COMPARISON OF AUTOREGRESSIVE (AR) STRATEGY WITH THAT OF REGRESSION APPROACH FOR DETERMINING OZONE LAYER DEPLETION AS A PHYSICAL PROCESS

M. A. K. Yousaf Zai, R. K. Ansari, J. Qaumar, J. Iqbal, M. A. Hussain

Abstract


This communication presents the development of a comprehensive characterization of ozone layer depletion (OLD) phenomenon as a physical process in the form of mathematical models that comprise the usual regression, multiple or polynomial regression and stochastic strategy. The relevance of these models has been illuminated using predicted values of different parameters under a changing environment. The information obtained from such analysis can be employed to alter the possible factors and variables to achieve optimum performance. This kind of analysis initiates a study towards formulating the phenomenon of OLD as a physical process with special reference to the stratospheric region of Pakistan. The data presented here establishes that the Auto regressive (AR) nature of modeling OLD as a physical process is an appropriate scenario rather than using usual regression. The data reported in literature suggest quantitatively the OLD is occurring in our region. For this purpose we have modeled this phenomenon using the data recorded at the Geophysical Centre Quetta during the period 1960-1999. The predictions made by this analysis are useful for public, private and other relevant organizations.

Full Text:

PDF

References


R. Garcia, Physics World 17 (1994) 49.

M.A.K. Yousuf Zai and J. Quamar, Indian J.

Phys. 75B, No. 4 (2001) 307.

NASA Facts, On Line, NASA Goddard Space

Flight Centre, USA ( 2003).

L.G. Richard and R. B. May, Environ. Sci.

Technol. 4 (1988) 22.

L. A. Alvin, Env. Sci. Technol. 3 (1993) 27.

L .Mátyás (ed.), Generalised Method of

Moments Estimation, UK, Cambridge,

University Press (1999).

H. Allen and R.Murphy, Probability, Statistics

and Decision Making in Atmospheric

Sciences, London: West View Press (1987).

K.E. Trenber and J. G. Olson, GreenhouseGas-Induced Climate Change: A Critical

Appraisal of Simulations and Observations,

Vol. 31, Amsterdam : Elsevier (1991) pp.

-259.

M. R. K Ansari and J. Quamar in Proceedings of Fifth International Conference of

Science, Technology & Development in the

New Millennium held at University of Karachi,

Pakistan, April 24 – 27 (2000) pp. 205-223.

J. W. Tukey, Exploratory data analysis,

Reading, Mass., Addison- Wesley (1977).

S. M. Pandit and S.M. Wu, Time Series and

System Analysis with Applications, New York:

J. Wiley (1985).

R. Bartoszynski and M. N. NiewiadomskaBugaj, Probability and Statistical Inference,

Wiley-Inter Science, New York (1996).

M.A.K Yousuf Zai, Ph.D thesis submitted at

the Institute of Space and Planetary

Astrophysics, University of Karachi (2003).


Refbacks

  • There are currently no refbacks.