Partitioning global land evapotranspiration using CMIP5 models constrained by observations

Xu Lian, Shilong Piao (), Chris Huntingford, Yue Li, Zhenzhong Zeng, Xuhui Wang, Philippe Ciais, Tim R. McVicar, Shushi Peng, Catherine Ottlé, Hui Yang, Yuting Yang, Yongqiang Zhang and Tao Wang
Additional contact information
Xu Lian: Peking University
Shilong Piao: Peking University
Chris Huntingford: Centre for Ecology and Hydrology
Yue Li: Peking University
Zhenzhong Zeng: Peking University
Xuhui Wang: Peking University
Philippe Ciais: Laboratoire des Sciences du Climat et de l’Environnement (LSCE), CEA CNRS UVSQ
Tim R. McVicar: CSIRO Land and Water
Shushi Peng: Peking University
Catherine Ottlé: Laboratoire des Sciences du Climat et de l’Environnement (LSCE), CEA CNRS UVSQ
Hui Yang: Peking University
Yuting Yang: Tsinghua University
Yongqiang Zhang: CSIRO Land and Water
Tao Wang: Chinese Academy of Sciences

Nature Climate Change, 2018, vol. 8, issue 7, 640-646

Abstract: Abstract The ratio of plant transpiration to total terrestrial evapotranspiration (T/ET) captures the role of vegetation in surface–atmosphere interactions. However, its magnitude remains highly uncertain at the global scale. Here we apply an emergent constraint approach that integrates CMIP5 Earth system models (ESMs) with 33 field T/ET measurements to re-estimate the global T/ET value. Our observational constraint strongly increases the original ESM estimates (0.41 ± 0.11) and greatly alleviates intermodel discrepancy, which leads to a new global T/ET estimate of 0.62 ± 0.06. For all the ESMs, the leaf area index is identified as the primary driver of spatial variations of T/ET, but to correct its bias generates a larger T/ET underestimation than the original ESM output. We present evidence that the ESM underestimation of T/ET is, instead, attributable to inaccurate representation of canopy light use, interception loss and root water uptake processes in the ESMs. These processes should be prioritized to reduce model uncertainties in the global hydrological cycle.

Date: 2018
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DOI: 10.1038/s41558-018-0207-9

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