Assessing the Robustness of Future Extreme Precipitation Intensification in the CMIP5 Ensemble

Author:

Bador Margot1,Donat Markus G.1,Geoffroy Olivier2,Alexander Lisa V.1

Affiliation:

1. Climate Change Research Centre, School of BEES, and Australian Research Council’s Centre of Excellence for Climate System Science, University of New South Wales, Sydney, New South Wales, Australia

2. Climate Change Research Centre, School of BEES, University of New South Wales, Sydney, New South Wales, Australia, and Centre National de Recherches Météorologiques, Météo-France/CNRS, Toulouse, France

Abstract

Abstract A warming climate is expected to intensify extreme precipitation, and climate models project a general intensification of annual extreme precipitation in most regions of the globe throughout the twenty-first century. We investigate the robustness of this future intensification over land across different models, regions, and seasons and evaluate the role of model interdependencies in the CMIP5 ensemble. Strong similarities in extreme precipitation changes are found between models that share atmospheric physics, turning an ensemble of 27 models into around 14 projections. We find that future annual extreme precipitation intensity increases in the majority of models and in the majority of land grid cells, from the driest to the wettest regions, as defined by each model’s precipitation climatology. The intermodel spread is generally larger over wet than over dry regions, smaller in the dry season compared to the wet season and at the annual scale, and largely reduced in extratropical compared to tropical regions and at the global scale. For each model, the future increase in annual and seasonal maximum daily precipitation amounts exceeds the range of simulated internal variability in the majority of land grid cells. At both annual and seasonal scales, however, there are a few regions where the change is still within the background climate noise, but their size and location differ between models. In extratropical regions, the signal-to-noise ratio of projected changes in extreme precipitation is particularly robust across models because of a similar change and background climate noise, whereas projected changes are less robust in the tropics.

Funder

Australian Research Council

Australian Research Council Centre of Excellence for Climate System Science

Publisher

American Meteorological Society

Subject

Atmospheric Science

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