Articles | Volume 14, issue 1
https://doi.org/10.5194/esd-14-81-2023
https://doi.org/10.5194/esd-14-81-2023
Research article
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26 Jan 2023
Research article | Highlight paper |  | 26 Jan 2023

Robust global detection of forced changes in mean and extreme precipitation despite observational disagreement on the magnitude of change

Iris Elisabeth de Vries, Sebastian Sippel, Angeline Greene Pendergrass, and Reto Knutti

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Cited articles

Allan, R. P., Liu, C., Zahn, M., Lavers, D. A., Koukouvagias, E., and Bodas-Salcedo, A.: Physically consistent responses of the global atmospheric hydrological cycle in models and observations, Surv. Geophys., 35, 533–552, https://doi.org/10.1007/s10712-012-9213-z, 2014. a
Allen, M. R. and Ingram, W. J.: Constraints on future changes in climate and the hydrologic cycle, Nature, 419, 228–232, https://doi.org/10.1038/nature01092, 2002. a
Allen, M. R. and Stott, P. A.: Estimating the signal amplitudes in optimal fingerprinting, Part I: Theory, Clim. Dynam., 21, 477–491, 2003. a
Avila, F. B., Dong, S., Menang, K. P., Rajczak, J., Renom, M., Donat, M. G., and Alexander, L. V.: Systematic investigation of gridding-related scaling effects on annual statistics of daily temperature and precipitation maxima: A case study for south-east Australia, Weather and Climate Extremes, 9, 6–16, https://doi.org/10.1016/j.wace.2015.06.003, 2015. a
Balan Sarojini, B., Stott, P. A., Black, E., and Polson, D.: Fingerprints of changes in annual and seasonal precipitation from CMIP5 models over land and ocean, Geophys. Res. Lett., 39, L21706, https://doi.org/10.1029/2012GL053373, 2012. a, b
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Chief editor
Detecting and attributing forced precipitation changes is a long-standing challenge in climate science. This study proposes an approach to efficiently extract information on forced precipitation changes from climate data and models, which can be valuable both from a scientific and policy-making perspective.
Short summary
Precipitation change is an important consequence of climate change, but it is hard to detect and quantify. Our intuitive method yields robust and interpretable detection of forced precipitation change in three observational datasets for global mean and extreme precipitation, but the different observational datasets show different magnitudes of forced change. Assessment and reduction of uncertainties surrounding forced precipitation change are important for future projections and adaptation.
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