Impact of the representation of stomatal conductance on model projections of heatwave intensity

Jatin Kala*, Martin G. De Kauwe, Andy J. Pitman, Belinda E. Medlyn, Ying Ping Wang, Ruth Lorenz, Sarah E. Perkins-Kirkpatrick

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

46 Citations (Scopus)

Abstract

Stomatal conductance links plant water use and carbon uptake, and is a critical process for the land surface component of climate models. However, stomatal conductance schemes commonly assume that all vegetation with the same photosynthetic pathway use identical plant water use strategies whereas observations indicate otherwise. Here, we implement a new stomatal scheme derived from optimal stomatal theory and constrained by a recent global synthesis of stomatal conductance measurements from 314 species, across 56 field sites. Using this new stomatal scheme, within a global climate model, subtantially increases the intensity of future heatwaves across Northern Eurasia. This indicates that our climate model has previously been under-predicting heatwave intensity. Our results have widespread implications for other climate models, many of which do not account for differences in stomatal water-use across different plant functional types, and hence, are also likely under projecting heatwave intensity in the future.

Original languageEnglish
Article number23418
JournalScientific Reports
Volume6
DOIs
Publication statusPublished - 21 Mar 2016

Bibliographical note

Funding Information:
This work was supported by the Australian Research Council Centre of Excellence for Climate System Science (CE110001028). S. E. P.-K. is supported by an Australian Research Council Discovery Early Career Researcher Award (DE140100952). We thank the National Computational Infrastructure at the Australian National University, an initiative of the Australian Government, for access to supercomputer resources; the Commonwealth Scientific and Industrial Research Organisation and the Bureau of Meteorology for their support in the use of the CABLE and ACCESS models; and, David Fuchs for assisting with Python scripting. All this assistance is gratefully acknowleged.

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