Synthesis of global actual evapotranspiration from 1982 to 2019

Abstract

Abstract. As a linkage among water, energy, and carbon cycles, global actual evapotranspiration (ET) plays an essential role in agriculture, water resource management, and climate change. Although it is difficult to estimate ET over a large scale and for a long time, there are several global ET datasets available with uncertainty associated with various assumptions regarding their algorithms, parameters, and inputs. In this study, we propose a long-term synthesized ET product at a kilometer spatial resolution and monthly temporal resolution from 1982 to 2019. Through a site-pixel evaluation of 12 global ET products over different time periods, land surface types, and conditions, the high-performing products were selected for the synthesis of the new dataset using a high-quality flux eddy covariance (EC) covering the entire globe. According to the study results, Penman–Monteith–Leuning (PML), the operational Simplified Surface Energy Balance (SSEBop), the Moderate Resolution Imaging Spectroradiometer (MODIS, MOD16A2105), and the Numerical Terradynamic Simulation Group (NTSG) ET products were chosen to create the synthesized ET set. The proposed product agreed well with flux EC ET over most of the all comparison levels, with a maximum relative mean error (RME) of 13.94 mm (17.13 %) and a maximum relative root mean square error (RRMSE) of 38.61 mm (47.45 %). Furthermore, the product performed better than local ET products over China, the United States, and the African continent and presented an ET estimation across all land cover classes. While no product can perform best in all cases, the proposed ET can be used without looking at other datasets and performing further assessments. Data are available on the Harvard Dataverse public repository through the following Digital Object Identifier (DOI): https://doi.org/10.7910/DVN/ZGOUED (Elnashar et al., 2020), as well as on the Google Earth Engine (GEE) application through this link: https://elnashar.users.earthengine.app/view/synthesizedet (last access: 21 January 2021).

Evapotranspiration Changes over the European Alps: Consistency of Trends and Their Drivers between the MOD16 and SSEBop Algorithms

“…The comparison with latent heat flux measured at eddy flux towers suggested that the two globally available ET products, MOD16 and SSEBop, both based on MODIS satellite data, perform similarly in the Alps. In contrast to studies indicating that SSEBop is generally more reliable than MOD16 [25], MOD16 exhibited a slightly better agreement with observed data in terms of mean daily RMSE and MBD, probably because the spatial resolution plays a crucial role in heterogenous mountain regions. It is reasonable to assume that a MOD16 spatial resolution of 500 m captures the heterogeneity of Alpine vegetation better than the SSEBop spatial resolution of 1 km.…”

“…Both ET products seem to be a good compromise in terms of physical robustness of the retrieval algorithm, applicability to large areas, spatial resolution (500 m × 500 m for MOD16 and 1 km × 1 km for SSEBop), length of the timeseries (almost 20 years), and temporal resolution (8 days for MOD16 and 10 days for SSEBop). The literature shows that MOD16 and SSEBop ET have comparable accuracy, with different performances according to climatic region [25,26]. MOD16 has been validated against several AmeriFlux (https: //ameriflux.lbl.gov/, last accessed on 29 April 2021) eddy flux tower sites, spanning different land cover types and climatic conditions, with a mean absolute error of daily ET between 0.01 and 0.66 (mm day −1 ) and root mean square error between 0.58 and 1.49 (mm day −1 ) [27].…”

Synthesizing a Regional Territorial Evapotranspiration Dataset for Northern China

“…Table 5. The simple mean of the selected three ET products and the global synthesis ET product generated by Elnashar et al [94,95], and the weighted mean results in this research (from 1982 to 2002, in mm) with corresponding bias to precipitation (in %) from 1982 to 2002 in Heihe River Basin. From Figure 16, it can be inferred that the simple mean and weighted mean of the three selected ET products generally outperformed the global synthesis ET product from 2003 to 2017.…”

“…Figure 16. Count of cells and corresponding percentages of the simple mean of the selected three ET products and the global synthesis ET product generated by Elnashar et al [94,95]. The weighted mean results in this research with level-1 and level-2 assessment and the total count of cells and their corresponding percentages are shown here.…”

“…Then, the weighted mean was treated as the synthesis result. Recently, Elnashar et al [94,95] generated a global synthesis ET product using a simple mean method with an assessment scheme that considered six indicators under 26 conditions. The simple mean of the selected ET products in this research and the aforementioned global synthesis ET product, together with the TSS-based weighted mean results, were assessed with the assessment sheet method using the validation dataset (from 2003 to 2017) and water balance method in Heihe River Basin (from 1982 to 2002), as mentioned in Section 4.4, and the results are as follows (Figure 16 and Table 5).…”