Informatics Publishing Limited

R. Samuel Selvaraj ¹, S. Tamil Selvi ²

Affiliations
1 Presidency College, Department of Physics, Chennai, IN
2 Dhanalakshmi Srinivasan College of Engineering and Technology, Mamallapuram, Chennai, IN

Abstract

An application of stochastic process for describing and analysing the daily rainfall pattern at Aduthurai is presented. A model based on the first-order Markov chain was developed. The model used in this study consists of rainfall occurrence model and rainfall magnitude model. Results of the study suggests that first order Markov chaining with two parameters gamma distributions were found to be adequate to generate daily rainfall sequences at Aduthurai.

Keywords

Daily Rainfall, First Order Markov Chain, Rainfall Occurrence Model, Rainfall Magnitude Model.

Full Text

     

R. Samuel Selvaraj ¹, S. Tamil Selvi ²

Affiliations
1 Department of Physics, Presidency College, Chennai, IN
2 Department of Physics, Dhanalakshmi Srinivasan College of Engineering and Technology, Chennai, IN

Abstract

The study of solar activity and solar terrestrial relations, the sunspot number has always been taken as the main indicator of the intensity of solar activity. Various new techniques like neural networks, learning nonlinear dynamics and others are used by researchers to predict solar activity. But we are yet to obtain reasonably good results. This is mainly because the reason of the variation of solar activity is still unknown. Hence it is important to analyze the characteristics of the data. This paper considers sunspot as the index of solar activity and fractal analysis is used to examine the predictability of solar activity. For the period 1994 to 2008, the average fractal dimension for periods of 10 days or less was about 1.49. But during the same period, the average fractal dimension was 1.92 for periods longer than 10 days. Hence the result is encouraging for short-term prediction (i.e.) within about 10 days, but discouraging for medium-term prediction ( longer than 10 days ).

Keywords

Solar Activity, Neural Networks, Nonlinear Dynamics, Fractal Analysis, Fractal Dimension.

Full Text

     

R. Samuel Selvaraj ¹, S. Tamil Selvi ²

Affiliations
1 Department of Physics, Presidency College, Chennai, IN
2 Dept. of Physics, Dhanalakshmi Srinivasan College of Engineering and Technology, Mamallapuram,, IN

Abstract

Tamil Nadu is the sub - division of the Indian union which receives most of the rainfall during North East monsoon season than South West monsoon. The North East monsoon rainfall over Tamil Nadu depends on several factors such as solar variability(aa index), southern oscillation index, ElNino, Outgoing long wave radiation, Tropical Easterly jet, Quasibinneal Oscillation and South West monsoon etc. The aa index is a measure of the disturbance level of Earth's magnetic field based on magnetometer observations at two, nearly antipodal, stations in Australia and England. The objective of the paper is to find the relationship between aa index and SouthWest monsoon and the North East monsoon. A correlation analysis between the South West and the North East rainfall series revealed that the South West monsoon rainfall is negatively correlated (-0.03400397) with that of the North East monsoon rainfall. Similarly, the correlation analysis between the aa index and the North East rainfall series revealed that the aa index is negatively correlated (-0.272399) with that of the North East monsoon rainfall. Using Back Propagation Neural Network method North East monsoon can be predicted.

Keywords

Solar Variability (AA Index), Correlation, Rainfall, EINino, Back Propagation Neural Network.

Full Text