Articles | Volume 17, issue 5
https://doi.org/10.5194/cp-17-2031-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/cp-17-2031-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| Highlight paper
| 
08 Oct 2021
Research article | Highlight paper |
| 08 Oct 2021
| 08 Oct 2021
Statistical characteristics of extreme daily precipitation during 1501 BCE–1849 CE in the Community Earth System Model
Climate and Environmental Physics, Physics Institute, University of Bern, Bern, Switzerland
Oeschger Centre for Climate Change Research, University of Bern, Bern, Switzerland
Richard Blender
Meteorological Institute and Center for Earth System Research and Sustainability (CEN), University of Hamburg, Hamburg, Germany
Michael Sigl
Climate and Environmental Physics, Physics Institute, University of Bern, Bern, Switzerland
Oeschger Centre for Climate Change Research, University of Bern, Bern, Switzerland
Martina Messmer
Climate and Environmental Physics, Physics Institute, University of Bern, Bern, Switzerland
Oeschger Centre for Climate Change Research, University of Bern, Bern, Switzerland
Christoph C. Raible
Climate and Environmental Physics, Physics Institute, University of Bern, Bern, Switzerland
Oeschger Centre for Climate Change Research, University of Bern, Bern, Switzerland
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Gill Plunkett, Michael Sigl, Hans F. Schwaiger, Emma L. Tomlinson, Matthew Toohey, Joseph R. McConnell, Jonathan R. Pilcher, Takeshi Hasegawa, and Claus Siebe
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Martina Messmer, Santos J. González-Rojí, Christoph C. Raible, and Thomas F. Stocker
Geosci. Model Dev., 14, 2691–2711, https://doi.org/10.5194/gmd-14-2691-2021, https://doi.org/10.5194/gmd-14-2691-2021, 2021
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Woon Mi Kim and Christoph C. Raible
Clim. Past, 17, 887–911, https://doi.org/10.5194/cp-17-887-2021, https://doi.org/10.5194/cp-17-887-2021, 2021
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Peter M. Abbott, Gill Plunkett, Christophe Corona, Nathan J. Chellman, Joseph R. McConnell, John R. Pilcher, Markus Stoffel, and Michael Sigl
Clim. Past, 17, 565–585, https://doi.org/10.5194/cp-17-565-2021, https://doi.org/10.5194/cp-17-565-2021, 2021
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Jakob Zscheischler, Philippe Naveau, Olivia Martius, Sebastian Engelke, and Christoph C. Raible
Earth Syst. Dynam., 12, 1–16, https://doi.org/10.5194/esd-12-1-2021, https://doi.org/10.5194/esd-12-1-2021, 2021
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Emmanuele Russo, Silje Lund Sørland, Ingo Kirchner, Martijn Schaap, Christoph C. Raible, and Ulrich Cubasch
Geosci. Model Dev., 13, 5779–5797, https://doi.org/10.5194/gmd-13-5779-2020, https://doi.org/10.5194/gmd-13-5779-2020, 2020
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The parameter space of the COSMO-CLM RCM is investigated for the Central Asia CORDEX domain using a perturbed physics ensemble (PPE) with different parameter values. Results show that only a subset of model parameters presents relevant changes in model performance and these changes depend on the considered region and variable: objective calibration methods are highly necessary in this case. Additionally, the results suggest the need for calibrating an RCM when targeting different domains.
Dimitri Osmont, Sandra Brugger, Anina Gilgen, Helga Weber, Michael Sigl, Robin L. Modini, Christoph Schwörer, Willy Tinner, Stefan Wunderle, and Margit Schwikowski
The Cryosphere, 14, 3731–3745, https://doi.org/10.5194/tc-14-3731-2020, https://doi.org/10.5194/tc-14-3731-2020, 2020
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In this interdisciplinary case study, we were able to link biomass burning emissions from the June 2017 wildfires in Portugal to their deposition in the snowpack at Jungfraujoch, Swiss Alps. We analysed black carbon and charcoal in the snowpack, calculated backward trajectories, and monitored the fire evolution by remote sensing. Such case studies help to understand the representativity of biomass burning records in ice cores and how biomass burning tracers are archived in the snowpack.
Patricio Velasquez, Martina Messmer, and Christoph C. Raible
Geosci. Model Dev., 13, 5007–5027, https://doi.org/10.5194/gmd-13-5007-2020, https://doi.org/10.5194/gmd-13-5007-2020, 2020
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This work presents a new bias-correction method for precipitation that considers orographic characteristics, which can be used in studies where the latter strongly changes. The three-step correction method consists of a separation into orographic features, correction of low-intensity precipitation, and application of empirical quantile mapping. Seasonal bias induced by the global climate model is fully corrected. Rigorous cross-validations illustrate the method's applicability and robustness.
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Short summary
To understand the natural characteristics and future changes of the global extreme daily precipitation, it is necessary to explore the long-term characteristics of extreme daily precipitation. Here, we used climate simulations to analyze the characteristics and long-term changes of extreme precipitation during the past 3351 years. Our findings indicate that extreme precipitation in the past is associated with internal climate variability and regional surface temperatures.
To understand the natural characteristics and future changes of the global extreme daily...
