Changes in reference evapotranspiration over China during 1960–2012: Attributions and relationships with atmospheric circulation

Abstract

This study investigates reference evapotranspiration (ET0) trends in China from 1960 to 2012 based on the Penman–Monteith equation and gridded meteorological measurements. Under the combined impacts of factors influencing ET0 (i.e., net radiation [RN], mean temperature [TAVE], vapour pressure deficit [VPD], and wind speed [WND]), both seasonal and annual ET0 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 ET0 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 ET0 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 ET0 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 ET0 and a certain index with a lead time of 0–3 seasons) correlation coefficients of ET0 with PDO in spring and summer, ENSO in autumn, and AO in winter. This study is not only significant for understanding ET0 changes, but it also provides preliminary and fundamental reference information for ET0 prediction.

Unraveling the influence of atmospheric evaporative demand on drought and its response to climate change

“…Hence, it is expected that AED is also influenced, but in a complex way due to atmospheric circulation effects on local climate and different sensitivities of AED to each of the governing meteorological variables (Hobbins, Wood, Streubel, & Werner, ; Roderick, Rotstayn, Farquhar, & Hobbins, ; Vicente‐Serrano, Azorin‐Molina, Sanchez‐Lorenzo, Revuelto, López‐Moreno, et al, ; Vicente‐Serrano, Azorin‐Molina, Sanchez‐Lorenzo, Revuelto, Morán‐Tejeda, et al, ; Vicente‐Serrano, Lopez‐Moreno, et al, ). Large‐scale atmospheric circulation patterns influence interannual variability of AED given their control upon local meteorological variables (Chai, Sun, Chen, & Zhou, ; Martens, Waegeman, Dorigo, Verhoest, & Miralles, ).…”

Changes in reference evapotranspiration over the non‐monsoon region of China during 1961–2017: Relationships with atmospheric circulation and attributions

“…u 2 was the dominant factor contributing to ET 0 in the NMR; this is generally consistent with previous studies in similar regions (Yin et al ., 2009; Han et al ., 2012; Liu and Zhang, 2013; Zhang et al ., 2013; Li et al ., 2014; Fan et al ., 2016; Wang et al ., 2017; Li et al ., 2017c; Chai et al ., 2018; Fan and Thomas, 2018). Table 3 indicates significant positive correlations between ET 0 and u 2 during periods I and II but a weak positive correlation during period III.…”

“…In recent years, there have been extensive research efforts to investigate the potential impact of climate change on ET 0 in this region. The results suggested that changes in ET 0 for northwest China can primarily be attributed to a decreased wind speed since the 1960s (Yin et al ., 2010; Han et al ., 2012; Huo et al ., 2013; Zhang et al ., 2013; Li et al ., 2014; Fan et al ., 2016; Wang et al ., 2017; Chai et al ., 2018; Fan and Thomas, 2018). Li et al .…”

“…Chai et al . (2018) found that annual and seasonal ET 0 in China always have significant correlations with the Arctic Oscillation (AO), NAO, Pacific Decadal Oscillation (PDO), and ENSO indices but with varied lead times. Atmospheric circulation can indirectly affect ET 0 by influencing climatic variables, including the air temperature T , R s , u 2 , and e a .…”

Observed Multi-Timescale Differences between Summertime Near-Surface Equivalent Temperature and Temperature for China and Their Linkage with Global Sea Surface Temperatures

“…To further reduce the possible uncertainties that were introduced by the inhomogeneity of the stations' geographic distribution, we followed Zhang et al [27] and Chai et al [28] to conduct a redistribution algorithm after the screening of the stations. In detail, this process redistributed the station data onto a 0.5 • × 0.5 • equal longitude-latitude grid, and each grid box only contained one station (if any grid contained more than one station, the station data that was last processed would represent the final value of that grid).…”