using the Sen-Slope and Mann-Kendall tests and constrain trends with at least 10% of cumulative changes over the 120-year period. Then, we assess convergence in the direction of trends across seasons. We highlight the world’s jurisdictions with consistent drying and wetting patterns as well as the seasonal dominance of precipitation trends.

A consistent drying pattern – where at least 78% of GCMs have decreasing precipitation trends – was observed in Central America, South and North Africa, South Europe, Southern USA and Southern South America. Unlike, a strong convergence in projected long-term wetness – where at least 78% of GCMs have increasing precipitation trends – was observed across most of Asia, Central Africa, Northern Europe, Canada, Northern US and South Brazil and surrounds.

Results show convergence in direction of seasonal precipitation trends revealing the world’s jurisdictions more likely to experience changes in future precipitation patterns. The approach is promisor to summarize trends in seasonal time-series from multiple GCMs and better constrain wetting and drying precipitation patterns. This study provides meaningful insights to inform water resource management and climate change adaptation globally.

How to cite: Trancoso, R. and Syktus, J.: Reconciling global projections of precipitation with CMIP6 and CMIP5 multi-model trends, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13321, https://doi.org/10.5194/egusphere-egu2020-13321, 2020

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Presentation version 1 – uploaded on 05 May 2020
  • AC1: Comment on EGU2020-13321, Ralph Trancoso, 05 May 2020

    Quick update:

    1) We ended up using 31 CMIP5 and 19 CMIP6 models.

    2) Due to space limitation we only show results for annual precipitation convergence on our poster/slide. If you are interested in the seasonal dominance, get in touch with us.

    3) If you have any querry about our research or would like to interact with us, please do get in touch: r.trancoso@uq.edu.au

    Kind regards,

    Ralph Trancoso

     

  • CC1: Comment on EGU2020-13321, Jennifer Catto, 08 May 2020

    Hi Ralph,

    Thank you for your presentation. Could you explain a little bit more about how your maps showing the multi-model wetting/drying convergence are calculated (bottom left figure)? Have the models been grouped depending on their trends? And do you calculate the long-term trends over globally averaged data or at every grid point?

    Many thanks, Jennifer.

    • AC2: Reply to CC1, Ralph Trancoso, 08 May 2020

      Hi Jennifer,

      Thanks for your question.

      The figure shows the frequency of models with a robust long-term drying or wetting signal. Models/grid cells were assessed individually on our ensemble of 50 models, we did not use ensemble averages. In order to be classified as a robust long-term drying or wetting signal, each model/grid-cell must meet two conditions: (i) have statistically significant trends detected (Mann-Kendall test); and (ii) the cumulative trend (Theil Sen slope) over the 120-year period must change the rainfall regime by at least 10%.

      What are your thoughts on this?

      Cheers, Ralph

  • CC2: Comment on EGU2020-13321, Jennifer Catto, 12 May 2020

    Thank you very much it is clear now. What are your plans for this work?

    Jennifer