Preprints
https://doi.org/10.5194/hess-2020-595
https://doi.org/10.5194/hess-2020-595

  09 Dec 2020

09 Dec 2020

Review status: this preprint is currently under review for the journal HESS.

Robust historical evapotranspiration trends across climate regimes

Sanaa Hobeichi1,2, Gab Abramowitz1,2, and Jason Evans1,2 Sanaa Hobeichi et al.
  • 1Climate Change Research Centre, UNSW Sydney, NSW 2052, Australia
  • 2ARC Centre of Excellence for Climate Extremes, UNSW Sydney, NSW 2052, Australia

Abstract. Evapotranspiration (ET) links the hydrological, energy, and carbon cycle on the land surface. Quantifying ET and its spatiotemporal changes is also key to understanding climate extremes such as droughts, heatwaves and flooding. Regional ET estimates require reliable observationally-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 a new version of the Derived Optimal Linear Combination Evapotranspiration (DOLCE) product, with observationally constrained spatiotemporally varying uncertainty estimates, higher spatial resolution, more constituent products and extended temporal reach (1980–2018). After successful evaluation of the efficacy of these uncertainty estimates out-of-sample, we derive novel ET climatology clusters for the land surface, based on the magnitude and variability of ET at each location. 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 vast majority of the Earth's surface, show clear robust increases in ET over the recent historical period.

Sanaa Hobeichi et al.

 
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Sanaa Hobeichi et al.

Data sets

Derived Optimal Linear Combination Evapotranspiration - DOLCE v2.1 Hobeichi, Sanaa, Abramowitz, Gab, and Evans, Jason P. https://doi.org/10.25914/5f1664837ef06

Sanaa Hobeichi et al.

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Short summary
We describe version 2 of the Derived Optimal Linear Combination Evapotranspiration (DOLCE), an observation-based hybrid evapotranspiration dataset with uncertainty estimates. DOLCE V2 is monthly, available at a 0.25° resolution for 1980–2018, and covers the global land. We performed a robust analysis of trends and found that over the vast majority of the Earth's surface, ET shows clear increases over the recent historical period. There are however many regions where no trends were detected.