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  Refining multi-model projections of temperature extremes by evaluation against land–atmosphere coupling diagnostics

Sippel, S., Zscheischler, J., Mahecha, M. D., Orth, R., Reichstein, M., Vogel, M., et al. (2017). Refining multi-model projections of temperature extremes by evaluation against land–atmosphere coupling diagnostics. Earth System Dynamics, 8(2), 387-403. doi:10.5194/esd-8-387-2017.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-002B-B083-5 Version Permalink: http://hdl.handle.net/21.11116/0000-0000-EB96-E
Genre: Journal Article

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http://dx.doi.org/10.5194/esd-8-387-2017 (Publisher version)
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 Creators:
Sippel, Sebastian1, 2, Author              
Zscheischler, Jakob, Author
Mahecha, Miguel D.1, Author              
Orth, René3, Author              
Reichstein, Markus, Author              
Vogel, Martha, Author
Seneviratne, Sonia I., Author
Affiliations:
1Empirical Inference of the Earth System, Dr. Miguel D. Mahecha, Department Biogeochemical Integration, Dr. M. Reichstein, Max Planck Institute for Biogeochemistry, Max Planck Society, ou_1938312              
2IMPRS International Max Planck Research School for Global Biogeochemical Cycles, Max Planck Institute for Biogeochemistry, Max Planck Society, Hans-Knöll-Str. 10, 07745 Jena, DE, ou_1497757              
3External Organizations, ou_persistent22              

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Free keywords: Biosphere Atmosphere Change Index
 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 5 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 10 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 15 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.

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 Dates: 2017-04-122017-05-312017-05
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Method: -
 Identifiers: Other: BGC2541
DOI: 10.5194/esd-8-387-2017
 Degree: -

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Project name : BACI
Grant ID : 640176
Funding program : Horizon 2020 (H2020)
Funding organization : European Commission (EC)

Source 1

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Title: Earth System Dynamics
  Other : Earth Syst. Dyn.
Source Genre: Journal
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Publ. Info: New York : Copernicus GmbH
Pages: - Volume / Issue: 8 (2) Sequence Number: - Start / End Page: 387 - 403 Identifier: ISSN: 2190-4979
CoNE: /journals/resource/2190-4979