Spatiotemporal variation of actual evapotranspiration and its response to changes of major meteorological factors over China using multi-source data

Abstract

Evapotranspiration (ET) is an important component of the water and energy cycle. To obtain more accurate actual ET estimation, three commonly used actual ET products (i.e., GLEAM, GLDAS, and SSEBop) are merged by the simple Taylor skill score fusion method. Validation results show that the merged actual ET data exhibits better correlation with eddy-covariance ET observation than single-source ET data. Based on the merged ET, the spatiotemporal variations of ET over China and their links to changes of three meteorological factors, i.e., precipitation, air temperature (Ta), and shortwave radiation (Rs), are analyzed. During 2003–2016, there is a general upward trend in ET with an increase rate of 1.6 mm/year over China. ET increases very significantly in northeastern China, the southern coastal region, and the northwestern corner of China, whereas it decreases significantly in Huang-Huai-Hai Plain. There is a clear spatial pattern of the relationship between ET and its driving factors, i.e., the variation of ET in the humid southeast is dominated by Ta and Rs; in the semi-humid and semi-arid zone, the variation of ET is controlled mainly by precipitation, followed by Ta; and in arid northwestern China, the variation of ET is controlled mainly by precipitation. HIGHLIGHTS The paper offers a feasible and effective method to merge different evapotranspiration data.; The quality assessment of merged ET and single ET product indicates the merged data is more reliable and accurate.; The Spatiotemporal variation of actual ET over China during 2003–2015 is analyzed.; The dominant meteorological factors driving changes of actual ET in different climate regions in China are identified.;

Keywords

• data merging
• evapotranspiration
• mann–kendall trend test
• meteorological factors
• partial correlation analysis
• spatiotemporal variations