COPULA BASED MODEL FOR TEMPERATURE AND PRECIPITATION DATA - KARIMNAGAR

The Present study deals with the analysis of two interdependent variables temperature and precipitation(rainfall). When the component distributions have different distributions for each component, the joint distribution can be obtained using a technique called “Copula analysis” when the variables are interdependent. There are approximately 226 Copula families all together. Out of these families, one can find the best-fitted distribution along with parameter estimates. The selection of the best distribution of Copula is based on AIC and BIC criteria. The distribution with the least value of AIC is identified as the best distribution. The research utilized chronicled monthly average precipitation and monthly average temperature information for 102 years for Karimnagar district, Telangana state. The outcome of the research implies that temperature and precipitation are negatively associated. Utilising the inferred bi-variate Copula distribution one can find the estimated values of temperature for the observed time point and the same also can be used for forecasting the temperature of the future. It has been observed that the fitted copula distribution is yielding good estimates and forecasts with accuracy. The results and analysis are presented in this paper.