Temporal Characteristics of Actual Evapotranspiration Over China Under Global Warming

Abstract

In this study, an assessment is made of the trends of actual evapotranspiration (AE) over China under global warming from an ensemble of the following data sets: National Centers for Environmental Prediction‐National Center for Atmospheric Research reanalysis I, National Centers for Environmental Prediction‐Department of Energy reanalysis II, Modern‐Era Retrospective Analysis for Research and Applications (MERRA), MERRA Version 2, European Centre for Medium‐Range Weather Forecasts Interim Re‐Analysis, and Japanese 55‐year Reanalysis. For China as a whole, annual AE exhibited a significant increasing trend from 1979 to 2015, and the rate of increase was highest in autumn and lowest in summer. By subdividing China into six climatic regions using the aridity index, significant increasing trends in AE are found over the hyperarid, arid, and humid regions, but slightly decrease over the dry subhumid and subhumid regions. For the hyperarid and arid regions, the increases in potential evapotranspiration and the water supply from melting glaciers due to both climate warming and human activities might be the main contributors to the AE increases. An increase in potential evapotranspiration driven by global warming is the main cause of the increased AE over the humid region. On a seasonal basis, most AE over China occurs in summer. However, increasing AE trends have been observed mainly in autumn and winter, and the increase is statistically significant over all of China's six climatic regions in winter. In view of data availability, reanalyses are compared with the results from Mezentsev‐Choudhury‐Yang equation (AE_Budyko). The correlations between individual reanalyses and AE_Budyko tend to be higher over the arid region.

Multimodel‐based analyses of evapotranspiration and its controls in China over the last three decades

“…For each month, the slopes of ET based on LSMs–ET were positive and consistent with that generated by the corresponding GLEAM ET (Figures S4–S6). Our analyses also suggested positive ET trends for each season, consistent with the GLEAM ET and Feng et al (). The GLEAM ET showed that the rate of increase in ET was largest in summer, with a value of 2.27 × 10 −1 mm year −1 (Figure S5), similar to that of the LSMs–ET (2.48 × 10 −1 mm year −1 ), whereas the LSMs–ET generated the greatest ET trend in spring (3.43 × 10 −1 mm year ‐1 ), which was higher than the corresponding GLEAM ET value (8.65 × 10 −2 mm year −1 ).…”

“…The trend was consistent with the GLEAM ET (4.55 × 10 −2 mm year −1 ), but with a high value (7.20 × 10 −2 mm year −1 ; Table 1 and Figure S6). This result confirmed several previous studies that reported positive trends of spatially averaged ET over China (Dong & Dai, 2017;Feng et al, 2018;Liu, Jia, Xie, & Shi, 2016)…”

“…For each month, the slopes of ET based on LSMs-ET were positive and consistent with that generated by the corresponding GLEAM ET ( Figures S4-S6). Our analyses also suggested positive ET trends for each season, consistent with the GLEAM ET and Feng et al (2018).…”

“…Mao and Wang () compared the ET estimates from surface water balance method, modified Penman–Monteith model, and reanalysis data over China and examined the spatiotemporal variations of ET and their drivers at annual scale. Using six reanalysis ET data sets, Feng et al () examined the trends in annual and seasonal ET over China during 1979–2015. Chen et al () compared ET estimates from five empirical and three process‐based models over China during 1982–2009.…”

“…reanalysis data, many researchers have examined the spatiotemporal variations of ET at regional and global scales (Elhag, Psilovikos, Manakos, & Perakis, 2011;Vinukollu, Sheffield, Wood, Bosilovich, & Mocko, 2012;Mueller et al, 2013;Li, Wang, Chen, Yang, & Wang, 2014;Mao & Wang, 2017;Feng, Su, Ji, Zhi, & Han, 2018;Hobeichi, Abramowitz, Evans, & Ukkola, 2018;Zhang et al, 2019). However, our knowledge about the drivers of longterm variations in ET and the controls of ET at regional and global scales are still insufficient, due to the substantial uncertainties in the ET estimates (Mueller et al, 2013;Chen et al, 2014;Wang et al, 2015;Liu et al, 2016b;Mao & Wang, 2017;Li et al, 2018;Wartenburger et al, 2018).…”