Revisiting the contribution of transpiration to global terrestrial evapotranspiration

• Published in: Geophysical research letters Vol. 44; no. 6; pp. 2792 - 2801
• Main Authors: Wei, Zhongwang, Yoshimura, Kei, Wang, Lixin, Miralles, Diego G., Jasechko, Scott, Lee, Xuhui
• Format: Journal Article
• Language: English
• Published: Washington John Wiley & Sons, Inc 28.03.2017
• Subjects: Algorithms; Balances (scales); Carbon dioxide; Carbon dioxide flux; Climate models; Computer simulation; Ecological monitoring; ET partitioning algorithm; Evaporation; Evapotranspiration; Evapotranspiration estimates; Geophysics; Global climate; Global climate models; Hydrologic analysis; Hydrologic cycle; Hydrologic models; Hydrology; Interception; Land; Leaf area; Leaf area index; Leaves; Measurement techniques; Numerical simulations; Partitioning; Remote sensing; site measurements; Soil; Soil water; Transpiration
• ISSN: 0094-8276; 1944-8007
• DOI: 10.1002/2016GL072235

Even though knowing the contributions of transpiration (T), soil and open water evaporation (E), and interception (I) to terrestrial evapotranspiration (ET = T + E + I) is crucial for understanding the hydrological cycle and its connection to ecological processes, the fraction of T is unattainable by traditional measurement techniques over large scales. Previously reported global mean T/(E + T + I) from multiple independent sources, including satellite‐based estimations, reanalysis, land surface models, and isotopic measurements, varies substantially from 24% to 90%. Here we develop a new ET partitioning algorithm, which combines global evapotranspiration estimates and relationships between leaf area index (LAI) and T/(E + T) for different vegetation types, to upscale a wide range of published site‐scale measurements. We show that transpiration accounts for about 57.2% (with standard deviation ± 6.8%) of global terrestrial ET. Our approach bridges the scale gap between site measurements and global model simulations,and can be simply implemented into current global climate models to improve biological CO2 flux simulations. Key Points We develop an ET partitioning method, by combining remote sensing, land surface model, and LAI regression obtained from in situ measurements We show that transpiration accounts for about 57.2% (with standard deviation ± 6.8%) of global terrestrial ET Uncertainty in canopy interception loss estimation is the largest source of bias in ET partitioning