Spectral analysis of local climatic fluctuations

Iqbal, Muhammad Jawed; Quamar, J.; Yousufzai, Muhammad Ayub Khan

doi:10.1007/s12517-010-0154-x

Cited by 5 publications

(2 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Statistical spectral analysis has been traditionally used to detect regular cyclical patterns of the time series. In this study, Fourier-based spectral analysis has been chosen for the assessment to recover the periodicities in the Karachi heat extreme which has been used in previous climatological studies (Negrón-Juárez and Liu, 2001;Aldriana and Djamila, 2008;Iqbal et al, 2011;Hasanean et al, 2013). The annual HI records are transformed through a finite Fourier transform that decomposes it in different frequency waves.…”

Section: Spectral Analysismentioning

confidence: 99%

See 1 more Smart Citation

Probablistic Modelling and Identifying Fluctuations in Annual Extreme Heatwave Regimes of Karachi

Rizvi

Iqbal

Ali

2021

Preprint

View full text Add to dashboard Cite

Climatic warming in the global mean has significantly increased the probability of occurrence of heat extremes on time scales ranging from months to seasons. As extreme heat events are most likely to become intense and frequent over the next decades, thus it’s important to examine these events to mitigate its negative impacts on public health and society. This study focuses on Karachi heat extremes over the last 23 years. The power spectral analyses of Karachi heat extremes records have been carried out by considering two indices: Heat Index (HI) and Effective Temperature Index (TEE), which are also found to be significantly correlated. The result indicates a regular cyclic pattern of 4.5 years which is estimated to face a heat index of more than 73.63\(℃\), associated with the El Niño–Southern Oscillation (ENSO). Other peaks are observed at 2.8 and 2.2 years with the expected value of the Karachi heat index of 70.53\(℃\) and 68.71\(℃,\) respectively. The probabilistic approach is also used to predict the future heatwave events of Karachi. Generalized Extreme Value (GEV) distribution is found to be the best-fitted probability distribution for the extreme heatwave events on the basis of goodness of fit test. Furthermore, the estimation of the return period of the heatwave event reveals that Karachi will be facing a maximum heat index of 84.37\(℃\) or more in the coming 33 years, which suggests an urgent need for mitigation strategies in Karachi to overcome the effects of extreme heatwave events.

show abstract

Section: Spectral Analysismentioning

confidence: 99%

“…The time series of HI and TEE has a significant correlation of 0.86 at 0.01 level and both series showed an almost similar return period. The 2.8-year middle frequency wave and 2.2-year short wave show some association with the quasi-biennial oscillations (Lamb, 1972;Iqbal et al, 2011).…”

Section: Power Spectrum and Coherencymentioning

confidence: 99%