Identification of relationship between sunspots and natural runoff in the Yellow River based on discrete wavelet analysis

Li, C. H.; Yang, Zhicheng; Huang, Guohe; Li, Y. P.

doi:10.1016/j.eswa.2008.01.083

Cited by 35 publications

(24 citation statements)

References 21 publications

(19 reference statements)

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“…With an increase in sunspot number, the precipitation in the . The results were similar to those of Li and Yang [13], who also reported that the annual precipitation at the Yellow River showed hysteresis for sunspot number. Zhang et al [14] reported that, at the peak of sunspot activity or 2a near it, the summer precipitation in Xi'an increased sharply.…”

Section: Wavelet Analyses Of Precipitation and Sunspot Numbersupporting

confidence: 81%

“…In addition, the solar cycle significantly influences regional hydrometeorological phenomenon [7]. Previously, a number of studies have investigated the relationships between solar activity and runoff, precipitation, and intense loess erosion using statistical methods [3]. These studies revealed close relationships between solar activity and hydrometeorological processes.…”

Section: Introductionmentioning

confidence: 99%

“…Solar activity, such as solar winds, flares, and solar radiation bursts, can lead to plasma movement and radiation enhancement [3,4]. Many scholars have researched the periodic variation of solar activity [5,6] and shown that the solar cycle has important impacts on climate change in a wide variety of ways.…”

Section: Introductionmentioning

confidence: 99%

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Response of Extreme Precipitation to Solar Activity and El Nino Events in Typical Regions of the Loess Plateau

Gao

Zhang

et al. 2017

Advances in Meteorology

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Extreme climatic oscillation has been the subject of global attention. The purpose of this study is to explore the response of extreme precipitation to solar activity and El Nino events in typical regions of the Loess Plateau-a case study in the Yan'an area. The precipitation data was from nine weather stations in Yan'an and the sunspot number and the Southern Oscillation Index (SOI) were from 1951 to 2015. The results show that maximum precipitation occurred mainly at the peak sunspot number or 2a near it and the sunspot number minimum and valley values were not significantly correlated. The results of Morlet wavelet showed that a 41-year period of precipitation was the most obvious within the 64-year scale. Similarly, sunspot number showed a 16-year periodic variability. Correlation analyses of the 16-year and 41-year scales demonstrated that the relationships between precipitation and sunspot number were close. In addition, extreme precipitation often occurred in the year following El Nino events. According to 10-year moving average curves, precipitation generally showed a downward trend when SOI was negative. The results indicate that solar activity and El Nino events had significant impacts on precipitation in typical regions of the Loess Plateau.

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Section: Wavelet Analyses Of Precipitation and Sunspot Numbersupporting

confidence: 81%

Section: Introductionmentioning

confidence: 99%

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Response of Extreme Precipitation to Solar Activity and El Nino Events in Typical Regions of the Loess Plateau

Gao

Zhang

et al. 2017

Advances in Meteorology

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“…These correlations are reasonable because the numbers of 587 sunspots predominate at 11-year and 60-year periodicities (Li et al, 2009). Figure S5 depicts the 588…”

Section: Figure 2 459 460mentioning

confidence: 90%

Wavelet-based variability of Yellow River discharge at 500-, 100-, and 50-year timescales

Miao

Borthwick

et al. 2017

Gondwana Research

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Highlights for reviews [a maximum of 85 characters, including spaces, per highlight] 13(1) Spatial and temporal variabilities of streamflow in the YR are investigated. 14 (2) Periodic changes of the streamflow are identified at 500-, 100-, and 50-year timescales. 15 (3) Periodicities are continuous at spatial scale and short timescales. 16 (4) Strong connection with the Niño 3.4, the AO, and sunspots. 17 18 2 Abstract: Water scarcity in the Yellow River, China, has become increasingly severe over the past 19 half century. In this paper, wavelet transform analysis was used to detect the variability of natural, 20 observed, and reconstructed streamflow in the Yellow River at 500-, 100-, and 50-year timescales. 21The periodicity of the streamflow series and the co-varying relationships between streamflow and 22 atmospheric circulation indices / sunspot number were assessed by means of continuous wavelet 23 transform (CWT) and wavelet coherence transform (WTC) analyses. The CWT results showed 24 intermittent oscillations in streamflow with increasing periodicities of 1-6 years at all timescales.

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“…The fundamental idea of CWT is to decompose a signal f(t) into wavelet coefficients as shown in Equation (4), thus the selection of wavelet functions is critical to wavelet analysis. The most common wavelet functions used in hydrology research are the Mexican hat wavelet, Haar wavelet, Daubechis wavelet, Morlet wavelet, and Mayer wavelet [21,28]. According to He et al [29], the Morlet wavelet is given the phase and oscillation of the real part and imaginary part, and has a phase difference of π/2, which can eliminate false periodicities so that the results are more accurate.…”

Section: Wavelet Analysismentioning

confidence: 99%

Spatiotemporal Variation of Precipitation Regime in China from 1961 to 2014 from the Standardized Precipitation Index

Yuan

2016

IJGI

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Prediction of drought and flood events can be difficult, but the standardized precipitation index (SPI) calculated from monthly data may be a useful tool for predicting future dryness/wetness events in China. The rainy season SPI was calculated from monthly precipitation data from 3804 meteorological stations in China. The spatiotemporal variation, periodic change, and trend in rainy season SPI from 1961 to 2014 in eight regions were investigated. The results indicate that the rainy season SPI is valuable for assessing dryness/wetness spatial and temporal variations. The SPI time series in the northwest and southwest show increasing trends, while northeast China, south China, and Taiwan show more than one upward/downward trend during the study period, and the SPI time series in central, east, and north China show no change in trend. South China has an approximately 10-year periodic oscillation, while the other regions show an approximately 16-year periodic oscillation. The results of this study imply that the SPI can be used to explore historical drought/flood spatiotemporal variations, as well as to predict future wetness/dryness variations.

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Identification of relationship between sunspots and natural runoff in the Yellow River based on discrete wavelet analysis

Cited by 35 publications

References 21 publications

Response of Extreme Precipitation to Solar Activity and El Nino Events in Typical Regions of the Loess Plateau

Response of Extreme Precipitation to Solar Activity and El Nino Events in Typical Regions of the Loess Plateau

Wavelet-based variability of Yellow River discharge at 500-, 100-, and 50-year timescales

Spatiotemporal Variation of Precipitation Regime in China from 1961 to 2014 from the Standardized Precipitation Index

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