On the coupling between precipitation and potential evapotranspiration: contributions to decadal drought anomalies in the Southwest China

Sun, Shurong; Chen, Haishan; Ju, Weimin; Wang, Guojie; Sun, Ge; Huang, Jin; Ma, Hedi; Gao, Chujie; Hua, Wenjian; Yan, Guoxin

doi:10.1007/s00382-016-3302-5

Cited by 62 publications

(58 citation statements)

References 121 publications

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“…Many studies reported that the precipitation showed a decreasing trend over Southwest China [6,50]. In this study, the precipitation was found decreased during the period of 1993-2015 (Table 2), particularly during 2000-2013 (−6.4 mm year −1 , p < 0.05).…”

Section: Impacts Of Change In Aridity Index On Droughtsupporting

confidence: 52%

“…Associated with the exacerbation of climate change [1], extreme climate events such as drought [2], extreme precipitation [3], and flooding [4] are increasing at different levels at both global and regional scales [5,6]. Drought, considered as one of the damaging extreme climate events, happened frequently and intensively in recent years [7], which brought more economic and population losses than other climatic disasters [8,9].…”

Section: Introductionmentioning

confidence: 99%

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Variation of Aridity Index and the Role of Climate Variables in the Southwest China

Feng

Liu

et al. 2017

Water

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Aridity index (AI), defined as the ratio of annual potential evapotranspiration to annual precipitation, has been widely applied in dividing climate regimes and monitoring drought events. Investigating variation of AI and the role of climate variables are thus of great significant for managing agricultural water resource and maintaining regional ecosystem stability. In this study, with the well-corrected precipitation records and the optimized parameters in estimating solar radiation, we investigated the variation of AI and its climatic attribution in the Southwest China using the observed climate records from 135 meteorological stations during the period of 1993-2015. The results showed that the AI increased significantly (0.0053 year −1 , p < 0.05) from 1993 to 2015 and abruptly increasing occurred around 2002. Approximately 85% of stations showed an increasing trend, while 24% of stations reached up to a significant increasing level, which demonstrated that the Southwest China was getting drier for the recent 20 years. Overall, the AI was most sensitive to maximum air temperature and precipitation with values of 1.11 and −1.00, respectively. The following factors are vapor pressure, solar radiation, minimum temperature, and wind speed. The declining precipitation and ascending maximum air temperature were the key variables in dominating the increase in aridity index during the period of 1993-2015, which contribute 38.98% and 36.26% of AI variation, respectively. Our results highlighted the influence of climate variability on aridity in the Southwest China.

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Section: Impacts Of Change In Aridity Index On Droughtsupporting

confidence: 52%

Section: Introductionmentioning

confidence: 99%

Variation of Aridity Index and the Role of Climate Variables in the Southwest China

Feng

Liu

et al. 2017

Water

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“…These sites and the 10 basins across China are shown in Figure . Before using, two data quality issues within this dataset (i.e., inhomogeneous and missing values) should be noted; therefore, we have followed the methods of Sun, Chen, Ju, et al () to solve them. For simplicity, the detailed procedure is not presented here but can be found in Sun, Chen, Ju, et al ().…”

Section: Methodsmentioning

confidence: 99%

“…However, it should be noted that the impacts of evapotranspiration (ET) or reference ET (ET 0 ) have been given less attention, even though they are closely associated with changes in climatic variables and are integrated indicators of climate change. For example, Hu and Willson () and Sun et al (), Sun, Chen, Ju, et al () have reported that the impact of ET 0 on drought could be equivalent to or even higher than that from precipitation. Consequently, understanding the spatial and temporal variations in ET 0 is a vital component for comprehensively understanding hydrometeorological changes and is helpful for better monitoring and predicting drought (Beguería, Vicente‐Serrano, Reig, & Latorre, ; Li, He, Quan, Liao, & Bai, ; McEvoy, Huntington, Mejia, & Hobbins, ; Sun et al, ; Sun, Chen, Sun, et al, ; Vicente‐Serrano, Beguería, & Lópezmoreno, ; Zhang et al, ).…”

Section: Introductionmentioning

confidence: 99%

“…Nevertheless, due to complex interactions among various meteorological factors for ET 0 (Paparrizos, Maris, & Matzarakis, ; Zhang et al, ; Zhang et al, ), it remains difficult to identify the impact of each driving factor alone, which consequently results in uncertainties and even errors in the conclusions (Li et al, ; Liu et al, ; Zhang et al, ). Recently, to overcome this issue (at least partially) and enhance the confidence level of the conclusions, Sun, Chen, Ju, et al () developed a new separation method to attribute ET 0 changes over Southwest China and stated that this method has a better performance (e.g., accuracy) compared with other methods. As a result, this provides an efficient tool to more accurately and comprehensively understand the underlying mechanisms of changed ET 0 across China.…”

Section: Introductionmentioning

confidence: 99%

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

Chai

Sun

Chen

et al. 2018

Hydrological Processes

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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.

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Shift in potential evapotranspiration and its implications for dryness/wetness over Southwest China

et al. 2016

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During 1961–2012, the regional average annual potential evapotranspiration (PET) of Southwest China (SWC) and the four subregions (named as SR1, SR2, SR3, and SR4) showed different decreases (excluding SR3); while the breakpoint analysis suggested that PET changes (i.e., sign and magnitude) have shifted. Based on a group of sensitivity experiments with Penman‐Monteith equation and a new separating method, the contributions of each climate factor alone (i.e., net radiation, Rn; mean temperature, Tave; wind speed, Wnd; and vapor pressure deficit, Vpd) to PET changes were calculated. Results showed that declined Wnd in SR1, reduced Rn in SR2, SR4, and SWC, and increased Vpd in SR3 were responsible for the PET changes during 1961–2012. However, the determinant factor for each subregion and SWC varied in different segmented periods, which were identified using the breakpoint analysis. The impacts of PET shifts on SWC dryness/wetness (reflected by the 3 month Standardized Precipitation‐Evapotranspiration index, SPEI‐3) during 1961–2012 were then quantified. Briefly, SPEI‐3 changes in SR3, SR4, and SWC had the determinant factor of PET in the first one or two period(s), and precipitation in the last period; while they were attributed to PET (precipitation) in SR1 (SR2) for each segmented period. It is found that PET and precipitation had comparable contributions to the variations in SWC dryness/wetness. Our findings have suggested that more attentions should be paid to the impacts of PET changes and shifts in future studies of dryness/wetness or drought.

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On the coupling between precipitation and potential evapotranspiration: contributions to decadal drought anomalies in the Southwest China

Cited by 62 publications

References 121 publications

Variation of Aridity Index and the Role of Climate Variables in the Southwest China

Variation of Aridity Index and the Role of Climate Variables in the Southwest China

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

Shift in potential evapotranspiration and its implications for dryness/wetness over Southwest China

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