1. Evaluation of global terrestrial evapotranspiration using state-of-the-art approaches in remote sensing, machine learning and land surface modeling
- Author
-
Danica Lombardozzi, Hanqin Tian, Sebastian Lienert, Atul K. Jain, Etsushi Kato, Steven W. Running, Naiqing Pan, Julia E. M. S. Nabel, Pierre Friedlingstein, Catherine Ottlé, Hao Shi, Benjamin Poulter, Stephen Sitch, Sönke Zaehle, Vivek K. Arora, Vanessa Haverd, Shufen Pan, Auburn University (AU), College of Engineering, Mathematics and Physical Sciences [Exeter] (EMPS), University of Exeter, College of Life and Environmental Sciences [Exeter], Canadian Centre for Climate Modelling and Analysis (CCCma), Environment and Climate Change Canada, CSIRO Marine and Atmospheric Research [Aspendale], Commonwealth Scientific and Industrial Research Organisation [Canberra] (CSIRO), Department of Atmospheric Sciences [Urbana], University of Illinois at Urbana-Champaign [Urbana], University of Illinois System-University of Illinois System, Tokyo Institute of Technology [Tokyo] (TITECH), Climate and Environmental Physics [Bern] (CEP), Physikalisches Institut [Bern], Universität Bern [Bern]-Universität Bern [Bern], National Center for Atmospheric Research [Boulder] (NCAR), Max Planck Institute for Meteorology (MPI-M), Max-Planck-Gesellschaft, Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Modélisation des Surfaces et Interfaces Continentales (MOSAIC), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), NASA Goddard Space Flight Center (GSFC), Biogeochemical Systems Department [Jena], Max Planck Institute for Biogeochemistry (MPI-BGC), Max-Planck-Gesellschaft-Max-Planck-Gesellschaft, Montana State University (MSU), Universität Bern [Bern] (UNIBE)-Universität Bern [Bern] (UNIBE), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), and Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)
- Subjects
Canopy ,010504 meteorology & atmospheric sciences ,530 Physics ,0208 environmental biotechnology ,02 engineering and technology ,lcsh:Technology ,01 natural sciences ,lcsh:TD1-1066 ,Evapotranspiration ,lcsh:Environmental technology. Sanitary engineering ,[SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment ,lcsh:Environmental sciences ,0105 earth and related environmental sciences ,General Environmental Science ,lcsh:GE1-350 ,[SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere ,Physical model ,lcsh:T ,Water stress ,lcsh:Geography. Anthropology. Recreation ,15. Life on land ,Arid ,Relative stability ,020801 environmental engineering ,lcsh:G ,13. Climate action ,Remote sensing (archaeology) ,Climatology ,General Earth and Planetary Sciences ,Environmental science ,Satellite - Abstract
Evapotranspiration (ET) is a critical component in global water cycle and links terrestrial water, carbon and energy cycles. Accurate estimate of terrestrial ET is important for hydrological, meteorological, and agricultural research and applications, such as quantifying surface energy and water budgets, weather forecasting, and scheduling of irrigation. However, direct measurement of global terrestrial ET is not feasible. Here, we first gave a retrospective introduction to the basic theory and recent developments of state-of-the-art approaches for estimating global terrestrial ET, including remote sensing-based physical models, machine learning algorithms and land surface models (LSMs). Then, we utilized six remote sensing-based models (including four physical models and two machine learning algorithms) and fourteen LSMs to analyze the spatial and temporal variations in global terrestrial ET. The results showed that the mean annual global terrestrial ET ranged from 50.7 × 103 km3 yr−1(454 mm yr−1)to 75.7 × 103 km3 yr−1 (6977 mm yr−1), with the average being 65.5 × 103 km3 yr−1 (588 mm yr−1), during 1982–2011. LSMs had significant uncertainty in the ET magnitude in tropical regions especially the Amazon Basin, while remote sensing-based ET products showed larger inter-model range in arid and semi-arid regions than LSMs. LSMs and remote sensing-based physical models presented much larger inter-annual variability (IAV) of ET than machine learning algorithms in southwestern U.S. and the Southern Hemisphere, particularly in Australia. LSMs suggested stronger control of precipitation on ET IAV than remote sensing-based models. The ensemble remote sensing-based physical models and machine-learning algorithm suggested significant increasing trends in global terrestrial ET at the rate of 0.62 mm yr−2 (p 0.05), even though most of the individual LSMs reproduced the increasing trend. Moreover, all models suggested a positive effect of vegetation greening on ET intensification. Spatially, all methods showed that ET significantly increased in western and southern Africa, western India and northeastern Australia, but decreased severely in southwestern U.S., southern South America and Mongolia. Discrepancies in ET trend mainly appeared in tropical regions like the Amazon Basin. The ensemble means of the three ET categories showed generally good consistency, however, considerable uncertainties still exist in both the temporal and spatial variations in global ET estimates. The uncertainties were induced by multiple factors, including parameterization of land processes, meteorological forcing, lack of in situ measurements, remote sensing acquisition and scaling effects. Improvements in the representation of water stress and canopy dynamics are essentially needed to reduce uncertainty in LSM-simulated ET. Utilization of latest satellite sensors and deep learning methods, theoretical advancements in nonequilibrium thermodynamics, and application of integrated methods that fuse different ET estimates or relevant key biophysical variables will improve the accuracy of remote sensing-based models.
- Published
- 2020