The impact of climate indices on precipitation variability in Baluchistan, Pakistan

Aamir, Erum; Hassan, Ishtiaq

doi:10.1080/16000870.2020.1833584

Cited by 14 publications

(6 citation statements)

References 44 publications

(62 reference statements)

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“…The PDO is a large‐scale climatic pattern characterized by SST swings between cool SST anomalies in the east‐central North Pacific and warm SST anomalies over North America's central west coast (Nalley et al ., 2019). Recently, various studies have explored the relationships between PDO and precipitation in Pakistan (Iqbal and Athar, 2018; Aamir and Hassan, 2020; Hussain et al ., 2021; Ullah et al ., 2021a). According to Krishnamurthy and Krishnamurthy (2014), PDO has an impact on the tropical Pacific, changing the relationship between monsoon rainfall and ENSO, while, during the warm PDO period, El Niño (La Niña) has a greater influence on monsoon rainfall (reduced) over South Asia.…”

Section: Resultsmentioning

confidence: 99%

“…Numerous studies have investigated the associations between precipitation and large-scale climate indices (CIs) across various subregions of Pakistan. Aamir and Hassan (2020) studied the influence of El Niño-Southern Oscillation (ENSO), Equatorial Indian Ocean Zonal Wind Index (EQWIN), North Atlantic Oscillation (NAO), Pacific Decadal Oscillation (PDO), and Atlantic Multidecadal Oscillation (AMO) on monthly precipitation in the southwestern region of Pakistan. The NAO, EQWIN, and ENSO influence annual precipitation, whereas PDO and AMO influence January precipitation on decadal scales.…”

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confidence: 99%

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

Hussain

Cao

Ali³

et al. 2022

Intl Journal of Climatology

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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

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Section: Resultsmentioning

confidence: 99%

mentioning

confidence: 99%

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

Hussain

Cao

Ali³

et al. 2022

Intl Journal of Climatology

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“…The dataset was found to be not normally distributed. Since precipitation data is not normally distributed, therefore, nonparametric analysis technique Mann-Kendall is used for trend detection (Libiseller & Grimvall, 2002;Bastiaanssen & Ali, 2003;Bastiaanssen and Ali, 2003;Aamir & Hassan, 2020;Webster, Toma, & Kim, 2011). Trend analysis is the most extensively studied topic in climatology.…”

Section: Methodsmentioning

confidence: 99%

“…The effect of the monsoon on the summer of this region is very mild. The effect of tropical storms in coastal areas is in autumn (Aamir et al, 2018;Ahmed, Shahid, & Nawaz, 2018;Gadiwala, Burke, & Geology, 2019;Sheikh et al, 2015;Aamir and Hassan 2020;Ahmed et al 2015;Ashraf et al 2015).…”

Section: Introductionmentioning

confidence: 99%

Population Challenges in a Changing World: An Overview of the 22nd Annual Research Conference of the Population Association of Pakistan

NJSSH¹

2023

NJSSH

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The Population Association of Pakistan (PAP), established in 2000,continues to emphasize the crucial relationship between population anddevelopment. The population and development programs in Pakistan have notprogressed as steadily as in most of the countries in the region or other Muslimmajoritycountries such as Egypt, Indonesia, Iran, and Turkey. PAP provides aplatform that offers an opportunity to bridge the various social sciencesdisciplines including economics, public and social policy, statistics,demography, public health, sociology, geography, and anthropology todeliberate upon solutions for pressing population and development relatedissues of Pakistan in this changing world. The 22nd Annual Population Research Conference of PAP was held atthe National University of Sciences and Technology (NUST), Islamabad from7th to 9th December 2021 in a hybrid mode encompassing both virtual and inpersonparticipation at the NUST. The theme of the Conference was“Population Challenges in a Changing World” with three specific sub-themes:I. Population, Universal Health Coverage, and Family Planning, in thecontext of COVID 19.II. Social, Economic, and Demographic Implications of High PopulationGrowth; andIII. Opportunities and Challenges for Resilience to Climate Change. Spanning these three sub-themes, divided across technical and plenarysessions, 18 research papers were presented and discussed in the technicalsessions, while in the four plenary sessions key population challenges inPakistan were discussed by the experts. Findings of 13 additional researchstudies were displayed on posters, which provided the respective authors anopportunity to interact directly with conference participants.2 All these sessions

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“…They also showed that the strength of influence of largescale atmospheric circulation patterns on Indian precipitation extremes varies with spatial physiography of the region. Aamir and Hassan (2020) studied the impact of climate signals on precipitation variability in Baluchistan, the biggest province of Pakistan. For this purpose, they used Mann-Kendall statistical test to identify the monthly significant precipitation trends in thirteen meteorological stations located in four regions of Baluchistan.…”

Section: Introductionmentioning

confidence: 99%

Influence of large-scale climate signals on theprecipitation variability over Iran

Javanshiri¹,

Babaeian²,

Pakdaman³

2022

Preprint

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This study investigates relationships between the twenty large-scale climatesignals and the precipitation variability during 1960–2018 in Iran.The twenty large-scale climate indicators include atmosphere-ocean teleconnectionsas well as El Ni˜no and Southern Oscillation (ENSO) signals,Pacific and Atlantic ocean Sea Surface Temperature (SST). WaveletCoherence Analysis (WCA) was applied to detect the impact of climatesignals on Iran’s monthly precipitation. The results revealed that (a) thesignificant wavelet coherence and the phase difference between monthlyprecipitation and climate signals were highly variable in time and periodicity,(b) at inter-annual scale, Iran’s precipitation had been linked moreto Extreme Eastern Tropical Pacific SST(0◦-10◦S, 90◦-80◦W) (Ni˜no1.2), Oceanic Ni˜no Index (ONI), and Western Hemisphere Warm Pool(WHWP), respectively, (c) decadal and inter-decadal precipitation variabilityare mainly associated with variability in Atlantic Meridional Mode(AMM), Western Pacific Index (WP) and Arctic Oscillation (AO), and(d) in the most recent decade, the coherence between precipitation andlarge-scale climate signals has been declined in decade and inter-decadescales, and an unstable coherence has been emerged in annual scale.

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The impact of climate indices on precipitation variability in Baluchistan, Pakistan

Cited by 14 publications

References 44 publications

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

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

Population Challenges in a Changing World: An Overview of the 22nd Annual Research Conference of the Population Association of Pakistan

Influence of large-scale climate signals on theprecipitation variability over Iran

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