Articles | Volume 8, issue 2
https://doi.org/10.5194/esd-8-387-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/esd-8-387-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Refining multi-model projections of temperature extremes by evaluation against land–atmosphere coupling diagnostics
Max Planck Institute for Biogeochemistry, Hans-Knöll-Str. 10, 07745 Jena, Germany
Institute for Atmospheric and Climate Science, ETH Zürich, 8075 Zurich, Switzerland
Jakob Zscheischler
Institute for Atmospheric and Climate Science, ETH Zürich, 8075 Zurich, Switzerland
Miguel D. Mahecha
Max Planck Institute for Biogeochemistry, Hans-Knöll-Str. 10, 07745 Jena, Germany
Rene Orth
Institute for Atmospheric and Climate Science, ETH Zürich, 8075 Zurich, Switzerland
Markus Reichstein
Max Planck Institute for Biogeochemistry, Hans-Knöll-Str. 10, 07745 Jena, Germany
Martha Vogel
Institute for Atmospheric and Climate Science, ETH Zürich, 8075 Zurich, Switzerland
Sonia I. Seneviratne
Institute for Atmospheric and Climate Science, ETH Zürich, 8075 Zurich, Switzerland
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- Land surface model influence on the simulated climatologies of temperature and precipitation extremes in the WRF v3.9 model over North America A. García-García et al. 10.5194/gmd-13-5345-2020
- Evaluating a land surface model at a water-limited site: implications for land surface contributions to droughts and heatwaves M. Mu et al. 10.5194/hess-25-447-2021
- Coupling between the terrestrial carbon and water cycles—a review P. Gentine et al. 10.1088/1748-9326/ab22d6
- How Daily Temperature and Precipitation Distributions Evolve With Global Surface Temperature. B. Samset et al. 10.1029/2019EF001160
- A network method to analyze compound extreme events: Risk enhancement relationship and trigger causal relationship in high voice traffic and high data throughput events L. Wang et al. 10.1016/j.chaos.2024.115661
- Soil Moisture–Evapotranspiration Coupling in CMIP5 Models: Relationship with Simulated Climate and Projections A. Berg & J. Sheffield 10.1175/JCLI-D-17-0757.1
- How representative are FLUXNET measurements of surface fluxes during temperature extremes? S. van der Horst et al. 10.5194/bg-16-1829-2019
- Sensitivity of simulated climate over the MENA region related to different land surface schemes in the WRF model K. Constantinidou et al. 10.1007/s00704-020-03258-5
- Recent Progress and Emerging Topics on Weather and Climate Extremes Since the Fifth Assessment Report of the Intergovernmental Panel on Climate Change Y. Chen et al. 10.1146/annurev-environ-102017-030052
- Evaluating CMIP6 model fidelity at simulating non-Gaussian temperature distribution tails A. Catalano et al. 10.1088/1748-9326/ab8cd0
- Human contribution to the record-breaking June and July 2019 heatwaves in Western Europe R. Vautard et al. 10.1088/1748-9326/aba3d4
- The effect of univariate bias adjustment on multivariate hazard estimates J. Zscheischler et al. 10.5194/esd-10-31-2019
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- Inter-seasonal connection of typical European heatwave patterns to soil moisture E. Felsche et al. 10.1038/s41612-023-00330-5
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- Prospects and Caveats of Weighting Climate Models for Summer Maximum Temperature Projections Over North America R. Lorenz et al. 10.1029/2017JD027992
- Observational evidence of regional increasing hot extreme accelerated by surface energy partitioning R. Wang et al. 10.1175/JHM-D-21-0114.1
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- Evaluation of heat wave forecasts seamlessly across subseasonal timescales T. Ford et al. 10.1038/s41612-018-0027-7
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- Impact of Deforestation on Land–Atmosphere Coupling Strength and Climate in Southeast Asia M. Tölle 10.3390/su12156140
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- Assessing the Dynamic Versus Thermodynamic Origin of Climate Model Biases K. Wehrli et al. 10.1029/2018GL079220
- CMIP6 MultiModel Evaluation of Present‐Day Heatwave Attributes A. Hirsch et al. 10.1029/2021GL095161
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Latest update: 20 Nov 2024
Short summary
The present study (1) evaluates land–atmosphere coupling in the CMIP5 multi-model ensemble against an ensemble of benchmarking datasets and (2) refines the model ensemble using a land–atmosphere coupling diagnostic as constraint. Our study demonstrates that a considerable fraction of coupled climate models overemphasize warm-season
moisture-limitedclimate regimes in midlatitude regions. This leads to biases in daily-scale temperature extremes, which are alleviated in a constrained ensemble.
The present study (1) evaluates land–atmosphere coupling in the CMIP5 multi-model ensemble...
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