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Earth System Dynamics An interactive open-access journal of the European Geosciences Union

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© Author(s) 2016. This work is distributed
under the Creative Commons Attribution 3.0 License.
Research article
27 Oct 2016
Review status
A revision of this discussion paper was accepted for the journal Earth System Dynamics (ESD) and is expected to appear here in due course.
Refining multi-model projections of temperature extremes by evaluation against land–atmosphere coupling diagnostics
Sebastian Sippel1,2, Jakob Zscheischler2, Miguel D. Mahecha1, Rene Orth2, Markus Reichstein1, Martha Vogel2, and Sonia I. Seneviratne2 1Max Planck Institute for Biogeochemistry, Hans-Knöll-Str. 10, 07745 Jena, Germany
2Institute for Atmospheric and Climate Science, ETH Zürich, 8075 Zürich, Switzerland
Abstract. The Earth's land surface and the atmosphere are strongly interlinked through the exchange of energy and matter (e.g. water and carbon). This coupled behaviour causes various land–atmosphere feedbacks and an insufficient understanding of these feedbacks contributes to uncertain global climate model projections. For example, a crucial role of the land surface in exacerbating summer heat waves in mid-latitude regions has been identified empirically for high-impact heatwaves, but individual climate models differ widely in their respective representation of land-atmosphere coupling. Here, we combine an ensemble of observations-based and simulated temperature (T) and evapotranspiration (ET) datasets and investigate coincidences of T anomalies with ET anomalies as a proxy for land-atmosphere interactions during periods of anomalously warm temperatures. We demonstrate that a relatively large fraction of state-of-the-art climate models from the Coupled Model Intercomparison Project (CMIP5) archive produces systematically too frequent coincidences of high T anomalies with negative ET anomalies in mid-latitude regions during the warm season and in several tropical regions year-round. Further, we show that these coincidences (high T, low ET), as diagnosed by the land-coupling coincidence metrics, are closely related to the variability and extremes of simulated temperatures across a multi-model ensemble. Thus, our approach offers a physically consistent, diagnostic-based avenue to evaluate these ensembles, and subsequently reduce model biases in simulated and predicted extreme temperatures. Following this idea, we derive a land-coupling constraint based on the spread of 54 combinations of T-ET benchmarking datasets and consequently retain only a subset of CMIP5 models that produce a land-coupling behaviour that is compatible with these observations-based benchmark estimates. The constrained multi-model projections exhibit lower temperature extremes in regions where models show substantial spread in T-ET coupling, and in addition, biases in the climate model ensemble are consistently reduced.

Citation: Sippel, S., Zscheischler, J., Mahecha, M. D., Orth, R., Reichstein, M., Vogel, M., and Seneviratne, S. I.: Refining multi-model projections of temperature extremes by evaluation against land–atmosphere coupling diagnostics, Earth Syst. Dynam. Discuss., doi:10.5194/esd-2016-48, in review, 2016.
Sebastian Sippel et al.
Sebastian Sippel et al.
Sebastian Sippel et al.


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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 overemphasise warm-season "moisture-limited" climate regimes in mid-latitude 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...