Relationship between Sunspot Numbers and Mean Annual Precipitation: Application of Cross-Wavelet Transform—A Case Study

Nazari-Sharabian, Mohammad; Karakouzian, Moses

doi:10.3390/j3010007

Cited by 18 publications

(10 citation statements)

References 60 publications

(98 reference statements)

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“…Large EASJI corresponds to strong extratropical cyclone activity in East China, which can produce large scale precipitation in all seasons. (Ma et al, 2021;Nazari-Sharabian and Karakouzian, 2020). Two signal sequences with significant correlation in Table 2 are selected for wavelet coherence analysis to study the phase relationship between extreme precipitation and atmospheric circulation.…”

Section: Response Of Extreme Precipitation Indices To Atmospheric Cir...mentioning

confidence: 99%

Spatial-temporal variations of extreme precipitation indices and their linkage with atmospheric circulation in the middle and lower reaches of the Yangtze River

Yang

Huang

et al. 2022

Preprint

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Under the background of climate change, increasing frequency and intensity of extreme precipitation causes serious impacts and huge losses to society and economy. It is significant to analyze the spatial and temporal variation of extreme precipitation for regional risk assessment. Nine extreme precipitation indices were calculated using the daily precipitation data of the middle and lower reaches of the Yangtze River (MLYR) from 1979 to 2015. Linear trend analysis and the Mann-Kendall trend test were carried out to determine the variation trend of the nine extreme precipitation indices. In addition, the potential influences of anomalous atmospheric circulation factors on extreme precipitation were explored using the wavelet coherence analysis technique. The results show that: (1) the overall wetting trend is detected in the MLYR, and the PRCPTOT and RX1day increased significantly; (2) Extreme precipitation decreased from southeast to northwest in the MLYR, indicating that extreme precipitation events are more prone to occur in the southeast of the MLYR; (3) the Western Pacific Subtropical High (WPSH), the South China Sea high (SCSH) and the East Asian westerly jet (EAJ) all strongly impact on the changes of precipitation in the MLYR, among which the WPSH has the most significant impact, followed by the SCSH, and the EAJ is weaker.

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Section: Response Of Extreme Precipitation Indices To Atmospheric Cir...mentioning

confidence: 99%

Spatial-temporal variations of extreme precipitation indices and their linkage with atmospheric circulation in the middle and lower reaches of the Yangtze River

Yang

Huang

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…During that time, the term wavelets was habitually used in different areas such as geophysics [43] or electrical engineering; however, modern wavelet theory [44] appeared toward the middle of the 1980s from the close collaboration between Grossman and Morlet [45], who coined the concept ondelette (wavelets denomination in French, see, e.g., Morlet et al [46] and Morlet [47]) to design a new theoretical-empirical framework in which the principles of geophysics in conjunction with mathematics could be extrapolated to other scientific fields [44]. This mutual cooperation would mark the beginning of a fertile relationship between mathematics and various disciplines of knowledge such as agriculture [48,49], astronomy [50], biology [51][52][53], electromagnetism [54,55], forestry [56,57], genetics [15], geophysics [46,58,59], hydrology [60,61], meteorology [62][63][64][65][66], oceanography [63], and seismology [43,67].…”

Section: Wavelets Literaturementioning

confidence: 99%

Testing the Resilience of CSR Stocks during the COVID-19 Crisis: A Transcontinental Analysis

Martínez

Cervantes

2021

Mathematics

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Investors and practitioners are increasingly concerned with financial assets within the scope of corporate social responsibility (CSR) meaning that, in recent times, such assets have become enshrined in the preferences of the new generations of investors and consumers. Just when the interest of investors was at its highest, SARS-CoV-2 (COVID-19) affected all international financial markets, so that, at first sight, it might seem that the financial assets assigned to CSR should have suffered collapses that were identical to the rest; however, our work shows the opposite, providing a comparative analysis of how the pandemic has affected the financial markets of each continent to demonstrate its outstanding resilience through the use of the Wavelets methodology. We analyzed the global impact of the registered cases of COVID-19 on the Dow Jones Sustainability World Index (DJSWI), the world’s leading indicator of sustainable companies, in addition to six other financial indices selected from each continent. The empirical results of this research show that the worldwide repercussions of the sudden outbreak of SARS-CoV-2 has had a substantially smaller effect on sustainability-related indices compared to the other considered indices. Similarly, the methodology employed allowed the establishment of a chronogram with details of the dating of COVID-19 expansion through the considered countries, a certain gradation in terms of the impact of the pandemic on these stock indices, and certain common guidelines describing their devastating effects on each of the financial markets represented by the indices in this research.

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“…For example, Ref. [20] discusses the effect of sunspot numbers on the mean annual precipitation (MAP), while Ref. [21] studies the relationship between COVID‐19 and the price of basic energy resources.…”

Section: Related Workmentioning

confidence: 99%

Wavelet‐attention‐based traffic prediction for smart cities

Nasser

Simon

2021

IET Smart Cities

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Traffic congestion is a problem facing today's world, especially in smart cities where the economy is booming. Solving this issue by upgrading the traffic infrastructure of the city might be very cost‐inefficient as well as time‐consuming. With the help of recent technologies, traffic can be predicted to give the authorities the time to react before congestion evolves. As traffic is affected by several external factors, such as weather and anomalies (accidents, not expected road closures etc.), understanding the relationship between traffic and these factors can improve the prediction even further. In this study, a new method, the weather‐based traffic analysis (hereafter WBTA), is utilised to investigate the temporal correlations between the traffic flow and the exogenous weather factors at different frequencies and time intervals. In addition, a novel method, the wavelet‐attention‐based calculation (hereafter WABC) is introduced to help to understand the importance of each external factor, compared with the others. Five weather factors (temperature, wind speed, rain, visibility, and humidity) are analysed, weighted, and merged with each other as one auxiliary input to improve traffic prediction accuracy. Based on that, the wavelet‐attention‐based prediction model is introduced, where the mean squared error is reduced by 32.3% and 24.52% for one future time step prediction, and 14.9% and 18.22% for five, compared with using the traffic time series alone, and with external factors without weights, respectively.

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Relationship between Sunspot Numbers and Mean Annual Precipitation: Application of Cross-Wavelet Transform—A Case Study

Cited by 18 publications

References 60 publications

Spatial-temporal variations of extreme precipitation indices and their linkage with atmospheric circulation in the middle and lower reaches of the Yangtze River

Spatial-temporal variations of extreme precipitation indices and their linkage with atmospheric circulation in the middle and lower reaches of the Yangtze River

Testing the Resilience of CSR Stocks during the COVID-19 Crisis: A Transcontinental Analysis

Wavelet‐attention‐based traffic prediction for smart cities

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