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.
Research article
| 
31 May 2017
Research article |
| 31 May 2017
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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- Generation and evaluation of energy and water fluxes from the HOLAPS framework: Comparison with satellite-based products during extreme hot weather A. García-García & J. Peng 10.1016/j.rse.2024.114451
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Latest update: 07 Mar 2025
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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