Principal Component Analysis to Explore Climate variability of Pakistan

Syed Afrozuddin Ahmed, Junaid Saghir Siddiqi


Various studies have reported that global warming causes unstable
climate and many serious impact to physical environment and public
health. The climatic or environmental structure data was processed
by coding, editing, tabulating, recoding, restructuring in terms of retabulating was carried out.Applying different statistical methods,
techniques and procedures for the evaluation.To study the global
warming effects on overall environmental conditions of Pakistan.
Annual data of maximum and minimum temperature of four provincial
capitals have been taken from 1947 to 2012. The data isconsideredas
representative environmental components, use for further analysis.
Time series plot shows difference of behaviors in maximum and
minimum temperatures of Karachi and Lahore while bend of Quetta
indicates increasing trend and Peshawar shows flat and smooth. The
fit of trend line, maximum temperature of Karachi, has significant
regression coefficient b = 0.0504 with p-value 0.000 and R2equal to
70.2%. The minimum temperature has decreasing trend but it is
insignificant. The data of Lahore shows decreasing and increasing
trends for maximum and minimum temperatures respectively shows
the differences reducing with the passage of time and expected to
have cooler weather than the past. Quetta and Peshawar temperatures
fit of trend lines and graphs, revealed that both cities getting warmer
with the passage of time.Principal component analysis is performed
for the purpose of finding if there is/are any general environmental
factor/structure which could be considered as Pakistani climate

The PC1 is constructed by six manifest variables and represent the
environmental factor called as “Index of Pakistan weather”. Explain
42.74% of the total variation. The time series plot of this index seems
to have increasing trend. The PC2 represents the temperature of
Karachi, Quetta and Lahore. PC3 is the contrast between of minimum
and maximum temperature. PC4 represents complex contrast between
maximum and minimum temperature explain 9.0% of total variation of
temperature. PC5 represent contrast between Karachi and Peshawar
weather and its contribution to the total or overall variation of Pakistani
weather is only 3.5%.

Full Text:



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Chief Editor

Prof. Dr. Tariq Rahim Soomro 
College of Computer Science & Information Systems


Dr. Muhammad Mansoor Alam
 Professor and Associate Dean
 College of Computer Science & Information Systems

Associate Editors

Engr. Syed Mubashir Ali
Senior Lecturer & Course Coordinator
College of Computer Science & Information Systems

Publication Coordinator
Humaira Kanwal

Editorial Advisory Board (Internal)

Dr. Syed Irfan Hyder
Dr. S.M. Aqil Burney
Dr. Ejaz Ahmed
Dr. Mohammad Irshad Khan
Dr. Shahid Amjad
Dr. Fatima Riaz
Dr. Insia Hussain
Dr. Dr. Ehsan Rehman
Dr. Imran Majid
Dr. Khurram Iqbal
Dr. Zeeshan Shahid
Dr. Seema Ansari
Dr. Sumaira Khan


Editorial Advisory Board (International)

Prof. Dr. Mazliham Mohd Su'ud, President, Universiti Kuala Lumpur, Malaysia
Prof. Dr. Ghassan Al-Qaimari, President, Emirates College of Technology, Abu Dhabi, UAE
Prof. Dr. Patrice Boursier, Universite de La Rochelle, La Rochelle, France
Prof. Dr. Mudassir Uddin, Professor, University of Karachi, Pakistan
Dr. Nadeem Doudpota, Associate Professor, Al-Baha University, KSA
Dr. Haithem Abdelrazaq Almefleh, Associate Professor, Yarmouk University, Yarmouk, Jordan
Dr. Saiful Islam Ansari, Assistant Professor, University of Tabuk, Saudi Arabia