Mallikarjuna, G.B.SRUTHI, U.2018-04-162018-04-162017-07-24Th-11661http://krishikosh.egranth.ac.in/handle/1/5810043504Climate change refers to any systematic change in the long-term weather parameters. The study aims at reducing the bias in the climatic parameter values obtained from the satellite models by comparing with the data obtained from the observatories. Nine years day wise data for the climatic parameters such as Rainfall, Maximum and Minimum temperature are collected from the AICRP on Agro meteorology UAS GKVK Bengaluru, for the study. The day wise data was converted to, standard meteorological weekly and monthly data for the period wise analysis. Climatic parameter data obtain from the observatories are always more accurate than those from the satellite model. Bias correction methods such as difference method (DM) and modified difference method (MDM) were attempted to minimize bias of the satellite model data compared to observatories data. Best bias correction method is identified based on the coefficient of variation. Results revealed that, among them MDM was better for all the three periods of rainfall. Similarly, MDM is an ideal correction measure for daily maximum and minimum temperature, for weekly and monthly maximum and minimum temperature data DM was found to be an ideal measure. Probability distribution functions were attempted for the climatic factors considered and best fit of them were identified using chi square test. The best fitted probability distribution for the different periods were identified as Gamma and Weibull distribution as most suitable for the rainfall data. For Maximum and minimum temperature, no generalize single model was found as best fit.ennullThesis