Robust historical evapotranspiration trends across climate regimes

Journal Article · Tue Jul 06 00:00:00 EDT 2021 · Hydrology and Earth System Sciences (Online)

DOI:https://doi.org/10.5194/hess-25-3855-2021· OSTI ID:1808463

Hobeichi, Sanaa ^[1]; Abramowitz, Gab ^[1]; Evans, Jason P. ^[1]

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1. Univ. of New South Wales, Sydney, NSW (Australia). Climate Change Research Centre; Univ. of New South Wales, Sydney, NSW (Australia). ARC Centre of Excellence for Climate Extremes

Evapotranspiration (ET) links the hydrological, energy and carbon cycles on the land surface. Quantifying ET and its spatio-temporal changes is also key to understanding climate extremes such as droughts, heatwaves and flooding. Regional ET estimates require reliable observation-based gridded ET datasets, and while many have been developed using physically based, empirically based and hybrid techniques, their efficacy, and particularly the efficacy of their uncertainty estimates, is difficult to verify. In this work, we extend the methodology used in Hobeichi et al. (2018) to derive two new versions of the Derived Optimal Linear Combination Evapotranspiration (DOLCE) product, with observationally constrained spatio-temporally varying uncertainty estimates, higher spatial resolution, more constituent products and extended temporal coverage (1980–2018). After demonstrating the efficacy of these uncertainty estimates with out-of-sample testing, we derive novel ET climatology clusters for the land surface, based on the magnitude and variability of ET at each location on land. The new clusters include three wet and three dry regimes and provide an approximation of Köppen–Geiger climate classes. The verified uncertainty estimates and extended time period then allow us to examine the robustness of historical trends spatially and in each of these six ET climatology clusters. We find that despite robust decreasing ET trends in some regions these do not correlate with behavioural ET clusters. Each cluster, and the majority of the Earth's surface, shows clear robust increases in ET over the recent historical period. The new datasets DOLCE V2.1 and DOLCE V3 can be used for benchmarking global ET estimates and for examining ET trends respectively.

• Research Organization: ARM Data Center, Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
• Sponsoring Organization: Australian Research Council; USDOE Office of Science (SC), Biological and Environmental Research (BER)
• Grant/Contract Number: AC05-76RL01830
• OSTI ID: 1808463
• Journal Information: Hydrology and Earth System Sciences (Online), Journal Name: Hydrology and Earth System Sciences (Online) Journal Issue: 7 Vol. 25; ISSN 1607-7938
• Publisher: European Geosciences Union (EGU)
• Country of Publication: United States
• Language: English

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54 ENVIRONMENTAL SCIENCES