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Changes in reference evapotranspiration over C hina during 1960–2012: A ttributions and relationships with atmospheric circulation
Author(s) -
Chai Rongfan,
Sun Shanlei,
Chen Haishan,
Zhou Shujia
Publication year - 2018
Publication title -
hydrological processes
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.222
H-Index - 161
eISSN - 1099-1085
pISSN - 0885-6087
DOI - 10.1002/hyp.13252
Subject(s) - evapotranspiration , climatology , environmental science , atmospheric sciences , dominance (genetics) , pacific decadal oscillation , el niño southern oscillation , physics , geology , biology , ecology , biochemistry , gene
This study investigates reference evapotranspiration (ET 0 ) trends in China from 1960 to 2012 based on the Penman–Monteith equation and gridded meteorological measurements. Under the combined impacts of factors influencing ET 0 (i.e., net radiation [RN], mean temperature [TAVE], vapour pressure deficit [VPD], and wind speed [WND]), both seasonal and annual ET 0 for the whole China and more than half of the grids decreased over the past 53 years. The attribution analyses suggest that for the whole China, the WND is responsible for annual and seasonal ET 0 decreases (excluding summer, where RN is responsible). Across China, the annual cause of WND with the largest spatial extent (43.1% of grids) mainly derives from north of the Changjiang River Basin (CJRB), whereas VPD (RN) as a cause is dispersedly distributed (within and to the south of the CJRB). In summer, RN is dominant in more than half of the grids, but the dominance of VPD and WND accounts for approximately 90% of grids during the remaining seasons. Finally, the correlation coefficients between ET 0 and the Atlantic Oscillation (AO), North AO, Indian Ocean Dipole (IOD), Pacific Decadal Oscillation (PDO), and El Niño Southern Oscillation (ENSO) indices with different lead times are calculated. For the whole China, annual and seasonal ET 0 always significantly correlate with these indices (excluding the IOD) but with varied lead times. Additionally, near half of the grids show significant and maximum (i.e., the largest one between ET 0 and a certain index with a lead time of 0–3 seasons) correlation coefficients of ET 0 with PDO in spring and summer, ENSO in autumn, and AO in winter. This study is not only significant for understanding ET 0 changes, but it also provides preliminary and fundamental reference information for ET 0 prediction.

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