STOCHASTIC MODELING FOR RAINFALL IN HUMID SUBTROPICAL MONSOON REGION OF INDIA
Ripunjai Shukla, Manish Thrived, and Manoj Kumar.
Rainfall is a phenomenon, which directly or indirectly affects all the sectors like agriculture,
insurance, industry and other allied fields. Modeling data that correspond to rainfall accumulated
over long periods of time presents the challenging problem of dealing with a random variable that
has a point mass at zero which corresponds to dry periods that occur with positive probability.
One way to overcome this difficulty it is assume that the data correspond to a normal variate that
has been truncated and transformed. The dry periods correspond to the (unobserved) negative values
and the wet periods correspond to some power of the positive ones.This manuscript identified the more
comprehensive pattern of yearly extreme rainfall behavior based on the Markov Chain models. For
this purpose, we derived annual maximum daily rainfall from 1956 to 2006 and frequency distribution
table formed. The class interval treated as states and then uncertainty under various states occupied
by formation of transition probability matrix.
Extreme Value, Rainfall, Frequency Distribution, Markov Chain
Ripunjai Shukla, firstname.lastname@example.org
Manish Thrived, email@example.com
Manoj Kumar, firstname.lastname@example.org
Al-Nasser, Amjad D., email@example.com
READING THE ARTICLE: You can read the article in
portable document (.pdf) format (111448 bytes.)
NOTE: The content of this article is the intellectual property of the authors, who retains all rights to future publication.
This page has been accessed 2008 times since AUGUST 7, 2009.
Return to the Home Page.