Journal cover Journal topic
Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
https://doi.org/10.5194/hess-2017-147
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
Research article
03 Apr 2017
Review status
This discussion paper is a preprint. A revision of the manuscript is under review for the journal Hydrology and Earth System Sciences (HESS).
Derived Optimal Linear Combination Evapotranspiration (DOLCE): a global gridded synthesis ET estimate
Sanaa Hobeichi1,2, Gabriel Abramowitz1,2, Jason Evans1, and Anna Ukkola2 1Climate Change Research Centre, University of New South Wales, Sydney, NSW 2052, Australia
2ARC Centre of Excellence for Climate System Science, University of New South Wales, Sydney, NSW 2052, Australia
Abstract. Accurate global gridded estimates of evapotranspiration (ET) are key to understanding water and energy budgets, as well as being required for model evaluation. Several gridded ET products have already been developed which differ in their data requirements, the approaches used to derive them and their estimates, yet it is not clear which provides the most reliable estimates. This paper presents a new global ET dataset and associated uncertainty with monthly temporal resolution for 2000–2009. Six existing gridded ET products are combined using a weighting approach trained by observational datasets from 159 FLUXNET sites. The weighting method is based on a technique that provides an analytically optimal linear combination of ET products compared to site data, and accounts for both the performance differences and error covariance between the participating ET products. We examine the performance of the weighting approach in several in-sample and out-of-sample tests that confirm that point-based estimates of flux towers provide information at the grid scale of these products. We also provide evidence that the weighted product performs better than its six constituent ET product members in three common metrics. Uncertainty in the ET estimate is derived by rescaling the spread of participating ET products so that their spread reflects the ability of the weighted mean estimate to match flux tower data. While issues in observational data and any common biases in participating ET datasets are limitations to the success of this approach, future datasets can easily be incorporated and enhance the derived product.

Citation: Hobeichi, S., Abramowitz, G., Evans, J., and Ukkola, A.: Derived Optimal Linear Combination Evapotranspiration (DOLCE): a global gridded synthesis ET estimate, Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2017-147, in review, 2017.
Sanaa Hobeichi et al.
Sanaa Hobeichi et al.
Sanaa Hobeichi et al.

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