Using Geo‐detector to attribute spatio‐temporal variation of pan evaporation across China in 1961–2001

Tao, Yang; Sun, Fubao; Liu, Wenbin; Hong, Wang; Wang, Tingting; Liu, Changming

doi:10.1002/joc.5976

Cited by 17 publications

(11 citation statements)

References 41 publications

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“…It is obvious that the annual average temperature displayed an upward trend, with the rate of 0.27 • C/10a, contrary to the variation of SD. Similar conclusions have been drawn by Ren et al [57] and Yang et al [58]. Therefore, annual SD was significantly negatively correlated with annual average temperature (R = −0.60, p < 0.01).…”

Section: Trends Of Annual Sd In Each Climate Regionsupporting

confidence: 90%

Reduction in Sunshine Duration and Related Factors over Mainland China during 1961–2016

et al. 2019

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As a kind of renewable energy, the development and utilization of solar energy is valued by many countries. Sunshine duration (SD), as an important factor to measure solar energy, has also been widely discussed as relevant in terms of distribution and variation. The spatial patterns and variation trends in SD and related factors (wind speed, precipitation, relative humidity, mean temperature and elevation) over mainland China have been studied based on data from 569 meteorological stations during 1961-2016. The results indicated that annual SD decreased significantly at the rate of −40.7 h/10a over mainland China and the decline trend was the most pronounced in the 1980s. Seasonally, the decline rate in SD was the largest in summer (−16.8 h/10a), followed by winter (−9.9 h/10a), autumn (−9.5 h/10a) and spring (−4.5 h/10a), respectively. Spatially, the decline trend in SD was significantly higher in the eastern region than in the western region during 1961-2016, especially in North China. SD was positively correlated with wind speed (R = 0.76); however, it was negatively correlated with mean temperature (R = −0.60) and precipitation (R = −0.41). Moreover, altitude and population density may affect the values and variations of annual SD over mainland China. This study provides a new perspective for the reduction of SD in mainland of China. The drastic changes in SD, such as abrupt changes and sudden decreases, were closely related to volcanic eruptions. Among them, the mean mutation and sudden decrease of SD in the 1980s were due to the long-time weakening of the aerosol accumulated by multiple volcanic eruptions. After the volcanic eruptions in the early 1990s, volcanic aerosols were gradually dissipating, resulting in a small rebound in SD.

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Section: Trends Of Annual Sd In Each Climate Regionsupporting

confidence: 90%

Reduction in Sunshine Duration and Related Factors over Mainland China during 1961–2016

et al. 2019

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“…Most recent studies have revealed increasing, decreasing or no trend in rainfall amounts indicating the influence of climate change over rainfall (in the case of regions showing increasing or decreasing trends) or no influence (regions showing no trends). A few studies have also reported statistical trends in rainy days, evaporation rates, air temperature and extreme rainfall events correlated with climate change scenarios (Xu et al, 2006;Burn & Hesch, 2007;Bandyopadhya et al, 2009;Fu et al, 2009;Kumar & Jain, 2010, 2011Abtew et al, 2011;Jhajharia et al, 2012;Soltani et al, 2012;Kumar et al, 2012;Madhu et al, 2015;Soro et al, 2016;Djaman et al, 2017;Oliveira et al, 2017;Toride et al, 2018;Yang et al, 2019;Behzadi et al, 2020). The statistical trend results provide evidence for climate change effects on parameters analyzed and its contribution to regional climatic changes.…”

Section: Introductionmentioning

confidence: 78%

Trend characteristics of rainy days and evaporation at a tropical rainforest region in East Malaysia, Borneo

Mv¹,

Mv²,

Vijith³

2020

Earth sci. res. j.

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Impact of climate change over the hydrological system in a region can be identified through statistical characterization of hydrometerological parameters such as rainfall, temperature, humidity and evaporation. In order to understand the influence of climate change, statistical trend characteristics of rainy days, non-rainy days and evaporation rate in the Limbang River Basin (LRB) in Sarawak, Malaysia, Northern Borneo was assessed in the present research. Annual rainfall and monthly evaporation data, over a period of 46 years, (1970 - 2015) corresponding to three rain gauging stations, the Limbang DID, Ukong and Long Napir were used in the research. Linear regression model, Mann Kendall and Sen’s slope estimator techniques were applied to detect the statistical trends in rainy days and evaporation. A statistically significant increasing trend in annual rainy days was found at all the stations. Non-rainy days showed a statistically significant decreasing trend at Limbang DID and Ukong. Monthly evaporation rates showed an overall increasing trend and the greatest increasing trend in evaporation was observed in September (2.55 mm/year) for the Limbang DID and in December (2.61 mm/year) for Ukong. Evaporation measured at the Ukong station also showed a non-significant decrease during June and September. A comparison of the evaporation controlling meteorological variables such as rainfall, temperature and relative humidity indicates inter-influence at various strengths. Along with local precipitation characteristics, wind and fluctuation of atmospheric temperature over the region plays a vital role in increased rate of evaporation from the region. Overall, the analysis identified a statistically significant increasing trend in rainy days and evaporation in the LRB. The results of the present research can be used as critical planning data for micro and macro hydroelectric projects in the river basin.

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“…However, in order to eliminate the influence of significant autocorrelation in the series of data, the researchers employed the modified MK test, in which the series were prewhitened (Jahani et al, 2018). The magnitude of trends were estimated by using a nonparametric Theil-Sen's slope procedure (Sen, 1968;Theil, 1992;Jahani et al, 2018), which is a well-known test (Darand et al, 2019;Delvaux et al, 2019;Yang et al, 2019).…”

Section: Statistical Analysesmentioning

confidence: 99%

Trend analysis of extreme precipitation events across Iran using percentile indices

Mahbod

Rafiee

2020

Intl Journal of Climatology

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Although a number of studies have been conducted on extreme precipitation trends in different parts of the world including Iran, a great number of such studies have reported only the total amount of daily precipitation greater than a certain percentage (e.g., 95%) of the long term data (R95p), ignoring other useful indices. To address this research gap, we used other modified indices, namely R95tot (fractional contribution of very wet days to annual total amounts), R95tt (fractional contribution of very wet days to the total annual obtained from fitted gamma probability distribution), and RS95 (same as R95tt except that it uses Weibull distribution and very wet days defined by 95 percentage of an individual year) by which the spatial and temporal changes of very wet days across Iran was assessed, 1985–2013. In addition, to evaluate the effect of the selected distribution on the results, a new index‐(RS95gm)—was introduced and reported. This index is similar to RS95, except that it uses gamma distribution instead of Weibull. According to trend analysis of R95p, R95tot, and R95tt, reduced frequency of extreme precipitation events was detected in some northwest, west and northeast parts of Iran. On the contrary, RS95 (RS95gm) results showed a higher frequency of extreme events across Iran. It was also demonstrated that while R95p, R95tot, and R95tt were unequivocally affected by changes in the mean wet‐day/ annual total precipitation, RS95 (RS95gm) was more influenced by changes in the distributional shape, showing more stable trends. Although RS95 and RS95gm were highly correlated with only 19% difference on average, their trend analysis results were not completely consistent (70% agreement). Thus, it may be concluded that any changes in statistical distribution in the calculation of the RS95 would have a considerable effect on whether the obtained trend is significant or not.

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Using Geo‐detector to attribute spatio‐temporal variation of pan evaporation across China in 1961–2001

Cited by 17 publications

References 41 publications

Reduction in Sunshine Duration and Related Factors over Mainland China during 1961–2016

Reduction in Sunshine Duration and Related Factors over Mainland China during 1961–2016

Trend characteristics of rainy days and evaporation at a tropical rainforest region in East Malaysia, Borneo

Trend analysis of extreme precipitation events across Iran using percentile indices

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