Study of probabilistic modeling of stratospheric ozone fluctuations over Pakistan and China regions

Jan, Bulbul; Zai, M. Ayub Khan Yousuf; Abbas, Shujaat; Hussain, S. M.; Ali, Mohammad Akbar; Ansari, Muhammad Rashid

doi:10.1016/j.jastp.2013.12.022

Cited by 6 publications

(5 citation statements)

References 6 publications

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“…To find out the variability of climatic factors (temperature and rainfall) and trend of dengue cases, time series analysis assisted to study the forecasting of future values of a time series from current and past values. It relates the actual performance and analyzes the cause of variations [39,40]. These results were verified by the coefficient of determination (R 2 ), F-test, and p-values [30,32].…”

Section: Data and Statistical Approachesmentioning

confidence: 90%

“…In the present study, we have utilized statistical approaches to find out the variability of climatic factors and their effects on dengue incidence in Lahore district. Previously, people have successfully used trend lines as a tool of prime importance to study the economic development, hydrological planning, and climate change of a country [39]. Therefore, we employed this technique to find the trend of temperature and rainfall in Lahore.…”

Section: Discussionmentioning

confidence: 99%

“…Dengue data from 2007 to 2012 (monthly data) was used for ordinary linear and multiple linear regression analyses [39]. The multiple regression analysis was utilized to compute the impacts of temperature and rainfall on dengue.…”

Section: Data and Statistical Approachesmentioning

confidence: 99%

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Changing Climatic Factors Favor Dengue Transmission in Lahore, Pakistan

et al. 2019

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Dengue fever (DF) is a national health problem in Pakistan. It has become endemic in Lahore after its recent reemergence in 2016. This study investigates the impacts of climatic factors (temperature and rainfall) on DF transmission in the district of Lahore through statistical approaches. Initially, the climatic variability was explored using a time series analysis on climatic factors from 1970 to 2012. Furthermore, ordinary and multiple linear regression analyses were used to measure the simulating effect of climatic factors on dengue incidence from 2007 to 2012. The time series analysis revealed significant annual and monthly variability in climatic factors, which shaped a dengue-supporting environment. It also showed a positive temporal relationship between climatic factors and DF. Moreover, the regression analyses revealed a substantial monthly relationship between climatic factors and dengue incidence. The ordinary linear regression of rainfall versus dengue showed monthly R2 = 34.2%, whereas temperature versus dengue presented R2 = 38.0%. The multiple regression analysis showed a monthly significance of R2 = 44.6%. Consequently, our study shows a substantial synergism between dengue and climatic factors in Lahore. The present study could help in unveiling new ways for health prediction modeling of dengue and might be applicable in other subtropical and temperate climates.

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Section: Data and Statistical Approachesmentioning

confidence: 90%

Section: Discussionmentioning

confidence: 99%

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Changing Climatic Factors Favor Dengue Transmission in Lahore, Pakistan

et al. 2019

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“…The trend analysis is a familiar method used in same data points and exploring the event in terms of the influential effect of advancement in environmental and other events (Machiwal and Jha 2008;Jan et al 2014).…”

Section: Introductionmentioning

confidence: 99%

Power Spectrum Inception of F2 Layer at Solar Terrestrial Region of Pakistan

Jan

Afridi

Nawaz

et al. 2022

Preprint

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In this study, we introduce a recent approach to implement the wavelet analysis of ionospheric parameters and anomaly detection during ionospheric irregularities over Pakistan. The most important aspect of the wavelet analysis is the timefrequency distribution representation of the signal. This study investigates the variability of ionospheric F2 layer and utilizes critical frequency (foF2) of F2 layer during the year 2008-2017 in Pakistan region. The results of this study identify the most important bands of low frequency variations, which are very relevant for study of periodicities measurements of F2 layer. Moreover, Morlet wavelet has revealed that generally the global wavelet power spectrum (GWPS) is the most prominent in the annual cycles. The multifaceted interactions of ionospheric fluctuations with different time scales, e.g. annual, biannual, become significant due to higher peaks appear during the periods 128-256, 256-512 and 512-1024 days in daily data sets. The wavelet trend revales a noticeablel power range between the 2–16 day bands, representing an annual fluctuation for daily observations of F2 layer. The low deviation in a frequency range highlights the existence of seasonality in the F2 layer during the study period. These results emphasize that foF2 observations exhibit irregular distrabances with non-stationary power at different frequencies.The study will be helpful for stakeholders and government authorities because high frequency sky-waves users schedule their programs one month in advance, but they also need day by day information about the ionospheric conditions in order to revise programs.

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“…The continuous probability distributions are widely used in several probabilistic studies, [1][2][3][4][5][6][7] due to the adjustment of their variables, which may not be perfect, but they describe a real situation well, providing answers to the hypotheses that may have been raised in the research. According to Ferreira,8 the random variables of the continuous distributions are those that assume their values in a real scale, modeled by a density function f(x) with the following properties:…”

Section: Introductionmentioning

confidence: 99%

Determination of the Best Probability Distribution of Fit for Ozone Concentration Data in Campo Grande-MS-Brazil

Souza¹,

Jan²,

Nawaz³

et al. 2019

ECB

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This study discussed the behavior of ozone level observed in the atmospheric region of Campo Grande. To determine the best adjusted distribution to describe the ozone co-generation data for the year 2016 in Campo Grande were used 15 functions adjusted for this purpose; the performances of the distributions are evaluated using three test qualities, namely Kolmogorov-Smirnov, Anderson-Darling and Chi-Square test. Finally, the result of the fitted quality test is compared, it was observed that the generalized extreme value distribution provides a good fit for the whole year and the distributions Gamma 3P; lognormal 3P; weibull and Gamma 3P for the seasons of the year: winter, spring, summer, autumn, which are empirically proven to be the most appropriate distribution of data.

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Study of probabilistic modeling of stratospheric ozone fluctuations over Pakistan and China regions

Cited by 6 publications

References 6 publications

Changing Climatic Factors Favor Dengue Transmission in Lahore, Pakistan

Changing Climatic Factors Favor Dengue Transmission in Lahore, Pakistan

Power Spectrum Inception of F2 Layer at Solar Terrestrial Region of Pakistan

Determination of the Best Probability Distribution of Fit for Ozone Concentration Data in Campo Grande-MS-Brazil

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Study of probabilistic modeling of stratospheric ozone fluctuations over Pakistan and China regions

Cited by 6 publications

References 6 publications

Changing Climatic Factors Favor Dengue Transmission in Lahore, Pakistan

Changing Climatic Factors Favor Dengue Transmission in Lahore, Pakistan

﻿Power Spectrum Inception of F2 Layer at Solar Terrestrial Region of Pakistan

Determination of the Best Probability Distribution of Fit for Ozone Concentration Data in Campo Grande-MS-Brazil

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Power Spectrum Inception of F2 Layer at Solar Terrestrial Region of Pakistan