Articles | Volume 11, issue 4
https://doi.org/10.5194/esd-11-1013-2020
© Author(s) 2020. 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-11-1013-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
18 Nov 2020
Research article |
| 18 Nov 2020
| 18 Nov 2020
Comparing interannual variability in three regional single-model initial-condition large ensembles (SMILEs) over Europe
Fabian von Trentini
CORRESPONDING AUTHOR
Department of Geography, Ludwig-Maximilians-Universität, Munich,
80333, Germany
Emma E. Aalbers
Royal Netherlands Meteorological Institute (KNMI), P.O. Box 201, 3730 AE
De Bilt, the Netherlands
Institute for Environmental Studies (IVM), Vrije Universiteit,
Amsterdam, 1081 HV, the Netherlands
Erich M. Fischer
Institute for Atmospheric and Climate Science, ETH Zurich, Zurich,
8092, Switzerland
Ralf Ludwig
Department of Geography, Ludwig-Maximilians-Universität, Munich,
80333, Germany
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Cited
22 citations as recorded by crossref.
- Uncertainty separation of drought projection in the 21st century using SMILEs and CMIP6 Y. Ji et al. 10.1016/j.jhydrol.2023.130497
- Comparative Analysis and Assessment of Artic Sea Ice: Predictions from CMIP6 Models Amid Global Climate Change Z. Fan 10.54097/ajst.v8i1.14003
- Role of mean and variability change in changes in European annual and seasonal extreme precipitation events R. Wood 10.5194/esd-14-797-2023
- Future offshore wind energy evolution in the Bay of Biscay H. Ezpeleta et al. 10.1016/j.seta.2024.103776
- Internal variability and temperature scaling of future sub-daily rainfall return levels over Europe B. Poschlod & R. Ludwig 10.1088/1748-9326/ac0849
- Variability in frost occurrence under climate change and consequent risk of damage to trees of western Quebec, Canada B. Marquis et al. 10.1038/s41598-022-11105-y
- Using Large Ensembles to Identify Regions of Systematic Biases in Moderate‐to‐Heavy Daily Precipitation N. Goldenson et al. 10.1029/2020GL092026
- The inherent uncertainty of precipitation variability, trends, and extremes due to internal variability, with implications for Western US water resources K. McKinnon & C. Deser 10.1175/JCLI-D-21-0251.1
- A perfect model study on the reliability of the added small-scale information in regional climate change projections G. Lenderink et al. 10.1007/s00382-022-06451-6
- ModE-Sim – a medium-sized atmospheric general circulation model (AGCM) ensemble to study climate variability during the modern era (1420 to 2009) R. Hand et al. 10.5194/gmd-16-4853-2023
- Exploiting large ensembles for a better yet simpler climate model evaluation L. Suarez-Gutierrez et al. 10.1007/s00382-021-05821-w
- Inter-seasonal connection of typical European heatwave patterns to soil moisture E. Felsche et al. 10.1038/s41612-023-00330-5
- Climate change impacts on regional fire weather in heterogeneous landscapes of central Europe J. Miller et al. 10.5194/nhess-24-411-2024
- Large ensemble climate model simulations: introduction, overview, and future prospects for utilising multiple types of large ensemble N. Maher et al. 10.5194/esd-12-401-2021
- An extremeness threshold determines the regional response of floods to changes in rainfall extremes M. Brunner et al. 10.1038/s43247-021-00248-x
- Effects of changes in climatic means, variability, and agro-technologies on future wheat and maize yields at 10 sites across the globe G. Bracho-Mujica et al. 10.1016/j.agrformet.2024.109887
- The SMHI Large Ensemble (SMHI-LENS) with EC-Earth3.3.1 K. Wyser et al. 10.5194/gmd-14-4781-2021
- Vulnerability of ski tourism towards internal climate variability and climate change in the Swiss Alps F. Willibald et al. 10.1016/j.scitotenv.2021.147054
- Applying machine learning for drought prediction in a perfect model framework using data from a large ensemble of climate simulations E. Felsche & R. Ludwig 10.5194/nhess-21-3679-2021
- Quantifying the Role of Model Internal Year-to-Year Variability in Estimating Anthropogenic Aerosol Radiative Effects X. Shi & Y. Zeng 10.3390/atmos15010079
- Consistency of Seasonal Mean and Extreme Precipitation Projections Over Europe Across a Range of Climate Model Ensembles N. Ritzhaupt & D. Maraun 10.1029/2022JD037845
- Reliability of simulating internal precipitation variability over multi‐timescales using multiple global climate model large ensembles in China J. Liu et al. 10.1002/joc.8210
22 citations as recorded by crossref.
- Uncertainty separation of drought projection in the 21st century using SMILEs and CMIP6 Y. Ji et al. 10.1016/j.jhydrol.2023.130497
- Comparative Analysis and Assessment of Artic Sea Ice: Predictions from CMIP6 Models Amid Global Climate Change Z. Fan 10.54097/ajst.v8i1.14003
- Role of mean and variability change in changes in European annual and seasonal extreme precipitation events R. Wood 10.5194/esd-14-797-2023
- Future offshore wind energy evolution in the Bay of Biscay H. Ezpeleta et al. 10.1016/j.seta.2024.103776
- Internal variability and temperature scaling of future sub-daily rainfall return levels over Europe B. Poschlod & R. Ludwig 10.1088/1748-9326/ac0849
- Variability in frost occurrence under climate change and consequent risk of damage to trees of western Quebec, Canada B. Marquis et al. 10.1038/s41598-022-11105-y
- Using Large Ensembles to Identify Regions of Systematic Biases in Moderate‐to‐Heavy Daily Precipitation N. Goldenson et al. 10.1029/2020GL092026
- The inherent uncertainty of precipitation variability, trends, and extremes due to internal variability, with implications for Western US water resources K. McKinnon & C. Deser 10.1175/JCLI-D-21-0251.1
- A perfect model study on the reliability of the added small-scale information in regional climate change projections G. Lenderink et al. 10.1007/s00382-022-06451-6
- ModE-Sim – a medium-sized atmospheric general circulation model (AGCM) ensemble to study climate variability during the modern era (1420 to 2009) R. Hand et al. 10.5194/gmd-16-4853-2023
- Exploiting large ensembles for a better yet simpler climate model evaluation L. Suarez-Gutierrez et al. 10.1007/s00382-021-05821-w
- Inter-seasonal connection of typical European heatwave patterns to soil moisture E. Felsche et al. 10.1038/s41612-023-00330-5
- Climate change impacts on regional fire weather in heterogeneous landscapes of central Europe J. Miller et al. 10.5194/nhess-24-411-2024
- Large ensemble climate model simulations: introduction, overview, and future prospects for utilising multiple types of large ensemble N. Maher et al. 10.5194/esd-12-401-2021
- An extremeness threshold determines the regional response of floods to changes in rainfall extremes M. Brunner et al. 10.1038/s43247-021-00248-x
- Effects of changes in climatic means, variability, and agro-technologies on future wheat and maize yields at 10 sites across the globe G. Bracho-Mujica et al. 10.1016/j.agrformet.2024.109887
- The SMHI Large Ensemble (SMHI-LENS) with EC-Earth3.3.1 K. Wyser et al. 10.5194/gmd-14-4781-2021
- Vulnerability of ski tourism towards internal climate variability and climate change in the Swiss Alps F. Willibald et al. 10.1016/j.scitotenv.2021.147054
- Applying machine learning for drought prediction in a perfect model framework using data from a large ensemble of climate simulations E. Felsche & R. Ludwig 10.5194/nhess-21-3679-2021
- Quantifying the Role of Model Internal Year-to-Year Variability in Estimating Anthropogenic Aerosol Radiative Effects X. Shi & Y. Zeng 10.3390/atmos15010079
- Consistency of Seasonal Mean and Extreme Precipitation Projections Over Europe Across a Range of Climate Model Ensembles N. Ritzhaupt & D. Maraun 10.1029/2022JD037845
- Reliability of simulating internal precipitation variability over multi‐timescales using multiple global climate model large ensembles in China J. Liu et al. 10.1002/joc.8210
Latest update: 26 Apr 2024
Short summary
We compare the inter-annual variability of three single-model initial-condition large ensembles (SMILEs), downscaled with three regional climate models over Europe for seasonal temperature and precipitation, the number of heatwaves, and maximum length of dry periods. They all show good consistency with observational data. The magnitude of variability and the future development are similar in many cases. In general, variability increases for summer indicators and decreases for winter indicators.
We compare the inter-annual variability of three single-model initial-condition large ensembles...
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