Wavelet coherence of monsoon and large‐scale climate variabilities with precipitation in Pakistan

Abstract Monsoon and its teleconnection with earth system internal processes affect the spatiotemporal distribution of precipitation and water resources . In this paper, the wavelet coherence analysis has been utilized, a time and frequency domain methodology for comparing the spectral features of t...

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Bibliographic Details
Published in:International Journal of Climatology
Main Authors: Hussain, Azfar, Cao, Jianhua, Ali, Shaukat, Ullah, Waheed, Muhammad, Sher, Hussain, Ishtiaq, Abbas, Haider, Hamal, Kalpana, Sharma, Shankar, Akhtar, Mobeen, Wu, Xiuqin, Zhou, Jinxing
Other Authors: Fundamental Research Funds for the Central Universities, National Natural Science Foundation of China, Special Fund for Forest Scientific Research in the Public Welfare
Format: Article in Journal/Newspaper
Language:English
Published: Wiley 2022
Subjects:
Soi
Online Access:http://dx.doi.org/10.1002/joc.7874
https://onlinelibrary.wiley.com/doi/pdf/10.1002/joc.7874
https://onlinelibrary.wiley.com/doi/full-xml/10.1002/joc.7874
https://rmets.onlinelibrary.wiley.com/doi/pdf/10.1002/joc.7874
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Summary:Abstract Monsoon and its teleconnection with earth system internal processes affect the spatiotemporal distribution of precipitation and water resources . In this paper, the wavelet coherence analysis has been utilized, a time and frequency domain methodology for comparing the spectral features of two independent time series superior to linear approaches. This technique is used to capture the significant modes of variabilities in the Indian Summer Monsoon Index (ISMI) and large‐scale climate indices (CIs) between ocean–atmosphere oscillations, like Indian Ocean Dipole (IOD), El Niño–Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), Southern Oscillation Index (SOI), North Atlantic Oscillation (NAO), Atlantic Multidecadal Oscillation (AMO), and Arctic Oscillation (AO) over Pakistan. Precipitation time series during 1960–2016 revealed significant interannual coherences with ISMI, whereas the remaining CIs (IOD, ENSO, PDO, SOI, NAO, AMO, and AO) revealed interannual, decadal and interdecadal coherences. However, AO revealed strongest coherences in R‐II, III, and VI at interdecadal scales among all CIs. Overall, the interannual cycles on ISMI are 2.8 years, IOD 1–5.3 years, PDO 0–5.3 years, SOI 1–5.3 years, NAO 0–5 years, AO 0–5 years, and AMO 0–8.3 years. Whereas, the remaining CIs shared interdecadal coherences over particular regions. The ISMI displayed coherences (except in the UIB) with the large‐scale CIs over various homogenous regions on an interannual scale. The dominant influence of ISMI is observed in R‐II and III; the significant coherences in R‐II ranged from ~8 to 32 months (~0.8–2.8 years). The IOD and NAO have major coherences than the remaining large‐scale CIs ranging from ~16 to 64 months (1.3–5.3 years). The AO has the most significant coherences observed in R‐II, III, and VI on the decadal/interdecadal scale from 128 months and above (almost 10–15 years). On a 1.0‐year timescale, all homogenous regions demonstrated strong intermittent coherence with ISMI, IOD, ENSO, PDO, SOI, NAO, ...