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

Hussain, Azfar; Cao, Jianhua; Ali, Shaukat; Ullah, Waheed; Sher, Muhammad; Hussain, Ishtiaq; Abbas, Haider; Hamal, Kalpana; Sharma, Shankar; Akhtar, Mobeen; Wu, Xiulan; Zhou, Jinxing

doi:10.1002/joc.7874

Cited by 17 publications

(13 citation statements)

References 87 publications

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“…The dynamic construction of monsoon indices is made using the relationship between circulation and convection in the tropics (Zhang et al, 2022). Past literature has confirmed the influence of ENSO on ISMR but has also augmented the variability of monsoon indices and the change in the dominant monsoon index on IMSR (Das et al, 2020;Hussain et al, 2022;Rehana et al, 2022;Reshma et al, 2021;Roy et al, 2017Roy et al, , 2019Roy et al, , 2022. The present study considers the monsoon index surrounding India, which includes ISMI, SASMI, EASMI, and WNPMI, to investigate long-distance interaction with ISMR.…”

Section: Discussionmentioning

confidence: 99%

Impact of Long‐Distance Interaction Indicator (Monsoon Indices) on Spatio‐Temporal Variability of Precipitation Over the Mahanadi River Basin

Sahu

Verma

Ahmad

2023

Water Resources Research

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Sea Surface Temperature (SST) is the most important physical characteristic of the ocean, that is, the temperature of water at the surface level, and it plays a significant role mainly with latitude (Ashok et al., 2001;Sahai et al., 2003;Verma, 1994). Atmospheric and oceanic behavior have been studied, but recent research has augmented the concern for an incomplete understanding of climate phenomena (Chakraborty & Singhai, 2021;Di Capua et al., 2020;Sundaram & Holland, 2022). The above concern is in connection with multi-scale system interaction, which typically exhibits unique local and non-local interrelationships (a statistical conceptualization). The SST and air temperature have a significant impact on the atmospheric moisture content, which is an

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Section: Discussionmentioning

confidence: 99%

Impact of Long‐Distance Interaction Indicator (Monsoon Indices) on Spatio‐Temporal Variability of Precipitation Over the Mahanadi River Basin

Sahu

Verma

Ahmad

2023

Water Resources Research

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“…It is an appropriate tool for evaluating the local fluctuations in the power in a time series. We used the wavelet transform coherence (WTC), a correlation coefficient localized in the time and frequency domain, to evaluate the degree of a linear relationship in time and frequency [54,55]. It can also detect the quasiperiodic component of a system anomaly [56,57].…”

Section: Wavelet Analysismentioning

confidence: 99%

Spatiotemporal Runoff Analysis and Associated Influencing Factors in Chitral Basin, Pakistan

Nawaz,

Wang,

Hussain

2023

Water

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Global warming has accelerated climate and weather changes, impacting the regional water cycle. This study assesses the temporal trends of seasonal and annual runoff in the Chitral River Basin (CRB) and its responses to regional climatic factors (i.e., temperature, precipitation, and Normalized Difference Vegetation Index (NDVI)) and oceanic indices at large scales (i.e., El Nino Southern Oscillation (ENSO), Indian Ocean Dipole (IOD), and Pacific Decadal Oscillation (PDO)). The non-parametric Mann–Kendall (MK) test, the Sequential Mann–Kendall test (SQMK) and Sen Slope (SS) is used to evaluate trends and magnitude. In contrast, wavelet analysis is used to assess the coherence. In general, precipitation increases in winter, summer and autumn, whereas it decreases in spring. The temperature increased significantly in winter and spring, while a significant increase in seasonal and annual runoff was evident. Annual NDVI increased, whereas the Normalized Difference Water Index (NDWI) and the Normalized Difference Snow Index (NDSI) decreased. Generally, runoff has significant inter-annual coherences with regional environmental factors, and a significant coherence with NDVI. Monthly runoff has a positive coherence with temperature and NDVI, whereas it has a negative correlation with precipitation, NDWI, and NDSI. In general, ENSO, IOD and PDO show a positive correlation with runoff. The MWC findings indicate that annual runoff prevailed interannual signals with local environmental factors and with the Pacific Ocean, whereas interannual and interdecadal coherences are obvious with the Atlantic Ocean. The results have significant implications for decision-makers seeking to enhance water resource planning, disaster prevention, and mitigation, especially in global warming and the intensification of human activities that influence hydroclimatic changes at high altitudes.

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“…The WC method has proven to be useful in geophysics and climatology, linking e.g. rainfall and the El Niño-Southern Oscillation (ENSO) index (Torrence and Webster, 1999) or rainfall and monsoon in Pakistan (Hussain et al, 2022). WC has already been used several times when coupling climatological factors such as temperature or rainfall and vegetation occurrence.…”

Section: Introductionmentioning

confidence: 99%

Coherency and time lag analyses between MODIS vegetation indices and climate across forests and grasslands in the European temperate zone

Kulesza,

Hościło

2024

Biogeosciences

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Abstract. Identifying the climate-induced variability in the condition of vegetation is particularly important in the context of recent climate change and plants' impact on the mitigation of climate change. In this paper, we present the coherence and time lags in the spectral response of three individual vegetation types in the European temperate zone to the influencing meteorological factors in the period 2002–2022. Vegetation condition in broadleaved forest, coniferous forest and pastures was measured with monthly anomalies of two spectral indices – normalised difference vegetation index (NDVI) and enhanced vegetation index (EVI). As meteorological elements we used monthly anomalies of temperature (T), precipitation (P), vapour pressure deficit (VPD), evapotranspiration (ETo), and the teleconnection indices North Atlantic Oscillation (NAO) and North Sea Caspian Pattern (NCP). Periodicity in the time series was assessed using the wavelet transform, but no significant intra- or interannual cycles were detected in both vegetation (NDVI and EVI) and meteorological variables. In turn, coherence between NDVI and EVI and meteorological elements was described using the methods of wavelet coherence and Pearson's linear correlation with time lag. In the European temperate zone analysed in this study, NAO produces strong coherence mostly for forests in a circa 1-year band and a weaker coherence in a circa 3-year band. For pastures these interannual patterns are hardly recognisable. The strongest relationships occur between conditions of the vegetation and T and ETo – they show high coherence in both forests and pastures. There is a significant cohesion with the 8–16-month (ca. 1-year) and 20–32-month (ca. 2-year) bands. More time-lagged significant correlations between vegetation indices and T occur for forests than for pastures, suggesting a significant lag in the forests' response to the changes in T.

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

Cited by 17 publications

References 87 publications

Impact of Long‐Distance Interaction Indicator (Monsoon Indices) on Spatio‐Temporal Variability of Precipitation Over the Mahanadi River Basin

Impact of Long‐Distance Interaction Indicator (Monsoon Indices) on Spatio‐Temporal Variability of Precipitation Over the Mahanadi River Basin

Spatiotemporal Runoff Analysis and Associated Influencing Factors in Chitral Basin, Pakistan

Coherency and time lag analyses between MODIS vegetation indices and climate across forests and grasslands in the European temperate zone

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