Wavelet analysis of annual rainfall over Kerala and sunspot number

Thomas, Elizabeth; Joseph, Irene; Abraham, Noble P.

doi:10.1016/j.newast.2022.101944

Cited by 7 publications

(4 citation statements)

References 60 publications

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“…As a result, the increase in the ET 0 in Heilongjiang Province during 1980-2019 was mainly attributed to the variation in average relative humidity. Wang et al [31] found that relative humidity was the main factor affecting the change in evapotranspiration of reference crops in Heilongjiang on an annual scale, which was consistent with the above conclusion.…”

Section: Influencing Factors Of Et 0 and Their Trend Characteristicsupporting

confidence: 74%

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Spatiotemporal Variation Characteristics of Reference Evapotranspiration and Relative Moisture Index in Heilongjiang Investigated through Remote Sensing Tools

et al. 2023

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Reference evapotranspiration (ET0) is one of the significant parameters in agricultural irrigation, especially in Heilongjiang, a big agricultural province in China. In this research, the spatiotemporal variation characteristics of evapotranspiration (ET), relative moisture index (MI) and influencing factors of ET0 in Heilongjiang, which was divided into six ecology districts according to landforms, were analyzed with meteorological data observed over 40 years from 1980 and MOD16 products from 2000 to 2017 using Morlet wavelet analysis and partial correlation analysis. The results indicated that (1) the spatial distribution of ET and PET in Heilongjiang in humid, normal and arid years showed a distribution of being higher in the southwest and lower in the northwest, and higher in the south and lower in the north. The PET was higher than ET from 2002 to 2017, and the difference was small, indicating that the overall moisture in Heilongjiang was sufficient in these years. (2) In the last 40 years, the ET0 increased while the annual MI decreased. The annual minimum of MI in the six regions of Heilongjiang was −0.25, showing that all six regions were drought free. (3) The importance of the meteorological factors affecting ET0 was ranked as average relative humidity > average wind speed > sunshine duration. This research provides scientific guidance for the study of using remote sensing to reverse ET.

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Section: Influencing Factors Of Et 0 and Their Trend Characteristicsupporting

confidence: 74%

“…Wavelet analysis [31] is widely applied to make the periodic analysis. It can not only reflect the periodic variation in a time series, but also help estimate qualitatively the future development trend.…”

Section: Morlet Wavelet Analysismentioning

confidence: 99%

Spatiotemporal Variation Characteristics of Reference Evapotranspiration and Relative Moisture Index in Heilongjiang Investigated through Remote Sensing Tools

et al. 2023

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“…The direct and indirect effects were studied. The results were often localised and contradicted other authors , Bhattacharyya & Narasimha, 2007, Hiremath, 2006, Hiremath et al, 2015, Jagannathan & Parthasarathy, 1973, Lihua et al, 2007, Malik & Brönnimann, 2018, Selvaraj & Aditya, 2011, Selvaraj et al, 2009a, Thomas et al, 2023.…”

Section: Introductioncontrasting

confidence: 63%

Solar Activity and Extreme Rainfall Over Kerala, India

Thomas,

Abraham

2023

Preprint

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“…As a final step of the methodology, we applied cross-wavelet transform (XWT) and wavelet coherence (WTC) analysis methods that give a possible relationship (correlation and phase) between the obtained periodicities from two different datasets. These two methods are also part of the bi-wavelet package [40], already used by other authors [36,38,[41][42][43] for different purposes. From the analysis, a nonlinear relationship and common periods between the datasets can be inferred, namely X and Y, as well as the phase relationship between the two time series.…”

Section: Methodsmentioning

confidence: 99%

Periodic Behavior of Selected Solar, Geomagnetic and Cosmic Activity Indices during Solar Cycle 24

Kilcik,

Rozelot,

Ozguc

2024

Universe

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In this study, we performed periodicity analyses of selected daily solar (flare index, coronal index, number of coronal mass ejections), geomagnetic (planetary equivalent range index, disturbance storm time index, interplanetary magnetic field) and cosmic ray indices for the last Solar Cycle 24 (from December 2008 to December 2019). To study the periodic variation of the above-listed datasets, the following analysis methods were applied; multi-taper method, Morlet wavelet, cross-wavelet transform and wavelet coherence analysis. The outcome of our analyses revealed the following. (i) The 25–33 days solar rotation periodicities exist in all datasets without any exception in the MTM power spectra. (ii) Except for the solar rotation periodicity, all periods show data preference, and they appear around the investigated cycle’s maximum phase. (iii) When comparing the phase relations between periodicities in the used datasets, they exhibit a gradual transition from small to large periods. For short-term periodicities, there are no phase relations but a mixed phase, whereas for high periodicities, there are complete phase/antiphase transitions. (iv) All identified flare index periodicities are common to all other datasets examined in this investigation.

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Wavelet analysis of annual rainfall over Kerala and sunspot number

Cited by 7 publications

References 60 publications

Spatiotemporal Variation Characteristics of Reference Evapotranspiration and Relative Moisture Index in Heilongjiang Investigated through Remote Sensing Tools

Spatiotemporal Variation Characteristics of Reference Evapotranspiration and Relative Moisture Index in Heilongjiang Investigated through Remote Sensing Tools

Solar Activity and Extreme Rainfall Over Kerala, India

Periodic Behavior of Selected Solar, Geomagnetic and Cosmic Activity Indices during Solar Cycle 24

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