Articles | Volume 14, issue 1
https://doi.org/10.5194/esd-14-81-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/esd-14-81-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| Highlight paper
| 
26 Jan 2023
Research article | Highlight paper |
| 26 Jan 2023
| 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
CORRESPONDING AUTHOR
Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland
Sebastian Sippel
Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland
Angeline Greene Pendergrass
Earth and Atmospheric Sciences, Cornell University, Ithaca, NY, USA
National Center for Atmospheric Research, Boulder, CO, USA
Reto Knutti
Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland
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Total article views: 6,392 (including HTML, PDF, and XML)
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Cited
18 citations as recorded by crossref.
- Robust global detection of forced changes in mean and extreme precipitation despite observational disagreement on the magnitude of change I. de Vries et al.
- Identifying climate models based on their daily output using machine learning L. Brunner & S. Sippel
- Assessment of solar geoengineering impact on precipitation and temperature extremes in the Muda River Basin, Malaysia using CMIP6 SSP and GeoMIP6 G6 simulations M. Tan et al.
- Detecting anthropogenically induced changes in extreme and seasonal evapotranspiration observations M. Egli et al.
- Framework for global emulation of extreme precipitation along global warming trajectories L. Pierini et al.
- Increasing hourly heavy rainfall in Austria reflected in flood changes K. Haslinger et al.
- Climate damage projections beyond annual temperature P. Waidelich et al.
- Bayesian estimates for changes of the Russian river runoff in the 21st century as based on the CMIP6 model ensemble simulations А. Medvedev et al.
- Extreme precipitation projections in Asian subregions: Review on CMIP6 development, geographic patterns, and research gaps A. Tandon et al.
- Assessing Latent and Kinetic Energy Trend Changes in Extratropical Cyclones From 1940 to 2020: Results From ERA‐5 Reanalysis A. Dzambo et al.
- Bayesian Estimates of Changes in Russian River Runoff in the 21st Century Based on the CMIP6 Ensemble Model Simulations A. Medvedev et al.
- Detectable Human Influence on Reduced Day‐to‐Day Temperature Variability in the Cold Season Driven by Arctic Sea‐Ice Loss P. Siew et al.
- Applying global warming levels of emergence to highlight the increasing population exposure to temperature and precipitation extremes D. Gampe et al.
- Dynamical adjustment reveals spatial patterns of wetting and drying in European winter precipitation J. Carruthers et al.
- Artificial intelligence for modeling and understanding extreme weather and climate events G. Camps-Valls et al.
- Precipitation disaster hotspots depend on historical climate variability I. de Vries et al.
- Faster than expected drying in western Europe: mechanisms, attribution and implications H. Douville
- Performance of regional climate model RegCM4 with a hydrostatic or non‐hydrostatic dynamic core at simulating precipitation extremes in China P. Qin et al.
18 citations as recorded by crossref.
- Robust global detection of forced changes in mean and extreme precipitation despite observational disagreement on the magnitude of change I. de Vries et al.
- Identifying climate models based on their daily output using machine learning L. Brunner & S. Sippel
- Assessment of solar geoengineering impact on precipitation and temperature extremes in the Muda River Basin, Malaysia using CMIP6 SSP and GeoMIP6 G6 simulations M. Tan et al.
- Detecting anthropogenically induced changes in extreme and seasonal evapotranspiration observations M. Egli et al.
- Framework for global emulation of extreme precipitation along global warming trajectories L. Pierini et al.
- Increasing hourly heavy rainfall in Austria reflected in flood changes K. Haslinger et al.
- Climate damage projections beyond annual temperature P. Waidelich et al.
- Bayesian estimates for changes of the Russian river runoff in the 21st century as based on the CMIP6 model ensemble simulations А. Medvedev et al.
- Extreme precipitation projections in Asian subregions: Review on CMIP6 development, geographic patterns, and research gaps A. Tandon et al.
- Assessing Latent and Kinetic Energy Trend Changes in Extratropical Cyclones From 1940 to 2020: Results From ERA‐5 Reanalysis A. Dzambo et al.
- Bayesian Estimates of Changes in Russian River Runoff in the 21st Century Based on the CMIP6 Ensemble Model Simulations A. Medvedev et al.
- Detectable Human Influence on Reduced Day‐to‐Day Temperature Variability in the Cold Season Driven by Arctic Sea‐Ice Loss P. Siew et al.
- Applying global warming levels of emergence to highlight the increasing population exposure to temperature and precipitation extremes D. Gampe et al.
- Dynamical adjustment reveals spatial patterns of wetting and drying in European winter precipitation J. Carruthers et al.
- Artificial intelligence for modeling and understanding extreme weather and climate events G. Camps-Valls et al.
- Precipitation disaster hotspots depend on historical climate variability I. de Vries et al.
- Faster than expected drying in western Europe: mechanisms, attribution and implications H. Douville
- Performance of regional climate model RegCM4 with a hydrostatic or non‐hydrostatic dynamic core at simulating precipitation extremes in China P. Qin et al.
Saved (final revised paper)
Latest update: 06 May 2026
Editorial statement
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.
Detecting and attributing forced precipitation changes is a long-standing challenge in climate...
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.
Precipitation change is an important consequence of climate change, but it is hard to detect and...
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