Derived Optimal Linear Combination Evapotranspiration (DOLCE): a global gridded synthesis ET estimate.

Accurate global gridded estimates of evapotran- spiration (ET) are key to understanding water and energy budgets, in addition to being required for model evalua- tion. Several gridded ET products have already been de- veloped which differ in their data requirements, the ap- proaches 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 uncer- tainty with monthly temporal resolution for 2000–2009. Six existing gridded ET products are combined using a weight- ing approach trained by observational datasets from 159 FLUXNET sites. The weighting method is based on a tech- nique that provides an analytically optimal linear combina- tion of ET products compared to site data and accounts for both the performance differences and error covariance be- tween the participating ET products. We examine the perfor- mance of the weighting approach in several in-sample and out-of-sample tests that confirm that point-based estimates of flux towers provide information on the grid scale of these products. We also provide evidence that the weighted prod- uct performs better than its six constituent ET product mem- bers in four common metrics. Uncertainty in the ET estimate is derived by rescaling the spread of participating ET prod- ucts so that their spread reflects the ability of the weighted mean estimate to match flux tower data. While issues in ob- servational 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.

Figure 8. Seasonal (a) global ET and (b) its variability (SD); (c) time average of uncertainty (the SD uncertainty σe 2 shown in Eq. 11); (d) SD of uncertainty over time; and (e) reliability. DJF is shown in the left column and JJA in the right column. The global mean values in mean ET(a–d) are area weighted.